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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

The effect of metformin on the pharmacokinetics of rifampicin, isoniazid, and pyrazinamide in adults with tuberculosis.

Metformin is under investigation as adjunctive host-directed therapy for tuberculosis (TB), which might interact with first-line TB treatment. We used population pharmacokinetic modeling to assess whether metformin alters first-line TB-drug pharmacokinetics in HIV/TB-coinfected adults without diabetes. Rifampicin, isoniazid, and pyrazinamide pharmacokinetics were investigated in participants from a randomized clinical trial of adjunctive metformin (500 mg twice daily to week 12) in adults starting HIV-associated TB treatment. Antiretroviral therapy (ART)-naïve participants initiated dolutegravir-based ART within 8 weeks. Intensive and semi-intensive sampling was conducted at week 5; concentration-time data were analyzed using non-linear mixed-effects modeling. Data from 78 individuals (43 receiving metformin, median weight 60.8 kg, 62.8% male, 79.5% on ART) were analyzed. Rifampicin and pyrazinamide were described by one-compartment models with linear elimination; typical clearances were 15.8 L/h (95% CI: 13.5-18.7) and 3.88 L/h (95% CI: 3.54-4.08), respectively. Isoniazid followed a two-compartment model with a mixture model for acetylator status; clearance was 10.5 L/h (95% CI: 9.44-11.9) in slow acetylators and 28.8 L/h (95% CI: 25.6-31.0) in fast/intermediate acetylators. Metformin reduced isoniazid bioavailability by 15.6% (95% CI: 4.45-26.4%, P < 0.009) and rifampicin bioavailability by 24.0% (95% CI: 7.83-36.3%, P < 0.007), decreasing the area under the curve from 0 to 24 h from 18.2 to 15.6 mg·h/L and from 35.9 to 27.1 mg·h/L, respectively. No significant effect on pyrazinamide was detected. We found that non-diabetic patients on metformin had lower isoniazid and rifampicin bioavailability. Lowered rifampicin exposure might be clinically relevant; simulations suggest that this could be offset by a single 150 mg rifampicin dose.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT04930744.

Humans↗

PubMed2026

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST + AI for prediction model studies. Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST + AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection. AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans↗

PubMed2026

Associations of clinical and laboratory parameters with pediatric urolithiasis composition: A retrospective, single-center study.

OBJECTIVE: To investigate demographic, clinical, and laboratory factors associated with distinct stone compositions in children. METHODS: This retrospective study included 237 children aged <14 years who underwent stone composition analysis between July 2008 and November 2023. Demographic, clinical, and laboratory data were collected, and propensity score matching (PSM) was used to control for confounding factors. RESULTS: The urate component (uric acid anhydrous, ammonium acid urate, and sodium urate) was most prevalent in infants, males, and non-Han children, whereas the calcium oxalate component predominated in older children. Analysis of coexisting components revealed urate is the most common partner to calcium oxalate (67.6%), and vice versa (82.8%). Struvite most frequently coexisted with carbonate apatite (60%), while carbonate apatite most often coexisted with calcium oxalate (54%). After PSM, the urate component was independently associated with host metabolic dysregulation, including lower high-density lipoprotein (β = -0.175, 95% CI: -0.279 to -0.071, p = 0.001) and with coagulation dysfunction, as evidenced by a prolonged prothrombin time (β = 0.595, 95% CI: 0.125 to 1.064, p = 0.014). Additionally, preoperative urinary tract infection (UTI) and congenital urinary tract anomalies were independently associated with both carbonate apatite and struvite components, with directionally consistent but quantitatively unstable signals in the struvite cohort, whereas the calcium oxalate component exhibited an inverse association with UTI (OR = 0.156, 95% CI: 0.030 to 0.819, p = 0.028). Furthermore, the carbonate apatite component was also independently associated with an elevated systemic immune-inflammation index (β = 416.53, 95% CI: 60.05 to 773.01, p = 0.024) and systemic inflammation response index (β = 1.286, 95% CI: 0.086 to 2.487, p = 0.038). CONCLUSION: Urate component was prevalent in infants, males, and non-Han children, whereas calcium oxalate predominated in older children. After adjusting for confounders, urate composition was associated with metabolic abnormalities, the carbonate apatite component was linked to infection and anatomical malformations, and a similar directional pattern was observed in the struvite cohort.

Humans↗

PubMed2026

Playing with Fire, Losing the Drive: Bidirectional Links Between Problematic Smartphone Use and Grit Dimensions.

This study examined bidirectional longitudinal associations between grit dimensions (consistency of interest [CI] and perseverance of effort [PE]) and problematic smartphone use (PSU) and tested cognitive flexibility as a mediating mechanism. A sample of 1,641 Chinese university students (55.2 percent female; Mage = 20.1 years) completed measures at two time points 6 months apart. A four-variable cross-lagged panel model revealed that CI and PSU negatively predicted each other over time, whereas PSU unidirectionally predicted decreased PE. Cognitive flexibility partially mediated the PSU-to-PE pathway (indirect effect = -0.004, 95 percent bootstrap CI [-0.010, -0.0001]). Competing models analysis confirmed this directionality: the forward mediation (PSU → cognitive flexibility → PE) was significant, whereas the reverse was not. These findings demonstrate that grit dimensions exhibit distinct longitudinal patterns with PSU and identify cognitive flexibility as a cognitive mechanism through which PSU specifically undermines effort persistence. Implications for dimensional approaches to grit and targeted interventions are discussed.

Humans↗

PubMed2026

Functions of tandem-repeat galectins and domain coordination governs galectin-4 activity in grass carp (Ctenopharyngodon idella).

Galectins are β-galactoside-binding lectins that play essential roles in innate immunity. Among them, tandem-repeat galectins (TrGals), typically composed of two distinct carbohydrate-recognition domains (CRDs) connected by a linker peptide, are well established as key regulators of pathogen recognition and host defense in mammals. However, their structural diversity and immunological functions in teleost fish remain poorly understood. In this study, five TrGals (Gal-4, Gal-8a, Gal-8b, Gal-9, and Gal-9like) were identified in grass carp. Sequence and structural analysis revealed that Gal-8a/b, Gal-9, and Gal-9like possess the canonical two-CRD architecture, whereas Gal-4 uniquely contains four highly similar tandem-repeat domains. All five TrGals were broadly expressed across examined tissues, with predominant expression in the liver. Upon Aeromonas hydrophila infection, Gal-4, Gal-8a, Gal-8b, and Gal-9 were rapidly up-regulated at early time points (3-6 h). To elucidate the functional significance of CRD number, recombinant full-length CiGal-4 (CiGal4-full) and three truncated variants containing one, two, or three CRDs (CiGal4-1CRD, CiGal4-2CRD, and CiGal4-3CRD) were generated and systematically characterized. All recombinant proteins contained the conserved β-sheet structure typical of galectin CRDs. Functional assays revealed that CiGal4-full displayed the strongest growth-inhibitory activity against all tested bacteria, whereas CiGal4-1CRD showed the weakest effect. Notably, CiGal4-2CRD exhibited the most potent bactericidal activity, surpassing the full-length protein, while CiGal4-3CRD showed no further enhancement. CiGal4-full and CiGal4-2CRD showed superior carbohydrate-binding activities compared with the other variants. Collectively, these results reveal that CRD copy number alone does not linearly determine galectin function. Instead, domain organization and conformational coordination are critical for optimizing antimicrobial activity. This study provides new insights into the structure-function relationships and evolutionary diversification of galectins in teleosts and highlights their potential as novel antimicrobial and immunomodulatory agents in aquaculture.

Animals↗

PubMed2026

Promoter Methylation of HOXA5 and NDRG2 in Multiple Myeloma Patients with Renal Impairment.

Renal impairment (RI) is frequently caused by multiple myeloma (MM), which makes clinical care more difficult if renal function deteriorates or renal failure develops. Thus, in this investigation, we looked at the relationship between HOXA5&NDRG2 promoter methylation in MM patients and evaluated their prognostic potential in predicting RI risk in MM patients. This study included 60 control volunteers and 120 MM patients. The promoter methylations of HOXA5&NDRG2 were quantitatively evaluated by real-time PCR (qPCR) after the extraction of gDNA from whole blood and then treated with bisulfite. The promoter methylation percentages of HOXA5&NDRG2 were significantly increased in MM patients (77.16 ± 2.43&45.49 ± 2.16;p < 0.05) when compared to controls (4.47 ± 0.61&3.33 ± 0.31,respectively), in stage II&III patients when compared to stage I patients and in patients with age ≥ 60 years when compared to patients with age < 60 years. While only the methylation percentage of NDRG2 promoter was significantly increased in MM patients with RI (53.61 ± 3.21,p < 0.05) when compared to MM patients without RI (37.37 ± 2.04). Results obtained from ROC curve revealed that both HOXA5&NDRG2 promoter methylation were good diagnostic tools for MM. The NDRG2 promoter methylation was good prognostic biomarker could predict renal while HOXA5 promoter in the prediction of MM staging. The Kaplan-Meier survival test showed that patients with higher HOXA5&NDRG2 promoter methylation had a shorter OS and a worse prognosis. Only NDRG2 promoter hypermethylation was significantly associated with the risk of RI development in MM patients. HOXA5&NDRG2 promoter hypermethylation may have roles in the molecular etiology of MM and could be used as a treatment regimen.

Humans↗

PubMed2026

The cellular protein TIAR mediates rapid initiation of West Nile virus genome RNA synthesis.

During the intracellular replication cycle of West Nile virus (WNV), genome RNA synthesis is initially inefficient but increases exponentially as viral replication complexes are sequestered in invaginations in the endoplasmic reticulum. In this study, we investigated the functional role of the cellular protein TIAR (T-cell intracellular antigen-related protein) in the transcription of WNV genome RNA. Close colocalization of cytoplasmic TIAR with viral double-stranded RNA was detected by a proximity ligation assay in WNV-infected cells. TIAR binds specifically to the WNV 3'(-) SL but not to the complementary WNV 5'(+) SL in in vitro RNA binding assays. Only the 3' end of the WNV minus-strand RNA was enriched by immunoprecipitation of infected cell lysates with anti-TIAR antibody. Stable overexpression of TIAR in clonal A549 cells increased the ratio of intracellular viral plus-strand to minus-strand RNA in a dose-dependent manner. TIAR contains three RNA recognition motifs (RRMs). Biophysical data indicated that only RRM2 directly contacts RNA and that up to three TIAR molecules can bind cooperatively to the WNV 3'(-) SL RNA. These data provide additional evidence that TIAR functions as a proviral host factor facilitating exponential amplification of WNV genome production in infected cells.IMPORTANCEWest Nile virus (WNV) is a mosquito-borne orthoflavivirus associated with increasing global human disease incidence. The molecular mechanisms underlying viral replication are not fully understood. In early stages of infection, viral genome transcription is inefficient; however, in late stages, viral genome transcription increases exponentially. T-cell intracellular antigen-related (TIAR) protein is a cellular protein that has been shown to interact with the 3' end of the WNV negative-sense antigenomic RNA. We obtained data showing colocalization of cellular TIAR with viral replication complexes in infected cells and an increased ratio of intracellular genomic to antigenomic viral RNA in TIAR-overexpressing cells, and confirmed preferential binding of TIAR to the 3' end of the WNV antigenome both in vitro and in infected cell extracts. We also demonstrated that multiple TIAR proteins can bind cooperatively to the WNV 3'(-) stem-loop RNA. These data provide supporting evidence for a model of TIAR-mediated rapid initiation of nascent genome RNA synthesis in infected cells.

TIAR↗

PubMed2026

From population to individual: advocating personalised digital tools for heat-health early warning in a changing climate.

Escalating heat extremes under climate change are imposing substantial health burdens, with 2023 and 2024 consecutively breaking global temperature records. Mounting evidence suggests that heatwaves elevate the risks of hospitalisation and mortality across multiple disease categories, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and acute kidney injury. Nonetheless, most existing heat-health warning systems remain primarily reliant on population-level predictions, and considering individual differences and disease-specific considerations when defining warning levels would benefit the effectiveness of early prevention for high-risk groups. In this Viewpoint, which is based on the framework of precision public health-delivering the right intervention to the right population at the right time-we propose a framework for personalised digital heat-health early warning tools comprising three dimensions: individualised, risk-stratified prediction models that generate tiered early warnings; personalised health prompts coupled with theory-informed behavioural interventions; and adaptive, equity-oriented alert delivery mechanisms tailored to diverse populations. Such tools have the potential to bridge precision disease prevention and climate adaptation, thereby helping to mitigate heat exposure risks and disease burdens, particularly among high-risk populations. Future implementation research will be essential to address substantial challenges related to feasibility, validation, and equity.

Journal Article↗

PubMed2026

Characterization and application potential of two newly isolated phages targeting the prevalent multidrug resistant Salmonella serovars in China.

The escalating global threat of multidrug resistant (MDR) Salmonella, a foodborne pathogen with animal-derived foods serving as the primary transmission vehicle, underscores the urgent need for effective lytic phages for biocontrol. From 142 environmental and farm samples in Shandong Province, we isolated 103 phages active against MDR S. Enteritidis and S. Typhimurium, which were the most prevalent Salmonella serovars in China. Two Siphoviridae phages vB-SenS-S1 and vB-SenS-SEC2 were selected for further study. With optimal multiplicities of infection (MOIs) of 10-2 (vB-SenS-S1) and 10-5 (vB-SenS-SEC2), both phages exhibited a 20 min latent period, yielding burst sizes of 52 and 37 PFU/cell, respectively. They also demonstrated stability across a range of temperatures (50-60 °C), pH levels (5-11), and after 1 h of UV exposure. Genomic analysis identified vB-SenS-S1 (43,002 bp, 47.04% GC) and vB-SenS-SEC2 (42,948 bp, 47.65% GC) as novel double-stranded DNA phages. Functional annotation confirmed the presence of genes essential for structural assembly, host lysis, and DNA replication/metabolism, and also verified the absence of resistance, virulence, and lysogeny-associated genes. Both phages vB-SenS-S1 and vB-SenS-SEC2 exhibited synergy with colistin and tetracycline. The synergy with colistin was particularly potent, leading to complete bacterial eradication in vitro. The in vivo therapeutic efficacy was further validated in both Galleria mellonella larvae and murine models of MDR Salmonella infection. Combination therapy with vB-SenS-SEC2 and colistin not only dramatically increased survival but also achieved a significant reduction in bacterial burden across multiple visceral organs of infected mice. Moreover, vB-SenS-S1 (108 PFU/mL) completely inhibited MDR Salmonella on chicken meat at 4 °C and -20 °C when initial contamination was ≤103 CFU/mL. This study not only expands the diversity of Salmonella phages but also highlights their potential as biocontrol agents in both clinical veterinary use and food decontamination, thereby enhancing food quality and safety at both the meat production source and the terminal product.

Animals↗

PubMed2026

Perioperative care for patients with opioid exposure and opioid use disorder: screening and treatment strategies.

PURPOSE OF REVIEW: The prevalence of opioid tolerance, dependence, and use disorder is increasing among patients presenting for surgical care, yet perioperative management strategies for these patients remain inconsistent. This review examines the impact of preoperative opioid exposure on surgical outcomes, the scope of untreated opioid use disorder (OUD) among surgical patients, and advances in clinical and systems-level approaches to perioperative care. RECENT FINDINGS: Preoperative opioid exposure independently predicts worse surgical outcomes, including higher opioid consumption, readmissions, complications, and mortality, in a dose-dependent manner. Perioperative opioid exposure predicts persistent opioid use after surgery, with the duration of exposure a stronger predictor of subsequent OUD than daily dose. Data-driven prescribing guidelines and structured opioid tapering reduce overprescribing without compromising pain control. Among surgical patients with diagnosed OUD, approximately two-thirds do not receive medications for opioid use disorder (MOUD), though treatment engagement and maintenance substantially improve outcomes. Evidence now clearly supports perioperative buprenorphine continuation over interruption. SUMMARY: Effective perioperative management of opioid-complex surgical patients requires systematic screening, evidence-based prescribing, MOUD continuation, and institutional infrastructure. The primary barrier is shifting from evidence generation to implementation.

Humans↗

PubMed2026

Beyond Photometric Consistency: Addressing Loss Insensitivity to Depth Noise in Endoscopic Estimation via Error Calibration.

Self-supervised monocular depth estimation in endoscopy is fundamentally constrained by the ill-posed nature of photometric supervision. In this work, we identify a critical yet overlooked cause of this ambiguity: the inherent insensitivity of photometric loss to depth noise. To overcome this intrinsic limitation, we propose Depth Error Calibration Learning (DECL), a two-stage framework that suppresses prediction variance and mitigates residual errors in self-supervised depth estimation. In Stage I (Variance Reduction), a cyclic depth generation strategy produces multiple depth hypotheses for the input image. The per-pixel empirical variance is quantified and integrated into a dedicated variance loss term, which penalizes inconsistent predictions and encourages the network to generate more stable and reliable depth estimates. In Stage II (Bias Calibration), an image-conditioned diffusion model refines the Stage-I depth prior and mitigates structured residuals through iterative denoising, thereby improving geometric accuracy and global consistency. Extensive experiments on three public endoscopic datasets demonstrate that DECL achieves consistent improvements over representative self-supervised monocular depth estimation methods under the evaluated protocols. Moreover, ablation studies on two representative backbones indicate that DECL is not restricted to a single network implementation, while broader validation on additional backbone families remains necessary. The source code is publicly available at https://github.com/DavidLuBit/EndoDenoising.

Journal Article↗

PubMed2026

Spatially resolved multi-omics analysis of indigenous Bacillus-fortified high-temperature Daqu.

Layer-dependent patterns associated with indigenous Bacillus fortification on high-temperature Daqu remain unclear. Here, six indigenous functional Bacillus strains were combined to fortify Daqu at three inoculation levels (QH4, QH5, QH6), with non-fortified as the control (CK). Upper, middle, and lower shelf-layer samples were profiled by physicochemical measurements, volatilomics, organic acid analysis, untargeted metabolomics, 16S/ITS amplicon sequencing, and metagenomics. PERMANOVA showed significant effects of treatment, spatial layer, and their interaction on physicochemical, volatile, bacterial, and fungal profiles (P = 0.001). Among the three inoculation levels, QH5 showed the most balanced performance: QH5_M exhibited the highest observed mean peak temperature (63.3 °C; +4.5 °C relative to CK_M), and its group-mean temperature remained ≥ 60 °C for seven consecutive days. Multi-omics analyses indicated coordinated, non-linear, and layer-dependent differences associated with indigenous Bacillus fortification, with QH5_M showing the most pronounced combined thermal, pyrazine, substrate, microbial, and predicted functional profile. These findings indicate that moderate indigenous Bacillus fortification was associated with distinct layer-dependent thermal and flavor profiles and coordinated microbial, metabolic, and predicted functional differences.

Bacillus↗

PubMed2026

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence↗

PubMed2026

Quantitative N-glycoproteomic analysis reveals glycosylation signatures of plasma immunoglobulin G in sepsis.

INTRODUCTION: Sepsis is a life-threatening condition resulting from organ dysfunction due to a dysregulated immune response to infection. Immunoglobulin G (IgG) plays a role in modulating immune responses. However, the precise IgG subclass-specific N-glycosylation profiles in patients with sepsis remain poorly characterized. METHODS: This study aimed to define the site-specific N-glycosylation signatures of plasma IgG subclasses in sepsis patients with different prognoses using quantitative glycoproteomics. By employing our established GlycoQuant strategy, we quantified the intact N-glycopeptides (IGPs) of IgG subclasses in 40 healthy controls and 40 sepsis patients with a clear prognosis. RESULTS: We identified 12 IGPs with altered abundances between patients with sepsis and healthy controls. After Benjamini-Hochberg (BH) correction of the 31 outcome-stratified IGP comparisons, IGP24 and IGP25 remained significant and met the prespecified fold-change criterion. Global BH correction across 124 IGP-clinical parameter correlations retained positive associations of IGP19, IGP22, and IGP23 with procalcitonin (PCT). In exploratory outcome-stratified ROC analyses, candidates were selected using the original unadjusted P-value and fold-change screen; five IGPs were evaluated, with IGP25 and IGP24 yielding the highest individual AUCs. Collectively, our findings underscore the potential of IgG subclass-specific glycosylation profiling as a novel translational approach for clinical applications in sepsis management. SIGNIFICANCE: Sepsis remains a leading cause of global mortality, with patient outcomes heavily dependent on timely diagnosis and accurate prognosis. The dysregulated host immune response, particularly involving immunoglobulins, is central to its pathophysiology. This study provides a significant advance in the field of clinical glycoproteomics by applying a quantitative, site-specific strategy to delineate the plasma IgG subclass N-glycosylation landscape in sepsis. We report, for the first time, a panel of subclass-specific intact IgG N-glycopeptides (IGPs) that are significantly altered in sepsis patients compared to healthy controls. The identified IGPs not only demonstrate diagnostic and prognostic potential but also show a significant correlation with procalcitonin, a key clinical severity index. These findings bridge a critical knowledge gap by moving beyond bulk IgG glycosylation analysis to subclass-resolved profiling, offering novel molecular insights into sepsis immunopathology. The identified glycosylation signatures hold substantial translational promise as a foundation for developing innovative, glycan-based biomarker panels to improve the precision management of this heterogeneous and life-threatening syndrome.

Humans↗

PubMed2026

The asymmetry of working memory training transfer: A systematic review and meta-analysis.

Working memory (WM) training is widely used to enhance cognitive performance; however, its transfer to untrained tasks remains controversial. Traditional theories emphasize task similarity as the primary determinant of training transfer, but they cannot fully explain emerging evidence of asymmetric transfer across tasks. Two directional transfer hypotheses are proposed here to explain this asymmetry: the resource-based transfer advantage hypothesis predicts stronger transfer from more to less cognitively demanding tasks, whereas the ability-based transfer advantage hypothesis predicts stronger transfer from tasks engaging broader task-general abilities to tasks engaging task-specific narrower abilities. The contrast between span and updating paradigms provides an informative framework for distinguishing these accounts, because updating tasks are generally more cognitively demanding, whereas span tasks involve broader abilities. Accordingly, we conducted a three-level meta-analysis of 55 studies (208 effect sizes; N = 3,492). The results showed that updating training transferred reliably to span tasks (g = 0.176, p < .001), whereas span training did not reliably transfer to updating tasks (g = 0.048, p = .453), supporting the resource-based account. This advantage of updating training also extended to non-WM outcomes and was more pronounced at lower training doses, in non-adult samples, and with verbal stimuli. Together, these findings extend WM transfer theory beyond task similarity by highlighting the importance of cognitive demand and offer guidance for WM training design.

Humans↗

PubMed2025

Application of causal discovery of factors driving dissolved oxygen in estuarine environments.

Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.

Estuaries↗

PubMed2026

Factors associated with additional intervention requirement following ESWL in pediatric patients with urolithiasis.

OBJECTIVE: To identify predictors of additional intervention following extracorporeal shock wave lithotripsy (ESWL) in pediatric patients and to develop a clinically applicable predictive model. MATERIALS AND METHODS: This retrospective cohort study included 647 pediatric patients who underwent ESWL between 2015 and 2025. Demographic, clinical, and radiological variables were analyzed. Univariable and multivariable logistic regression analyses were performed to identify independent predictors of additional intervention. Model performance was evaluated using receiver operating characteristic curve analysis. RESULTS: Additional intervention was required in 65 patients (10.0%). On multivariable analysis, stone size 10-20 mm (OR: 3.04, p = 0.003), moderate (OR: 2.16, p = 0.049) and severe hydronephrosis (OR: 6.05, p < 0.001), and multiple stones (OR: 3.52, p = 0.030) were identified as independent risk factors. Increasing age (OR: 0.84, p = 0.026), history of urolithiasis (OR: 0.41, p = 0.006), and lower calyx location (OR: 0.14, p = 0.034) were associated with a reduced risk. The model demonstrated good discriminative performance (AUC: 0.794), with a sensitivity of 72% and specificity of 75%. Internal validation using bootstrap resampling demonstrated stable model performance, yielding a corrected AUC of 0.732. CONCLUSION: Stone burden, hydronephrosis severity, and stone multiplicity are key determinants of additional intervention after ESWL in pediatric patients. The proposed model shows good predictive performance and may support individualized risk stratification and clinical decision-making.

Humans↗