Category: 4. Technology

Casio’s $120 CRW001-1 (AKA the Ring Watch) is back in stock on Casio’s website for the first time since it launched — then swiftly sold out — in December. The Ring Watch was released to commemorate the 50th anniversary of its original digital watch. While it may look like a novelty, the fully-functional watch impressed The Verge’s Victoria Song as both a fashion statement and a practical gadget. The silver ring has a sub-inch screen and comes in one ring size: 10.5. However, Casio includes 16 and 19 millimeter spacers to accommodate smaller fingers.

The Ring Watch’s LCD screen can display six digits, and be set to standard or military time. The three buttons around its face can start a stopwatch, display the date, or show the time in a different timezone. An alarm function will flash in the corner of its screen when the counter is complete.

Kipu Quantum and IonQ have published a landmark achievement in quantum computing, announcing the successful solution of the most complex known protein folding problem ever done on quantum hardware. This collaboration highlights the powerful synergy between Kipu Quantum’s advanced algorithmic approaches and IonQ’s cutting-edge quantum systems.

A new benchmark in protein folding

In their latest study, the two companies tackled a 3D protein folding problem involving up to 12 amino acids – the largest of its kind to be executed on quantum hardware. This study marks a critical moment in leveraging quantum technologies for applications in drug discovery and computational biology.

The success of this study showcases the increasing capability of near-term quantum computing to address real-world scientific challenges.

Record performance across problem types

The collaboration also achieved optimal solutions in two other highly complex problem classes. The first involved all-to-all connected spin-glass problems formulated as QUBOs (Quadratic Unconstrained Binary Optimisation) a  challenging class of problems commonly used to  benchmark quantum algorithms and hardware. The second involved MAX-4-SAT, a Boolean satisfiability problem expressed as a HUBO (Higher-Order Unconstrained Binary Optimisation), which was solved using up to 36 qubits – the basic units of quantum information.

For those outside the computing field, this means the team successfully used quantum hardware to solve notoriously difficult mathematical problems – the kind that model real-world challenges in areas like logistics, drug discovery and AI. It’s a sign that quantum systems are becoming powerful enough to take on practical, high-value tasks that classical computers struggle with.

All computational instances were run on IonQ’s Forte-generation quantum systems using Kipu Quantum’s proprietary BF-DCQO (Bias-Field Digitised Counterdiabatic Quantum Optimisation) algorithm.

Innovation through algorithm and architecture

Kipu’s BF-DCQO algorithm stands out for being non-variational and iterative, allowing it to deliver high-accuracy results while using fewer quantum operations with each iteration. This approach is particularly suited to problems like protein folding, which require managing complex, long-range interactions.

“Connectivity between qubits in quantum computing impacts efficiency and accuracy. Having all-to-all connectivity means faster time to solution, with higher quality results, and is a unique characteristic of trapped-ion systems. Combining that with Kipu’s unique quantum algorithms results in unparalleled performance with minimal resources, a sine qua non path to quantum advantage with IonQ’s next-generation system,” said Professor Enrique Solano, Co-CEO and Co-Founder of Kipu Quantum. “This collaboration is not only breaking performance records but is also positioning us to actively pursue quantum advantage using trapped-ion technologies with IonQ for a wide class of industry use cases.”

Demonstrating the full power of the stack

IonQ emphasised the role of its full hardware-software stack in achieving these breakthroughs.

“Our collaboration with Kipu Quantum has delivered breakthroughs in both speed and quality that sets a new standard for what’s possible in quantum computing today,” said Ariel Braunstein, SVP of Product at IonQ. “This collaboration demonstrates the value of every part of IonQ’s quantum computing stack – from the quality of our qubits and how they are connected, to our compiler and operating system to how error mitigation techniques are applied. Kipu’s capabilities complement IonQ’s cutting-edge systems perfectly and this collaboration is only the first step in our mutual pursuit of near-term commercial value for customers across multiple industries.”

Looking ahead: scaling up to real-world impact

Building on this success, IonQ and Kipu Quantum plan to extend their partnership by exploring even larger-scale problems using IonQ’s upcoming 64-qubit and 256-qubit systems. These next-generation chips will tackle industrially relevant challenges in areas such as drug discovery, logistics optimisation, and advanced materials design.

By aligning new algorithms with robust hardware, the collaboration between Kipu Quantum and IonQ is laying the groundwork for realising quantum advantage across a broad range of real-world applications – and bringing the commercial promise of quantum computing closer to being a reality.

Background

Sepsis, characterized by life-threatening organ dysfunction due to a dysregulated host response to infection,¹ is responsible for approximately 20% of global deaths prior to the COVID-19 pandemic.² Numerous randomized controlled trials have been conducted to improve the outcome,^3–6 however, current treatment options are limited to antibiotics and organ support therapy. The reasons are multifactorial, including diverse pathogens, genetic backgrounds, ages, sexes, environments, and comorbidities, indicating sepsis is a highly heterogeneous clinical syndrome with distinct phenotypes.^7–9 The individuals with cancer have a sepsis risk around tenfold higher than that of the general population.¹⁰ It is well known that cancer and therapy for cancer (eg, chemotherapy, radiation, surgery, etc) increase the risk of sepsis.^11,12 Around 20% of sepsis hospitalizations were estimated to be linked with cancer.¹³ In-hospital mortality was estimated to 1.5-fold higher (about 27.9%) in sepsis with cancer versus without cancer admissions.¹³

Previous studies have revealed that sepsis, with or without cancer, exhibits similar overall organ dysfunction, although there are differences in mortality. Patients of sepsis with cancer are more prone to hematological system dysfunction but are less likely to experience pulmonary or renal dysfunction.¹⁴ The impact of cancer types on sepsis risk varies significantly. Patients with hematologic malignancies exhibit substantially higher sepsis incidence and mortality than solid tumor patients, primarily due to more severe immune impairment (particularly higher rates of neutropenia).¹⁰ Although solid tumors generally confer lower risk, certain types (eg, lung cancer) are associated with higher sepsis-related mortality.¹³

Sepsis-induced immunosuppression is characterized by monocyte dysfunction, reduced dendritic cell (DC) numbers, and impaired DC activity.⁶ Cancer patients inherently exhibit an immunosuppressive state, marked by lymphopenia and increased regulatory T cells and B cells, which sepsis further exacerbates.¹⁵ In sepsis with non-cancer, early pro-inflammatory cytokine storms transition to anti-inflammatory cytokine, reflecting immune paralysis. In contrast, sepsis with cancer occurs against a backdrop of chronic low-grade inflammation, leading to higher baseline anti-inflammatory cytokine, increased G-CSF, and more profound immunosuppression, resulting in dysregulated inflammatory responses compared to sepsis alone.

Both sepsis and cancer have profound effects on myeloid cells, including neutrophils and monocytes, which are key components in defense against infection and/or cancer.^15,16 Neutrophils, the predominant leukocytes in peripheral blood, are the first recruited to infection sites, where they perform pathogen phagocytosis and clearance.¹⁵ Monocytes exhibit plasticity, differentiating into macrophages or dendritic cells, and modulate inflammatory processes through cytokine and chemokine secretion.¹⁶ At infection sites, these cells interact via cytokine networks, synergistically contributing to pathogen elimination, inflammation regulation, and tissue repair. In the previous studies, it was discovered that tumor-associated neutrophils exert dual functions: promote tumor progression through angiogenesis, extracellular matrix remodeling, metastasis and immunosuppression or exert anti-tumor efforts by direct killing of tumor cells.^17,18 Additionally, monocytes can engage with T cells and natural killer cells, impacting tumor progression by producing chemokines.^19–21 The reduction of HLA-DR expression was a key characteristic of monocytes in sepsis, and the responsiveness of monocytes to lipopolysaccharide (LPS) was severely diminished.^22,23 Under inflammatory conditions, immature cells of granulocytic and monocytic lineages can differentiate into myeloid-derived suppressor cells (MDSCs), the presence of which has been correlated with poor prognosis in multiple tumor types.^24–27 The presence of cancer complicates the clinical situation of sepsis and profoundly affects the immune response and outcomes in septic patients.

Considering the high in-hospital mortality rates and similar organ dysfunction in sepsis with cancer, whether immune dysfunction of the tumor-associated neutrophils and monocytes may contribute to clinical outcomes, which cannot be overlooked. In this pilot study, we attempted to investigate alteration of the subsets and immune functions of neutrophils and monocytes between sepsis with non-cancer (SNC) and with cancer (SC).

Materials and Methods

Study Design

In this study, thirty septic patients were recruited from the ICU of Beijing Ditan Hospital, Capital Medical University and Beijing Shijitan Hospital, Capital Medical University between July 2023 and December 2023. Ten age and sex matched healthy controls (HC) were recruited as controls at the Health Examination Center of Beijing Shijitan Hospital, Capital Medical University. Depending on whether they had solid cancer in diagnoses of ICU admission, septic patients were divided into the SNC (n = 19) and the SC (n = 11) (Figure 1). Patients were tracked until January 2024 to record the 28-day survival, infectious events, and the development of organ failure.

Figure 1 Flowchart of patients selection.

Inclusion and Exclusion Criteria

Diagnostic criteria for sepsis were:¹ 1) between the ages of 18 and 93; 2) Sequential Organ Failure Assessment (SOFA) score increased by 2 or equal to 2 when there is confirmed or suspected infection. Quick SOFA (qSOFA) uses 3 variables to predict patients at high risk of sepsis: a Glasgow Coma Score <15, a respiratory rate ≥22 breaths/min and a systolic blood pressure ≤100 mmHg; 3) The diagnostic criteria for septic shock were that vasopressor drug therapy is needed to maintain a mean arterial pressure >65 mmHg or a serum lactate level >2 mmol/L. This study was approved by the Committee of Ethics at Beijing Ditan Hospital and Beijing Shijitan Hospital, Capital Medical University. Blood samples and clinical data of patients were collected after obtaining informed consent of the patients and their families.

The following patients were excluded from this study: 1) patients with incomplete clinical data; 2) death within 24h; 3) diagnosed with COVID-19 upon admission; 4) patients with human immunodeficiency virus (HIV); 5) patients with successful resuscitation after sudden cardiac arrest; 6) pregnant women.

Neutrophil Isolation

We collected peripheral blood from HC and sepsis patients in tubes with EDTA. Using red blood cell (RBC) lysing solutions to isolate neutrophils and surface marker staining (CD16/CD10 with appropriate isotype controls).

Isolation of Peripheral Blood Mononuclear Cells (PBMCs)

We collected 8mL of peripheral blood from HC and sepsis patients in Vacutainer tubes with Ethylene Diamine Tetra acetic Acid (EDTA) and processed for PBMCs isolation. The blood was diluted 1:1 with phosphate buffered saline (PBS), layered onto Ficoll-Paque (GE Healthcare, Marlborough, MA, USA), and processed according to the manufacturer’s instructions.

Flow Cytometric Analysis

Peripheral blood or freshly isolated PBMCs were incubated with directly conjugated fluorescent antibodies for 30 min at 4°C. Antibodies used included anti-human CD3-Percp-Cy5.5, CD15-Percp-Cy5.5, CD19-Percp-Cy5.5, CD45-FITC, CXCR4-FITC, CX3CR1-FITC, CD101-PE-Cy7, CCR2-PE-Cy7, CD10-PE, CD10-APC-Cy7, CD3-Alexa Fluor 700, CD45-Alexa Fluor 700, CD14-APC, CD177-APC, CD14-BV605, CD62L-BV605, CD16-BV510, HLA-DR-BV421, CD62L-BV421 (BioLegend, San Diego, CA, USA), TNF-α-FITC, IL-6-PE-Cy7 (eBioscience, San Diego, CA, USA), TIM3-APC-Cy7 (BD Bioscience, San Diego, CA, USA). The cells were washed before BD FACSCanto flow cytometry (BD Bioscience, San Diego, CA, USA) analysis.^28,29 The gating strategy applied is shown in Figure S1. FlowJo software (Tree Star, Ashland, OR, USA) was used to analyze the flow cytometry data. GraphPad Prism 9 (GraphPad Software, USA) and R program were used to perform the graphing and statistical analysis.

Multicolor Flow Cytometry Dimensionality Reduction and Clustering Analysis

Using FlowJo 10.8.1 DownSample plugin, mononuclear cells were subsampled at 3000 cells/sample. The subsampled data were then merged into a single file using Conculation program. The merged file was subsequently analyzed using UMAP dimensionality reduction and FlowSOM clustering for data visualization. The FlowSOM clustering analysis strategy included data preprocessing, parameter optimization, clustering (using markers: CD14, CD16, HLA-DR, TIM3, CD62L, PD-L1, CCR2, and CX3CR1), as well as result evaluation and application.

Phagocytosis Assay

Latex Beads (Carboxylate-modified, Yellow-green, Sigma, USA) were added to peripheral blood and incubated in a carbon dioxide incubator at 37°C for 3 hours; placed on ice for 10 minutes to stop phagocytosis and then washed twice with PBS buffer. The corresponding cell surface fluorescent antibody combination was added and allowed to incubate at 4°C for 15 minutes in the dark. The ratio of beads (+) cells in neutrophils and monocytes were detected and analyzed using a flow cytometer to determine the phagocytic capacities.^29,30

In vitro Stimulation and Intracellular Staining

For block the secretion of cytokines, Golgiplug (BD Bioscience, USA) was added to the PBMCs suspension. PBMCs were cultured in RPMI-1640 media (GIBGO, USA) containing 10% fetal bovine serum (FBS), with or without LPS (100 ng/mL, STEMCELL Technologies, Canada) for 3 hours. Cell stained with surface and intracellular antibodies, and the corresponding isotype controls. Data acquisition was performed on BD FACSCanto flow cytometry (BD Bioscience, USA), and data were analyzed with FlowJo software (Tree Star, USA).

Measures of Blinding

This study employed a double-blind design. During sample processing, researchers were unaware of participants’ group assignments, with samples labeled by anonymous codes known only to an independent third party. Throughout data analysis, statisticians remained blinded to group allocation to minimize subjective bias.

Statistical Analysis

Data were expressed as mean ± standard deviation (SD) or median and interquartile range (IQR, 25th to 75th percentile). Statistical analyses were performed using GraphPad Prism 9 (GraphPad Software, USA) and the R program (https://cran.r-project.org/). For comparisons between two unpaired groups, the Wilcoxon test was utilized. Paired data were analyzed using the paired sample t-test. When comparing more than two groups, one-way ANOVA was applied. Data that were not normally distributed were presented as median and IQR. The Mann–Whitney U-test was used for comparisons between two unpaired groups, while the Wilcoxon signed-rank test was used for paired data. Descriptive statistics and Spearman’s rank correlation coefficients were employed to assess correlations. A P-value of less than 0.05 was considered to indicate statistical significance. To control for multiple comparisons, P-values were adjusted using the Benjamini–Hochberg false discovery rate (FDR) correction method (Supplemental Table 1).

Results

Characteristics of Patients

To study the immune profile in sepsis with or without cancer, we enrolled thirty septic patients between July and December of 2023. Demographic information and characteristics of these patients were shown in Table 1 and septic patients have a median age of 72 years old (IQR: 66–81) years, with men accounting for 51.8%. Based on evidence of cancer in diagnoses of ICU admission, we classified septic patients into two groups: sepsis with non-cancer group (SNC) (n = 19) and sepsis with cancer group (SC) (n = 11) (Figure 1). There was no significant difference in comorbidity, initial SOFA score and vital signs between two groups (Table 1). By comparing the internal environment of patients on the first day of diagnosis, it was observed that the potential of hydrogen (pH) in the SC group was significantly higher than that in the SNC group (7.45 ± 0.04 vs 7.38 ± 0.07, P = 0.01). And the base excess (BE) in the SC group was significantly higher than that in the SNC group (1.1 vs −3.4 mmol/L, P = 0.02). In addition, the platelet (PLT) count in the SC group was significantly higher than the SNC group (222.9 ± 64.7 vs 159.6 ± 72.410⁹/L, P = 0.02). The level of the C-reactive protein (CRP) in the SC group was higher than that of the SNC group (155.2 vs 45.8 mg/L, P = 0.01). Despite no statistical differences were observed in liver, renal and coagulation function between SC and SNC group. In terms of mortality, the 28-day mortality for all septic patients was 30%, and the 28-day mortality of the SC group was significantly higher than that of the SNC group (54.6% vs 14.3%, P = 0.03). These results suggest that the SC group exhibit significant internal environment disorders, including elevated pH, BE, PLT, and CRP levels compared to the SNC group. Additionally, the higher 28-day mortality in the SC group highlights the poorer prognosis.

Table 1 Basic Clinical Characteristics of Patients

Expansion of Activated Band Neutrophil in SC Group

Compared to HC, septic patients exhibited increased proportion of neutrophils of nucleated cell (P < 0.001), neutrophil-to-lymphocyte ratio (NLR) (P < 0.001), and decreased proportion of lymphocyte of nucleated cell (P < 0.001) irrespective of whether SC or SNC (Figure S2A and S2B). First, to explore the effect of sepsis on the neutrophil subsets, we applied the multi-color flow cytometry to investigate the ability of phagocytosis among HC (n = 5), SNC (n = 11) and SC (n = 9). According to our previous study,³¹ circulating neutrophils were divided into four subsets: myelocytes, metamyelocytes, band neutrophils, and segmented neutrophils based on the different expression levels of CD10 and CD16 (Figure S3A). Compared with the HC, SNC and SC displayed significantly decreased percentages of circulating mature neutrophils (segmented neutrophils; P < 0.001, P < 0.001), significantly increase in the proportions of immature neutrophils, including myelocytes (P = 0.017, P = 0.021), metamyelocytes (P < 0.001, P = 0.005), and band neutrophils (P < 0.001, P < 0.001) (Figure 2A). However, these differences were not observed between the SNC and SC. Additionally, we explored the phagocytic function of neutrophils subsets. We found that the phagocytic function of myelocytes were lower than other neutrophil subsets (Figures 2B, S3B and S3C). Compared to the SNC, the phagocytic function of band neutrophils in the SC was also impaired (P = 0.031) (Figure 2B).

Figure 2 Characterization of the proportion, phagocytic capacity, activation and maturation of neutrophil subsets in healthy control (HC), sepsis with non-cancer (SNC) and sepsis with cancer (SC). (A) Comparison of the proportion of neutrophil subsets among healthy control (HC, n = 10), SNC (n = 19) and SC (n = 11). (B) Analysis of the myelocytes and band neutrophils phagocytic capacity by stimulating peripheral blood from HC (n = 4), SNC (n = 18), and SC (n = 10) with LPS (100 ng/mL) for 3 hours in vitro. (C and D) The proportions of CD177+ in myelocytes and band neutrophils (C), and CD101+ in band and segmented neutrophils (D) among HC (n = 7), SNC (n = 19) and SC (n = 11) were analyzed by flow cytometry. Statistical evaluation using Wilcoxon signed-rank test. P-values were adjusted using the Benjamini-Hochberg false discovery rate (FDR) correction method.

Further, the expression of a mature marker CD101, activation marker CD177, CD62L, chemokine receptor CXCR2 in four neutrophil subsets were further analyzed. In HC group, segmented neutrophils exhibited expression of CXCR2, more that 95% segmented neutrophils were positive for CD101 and CD62L, and approximately 83% segmented neutrophils were positive for CD177 (Figures 2D, S4A–4C). The expression of CXCR2 of neutrophils subsets was comparable among HC, SNC and SC group (Figure S4D). Compared to HC, the proportion of CD101⁺ band and segmented neutrophils were significantly decreased in SNC and SC group (band: P = 0.033, P = 0.011; segmented: P = 0.038, P = 0.009) (Figure 2D); the proportion of CD177⁺ in myelocytes was significantly increased in SC and SNC group (P = 0.032, P = 0.030) (Figure 2C). Compared to SNC group, the proportion of CD177⁺ in band neutrophils was significantly increased in SC group (P = 0.031) (Figure 2C). Thus, sepsis induces release of immature neutrophils (myelocytes, metamyelocytes, band neutrophils) into the peripheral blood and band neutrophils in SC group display a more activated phenotype.

Monocytes in Septic Patients Exhibit Hypophagocytosis and Impaired Cytokine Secretion

In addition, compared to HC, patients with sepsis exhibited decreased proportion of lymphocyte-to-monocyte ratio (LMR) (P < 0.001, P < 0.001) (Figure S2B). We applied the flow cytometry to investigate the ability of phagocytosis, and cytokine-secreting among HC (n = 6), SNC (n = 12) and SC (n = 10). Compared to HC, the phagocytic capacity of monocytes in septic patients was significant reduced (P = 0.041, P < 0.001). Further, compared with SNC group, SC group exhibited a more significant decrease in monocyte phagocytosis (P = 0.037) (Figures 3A and S5A). We further explored the effect of sepsis on the intracellular TNF-α and IL-6 secretion capacity of monocytes (Figures 3B, S5B and S5C). Compared with HC, the TNF-α secretion capacity of monocytes from SNC group was significantly decreased (P = 0.044) (Figure 3B). Given the above results, monocytes exhibit impaired phagocytosis and pro-inflammatory cytokine secretion capacity in the SNC and SC group, with a more pronounced phagocytosis impairment observed in the SC group.

Figure 3 Characterization of the function of monocyte and the proportion of monocyte subsets in HC, SNC and SC. (A) Comparison of the monocyte phagocytic function by stimulating with LPS (100 ng/mL) for 3 hours in vitro from HC (n=6), SNC (n=12), and SC (n=10). (B) Intracellular staining for the percentage of TNF-α+ monocytes by stimulating with LPS (100 ng/mL) for 3 hours in vitro from HC (n=6), SNC (n=10), and SC (n=9). (C) Flow cytometry data in a UMAP plot with FlowSOM clusters with cell identities established based on the expression displayed markers (CD14, CD16, HLA-DR, TIM3, CD62L, CX3CR1 and CCR2); 71070 live cells from HC (n=9), SNC (n=16), and SC (n=11) are shown after concatenation. (D) Boxplots of cluster 5 classical monocyte and cluster 12 non-classical monocyte subsets from HC, SNC, and SC. Statistical evaluation using Wilcoxon signed-rank test. P-values were adjusted using the Benjamini-Hochberg false discovery rate (FDR) correction method.

Emergence of HLA-DR^lowCCR2^low Classical Monocyte in SC Group

To explore the effect of sepsis on the monocyte subsets, we used the UMAP and FlowSOM to analyze multi-color FCM data of monocyte from HC (n = 9), SNC (n = 16) and SC (n = 11) (Figure 3C). Unsupervised clustering analysis of all monocytes in all samples revealed 12 major clusters of CD14^lowCD16⁻ immature monocytes (Mo0, cluster 1 and 2), CD14^highCD16⁻ classical monocytes (Mo1, cluster 3, 4, 5, 6 and 7), CD14^highCD16⁺ intermediate monocytes (Mo2, cluster 8, 9 and 10), and CD14^lowCD16⁺ non-classical monocytes (Mo3, cluster 11 and 12) (Figures 3C and S6A). ^32,33 The frequence of Mo0 (clusters 1 and 2) among monocytes was relatively low in HC, SNC and SC (Figure S6B). Compared with HC, the proportion of cluster 5 Mo1 (HLA-DR^lowCCR2^lowCX3CR1^low) (P = 0.033, P = 0.033) in SNC and SC was increased. Compared SNC, the percentage of cluster 5 Mo1 was significantly higher in SC (P = 0.045) (Figure 3D). The proportion of cluster 11 Mo3 (HLA-DR^highCCR2^medCX3CR1^high) in SC was significantly lower than that in HC (P = 0.017) (Figure S6B). The proportion of cluster 12 Mo3 (HLA-DR^lowCCR2^lowCX3CR1^low) in SNC and SC (P = 0.036, P = 0.002) was significantly higher than that in HC, and the change was more significant in SC (P = 0.032) (Figure 3D). No significant differences in other monocyte subsets were observed among the HC, SNC, and SC (Figure S6B). These results indicated that the emergence of HLA-DR^lowCCR2^low classical monocyte in SC group with defective antigen presentation and chemotaxis.

The Elevation of HLA-DR^lowCCR2^low Mo1 and CD177⁺ Myelocytes Might Indicative of Poor Outcomes

In our study, the 28-day mortality in sepsis with cancer was significantly higher than in sepsis with non-cancer (Figure 4A). To investigate the impact of myeloid cell subsets on the prognosis of the two patient groups, we conducted a subgroup analysis. In the forest plot of the subgroup analysis, we observed that no significant differences of survival outcomes were noted between SNC and SC (Figure S7A). To clarify whether myeloid cell subsets may predict patients’ prognosis, the patients were divided into the survivor and the non-survivor group based on the 28-day mortality. We observed that the proportion and number of HLA-DR^lowCCR2^low classical monocytes in the non-survivors were significantly higher than that in the survivor group (P = 0.032, P = 0.041), with an area under the receiver operating characteristic (ROC) curve of 0.722 and 0.782 (Figure 4B and 4C). Afterwards, the proportion and number of CD177⁺ myelocytes and in the non-survivors were significantly higher than that in the survivors (P = 0.034, P = 0.035), with an area under the ROC curve of 0.728 and 0.704 (Figure 4D and E). These results further highlighted that the elevation of percentage and numbers of HLA-DR^lowCCR2^low Mo1 and CD177⁺ myelocytes maybe indicative of poor outcomes.

Figure 4 Cluster 5 classical monocytes and CD177+ myelocytes may indicative of poor outcomes. (A) Kaplan-Meier survival estimates at 28-days are provided for the SNC (n = 19) and SC (n = 11). (B and D) Boxplots of comparison between survivors (n = 21) and non-survivors (n = 9) in the proportion and cell counts of cluster 5 Mo1 (B) and CD177+ myelocytes (D). Statistical evaluation using Wilcoxon signed-rank test. (C and E) Predicted mortality at cluster 5 Mo1 (C) and CD177+ myelocytes (E). Curved red lines represent 95% confidence interval for predicted mortality at cluster 5 Mo1 and CD177+ myelocytes.

Correlation between the Myeloid Subsets with Clinical Parameters

We further investigated the correlations between the percentage and numbers of myeloid subsets with thirty one critical clinical parameters, including blood gas test, blood routine test, biochemical test, as well as coagulation function test. Our findings indicated that higher proportion of HLA-DR^lowCCR2^low classical monocytes was positively correlated with pH and BE (P < 0.001, P = 0.008) (Figure 5A). We observed that the proportion of CD177⁺ myelocytes positively correlated with activated partial thromboplastin time (APTT) (P = 0.005) (Figure 5B). These results revealed that HLA-DR^lowCCR2^low classical monocyte and CD177⁺ myelocytes exhibit significant correlations with internal environment and coagulation markers.

Figure 5 Correlation between cluster 5 classical monocytes and CD177+ myelocytes with clinical laboratory indicators. (A) Positive correlation between cluster 5 Mo1 subsets with pH and BE. (B) Positive correlation between CD177+ myelocyte with APTT. Spearman’s rank correlation coefficients were employed to assess correlations.

Discussion

Patients suffering from both sepsis and cancer exhibit exacerbated physiological abnormalities and a markedly elevated 28-day mortality rate compared to septic patients without cancer. Our study provides a comprehensive analysis of the immunological landscape in septic patients, with a particular focus on those with concurrently diagnosed with cancer. In the sepsis cohort, significant alterations in the function and phenotype of CD177⁺activated band neutrophil and HLA-DR^lowCCR2^low classical monocyte were observed, which may indicate a dysregulation of the immune response. Furthermore, the HLA-DR^lowCCR2^low classical monocyte and CD177⁺ myelocytes correlated with internal environmental disorders and coagulation markers in sepsis patients, potentially serving as crucial biomarkers for diagnostic and prognostic evaluations.

In our study, we observed an overall mortality rate of 30% among the septic patient. The findings align with the previous studies, which have consistently demonstrated that the mortality rate among septic patients with cancer is markedly higher at severe infection and critical organ damage compared to those without cancer.^33,34 The mortality rate for SNC group was 15.3%, whereas for SC group, the rate was significantly higher at 54.6%. Our findings also reveal significant differences in blood pH levels and BE between the SNC and SC groups, which may indicate disturbances in metabolic and acid–base balance in SC patients. More studies have recognized that pH as a factor in cancer initiation and progression.^14,35,36 Cancer is an intriguing case in terms of the altered the intracellular pH (pH_i), as it has been well established that the pH_i of cancer tissue cells becomes basic (at 7.4 or 7.5).³⁷ The elevated pH/base excess in sepsis with cancer represents an underexplored metabolic phenomenon requiring mechanistic elucidation. Potential etiologies include: paraneoplastic metabolic alkalosis (such as ectopic hormone secretion and altered lactate metabolism); compensation for cancer-related chronic respiratory alkalosis; or chemotherapy-induced renal tubular dysfunction.³⁷ The characteristic hypochloremia of tumor-associated alkalosis contrasts with sepsis-related hyperchloremic acidosis, suggesting pathophysiological interplay. Furthermore, SC patients exhibited higher CRP levels, which could be associated with the inflammatory status of cancer patients. Consistent with previous studies, there is no significant difference in laboratory examination of organs function among septic patients, regardless of the presence of coexisting cancer.^38,39

Our study confirmed the previous findings that sepsis is characterized by increased neutrophil proportion and NLR, along with reduced LMR, indicative of systemic inflammation and immune imbalance.^4,40,41 Both SC and SNC groups exhibited a decrease in mature neutrophils (segmented neutrophil) and increase in immature neutrophil subsets (myelocytes, metamyelocytes, band neutrophils), indicating a shift in the neutrophil developmental trajectory in response to the overwhelming inflammation.^17,42 The decreased expression of CD101 on band and segmented neutrophils in SC and SNC groups suggests impairment of neutrophil maturation.^43,44 Meanwhile, our study has also observed the impaired phagocytic function of myelocytes and band neutrophils, especially in the SC group. The increased proportion of CD177⁺ cells in myelocytes and band neutrophils in the SC group indicates an activated state, which may be a response to the underlying cancer or the sepsis itself.^43,45 More importantly, we found that the elevation of CD177⁺ myelocytes might be indicative of poor prognosis. Previous studies have found that the proportion of CD123⁺ immature neutrophils correlated with clinical severity in sepsis.⁴⁶ Although the activated myelocytes increased, their phagocytic function was significantly impaired. Therefore, the accumulation of the proportion and numbers of activated myelocytes did not enhance the pathogen clearance capability and further lead to a worse prognosis. This finding points to a potential mechanism by which sepsis with cancer impairs the innate immune response, leaving patients more susceptible to infections and contributing to the high mortality rates.^4,10 Previous studies have indicated that in sepsis, the counts of neutrophils may be associated with alterations in coagulation function. APTT, serving as a marker of coagulation function, may exhibit relation to the activity of neutrophils.⁴⁷ Furthermore, APTT is not merely an indicator of coagulation status but could also be a significant factor in evaluating the prognosis of sepsis patients.⁴⁸ Consistent with previous research, we also found that the negative correlation between CD177⁺ myelocytes and APTT suggested a link between neutrophil dysfunction and coagulation in sepsis.

Our study found that the significant reduction in monocyte phagocytosis and cytokine secretion capacity in septic patients, especially in SC patients, which was consistent with previous studies. The classical monocytes express the chemokine receptor CCR2, while non-classical monocytes express the chemokine receptor CX3CR1.^30,49,50 The emergence of HLA-DR^lowCCR2^low Mo1 in SC group is a novel finding that warrants attention. The aberrant expression of CCR2 and CX3CR1 on classical monocyte might disrupt the migratory capacity of monocytes, thereby affecting their respond to infection in the tissue.^49,51 The positive correlation between HLA-DR^lowCCR2^low Mo1 and pH, as well as BE, suggests a link between monocyte dysfunction and internal environment disorder in sepsis with cancer. Additional studies have found that HLA-DR^low classical monocytes as biomarkers to predicted poor outcomes of sepsis.^22,52,53 Similar to the previous studies, our results further revealed that the percentage and numbers of HLA-DR^lowCCR2^low Mo1 as a predictor for 28-day mortality. Due to the limited cell numbers, HLA-DR^lowCCR2^low Mo1 were not explored by cell sorting and RNA sequence. We will further investigate the functions of HLA-DR^lowCCR2^low Mo1 with single-cell sequencing in the future. The results underscore the complexity of monocyte dysfunction in the context of sepsis and cancer, potentially involving multiple mechanisms that merit further investigation. The identification and investigation of these biomarkers could aid in the early recognition of high-risk patients, thereby guiding timelier and more targeted therapeutic interventions.

The integration of biomarkers in clinical management of sepsis patients with malignancies holds significant prognostic and therapeutic implications. Systematic monitoring of HLA-DR^lowCCR2^low classical monocytes and CD177⁺ myeloid cells, combined with microenvironmental and coagulation markers (pH, BE, APTT), enables early risk stratification and dynamic assessment. These biomarkers reflect the severity of immune dysfunction, inflammatory status, and coagulopathy, facilitating timely therapeutic adjustments. Further optimization of anti-inflammatory and anticoagulant strategies can be achieved through biomarker-guided approaches. Future multicenter studies should validate these clinical utility of biomarkers and elucidate their molecular mechanisms to develop personalized therapies, ultimately improving survival and quality of life in this high-risk population.

However, this study has several limitations that warrant further refinement. First, the relatively limited sample size may significantly compromise statistical power, necessitating expanded cohort sizes in future studies to enhance result reliability. Second, substantial heterogeneity among cancer patients (including variations in pathological types, disease stages, treatment regimens, and immune status) could confound the interpretation of immune cell subset dynamics, underscoring the need for standardized stratified analyses in subsequent research. Currently, the findings remain predominantly descriptive, lacking mechanistic exploration of immune cell functional alterations; thus, integration of in vitro assays, animal models, and molecular techniques, such as single-cell sequencing and functional blockade experiments, is required for validation. Furthermore, the observational design precludes causal inference, highlighting the importance of future prospective cohort studies or immune cell-targeted interventional trials to evaluate the therapeutic potential of these cellular subsets.

Conclusions

In conclusion, our pilot study reveals the septic patients, particularly those patients with cancer, increased CD177⁺ activated band neutrophil and HLA-DR^lowCCR2^low classical monocyte, decreased phagocytic activity of immature neutrophil and monocyte. And we found that HLA-DR^lowCCR2^low classical monocyte and CD177⁺ myelocytes may serve as immunological predictors of poor prognosis. By identifying distinct monocyte and neutrophil subsets with potential prognostic significance, it advances our understanding of the immune profiles of sepsis with cancer. These findings are of great importance for improving outcomes in the high-risk populations.

Abbreviations

LPS, Lipopolysaccharide; MDSCs, Myeloid-derived suppressor cells; HC, Healthy control; SNC, Sepsis with non-cancer; SC, Sepsis with cancer; ICU, Intensive care unit; SOFA, Sequential Organ Failure Assessment; HIV, Human Immunodeficiency Virus; PBMCs, Peripheral Blood Mononuclear Cells; EDTA, Ethylene Diamine Tetra acetic Acid; PBS, Phosphate buffered saline; RBC, Red blood cell; FBS, Fetal bovine serum; UMAP, Uniform manifold approximation and projection; FlowSOM, Flow or mass cytometry analysis algorithm using a Self-Organizing Map; SD, Standard deviation; IQR, Interquartile range; FDR, False discovery rate; pH, Potential of Hydrogen; BE, Base excess; PLT, Platelet; CRP, C-reactive protein; NLR, Neutrophil-to-lymphocyte ratio; LMR, Lymphocyte-to-monocyte ratio; Mo0, immature monocytes; Mo1, classical monocytes; Mo2, intermediate monocytes; Mo3, non-classical monocytes; ROC, receiver operating characteristic; APTT, Activated Partial Thromboplastin Time.

Data Sharing Statement

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

Ethics Approval and Consent to Participate

Ethics committees or institutional review boards at Beijing Ditan Hospital, Capital Medical University and Beijing Shijitan Hospital, Capital Medical University approved the protocol and all amendments (NO.DTEC-KY2022-050-01 and I-22PJ091). All patients, or their legally authorized representatives, provided written informed consent. And our study complied with the Declaration of Helsinki.

Acknowledgments

We acknowledge all the physicians and nurses in the Department of Intensive Care Unit, Beijing Ditan Hospital, Capital Medical University and Beijing Shijitan Hospital, Capital Medical University, for their dedication to patient care and their support of our 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 was supported by the Beijing Clinical Key Specialty Construction Project (Intensive Care Medicine, Beijing Ditan Hospital), the National Natural Science Foundation of China (No. 82372163) the high-level public health talents (lingjunrencai-02-06 and xuekegugan-03-19).

Disclosure

The authors declare that they have no competing interests.

References

1. Singer M, Deutschman CS, Seymour CW, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016;315:801–810. doi:10.1001/jama.2016.0287

2. Rudd KE, Johnson SC, Agesa KM, et al. Global, regional, and national sepsis incidence and mortality, 1990-2017: analysis for the global burden of disease study. Lancet. 2020;395:200–211. doi:10.1016/S0140-6736(19)32989-7

3. Bode C, Weis S, Sauer A, Wendel-Garcia P, David S. Targeting the host response in sepsis: current approaches and future evidence. Crit Care. 2023;27:478. doi:10.1186/s13054-023-04762-6

4. Cao M, Wang G, Xie J. Immune dysregulation in sepsis: experiences, lessons and perspectives. Cell Death Discov. 2023;9:465. doi:10.1038/s41420-023-01766-7

5. Heming N, Azabou E, Cazaumayou X, et al. Sepsis in the critically ill patient: current and emerging management strategies. Expert Rev Anti Infect Ther. 2021;19:635–647. doi:10.1080/14787210.2021.1846522

6. Lelubre C, Vincent JL. Mechanisms and treatment of organ failure in sepsis. Nat Rev Nephrol. 2018;14:417–427. doi:10.1038/s41581-018-0005-7

7. Kwok AJ, Mentzer A, Knight JC. Host genetics and infectious disease: new tools, insights and translational opportunities. Nat Rev Genet. 2021;22:137–153. doi:10.1038/s41576-020-00297-6

8. Scicluna BP, van Vught LA, Zwinderman AH, et al. Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study. Lancet Respir Med. 2017;5:816–826. doi:10.1016/S2213-2600(17)30294-1

9. Antcliffe DB, Burnham KL, Al-Beidh F, et al. Transcriptomic signatures in sepsis and a differential response to steroids. from the VANISH randomized trial. Am J Respir Crit Care Med. 2019;199:980–986. doi:10.1164/rccm.201807-1419OC

10. Williams JC, Ford ML, Coopersmith CM. Cancer and sepsis. Clin Sci. 2023;137:881–893. doi:10.1042/CS20220713

11. Mirouse A, Vigneron C, Llitjos JF, et al. Sepsis and cancer: an interplay of friends and foes. Am J Respir Crit Care Med. 2020;202:1625–1635. doi:10.1164/rccm.202004-1116TR

12. Liu Z, Mahale P, Engels EA. Sepsis and risk of cancer among elderly adults in the United States. Clin Infect Dis. 2019;68:717–724. doi:10.1093/cid/ciy530

13. Hensley MK, Donnelly JP, Carlton EF, Prescott HC. Epidemiology and outcomes of cancer-related versus non-cancer-related sepsis hospitalizations. Crit Care Med. 2019;47:1310–1316. doi:10.1097/CCM.0000000000003896

14. Sahni V, Choudhury D, Ahmed Z. Chemotherapy-associated renal dysfunction. Nat Rev Nephrol. 2009;5:450–462. doi:10.1038/nrneph.2009.97

15. Mullard A. Addressing cancer’s grand challenges. Nat Rev Drug Discov. 2020;19:825–826. doi:10.1038/d41573-020-00202-0

16. de Visser KE, Joyce JA. The evolving tumor microenvironment: from cancer initiation to metastatic outgrowth. Cancer Cell. 2023;41:374–403. doi:10.1016/j.ccell.2023.02.016

17. Jaillon S, Ponzetta A, Di Mitri D, et al. Neutrophil diversity and plasticity in tumour progression and therapy. Nat Rev Cancer. 2020;20:485–503. doi:10.1038/s41568-020-0281-y

18. van Vlerken-Ysla L, Tyurina YY, Kagan VE, Gabrilovich DI. Functional states of myeloid cells in cancer. Cancer Cell. 2023;41:490–504. doi:10.1016/j.ccell.2023.02.009

19. Mulder WJM, Ochando J, Joosten LAB, et al. Therapeutic targeting of trained immunity. Nat Rev Drug Discov. 2019;18:553–566. doi:10.1038/s41573-019-0025-4

20. Guan X, Hu R, Choi Y, et al. Anti-TIGIT antibody improves PD-L1 blockade through myeloid and T(reg) cells. Nature. 2024;627:646–655. doi:10.1038/s41586-024-07121-9

21. Friedrich M, Hahn M, Michel J, et al. Dysfunctional dendritic cells limit antigen-specific T cell response in glioma. Neuro Oncol. 2023;25:263–276. doi:10.1093/neuonc/noac138

22. Yao RQ, Zhao PY, Li ZX, et al. Single-cell transcriptome profiling of sepsis identifies HLA-DR(low)S100A(high) monocytes with immunosuppressive function. Mil Med Res. 2023;10:27. doi:10.1186/s40779-023-00462-y

23. Leijte GP, Rimmele T, Kox M, et al. Monocytic HLA-DR expression kinetics in septic shock patients with different pathogens, sites of infection and adverse outcomes. Crit Care. 2020;24:110. doi:10.1186/s13054-020-2830-x

24. Kwak T, Wang F, Deng H, et al. Distinct populations of immune-suppressive macrophages differentiate from monocytic myeloid-derived suppressor cells in cancer. Cell Rep. 2020;33:108571. doi:10.1016/j.celrep.2020.108571

25. Gabrilovich DI. Myeloid-derived suppressor cells. Cancer Immunol Res. 2017;5:3–8. doi:10.1158/2326-6066.CIR-16-0297

26. Bronte V, Brandau S, Chen SH, et al. Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards. Nat Commun. 2016;7:12150. doi:10.1038/ncomms12150

27. Kumar V, Patel S, Tcyganov E, Gabrilovich DI. The nature of myeloid-derived suppressor cells in the tumor microenvironment. Trends Immunol. 2016;37:208–220. doi:10.1016/j.it.2016.01.004

28. Quintelier K, Couckuyt A, Emmaneel A, et al. Analyzing high-dimensional cytometry data using FlowSOM. Nat Protoc. 2021;16(8):3775–3801. doi:10.1038/s41596-021-00550-0

29. Lamb ER, Glomski IJ, Harper TA, et al. High-dimensional spectral flow cytometry of activation and phagocytosis by peripheral human polymorphonuclear leukocytes. J Leukoc Biol. 2025;117(4):qiaf025.

30. Dustin ML. Complement receptors in myeloid cell adhesion and phagocytosis. Microbiol Spectr. 2016;4:10.1128. doi:10.1128/microbiolspec.MCHD-0034-2016

31. Fan L, Han J, Xiao J, et al. The stage-specific impairment of granulopoiesis in people living with HIV/AIDS (PLWHA) with neutropenia. J Leukoc Biol. 2020;107:635–647. doi:10.1002/JLB.1A0120-414R

32. Cao Y, Fan Y, Li F, et al. Phenotypic and functional alterations of monocyte subsets with aging. Immun Ageing. 2022;19:63. doi:10.1186/s12979-022-00321-9

33. Cuenca JA, Manjappachar NK, Ramirez CM, et al. Outcomes and predictors of 28-day mortality in patients with solid tumors and septic shock defined by third international consensus definitions for sepsis and septic shock criteria. Chest. 2022;162:1063–1073. doi:10.1016/j.chest.2022.05.017

34. Nazer L, Lopez-Olivo MA, Cuenca JA, et al. All-cause mortality in cancer patients treated for sepsis in intensive care units: a systematic review and meta-analysis. Supp Care Cancer. 2022;30:10099–10109. doi:10.1007/s00520-022-07392-w

35. Swietach P, Boedtkjer E, Pedersen SF. How protons pave the way to aggressive cancers. Nat Rev Cancer. 2023;23:825–841. doi:10.1038/s41568-023-00628-9

36. Yan R, Zhang P, Shen S, et al. Carnosine regulation of intracellular pH homeostasis promotes lysosome-dependent tumor immunoevasion. Nat Immunol. 2024;25:483–495. doi:10.1038/s41590-023-01719-3

37. Zhou Y, Chang W, Lu X, et al. Acid-base homeostasis and implications to the phenotypic behaviors of cancer. Genomics Proteomics Bioinf. 2023;21:1133–1148. doi:10.1016/j.gpb.2022.06.003

38. Bou Chebl R, Safa R, Sabra M, et al. Sepsis in patients with haematological versus solid cancer: a retrospective cohort study. BMJ Open. 2021;11:e038349. doi:10.1136/bmjopen-2020-038349

39. Borges A, Bento L. Organ crosstalk and dysfunction in sepsis. Ann Intensive Care. 2024;14:147. doi:10.1186/s13613-024-01377-0

40. Wei W, Huang X, Yang L, et al. Neutrophil-to-lymphocyte ratio as a prognostic marker of mortality and disease severity in septic acute kidney injury patients: a retrospective study. Int Immunopharmacol. 2023;116:109778. doi:10.1016/j.intimp.2023.109778

41. Di Rosa M, Sabbatinelli J, Soraci L, et al. Neutrophil-to-lymphocyte ratio (NLR) predicts mortality in hospitalized geriatric patients independent of the admission diagnosis: a multicenter prospective cohort study. J Transl Med. 2023;21:835. doi:10.1186/s12967-023-04717-z

42. Montaldo E, Lusito E, Bianchessi V, et al. Cellular and transcriptional dynamics of human neutrophils at steady state and upon stress. Nat Immunol. 2022;23:1470–1483. doi:10.1038/s41590-022-01311-1

43. Kwok AJ, Allcock A, Ferreira RC, et al. Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis. Nat Immunol. 2023;24:767–779. doi:10.1038/s41590-023-01490-5

44. Hong CW. Current understanding in neutrophil differentiation and heterogeneity. Immune Netw. 2017;17:298–306. doi:10.4110/in.2017.17.5.298

45. Quail DF, Amulic B, Aziz M, et al. Neutrophil phenotypes and functions in cancer: a consensus statement. J Exp Med. 2022;219:e20220011. doi:10.1084/jem.20220011

46. Meghraoui-Kheddar A, Chousterman BG, Guillou N, et al. Two new neutrophil subsets define a discriminating sepsis signature. Am J Respir Crit Care Med. 2022;205:46–59. doi:10.1164/rccm.202104-1027OC

47. Tang A, Shi Y, Dong Q, et al. Prognostic differences in sepsis caused by gram-negative bacteria and gram-positive bacteria: a systematic review and meta-analysis. Crit Care. 2023;27:467. doi:10.1186/s13054-023-04750-w

48. Malik RA, Liao P, Zhou J, et al. Histidine-rich glycoprotein attenuates catheter thrombosis. Blood Adv. 2023;7:5651–5660. doi:10.1182/bloodadvances.2022009236

49. Shi C, Pamer EG. Monocyte recruitment during infection and inflammation. Nat Rev Immunol. 2011;11:762–774. doi:10.1038/nri3070

50. Sommer K, Garibagaoglu H, Paap EM, et al. Discrepant phenotyping of monocytes based on CX3CR1 and CCR2 using fluorescent reporters and antibodies. Cells. 2024;14:13. doi:10.3390/cells14010013

51. Phiri TN, Mutasa K, Rukobo S, et al. Severe acute malnutrition promotes bacterial binding over proinflammatory cytokine secretion by circulating innate immune cells. Sci Adv. 2023;9:eadh2284. doi:10.1126/sciadv.adh2284

52. Reyes M, Filbin MR, Bhattacharyya RP, et al. An immune-cell signature of bacterial sepsis. Nat Med. 2020;26:333–340. doi:10.1038/s41591-020-0752-4

53. Monneret G. Advancing our understanding of monocyte HLA-DR, S100A9, and the potential for individualized therapies in sepsis. Mil Med Res. 2023;10:28. doi:10.1186/s40779-023-00465-9

Xbox has confirmed the first batch of Game Pass additions for July. The headliner this time around is Tony Hawk’s Pro Skater 3 + 4, which is coming to Game Pass Ultimate and PC Game Pass on July 11, which is the game’s release day. It was already known that this remake bundle was going to arrive on Game Pass on day one, but hey, there’s nothing wrong with a little reminder.

The rest of the first wave of July additions include some titles that are returning to Game Pass. Several are coming to the entry-level, console-only Game Pass Standard tier. Here’s a breakdown of what to expect and when across Xbox Cloud Gaming, console and PC:

July 1

• Little Nightmares II — Game Pass Ultimate, PC Game Pass and Game Pass Standard

• Rise of the Tomb Raider — Game Pass Ultimate, PC Game Pass and Game Pass Standard

July 2

July 3

July 8

July 9

July 11

July 15

Little Nightmares II, Rise of the Tomb Raider and High on Life are perhaps among the bigger games on the list. I meant to try The Ascent the last time it was on Game Pass, so maybe I’ll get a chance to do so this time around. Minami Lane, meanwhile, is a cozy, lovely-looking street management sim.

Meanwhile, there are several titles leaving Game Pass on July 15. Among them is the fantastic Tchia, one of my favorite games of 2023. The others are Flock, Mafia Definitive Edition, Magical Delicacy, The Callisto Protocol and The Case of the Golden Idol.

When NETL’s Dirk Van Essendelft first met with leaders of the American artificial intelligence company Cerebras Systems Inc. in October 2019, he quickly realized the potential of the company’s groundbreaking Wafer-Scale Engine (WSE) to revolutionize how the Lab modeled energy systems.

More than five years later, the NETL-Cerebras collaboration has racked up an impressive list of accomplishments, several of which were featured during the Lab’s 25th anniversary poster event.

“Right from the beginning, we saw that the WSE was a much faster computational tool — hundreds of times faster — than the traditional high-performance computer hardware we were using to run our computational fluid dynamics (CFD) software,” Van Essendelft said. “Furthermore, it was achieving these speeds while consuming a fraction of the energy compared to traditional processing units. Based on these initial promising results, we formed a partnership that is still yielding powerful results today.”

NETL has been modeling complex energy systems for more than three decades with its renowned Multiphase Flow with Interphase eXchanges (MFiX), a versatile toolset for understanding the behavior and characterizing the performance of energy conversion processes. CFD software such as MFiX accelerates reactor development, reduces costs, optimizes performance and reduces design risk. The WSE could make all of this happen faster and with far less energy.

“We’ve accomplished much in the last five years,” Van Essendelft said. “From the development of a simple user interface that allows researchers to easily program the WSE to setting a world record for speed in several critical models, we’re seeing massive gains in compute speed in an extremely energy efficient manner. We also now have a very capable library to solve a variety of scientific problems related to materials and subsurface modeling in addition to CFD.”

Research using the WSE continues, and Van Essendelft and his team continue to pioneer applications of national importance that require increasingly advanced computing to model complex phenomena and manage extensive data. They plan to continue using the unique capabilities of the WSE to support technologies that will develop American energy technologies and help promote the use of the nation’s abundant, reliable, affordable, domestic energy resources.

NETL is a DOE national laboratory dedicated to advancing the nation’s energy future by creating innovative solutions that strengthen the security, affordability and reliability of energy systems and natural resources. With laboratories in Albany, Oregon; Morgantown, West Virginia; and Pittsburgh, Pennsylvania, NETL creates advanced energy technologies that support DOE’s mission while fostering collaborations that will lead to a resilient and abundant energy future for the nation.

XG, The Global Girl Group Taking the World by Storm

DOVER, N.J., July 1, 2025 /PRNewswire/ — Today, Casio America, Inc. announced the appointment of the internationally acclaimed hip hop / R&B girl group, XG, as the global ambassador for the G-SHOCK brand of shock-resistant watches.

Known for its bold music and powerful performances, XG consists of seven members; JURIN, CHISA, HINATA, HARVEY, JURIA, MAYA, and COCONA. The name XG stands for “Xtraordinary Girls,” reflecting their commitment to empowering people from all walks of life around the world through a genre-defying style that breaks conventions. With a strong global following, especially among younger people, XG is rising as a new force in international music and culture.

Having pioneered a new music genre called “X-Pop,” XG is breaking away from the conventions of J-Pop and K-Pop to create a style of their own. This spirit of originality and strength closely aligns with G-SHOCK, a unique brand known for its toughness, shock resistance, and distinctive design — making XG a natural choice as the brand’s global ambassador.

To celebrate the partnership, a special website will showcase key visuals and a promotional video featuring XG. Centered around the slogan “No Destination,” the video portrays XG boldly stepping into a new world with G-SHOCK, expressing the strength to shape one’s future without fear or hesitation. Art direction came from YAR, the creative team led by YOSHIROTTEN — one of Japan’s most promising rising artists — and delivered a bold and energetic visual experience.

 “G-SHOCK watches always remind us of how we never gave up on chasing our dreams, even when things got tough.” Said XG. “It gives us the courage to keep going and keep challenging ourselves. XG-SHOCK, let’s go!”

Additional key visuals and content will be released over time as G-SHOCK continues to share its world in collaboration with XG.

For more information on this announcement visit the XG landing page on gshock.casio.com/us.

About G-SHOCK
CASIO’s shock-resistant G-SHOCK watch is synonymous with toughness, born from the developer Mr. Ibe’s dream of ‘creating a watch that never breaks’. Over 200 handmade samples were created and tested to destruction until finally in 1983 the first, now iconic G-SHOCK hit the streets of Japan and began to establish itself as ‘the toughest watch of all time’. Each watch encompasses the 7 elements; electric shock resistance, gravity resistance, low temperature resistance, vibration resistance, water resistance, shock resistance and toughness. The watch is packed with Casio innovations and technologies to prevent it from suffering direct shock; this includes internal components protected with urethane and suspended timekeeping modules inside the watch structure. Since its launch, G-SHOCK has continued to evolve, continuing to support on Mr. Ibe’s mantra “never, never give up.” www.gshock.casio.com/us/ 

About XG

XG is a seven-member hip hop / R&B girl group consisting of members JURIN, CHISA, HINATA, HARVEY, JURIA, MAYA, and COCONA. They made their debut in March 2022 with their first single, “Tippy Toes.” The group’s name, XG, stands for “Xtraordinary Girls” and reflects their commitment to empowering people from diverse backgrounds around the world through their boundary-defying music and performances.

XG has achieved numerous global milestones, including becoming the first Japanese artist to top the U.S. Billboard “Hot Trending Songs Powered by Twitter” chart in the weekly ranking, and the first Japanese girl group to grace the cover of the U.S. Billboard magazine. In November 2024, their second mini-album, AWE, marked their first appearance on the Billboard 200 album chart. XG launched their first world tour, XG 1st WORLD TOUR “The first HOWL,” in 2024, performing 47 shows across 35 cities before concluding at Tokyo Dome on May 14, 2025. In April 2025, they also became the only Japanese act to perform at the Coachella Valley Music and Arts Festival, where they closed the Sahara Stage and received high praise from both domestic and international media.

FOR MEDIA INQUIRIES CONTACT:
5WPR
[email protected] 

Sue VanderSchans / Cecilia Lederer
CASIO AMERICA, INC.
(973) 361-5400
[email protected]
[email protected]

SOURCE Casio America, Inc.

Apple Inc. is considering using artificial intelligence technology from Anthropic PBC or OpenAI to power a new version of Siri, sidelining its own in-house models in a potentially blockbuster move aimed at turning around its flailing AI effort.

The iPhone maker has talked with both companies about using their large language models for Siri, according to people familiar with the discussions. It has asked them to train versions of their models that could run on Apple’s cloud infrastructure for testing, said the people, who asked not to be identified discussing private deliberations.

If Apple ultimately moves forward, it would represent a monumental reversal. The company currently powers most of its AI features with homegrown technology that it calls Apple Foundation Models and had been planning a new version of its voice assistant that runs on that technology for 2026.

A switch to Anthropic’s Claude or OpenAI’s ChatGPT models for Siri would be an acknowledgment that the company is struggling to compete in generative AI — the most important new technology in decades. Apple already allows ChatGPT to answer web-based search queries in Siri, but the assistant itself is powered by Apple.

Apple’s investigation into third-party models is at an early stage, and the company hasn’t made a final decision on using them, the people said. A competing project internally dubbed LLM Siri that uses in-house models remains in active development.

Making a change — which is under discussion for next year — could allow Cupertino, California-based Apple to offer Siri features on par with AI assistants on Android phones, helping the company shed its reputation as an AI laggard.

Representatives for Apple, Anthropic and OpenAI declined to comment. Shares of Apple closed up over 2% after Bloomberg reported on the deliberations.

The project to evaluate external models was started by Siri chief Mike Rockwell and software engineering head Craig Federighi. They were given oversight of Siri after the duties were removed from the command of John Giannandrea, the company’s AI chief. He was sidelined in the wake of a tepid response to Apple Intelligence and Siri feature delays.

Rockwell, who previously launched the Vision Pro headset, assumed the Siri engineering role in March. After taking over, he instructed his new group to assess whether Siri would do a better job handling queries using Apple’s AI models or third-party technology, including Claude, ChatGPT and Alphabet Inc.’s Google Gemini.

After multiple rounds of testing, Rockwell and other executives concluded that Anthropic’s technology is most promising for Siri’s needs, the people said. That led Adrian Perica, the company’s vice president of corporate development, to start discussions with Anthropic about using Claude, the people said.

The Siri assistant — originally released in 2011 — has fallen behind popular AI chatbots, and Apple’s attempts to upgrade the software have been stymied by engineering snags and delays.

A year ago, Apple unveiled new Siri capabilities, including ones that would let it tap into users’ personal data and analyze on-screen content to better fulfill queries. The company also demonstrated technology that would let Siri more precisely control apps and features across Apple devices.

The enhancements were far from ready. Apple initially announced plans for an early 2025 release but ultimately delayed the launch indefinitely. They are now planned for next spring, Bloomberg News has reported.

People with knowledge of Apple’s AI team say it is operating with a high degree of uncertainty and a lack of clarity, with executives still poring over a number of possible directions. Apple has already approved a multibillion dollar budget for 2026 for running its own models via the cloud but its plans for beyond that remain murky.

Still, Federighi, Rockwell and other executives have grown increasingly open to the idea that embracing outside technology is the key to a near-term turnaround. They don’t see the need for Apple to rely on its own models — which they currently consider inferior — when it can partner with third parties instead, according to the people.

Licensing third-party AI would mirror an approach taken by Samsung Electronics Co. While the company brands its features under the Galaxy AI umbrella, many of its features are actually based on Gemini. Anthropic, for its part, is already used by Amazon.com Inc. to help power the new Alexa+.

In the future, if its own technology improves, the executives believe Apple should have ownership of AI models given their increasing importance to how products operate. The company is working on a series of projects, including a tabletop robot and glasses that will make heavy use of AI.

Apple has also recently considered acquiring Perplexity in order to help bolster its AI work, Bloomberg has reported. It also briefly held discussions with Thinking Machines Lab, the AI startup founded by former OpenAI Chief Technology Officer Mira Murati.

Apple’s models are developed by a roughly 100-person team run by Ruoming Pang, an Apple distinguished engineer who joined from Google in 2021 to lead this work. He reports to Daphne Luong, a senior director in charge of AI research.

Luong is one of Giannandrea’s top lieutenants, and the foundation models team is one of the few significant AI groups still reporting to Giannandrea. Even in that area, Federighi and Rockwell have taken a larger role.

Regardless of the path it takes, the proposed shift has weighed on the team, which has some of the AI industry’s most in-demand talent.

Some members have signaled internally that they are unhappy that the company is considering technology from a third-party, creating the perception that they are to blame, at least partially, for the company’s AI shortcomings. They’ve said that they could leave for multimillion-dollar packages being floated by Meta Platforms Inc. and OpenAI.

Meta, the owner of Facebook and Instagram, has been offering some engineers annual pay packages between $10 million and $40 million — or even more — to join its new Superintelligence Labs group, according to people with knowledge of the matter. Apple is known, in many cases, to pay its AI engineers half — or even less — than what they can get on the open market.

One of Apple’s most senior large language model researchers, Tom Gunter, left last week. He had worked at Apple for about eight years, and some colleagues see him as difficult to replace given his unique skillset and the willingness of Apple’s competitors to pay exponentially more for talent.

Apple this month also nearly lost the team behind MLX, its key open-source system for developing machine learning models on the latest Apple chips. After the engineers threatened to leave, Apple made counteroffers to retain them — and they’re staying for now.

In its discussions with both Anthropic and OpenAI, the iPhone maker requested a custom version of Claude and ChatGPT that could run on Apple’s Private Cloud Compute servers — infrastructure based on high-end Mac chips that the company currently uses to operate its more sophisticated in-house models.

Apple believes that running the models on its own chips housed in Apple-controlled cloud servers — rather than relying on third-party infrastructure — will better safeguard user privacy. The company has already internally tested the feasibility of the idea.

Other Apple Intelligence features are powered by AI models that reside on consumers’ devices. These models — slower and less powerful than cloud-based versions — are used for tasks like summarizing short emails and creating Genmojis.

Apple is opening up the on-device models to third-party developers later this year, letting app makers create AI features based on its technology.

The company hasn’t announced plans to give apps access to the cloud models. One reason for that is the cloud servers don’t yet have the capacity to handle a flood of new third-party features.

The company isn’t currently working on moving away from its in-house models for on-device or developer use cases. Still, there are fears among engineers on the foundation models team that moving to a third-party for Siri could portend a move for other features as well in the future.

Last year, OpenAI offered to train on-device models for Apple, but the iPhone maker was not interested.

Since December 2024, Apple has been using OpenAI to handle some features. In addition to responding to world knowledge queries in Siri, ChatGPT can write blocks of text in the Writing Tools feature. Later this year, in iOS 26, there will be a ChatGPT option for image generation and on-screen image analysis.

While discussing a potential arrangement, Apple and Anthropic have disagreed over preliminary financial terms, according to the people. The AI startup is seeking a multibillion-dollar annual fee that increases sharply each year. The struggle to reach a deal has left Apple contemplating working with OpenAI or others if it moves forward with the third-party plan, they said.

If Apple does strike an agreement, the influence of Giannandrea, who joined Apple from Google in 2018 and is a proponent of in-house large language model development, would continue to shrink.

In addition to losing Siri, Giannandrea was stripped of responsibility over Apple’s robotics unit. And, in previously unreported moves, the company’s Core ML and App Intents teams — groups responsible for frameworks that let developers integrate AI into their apps — were shifted to Federighi’s software engineering organization.

Apple’s foundation models team had also been building large language models to help employees and external developers write code in Xcode, its programming software. The company killed the project — announced last year as Swift Assist — about a month ago.

Instead, Apple later this year is rolling out a new Xcode that can tap into third-party programming models. App developers can choose from ChatGPT or Claude.

Gurman writes for Bloomberg.

Miley Cyrus doesn’t have to buy herself flowers when she’s got Gucci‘s new Gorgeous Gardenia Eau de Parfum Intense, the latest scent in the Italian brand’s Flora collection. The 32-year-old “Used to be Young” singer was tapped to be the face of the campaign after serving as the ambassador of the Gucci Flora Gorgeous Gardenia fragrance since its initial release in 2021.

Set against the Los Angeles skyline at sunset, the campaign imagery, shot by Tyler Mitchell, features Cyrus sprawled in a field of pink and white flowers, with a fuchsia fragrance bottle in hand. The serene scene is meant to mimic the dichotomy of the scent: a powerful blend of florals mixed with vibrant woody notes.

The entire Flora collection is designed as an ode to female empowerment, femininity and freedom. This particular aroma, a reinterpretation of the original Gorgeous Gardenia, celebrates the delicate and fearless duality of womanhood, encouraging its wearer to pursue their deepest desires.

“With Gucci Flora Gorgeous Gardenia Eau de Parfum Intense, I wanted to enhance the sensuality of the gardenia by capturing the flower’s full depth, from its creamy richness to its woody facets,” Blanc explained. “The scent opens with a rush of citrus, unfolding into its full floral elegance, before embracing the bold warmth of its intensely enveloping depths.”

Like the existing Flora fragrances, the Eau de Parfum Intense is wrapped in the brand’s heritage floral print painted by Vittorio Accornero de Testa for Gucci in 1966. The “Intense” is written in a shimmery gold font. Size options include a 10-ml spray pen, as well as 30-, 50- and 100-ml bottles.

Cyrus has been working as an ambassador for Gucci Flora scents for four years now. She first joined as part of the brand’s 100th anniversary. Since then, she’s starred in campaigns for the Gucci Flora Gorgeous Orchid Eau de Parfum and the Gorgeous Jasmine scent.

The brand describes Cyrus as the perfect model for the nascent fragrance; someone who’s both free-spirited and versatile. When she first joined forces with Gucci, then creative director Alessandro Michele said: “Miley Cyrus is an artist with a spirit that is both rock ‘n’ roll and eclectic at the same time.”

 

UK campaign group The Good Law Project has accused Apple and Google of allowing ‘fake age ratings’ on the app stores – and says King, Supercell and many more have been deliberately providing them.

The group has launched a new campaign accusing platform holders Apple and Google of deceiving players by allowing game-makers to display one age rating at the point of download, but hiding the ‘real’ age rating in their games’ service agreements.

Game-makers specifically accused of the practice by the Good Law Project include King, Supercell, Century Games, Kooapps, Toca Boca and SayGames. But there are “thousands and thousands” more, says the group, which is also working with child safety NGO 5Rights to shed light on the issue.

In particular, the campaign focuses on King’s Candy Crush Saga. The Good Law Project claims that King deceives players by showing a 4+ rating on the app stores, but a peek into the game’s service agreement actually requires players to be 13 or over to view the ads served in the game.

The Good Law Project also namechecks Whiteout Survival, Clash of Clans, Pop Us!, Snake.io and Toca Boca World as supposedly having deceptive age ratings.

“Candy Crush isn’t the only app playing this game,” says The Good Law Project. “Thousands and thousands of apps are declaring one age range across the top and hiding another in the terms and conditions.”

“And it’s all to make money out of tricking kids,” the group continues. “Firms can’t build up profiles and dish out surveillance ads to children under 13 without explicit consent from their parents – it’s illegal. But the firms think they’ve covered their backs if the small print that nobody ever reads says users have to be “at least 13″, whatever it says at the top of the page.”

“So young kids are playing apps that bombard them with ads aimed at much older kids. And app developers and app stores are complicit.”

As a result of its findings, The Good Law Project filed an official complaint to the UK’s Competition and Markets Authority yesterday. The complaint claims that the behaviour is unlawful and in breach of UK consumer protection and data processing regulations.

It also claims that Apple and Google have a “special responsibility to protect consumers’ interests” due to their “effective monopoly” on app stores. Apple and Google’s lack of oversight “constitute abuses of their respective dominant positions,” it says.

Apple sent us the following statement in response to the Good Law Project’s claims: “We are committed to protecting user privacy and security and providing a safe experience for children. We do this by giving parents and developers important tools to help protect children on the App Store and across the apps they use.”

“When parents or guardians create an Apple Account for a child under 13 years of age, tracking permissions are disabled by default – so apps can’t request to track them through App Tracking Transparency. These protections are based on the user’s age, not the app. We also require developers to provide clear age ratings consistent with App Store policies, and in instances where an app’s age rating does not match its content, we take immediate action to ensure the issue is corrected.”

We also asked King, Google and Supercell for comment on this story, and will update this article with their remarks if or when they provide them.

At the time of writing, over 6,800 people have added their name to The Good Law Project’s petition to force Google and Apple to make their app stores safer for children.