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PubMed2026

Molecular characterization and biological characteristics of a highly pathogenic recombinant ALV-J strain (HUE2023) with cross-clade gp85 recombination.

Avian leukosis virus subgroup J (ALV-J) has undergone extensive diversification into phylogenetically distinct clades, yet whether recombination between these clades within the gp85 envelope glycoprotein generates variants with altered pathogenicity has received little direct investigation. A field strain (HUE2023) was recovered from breeding roosters displaying vascular tumors. The viral genome was sequenced and subjected to phylogenetic and recombination analyses. The three-dimensional structure of gp85 was predicted with AlphaFold3; electrostatic surface potentials and surface hydrophobicity were computed using the Adaptive Poisson-Boltzmann Solver and the Eisenberg hydrophobicity scale, respectively. Pathogenicity and immunosuppressive effects were assessed in Hy-Line Brown chickens. Recombination analysis revealed that HUE2023 is an inter-clade recombinant derived from Clade 1.1 (major parent: JS14NT01) and Clade 1.2 (minor parent: JS09GY3). A single-residue deletion at position 61 within receptor-binding domain 1 (RBD-1), unique to the recombinant, induced a localized conformational rearrangement that generated a concentrated electronegative surface patch and a contiguous hydrophobic pocket not observed in either parental gp85. Animal challenge showed that HUE2023 is highly pathogenic: female chickens in the high-dose group reached only 61% survival and displayed significant growth retardation (P < 0.05) together with marked immunosuppression. The recombination in the RBD-1 led to local conformational rearrangement, resulting in a concentrated and negatively charged surface area as well as a continuous hydrophobic pocket, which were never present in any of the parental gp85 sequences. These results indicate that gp85 recombination across clades can yield variants with fundamentally altered receptor-binding surfaces and argue for integrating structural surveillance into ALV-J monitoring programmes.

Animals↗

PubMed2026

Cisplatin-Induced Hearing Loss Prevention With Intratympanic Therapy Systematic Review and Meta-Analysis.

INTRODUCTION: Cisplatin-induced hearing loss (CIHL) is a well-described, long-term consequence of cisplatin treatment for malignancy. Intratympanic (IT) injections have been trialed to prevent CIHL in humans. To provide clarity on which agents have been studied through IT injection and to review their efficacy for hearing loss prevention, we performed a systematic review and meta-analysis. DATA SOURCES: OVID Medline, Embase, Web of Science, and Cochrane Library were queried. METHODS: Databases were searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Prospective randomized trials were included, and a systematic review was performed for all studies. Demographic, audiometric, and therapeutic data were collected. Random-effects models were used to compare across studies, and subgroup analyses were performed for each IT agent. RESULTS: The initial database search yielded 1017 articles, which were screened according to inclusion and exclusion criteria. Ten studies were identified, involving a total of 284 patients. Studies included data on IT dexamethasone, IT N-acetylcysteine (NAC), and IT sodium thiosulfate (STS). Pooled analysis across all agents and frequencies did not reveal a significant difference in hearing thresholds between treatment and control ears [prediction interval [-3.77, 3.20], negative favors treatment). Subgroup analysis of IT dexamethasone [-1.74, 3.80] and IT NAC [-1.02, 4.64] also did not demonstrate significant differences. STS data were not amenable to pooled analysis; however, one study demonstrated a significant decrease in ASHA-defined ototoxicity (40% vs. 85%, P =0.0027). CONCLUSIONS: To date, no IT agent has consistently prevented CIHL, although limited data suggest that IT STS may decrease ototoxicity. More trials are necessary to fully elucidate these effects.

Humans↗

PubMed2026

Financial incentives and social messaging for repeat SARS-CoV-2 antibody testing among the underserved: A randomized trial.

Financial incentives may influence health behavior beyond their expected monetary value, and their effectiveness may depend on how the behavior is framed. Behavioral theories of decision making suggest that individuals may value protection against small-stakes losses more than expected utility predicts, while theories of family-centered health behavior suggest that messages emphasizing benefits to family members may strengthen participation in preventive health activities. We tested these ideas in a 2×2 factorial randomized trial involving 625 households recruited from a Federally Qualified Health Center serving low-income Latino/Hispanic communities. Participants completed repeat SARS-CoV-2 antibody testing. The trial crossed two messaging strategies (Family vs. Personal) with two incentive structures (Loss Protection vs. Lottery) that offered equivalent expected monetary value. Family Messaging emphasized protecting one's family from COVID-19, whereas Personal Messaging emphasized protecting oneself. Loss Protection allowed participants to secure an at-risk reward through repeat testing, whereas the Lottery condition offered a chance of a large reward. Repeat testing was approximately 8 percentage points higher under Family Messaging and 7 percentage points higher under Loss Protection. Baseline trust in medical providers, financial barriers to vaccination, and risk aversion were associated with initial testing, whereas household characteristics were not associated with repeat testing. Incentive design may matter beyond expected monetary value and that framing health behaviors in terms of family welfare may increase participation in repeated healthy activities. Broadly, the results support behavioral theories emphasizing loss aversion, anticipated regret, and family-centered motivations, and suggest practical approaches for improving engagement in repeat health behaviors. CLINICALTRIALS.GOV REGISTRATION NUMBER:: NCT01901624.

Adult↗

PubMed2026

Integrated exome and mitochondrial genome sequencing reveals the genetic landscape of primary mitochondrial diseases: findings from a large Tunisian cohort.

Primary mitochondrial diseases are a heterogeneous group of neurometabolic disorders recognized as the most common metabolic genetic diseases. They manifest at any age, affecting any tissue or organ, especially those with high energy demands, and are caused by pathogenic variants in both mitochondrial and nuclear genomes. Here, we aimed to describe the genetic spectrum of a Tunisian pediatric cohort with suspected mitochondrial diseases. We recruited 47 unrelated families who underwent exome sequencing as a first-tier test followed by whole mitochondrial genome sequencing for unsolved cases. Dedicated bioinformatic pipelines and prediction tools were used to determine the potential disease-causing variants. Sanger sequencing confirmed the presence and segregation within parents. For the newly identified variants, structural modeling was conducted to study the impact of these variants on protein structure and motions. Dual genome sequencing yielded a molecular diagnosis in 33/47 families (70%) and 18/47 (38%) showed disease-causing variants in genes encoding mitochondrial proteins. Among them, four families disclosed novel variants in FASTKD2, SERAC1 and GATB, which were supported by in-depth in silico and structural analyses demonstrating their deleterious effect. The remaining families (32%, 15/47) disclosed other metabolic and neurological disorders. An exome-first strategy delivers a high diagnostic yield in Tunisia, where consanguinity remains high and simultaneously captures mitochondrial and non-mitochondrial etiologies. Mitochondrial sequencing remains indispensable in the case of an inconclusive exome. Thus, our data expand the clinical and genetic spectrum of primary mitochondrial diseases in Tunisia, an underrepresented and admixed population.

Humans↗

PubMed2026

Novel environmental contaminant 6PPD-quinone promotes malignant phenotypes in colorectal cancer cells and identifies candidate response-associated genes.

6PPD-quinone (6PPDQ), an oxidative transformation product of the widely used tire antioxidant 6PPD, is a ubiquitous environmental contaminant with bioaccumulation potential and widespread human exposure. Recent epidemiological evidence indicates a positive association between urinary 6PPDQ levels and colorectal cancer (CRC) risk; however, its biological effects on CRC-related phenotypes and associated molecular responses remain unclear. We integrated bioinformatics analysis, prognostic modeling, molecular docking and dynamics simulations, and in vitro experiments to investigate cellular and molecular responses to 6PPDQ in CRC models. Predicted 6PPDQ targets were intersected with CRC prognosis-related genes from The Cancer Genome Atlas, followed by functional enrichment and LASSO regression to construct a prognostic risk model, with 1-, 3-, and 5-year AUC values of 0.727, 0.754, and 0.778, respectively. Molecular docking and 100-ns molecular dynamics simulations suggested interactions between 6PPDQ and candidate proteins, including CPT2, SHC2, SRMS, and STK35. Functional assays showed that 6PPDQ exposure altered proliferation, wound-closure capacity, and invasion in Caco-2 and HCT116 cells across the nanomolar concentration range, with non-monotonic and cell-line-dependent responses. In contrast, NCM460 cells showed no increase in EdU incorporation at 10 or 100 nM, whereas reduced proliferation at higher concentrations was accompanied by increased LDH release. 6PPDQ also altered the expression of several prognosis-associated candidate genes. These findings identify cellular phenotypes and candidate molecular responses associated with 6PPDQ exposure under the tested in vitro conditions, but do not establish their causal roles or in vivo relevance. Further mechanistic and in vivo studies are required.

Humans↗

PubMed2026

Nociception-guided opioid administration within multimodal analgesia for laparoscopic endometriosis surgery: a randomized controlled trial.

Women with endometriosis are at increased risk of severe postoperative pain due to nociceptive sensitization. While multimodal analgesia reduces opioid use, the added value of objective nociception monitoring remains unclear. This study evaluated whether NOL®-guided opioid titration improves perioperative outcomes within a standardized multimodal regimen. In this prospective, randomized, single-blinded trial, premenopausal women undergoing laparoscopic surgery for suspected endometriosis or adenomyosis were assigned to NOL®-guided analgesia or standard care based on clinical assessment. All patients received a standardized multimodal protocol. The primary outcome was total perioperative opioid consumption. Secondary outcomes included postoperative pain scores (NRS) and PACU length of stay. Exploratory analyses assessed the association between preoperative pain (Mankoski Pain Scale, MPS) and postoperative outcomes. A total of 111 patients were analyzed (NOL®: n = 54; control: n = 57). Total perioperative opioid consumption did not differ significantly between groups (adjusted mean difference = 14 μg for Fentanyl and 52 μg for Remifentanil; p = 0.8). Surgery duration was an independent predictor of opioid use (p < 0.001) and PACU length of stay (p = 0.01), whereas treatment group had no significant effect. Postoperative pain scores were comparable between groups at all time points. NOL®-derived metrics were not associated with opioid consumption or pain. Higher preoperative MPS scores independently predicted higher pain scores in the late PACU phase. NOL®-guided opioid titration did not reduce perioperative opioid consumption or improve early postoperative outcomes compared with standard multimodal analgesia in women undergoing laparoscopic surgery for endometriosis.

Humans↗

PubMed2025

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5 concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

Alcohol use disorder and childhood adversity in the association between polygenic risk and suicidality.

OBJECTIVE: Suicidal ideation (SI) and suicide attempt (SA) are both influenced by genetic, behavioral, and environmental factors. Alcohol use disorder (AUD) and adverse childhood experiences (ACEs) may mediate or moderate the effects of genetic liability for suicidality. METHODS: Using data from 10,275 participants (43.8% female; 47.2% African-like genetic ancestry [AFR], 52.8% European-like genetic ancestry [EUR]), we tested whether polygenic scores (PGS) for SI and SA predicted lifetime suicidality outcomes. We evaluated whether AUD partially accounted for these associations and ACEs moderated the direct and indirect associations. RESULTS: The SA PGS was significantly associated with SA (AFR: b = 0.36, SE = 0.01; EUR: b = 0.17, SE = 0.01; both ps < 2e-16), but the SI PGS was not associated with SI (p > 0.55). AUD statistically mediated the association between the SA PGS and SA, accounting for approximately 2% of the total association in AFR individuals and 10% in EUR individuals (both ps < 2e-16). Notably, the proportion of the association that was accounted for by AUD decreased as ACEs exposure increased, from 4.30% to 0.54% in AFR individuals and from 13.31% to 3.44% in EUR individuals. In contrast, there was only very modest mediation and no moderated mediation for SI. CONCLUSIONS: Particularly among individuals with lower ACEs exposure, AUD accounted for a meaningful proportion of the association between genetic liability to SA and lifetime SA. These findings highlight different correlates across suicidality phenotypes and suggest potential clinical relevance for AUD in the association between genetic liability and SA.

Adult↗

PubMed2026

The Effect of Pain Catastrophizing on Acupuncture Treatment for Chronic Pain in Cancer Survivors.

CONTEXT: Pain catastrophizing (PC) predicts worse pain outcomes in cancer survivors. However, little is known whether PC influences pain outcomes of nonpharmacological treatments such as acupuncture. OBJECTIVES: This study aimed to assess the impact of PC on acupuncture efficacy for chronic pain in cancer survivors. METHODS: This secondary analysis of PEACE trial used two-sample t-test and Pearson's chi-squared test to analyze the pain outcomes of cancer survivors who received electroacupuncture (EA) or battlefield acupuncture (BFA). PC was measured using Pain Catastrophizing Scale (PCS). The Brief Pain Inventory (BPI) was used to measure pain severity and interference at the primary endpoint (week 12). RESULTS: Among 266 participants, 41 (15.41%) had a high baseline PC. Among those receiving EA, high PC patients had greater reductions in pain severity (-3.9 vs. -2.1, P = 0.006) and pain interference (-3.8 vs. -2.6, P = 0.04) than low PC. PC was not associated with pain outcomes in BFA group (P > 0.05 for both severity and interference). Among patients with high PC, a greater proportion were responders in the EA group than those in BFA group (83.3% vs. 43.5%, P = 0.009). Among low PC patients, there was no significant difference in the proportion of responders between the EA and BFA groups (66.1% vs. 64.5%, P = 0.8). CONCLUSION: We found that cancer survivors with high baseline PC had greater pain reductions with EA than BFA and compared to low PC patients. These findings suggest that EA may serve as a targeted treatment option for vulnerable patients with high PC and further support precision pain management.

Humans↗

PubMed2026

Effect of cognitive enhancement therapy for early course schizophrenia on gray matter volume: A confirmatory multisite randomized clinical trial.

BACKGROUND: Cognitive Enhancement Therapy (CET) is an evidence-based cognitive remediation intervention for early course schizophrenia with established benefits for cognition. CET may protect against broad temporolimbic gray matter volume loss associated with cognitive improvement, but this finding has yet to be replicated. This research reexamined if CET protects against temporolimbic gray matter volume loss in an independent and larger multisite early course sample, and if this neuroprotective effect predicts cognitive and social adjustment improvement. METHODS: Ninety-nine participants with early course schizophrenia completed MRI, cognitive, and social adjustment assessments at baseline, 9 (mid-treatment), and 18 (end of treatment) months. Linear mixed-effects models examined the differential impact of CET (n = 56) compared to Enriched Supportive Therapy (n = 43) on temporolimbic gray matter volume in regions-of-interest (ROIs) that previously demonstrated CET-related neuroprotection (primary ROIs), as well as frontotemporal ROIs outlined in the first trial (secondary ROIs). RESULTS: The right rostral anterior cingulate was the only primary ROI to demonstrate a significant group × time interaction, but was unrelated to cognitive and social adjustment change. No secondary ROIs exhibited a differential treatment effect. CONCLUSION: This confirmatory trial did not recapitulate the observed broad pattern of CET-related temporolimbic gray matter volume neuroprotection. Consistent with the larger literature demonstrating limited evidence of cognitive remediation effects on the brain in schizophrenia, these findings underscore the need for continued investigation of CET-related changes with other neuroimaging modalities, especially given its established cognitive benefits. Such information is critical for cognitive remediation optimization based on validated therapeutic mechanisms.

Humans↗

PubMed2026

The neuroendoscopic factors affecting outcome of endoscopic third ventriculostomy in pediatric patients with post infectious hydrocephalus.

BACKGROUND: The role of endoscopic third ventriculostomy(ETV) in infective hydrocephalus remains uncertain. Infection alters cerebrospinal-fluid composition, flow-dynamics, absorptive capacity, undermining the effectiveness of ETV. AIMS AND OBJECTIVES: This study aims to describe the intraventricular morphological findings and its correlation with ETV outcomes in a cohort of paediatric infective hydrocephalus. METHODOLOGY: Total 98 cases of infective HCP underwent ETV, were studied for intraventricular findings. Thin transparent third ventricular floor were considered as type-1, transluscent as type-2, floor with granuloma as type-3 and unidentifiable anatomy as type-4. Infective deposits were sent for histopathology. RESULT: Overall ETV was successful in 46 patients (46.93%). Success rate of ETV in type 1 (72.7%) was better than type-2 (50%) and type-3 (33.3%). The difference between type-1 and type-3 was statistically significant, p = 0.01. The success rate in presence of pre-pontine adhesions (46 cases) was 34.7%, significantly lower than the 66.6% observed in their absence (p = 0.005). ETV was not successful in all the 7 cases withy type-4 floor. Tissue biopsy confirmed microbiological diagnosis in 13 cases and helped in modifying pharmacological treatment as per culture (two with tuberculosis and three with fungal infection). CONCLUSION: ETV offers a meaningful therapeutic option in post-infectious HCP. Endoscopic appearance of the third ventricular floor and the pre-pontine space may predict its outcome. A thin, transparent floor in the absence of cisternal adhesions is associated with best outcomes, while progressive floor thickening, granuloma formation, and pre pontine fibrosis each correlate with declining success rates. The culture from exudates often helps in achieving organism oriented pharmaco-therapy that improves ETV success rate.

Humans↗

PubMed2026

Utility of monocyte-derived cells to investigate immune-mediated drug-induced liver injury.

Immune-mediated drug-induced liver injury (DILI) is triggered or exacerbated by the immune system mounting an attack against the drug or its metabolites. The array of in vitro assays for evaluating drug immune liability is limited, highlighting a significant gap in effectively predicting and understanding immune-mediated hepatotoxicity. We aimed to investigate whether monocytes differentiated with the Metaheps (MH) protocol could provide insights into the molecular mechanisms of immune-mediated DILI. MH were generated from monocytes of healthy volunteers (HV) and DILI patients. MH phenotypic characterization was performed by proteomics and qPCR. MH sensitivity to drugs associated with immune-mediated DILI was assessed by lactate dehydrogenase (LDH) assay. Drug-induced LDH release by DILI-derived MH was compared to the upper limit of the 95% CI calculated from HV-derived MH cells treated with the same drug. The 95% CI determined in HV-derived MH was set as the sensitivity threshold for the specific drug. MH cells retain the expression of several immune-related proteins of the parental monocytes and activate a pro-inflammatory response upon exposure to lipopolysaccharide. For all MH (6 out of 6) generated from patients with penicillin-induced DILI, the LDH release upon re-challenge was above the threshold. The sensitivity of MH generated from seven patients with immune checkpoint inhibitor (ICI)-induced hepatotoxicity was ICI-dependent, responding to nivolumab and/or ipilimumab (4 out of 5), but not to pembrolizumab (0 out of 2). Additionally, DILI-derived MH were not sensitive to non-DILI drugs. In conclusion, monocyte-derived cells may serve as an additional tool for drug-specific mechanistic studies of immune-mediated DILI.

Humans↗

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

Meniscal preservation in the age of biologics: toward a quantitative decision algorithm for personalized repair.

BACKGROUND: Despite advances in arthroscopic repair and biologic augmentation, surgical indication for meniscal tears remains heterogeneous. No standardized framework currently integrates biomechanical, clinical, and biological determinants to guide repair versus resection. PURPOSE: To develop a quantitative decision model-the Meniscal Preservation Score (MPS)-that unifies biomechanical and biological evidence to stratify reparability potential and standardize treatment selection in meniscal surgery. METHODS: A systematic evidence synthesis conducted in accordance with PRISMA 2020 reporting standards of studies published from 2000 to 2025 in PubMed, Embase, and Scopus identified key determinants of meniscal healing. Five consistent predictors-patient age, vascularity, tear morphology, associated pathology, and activity profile-were weighted through a two-round modified Delphi consensus among ten experienced knee surgeons. The resulting 0-9-point MPS was incorporated into a stepwise decision tree linking lesion morphology, biological context, and surgical strategy. Conceptual validation used 50 simulated cases and a retrospective cohort of 45 patients to test agreement between algorithm recommendations and expert surgical decisions. RESULTS: The MPS achieved 86% concordance with expert judgment in simulation and 84% agreement in clinical validation. In this retrospective exploratory cohort, cases in which surgical management was concordant with MPS recommendations demonstrated higher mean IKDC scores at 24 months and lower observed reoperation rates. These findings should be interpreted as associative rather than causal, as treatment allocation was not controlled and discordant cases may have represented inherently more complex pathology. CONCLUSION: The MPS represents an evidence-informed decision-support framework designed to systematize reparability assessment. While exploratory analyses suggest structural coherence with expert reasoning, prospective implementation and external validation are required before clinical adoption as a predictive tool. LEVEL OF EVIDENCE: conceptual model with exploratory validation.

Humans↗

PubMed2026

Compound muscle action potential amplitudes in newborn screen positive spinal muscular atrophy.

OBJECTIVE: To evaluate the utility of compound muscle action potential (CMAP) amplitudes as biomarkers of disease severity in newborn screening (NBS)-positive infants with spinal muscular atrophy (SMA). METHODS: We conducted a retrospective review of 21 infants identified through SMA NBS (11 with 2 SMN2 copies and 10 with 3 SMN2 copies). Baseline and serial right median, ulnar, and fibular motor nerve CMAP amplitudes (millivolts, mV) were obtained during the study. Functional outcomes were assessed using the Children's Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP-INTEND). RESULTS: At baseline, infants with 2 SMN2 copies demonstrated significantly lower median, ulnar, and fibular CMAP amplitudes compared with infants with 3 SMN2 copies (p < 0.05). In contrast, baseline CHOP-INTEND scores did not differ significantly between the two groups. Prior to genetic confirmation, a right median CMAP amplitude ≥3.2 mV predicted ≥3 SMN2 copies. Following treatment, right median and fibular CMAP amplitudes demonstrated significant improvement over time, including in analyses accounting for SMN2 copies number. CONCLUSION: CMAP amplitudes obtained from multiple upper- and lower-extremity motor nerves provided objective electrophysiological measures that distinguished infants with two versus three SMN2 copies, despite similar baseline CHOP-INTEND scores. Furthermore, CMAP abnormalities were detectable in some cases before confirmatory genetic testing results became available. Serial CMAP measurements demonstrated significant longitudinal changes following treatment, whereas functional assessments approached ceiling values, supporting the potential value of electrophysiological monitoring in the era of disease-modifying therapies. SIGNIFICANCE: CMAP assessment is a useful adjunct in the evaluation of infants identified through SMA NBS.

Humans↗

PubMed2026

Comparative phylogenomics and transcriptional regulatory networks of AQPs, HSPs, and LEA proteins in salt-stressed Portulaca oleracea.

Soil salinization severely threatens global food security, necessitating systematic investigations of halophytes like Portulaca oleracea to decode the molecular mechanisms of environmental resilience. Utilizing an integrated framework of deep learning-based genome annotation (58,817 predicted genes; 96.5% BUSCO completeness), multi-tissue RNA-Seq, phylogenomics, and gene regulatory network (GRN) inference, the synergistic orchestration of 78 aquaporins (AQPs), 525 heat shock proteins (HSPs), and 119 late embryogenesis abundant (LEA) proteins was elucidated. The active transcriptome, encompassing 39,065 expressed loci, revealed a systemic growth-defense trade-off. Tissues displayed distinct adaptive mechanisms: leaves modulated intracellular water balance via specialized AQPs, whereas adult roots maintained proteostasis through robust HSP20/HSP70 induction. Phylogenomic clustering across 154 species demonstrated that salinity tolerance constitutes an evolutionary mosaic, identifying 81 halophyte-exclusive orthogroups and 1129 species-specific clusters. Comparative topology across six independent GRNs (4.2M-5.3 M edges) unmasked a highly modular transcriptional reprogramming strategy governed by a core apparatus of 22 stress-exclusive regulators, with functional enrichment heavily prioritizing protein dimerization and chromatin remodeling. Theoretically, the distinct convergence of Trihelix transcription factors with guard cell differentiation pathways offers a candidate transcriptomic framework to explain the plant's characteristic C4-CAM photosynthetic plasticity under severe osmotic pressure. Practically, these evolutionary blueprints and specific master switches transcend single-gene transgenic limitations. Utilizing these root-sustained and stress-inducible targets under localized promoters provides a naturally optimized, network-level precision engineering roadmap to transfer robust, compartmentalized halotolerance to sensitive glycophytic crops.

Gene Regulatory Networks↗

PubMed2026

Pathogenic properties of myasthenia gravis AChR autoantibodies associate with clinical response to efgartigimod.

BACKGROUND: Efgartigimod, a neonatal Fc receptor (FcRn) blocker, effectively reduces total IgG, including pathogenic acetylcholine receptor (AChR) autoantibodies in myasthenia gravis (MG); however, clinical responses vary. To investigate this variability, we studied how efgartigimod impacts AChR-specific autoantibody profiles and associated pathogenic mechanisms, including complement activation, AChR internalisation and ACh-binding site blockade. METHODS: Serum samples (N=150) were sourced from 50 AChR autoantibody-positive generalised MG patients participating in the phase 3 ADAPT study, randomised to receive efgartigimod (N=40) or placebo (N=10) in cycles of 4-weekly infusions. Samples were collected at baseline, day 29 and day 57 during the first cycle. Live cell-based assays quantified AChR-specific IgG subclasses and isotypes and assessed their capacity to mediate pathomechanisms. RESULTS: Efgartigimod decreased all detectable AChR-specific IgG subclasses. At baseline, AChR autoantibody-mediated C3b deposition, AChR internalisation and ACh-binding site blockade were detected in 42 (84%), 41 (82%) and 10 (20%) patients, respectively. After 4-weekly infusions of efgartigimod, the magnitude of all three pathomechanisms was significantly decreased. However, the extent of this reduction varied across individuals. Double responders on both MG-activities of daily living and quantitative MG scores demonstrated a greater reduction in complement activity and AChR internalisation compared with patients who responded on only one score or were double non-responders. In addition, efgartigimod reduced IgG-dependent IgM binding to AChR. CONCLUSIONS: These findings suggest that clinical efficacy may be more closely associated with functional modulation of the AChR-specific autoantibodies than with their absolute quantity alone. These results support the evaluation of mechanistic pathway monitoring as a potential strategy to predict or guide efgartigimod treatment response.

Humans↗