Category: 3. Business

Tietoevry Tech Services and COSMO CONSULT have formed a partnership to provide enhanced solutions for waste management companies leveraging Microsoft Dynamics 365 as their ERP. This collaboration combines Nordic market understanding and industry-specific expertise to help companies in this sector modernize their operations through digital transformation.

COSMO CONSULT will contribute its COSMO Environmental Services solution, based on Microsoft Dynamics 365 Finance and Supply Chain Management. This solution integrates key waste management processes — from contract management to material flow handling — into a single system. Tietoevry Tech Services complements this with its strong presence in the Nordic region and its expertise in cloud-based ERP transformation and managed services.

“This partnership enables us to provide customers in the waste management industry with customer centric digital transformation advice and support. By combining our ERP and cloud expertise with COSMO CONSULT’s industry-specific capabilities, we can help customers to streamline their operations and gain better control over their complex material flows”, says Peter Andersson, Sales Manager at Tietoevry Tech Services.

‘With Tietoevry Tech Services, we have another partner on our side that understands the Nordic market and shares our commitment to practical, customer-focused digitalization. This collaboration allows us to deliver our industry solution where it’s most needed, helping Nordic waste management companies to operate more efficiently and sustainably,’ adds Matthäus Mayer, Sales Director of Industry Solutions at COSMO CONSULT.

 

For more information, please contact:

Tietoevry Newsdesk, news@tietoevry.com, +358 40 570 4072  

COSMO CONSULT Group, contact@cosmoconsult.com

 

About Tietoevry Tech Services

Tietoevry Tech Services is a leading transformation and managed services provider, focusing on Nordic-based private and public customers across various industries. With our full scope of cutting-edge digital solutions, including applications, multi-cloud, data and AI, and security services, we help businesses thrive and keep Nordic societies running. We are a global team of more than 7,000 experts representing over 50 nationalities, delivering services to our customers by combining global capabilities with Nordic proximity. Our annual revenue is approximately EUR 1 billion.

 

About COSMO CONSULT

Founded in 1996, the COSMO CONSULT Group is one of the world’s leading Microsoft partners for enterprise software and digitalization consulting. With more than 1,600 employees at 52 locations in 20 countries, COSMO CONSULT is also the largest owner-managed partner worldwide.

The digitalization specialist is firmly established in many industries, including waste management, and has a deep understanding of their specific requirements. As a market leader in the German-speaking region, the software and consulting company offers smart industry solutions based on Microsoft platforms. The extensive portfolio includes solutions in the areas of Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Data & Analytics and BI, Modern Workplace, Human Resources (HR), Cloud Computing, and Digital Services.

With artificial intelligence (AI) and intelligent automation tools, COSMO CONSULT helps companies optimize workflows and build fully integrated, consistently digital processes. Expert teams accompany the digital transformation with tailored consulting services such as Change Management and Customer Strategy Management. The solutions are used by large, medium-sized, and small companies in many industrial and service sectors. Learn more about Cosmo Environmental Services for waste management and recycling companies.

 

New York
 — 

Nearly a year ago, Jaguar unveiled a refreshed brand identity that was supposed to usher in its future. So far, it’s been mostly a headache.

The 102-year-old luxury automaker, once a head-to-head competitor with brands like Mercedes-Benz and BMW, had been plagued with problems even before the advertising campaign was released, including leadership changes, declining sales amid a stale lineup and stiff competition from the likes of both German luxury carmakers as well as relative upstarts like Tesla.

Now it can add two more problems: misleading headlines about its sales, and outrage from the political right — most notably the US president.

On Monday, President Donald Trump trashed Jaguar for what he called a “stupid” and “seriously WOKE” ad campaign last year, which featured an avant-garde commercial that featured slogans such as “live vivid,” and what appeared to be gender-fluid models, but zero images of its cars or even concepts of a car.

“Who wants to buy a Jaguar after looking at that disgraceful ad,” quipped Trump on Truth Social. “The market cap destruction has been unprecedented with BILLIONS OF DOLLARS SO FOOLISHLY LOST.”

But the reality is different.

Jaguar Land Rover has been owned by Tata Motors since 2008, when the Indian company bought it from Ford, which means Jaguar doesn’t have a market cap. And Tata itself is doing fine as a massive multinational conglomerate with a wide variety of operations worth about $28 billion.

Plus, Jaguar’s problems are more fundamental. Although most legacy automakers have tried to manage a smooth transition to fully electric propulsion, Jaguar simply ceased making cars entirely in 2024 pulling all of its products off the market as it tries to reinvent itself as an electric vehicle maker.

But that’s enough to establish a narrative in the minds of many. Headlines swirled last month that Jaguar’s sales across Europe were down 97.5% year-over-year in April, citing data from the European Automobile Manufacturers’ Association. That makes sense given Jaguar stopped manufacturing cars but the news was enough to draw the wrath of Trump and some conservatives.

Shortly after the ad was released, Jaguar revealed its Type 00 concept car at Miami Art Week — notably, not at a traditional automotive show. While the concept isn’t intended for production, it is meant to show Jaguar’s general future design direction.

Jaguar didn’t respond to a question from CNN about when it will start production again.

Last week, Jaguar Land Rover CEO Adrian Mardell announced he was stepping down after 35 years with the brand. He had a largely successful stint, having helped eliminate billions of dollars of debt and with JLR reporting its ninth consecutive profitable quarter in January on the back of strong SUV sales.

Tata Motors on Monday named P.B. Balaji, currently the company’s chief financial officer, as Jaguar Land Rover’s new CEO. He begins in November.

Introduction

Chronic obstructive pulmonary disease (COPD) is a common chronic lung disease, including emphysema, chronic bronchitis, and others. Currently, the causes of COPD are not yet clear and may be related to external environmental factors, including smoking, second-hand smoke inhalation, polluting dust, harmful chemical gases, air pollution, and other factors.¹ There are also personal factors, such as genetics, diseases, etc.² COPD is more common in people over 40 years of age, possibly due to the decline in physical function and immunity of middle-aged and elderly patients.³ The pathological and physiological characteristics of COPD are persistent airflow limitation, completely irreversible, and persistent malignant development.⁴ Clinical manifestations include dry vomiting, coughing, and sputum production, which worsen with increasing physical activity and seriously affect the patient’s quality of life.⁵ Treatment for COPD is based on improving lung function, alleviating clinical symptoms, and improving quality of life. Common treatment methods include rehabilitation therapy, medication therapy, and home oxygen therapy.⁶ As the disease progresses, some patients may also have pulmonary fibrosis and, if left untreated, there is a risk of developing into pulmonary failure.⁷ Therefore, early identification and diagnosis of such patients and timely treatment of medications are of great significance to improve the patient’s prognosis.

In recent years, ferroptosis, as a new type of programmed cell death, has gradually attracted widespread attention due to its dependence on intracellular Fe ²⁺accumulation and lipid peroxidation.^8,9 Numerous studies have shown that ferroptosis plays a crucial role in the onset and progression of lung diseases.¹⁰ Ferroptosis not only differs morphologically from other forms of cell death, but also exhibits unique mechanisms at the biochemical level. In particular, oxidative stress caused by iron overload and disorders of lipid metabolism is considered an important factor in the induction of ferroptosis.^11,12 These findings provide new opportunities for the treatment of lung diseases by regulating iron metabolism and lipid peroxidation processes, which may effectively promote or prevent ferroptosis, thus improving the therapeutic effect of these diseases.

Transferrin protein 1 (TFR1), also known as CD71 or TFRC, is a type II transmembrane glycoprotein composed of 760 amino acids, exist in the form of a dimer, connected by disulfide bonds on the cell surface. The TFR1 monomer consists of an extracellular C-terminal domain, a transmembrane region, and an intracellular N-terminal domain, where the C-terminal region contains the transferrin (TF) binding site. Each TFR1 monomer can bind 1 molecule of TF and 2 Fe3+ ions, so 1 molecule of TFR1 can bind up to 2 molecule of TF and 4 Fe3+ ions, ultimately delivering iron into the cell in the form of an iron-TF-TFR1 complex.^13,14 Human TFR1 is widely expressed in different tissues and organs. Under physiological conditions, cellular iron absorption is primarily controlled by the plasma membrane protein TFR1, which transports transferrin bound iron into cells through receptor-mediated endocytosis.¹⁵ Therefore, TFR1 is considered a marker protein for ferroptosis. Blocking this process by eliminating TFR1 can prevent ferroptosis.¹⁶ Previous studies have confirmed that high expression of TFR1 in bronchoalveolar lavage fluid (BALF) in asthma patients is associated with impaired lung function, and it is believed that high expression of TFR1 in the sputum is related to the severity of asthma.¹⁷ Down-regulation of TFR1 partially blocked the high secretion of MUC5AC, goblet cell proliferation, and the release of inflammatory factors in COPD model rats, indicating that TFR1 is involved in promoting airway inflammation and airway mucus cell proliferation in COPD.¹⁸ However, TFR1 expression in patients with COPD has not yet been reported.

In the aforementioned study, we have identified ferroptosis involvement in the pathological process of progression of COPD to pulmonary fibrosis in animal models and we found that ferroptosis-related indicators, including GSH and MDA, are correlated with the degree of pulmonary fibrosis. Based on this, this study aims to detect the expression level of TFR1 in COPD patients and analyze its relationship with the severity of COPD and pulmonary fibrosis and to verify the relationship between the expression level of TFR1 and lung injury and pulmonary fibrosis in animal models. The purpose of this study is to provide a reliable biomarker and a potential therapeutic target for patients with COPD progression to pulmonary fibrosis.

Materials and Methods

COPD Patients

97 patients with COPD were included in this study. COPD was diagnosed by pulmonary function test according to the standards of the Global Initiative for Chronic Obstructive Lung Disease (GOLD).¹⁹ Inclusion criteria: (1) FEV1/FVC<0.7 after bronchodilators, and excludes other diseases that may cause limitation of airflow (such as asthma and bronchiectasis). (2) Age over 40 years old, COPD duration ≥ 1 year. Exclusion criteria: (1) Other diseases that cause pulmonary fibrosis: connective tissue diseases (such as rheumatoid arthritis, scleroderma), occupational lung diseases (pneumoconiosis, asbestosis), drug-induced pulmonary fibrosis, or idiopathic pulmonary fibrosis. (2) Combined with asthma, bronchiectasis, active pulmonary tuberculosis, and pulmonary embolism. (3) Serious complications, such as active lung cancer, severe heart failure (NYHA III–IV grade), end-stage renal disease, liver failure, etc. (4) Usage of anti-fibrotic drugs (such as pirfenidone, nintedanib) or immunosuppressants (such as cyclophosphamide, rituximab) within 6 months.

Data including sex, age, smoking index, BMI, CRP, IL-6, ESR, LDH, routine blood examination, lung function, 6 MWT, CAT score, grade mMRC, grade GOLD, frequency of acute exacerbation, and fibrosis score based on HRCT examination were collected from hospital electronic records between January 1, 2022 and December 31, 2024. At the same time, peripheral blood samples were collected from all patients for the detection of serum levels of TFR1 and COL3 using the ELISA assay. This study was approved by the Medical Ethics Committee of the Hunan Provincial People’s Hospital (2024–260).

Mice COPD Model

4-week-old C57BL.6 J mice (18–20g) were purchased from Hunan Slake Jingda Experimental Animal Co., Ltd. (Changsha, China). All animals were fed in the SPF animal facility with a normal day and night cycle. They also had free access to a common diet and water. Mice were randomly divided into 3 groups: control group (n=5), model 1 group (COPD / CSE) (n = 5), and model 2 group (COPD-PF / CSE + LPS) (n = 5 as Supplementary Figure 1. The mice COPD model was constructed as in our previous study.²⁰ All animal experiments were conducted according to the ARRIVE guidelines. The animal study protocol was approved by the Animal Care and Use Committee (ACUC) of Hunan Provincial People’s Hospital, protocol number [2024–260]. The study adhered to the guidelines set by the committee.

ELISA Assay

Human sTfR1 (Soluble Transferrin Receptor1) ELISA kit (EH0386), Mouse TFR (Transferrin Receptor) ELISA kit (EM1400) and Human COL3 (Collagen Type III) ELISA kit (EH2866) were purchased from Fine Test Biotechnology (Wuhan, Hubei, China). COL3 was a biomarker of fibrosis. The levels of TFR1 and COL3 in the serum of COPD patients were measured using an ELISA assay according to the manufacturer’s instructions. The OD450 was measured by Microplate reader. Each sample was calculated on the basis of a standard curve.

Hematoxylin & Eosin Staining

The lung tissue of the mice was fixed in 4% paraformaldehyde for at least 24 hours, followed by gradient dehydration and paraffin embedding. After embedding in paraffin, tissues were cut into sections with a thickness of 4 (m for H&E staining). After dewaxing, staining with hematoxylin and eosin, dehydration, permeabilization, and sealing, observation, and image collection were performed under an inverted microscope (Olympus, Tokyo, Japan). The lung injury score was referred to the previous study, mainly including pulmonary congestion, hemorrhage, neutrophil filtration and aggregation, and alveolar wall thickness and transparent membrane formation.²¹

Masson Trichrome Staining

Paraffin sections were deparaffinized and sequentially stained with Regaud’s hematoxylin staining solution, Masson’s acid eosin solution, and aniline blue. After staining, dehydration, permeabilization, and sealing, observation and image collection were performed under an inverted microscope (Olympus, Tokyo, Japan). The lung injury score was evaluated on the basis of Ashcroft score criteria.²²

IHC Staining

Sections with a thickness of 4 (m obtained from paraffin-embedded lung tissues were deparaffinized, antigen retrieval, blocked, and incubated with primary antibodies against TFR1 (Cat No. 65236-1-Ig, Proteintech, Wuhan, China) with a dilution of 1:200 and (-SMA (Cat No. 14395-1-AP, Proteintech, Wuhan, China) with a dilution of 1:1000. The sections were then incubated with a secondary antibody kit, and observation was performed with a laser scanning microscope (Olympus, Tokyo, Japan).

Statistical Analysis

Parametric data were presented as mean ± standard deviation or mean (range). Nonparametric data were presented as median (interquartile range, IQR). Spearman bivariate correlation analysis was performed between TFR1 and basic demographic information, systemic inflammatory level, and pulmonary function in patients with COPD. The chi-square test was applied to analyze differences in clinical characteristics between the higher TFR1 group and the lower TFR1 group in patients with COPD. Student’s t test was applied to analyze differences between two groups, while variance (ANOVA) was applied to analyze differences between the three groups. Statistical significance was established at P<0.05. SPSS software (version 20.0; SPSS, Inc., Chicago, IL, USA) was used for statistical analysis. GraphPad Prism 8 (GraphPad, San Diego, CA) was used to generate the images.

Results

Characteristics of the COPD Patient

In this study there were 97 patients with COPD. The results of the spearman bivariate correlation analysis between TFR1 and basic demographic information, systemic inflammatory level, lung function in patients with COPD showed that TFR1 levels did not show correlation with gender, age, smoking index, BMI, CRP, IL-6, LDH, WBC, neutrophil count, Hb, EOS%, RV/TLC%, FEV1%pred, mMRC grade. However, TFR1 levels exhibited a positive correlation with FEV1/FVC%, MMEF%, CAT score, GOLD grade, frequency of acute exacerbation and fibrosis score and a negative correlation with lymphocyte count, NLR, DLCO%, DLCO/VA%, 6MWT (see Table 1 for details).

Table 1 Spearman Bivariate Correlations Analysis Between TFR1 and Basic Demographic Information, Systemic Inflammatory Level, Pulmonary Function in COPD Patients

The Frequency of Acute Exacerbation and the Fibrosis Score Differ in COPD Patients with Higher and Lower Levels of TFR1

The TFR1 level of 97 patients was 5.44 ± 0.56 ng/mL. According to the average TFR1 value, they were divided into a low TFR1 group (serum TFR <5.44 ng/mL) and a high TFR1 group (serum TFR1 ≥ 5.44 ng/mL). There were differences in DLCO%, 6 MWT, GOLD grade, frequency of acute exacerbation, and fibrosis score between the two groups (see Table 2 for details). A higher level of TFR1 was associated with a lower percentage of DLCO, a shorter distance of 6 MWT, a higher grade of GOLD, a higher frequency of acute exacerbation and a higher fibrosis score. All of these results suggested that TFR1 was a biomarker positively correlated with the severity of COPD, with higher levels of TFR indicating more severe COPD.

Table 2 Differences of Clinical Characteristics Between Higher TFR1 Group and Lower TFR1 Group in COPD Patients

The TFR1 Level Was Associated with the Frequency of Acute Exacerbation in COPD Patients

The gradual progression of COPD to pulmonary fibrosis is a slow process closely related to repeated acute exacerbation of inflammatory damage. The frequency of acute exacerbation was recorded in one year and all patients were divided into two groups according to the frequency of acute exacerbation, with a frequency of less than or equal to 2 per year recorded as the low-frequency group and more than 2 recorded as the high-frequency group. Representative CT images of patients in the low-frequency and high-frequency groups of acute exacerbation were show in Figure 1A. Then we analyzed the plasma levels of TFR1 and COL3 of the patients in the low-frequency and high-frequency groups and found that the levels of TFR1 and COL3 were significantly lower in the low-frequency group and significantly higher in the high-frequency group (Figure 1B and C). The levels of TFR1 were positively correlated with COL3 (Figure 1D). To predict the frequency of acute exacerbation in COPD, the area under the TFR1 curve was 0.9534 (95% CI:0.9167–0.9901), P<0.0001, the area under the COL3 curve was 0.7289 (95% CI:0.6243–0.8334), P=0.0006, and the area under the fibrosis score curve is 0.7969 (95% CI:0.6851–0.9087), P<0.0001 (Figure 1E).

Figure 1 The TFR1 level was associated with the frequency of acute exacerbation in patients with COPD. (A) Representative CT images of patients in the low-frequency and high-frequency groups of acute exacerbation. (B) Serum TFR1 concentration in the low-frequency and high-frequency groups. (C) Serum COL3 concentration in the low-frequency and high-frequency groups. (D) The spearman analyzes the serum TFR1 concentration and the serum COL3 concentration. (E) ROC cure for TFR1, COL3, and fibrosis scores to predict the frequency of acute exacerbation in COPD. Notes: the low group stands for the low frequency group with a frequency of acute exacerbation less than 2. The high group represents the high-frequency group with an acute exacerbation frequency greater than 2. ***means P < 0.001.

The TFR1 Level Was Correlated with Lung Injury in COPD Mice

To verify the relationship between TFR1 and lung injury, we constructed lung injury models with different degrees of injury. Model 1 was mainly exposed to cigarettes to simulate stable COPD lung injury. Model 2 added an intraperitoneal injection of a combination of LPS exposure to cigarettes to simulate the impact of infection after COPD lung injury, that is, AECOPD. As expected, the Model 1 group showed significant lung injury, while the Model 2 group had more significant lung injury and significant interstitial thickening (Figure 2A and B). And the levels of TFR1 were detected in BALF and plasma. Compared to the control group, TFR1 in both model 1 and model 2 groups increased significantly, and the TFR1 level in model 2 group was higher than in the TFR1 group, indicating that the TFR1 level was related to the degree of lung injury (Figure 2C and D).

Figure 2 The TFR1 level was correlated with lung injury in COPD mice. (A) HE staining of lung tissue. (B) Lung injury scores for the three groups. (C) The content of TFR1 in the BALF. (D) The contents of TFR1 in serum. *means P < 0.05. **means P < 0.01. ***means P < 0.001.

TFR1 Level Correlated with Lung Fibrosis in COPD Mice

There was a positive correlation between TFR1 levels and COL3 pulmonary fibrosis index, as well as CT pulmonary fibrosis score in patients with COPD. Furthermore, the relationship between TFR1 levels and pulmonary fibrosis was also analyzed in COPD mouse models. Through Masson’s trichrome staining, the results showed that varying degrees of pulmonary fibrosis injury were observed in the Model 1 and Model 2 groups, with the Model 2 group showing more significance (Figure 3A and B). Furthermore, TFR1 and a-SMA expression in each group were evaluated by immunohistochemical staining and the results showed that TFR1 was significantly up-regulated in the model groups, with higher positivity in the Model 2 group, consistent with the expression of a-SMA (Figure 3C–E). These results indicated that the level of TFR1 was also closely related to pulmonary fibrosis injury.

Figure 3 The TFR1 level was correlated with lung fibrosis in COPD mice. (A) Masson trichrome staining of lung tissues. (B) Lung fibrosis scores for the three groups. (C and A) IHC staining of TFR1 and α-SMA in lung tissues. (D and E) the positive percentage of TFR1 and α-SMA based on IHC staining. *means P < 0.05. **means P < 0.01. ***means P < 0.001.

Discussion

This study is the first to demonstrate that COPD patients with increased serum TFR1 in COPD patients were related to recurrent acute exacerbations and develop pulmonary fibrosis. TFR1, as a marker for ferroptosis, might serve as a potential indicator for the evaluation of the severity of pulmonary fibrosis in clinical practice in the future.

The objective of the evaluation of COPD is to clarify the severity of the disease, its impact on the patient’s health status, and the risk of certain events (acute exacerbation, hospitalization, and death), while guiding treatment.^23,24 The comprehensive evaluation included symptoms of the disease, the degree of airflow limitation (lung function test), the risk of acute exacerbation, and comorbidities. MMRC is positively correlated with the severity of airflow limitation and lung function impairment, with mMRC greater than 2 serving as the boundary between “mild respiratory distress” and “severe respiratory distress”. A CAT score <10 indicates the need for medical intervention.^25,26 Due to the fact that all of the patients we collected were in the hospital, the mean mMRC values for both the low TFR1 group and the high TFR1 group were greater than 2. The mean values of the CAT score of the patients in both the low TFR1 group and the high TFR1 group were greater than 10. However, it can be seen that the mMRC and CAT scores of the TFR1 high group are higher, which also indicates that the level of the TFR1 group is related to the severity of the disease, although there is no statistical difference. Lung function is another important diagnostic and reference basis for evaluating the condition of COPD. This study examined indicators of lung function such as RV/TLC%, FEV1% pred, FEV1/FVC%, MMEF%, DLCO%, DLCO / VA% and GOLD grade. It also indicated that the levels of TFR1 were related to the lung function. The acute exacerbation of COPD patients is mainly related to infection, and among the infection-related indicators, we observed that TFR1 was only related to the rate of erythrocyte sedimentation and had no relationship with levels of IL-6, C-reactive protein, and LDH. Furthermore, by comparing the differences in inflammatory indicators between high and low levels of TFR1, it was found that there was no significant difference in TFR1 levels and inflammatory indicators. This indicated that the level of TFR1 was associated with lung but not with inflammatory factors.

As COPD progresses and acute exacerbations recur, it can cause airway remodeling and changes in lung interstitial, which eventually develop into pulmonary interstitial fibrosis.^27,28 As a more serious complication in the course of COPD, pulmonary interstitial fibrosis can further aggravate lung function damage as the severity of fibrosis increases.^29,30 Failure to provide timely treatment and control of the disease can lead to respiratory failure or death in patients.³¹ Our results indicated that the level of TFR1 is positively correlated with the frequency of acute exacerbations and the score of lung fibrosis in one year. And it was found that by grouping with increased frequency to observe TFR1 levels and indicators related to fibrosis, patients with more frequent acute exacerbation (more than 2 times per year) had higher levels of TFR1 and COL3. The results of predicting the frequency of acute exacerbations based on the level of TFR1, the level of COL3, and the fibrosis score indicated that TFR1 had greater sensitivity and specificity compared to the level of COL3 and the fibrosis score. Taking into account the difficulty of obtaining lung biopsy tissue from COPD patients, we also observed the association between TFR1 levels and lung injury in a mouse COPD model. As expected, we observed a more intuitive correlation between TFR1 levels and lung injury and fibrosis scores in a mouse COPD model. This result supported the use of TFR1 as a biomarker to predict the degree of lung injury and evaluate pulmonary fibrosis.

With the deepening and enrichment of the research on TFR1, it is now clear that TFR1 is closely related to various tumors and some brain diseases, including Parkinson’s, stroke, and acute brain injury.^32,33 And based on these studies, a series of drugs targeting TFR1 have also been developed for clinical diseases, which currently in the clinical trial stage.^13,34 We can see the broad applications prospects of drugs targeting TFR1 inhibition. However, currently there is very little research on the relationship between TFR1 and COPD. A study found that TTR1+macrophages are involved in the process of pulmonary fibrosis injury, and DFO treatment can work by reducing ferroptosis.³⁵

Conclusion

This study provides some evidence that TFR1 is involved in COPD lung injury, indicating that TFR1 is related to the acute exacerbations of COPD and COPD-associated pulmonary fibrosis, and also provides new evidence for targeted inhibition of TFR1 therapy for COPD. However, only 97 patients were included in the study, and more patients are needed to clarify the specific levels of TFR1 and the cutoff values for grouping. Patients who have not developed pulmonary fibrosis should be set as controls to clarify the level of TFR1 in pulmonary fibrosis. In summary, the prevention and treatment of COPD are crucial and TFR1 is a highly promising therapeutic target. We hope that our research can help improve and improve the prognosis of patients with COPD.

Data Sharing Statement

The data sets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics Approval and Consent to Participate

This study contained COPD patients was approved by the Ethics Committee of Hunan Provincial Hospital, Hunan Normal University (2024-260) and was carried out according to the Declaration of Helsinki guidelines. All patients signed informed consent. The animal study was approved by the Ethics Committee of Hunan Provincial Hospital, Hunan Normal University (2024-107). All methods were performed in accordance with the relevant guidelines and regulations.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This study was supported by the Hunan Province Natural Science Foundation (2024JJ9279), Hunan Provincial Health Commission Project (D202316006632) and Hunan Province Innovation Guidance Project (2021SK50903).

Disclosure

The authors declare that they have no conflict of interest.

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23. Jones PW, Harding G, Berry P, Wiklund I, Chen WH, Kline Leidy N. Development and first validation of the COPD assessment test. Eur Respir J. 2009;34(3):648–654. doi:10.1183/09031936.00102509

24. Ko FW, Chan KP, Hui DS, et al. Acute exacerbation of COPD. Respirology. 2016;21(7):1152–1165. doi:10.1111/resp.12780

25. Chuatrakoon B, Uthaikhup S, Ngai SP, Liwsrisakun C, Pothirat C, Sungkarat S. The effectiveness of home-based balance and pulmonary rehabilitation program in individuals with chronic obstructive pulmonary disease: a randomized controlled trial. Eur J Phys Rehabil Med. 2022;58(3):478–486. doi:10.23736/S1973-9087.22.07383-X

26. Wang J, Chen X, He S, et al. COPD assessment test and risk of readmission in patients with bronchiectasis: a prospective cohort study. ERJ Open Res. 2024;10(2):00867–2023. doi:10.1183/23120541.00867-2023

27. Hage R, Gautschi F, Steinack C, Schuurmans MM. Combined pulmonary fibrosis and emphysema (CPFE) clinical features and management. Int J Chron Obstruct Pulmon Dis. 2021;16:167–177. doi:10.2147/COPD.S286360

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Introduction

Hematopoietic Stem Cell Transplantation (HSCT) is a well-established curative therapy for a broad spectrum of conditions, particularly malignant hematologic diseases, as well as select nonmalignant congenital and acquired diseases of the hematopoietic system.¹ Since the first transplantation performed more than 6 decades ago,² the use of HSCT has steadily increased. This growth can be attributed to expanding indications, improved patient selection, less toxic conditioning regimens, and enhanced supportive care measures.^2,3 While HSCT has significantly improved survival rates, patients who undergo this procedure remain at heightened risk for a range of late complications, including graft-versus-host disease (GVHD) and disease relapse, as well as unique long-term sequelae related to the transplant itself.⁴

Over the past two decades, accumulating evidence has underscored the critical role of exercise in both the prevention and management of cancer.⁵ Targeted physical activity interventions have demonstrated substantial benefits in improving physical function, quality of life (QoL), and reducing cancer-related fatigue in various patient populations, including those who have undergone HSCT. In fact, the American College of Sports Medicine assigns a high level of evidence to the safety and efficacy of aerobic and strength training for adults during or after HSCT.⁶

Despite these established benefits, numerous barriers often limit patient access to comprehensive cancer rehabilitation services. Socioeconomic factors, transportation challenges, employment obligations, financial costs, and time constraints can all impede patients from receiving consistent in-person exercise-based interventions.^7,8 In this scenario, telemedicine has emerged as a promising strategy to deliver specialized care remotely. By leveraging digital communication tools, telemedicine can enhance access to post-HSCT services, reduce the logistical and financial burdens associated with frequent in-person visits, and maintain close patient monitoring even when individuals are deemed clinically unstable.⁹

Although telemedicine holds considerable promise for optimizing care delivery and long-term management in HSCT populations, its implementation, effectiveness, and overall impact have not been comprehensively explored. This gap in the literature warrants a systematic examination to identify current telemedicine applications, evaluate their feasibility and effectiveness, and highlight areas requiring further investigation. Accordingly, this scoping review aims to map the current landscape of telemedicine-supported exercise interventions in HSCT, assessing their clinical and technical characteristics, feasibility, effectiveness, and gaps in the literature.

Methods

Study Design

This scoping review was conducted following the framework proposed by Arksey and O’Malley,¹⁰ with enhancements suggested by Levac et al¹¹ and the Joanna Briggs Institute (JBI) Manual for Evidence Synthesis.¹² Our methods adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews¹³ (See Table S1).

Information Sources and Search Strategy

A comprehensive search was conducted in the following databases: MEDLINE (via PubMed), SCOPUS, Web of Science, and Embase. We used controlled vocabulary (eg, MeSH terms) and keywords related to telemedicine and hematopoietic stem cell transplantation (eg, “telemedicine”, “telehealth”, “HSCT”). The search included studies published from database inception to July 31, 2024, without language restrictions. Search strategies for each database are detailed in Tables S2–S5.

Study Selection

We included experimental studies, such as randomized and non-randomized clinical trials, as well as quasi-experimental designs (eg, pre-post studies) that were published as peer-reviewed articles, letters, or short communications. The eligible studies reported results on telemedicine-supported exercise interventions pre-, during, and post-HSCT. Additionally, documents reporting any type of healthcare services related to HSCT delivered via telehealth were also included. Conversely, we excluded secondary research studies, including systematic reviews, umbrella reviews, and scoping reviews; however, references within these studies were consulted to identify relevant primary research. Other exclusions included protocols, opinions, case reports, case series, and non-peer-reviewed documents.

The study selection process involved two stages and was conducted using the Rayyan.ai platform. In the first stage, two independent reviewers screened the titles and abstracts of all identified studies. Any disagreements between the reviewers were resolved by a third reviewer. In the second stage, the full texts of selected articles were retrieved and assessed against the predefined eligibility criteria. To ensure consistency in the application of inclusion and exclusion criteria, a pilot screening of 11 documents was conducted prior to the formal selection process. This pilot exercise allowed for standardization of the reviewers’ approach and refinement of the criteria.

Data Charting Process

We developed a standardized data charting form, capturing key information on study design, participant demographics, telemedicine technical features, therapeutic approaches, and outcomes evaluated. This form was piloted on two studies to ensure its clarity and comprehensiveness. Data extraction was conducted independently by two pairs of reviewers. Any discrepancies in data extraction were resolved through discussion or consultation with a third reviewer.

Data Synthesis

Data were synthesized narratively and presented using descriptive statistics and cross-tabulation to illustrate the main findings. We synthesized information on the study designs, technical characteristics of telemedicine interventions, therapeutic approaches used, and outcomes assessed. The results were categorized based on themes identified during the data extraction phase, and tables were generated to provide a detailed summary of the studies included.

Results

Selection Process

We found in our query research 1116 potential papers to be included in the study. After duplicates were removed, 644 reports were screened by title and abstract, 624 of them were excluded and we found 20 relevant documents to the research question. All these studies were then read in detail, resulting in 10 articles to be included in the final study.^14–23 Specific reasons for excluding the remaining full-text articles are provided in Table S6. This process is detailed in Figure 1.

Figure 1 PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart of the study search and exclusion process.

General Characteristics

Table 1 describes the findings regarding the main characteristics of the studies and participants. The included studies were published between 2005 and 2024, with the highest concentration in 2023 (30%, n=3).^20–22 Most studies were conducted in the United States (70%, n=7),^{14,16–18,20,21,23} with the remaining studies carried out in Germany,¹⁵ Australia,¹⁹ and the United Kingdom (10% each).²²

Table 1 Study Design and Participants Characteristics

The majority of studies (90%, n=9) focused on feasibility,^14,16–23 with quasi-experimental designs predominating (60%, n=6).^{14,16,18–20,23} Half of the studies (n=5) included one arm,^{14,18–20,23} while the other half included two arms.^{15–17,21,22} All studies followed prospective designs. Half of the studies (n=5) were single-arm pre-post studies,^{14,18–20,23} one of them being a study that includes dyads of patient-caregiver.²³ Randomized controlled trials (RCTs) were present in 40% of studies.^15,17,21,22 Among these, two RCTs evaluated outcomes across two time points (pre- and post-intervention),^17,21 another across four time points (2 pre-HSCT and 2 post-HSCT),¹⁵ and one across three time points (1 pre-HSCT and 2 post-HSCT).²² The sample sizes were limited, with 8 out of 10 studies (80%) enrolling fewer than 50 participants.^{14,16–21,23} The details on inclusion of patients with autologous (auto) and allogeneic (allo) HSCT as well as patients with GVHD are delineated in Table 1.

Participants Characteristics

Regarding gender distribution, 8 studies (80%) reported a higher proportion of men,^{15–20,22,23} whereas only one study (10%) included more women,¹⁴ and another (10%) had equal representation of men and women.²¹ Age characteristics were reported in various formats. Mean ages were provided 60% of the studies and ranged from 48.8 to 64.7 years.^{14,15,20–23} Median ages were reported in 3 studies (30%) and ranged from 52 to 60.5 years.^16,17,19 Age ranges were described in 5 studies (50%), spanning from as young as 18 to as old as 76.4 years.^15,17–20

Regarding diagnoses, leukemia^15–21,23 and lymphoma^{14,16–21,23} were the most frequently studied conditions, with both being addressed in 8 out of 10 studies (80%). Multiple myeloma followed, appearing in 70% (n=7) of studies.^{14–17,21–23} Most interventions were conducted after HSCT (50%, n=5),^{14,18,19,21,23} while 30% (n=3) were conducted before transplantation^16,17,20 and 20% (n=2) spanned from before to after HSCT.^15,22

Technology Used

As show in Table 2, phone calls and medical devices were the predominant technologies, used in 80% (n=8)^{14–18,20,22,23} and 70% (n=7)^{14,16,17,20–23} of studies, respectively. Videoconferencing was reported in 4 out of 10 studies (40%).^19,20,22,23 Fewer studies incorporated web systems (20%, n=2),^21,23 mobile apps (10%, n=1),²⁰ or SMS (10%, n=1).²⁰ Various medical devices were used, including smart-watches (n=4, 40%),^16,17,20,23 heart-rate monitors (n=2, 20%),^14,22 and gait sensors (n=1, 10%).²¹ Most studies relied on one (30%, n=3)^15,18,19 or two (40%, n=4)^14,16,17,21 technologies, while fewer incorporated three or more (n=3, 30%).^20,22,23

Table 2 Intervention Characteristics

Exercise Program Details

Table 3 summarizes exercises modalities and exercise prescription approaches reported in the reviewed articles. Seven out of 10 studies (70%) reported self-directed exercise programs,^{14–18,20,23} while 30% (n=3) were guided by healthcare providers.^19,21,22 Half of the studies present hybrid exercise delivery (home and clinic) (n=5),^{14,16,17,21,23} with 2 studies (20%) with this delivery of exercise among the whole period of the intervention^15,22 and 3 studies (30%) presenting this modality for the initial sessions.^18–20 Aerobic exercise was the most common modality, included in 80% (n=8) of studies.^{14–17,19,20,22,23} Resistance exercises were implemented in 5 out of 10 studies (50%),^{15,18,19,21,22} whereas flexibility and other exercises, such as mindfulness-based stress management and balance training, appeared in fewer studies.

Table 3 Exercise Description

Exercise program durations ranged from 6 to 15.3 weeks, with some studies reporting unclear durations (n=1, 10%).¹⁵ The most frequently reported session length was 30 minutes, described in 40% (n=4) of studies.^16,17,20,21 Most of the studies reported some way of intensity goals for the exercise programs (n=7, 70%),^{14–17,19,20,22} being HRR the most frequent intensity indicator (n=3, 30%),^14,20,22 followed by MHR (n=2, 20%),^16,17 and the Borg Perceived Exertion Scale (n=2, 20%).^15,19 Only 2 studies (20%) explicitly mentioned the use of any behavioral change theory or technique to guide the exercise intervention.^22,23

Regarding monitoring performance, most studies (n=5, 50%) delivered in a differed way (after the exercise session) by phone-calls (n=4, 30%)^14–16,18 or web-interface connected to medical devices (n=1, 10%).²³ Three studies conducted monitoring during the exercise session using videoconference services (30%).^19,20,22

Outcomes Measured

Functional outcomes were reported in the majority of studies (90%, n=9)^14–22 likely feasibility outcomes which appeared in 90% (n=9).^14,16–23 Quality of life was evaluated in 5 out of 10 studies (50%).^{14,15,17,19,22} Usability outcomes were less common, included in only 20% (n=2) of studies.^19,20 Adverse events were monitored in 60% (n=6) of studies,^{14–16,19,20,22} though no reactions attributable to exercise were reported.

Across the included studies, exercise-based interventions delivered via telemedicine demonstrated varied and meaningful outcomes for patients undergoing hematopoietic stem cell transplantation (HSCT). Significant improvements in physical fitness and functioning were observed, including increases in VO2peak from 14.6 ± 3.1 to 17.9 ± 3.3 mL/kg/min (P < 0.001).²⁰ Sustained improvements in the 6-minute walk test (6MWT) were reported, with mean differences of 79.6 m (95% CI: 28–131) at 3 months and 48.4 m (95% CI: 13–84) at 12 months, along with improvements in sit-to-stand repetitions and handgrip strength.¹⁹ Gait speed and handgrip strength improvements were described as clinically meaningful due to their associations with reduced mortality risk.^18,21 Functional outcomes, such as step counts, also increased significantly during interventions, with one study reporting an increase from 2249 ± 302 steps/day in week 1 to 4975 ± 1377 steps/day in week 8 for participants, while caregivers saw an increase from 8676 ± 3760 to 9838 ± 3723 steps/day during the same period.²³

Interventions positively influenced quality of life and fatigue outcomes. Improvements in quality of life, measured by FACT-G and FACT-BMT, and fatigue, measured by FACIT-F, exceeded minimal important differences during the intervention periods.²² However, declines in quality of life were noted during hospitalization phases, such as autologous stem cell transplantation (ASCT), followed by recovery improvements during rehabilitation phases.²² The exercise group in one study experienced a 15% improvement in fatigue scores compared to a 28% deterioration in the control group (P =0.01–0.03).¹⁵

Home-based aerobic and resistance exercises were frequently implemented and well-accepted, with studies reporting their safety and effectiveness.^15,19 High-intensity interval training programs also yielded significant functional and physiological gains, with observed changes surpassing clinically important thresholds.²⁰ However, one pilot study reported feasibility challenges with its prehabilitation design, limiting its ability to draw definitive conclusions and underscoring the need for refined future interventions.¹⁷

Discussion

Principal Results and Comparison with Prior Work

This review aimed at mapping the current state of research regarding the clinical and technical applications of telemedicine in the context of HSCT. Ten eligible articles reporting experimental results were used for a critical overview of the current landscape and informing future research directions of the telemedicine-supported exercise interventions in patients undergoing HSCT. Although the number of eligible studies was limited, collectively they suggest that telemedicine modalities, ranging from telephone-based consultations to videoconferencing and wearable devices, can effectively support exercise programs for HSCT recipients before, during, and after transplantation (Figure 2). Across these studies, telemedicine-facilitated exercise regimens were generally found to be feasible, acceptable, and safe. Importantly, patients who engaged in these interventions often experienced improvements in functional capacity, including enhanced VO2peak, 6-minute walk test performance, handgrip strength, and 30-second sit-to-stand test scores, as well as better quality of life outcomes.^14–23

Figure 2 Relations between key characteristics of the included studies.

The outcome improvements resulting from telemedicine-supported exercise programs in HSCT patients are analogous to the outcome improvements reported in the comprehensive reviews of in-person exercise interventions conducted in both allo- and auto-HSCT patients.^24–26 A systematic review and meta-analyses of randomized controlled trials assessing impact of physical exercise for patients undergoing hematopoietic stem cell transplantation demonstrated sufficient evidence that recipients of HSCT benefit from physical exercise.²⁷ DeFor et al found that physical exercise provided numerous benefits for HSCT patients, including enhancing both physical and emotional recovery after transplant therapy and potentially speeding up their return to health and functionality following the procedure.²⁸ The review by Morishita et al concluded that physical exercise is beneficial for the physiological, psychological, and psychosocial health of allo-HSCT patients.²⁴ This review recommended encouraging patients to perform physical exercise before, during, and after transplantation, and stated that physical exercise should be integrated into the conditioning and recovery plans for all allo-HSCT patients.²⁴ Those results are very well aligned with the findings from the studies included in this review.

The results of this review are in concordance with the recent report by Gandhi et al⁹ concluding that telemedicine-supported physical activity yields positive results in patients undergoing HSCT. Gandhi et al underscored the potential of telemedicine-supported exercise in frail patients whose functional reserve can be significantly enhanced while following home-based exercise program.⁹ These recommendations are especially relevant in the light of the fact that not only the overall numbers of HSCT are increasing, but HSCTs in adults over 70 years old are increasing at an even greater rate.^24,25 Incorporating telemedicine into exercise interventions will aid in reducing both disability and healthcare utilization among these individuals.

Telemedicine-supported exercise programs have also a potential to address the economic and geographic barriers to access guideline-concordant care. Delamater et al found that fifty million adults reside more than 90 min from the nearest care facility. Access to cancer rehabilitation services is certainly influenced by geography; however, numerous additional factors may limit access to best available care, including sociodemographic status, health insurance and resource availability. Potential alternative strategies to address the transportation challenges for HSCT patients residing in remote location include implementation of telemedicine systems for home-based care delivery.²⁵ Overall, physical exercise delivered via telemedicine provided numerous benefits for HSCT patients, including enhancing both physical and emotional recovery after transplant therapy and potentially speeding up their return to optimal health and functional capacity following HSCT.²⁴ Future approaches for telemedicine-supported exercise in HSCT patients should be enhanced by the recent advances in machine learning optimization of individualized exercise plans,^29,30 predictive analytics utilizing patient-generated data,^31,32 and interfaces with electronic health records to support personalization,^33,34 adherence, efficacy, and safety of the home-based exercise programs.^35,36 Patient engagement in exercise programs can be facilitated by exergaming in virtual reality^37,38 and artificial intelligence-based chatbots^39,40 promoting patient education^41,42 and healthy behaviors.^43,44

Limitations

This review presented some limitations. The included studies were relatively few and predominantly pilot or feasibility trials, limiting the strength of the conclusions and their generalizability. Many studies lacked robust sample sizes and long-term follow-up data, and outcome measures varied considerably across the literature. Additionally, the majority of studies were conducted in high-income countries, which may not reflect global healthcare contexts or resource constraints. Such factors underscore the need for more geographically diverse, large-scale, and standardized research efforts to fully establish the efficacy, cost-effectiveness, and global applicability of telemedicine-based exercise interventions for HSCT patients residing in urban and rural areas. Limited information is available on differences in responses to the telemedicine-supported exercise interventions in patients receiving autologous or allogeneic stem cell transplantation. The impact of telemedicine-supported exercise interventions in patients with GVHD as compared to patients without GVHD has not been systematically studied. Another limitation is that this review did not conduct a formal risk of bias assessment for the included studies. While this could have provided a more thorough evaluation of the methodological rigor of the evidence, this limitation is mitigated by the fact that only peer-reviewed articles and experimental designs were included. These criteria inherently ensure a higher level of methodological quality and reduce the likelihood of significant bias within the included studies.

Conclusions

Telemedicine for patients pre-, post- and during HSCT demonstrated to be feasible, beneficial, acceptable and effective with improvements in quality of life and physical function. However, the evidence base remains limited by small sample sizes, short follow-up periods, and predominantly feasibility-focused designs. Future research should emphasize larger, methodologically robust trials, consistent outcome measures, and include both urban and rural settings in order to establish best practices and guide broader implementation.

Acknowledgments

We would like to express our gratitude to David Villarreal-Zegarra for his invaluable support in managing the Rayyan platform, which facilitated the screening of titles, abstracts, and full-text articles. We also extend our thanks to Stefan Escobar-Agreda for his contributions as a reviewer during the screening and selection process. Their assistance was instrumental in the successful completion of this study.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

This study has been in part supported by the contract HT9425-24-1-0264 from the Congressionally Directed Medical Research Program.

Disclosure

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Introduction

Hepatocellular carcinoma (HCC) stands as a pressing global health challenge characterized by a rising incidence and mortality rate.^1,2 Although the overall survival of HCC patients was improved accompanied by the emergence of immunotherapies recently, research on HCC survivorship remains limited.

Vital facets of HCC survivorship encompass enhancing overall survival, navigating the array of long-term adverse effects from HCC treatment, and comprehending their impact on patient-reported outcomes like quality of life (QOL) and financial toxicity (FT). Despite patients with early-stage HCC typically being asymptomatic, individuals across all stages and treatment modalities often endure diminished QOL relative to the general or cirrhotic populations.^3–5 The term FT has been used to describe both the objective financial burdens of medical care as well as the subjective distress.⁶ Several researches have reported that FT was associated to decreased QOL in other cancers such as lung cancer, colorectal cancer, breast cancer, and so on,^7–9 but FT is yet to be reported in HCC patients. In addition, HCC patients commonly contend with chronic liver diseases like HBV infection, HCV infection, steatohepatitis, and alcoholic hepatitis. In China, approximately 80% of HCC patients are infected with HBV,¹⁰ and they are recommended to take antiviral drugs for whole life long.^11,12 Beyond HCC, the treatment of chronic liver diseases like antivirals for HBV and liver protectants further compounds FT among HCC patients, which may cause higher FT for them compared to other cancers.

Cancer can also disrupt the social fabric of patients,¹³ which may in turn influence the support they receive during their illness.^14,15 It is reported that social support could ameliorate the negative psychological repercussions of cancer diagnosis and treatment.^16,17 In our investigation, we employed the Social Support Rating Scale (SSRS),^18,19 besides subjective support (perceived support or emotional assistance), objective support (actual support received, such as financial support) and utilization of support (effective use of social support) are also included into the dimensions of SSRS. Thus, delving into the impact of social support on FT and various QOL dimensions beyond emotional well-being holds significance.

In this study, we aim to (1) report the presence and degree of FT experienced by HCC patients and identify demographic and clinical risk factors for FT, (2) pinpoint demographic and clinical risk factors for different dimensions of QOL in HCC patients, and (3) investigate the association among social support, FT and QOL.

Methods

Study Design and Participants

We have investigated 239 patients diagnosed with HCC at Sun Yat-sen University Cancer Center from August 1, 2023, to December 30, 2023, a convenience sampling method was used in this study. Inclusion criteria encompassed: 1) Histologically or radiologically confirmed HCC diagnosis; 2) Age ≥ 18 years; 3) Primary school education or higher; 4) Awareness of their HCC diagnosis; 5) Willingness to participate in this study. Exclusion criteria involved: 1) History of mental illness; 2) Severe systemic infections, severe anemia, or cachexia; 3) Patients with communication barriers. This research received approval from the Ethics Committee Board of Sun Yat-sen University Cancer Center (Approval number B2023-261-01). Participants were briefed face-to-face on questionnaire completion procedures and guidelines. They independently completed the questionnaire, with certain sections filled by investigators based on medical records or consultation with participants. All questionnaires were distributed and reviewed promptly post-collection to rectify any oversights, ensuring data integrity. Out of 250 distributed surveys, 239 valid responses were obtained, yielding an impressive response rate of 95.6%.

The questionnaire comprised the Comprehensive Score for Financial Toxicity (COST) measure, the Social Support Rating Scale (SSRS), and the Functional Assessment of Cancer Therapy-Hepatobiliary (FACT-Hep). The COST tool, validated with 11 items, gauges cancer patients’ financial toxicity (lower scores indicating higher FT).²⁰ The SSRS,^18,19 devised by Shuiyuan Xiao, was employed to evaluate social relationships across three dimensions through ten items: objective support (actual support received), subjective support (perceived support or emotional assistance), and utilization of support (effective use of social support). The FACT-Hep is an extension of the FACT-G (Functional Assessment of Cancer Therapy-General, consisting of 27 items) with an added liver-specific module- “additional concerns” (comprising 19 items closely related to physical health issues in patients with liver cancer), resulting in a 46-item self-assessment scale.²¹ It includes five dimensions: physical well-being, social/family well-being, emotional well-being, functional well-being, and additional concerns, all rated on a 5-point scale (0–4 points), with higher scores indicating a higher quality of life (QOL) in that aspect for the patient.

Statistical Analysis

Participant demographic and clinical characteristics are summarized using frequencies and percentages. Scores on the QOL scale, COST tool, and social support measure are summarized using medians and interquartile ranges (IQRs). Multivariable linear regression analysis, incorporating significant factors from univariate analysis (P < 0.05), was performed to identify the independent risk factors associated with QOL and FT. Constructing a deeper understanding of the relationships among social support, FT, and QOL, structural equation models (SEM) were crafted using The AMOS 24.0 software. The verification of the impact of social support on the interplay between FT and QOL was examined through bootstrapping analyses with 5000 samples. The effect size for each indirect effect was assessed using completely standardized indirect effect beta values.²² The indirect effect was considered significant if the 95% bias-corrected confidence intervals did not include 0. A two-tailed P value of <0.05 was deemed statistically significant. Statistical analyses were conducted using SPSS version 26.0 or R version 4.2.2 (R Foundation, Vienna, Austria).

Results

Patient Demographics and Characteristics

Of the 250 patients with HCC approached for participation, 239 (95.6%) completed the survey and were included in this study. The average age of the respondents was 50.5 (standard deviation [SD], 11.1) years, the majority were male (192 [80.3%]), of Han nationality (235 [98.3%]), married (214 [89.5%]), and possessed social basic medical insurance (202[84.5%]). Approximately half of the patients reported a household income of ¥2000–4000/month/person (101 [42.3%]), and had an educational level below high school (122 [51.0%]). The predominant occupation before illness was peasantry (62 [25.9%]), followed by service (53 [22.2%]), and worker (43 [18.0%]). Not coincidentally, the most residence of patients was rural (81 [33.9%]). For work status currently, around half of the patients were employed on sick leave (112 [46.9%]), notably, 88 (36.8%) patients were unemployed, much higher than that (13 [5.4%]) before illness. Details are described in Table 1.

Table 1 Patient Demographics and Characteristics

Around half of the patients had stage III disease at diagnosis (110 [46.0%]) and received combination therapy of immunotherapy, targeted therapy, and interventional therapy (135 [56.5%]). A majority of patients had a family history of cancer (184 [77.0%]) and were accompanied with chronic disease such as diabetes and hypertension (152 [63.6%]). Most patients were diagnosed less than 6 months (183 [76.6%]) and had been hospitalized fewer than 5 times in the past year (195 [81.6%]). Hospitalization costs for 104 patients (43.5%) ranged between ¥20000 and 40000.

Financial Toxicity Analysis

The median COST score was 19 (IQR, 10–25), and high FT was defined as a COST score below the cohort’s median (<19). Univariate analysis of the COST score (Supplementary Table 1) revealed several demographic and clinical factors that were associated with higher FT, including residence in rural (β, −4.56; 95% CI, −7.49 ~ −1.63; P = 0.003), unemployment currently (β, −6.17; 95% CI, −9.72 ~ −2.61; P < 0.001), private in medical insurance (β, −6.19; 95% CI, −11.01 ~ −1.38; P = 0.012), treatment of hepatic arterial infusion chemotherapy (HAIC) (β, −8.50; 95% CI, −14.53 ~ −2.47; P = 0.006) or combination treatment (β, −4.15; 95% CI, −6.74 ~ −1.55; P = 0.002), higher disease stage (stage III vs stage I: β, −13.09; 95% CI, −19.53 ~ −6.64; P < 0.001; stage IV vs stage I: β, −17.44; 95% CI, −25.97 ~ −8.90; P < 0.001), occupation of peasantry (β, −4.68; 95% CI, −8.62 ~ −0.73; P = 0.021) and unemployment before illness (β, −7.05; 95% CI, −12.90 ~ −1.1; P = 0.019). Overall social support (β, 0.16; 95% CI, 0.02 ~ 0.30; P = 0.025) and higher household income (¥2000–4000/month/person vs <¥2000/month/person: β, 3.93; 95% CI, 0.79 ~ 7.06; P = 0.015; ≥¥4000/month/person vs <¥2000/month/person: β, 8.11; 95% CI, 4.93 ~ 11.2; P < 0.001) were associated with lower FT.

Multivariate analysis (Table 2) suggested that unemployment currently (β, −4.17; 95% CI, −7.65 ~ −0.69; P = 0.02), and treatment of HAIC (β, −7.65; 95% CI, −13.55 ~ −1.7; P = 0.012) or combination treatment (β, −3.93; 95% CI, −7.09 ~ −0.78; P = 0.015) were independently associated with higher FT. Overall social support (β, 0.13; 95% CI, 0.01 ~ 0.26; P = 0.048) and higher household income (¥2000–4000/month/person vs <¥2000/month/person: β, 3.20; 95% CI, 0.09 ~ 6.30; P = 0.045; ≥¥4000/month/person vs <¥2000/month/person: β, 7.62; 95% CI, 4.53 ~ 10.7; P < 0.001) were independently associated with lower FT.

Table 2 The Multivariate Analysis of Risk Factors for Financial Toxicity (COST Score)

Based on the above analysis, the following were identified as the independent risk factors for high financial toxicity: (1) unemployment currently, (2) treatment of HAIC and combination treatment, (3) lower overall social support (score < 36 [median]), (4) household income < ¥2000/month/person. Within our cohort, 11.7% (n = 28) of patients had zero risk factors, 35.1% (n = 84) had one, 32.2% (n = 77) had two, 18.4% (n = 44) had three, and 2.5% (n = 6) had all four risk factors. The relationship between high FT and the median COST score, stratified by the number of risk factors, is illustrated in Figure 1. As the number of risk factors increased from zero to four, the percentage of patients with high FT increased from 25.0% (n = 7/28) to 36.9% (n = 31/84) to 50.6% (n = 39/77) to 77.3% (n = 34/44) and to 100% (n = 6/6), respectively (P < 0.001). As expected, the median COST score decreased as the number of risk factors increased. The median COST score for those with zero risk factors was 24.5 (range: 7–35), one risk factor was 21 (range: 3–41), two risk factors was 18 (range: 1–41), three risk factors was 12 (range: 0–27), and four risks was 4.5 (range: 0–13).

Figure 1 The bar graph represents the percentage of patients with high financial toxicity [Comprehensive Score for Financial Toxicity (COST) <19] and the line graph represents the median COST score stratified by the number of risk factors. Lower median COST score indicates higher financial toxicity. As the number of risk factors increased from zero to four, the percentage of patients with high FT increased from 25.0% (n = 7/28) to 36.9% (n = 31/84) to 50.6% (n = 39/77) to 77.3% (n = 34/44) and to 100% (n = 6/6), respectively (P < 0.001).

Quality of Life Analysis

The median overall QOL score was 111 (IQR, 97–124). Univariate analysis results for overall QOL are provided in Supplementary Table 2. The multivariate analysis (Table 3) revealed that time since diagnosis is longer than 6 months (β, −7.12; 95% CI, −12.73 ~ −1.5; P = 0.014), and stage II (β, −9.3; 95% CI, −15.10 ~ −3.5; P = 0.002) or stage III (β, −8.35; 95% CI, −16.41 ~ −0.2; P = 0.043) disease were independently associated with lower overall QOL. Lower FT (higher COST score) (β, 0.74; 95% CI, 0.49 ~ 0.99; P < 0.001) and overall social support (β, 1.47; 95% CI, 0.73 ~ 2.21; P < 0.001) were independently associated with higher overall QOL.

Table 3 The Multivariate Analysis of Risk Factors for Overall QOL

Overall QOL comprises five parts, including physical well-being, social/family well-being, emotional well-being, functional well-being, and additional concerns. To explore how demographic and clinical factors influence overall QOL across these domains, we conducted further univariate and multivariate analyses of the five components. Univariate analysis results for physical well-being (Supplementary Table 3), social/family well-being (Supplementary Table 4), emotional well-being (Supplementary Table 5), functional well-being (Supplementary Table 6), and additional concerns (Supplementary Table 7) are provided in the supplementary.

The multivariate analysis (Table 4) revealed that high school/technical secondary school/junior college education (β, −1.71; 95% CI, −3.01 ~ −0.41; P = 0.011) and stage II (β, −2.09; 95% CI, −4.10 ~ −0.08; P = 0.043), stage III (β, −2.98; 95% CI, −4.56 ~ −1.40; P < 0.001) or stage IV (β, −5.07; 95% CI, −7.18 ~ −2.97; P < 0.001) disease were independently associated with worse physical well-being, and lower FT (β, 0.17; 95% CI, 0.10 ~ 0.24; P < 0.001) was independently associated with better physical well-being. Objective support (β, 0.18; 95% CI, 0.02 ~ 0.35; P = 0.033) and subjective support (β, 0.24; 95% CI, 0.16 ~ 0.33; P < 0.001) were independently associated with better social/family well-being. Time since diagnosis longer than 6 months (β, −1.2; 95% CI, −2.36 ~ −0.03; P = 0.045) was independently associated with worse emotional well-being, and lower FT (β, 0.13; 95% CI, 0.08 ~ 0.19; P < 0.001) was independently associated with better emotional well-being. Time since diagnosis longer than 6 months (β, −2.44; 95% CI, −3.93 ~ −0.95; P = 0.002) was independently associated with worse functional well-being, and lower FT (β, 0.11; 95% CI, 0.04 ~ 0.18; P = 0.003), overall social support (β, 0.14; 95% CI, 0.05 ~ 0.23; P = 0.003), and Bachelor’s degree education (β, 2.48; 95% CI, 0.08 ~ 4.88; P = 0.044) were independently associated with better functional well-being. Employment on sick leave (β, −3.95; 95% CI, −7.61 ~ −0.29; P = 0.035) or unemployment currently (β, −4.89; 95% CI, −8.80 ~ −0.98; P = 0.015) and treatment of HAIC (β, −7.38; 95% CI, −13.76 ~ −1.0; P = 0.024) or combination treatment (β, −4.12; 95% CI, −6.94 ~ −1.30; P = 0.005) were independently associated with worse additional concerns, and lower FT (β, 0.22; 95% CI, 0.08 ~ 0.36; P = 0.002) and overall social support (β, 0.18; 95% CI, 0.03 ~ 0.32; P = 0.017) were independently associated with better additional concerns.

Table 4 Multivariate Analysis of Risk Factors for Physical Well-Being, Social/Family Well-Being, Emotional Well-Being, Functional Well-Being, and Additional Concerns

In summary, lower FT was independently associated with improved physical well-being, emotional well-being, functional well-being, and additional concerns; social support was independently associated with improved social/family well-being, functional well-being, and additional concerns (Figure 2).

Figure 2 The effect of social support and financial toxicity on different dimensions of quality of life (QOL).

Association Among Social Support, Financial Toxicity, and Quality of Life

As previously discussed, social support was found to be independently associated with FT and QOL, while FT was independently associated with QOL. Thus, mediation analyses were performed to ascertain whether social support indirectly influenced QOL through FT. The structural equation model (SEM) was constructed (Figure 3), and the Bootstrap sampling test method was employed to conduct a study on the effect of social support between FT and QOL with 5000 sampling iterations. The results showed that the total effect of social support on QOL was 0.76 (P<0.001, 95% CI [0.45–1.06]), the direct effect of social support on QOL was 0.62 (P<0.001 95% CI [0.33–0.90]), and the indirect effect of social support on QOL through FT was 0.14 (95% CI [0.03–0.28]), accounting for 18.4% of the total effect.

Figure 3 The direct and indirect effect of social support on quality of life (QOL): total effect of social support on QOL was 0.76 (P<0.001, 95% CI [0.45–1.06]), the direct effect of social support on QOL was 0.62 (P<0.001 95% CI [0.33–0.90]), and the indirect effect of social support on QOL through FT was 0.14 (95% CI [0.03–0.28]), accounting for 18.4% of the total effect.

Discussion

Financial Toxicity in Hepatocellular Carcinoma Patients

This research marks the inaugural exploration into FT in HCC patients. The median COST score was 19 in our cohort, a figure lower than that observed in other cancer types such as lung cancer (median COST score: 24–29),^23–25 colorectal cancer (median COST score: 21–24.5),²⁶ and breast cancer (median COST score: 28),²⁷ indicating higher FT. Notably, HCC patients commonly contend with chronic liver diseases like HBV infection, HCV infection, steatohepatitis, and alcoholic hepatitis. In China, approximately 80% of HCC patients are infected with HBV,¹⁰ and they are recommended to take antiviral drugs for whole life long.^11,12 Beyond HCC, the treatment of chronic liver diseases like antivirals for HBV and liver protectants further compounds FT among HCC patients, which may cause higher FT for them compared to other cancers.

This study illuminates that unemployment and lower household income stand as independent factors associated with higher FT, echoing findings in other cancer studies.²⁸ Moreover, we identified treatment of HAIC and combination treatment were independently associated with higher FT. HAIC and combination treatment were palliative treatment for median or advanced stage HCC, requiring patients for multiple hospitalizations, which interrupted the normal life of HCC patients and consequently resulted in higher FT. Noteworthy is the revelation that social support emerged as a pivotal factor in mitigating FT within our study.

Building on the work of Melinda et al, it is evident that unmet physical, social, and medical needs are associated with lower QOL, with only unmet social needs correlating with higher FT in lung cancer patients.²⁵ The provision of social support effectively addresses patients’ social needs, underscoring its significant impact on FT.

We have identified four risk factors independently associated with FT as described above. As the number of risk factors increased from zero to four, the percentage of patients with high FT increased accordingly. As expected, the median COST score exhibited a decline with an increasing number of risk factors (Figure 1).

Quality of Life in Hepatocellular Carcinoma Patients

Longer time since diagnosis, higher stage disease, higher FT, and less social support were identified as independent factors associated with lower overall QOL in this study. Beyond overall QOL, our investigation delved into factors influencing diverse dimensions of QOL, encompassing physical well-being, social/family well-being, emotional well-being, functional well-being, and additional concerns (liver-specific module).

Our findings indicate that lower FT was independently associated with better physical well-being, emotional well-being, functional well-being, and additional concerns, except for social/family well-being. FT intensifies feelings of anxiety, depression, and fatigue due to increased medical interventions, leading to compromised emotional well-being.^29,30 Patients with cancer are also more likely than individuals without cancer to experience loss of income because of decreased productivity and job loss and are more likely to miss work, take unexpected sick days or unpaid leave, and miss opportunities for promotion and raises,^31,32 resulting in worse functional well-being. Additionally, patients with higher FT may be less able to focus on the day-to-day clinical management,³³ delay or forgo necessary medical care and prescriptions,³⁴ and have higher rates of adverse events because of lower capacity to manage them, thereby compromising physical well-being and raising additional concerns.

We found that social support was independently associated with social/family well-being, functional well-being, and additional concerns. Conversely, the absence of an independent association between social support and emotional well-being was unexpected, especially given previous reports linking social support to emotional QOL in other cancer survivor populations.^35,36 The reasons may be as follows: firstly, a different QOL tool would have a different outcome,^37,38 we employed a liver-specific QOL tool (FACT-Hep) in this study; secondly, we found longer time since diagnosis and FT were independently associated with the emotional well-being in the multivariable analysis, these two factors may contribute more to the impact of emotional well-being than social support; thirdly, social support was independently associated with FT, which may indirectly affect emotional well-being.

As mentioned above, social support was not only independently associated with QOL but also FT, and FT was the independent factor associated with QOL. To elucidate the interplay between social support, FT, and QOL, we employed a structural equation model with mediation analysis. This approach allows us to disentangle direct effects (eg, how social support independently improves QoL) from indirect effects (eg, how social support alleviates FT, which in turn enhances QoL). The Bootstrap method (5000 resamples) was used to calculate confidence intervals for these effects, as it is robust to non-normal data distributions and provides reliable estimates even in smaller samples. For total effect, Social support improved QoL by 0.76 units; for direct effect, 81.6% of this improvement (0.62 units) occurred independently of FT reduction; for indirect effect, the remaining 18.4% (0.14 units) operated through reducing FT. The Bootstrap 95% CI for the indirect effect ([0.03–0.28]) excluded zero, confirming its significance. The 18.4% mediation proportion suggests that interventions targeting both social support and FT may amplify QoL improvements compared to isolated approaches.

Most independent factors associated with FT and QOL are immutable (eg, disease stage, treatment methods, time since diagnosis, income, and work status), social support remains a modifiable factor that medical professionals can guide and enhance.³⁵ Medical professionals can guide patients to actively seek social support, strengthen the utilization of social support, and educate family members and friends to provide social support for patients, which may significantly bolster patients’ QOL and alleviate FT burdens.

Strengths and Limitations

Our study has several other strengths including a very high response rate of 95.6%, thereby ensuring the representativeness of our study population among HCC patients at our institution. Furthermore, the provision of standardized instructions and face-to-face interactions during questionnaire completion facilitated high-quality data collection, with immediate post-collection scrutiny to rectify any omissions or errors promptly.

Conversely, our study has certain limitations. Being cross-sectional in nature, it fails to capture the evolving patient experiences over time, necessitating longitudinal investigations for a comprehensive understanding of patient trajectories. Moreover, our study overlooks the perspectives of caregivers concerning QOL, FT, and social support, crucial for a holistic comprehension of the survivorship journey.

Conclusions

We found that unemployment, lower household income, treatment of HAIC or combination treatment, and lower social support were independently associated with higher FT. Lower FT was independently associated with better physical well-being, emotional well-being, functional well-being, and additional concerns, except for social/family well-being. Social support was independently associated with social/family well-being, functional well-being, and additional concerns. Social support not only affected the QOL directly but also indirectly through FT. The interplay between social support, FT, and QOL offers insights to tailor interventions effectively, mitigating FT burdens, and enhancing QOL for HCC patients.

Abbreviations

HCC, hepatocellular carcinoma; COST, The comprehensive score for financial toxicity; FACT-Hep, the Functional Assessment of Cancer Therapy-Hepatobiliary; FT, financial toxicity; HAIC, hepatic arterial infusion chemotherapy; IQRs, interquartile ranges; QOL, quality of life; SD, standard deviation; SEM, structural equation models.

Data Sharing Statement

All data generated or analyzed during this study are included in this article. Further information is available from Yaojun Zhang upon request.

Ethics Approval Statement

This study was conducted according to the ethical guidelines of the 1975 Declaration of Helsinki. This research was approved by the institutional review board of Sun Yat-sen University Cancer Center (Approval number B2023-261-01). Informed consent was obtained from all subjects involved in the study.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

Supported by Postdoctoral Fellowship Program of CPSF (GZB20240893).

Disclosure

The authors declare no conflicts of interest in this work.

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Automotive: significant improvement in earnings; EBIT margin at upper end of guidance 

The Automotive group sector recorded sales of €4.7 billion in the second quarter (Q2 2024: €5.0 billion, -5.0 percent). Before exchange-rate effects and changes in the scope of consolidation, it posted organic sales growth of -1.2 percent. Its adjusted EBIT margin was 9.0 percent. Even without the application of IFRS 5, its adjusted EBIT margin would have improved significantly to 4.0 percent (Q2 2024: 2.9 percent). Automotive’s earnings in the second quarter were therefore at the upper end of the outlook for the year (adjusted EBIT margin outlook for Automotive: 2.5 to 4.0 percent). It achieved this despite declining automotive markets in Europe and North America. The year-on-year improvement was due to the rigorous implementation of measures to reduce costs as well as sustained price adjustments. 

Order intake for the Automotive group sector amounted to €5.7 billion in the second quarter of 2025 and was therefore significantly higher than sales during the quarter. With a volume exceeding €3 billion, orders for satellite cameras, brake systems and electronic control units made a major contribution. 

Furthermore, Automotive has established a new unit to develop semiconductors for vehicle electronics, with the aim of further reducing its dependence on suppliers for its future requirements and bringing new technologies to market faster. The Advanced Electronics and Semiconductor Solutions unit will focus on the development of semiconductors, while production will be handled by partner Global Foundries. 

The company has also launched an updated, second-generation smart tachograph for trucks. The device automatically detects when a truck crosses a border and securely stores position data thanks to European satellite technology. This innovation helps authorities with conducting checks and fleet operators with planning. In doing so, it meets the requirements of the EU Mobility Package, which stipulates gradual retrofitting of the second-generation smart tachograph: by August 19, 2025, all commercial vehicles over 3.5 tons used in international transport must be equipped with a latest-generation device.

Tires: resilient despite changing conditions 

The Tires group sector recorded sales of €3.3 billion in the second quarter (Q2 2024: €3.4 billion, 
-2.0 percent). It achieved a double-digit adjusted EBIT margin and was only slightly below the previous year’s level for the first half of the year. In the second quarter, its adjusted EBIT margin was 12.0 percent (Q2 2024: 14.7 percent). The main reasons for the year-on-year decline were US tariff increases, exchange-rate effects and positive catch-up effects in the second quarter of last year. 

Tires from Continental are repeatedly recognized for their high quality. In June 2025, Continental’s tires were voted “Quality Winner 2025” following a survey of around 45,000 consumers in Germany conducted by the German Institute for Service Quality (DISQ) in collaboration with news channel n-tv. Furthermore, Continental tires took first place 10 times and second place four times in independent comparison tests in Europe. The SportContact 7 was voted the winner in seven out of eight tests, while the UltraContact NXT achieved top marks for safety and sustainability. The PremiumContact 7 also scored highly in the current season, with British magazine Tyre Reviews declaring it the winner of its summer tire test.

This is also why Continental has a strong position in the market for ultra-high-performance (UHP) tires. UHP tires are technologically sophisticated, available in sizes from 18 inches and designed for safe and dynamic driving at high speeds. Between 2019 and 2024, Continental increased sales of these tires in the passenger car and light truck segment by around 15 percentage points worldwide. Over the same period, the share of sales of UHP tires for all Continental brands rose from 38 to 52 percent, and to 60 percent for the core Continental brand. Five years ago, this figure sat at 46 percent.

ContiTech: increase in adjusted EBIT margin compared with the start of the year 

The ContiTech group sector achieved sales of €1.6 billion in the second quarter of 2025 (Q2 2024: €1.6 billion, -5.2 percent). Its adjusted EBIT margin was 5.8 percent (Q2 2024: 7.1 percent), higher than in the first quarter of the year (Q1 2025: 5.4 percent). Earnings improved compared with the start of the year, especially due to higher industrial demand for ContiTech products and stricter cost discipline. The market environment remains gloomy, although there are signs of improvement in Europe as well as North and South America. Exchange rates are also affecting earnings.

Despite the challenging conditions, ContiTech continues to focus on innovation and future-oriented solutions. For example, it introduced new premium cooling hoses for data centers in the past quarter, which ensure stable temperatures for servers and help save energy, prevent malfunctions and extend equipment life. The hoses are extremely heat-resistant and meet strict fire safety standards. They are designed for modern cooling methods, such as direct-to-chip single-phase cooling, and help to reduce energy costs and carbon emissions in data centers.

The biggest battery on Australia’s energy grid is now on standby as a shock absorber to prevent blackouts in New South Wales.

The Waratah Super Battery will also allow NSW to use and transmit more energy, applying further downward pressure on electricity prices, experts say.

The battery, built on the site of the former Munmorah coal-fired power station on the Central Coast, has added 350MW of battery capacity to the energy grid since plugging in last September.

Waratah’s backstop system was brought online on Friday, making it the largest energy system integrity protection scheme (SIPS) in the country.

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The NSW energy minister, Penny Sharpe, said the battery was a crucial addition to state infrastructure.

“As it comes online, it will help power our homes and businesses while stabilising the grid to avoid blackouts,” she said.

In the event of blackout risks or power surges from bushfires, lightning strikes or other disruptions, the battery would activate as a shock absorber and steady the state’s energy supply, Ahmad Ebadi, a senior project manager at Transgrid, said.

“[The battery system] monitors 36 transmission lines in real time across NSW, detects overloading and responds in seconds … to increase generation,” he said.

More power could be transmitted and used across NSW once the battery’s full capacity of 850MW comes online; that is expected by the end of 2025.

Operating at full capacity, the battery would ease the urgency of building more energy transmission, said Dylan McConnell, an energy systems researcher at UNSW.

“By increasing the utilisation of your existing transmission network, you can actually reduce the need to build more transmission in the future,” he said.

“Ideally, it [means] lower electricity prices in the long run.”

An agreement with the NSW government will mean the battery reserves 700MW of its capacity for the system-protecting service during the day in summer. Waratah can store and discharge energy like other big battery projects.

The project was one of 12 battery systems to enter the national energy market in the year to June – more than doubling grid-scale battery discharge, the Australian Energy Market Operator (Aemo) reported in July.

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Investment in big batteries has accelerated in 2025. More projects are under construction, including one at Eraring, the site of the nation’s biggest coal-fired power station, and another at former coal plant Liddell.

The NSW government in 2024 extended Eraring’s operations to 2027 after Aemo in 2024 warned its retirement would increase blackout risks. More coal-fired power stations are scheduled to retire in coming years.

Anna Freeman, acting chief policy and impact officer at the Clean Energy Council, said the Waratah battery would help reduce the state’s reliance on coal.

“[It] is capable of holding as much energy as half an Eraring coal-fired power station and plays a pivotal role in ensuring that NSW can push ahead with confidence to a future powered by renewables,” she said.

Tim Buckley, the director of Climate Energy Finance, said the battery’s delivery could help bring energy prices down by supporting more green energy projects to completion.

“It will [help] more wind and solar and firming capacity into the grid, all of which means we will see electricity prices stabilise and then progressively, hopefully come down over time,” he said.