Category: 3. Business

The co-founder of Ben & Jerry’s has accused its owner of being part of a movement of “corporate butt kissing” of Donald Trump and says management blocked the ice-cream brand from producing a flavour in support of peace in Gaza.

Ben Cohen told the Guardian that Unilever was pursuing a “corporate attack on free speech” by blocking the development of a special flavour in solidarity with the Palestinian people. It is understood the flavour had been approved by Ben & Jerry’s independent board and first mooted about a year ago.

Magnum, the group’s ice-cream arm, confirmed it had not gone ahead with the board’s suggestion for a Palestine product this summer.

Cohen has mounted a “Free Ben & Jerry’s” campaign to persuade Unilever to sell the brand to a group of socially minded investors who he says have pledged to allow it to continue its “social mission.”

With an increasingly authoritarian Trump in the White House, Cohen says now is the time that “companies and anyone who believes in justice, freedom and peace stands up. This is the moment when it is most needed for Ben & Jerry’s to be able to raise its voice.

“It seems like since Trump got elected anything that Trump is against, DEI, black history, protesters’ rights to free speech, all those things got censored.”

Previous Ben & Jerry’s flavours with an activist bent have included “Save Our Swirled” to highlight the need for action at the 2015 Paris climate meetings, “I Dough, I Dough” to celebrate the legalisation of same-sex marriage at a US federal level, and “Home Sweet Honeycomb” in support of resettling refugees in Europe.

Cohen’s criticisms, which he has backed up with a video posted on Instagram, are the latest blow in the acrimonious spat between the brand’s founders and owners. Unilever is planning to spin off the Magnum Ice Cream Company into a separate business, which it hopes to list in Amsterdam with secondary listings in London and New York.

Those plans were this week delayed because of the US government shutdown, although they could proceed by the end of the year. Unilever said remained confident of implementing its demerger plans this year.

Unilever and Magnum said Ben & Jerry’s was “not for sale”.

Magnum said: “The independent members of Ben & Jerry’s board are not, and have never been, responsible for the Ben & Jerry’s commercial strategy and execution.”

Referring to the proposed pro-Palestinian flavour, a spokesperson said: “Recommendations are considered by Ben & Jerry’s leadership, and management has determined it is not the right time to invest in developing this product.”

The company said Ben & Jerry’s was focused on “campaigns close to its communities” such as improved conditions in refugee accommodation in the UK and campaigning in defence of the first amendment and freedom of speech in the US.

Magnum added: “We remain committed to Ben & Jerry’s unique three-part mission – product, economic and social – and look forward to building on its success as an iconic, much-loved brand.”

Unilever, the British owner of consumer brands ranging from Dove soap to Hellmann’s mayonnaise, bought Ben & Jerry’s in 2000 for $326m, but agreed an unusual deal for the ice-cream brand to preserve an independent board with the ability to speak out on social justice issues.

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The founders argue that Unilever has reneged on that promise, particularly in relation to the humanitarian crisis in Gaza as the Israeli government destroyed much of the territory.

A spokesperson for Unilever said: “We have always sought to work constructively with the Ben & Jerry’s teams to make sure we stayed true to the original agreement around the progressive, non-partisan social mission.”

Ben & Jerry’s was founded in 1978 by Cohen and Jerry Greenfield after the friends took a $5 correspondence course in ice-cream making. They opened their first store in a renovated petrol station in Burlington, Vermont, with a mission to “advance human rights and dignity”.

Under Unilever, the pair have officially been paid employees with no formal role in the business beyond promoting its values as “brand ambassadors”. Cohen remains in that role, but Greenfield resigned from Ben & Jerry’s in September, saying it had lost its independence.

Cohen said Ben & Jerry’s was being blocked from “making ice-cream with purpose”, and pledged to create a Palestine solidarity flavour in his own kitchen.

Members of the public are being asked to name and help create the flavour in a two-week competition. He suggested it would be based on watermelon, itself a symbol of solidarity with the Palestinian people.

The ice-cream, which would be created as a small batch under his personal Ben’s Best brand, will not be for sale, but is intended to draw attention to the cause of “rebuilding, and peace and dignity for the people of the region”. He has previously used the Ben’s Best brand, first created in 2016 to back leftwing Vermont senator Bernie Sanders, to support a number of causes.

Ben & Jerry’s has clashed repeatedly with its parent company over Palestinian rights. It refused to sell ice-cream in territories occupied by Israel, took legal action against Unilever when it sold the brand’s Israeli division to a local operator. In May the brand called Israel’s actions in Gaza a genocide, a description used last month by a United Nations independent international commission of inquiry.

Updated data from the phase 1/2 OptimUM-01 trial (NCT03947385) shared during the 2025 Society for Melanoma Research Congress showed that treatment with the combination of darovasertib and crizotinib (Xalkori) led to a median overall survival (OS) of 21.1 months (95% CI, 12.5-27.1) when used in the first-line for patients with metastatic uveal melanoma, which compares favorably with the 10 to 12 months achieved with historical controls.¹

Investigators reported that the median OS was “notable compared to historical controls,” despite slightly more than one-third (39%) of patients having an ECOG performance status of 1. The median progression-free survival (PFS) with darovasertib plus crizotinib also compared favorably with historical controls. At a median follow-up of 25 months, the median PFS in the respective groups was 7.0 months (95% CI, 3.8-7.7) vs just 2.8 months (95% CI, 2.7-3.4).

The doublet (n = 41) elicited an objective response rate (ORR) of 34.1% (95% CI, 20.1%-50.6%), which was comprised entirely of partial responses; 56.1% of patients achieved stable disease, and 9.8% experienced disease progression. The median duration of response (DOR) was 9.0 months (95% CI, 3.8-12.0). The disease control rate achieved with the combination was 90.2% (95% CI, 76.9%-97.3%), with 85% of patients experiencing any reduction in target lesions.^1,2

“These findings suggest that darovasertib plus crizotinib may represent a novel first-line treatment option and support the ongoing registrational phase 2/3 [OptimUM-02 trial (NCT05987332)] in the first-line setting,” Meredith McKean, MD, of Sarah Cannon Research Institute, in Nashville, Tennessee, and colleagues wrote in the presentation.¹

How might darovasertib plus crizotinib address an unmet need in metastatic uveal melanoma?

It is known that those with metastatic uveal melanoma have a poor prognosis, which median PFS under 3 months and median OS ranging under 1 year. Moreover, the majority of these tumors are known to have PKC-activating mutations in GNAQ/11. Darovasertib targets PKC and has been shown to have activity in this disease. Preclinical evidence supports that crizotinib has complementary activity to darovasertib; as such, investigators sought to evaluate the combination in this population as part of the OptimUM-01 study.

What was the design of OptimUM-01?

The phase 1/2, multicenter, open-label trial enrolled patients with metastatic uveal melanoma with GNAQ/GNA11 mutations or PRKC fusions who were at least 18 years of age and had an ECOG performance status no higher than 1, measurable disease by RECIST 1.1 criteria, and acceptable organ function. Patients could not have had prior exposure to PKC/MET/GNAQ11 inhibitors in the metastatic setting, nor could they have symptomatic or untreated central nervous system metastases. They were allowed to have previously received ablations, had oligometastatic disease surgically resected, or received neoadjuvant or adjuvant therapy.

In the dose-expansion portion of the research, patients were administered darovasertib at a twice-daily dose of 300 mg and crizotinib at a twice-daily dose of 200 mg. The primary end points for the phase 1 portion were safety, tolerability, and ORR by RECIST 1.1 criteria for the phase 2 portion. Secondary end points included PFS, ORR, and DOR by RECIST 1.1 criteria, quality-of-life measures, and safety.

What has previously been reported?

In April 2023, interim data from the study were released.³ At a data cutoff date of March 8, 2023, when darovasertib was given at a twice-daily dose of 300 mg with crizotinib given at a twice-daily dose of 200 mg in the first-line setting (n = 20), it induced a confirmed ORR of 45% by RECIST 1.1 criteria; 9 patients achieved a PR. The DCR was 90%, and the median PFS was about 7 months.

When the regimen was given in any line (n = 63), the ORR was 30%; 19 patients experienced a PR. Here, the DCR was 87% and the median PFS was about 7 months. In the group of patients who received the regimen in the first- and any-line but had hepatic-only disease (n = 20), the confirmed ORR was 35%. The DCR was 100% and the median PFS was approximately 11 months.

What were the baseline characteristics of patients enrolled to OptimUM-01?

The median patient age was 64.5 years, with half of patients younger than 65 years and the other half 65 years and older. Most patients were White (93.2%), 52.3% were male, and more than half (61.4%) had an ECOG performance status of 0. Baseline lactate dehydrogenase level was normal for 65.9% of patients. The largest metastatic lesion was no larger than 3.0 cm for 54.5% of patients, 3.1 cm to 8.0 cm for 34.1% of patients, and 8.1 cm or larger for 9.1% of patients. Location of metastases were hepatic only for 52.3% of patients, extrahepatic only for 4.5% of patients, and both for 40.9% of patients. In terms of HLA-A2*02:01 status, 68.2% of patients were negative and 27.3% were positive; this was unknown for 4.5% of patients.

What was the safety profile of darovasertib plus crizotinib?

The median dose intensity for darovasertib was 92.6% and 88.0% for crizotinib. Moreover, the mean duration of exposure to darovasertib was 10.0 months. Treatment-related adverse effects (TRAEs) of any grade were experienced by 97.7% of patients who received the doublet; they were grade 3 or higher for 27.3% of patients. Treatment-related serious adverse effects were experienced by 9.1% of patients and were grade 3 or higher for 6.8% of cases. TRAEs resulted in discontinuation for 4.5% of patients.

The most common TRAEs experienced by more than 30% of patients who received the combination were diarrhea (all grade, 90.9%; grade ≥3, 2.3%), nausea (79.5%; 0%), peripheral edema (61.4%; 0%), vomiting (47.7%; 0%), dermatitis acneiform (43.2%; 0%), hypoalbuminemia (43.2%; 2.3%), and fatigue (38.6%; 0%).

What is the significance of these data? What’s next for darovasertib plus crizotinib?

“These first reported OS data and broader clinical efficacy observed with a manageable safety profile underscores the potential of the darovasertib and crizotinib combination in the first-line treatment landscape for patients with metastatic uveal melanoma,” Darrin Beaupre, MD, PhD, chief medical officer of IDEAYA Biosciences, stated in a news release.²

In April 2025, the FDA granted breakthrough therapy designation to single-agent darovasertib for use in the neoadjuvant setting in adult patients with uveal melanoma based on updated interim data from the phase 2 OptimUM-09 trial (IDE196-009; NCT05907954).⁴Data from the plaque brachytherapy cohort of the study shared in September 2025 showed that 76% of efficacy evaluable patients (n = 21) had ocular tumor shrinkage of at least 20% by product diameters. Forty-eight percent of patients had a minimum 20% reduction in simulated radiation dose to at least 1 visual structure, and 86% experienced any reduction.⁵

The phase 2/3 OptimUM-02 trial will evaluate the safety, tolerability, pharmacokinetics, and antitumor activity of darovasertib plus crizotinib in patients with HLA-A*02:01–negative metastatic uveal melanoma.⁶ The regimen will be compared with investigator’s choice of treatment, which could include pembrolizumab (Keytruda), ipilimumab (Yervoy) plus nivolumab (Opdivo), or dacarbazine.

References

1. McKean M, Chmielowski B, Butler MO, et al. First reported overall survival results from a phase 1/2 study of darovasertib plus crizotinib as first-line treatment for metastatic uveal melanoma (OptimUM-01). Presented at: 2025 Society for Melanoma Research Congress; October 25-27, 2025; Erlangen, Germany. https://filecache.investorroom.com/mr5ir_ideayabio/555/McKean_et_al-OptimUM-01-SMR_2025_Poster_Slides_vF.pdf
2. IDEAYA Biosciences reports positive median overall survival data from phase 2 trial of the darovasertib and crizotinib combination in first-line metastatic uveal melanoma at the 2025 Society for Melanoma Research Congress. News release. IDEAYA Biosciences, Inc. October 20, 2025. Accessed October 27, 2025. https://ir.ideayabio.com/2025-10-20-IDEAYA-Biosciences-Reports-Positive-Median-Overall-Survival-Data-from-Phase-2-Trial-of-the-Darovasertib-and-Crizotinib-Combination-in-First-line-Metastatic-Uveal-Melanoma-at-the-2025-Society-for-Melanoma-Research-Congress
3. Ideaya announces positive interim phase 2 data for darovasertib and crizotinib combination and successful FDA type C meeting on registrational trial design for accelerated approval in first-line metastatic uveal melanoma. News release. Ideaya Biosciences, Inc. April 23, 2023. Accessed October 27, 2025. https://www.prnewswire.com/news-releases/ideaya-announces-positive-interim-phase-2-data-for-darovasertib-and-crizotinib-combination-and-successful-fda-type-c-meeting-on-registrational-trial-design-for-accelerated-approval-in-first-line-metastatic-uveal-melanoma-301804804.html
4. IDEAYA Biosciences receives US FDA breakthrough therapy designation for darovasertib monotherapy in neoadjuvant uveal melanoma. News release. IDEAYA Biosciences, Inc. March 31, 2025. Accessed October 27, 2025. https://ir.ideayabio.com/2025-03-31-IDEAYA-Biosciences-Receives-US-FDA-Breakthrough-Therapy-Designation-for-Darovasertib-Monotherapy-in-Neoadjuvant-Uveal-Melanoma
5. IDEAYA Biosciences announces positive interim phase 2 data for darovasertib in the neoadjuvant setting of primary uveal melanoma. News Release. IDEAYA Biosciences. September 8, 2025. Accessed September 8, 2025. https://media.ideayabio.com/2025-09-08-IDEAYA-Biosciences-Announces-Positive-Interim-Phase-2-Data-for-Darovasertib-in-the-Neoadjuvant-Setting-of-Primary-Uveal-Melanoma
6. IDE196 (darovasertib) in combination with crizotinib as first-line therapy in metastatic uveal melanoma. ClinicalTrials.gov. Updated October 20, 2025. Accessed October 27, 2025. https://www.clinicaltrials.gov/study/NCT05987332

IH exacerbates lung remodelling in mice

We exposed C57BL/6J mice to either IH or normoxia for 6 weeks to investigate the effects of IH on lung tissue. After the exposure period, lung tissues were collected for histopathological staining and analysis. Compared with control mice, those exposed to IH exhibited significant increases in pulmonary inflammation, mucus staining, and collagen deposition (Fig. 1A-D). Phalloidin staining revealed enhanced cytoskeletal organization and increased stress fiber formation, which may reflect actin remodeling associated with both structural cells and infiltrating inflammatory cells in the lungs of IH-exposed mice (Fig. 1A, E). Additionally, histochemical staining revealed increased expression of Cd11b, Mpo, and Cd68 in the lungs of IH-exposed mice, indicating that IH exposure promoted infiltration of immune cells. The upregulation of Cd31 expression in lung tissue further confirmed that IH exposure stimulated remodeling of pulmonary blood vessels (Fig. 1F-G). In summary, IH exposure induced pronounced inflammatory infiltration and structural alterations, contributing to extensive pulmonary tissue and vascular remodeling in mice.

Construction of a single-cell transcriptome map of IH-exposed mouse lungs

Next, we retrieved scRNA-seq data from the GEO database, including lung tissue samples from both IH model mice (n = 3) and healthy control mice (n = 3), to gain a comprehensive understanding of the cellular landscape in the lung tissue of IH model mice (Supplementary Table 1). After rigorous quality control and filtering, a total of 48,272 cells were retained from the scRNA-seq data for downstream analysis (Supplementary Fig. 1 and Supplementary Table 1). In the scRNA-seq dataset, the median number of unique molecular identifiers (UMIs) per cell was 1978, and the median number of genes detected per cell was 996. After PCA-mediated reduction of these high-quality data, the first 15 PCs were included in the follow-up analysis (Supplementary Fig. 1). We applied the Harmony algorithm to each dataset again to minimize batch effects between different scRNA-seq datasets. Subsequently, we adopted a clustering method based on t-SNE to initially identify 12 clusters according to typical markers of different cell types. These cell types include type 1 alveolar epithelial cells (AT1), type 2 alveolar epithelial cells (AT2), macrophages/monocytes, megakaryocytes, B cells, T cells, fibroblasts, endothelial cells, eosinophils, natural killer (NK) cells, neutrophils, and erythroid cells (Fig. 2A-B, Supplementary Table 2). These cells were present in each sample (Fig. 2E and Supplementary Fig. 1). The specific number of cells identified in each sample is provided in Supplementary Table 2. A total of 195 cells in Clusters 19 and 21 carried markers of two cell types whose expression differed significantly at the same time. We conducted a secondary analysis and divided these 195 cells into three clusters to exclude the possibility of insufficient dimensionality reduction (Fig. 2C). A total of 154 cells in Clusters 0 and 2 expressed endothelial cell and B-cell markers simultaneously. Forty-one cells in Cluster 1 expressed both B-cell and T-cell markers (Fig. 2D-F). We decided not to include these double-positive cells in subsequent analyses to ensure the accuracy and reliability of our results. The calculation of the cell proportion for each cell type indicated significant changes (Fig. 2G). Among all the cells collected, endothelial cells accounted for the largest proportion and exhibited the most obvious increase, and macrophages presented the greatest change among immune cells. Consistent with previous reports, IH exposure increased the number of type 1 alveolar epithelial cells [21]. Notably, IH also promoted the aggregation of fibroblasts in the lung (Fig. 2H) [22, 23].

Characterization of fibroblasts in IH-exposed mouse lungs

Fibroblast heterogeneity was analyzed in scRNA-seq data from six samples (Fig. 3A). Reclustering revealed four fibroblast subtypes (F1-F4) with distinct gene expression profiles (Fig. 3B-C). Acta2⁺ fibroblasts (F1) expressed high levels of smooth muscle contraction genes such as Actc1 and Myh11 (Fig. 3E), consistent with myoid fibroblasts described previously [24]. GO analysis showed enrichment in actomyosin and muscle system processes for F1 (Fig. 3D). Tcf21⁺ fibroblasts (F2) highly expressed vascular development genes (Fig. 3E), with GO terms related to blood vessel morphogenesis (Fig. 3D). Dcn⁺ fibroblasts (F4) expressed extracellular matrix (ECM) genes (Col1a1, Col3a1) and were enriched in ECM organization pathways (Fig. 3D-E). A proliferative fibroblast cluster (F3) was identified by high ribosomal gene expression and low apoptosis gene expression (Fig. 3E).

Compared to controls, all four fibroblast subtypes expanded after IH exposure, with the most significant increases seen in F1 and F2 cells (Fig. 3F-G). Through transcription factor target analysis, we characterized the predominant regulatory networks in each fibroblast subtype. In F2 and F4 cells, Sp1—a transcription factor involved in transcriptional activation—was predicted to regulate numerous target genes. F1 cells were predominantly regulated by serum response factor (Srf), a well-known transcription factor implicated in the contractile phenotype of vascular smooth muscle cells (Fig. 3H) [25]. In F3 cells, Erg was identified as a key regulator, consistent with its known role in fibroblast activation [26]. Gene set scoring revealed F1 fibroblasts had the highest contractility score, F4 fibroblasts the highest ECM score, and F3 the lowest apoptosis score (Fig. 3I). Glycolytic activity scores did not differ significantly among the subtypes. During disease progression, significant proportional changes in fibroblast subtypes were observed. Trajectory analysis showed that F1 and F2 cells were evenly distributed along the developmental timeline, while F4 cells were mainly present during the intermediate stages, and F3 cells were predominantly enriched at the late stages. These trends may explain the greater incidence of hypertension and pulmonary fibrosis in OSAHS patients than in the general population(Fig. 3J-K, Supplementary Fig. 2) [27, 28].

Characterization of monocytes and macrophages in IH-exposed mouse lungs

The t-SNE analysis grouped monocytes and macrophages into 14 clusters based on 2,000 highly variable genes (Fig. 4A, Supplementary Fig. 3). Clusters 0, 5, and 8 were annotated as macrophage subtype 1 (Mφ1), marked by Wfdc21, Ear1, and Plet1. Clusters 2, 10, 11, and 12 formed monocyte subtype 1 (M1), expressing Treml4 and Cx3cr1, corresponding to nonclassical monocytes. Clusters 3, 4, 6, 7, and 13 were macrophage subtype 2 (Mφ2), marked by Cd209a, H2-Dmb1, Klrd1, and Ccnd1. Clusters 1 and 9 were monocyte subtype 2 (M2), expressing Ly6c2 and Ccr2, corresponding to classical monocytes (Fig. 4B-C).

Compared to controls, the proportion of M1 cells decreased while Mφ1 cells increased significantly. Pseudotime analysis indicated that monocytes progressed from M1 to M2, then to Mφ2 and ultimately Mφ1, supporting enhanced monocyte-to-macrophage transition in the lungs under IH exposure (Fig. 4F, Supplementary Fig. 4). Functional scoring revealed that Mφ1 exhibited the highest fatty acid oxidation and lowest inflammation levels among the four subtypes, while M2 showed the strongest chemotaxis, likely due to recruitment by inflammatory signals. Both macrophage subtypes had lower glycolysis levels than monocytes, and Mφ1 displayed disordered apoptosis-related gene expression, suggesting terminal differentiation (Fig. 4E-F). Transcription factor analysis indicated that Sp1 predominantly regulated Mφ1-related genes, with higher expression in the IH group (Fig. 4G-I). GO enrichment showed that M1 was associated with innate immune responses, M2 with immune regulation, Mφ2 with lymphocyte activation, and Mφ1 with lipid metabolism and endocytosis (Supplementary Fig. 4H-K).

Additionally, we analyzed cytokine expression in Mφ1 and Mφ2 from the lungs of IH-exposed mice. The results showed that Mφ1 is characterized by a high expression level of Il18, whereas Mφ2 displayed higher levels of Ccl5, Ccr2, and Cd68, indicative of a classical pro-inflammatory phenotype (Fig. 4J). GSEA of Mφ1 signature genes linked them to processes such as monovalent inorganic cation homeostasis, cell adhesion, and carbohydrate metabolism (Fig. 4K), indicating roles in ion balance and metabolic regulation. KEGG analysis showed significant enrichment of PPAR-related pathways in Mφ1 (Supplementary Fig. 4L), highlighting PPAR’s role in metabolism and immune function. Using lactate-treated macrophage data (GSE115354), we found 43 overlapping upregulated genes enriched in PPAR pathways (Fig. 4L-M), confirming PPAR’s involvement in IH-induced Mφ1 changes. Expression of key PPAR pathway genes (Acaa1a, Acaa1b, Acox1, Cpt1a, Lpl, Nfe2l2, Pparg) increased over pseudotime (Fig. 4N), indicating enhanced fatty acid oxidation and lipid metabolism in macrophages after IH exposure.

Characterization of T cells in IH-exposed mouse lungs

The t-SNE analysis of scRNA-seq data from six samples revealed the heterogeneity of T cells and identified nine distinct subtypes through clustering (Fig. 5A and B). By calculating the similarity between cell clusters (Fig. 5C), we further classified these clusters into five major subtypes (Fig. 5D). Subtype T1 (Cluster 6) corresponds to exhausted CD8⁺ T cells, characterized by markers of chronic antigen stimulation and functional exhaustion. Subtype T2 (Clusters 0, 1, 2, 3) represents memory CD8⁺ T cells with high Cd8a and Ccr7 expression, involved in antigen recognition and immune surveillance. Subtype T3 (Clusters 7, 8) is marked by elevated Gata3, Ccr2, and Cxcr6, consistent with CD4⁺ Th2 cells that regulate allergic inflammation. Subtype T4 (Cluster 4) shows effector memory features, with Ccl5, Cd8a, and Cxcr3 expression indicating strong migratory and antiviral capacity. Subtype T5 (Clusters 5, 9) comprises regulatory T cells (Tregs), characterized by Foxp3, Ctla4, and Lcos expression, crucial for immune tolerance and suppressing excessive immune responses.

After IH exposure, the proportion of memory T cells (T2) decreased significantly, while CD4⁺ Th2 cells (T3) increased (Fig. 5F-G). Notably, SP1, a transcriptional regulator linked to T3 signature genes, was significantly upregulated in the IH group, suggesting its role in T3 cell regulation (Fig. 5H). KEGG and GO analyses of T3 highly expressed genes showed enrichment in pathways related to CD4-positive, alpha-beta T-cell differentiation and activation, including Th17 and Th1/Th2 differentiation (Fig. 5I-J). Trajectory analysis showed that T1 and T2 cells were evenly distributed along the developmental timeline, while T4 cells were mainly enriched during the intermediate-to-late stages, and T3 cells were predominantly present at the late stage (Fig. 5L). T3 cells exhibited the highest inflammation score, indicating that their activation and cytokine secretion may exacerbate pulmonary inflammation in late-stage IH (Fig. 5K). Fatty acid oxidation was similar across subtypes, while T1 cells displayed markedly lower glycolysis, consistent with an exhausted phenotype. These findings demonstrate that IH reshapes T-cell composition and function, promoting Th2-skewed inflammation and T-cell exhaustion.

Characterization of endothelial cells in IH-exposed mouse lungs

We analyzed endothelial cells from six samples using scRNA-seq data. t-SNE analysis identified nine clusters (Fig. 6A), which were grouped into five subtypes based on cluster similarity (Fig. 6B): endo1 (Clusters 1 and 5), endo2 (Clusters 1, 3, and 4), endo3 (Clusters 6, 7, and 9), endo4 (Cluster 0), and endo5 (Cluster 8). The distribution of these subtypes across samples is shown in Fig. 6C and D. Marker gene analysis revealed distinct profiles: Cyb5r3 and Rps29 for endo1; Cldn5 and Foxf1 for endo2; Emp2 and Cdh5 for endo3; Vwf and Cytl1 for endo4, consistent with venous endothelial cells [29]; and Ccl21a and Mmrn1 for endo5, matching lymphatic endothelial cell signatures (Fig. 6E) [29]. Among these, endo2 was the most abundant, while endo5 was the least prevalent. Notably, IH exposure increased the proportions of endo1 to endo3 cells (Fig. 6F). Pseudotime trajectory analysis revealed a dynamic transition of endothelial subtypes over time: endo2 and endo5 predominated in the early stages, endo3 was evenly distributed throughout the trajectory, and endo1 and endo4 became dominant at the terminal stage (Fig. 6G, Supplementary Fig. 5). KEGG enrichment analysis demonstrated subtype-specific functional programs: endo1 was enriched in “ribosome” and “oxidative phosphorylation”; endo2 in “antigen processing and presentation” and “fluid shear stress and atherosclerosis”; endo3 in “IL-4/IL-13 signaling” and “apoptosis”; endo4 in “TGF-beta signaling” and “stem cell pluripotency”; and endo5 in “ferroptosis” and “autophagy” (Fig. 6H). These findings suggest that during IH exposure, endothelial cells undergo functional reprogramming from immune and stress responses toward a more reparative and metabolically active phenotype.

Analysis of interactions between monocytes/macrophages and other altered cell types

We analyzed receptor‒ligand interactions between monocytes/macrophages and other altered cell types to further elucidate the cellular interactions within lung tissue exposed to IH. The results revealed that the interactions between the endo2 and other cell subtypes were particularly strong. Among these interactions, endo2 cells exhibited similarly strong interactions with both Mφ1 and M2 , and these interactions were markedly stronger than those observed with other cell types (Fig. 7A and B). Additionally, interactions between Tgfb1–(Tgfbr1 + Tgfbr2), Ccl6–Ccr2, Sema3a–(Nrp1 + Plxna2), and Sema3c–(Nrp1 + Plxna2) are highly probable within the network of monocytes/macrophages and other altered cell types, with Ccl6–Ccr2 showing the strongest potential for interaction. Notably, the receptor for Ccl6, Ccr2, was expressed in multiple cell subtypes, with prominent expression in endothelial cells and macrophage/monocyte-related subtypes (Fig. 7E). We performed immunohistochemistry to investigate this phenomenon further, and the results confirmed that Ccr2 expression was indeed upregulated in the lung tissue of the IH-exposed group (Fig. 7F), suggesting that Ccr2 may play a significant role in the pathophysiology of IH.

Effect of the SP1 intervention on the lung tissue of IH-Exposed mice

In this study, we first confirmed that SP1 expression was significantly upregulated in the lungs of mice exposed to IH, as evidenced by both immunofluorescence staining and western blot analysis (Fig. 8A-D). Based on this observation, we established an IH mouse model combined with the SP1 inhibitor plicamycin to further investigate its therapeutic potential. Western blot analysis and immunofluorescence analysis (Fig. 8E-F and H-I) showed that plicamycin treatment partially reversed the IH-induced upregulation of SP1 in lung tissue. Similarly, measurement of lung hydroxyproline levels suggested a modest reduction following plicamycin treatment compared with IH alone (Fig. 8G). Subsequently, histopathological evaluation revealed that plicamycin tended to attenuate IH-induced pulmonary inflammation, mucus secretion, and collagen deposition (Fig. 8H and J–L), indicating that SP1 plays a central role in mediating lung injury under IH exposure. Additionally, phalloidin staining revealed increased F-actin remodeling and stress fiber formation in the lungs of IH-exposed mice, which was partially alleviated by plicamycin treatment (Fig. 8H and M). Furthermore, PCR analysis revealed that plicamycin effectively reduced the expression of genes involved in inflammation and fibrosis, including Fizz1, Ym1, Il6, α-Sma, Cd68, Ccl2, Cd80, Ccl7, Col1a1, and iNOS (Supplementary Fig. 6 A), further suggesting that SP1 plays a key role in pulmonary inflammation and fibrosis induced by IH exposure. In conclusion, the SP1 inhibitor plicamycin significantly suppresses the inflammatory response, cytoskeletal remodeling, and fibrosis in the lung tissue of IH-exposed mice.

Britain’s leading AI institute has announced a new mission to help protect the nation from cyber-attacks on infrastructure, including energy, transport and utilities, after it was embroiled in allegations of toxic work culture and the chair resigned amid ministerial pressure.

The Alan Turing Institute will “carry out a programme of science and innovation designed to protect the UK from hostile threats”, it announced on Tuesday as part of changes following the resignation last month of Jean Innes, its chief executive, after a staff revolt and government calls for a strategic overhaul of the state-funded body.

The mission comes amid growing concern over Britain’s vulnerability to internet outages and cyber-attacks after this month’s incident affecting Amazon’s cloud computing globally and recent cyber-attacks crippling production at Jaguar Land Rover factories, and supply chains at Marks & Spencer and the Co-op.

Blythe Crawford, the former commander of the UK’s air and space warfare centre , will report back next month on how the government-funded institute “can best support the scale of government AI ambitions in defence, national security and intelligence”.

The chair, former Amazon UK boss Doug Gurr, said 78 different research projects at the 440-staff institute have been closed, spun out or completed because they do not align with the new direction.

The institute has been beset by internal strife since last year as staff protested against changes, culminating in a group of employees filing a whistleblower complaint to the Charity Commission.

Gurr said in an interview with the BBC that the whistleblower claims were “independently investigated” by a third party that found them to have “no substance”.

The institute was named after the mathematical genius who helped crack the Enigma code during the second world war and outlined key concepts of AI. He also invented the eponymous test to determine if a computer can show human intelligence.

It will also focus on deploying AI for the environment and health. The institute will develop ways to use the fast-advancing technology to more rapidly and accurately forecast changes in weather, oceans and sea ice, in part to better inform UK government emergency planners. It will also target “tangible emissions reductions in transportation networks, manufacturing processes and critical infrastructure”.

On health, it will focus on creating digital twins of human hearts, a frontline of personalised AI-enabled medicine, which could improve medical interventions and patient outcomes for critically ill cardiac patients.

Description of study participants

Data were collected for eight individuals with spastic CP planned for MLS at the time of their pre-operative clinical gait assessment (Table 1). Parents or caregivers signed an informed consent form, participants older than twelve signed an informed assent form. The study was approved by the Ethical Committee UZ/KU Leuven (S64909).

Description of experimental data

All study participants had a clinical examination and 3D gait analysis followed by an MRI scan of the legs and pelvis.

Clinical examination

The clinical examination was performed by an experienced clinician. This examination was part of standard clinical care and was used to inform clinical decision making. It assessed muscle length, strength, bony alignment, and motor control. Muscle length was evaluated by passively moving the joints to the end of range of motion and measuring the final angle with a goniometer. Evaluated joint motions were hip flexion, hip extension, knee flexion, knee extension, ankle dorsiflexion, and ankle plantarflexion. Muscle strength was evaluated using modified Manual Muscle Testing (MMT). The strength of hip flexors, extensors, abductors and adductors, knee flexors and extensors, ankle plantar flexors and dorsiflexors, invertors and evertors was tested. When no muscle contraction could be palpated, the muscle group was scored 0, when the individual could move against gravity with maximal resistance the muscle group was scored 5 (Table S1 refers to supplement). A specific evaluation of abdominal and back muscles was also performed and scored between 0 and 5 (Table S2-S3). For alignment, femoral anteversion [21], bimalleolar angle and tibiofemoral angle [22] were evaluated. For motor control, both spasticity and selectivity were assessed. Spasticity was assessed using the modified Ashworth scale [23], Tardieu scale [24], and Duncan-Ely [22]. The Selective Motor Control Test [25] and Selective Control Assessment of the Lower Extremity [26] were used to evaluate selectivity.

3D gait analysis

The gait analysis was performed at a self-selected speed and marker trajectories were captured with a 12-camera Vicon system (Vicon, Oxford, UK; sampling frequency of 100 Hz). Markers were attached according to an extended lower limb plug-in gait model (Table S4). Ground reaction forces were collected at 1000 Hz with two embedded force plates (AMTI, Watertown MA, USA) in the raised 10-meter walkway. Muscle activity of eight muscles was measured bilaterally with a 16-channel telemetric surface electromyography system (Zerowire, Cometa, Italy) at 1000 Hz. The electrodes were placed according to the SENIAM guidelines [27]. In this study, we only evaluated and compared kinematics.

MRI

MRI of the lower limbs and pelvis were acquired similar to Bosmans et al. [28]. Depending on the individual’s size, three to five axial image series were acquired on a 3T Siemens MR scanner using a T1 weighted SE sequence with the participants lying supine with extended knees. For the image series containing the hip, knee, or ankle, inter-slice distance was 1 mm with a voxel size of 1.04 × 1.04 × 1 mm. For the other image series, the inter-slice distance was 2 mm with a voxel size of 1.04 × 1.04 × 2 mm. Glycerin markers were placed on the marker locations of the 3D gait analysis to ensure correct registration for inverse kinematics.

Predictive simulations

We performed predictive simulations of walking using PredSim [7, 29]. In short, we solved for the gait cycle duration, muscle controls, and the corresponding gait pattern by minimizing a cost function while imposing task constraints and musculoskeletal dynamics without relying on experimental gait data. The task constraints were an imposed average forward speed of the pelvis as well as periodicity. We prescribed the participants’ walking speed in the simulations. Since we did not explicitly model contact between limbs, we used distance constraints scaled based on body height to prevent segments penetrating each other. We used a previously determined cost function [7], i.e. the integral of the weighted sum of squared metabolic energy rate ((:dot{E})), muscle activations ((:a)), joint accelerations ((:{u}_{a}^{})), and passive joint torques ((:{T}_{p}^{})):

where (:d) is the distance traveled, (:{t}_{f}) is gait cycle duration, (:t) is time, and (:{w}_{1}-:{w}_{4}) are weight factors, (:{M}_{subject}) is the mass of the subject, (:{L}_{subject}) is the height of the subject, and (:{M}_{DHondt{2024}_{}}) and (:{L}_{DHondt{2024}_{}}) are the mass and height of the generic model (described in detail below). Muscle metabolic energy was calculated using the model of Bhargava et al. [30], which was made continuously differentiable by approximating conditional statements with a hyperbolic tangent.

The resulting optimal control problems were solved using direct collocation (100 mesh intervals, 3 collocation points) and algorithmic differentiation. Problems were formulated and solved in MATLAB (R2021b, MathWorks Inc, Natick, Massachusetts, USA). Skeleton dynamics was formulated through OpenSimAD [31], CasADi [32] was used for problem formulation and algorithmic differentiation, and the resulting nonlinear programming problems were solved in IPOPT [33] (tolerance: 10⁻⁴). For each model, we used at least two initial guesses. The converged simulation with the lowest cost was chosen as final result.

Model personalization

We performed a series of simulations based on models with different levels of personalization to evaluate how musculoskeletal impairments affect the gait pattern. We divided the musculoskeletal impairments into muscle weakness, muscle contractures, and bony deformities. Muscle weakness and contractures were derived from the clinical examination. We derived bony deformities from the MR images using a previously developed approach to determine hip joint centers and knee axes as well as muscle-tendon paths of muscles spanning the hip and knee (but not the ankle) [13]. To investigate the contribution of these impairments as well as interaction effects, we created eight musculoskeletal models as described in Table 2.

Generic musculoskeletal model

All models were based on the model with a three-segment foot (talus, hindfoot-midfoot-forefoot, and toes) proposed by D’Hondt et al. [34]. The model has 31 degrees of freedom (DOFs) (pelvis-to-ground: 6 DOFs, hip: 3 DOFs, knee: 1 DOF, ankle: 1 DOF, subtalar: 1 DOF, metatarsophalangeal: 1 DOF, lumbar: 3 DOFs, shoulder: 3 DOFs, and elbow: 1 DOF). The lower limb and lumbar joints are actuated by 92 Hill-type muscle-tendon units [35, 36]. The MTP joint is actuated by a spring and damper. The shoulder and elbow joints are actuated by eight ideal torque actuators. Foot-ground contact is modeled by five Hunt-Crossley contact spheres per foot. Passive joint torques with exponential stiffness and damping [37] represent the effects of unmodeled passive structures in the lower limb and lumbar joints [7]. Muscle excitation-activation coupling was described by Raasch’s model [38, 39]. Skeletal motion was modeled with Newtonian rigid body dynamics [31, 40]. We removed quadratus femoris and gemellus because modeling bony deformities caused unrealistic operating ranges (>1.5 normalized fiber lengths) of these small muscles for some participants whereas removing both muscles from the generic model had little effect on the simulated gait pattern.

Reference model

The reference model (GEN) is the generic model described above scaled to the participant’s anthropometry using the OpenSim Scale Tool [9]. We additionally scaled maximal isometric force, which is not affected by scaling in OpenSim, based on subject mass [41]:

with (:{F}_{}^{max}) the maximal isometric force and (:M) the mass of the respective models. Parameters of the foot-ground contact model, and stiffness and damping of the joints, were also scaled based on the subject’s anthropometry (equations S1–S4). This model does not include impairments, with exception of leg length differences and was used as the basis for further personalization.

Modeling muscle weakness

To model muscle weakness, active fiber force was scaled based on the MMT scores from the clinical examination:

where (:{F}_{m}) is muscle force, (:{F}_{m}^{max}) is the maximal isometric force, (:sf) is the weakness scale factor, (:{f}_{m}^{act}) is the active muscle force-length-velocity characteristic, (:{stackrel{sim}{l}}_{m}) is normalized fiber length, (:{stackrel{sim}{v}}_{m}) is normalized fiber velocity, (:a) is muscle activation, and (:{f}_{m}^{pass}) is the passive muscle force-length characteristic. The weakness scale factors were determined semi-arbitrarily. We performed preliminary simulations with different sets of scaling factors, which were chosen based on intuition about how MMT scores would translate to reductions in strength. For four out of the eight participants we performed simulations with two different scaling sets [1.0, 0.7, 0.5, 0.3, 0.2, 0.1] and [0.7, 0.5, 0.3, 0.2, 0.1, 0.05] for MMT scores of 5, 4, 3, 2, 1, 0 combined with either the same or larger reductions in strength for plantar flexors and selected the set for which weakness explained most of their gait deficits. This resulted in scale factors for active fiber force of 0.7, 0.5, 0.3, 0.2, 0.1, and 0.05 for MMT scores of 5, 4, 3, 2, 1, 0, respectively. For plantar flexors, we reduced the scaling factor by one step (e.g. a score of 3 corresponds to a scaling factor of 0.2 instead of 0.3). We then applied the same scaling set for all participants. We grouped muscles to link the MMT scores to individual muscles. Hip muscles were divided into abductors (gluteus minimus and medius, tensor fascia latea and piriformis), adductors (adductors and pectineus), flexors (iliacus and psoas) and extensors (gluteus maximus and biceps femoris long head). Knee muscles were divided into flexors (remaining knee flexors attaching on pelvis or femur) and extensors (quadriceps). Muscles spanning the ankle were divided into plantar flexors (gastrocnemius medialis, gastrocnemius lateralis, soleus), dorsiflexors (tibialis anterior and toe extensor muscles), evertors (peronei) and invertors (toe flexors and tibialis posterior).

Modeling muscle contractures

Muscle fiber lengths have been observed to be shorter in CP [42]. Therefore, we chose to model contractures in the Hill-type muscles by reducing optimal fiber length. When optimal fiber length is reduced, muscle fibers will be stretched more at the same muscle-tendon length resulting in higher passive forces.

We only modeled contractures when there was a clinical indication (Fig. 1), i.e. clinical examination angles for passive range of motion were out of the typical range [43]. To determine the optimal fiber length for contracted muscles, we placed the musculoskeletal model in the same position as during the passive range of motion assessment and activated the muscle to 1%. We then determined the optimal fiber length such that the net modeled joint torque was 15 Nm at the end of range of motion.

Soleus length was scaled based on maximal dorsiflexion angle with the knee flexed to 90°. The gastrocnemii length was scaled based on maximal dorsiflexion angle with the knees fully extended. Knee flexor length was scaled based on the bilateral popliteal angle. We used the same scaling factor for all knee flexors, i.e. biceps femoris long head, semimembranosus, semitendinosus, gracillis and sartorius. To obtain scaling factors for rectus femoris, we translated the score of the slow Duncan-Ely test to fixed scaling factors since one score allows for a wide range of knee flexion angles. For score 0 scaling was 1, for score 1 scaling was 0.9, and for score 2 scaling was 0.8 of nominal optimal fiber length.

We used a different approach to model iliopsoas contractures as their assessment is different. Iliopsoas contractures will lead to a different uni- ((:{theta:}_{uni})) and bilateral ((:{theta:}_{bi})) popliteal angle, that is the knee angle at maximal extension when the individual is supine with the thigh of the evaluated limb or both thighs vertical. When assessing the unilateral popliteal angle, the contralateral leg is laying down. Iliopsoas contractures will cause flexion of the contralateral hip and this will be compensated for by anterior pelvis tilt, which in turn will lead to increased hip flexion to position the thigh of the evaluated leg vertically. Increased hip flexion will in turn increase bi-articular hamstrings length and will thus lead to a larger knee extension deficit. The increase in hip flexion angle was determined based on the difference in popliteal angles and the ratio of the average moment arms of all bi-articular hamstrings with respect to the knee and hip:

with n the number of bi-articular hamstrings, and (:{ma}_{knee,i}) and (:{ma}_{hip,i}) the moment arm of muscle i around knee and hip when in the position of the bilateral popliteal angle. We then determined the contracture of the contralateral iliopsoas by solving for the scaling factor that led to passive torque when the contralateral hip was extended beyond (:varDelta:{theta:}_{hip}).

Observed knee extension and plantar flexion deficits were modeled by shifting the coordinate limit torques that model the stiffness of the non-muscle soft tissues around the joint. For the knee, we shifted the limits such that torque started to develop at the observed angle for knee extension minus two degrees to obtain around 15 Nm torque at end range of motion. We modeled plantar flexion deficits based on the reported range of motion for the ankle towards plantar flexion. The onset of the coordinate limit torques was changed to 25° plantar flexion or 0° when the score was respectively ‘discrete’ or ‘severe’.

Modeling bony deformities

Bony deformities were modeled based on the MR images. First, bones were segmented with Materialise Mimics (Materialise, Leuven, BE). Further processing was performed in MuscleSegmenter [13]. We determined the pelvic frame based on anatomical landmarks of the pelvis and located the glycerin markers. Next, the hip joint center was estimated by fitting a sphere to the femoral head. Then, reference frames of the femur, patella and tibia were determined based on anatomical landmarks. Next, the knee joint axis was determined based on fitting two ellipsoids to the condyles and visual inspection (congruence of joint contact surfaces) of the knee motion. Next, the paths of muscles spanning the hip and knee as well as the attachment points of the gastrocnemii on the femur were segmented. Muscle paths were chosen such that they approximated the centroid of the muscle belly. Next, the scaled generic model was updated by replacing the original joint centers, marker locations, and muscle paths by the values obtained from the MR images followed by linear scaling of optimal fiber lengths and tendon slack lengths (similar to the OpenSim Scale Tool) through a custom-made MATLAB (R2021b, MathWorks Inc, Natick, Massachusetts, USA) script.

Strength deficits observed during MMT can be due to both moment arm deficits or reduced muscle force generating capacity. The MRI-informed models already capture weakness due to moment arm deficits. Therefore, we modified the weakness scale factor derived from MMT to correct for weakness due to moment arm deficits:

with (:{sf}_{geo}) the corrected weakness scale factor to be used in the model with bony deformities, (:sf) the weakness scale factor derived from MMT, (:{T}_{max}^{GEN}) the maximal torque the muscle group could generate in the GEN model, and (:{T}_{max}^{GEO}) the maximal torque the muscle group could generate in the GEO model. The ratio between(::{T}_{max}^{GEO}) and (:{T}_{max}^{GEN}) thus reflects the moment arm deficit (Table S8). (:{T}_{max}^{}) was evaluated with the model in the same position as during MMT and agonist muscles activated to 100%.

Since muscle-tendon paths differ in the GEO model compared to GEN, we estimated contractures in both models separately.

Outcome measures and statistical analysis

Experimental kinematics were calculated from marker trajectories collected during walking at self-selected speed based on the GEO model with OpenSim’s Inverse Kinematics Tool. Means and standard deviations of the experimental gait were calculated based on five to ten strides per side. Walking speed was determined based on the average forward speed of the posterior pelvis marker over at least four strides.

Root Mean Square Differences (RMSD) and Pearson correlations (r) were calculated between simulated and mean experimental kinematics for hip flexion, hip adduction, hip rotation, knee flexion and ankle dorsiflexion. We calculated the mean RMSD and correlation over all sagittal and non-sagittal plane degrees of freedom for each subject-model pair. Differences in median and interquartile range (IQR) between GEN and the other models were used to interpret the contribution of the modeled impairments to the altered gait. The minimal important difference for RMSD was defined to be 1.6° [44]. We deemed differences in correlation of 0.05 practically relevant for this study.

We tested whether personalized models better captured the experimental data than the generic model (GEN) using SPM1D [45] to analyze differences in the deviation of simulated from experimental kinematics between GEN and each of the personalized models. We used the paired t-test from the SPM1D Matlab package with two-tailed inference at alpha 0.05 [46]. We performed the analysis for each degree of freedom separately, but we combined trajectories from left and right legs. As our study design resulted in many different models to assess contributions of different impairments, the statistical analysis should be considered exploratory, i.e. we did not correct for multiple comparisons. We reported the statistical parametric map of t-values (SPM{t}) as well as p-values over intervals where the agreement between modeled and simulated kinematics differed between models (Figs. S4, S5) .

We determined the contribution of impairments to RMSD and correlations between simulated and experimental gait kinematics using Shapley values [47]. We computed Shapley values to quantify the contribution of weakness, contractures, bony deformities and any combination of two of these impairments. Shapley values are a weighted average of the marginal contribution of an impairment or set of impairments across all model combinations that differ in the impairments under investigation. Marginal contributions with respect to the generic model and fully personalized model are weighed more heavily (see supplement Sect. 9 for additional information).

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MIAMI, Oct. 28, 2025 /PRNewswire/ — Oceania Cruises^®, the world’s leading culinary- and destination-focused luxury cruise line, invites travelers to experience the ultimate global journey aboard the luxurious Oceania Vista during its 2027 Around the World cruise. In addition to options ranging from 127 days to more than eight months, the once-in-a-lifetime 244-day voyage has been thoughtfully divided into 17 immersive segments ranging from 9 to 20 days, offering guests the opportunity to experience the world on their own terms and at their own pace.

Featuring more than 125 ports across 53 countries, OceaniaVista‘s leisurely sojourn is not just a world cruise; it is a meticulously curated mosaic of cultures, cuisines and coastlines. Reflecting the line’s commitment to explore Your World. Your Way^®, the diverse segments allow guests to tailor a personalized journey to fit their timeline, offering them the luxury of choice to create their ideal voyage – from the incredible destinations they choose to visit, to the small-group immersive tours ashore, to enjoying the always included selection of gourmet specialty restaurants while on board the elegantly refined Oceania Vista.

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“While our Around the World cruise is an incredible way to explore the world in style, we understand that not all guests have the time to enjoy a 244-day sailing,” said Jason Montague, Chief Luxury Officer of Oceania Cruises. “To make the wonders of the world more accessible while catering to our guests’ varying lifestyles, Oceania Cruises is thrilled to offer this epic Around the World journey, also available as a series of segmented itineraries, each offering the same unparalleled luxury, personalized service and immersive destination experiences at sea.”

As guests embark on their journey, Oceania Vista will serve as a luxurious home base, blending refined luxury with a welcoming sense of comfort. On board, guests will enjoy spacious all-veranda accommodations, warm and intuitive onboard service, and exquisite dining experiences, including four always included specialty restaurants: Toscana, the line’s signature Italian restaurant; pan-Asian venue Red Ginger; Jacques, serving classic and contemporary French bistro dishes; and Polo Grill steakhouse. Plus, the ship offers enriching activities such as hands-on cooking classes at The Culinary Center, art workshops in the Artist Loft and engaging guest speakers, along with serene spaces like the top-of-ship library and Aquamar^® Spa + Vitality Center with its tranquil terrace.

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Treasures of Two Oceans:

 15 days from Miami to Los Angeles, visiting George Town, Cayman Islands; Cartagena, Colombia; Puerto Quetzal, Guatemala; Acapulco and Cabo San Lucas, Mexico; San Diego, California. Departs Jan. 6, 2027.

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 18 days from Los Angeles to Papeete, visiting Kahului, Maui; Nawiliwili, Kauai; Honolulu, Oahu; Hilo, Hawaii; Bora Bora, Raiatea and Moorea, French Polynesia. Departs Jan. 21, 2027.

Koalas to Komodos


: 15 days from Sydney to Bali, featuring one overnight in Cairns and Darwin, Australia and visiting Sydney, Mooloolaba and Whitsunday Island, Australia; Komodo, Lombok and Bali, Indonesia. Departs Feb. 26, 2027.

Koi Ponds to Kimonos


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Arabian & Aegean Gems: 20 days from Doha to Athens, featuring one overnight in Luxor (Safaga), Egypt, visiting Dubai, United Arab Emirates; Salalah, Oman; Jeddah, Saudi Arabia; Aqaba, Jordan; Sharm el Sheikh and Ain Sokhna, Egypt; Limassol, Cyprus; Rhodes, Greece; Ephesus, Turkey. Departing May 13, 2027.

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Untamed North Atlantic: 17 days from Reykjavik to New York, visiting Grundarfjordur, Iceland; Cruising Prince Christian Sound; Paamiut and Nuuk, Greenland; Corner Brook, Newfoundland; Charlottetown, Prince Edward Island; Sydney and Halifax, Nova Scotia; Boston, Massachusetts. Departing Aug 21, 2027.

Shipboard Highlights of OceaniaVista
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An epic journey calls for an equally exceptional ship, and OceaniaVista delivers with unmatched elegance and charm.

• The 1,200-guest ship offers all-veranda accommodations, featuring the most spacious standard staterooms at sea, at an astounding 291 square feet.
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• Oceania Vista offers an elegant onboard experience with 8 sophisticated bars, lounges and entertainment venues.
• Thousands of immersive small-group shore excursions and tours to choose from in destinations across the globe, offering the opportunity to see destinations through a new lens, whether the focus is food, wine, art, history or architectural design.
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For additional information on Oceania Cruises’ Small Ship Luxury™, exquisitely crafted cuisine, and expertly refined travel experiences, visit OceaniaCruises.com, call 855-OCEANIA, or speak with a professional travel advisor.

About Oceania Cruises
Oceania Cruises^® is the world’s leading culinary- and destination-focused luxury cruise line. The line’s eight small, luxurious ships carry a maximum of 1,250 guests and feature The Finest Cuisine at Sea^® and destination-rich itineraries that span the globe. Expertly curated travel experiences are available aboard the designer-inspired, small ships, which call on more than 600 marquee and boutique ports in more than 100 countries on seven continents, on voyages that range from seven to more than 200 days. Oceania Cruises® has four Sonata Class ships on order scheduled for delivery in 2027, 2029, 2032, and 2035. Oceania Cruises® is a wholly owned subsidiary of Norwegian Cruise Line Holdings Ltd. (NYSE: NCLH). To learn more, visit www.nclhltd.com.

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