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PubMed2026

Biologic-biologic and biologic-JAK inhibitor combination therapy in refractory systemic autoinflammatory diseases.

OBJECTIVES: Systemic autoinflammatory diseases (SAIDs) arise from genetic defects in innate immunity, leading to dysregulated activation of inflammatory pathways, including interleukin (IL)-1, IL-6, TNF, and JAK/STAT. Clinical manifestations range from recurrent fever to severe complications such as encephalitis and AA amyloidosis. Management aims to control inflammation using immunosuppressive agents and targeted monotherapies (biologics or JAK inhibitors). Advanced combination therapy (ACT), defined as the use of biologics and/or JAK inhibitors in combination, has emerged as a strategy for refractory disease. METHODS: In this observational retrospective longitudinal cohort study, patients with SAIDs treated with ACT were included. Demographic, clinical, treatment, and safety data were collected. Treatment response was assessed using a composite outcome incorporating corticosteroid dose, C-reactive protein (CRP), and clinical improvement and categorized as non-response, partial response, or complete response. RESULTS: Thirty-eight patients (median age 30 years [range 4-76]) were included. The most common indications for ACT were pyogenic arthritis, pyoderma gangrenosum and acne (PAPA), mevalonate kinase deficiency (MKD), and undifferentiated SAIDs. Most patients had disease-related complications and were dependent on glucocorticoids and/or opioids to control inflammation and pain, respectively. Following multiple ACT trials, complete response was observed in 21 patients (55.3%), partial response in 12 (31.6%), and no response in 5 (13.1%). Overall, 65 ACT regimens were administered, most commonly combining IL-1 and TNF inhibitors. Thirty-nine regimens were discontinued because of lack of efficacy, secondary loss of response, or adverse events. At the final follow-up, 26 patients (68%) remained on ACT, with a median treatment duration of 60 months (range, 11-186). CONCLUSIONS: ACT offers significant clinical benefits for patients with difficult-to-treat SAIDs, though challenges such as secondary loss of efficacy and infection risks remain.

Humans↗
PubMed2026

Longitudinal comparison of treat-to-target states and clinical outcomes in patients with late-onset versus early-onset systemic lupus erythematosus.

OBJECTIVE: We compared demographic and clinical characteristics between patients with late-onset (LO) and early-onset (EO) systemic lupus erythematosus (SLE) and examined their longitudinal associations with treatment targets and long-term outcomes, irreversible organ damage accrual and health-related quality of life (HRQoL). METHODS: We analyzed prospectively collected data from patients enrolled in the Asia Pacific Lupus Collaboration cohort. Patients diagnosed with SLE at age >50 years were classified as LO-SLE and compared with those diagnosed at age ≤50 years (EO-SLE). Longitudinal associations with treatment targets (LLDAS and DORIS remission), organ damage accrual (SLICC/ACR Damage Index), and HRQoL (SF36v2 physical and mental component summary (PCS and MCS) scores) were examined using multivariable multilevel logistic, recurrent-event survival, and linear mixed-effects models, respectively. Disease activity, flares, medication exposure, and other clinical characteristics were also compared between groups. RESULTS: Among 3,917 patients studied, 346 (8.8%) had LO-SLE. Compared with EO-SLE, patients with LO-SLE had lower disease activity, lower glucocorticoid and immunosuppressant exposure, and higher attainment of treatment targets; LO-SLE was associated with higher odds of attaining LLDAS (OR: 2.33 (1.66, 3.28)) and DORIS remission (OR: 2.22 (1.45, 3.38)). However, they were at a greater risk of damage accrual (HR:1.82 (1.50, 2.21)) and lower PCS scores, meaning poorer physical health (regression coefficient (RC) = -3.63 (-4.58, -2.68)) but not MCS (RC= 0.68 (-.50, 1.86)). CONCLUSION: Despite higher attainment of treatment targets, patients with LO-SLE experienced greater damage accrual and poorer physical health, suggesting that disease activity targets alone may not fully capture outcome risk in LO-SLE.

Journal Article↗
PubMed2026

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗
PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗
PubMed2026

A systematic review of international/national guidelines for the management of nasopharyngeal carcinoma: Convergence and divergence of recommendations.

Increasing numbers of clinical practice guidelines have been published by international/national groups for nasopharyngeal carcinoma (NPC), providing valuable references for clinicians in making evidence-based decisions on treatment. However, there are substantial discrepancies in various recommendations, leading to uncertainties in choosing the optimal strategies. The authors systematically searched databases and organizational websites for NPC guidelines published between January 2000 and November 2025. All identified guidelines underwent quality appraisal; in total, 26 clinical practice guidelines rated recommended for use were included. The recommendations covering all management aspects (diagnosis, staging, radiotherapy, systemic therapy, follow-up surveillance, biomarkers, and salvage of recurrent/metastatic diseases) were summarized and comparatively analyzed for consistency and disparities. Strong consensus exists for diagnostic workup, staging systems, and induction chemotherapy plus concurrent chemoradiotherapy for advanced disease, whereas marked disparities exist on radiotherapy details, particularly target volume delineation, elective coverage extent, and dose specifications. Although systemic therapy strategies for different stage groups were mostly consistent, substantial disparities exist in alternative options and treatment details. This first comprehensive systematic synthesis of international NPC guidelines provides a practical reference for clinicians to understand all recommendations and select optimal options based on local resources and expertise while identifying current controversies that demand future research for further standardization and harmonization.

Humans↗
PubMed2026

A framework for delivering real-time, instrument-relative navigation in transoral robotic surgery.

Transoral robotic surgery (TORS) is a minimally invasive, inside-out technique that, compared with traditional open approaches, provides fewer post-operative complications, shorter hospital stays, and improved survival for early-stage head and neck cancer. However, TORS is limited by its steep learning curve and poor visualization of deep tumor margins. This randomized crossover study evaluated a surgical navigation system's potential to enhance accuracy and user experience with real-time, instrument-relative feedback. Seven Teflon beads (d = 2.381 mm) were embedded at the tongue base of a porcine pharynx-and-larynx model. Tongue blade compression and retraction were applied to the model to mimic intraoperative tissue deformation, reproducing the anatomical shifts that occur relative to preoperative imaging. Eight participants used the da Vinci Surgical system to localize the beads by placing pins under two conditions: (a) preoperative computed tomography with no navigation; (b) model-based visual navigation with quantitative instrument-to-target metrics. Surgical accuracy was determined by calculating the target localization error (TLE, pin-to-bead Euclidean distance) and the angular error (AE, pin axis trajectory to bead). Accounting for training level and bead depth, surgical navigation reduced TLE by 5.44 mm (95% CI, 4.02-6.86 mm; p = 2.00e-11) and AE by 8.47 degrees (95% CI, 6.21-10.72 degrees; p = 5.17e-11). Impressions of the system were generally favorable using a 5-point Likert survey and task duration (p = 0.26) or cognitive workload via the NASA-Task Load Index (p = 0.22) were not significantly affected. The navigation system demonstrated translational promise, offering improved target localization accuracy and more consistent performance across experience levels, two critical determinants of surgical quality in TORS.

Robotic Surgical Procedures↗
PubMed2026

LitCTL1: A novel C-type lectin involved in the mucosal and cellular immunity of the common periwinkle Littorinalittorea.

C-type lectins (CTLs) are vital pattern-recognition receptors (PRRs) that mediate innate immune responses in mollusks, yet their characterization in Caenogastropoda, the largest gastropod group, remains limited. This study characterizes LitCTL1, a novel secreted single-domain C-type lectin from the common periwinkle, Littorina littorea. The 199-amino acid polypeptide contains a conserved carbohydrate recognition domain with canonical QPD and WND motifs and is predicted to form a homodimer. Uniquely, LitCTL1 was localized in both circulating hemocytes and mucus-secreting epithelial cells of the foot, mantle, and hypobranchial gland - the first report of such dual localization for a molluscan lectin, linking systemic and mucosal defense. Expression analysis revealed that LitCTL1 is constitutively expressed in hemocytes. Functional assays with recombinant LitCTL1 demonstrated its role as a potent opsonin with hemagglutinating activity, significantly enhancing hemocyte spreading and the phagocytosis of zymosan. Genomic analysis reveals that LitCTL1 belongs to a rapidly diversifying, genus-specific expansion distinct from conserved perlucin-like lineages. These results identify LitCTL1 as a key effector molecule in both systemic and mucosal innate immunity, likely reflecting an evolutionary adaptation to the microbial challenges of the intertidal environment.

Animals↗
PubMed2026

Spatial transcriptomics of Ciona adult brains reveals functional zonalization and insights into neural gland function.

The ascidian Ciona is a pivotal chordate model for illuminating the evolutionary origins of the vertebrate brain. Here, spatial transcriptomics of the adult Ciona neural complex, combined with image-based computational super-resolution mapping, resolved distinct tissue domains including the cerebral ganglion, neural gland, ciliated funnel, neural gland duct/dorsal strand, and body wall muscle. Within the cerebral ganglion, high-resolution mapping revealed clear molecular zonalization separating the cortex and medulla, alongside regional specialization within the cortex itself. The neural gland exhibited localized enrichment of genes associated with extracellular matrix and cell-cell interactions. These spatial features suggest that the neural gland functions as a homeostatic and signaling interface, reminiscent of primitive vertebrate meninges or choroid plexus. Overall, this spatially defined gene expression map provides a foundational framework for understanding functional regionalization in the tunicate brain and its evolutionary relationship to vertebrate nervous systems.

Ciona↗
PubMed2026

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n = 65) or routine nursing only (n = 65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6 months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6 months ranged from small for resilience (D = 0.28) and avoidance coping (D = 0.26) to moderate for confrontation coping (D = 0.60) and resignation coping reduction (D = -0.51), and large for attributional style (D = 0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans↗
PubMed2026

Systemic biomarkers of treatment response to methotrexate in people with painful knee osteoarthritis: A biological substudy of the PROMOTE randomised controlled clinical trial.

OBJECTIVE: Stratification of therapeutic responses may help identify efficacious therapies for osteoarthritis (OA). In the PROMOTE randomised trial, participants with elevated baseline high-sensitivity C-reactive protein (hs-CRP) showed greater pain reduction after methotrexate treatment. We set out to interrogate a broader panel of serum/plasma inflammatory response markers relevant to methotrexate actions as potential biomarkers of therapeutic effect. Our objectives were to: (i) characterize changes in these systemic markers during methotrexate treatment; determine whether (ii) baseline levels or (iii) changes in any marker during treatment were associated with treatment response; and (iv) compare these findings with the more established clinical inflammatory marker, hs-CRP. DESIGN: Plasma/serum samples from participants in PROMOTE's biological substudy were analysed for 35 inflammatory markers at baseline (pre-treatment) and at 6-months (post-treatment), by MesoScale V-plex multiplex assay. Those with paired biological and clinical data at both baseline and 6-months were included in the substudy analysis set. Relationships between markers and overall data structure were assessed by Pearson correlation and Principal Component analysis. Associations between markers (baseline levels or change over time) and change in average knee pain severity in past week (numerical rating scale, NRS) were evaluated by univariable linear regression, adjusting for baseline age, sex, and body mass index. Least Absolute Shrinkage and Selection Operator (LASSO) regression with bootstrap resampling enabled marker selection. Benjamini-Hochberg correction adjusted for multiple testing (Padj). RESULTS: 87 participants with paired blood marker and clinical data were eligible for substudy analysis. 18/35 markers were quantifiable and analysed. Systemic IL-8 and TNF-α levels decreased (Padj=0.015, 0.048 respectively) while IL-15 increased (Padj=0.033) with methotrexate treatment over 6-months. Analysing within this active treatment randomised arm, higher baseline IFN-γ was associated with greater reduction in NRS pain change (0.66 [0.01, 1.31], P=0.047), as was decreasing TNF-α over 6-months (2.25 [0.00, 4.5], P=0.049). LASSO identified higher IFN-γ, lower plasma IL-15 and IL-16, and younger age as the most important baseline predictors of pain improvement. hs-CRP was highly selected by LASSO for treatment response in both arms. In a secondary univariate treatment arm-by-biomarker interaction analysis, of the 19 markers, only hs-CRP showed consistent effects in adjusted models (at baseline, coeffic. 2.34 [0.53, 4.15], P=0.001; change over 6-months, (0.36 [0.06, 0.66], P=0.018). CONCLUSIONS: Blood measurement of IFN-γ, TNF-α, IL-15 and IL-16 as well as hs-CRP could act as potential markers to stratify the treatment response by average knee pain to methotrexate in knee osteoarthritis.

Humans↗
PubMed2026

Multiscale Modeling Primer: Focus on Chromatin and Epigenetics.

A central challenge in modern biology is to understand how molecular interactions produce cellular and organismal functions across vast spatiotemporal scales. Nowhere is this challenge more apparent than in the study of chromatin, where meters of DNA compact into a micron-sized nucleus. How this polymer folds is a dynamic process, regulated by epigenetic modifications-chemical changes to DNA and histones that involve only a handful of atoms. These small changes cooperate to produce emergent, higher-order structures that define cellular identity and function. To explain this system, we must integrate static, high-resolution snapshots from techniques like cryo-EM with dynamic, lower-resolution data from microscopy and genomics. Multiscale computational models are essential tools that bridge these experimental gaps and reveal the mechanisms of emergent behavior. However, the communication divide between experimental biologists and quantitative modelers often hampers progress. This primer addresses that gap. It first introduces the fundamental biology of chromatin and epigenetics at an introductory level for non-biologists audiences. We then survey the landscape of computational approaches, from atomistic to systems-level models, and connect them to the experimental data that inform and validate them at an introductory level for non-computationalists. We argue that the next frontier will require us to build integrative models that can predict how molecular perturbations mechanistically alter cellular phenotypes, which will open a new era of chromatin-targeted therapeutics.

Chromatin Dynamics↗
PubMed2026

Comparative Efficacy of Different AI Systems for Polyp Detection by Size During Colonoscopy: Systematic Review and Network Meta-Analysis.

BACKGROUND: Colorectal cancer remains a leading cause of death despite being largely preventable through polypectomy. AI systems designed to enhance polyp detection during colonoscopy have shown promise, but the extent to which they improve detection of different-sized polyps remains unclear. OBJECTIVE: This study compared the size-stratified efficacy of AI-assisted colonoscopy vs standard colonoscopy using the Hartung-Knapp-Sidik-Jonkman (HKSJ) method, and generated exploratory rankings while acknowledging all cross-platform comparisons are indirect. METHODS: This systematic review and network meta-analysis (NMA) searched PubMed, Embase, Cochrane CENTRAL, and Web of Science from inception to July 25, 2026, supplemented by citation searching. We included randomized controlled trials (RCTs) comparing AI-assisted vs standard colonoscopy in adults (≥18 years of age), reporting mean polyp detection counts stratified by size (≤5 mm, 6-9 mm, and ≥10 mm). Two reviewers screened studies, extracted data, and assessed risk of bias using the Cochrane Risk of Bias 2.0. We conducted frequentist NMA using the HKSJ method with restricted maximum likelihood estimation, calculated 95% prediction intervals (PIs), and assessed heterogeneity using I2 and τ2. Certainty of evidence was rated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework. RESULTS: A total of 13 RCTs (4156 participants) compared 8 AI systems to standard colonoscopy, forming a network without direct AI comparisons. For diminutive polyps (≤5 mm), AI showed a modest advantage (standardized mean difference [SMD] 0.21, 95% CI 0.07 to 0.35, 95% PI -1.12 to 1.54), but substantial heterogeneity (I2=86.6%) and wide PI crossing the null indicated high uncertainty. EndoScreener showed the most consistent evidence (SMD 0.36, 95% CI 0.18-0.54). For small and large polyps, effects were minimal (SMD 0.02, 95% CI -0.02 to 0.06, 95% PI -0.03 to 0.07; SMD 0.01, 95% CI 0.00-0.02, 95% PI -0.01 to 0.03). GRADE certainty was very low for diminutive polyps and low for small and large polyps. Sensitivity analysis excluding Tianjin YuJin did not materially change findings. CONCLUSIONS: AI may modestly enhance diminutive polyp detection, but effects on small and large polyps are minimal, with no platform superiority. Given very low to low certainty, findings are hypothesis-generating. This exploratory NMA provides size-stratified comparisons that can inform future head-to-head trial design. Unlike prior reviews aggregating all polyp sizes, we show the overall AI benefit is driven by diminutive polyp detection, providing a framework for targeted deployment-prioritizing AI for diminutive polyp screening, with limited value for larger lesions. Head-to-head trials are urgently needed. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD420251266932; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251266932.

Colonoscopy↗
PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

Humans↗
PubMed2026

Inducible flocculation in Komagataella phaffii enables enhanced biomass separation for biopharmaceutical production.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50 % create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (ScFLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation or gravity sedimentation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY® VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

Flocculation↗
PubMed2026

Feasibility and efficacy of left bundle branch area pacing guided by modified chest lead 1.

BACKGROUND: Left bundle branch area pacing (LBBAP) typically requires 12‑lead electrocardiogram (ECG) measurements using an electrophysiology (EP) recording system. However, a simplified approach using modified chest lead 1 (MCL1) is potentially feasible. This study aimed to compare the success rate and pacing outcomes of LBBAP guided by MCL1 with those guided by the 12‑lead ECG using an EP recording system. METHODS: This retrospective, single-center study included patients with preserved left ventricular ejection fraction who underwent LBBAP for bradyarrhythmia. LBBAP was either guided by 12‑lead ECG using an EP recording system or by MCL1. In the MCL1 group, a follow-up examination with a 12‑lead ECG using an EP recording system was conducted within one week postoperatively. RESULTS: A total of 65 patients underwent LBBAP (EP recording system group: n = 35; MCL1 group: n = 30). The overall success rate of LBBAP was 84.6%, with no significant difference between groups (88.5% vs. 80.0%, p = 0.49). No significant differences were observed in the paced QRS duration (140.4 ± 8.0 vs. 141.9 ± 13.1 ms, p = 0.54), V6-V1 interpeak interval (39.7 ± 16.5 vs. 38.3 ± 15.6 ms, p = 0.79), or V6 R-wave peak time (69.8 ± 12.3 vs. 71.5 ± 12.1 ms, p = 0.68). CONCLUSIONS: MCL1-guided LBBAP was feasible and achieved a high success rate, with outcomes comparable to those of conventional EP recording system-guided implantation. This simplified approach may reduce procedural complexity and may allow LBBAP implantation without the routine use of an EP recording system.

Humans↗
PubMed2026

Silent crises in the COVID-19 pandemic shadow: a six-year medico-legal review of non-lethal intimate partner violence in Morocco.

Intimate partner violence (IPV) is a major global public health concern and one of the most prevalent forms of gender-based violence, with significant consequences. This study analyzes non-lethal IPV cases reported to a medico-legal unit of Casablanca between 2018 and 2023. Data from 4,784 female victims were reviewed, focusing on socio-demographics, violence types, perpetrator relationships, and judicial involvement across the pre-COVID, peak COVID-19, and post-COVID periods. Married women represented 59.2% of victims. Physical violence predominated (83.1%), while sexual violence was underreported (14.7%). The year 2020 marked a sharp increase in reported non-lethal IPV cases (n = 1,005), correlating with pandemic confinement. Among married women, judicial requisition (legal request for forensic examination) and medico-legal certification (medical documentation for judicial use) rates were high (81.5% and 81.0%, respectively). Post-pandemic years declined moderately but remained above pre-COVID levels. International comparison confirmed a global rise in IPV during COVID-19, with Morocco displaying comparatively higher rates of medico-legal documentation and judicial involvement. IPV in Morocco is entrenched and intensified by COVID-19. While the medico-legal system is robust in documentation, the system must evolve by integrating systematic psychological assessment into medico-legal evaluations, standardizing certification and referral protocols, and strengthening coordination between medico-legal, health, and social support services to improve victim protection.

Humans↗
PubMed2026

The Case for Master Protocols for Rare Neurological Diseases.

Master protocol trials allow for simultaneous multiple hypothesis testing within a common framework and might be applicable for rare diseases. In May 2025, the Network for Excellence in Neuroscience Clinical Trials convened a multistakeholder conference to discuss master protocol trials in rare neurological disorders. In this paper, we explore how master protocol trial designs may apply to rare neurological disorders, using the neuronal ceroid lipofuscinoses as an example. Through shared protocol elements and trial infrastructure, master protocols may decrease cost and improve efficiency in testing potential therapeutics in rare disease, accelerating the delivery of urgently needed therapies to patients. ANN NEUROL 2026;100:477-486.

Humans↗
PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗