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Biomarker Analysis from Patients with Metastatic PDAC Treated with TGFβ Antibody NIS793 plus Abraxane + Gemcitabine versus Abraxane + Gemcitabine Alone in a Phase II, Open-Label, Randomized Study.

PURPOSE: Transforming growth factor β (TGFβ) plays a dual role in cancer, acting as a tumor suppressor early in the disease but promoting progression and immune evasion when dysregulated. In pancreatic ductal adenocarcinoma (PDAC), TGFβ-driven desmoplasia fosters chemoresistance and immunosuppression, limiting therapeutic efficacy. NIS793, a fully human mAb targeting TGFβ, demonstrated antifibrotic and immunomodulatory activity in preclinical models and early-phase trials. PATIENTS AND METHODS: We conducted a randomized, open-label, phase II study in treatment-naïve patients with metastatic PDAC (mPDAC) to evaluate NIS793 ± spartalizumab (anti-PD-1) combined with nab-paclitaxel (or Abraxane)/gemcitabine (ABRA/GEM) versus ABRA/GEM alone. The primary endpoint was progression-free survival (PFS); secondary endpoints included overall survival (OS), safety, pharmacokinetics, and biomarker analyses. Exploratory assessments included paired tumor RNA sequencing, cell-free DNA profiling, and plasma proteomics. RESULTS: NIS793 demonstrated target engagement and suppression of TGFβ signaling, confirmed by transcriptomic and proteomic analyses. Stromal remodeling was evident, with significant downregulation of cancer-associated fibroblast markers (Acta2, Fap) and collagen-related signatures. Despite proof of mechanism, clinical efficacy was not observed: Median PFS and OS were comparable or numerically worse in the NIS793 arm versus control (HR for OS in NIS793 + ABRA/GEM vs. ABRA/GEM: 1.32; 95% confidence interval, 0.84-2.07). The safety profile was manageable, with no unexpected toxicities. Biomarker data revealed increased expression of neutrophil-related genes after treatment, suggesting potential induction of tumor-promoting inflammation. CONCLUSIONS: NIS793 effectively inhibited TGFβ signaling and led to stromal remodeling but failed to improve outcomes in mPDAC. These findings highlight the complexity of TGFβ biology and caution against its blockade in combination with chemotherapy for PDAC. Future strategies should consider context-dependent effects of TGFβ inhibition.

Humans

Intravesical mitomycin-C administered immediately before transurethral resection of bladder tumor in non-muscle-invasive bladder cancer: Clinical outcomes and molecular predictors from over 3 years of extended follow-up in a phase II trial.

PURPOSE: To evaluate the long-term outcomes and molecular correlates of response after immediate preoperative intravesical chemotherapy (IPeIC) with mitomycin-C (MMC) in patients with non-muscle-invasive bladder cancer (NMIBC). MATERIALS AND METHODS: In this single-center, open-label, randomized phase II trial, 33 patients received two split doses of IPeIC/MMC (40 mg/20 mL), whereas 38 patients underwent transurethral resection of bladder tumor (TURBT) alone. The primary endpoint was 3-year recurrence-free survival (RFS), and secondary endpoints included progression-free survival (PFS). Exploratory RNA sequencing was performed on IPeIC-treated patients (three with recurrence, 25 without) using a Monte Carlo-based resampling strategy. RESULTS: The median follow-up durations were comparable between the intervention (60.0 months) and control arms (60.4 months). IPeIC/MMC reduced recurrence risk by 76.8% versus TURBT alone (p=0.024), yielding a 3-year RFS rate of 90.7% versus 78.6%. On multivariable analysis, IPeIC/MMC independently improved RFS (hazard ratio [HR] 0.266, p=0.044). IPeIC was associated with superior PFS, with 3-year and 5-year rates of 100% versus 92.1% and 85.8%, respectively, in the controls (HR 0.078, p=0.014). Exploratory transcriptomics identified low Glutathione S-transferase Mu 1 (GSTM1) expression as the factor most strongly associated with recurrence. CONCLUSIONS: IPeIC/MMC is associated with improved long-term oncological outcomes compared with TURBT alone and represents a safe prophylactic option for patients with NMIBC who are unable to receive standard immediate postoperative intravesical chemotherapy because of safety concerns or practical constraints. The GSTM1 findings are hypothesis-generating and support future biomarker-driven validation studies.

Aged

Multi-omics panorama of glaucoma: Pathogenesis, biomarkers, and novel therapeutic strategies.

Glaucoma is a group of irreversible, blinding eye diseases characterized by progressive loss of retinal ganglion cells, leading to gradual visual field defects that severely impact patients' quality of life. Its complex pathophysiological mechanisms remain incompletely understood, limiting the development of early diagnostic and effective therapeutic strategies. Advances in omics technologies have provided new insights into elucidating the pathophysiology of glaucoma. We summarize specific alterations in genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics associated with glaucoma. We emphasize the systematic analysis of disease mechanisms, identification of clinically applicable biomarkers, and discovery of novel therapeutic targets through the integration of these data. This approach paves new pathways for glaucoma subtype diagnosis and personalized treatment, while also outlining future research directions and challenges.

Humans

RENOIR phase 3 rituximab-lenalidomide vs rituximab as maintenance treatment in relapsed/refractory follicular lymphoma.

Maintenance treatment in older patients with relapsed or refractory (R/R) follicular lymphoma (FL) remains an area of investigation. RENOIR was a multicenter, phase 3, open-label randomized trial conducted by the Fondazione Italiana Linfomi (FIL) in older patients with R/R FL after 1 or 2 previous therapies. Patients achieving partial response or complete response (CR) after 4 to 6 cycles of standard rituximab (R)-based chemotherapy were randomized 1:1 to maintenance with R alone (standard arm) or R plus lenalidomide (R2; experimental arm). The primary end point was 2-year progression-free survival (PFS) from randomization, with an expected hazard ratio (HR) of 0.5. A total of 152 patients (median age, 71 years) were enrolled. After induction, 129 (85%) achieved an overall response (CR, 58%) and were randomized to R (n = 65) or R2 (n = 64). At a median follow-up of 68 months, the 2-year PFS was 73% in the R2 arm and 64% in the R arm. An unplanned hypothesis-generating subgroup analysis showed a greater 2-year PFS benefit with R2 in patients aged <70 years: R2, 96% vs R, 69%. Two-year overall survival rates were similar (R2, 80% vs R, 89%). Grade 3/4 adverse events were more frequent in R2, mainly neutropenia and gastrointestinal disorders. In conclusion, the primary end point of the study was not met, and R2 maintenance did not significantly improve 2-year PFS in older patients with R/R FL, although a numerical benefit was observed. R2 showed a more favorable benefit-risk profile in patients aged <70 years, whereas in older patients careful consideration of individual tolerability is warranted. This trial was registered at www.clinicaltrials.gov as NCT02390869.

Humans

Ketamine assisted psychotherapy to reduce chronic neuropathic pain: A mixed-methods randomized pilot trial.

BACKGROUND: Intravenous ketamine can provide short-term analgesia in chronic neuropathic pain but benefits often wane after treatment. We conducted a randomized pilot trial to assess the feasibility of combining ketamine infusions with psychotherapy to inform future efficacy trials. METHODS: In this single-center, randomized, outcome-assessor-blinded pilot trial at a Canadian tertiary pain clinic, adults with moderate-to-severe chronic neuropathic pain were randomly assigned in 1:1:1 ratio to the ketamine, psychotherapy, or combined ketamine plus psychotherapy arm. Ketamine was delivered as three intravenous infusions over 16 weeks; psychotherapy consisted of 16 weekly cognitive behavioral therapy and mindfulness-based meditation sessions. The primary outcome was feasibility, assessed using prespecified progression criteria. Exploratory outcomes included changes in pain interference (PROMIS 6a T-score), pain intensity, mood, and qualitative interview findings at week 20 (ClinicalTrials.gov: NCT05639322). FINDINGS: Between October 23, 2023, and March 31, 2025, 30 participants were randomized, and 26 (87%) completed 20-week follow-up. Most feasibility criteria, including consent, retention, data completeness, and absence of study-related serious adverse events, were met; adherence targets were partially met. Exploratory pain outcomes showed numerical improvement across groups, with clinically meaningful reductions observed for pain interference and pain intensity. Sixty-four adverse events were recorded, mostly mild and in ketamine-containing groups; no serious study-related adverse events occurred. CONCLUSIONS: Combined ketamine and psychotherapy was feasible and acceptably safe in this pilot trial, supporting evaluation in a larger efficacy-powered study. FUNDING: The study was funded by the St. Michael's Hospital Innovation Fund, The Canadian Pain Society Early Investigator Award and the Physician Services Incorporation Early Career Researcher Award.

Humans

Candidate biomarkers for early Giardia duodenalis infection revealed by time-resolved secretome proteomics.

Giardia duodenalis is a zoonotic protozoan parasite that causes giardiasis in humans and other mammals. Early diagnosis remains challenging because current diagnostic methods, including microscopy and enzyme-linked immunosorbent assays (ELISAs), primarily detect established infections. Consequently, a critical diagnostic gap exists during the early stage of infection within the first 2-48&#xa0;h following exposure. To address this limitation, we characterized the proteins released by in vitro-cultured G. duodenalis trophozoites under serum-free conditions and evaluated their potential as early diagnostic biomarkers. Proteomic analysis of culture supernatants collected during early trophozoite incubation identified 31,773 peptides corresponding to 2504 quantifiable proteins. Temporal profiling showed distinct secretion patterns, including proteins that peaked during the early stage, progressively accumulated over time, or remained persistently abundant throughout the incubation period. Based on their secretion characteristics and predicted immunogenic properties, five candidate biomarkers were selected for further evaluation. Polyclonal antibodies raised against selected candidates successfully detected the corresponding proteins in serum-free culture supernatants, providing preliminary evidence for their potential utility as early-stage diagnostic targets. These findings identify stage-associated candidate proteins that may serve as a resource for future early giardiasis diagnostic development, provide a valuable resource for investigating host-parasite interactions, and establish a foundation for future diagnostic assay development. However, further validation in clinical and biological samples is required to confirm their diagnostic applicability. SIGNIFICANCE: Giardiasis, caused by Giardia duodenalis, is a major diarrheal disease worldwide. Although enzyme-linked immunosorbent assays (ELISAs) provide rapid detection, their diagnostic utility is limited by the lack of biomarkers capable of identifying infection during its earliest stages, creating a critical gap in the detection of active infection within 2-48&#xa0;h following exposure. Using data-independent acquisition proteomics, this study provides a time-resolved characterization of proteins released by G. duodenalis trophozoites into serum-free culture supernatants. Our findings reveal temporal secretion dynamics of protein secretion and identify candidate biomarkers with potential utility for the development of early-stage diagnostic assays pending rigorous biological and clinical validation. In addition, this proteomic resource provides a foundation for investigating host-parasite interactions and may facilitate the development of future point-of-care diagnostic strategies.

Giardiasis

Spinal meningiomas: histopathological grading using a benchmark radiomics model with notes on disease control.

OBJECTIVE: Spinal meningiomas (SMs) are common primary spinal tumors for which surgery is considered the first-line treatment when safe and feasible. The ability to extrapolate the tumor grade from preoperative imaging may significantly inform early patient expectation-setting regarding recurrence. Building on radiomics studies in cranial meningiomas, the authors aimed to construct a benchmark radiomics model to preoperatively identify the histological grade of SMs. METHODS: Institutional surgical records from May 2012 to November 2025 were queried for pathology-confirmed meningiomas below the foramen magnum, with preoperative contrast-enhanced imaging available for segmentation. SMs were classified as low-grade (WHO grade 1) and high-grade (WHO grade 2 tumors and grade 1 tumors with atypia). Tumors were manually segmented, and features were extracted using the PyRadiomics software package. An ensemble model of k-nearest neighbors, random forest, and support vector machine classifiers was trained using nested cross-validation on a subset of 10 features to differentiate tumor grades. Clinical data for the cohort were also extracted, and disease control in an adjunctive clinical series was assessed. RESULTS: Seventy-four patients were included in radiomics analysis, with an area under the receiver operating characteristic curve of 0.879 and a mean F1 score of 0.748. The model's top 5 features were all texture features that differed significantly (p < 0.05) across low- and high-grade SMs. These included measures of tumor textural and contrast-enhancement heterogeneity, with overlap with features reported in radiomics models for histological grading of intracranial meningiomas. Fifty-five patients with a median radiographic follow-up of 22.2 (range 1.9-86.4) months remained for clinical analysis after exclusion of patients with less than 1 month of follow-up and syndromic meningiomas. Four recurrences occurred at a median of 20.8 (range 1.8-41.8) months. High-grade tumor pathology did not significantly impact progression-free survival (p = 0.682, log-rank test; Cox regression high vs low grade hazard ratio [HR] 0.62, 95% CI 0.06-6.11, p = 0.685). Subtotal resection was associated with poorer progression-free survival than gross-total resection (p = 0.004, log-rank test; Cox regression subtotal vs gross-total resection HR 10.62, 95% CI 1.46-77.05, p = 0.019). These findings remain contextualized within a relatively limited follow-up window and small recurrence event count, suggesting a need to characterize the interplay between tumor grade and extent of resection as drivers of local disease control in SMs. CONCLUSIONS: A preoperative radiomics model can stratify high-grade SMs using open-source tools applied to single-institution data.

Humans

Retinoid dynamics in immune cells during age-related diseases.

Retinoids comprise vitamin A and its structurally related natural and synthetic derivatives. Retinoid dynamics involves multiple retinoid forms, carrier proteins, and enzymes that orchestrate the absorption, transport, storage and biotransformation of dietary vitamin A. Beyond their canonical metabolic functions, metabolites and proteins involved in retinoid metabolism also play distinct roles in signal transduction and transcriptome reprogramming, broadening the mechanisms that influence immune cell fate decisions. Age&#x2011;related changes in retinoid bioavailability and signaling intensity alter immune cell polarization and function, thereby contributing to the pathogenesis of chronic inflammation in neurodegenerative diseases, cardiovascular diseases, osteoarthritis, and other age-related diseases. In this review, we focus on age-related alterations in the retinoid metabolic pathway and their impact on inflammation and the progression of age-related diseases. This review highlights the pivotal role of retinoid metabolism in anti-ageing interventions and considers future directions and challenges in this field.

Humans

Distinct functions of mammalian RAD51 paralogs in genome maintenance.

RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3) are evolutionarily conserved essential proteins for cell survival and genome maintenance. RAD51 paralogs were originally identified to play a role in homologous recombination-mediated repair of DNA double-strand breaks (DSBs). However, investigations over the last decade have uncovered new roles of RAD51 paralogs beyond DSB repair in replication stress responses, including replication fork progression, fork stability, and its restart. Recent structural studies have not only uncovered the molecular architecture of previously known RAD51 paralog complexes but also identified novel paralog complex assemblies, providing mechanistic insights into their various genome-maintenance functions. Additionally, a role for RAD51 paralogs in resolving R-loops has been identified, and studies with cancer-associated variants suggest that RAD51 paralogs are potential determinants of cancer susceptibility and therapeutic responses. In the present review, we highlight the recently deciphered structures and novel functions of RAD51 paralog complexes and discuss the clinical and therapeutic implications.

Rad51 Recombinase

Transcription regulation of cell fate plasticity - from embryonic development to tissue regeneration.

Cell fate plasticity refers to the capacity of cells sharing the same genome to alter, reverse, or reconfigure their identity under physiological, pathological, or experimental conditions. This property underlies embryonic development, cellular reprogramming, and tissue regeneration, but becomes progressively restricted as lineage identity is stabilized. Embryonic development represents an intrinsic process of fate transitions, whereas reprogramming and regeneration reveal how differentiated cells can dedifferentiate or transdifferentiate under specific conditions. Across these contexts, plasticity is governed by multilayered regulatory networks involving transcription factors, epigenetic regulators, cofactors, and the core transcription machinery. Robust regulatory programs stabilize cell identity, whereas stochastic fluctuations in gene expression and chromatin state can prime cells for fate transitions, adding a tunable dimension to plasticity control. In this review, we synthesize recent advances in the regulation of cell fate plasticity across development, reprogramming, and regeneration, highlighting how transcription factors, epigenetic modifications, transcriptional cofactors, and core transcription machinery cooperate to control cell fate decisions and plasticity.

Animals

Efficacy, tolerability, and threshold effect of atropine eye drops for myopia control: A systematic review and dose-response meta-analysis.

Atropine is an emerging therapy for myopia, yet the optimal concentration for prescription remains uncertain. We searched PubMed, Embase, Web of Science, Cochrane Library, World Health Organization International Clinical Trials, and ClinicalTrials.gov registry platforms. We included the randomized clinical trials (RCTs) that compared any dose of atropine against a placebo in myopic children. Among 3566 studies assessed, we identified 33 eligible RCTs involving 6301 children aged 4-18 years, with 10 different concentrations and a mean follow-up time of 19.5&#x202f;&#xb1;&#x202f;12.3 months. A nonlinear relationship was observed between atropine dosage and treatment efficacy (P&#x202f;<&#x202f;0.001). Compared to placebo groups, the mean differences in reducing annual spherical equivalent refraction progression for atropine concentrations of 0.01%, 0.02%, 0.03%, 0.04%, and 0.05% were 0.21 diopters (D) (95% CI, 0.13-0.28), 0.35 D (95% CI, 0.23-0.46), 0.42 D (95% CI, 0.28-0.56), 0.45 D (95% CI, 0.30-0.60), and 0.46 D (95% CI, 0.32-0.61) respectively For higher concentrations, the estimates were 0.49 D (95% CI, 0.34-0.63) for 0.1% and 0.99 D (95% CI, 0.66-1.31) for 1%, although these were based on fewer and smaller trials. Higher doses of atropine were associated with decreased amplitude of accommodation (P&#x202f;=&#x202f;0.02), increased pupil diameters (P&#x202f;=&#x202f;0.01) and a higher frequency of photophobia (P&#x202f;=&#x202f;0.02). Our findings suggest that the increase in treatment efficacy with higher concentrations may plateau beyond a certain range, and that the current practice of increasing atropine concentrations for children who show inadequate responses to lower doses should be confined to a specific concentration range. This analysis is limited by the number, design heterogeneity, and sample sizes of available trials for higher concentrations, and by the frequent lack of pre-intervention refractive history in included studies. Therefore, estimates-particularly for doses exceeding 0.1%-should be interpreted with caution.

Humans

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (&#x394;AUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry

Induced degradation of Ufd1 reveals regulation of cohesin by the VCP/p97Ufd1-Npl4 complex.

The AAA ATPase VCP/p97 has emerged as a critical regulator of ubiquitin and chromatin-associated processes but progress in understanding has been hampered by the complexity of p97 functions and the various p97 cofactors involved. Here, we combined ubiquitin profiling with acutely induced degradation of the Ufd1 subunit of the p97 ubiquitin adapter, Ufd1-Npl4, in human cells. We identified a set of chromatin regulators, HUS1, XRCC1, MORF4L1, and the cohesin subunit RAD21 as targets of p97Ufd1-Npl4 We find that RAD21 is ubiquitylated and targeted by p97Ufd1-Npl4 specifically in S phase to remove a subpopulation of cohesin from chromatin. Acute degradation of Ufd1 in S phase, after replication licensing is completed, impedes replication and leads to replication-associated DNA damage. Our findings suggest that a fraction of cohesin rings need to be removed by p97Ufd1-Npl4 from DNA to allow unhindered replication and reveal a critical function of p97 that ensures genome stability.

Cell Cycle Proteins

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon sources, particularly for hydrophobic carbon sources, coupled with robust growth and diverse biosynthetic capacities, making them promising hosts for sustainable production of chemicals, fuels, and proteins. Despite these advantages, industrial deployment of Candida species has been hindered by concerns regarding opportunistic pathogenicity and the historical lack of efficient genetic manipulation tools, leading to a substantial gap between metabolic potential and practical utilization. Recent advances in functional genomics, genome editing, and systems metabolic engineering are rapidly overcoming these barriers, enabling more precise and efficient strain development. In this review, we systematically summarize recent progress in the metabolic engineering of Candida species as microbial cell factories, with particular emphasis on expanding genetic toolkits, utilizting renewable and non-conventional carbon sources, and biosynthesizing high-value compounds. In addition, we propose a biosafety-oriented classification framework to support their safe industrial deployment. Finally, we discuss current challenges and emerging opportunities, emphasizing that the synergy of synthetic biology and artificial intelligence-driven design holds the key to unlocking the biotechnological potential of Candida yeasts.

Candida

Insights into the regulation of the HOTAIR proximal promoter.

HOTAIR (HOX transcript antisense RNA) is a HOXC-cluster long intervening non-coding RNA (lincRNA) whose cancer relevance is tightly coupled to how its transcription is wired into hormone, hypoxia, inflammatory, and developmental signaling. HOTAIR is known to associate with cancer cell proliferation, motility, tumor invasion, and metastasis. The present mini-review focuses on the regulatory architecture and mechanistic complexity of HOTAIR transcriptional regulation, with emphasis on three organizing principles. First, we consider the impact of promoter choice between a canonical proximal promoter (P1), which supports the 2.2-2.4 kb transcript, and an alternative upstream promoter/TSS (P2), which contributes to context-dependent transcription initiation. Second, we examine the long-distance enhancer-promoter communication between HOTAIR distal enhancer and P1/P2. Third, we summarize the recent epigenetic and epi-transcriptomic mechanisms involved in HOTAIR transcript initiation and elongation. A combination of these events determines isoform-specific transcription to govern cell-type-, context-, and cancer specific modulation of HOTAIR expression that promotes tumor formation and cancer progression. Finally, the review proposes how large-scale RNA datasets, long-read sequencing, and isoform-specific studies can refine our understanding of this versatile lincRNA's regulation.

Humans

Structured robotic colorectal training in a non-tertiary NHS hospital: a 502-case consecutive cohort implementation study.

Robotic-assisted colorectal surgery has expanded rapidly across NHS practice in the UK. Structured unit-wide training pathways are essential for safe technology adoption, yet published outcome data from non-tertiary hospitals remain limited. This study describes the implementation and feasibility of a unit-wide robotic colorectal program at a high-volume non-tertiary hospital, reporting outcomes across 502 consecutive resections performed by eight consultant surgeons and presenting these in the context of nationally published benchmarks. A retrospective cohort study of 502 consecutive robotic colorectal resections performed at York Teaching Hospital between May 2022 and December 2025. Eight consultant surgeons (A-H) participated in a structured four-phase training pathway incorporating simulation training, proctored cases, complexity-based case progression, and formal credentialing. Primary outcomes were 30-day mortality, unplanned return to theatre (RTT), and anastomotic leak (AL). Anastomotic leak was calculated using only patients who underwent anastomosis as the denominator. Procedure-stratified and individual surgeon outcomes with 95% confidence intervals were reported. Risk-adjusted cumulative sum (RA-CUSUM) analysis was performed to evaluate learning curves. Outcomes are presented descriptively alongside nationally published reference data; no formal statistical comparison against national benchmarks was performed. 502 robotic colorectal resections were performed. Mean patient age was 70.0 &#xb1; 11.3&#xa0;years; 58.4% were male. Median ASA grade was III. The indication was malignancy in 89.2% of cases. Length of stay was non-normally distributed and is therefore reported using median and interquartile range in the revised analysis. Key outcomes: - 30-day mortality: 1.0% (5/502; 95% CI 0.4-2.3%) - Unplanned return to theatre (RTT): 5.2% (26/502; 95% CI 3.6-7.5%) - Anastomotic leak (AL): 3.3% (15/450; 95% CI 2.0-5.5%; denominator = patients with anastomosis) - 30-day unplanned readmission: 5.0% (25/502; 95% CI 3.4-7.2%) - Conversion to open surgery: 3.6% (18/502; 95% CI 2.3-5.6%) - Lymph node yield &#x2265;12: 91.3% of cancer resections - R0 resection rate: 95.1% of cancer resections All primary outcomes fell within or below the published reference ranges used for descriptive context. RA-CUSUM trajectories were heterogeneous: no surgeon crossed the predefined upper control limit, but several curves showed later upward movement. Accordingly, the analysis is interpreted as safety surveillance rather than evidence of uniform performance improvement. RA-CUSUM monitoring showed that no surgeon crossed the predefined upper control limit; however, heterogeneous trajectories precluded a claim of uniform performance improvement.

Humans