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PubMed2026

Sex-stratified mortality trends in preterm birth complications in Sierra Leone: progress, persistence, and equity implications.

BACKGROUND: Preterm birth complications remain a leading cause of neonatal mortality in Sierra Leone, despite recent health system gains. Evidence on long-term sex-specific disparities in mortality due to preterm birth complications is limited, constraining equitable neonatal care planning. OBJECTIVE: To examine two‑decade trends in sex‑stratified mortality from preterm birth complications using standardized equity indicators. METHODS: We conducted a retrospective longitudinal analysis of sex-disaggregated mortality estimates from the World Health Organization (WHO) Global Health Estimates (GHE), accessed through the WHO Health Equity Assessment Toolkit (HEAT), Built-in Database Edition (Version 6.0). Mortality rates per 100,000 population were extracted for 2001, 2006, 2011, 2016, and 2021. Inequality was assessed using absolute difference (D), relative ratio (R), population attributable risk (PAR), and population attributable fraction (PAF). RESULTS: Mortality declined substantially between 2001 and 2021 for both males (85.1-49.3 per 100,000) and females (71.2-39.9 per 100,000). Male mortality remained consistently higher across all years, with relative ratios indicating approximately 20-25% excess mortality among male neonates. Absolute inequalities narrowed modestly over time, whereas relative inequalities remained largely unchanged. PAR and PAF remained close to zero throughout the study period. Wider uncertainty intervals in earlier years reflected limited empirical data availability. CONCLUSION: Although preterm mortality declined over two decades, a persistent male disadvantage remained in Sierra Leone. These findings highlight the importance of integrating sex-disaggregated equity monitoring into neonatal policies and programmes. Future research should evaluate strategies to reduce the persistent excess mortality among male neonates while sustaining overall improvements in neonatal survival and progress toward Sustainable Development Goal 3.2.

Humans↗

PubMed2026

Association of ERBB4 and SHBG gene polymorphisms with polycystic ovarian syndrome in South Indian women: a case-control genetic analysis.

INTRODUCTION: Polycystic ovary syndrome (PCOS) is a multifactorial endocrinological disorder with a substantial genetic component. However, the role of genes involved in follicular development and androgen regulation remains incompletely understood, particularly in South Indian populations. This study aimed to evaluate how variations in the ERBB4 and SHBG genes affect PCOS risk. METHODOLOGY: A hospital-based case-control study was conducted among 400 South Indian women, comprising 200 women with PCOS and 200 age-matched healthy controls. Genomic DNA was extracted to study SNPs at ERBB4 (rs2178575 and rs1351592) and SHBG (rs1799941 and rs727428) using ARMS-PCR genotyping. The study compared genotype and allele frequencies between cases and controls while assessing their associations with allelic, homozygous, heterozygous, dominant, recessive, and over-dominant genetic models. Genotyping accuracy was confirmed by re-genotyping and Sanger sequencing of a subset of samples. RESULTS: The ERBB4 rs2178575 polymorphism demonstrated a significant association with PCOS, as the AA genotype and A allele combination increased risk across all three genetic models, including homozygous, recessive, and allelic models. The ERBB4 rs1351592 variant was associated with 3-fold higher risk of PCOS in heterozygous and GC carriers. The SHBG rs1799941 polymorphism showed a significant link to PCOS through its effects on heterozygous and allelic states, whereas rs727428 displayed no significant connection due to its monomorphic distribution. CONCLUSION: These findings suggest that polymorphisms in ERBB4 and SHBG may contribute to PCOS susceptibility in South Indian women in a locus- and model-specific manner, revealing the intricate genetic structure that defines this medical condition.

Humans↗

PubMed2026

Development and validation of an LC-MS/MS method for the quantification of the KRASG12C inhibitor divarasib.

Divarasib is a newly developed covalent KRASG12C inhibitor, currently under clinical investigation in a phase 3 trial in patients with non-small cell lung cancer (NSCLC). At the moment, very limited pharmacokinetic data are publicly known. However, obtaining more insight into the pharmacokinetic properties of divarasib is important, since this may provide a better understanding of its efficacy and safety risks. Pre-clinical studies have been performed in mouse models to evaluate the effect of drug transporters and drug-metabolizing enzymes on the plasma exposure and tissue distribution of divarasib. Therefore, a reliable quantification method is required. To our knowledge, no bioanalytical assay of divarasib has been published yet. Therefore, in this study we developed and validated an assay to quantify divarasib in human plasma and in eight different mouse-related matrices, and partially in mouse plasma, using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method was initially evaluated over a concentration range of 1-10,000 nM. However, due to carry-over observed at 10,000 nM, the validated calibration range was established at 1-2000 nM, with matrix-dependent LLOQs of 1-10 nM. Erlotinib was used as an internal standard and acetonitrile was utilized to perform protein precipitation as sample pretreatment. Divarasib demonstrated stability in human plasma and in mouse plasma and tissue homogenates under various experimental conditions. A pilot in vivo study showed the applicability of our validated LC-MS/MS method. Ongoing clinical trials may collect plasma samples, and this developed method enables quantification of divarasib in both mouse and human plasma samples.

Animals↗

PubMed2026

Artificial intelligence-derived myocardial fibrosis on cardiac magnetic resonance for prognosis in cardiomyopathy: A systematic review of a sparse evidence base.

BACKGROUND: Myocardial fibrosis on cardiovascular magnetic resonance (CMR), assessed by late gadolinium enhancement (LGE) and parametric mapping, is an established predictor of adverse events in cardiomyopathy. We assessed whether artificial intelligence (AI) quantification of fibrosis adds independent prognostic value. METHODS: We searched six databases, a clinical-trials register, and a preprint server from inception to 13 June 2026. Eligible studies used AI to generate a fibrosis marker in adults with ischemic or nonischemic cardiomyopathy, with covariate-adjusted outcomes over ≥12 months. Risk of bias was assessed using PROBAST, PROBAST+AI, and QUIPS. Fewer than three comparable studies precluded meta-analysis; certainty was rated using GRADE. RESULTS: Of 448 records (381 after de-duplication), 18 full texts were reviewed and two included, one peer-reviewed and one preprint. In an ischemic-cardiomyopathy registry (Ghanbari et al.; n = 216 analytic, 26 events), AI-derived dense LGE scar predicted arrhythmic events (univariable hazard ratio [HR] 2.35, 95% CI 1.33-4.15), and AI-derived but not manual scar improved discrimination beyond guideline criteria (area under the curve 0.63 to 0.68; p = 0.02). In a nonischemic dilated-cardiomyopathy preprint (Kim et al.; n = 347, 119 events), automated extracellular volume ≥30% predicted cardiovascular death or heart-failure hospitalization (adjusted HR 2.00, 95% CI 1.32-3.03). Both were at high risk of bias, with data-derived thresholds and no external validation. CONCLUSIONS: Across only two studies, AI-derived fibrosis was independently associated with adverse cardiovascular events, but its added value over manual quantification remains unproven. Certainty was very low. The evidence base is sparse and not yet ready for clinical use.

Humans↗

PubMed2026

Beyond Glycaemia: Fear of Hypoglycaemia, Cognition and Functional Mobility After Advanced Hybrid Closed-Loop Therapy in Older Adults With Type 1 Diabetes: A Prespecified Secondary Analysis of a Randomised, Single-Centre Study.

BACKGROUND: Evidence on psychological, cognitive and functional outcomes of advanced diabetes technologies in older adults with long-standing type 1 diabetes (T1D) remains limited. We evaluated whether initiation of advanced hybrid closed-loop (AHCL) therapy was associated with changes in fear of hypoglycaemia, diabetes distress, psychological well-being, cognition, frailty-related measures and mobility-related function in adults aged ≥ 65 years with T1D. METHODS: This prespecified, exploratory secondary analysis was conducted within a single-centre, open-label, randomised, controlled, parallel-group trial including adults aged ≥ 65 years with long-standing T1D. Participants were randomly assigned (1:1) to initiate AHCL therapy using the MiniMed 780G system or to continue standard diabetes treatment. The secondary outcomes included WHO-5, the 17-item Diabetes Distress Scale (DDS), Hypoglycemia Fear Survey-II (HFS-II), Montreal Cognitive Assessment, Digit Symbol Substitution Test, Fried frailty phenotype and performance-based functional measures. No formal sample-size calculation was performed for these secondary outcomes. RESULTS: Thirty-one participants were randomised and 29 completed 12 months of follow-up and were included in the treatment-effect analyses. In the baseline-adjusted primary analysis, AHCL therapy was associated with a lower HFS-II score than standard treatment (adjusted mean difference -18.9; 95% CI: -32.4 to -5.4; nominal p = 0.008), although this finding did not remain statistically significant after Holm correction (adjusted p = 0.104) or in an exploratory model additionally adjusted for sex (difference -13.6; 95% CI: -32.2 to 5.0; p = 0.145). Diabetes distress, psychological well-being, global cognition and processing speed did not differ between groups. In sex-adjusted sensitivity analyses, the between-group differences remained statistically significant for 6-min walk distance (92.6 m; 95% CI: 36.8 to 148.3; p = 0.002) and Timed Up and Go performance (-2.27 s; 95% CI: -4.28 to -0.27; p = 0.028), but not for gait speed (0.27 m/s; 95% CI: -0.05 to 0.59; p = 0.099). At 12 months, 12 of 14 AHCL participants were robust and 2 were pre-frail; in the control group, 11 of 15 were robust and 4 were pre-frail. No participant was classified as frail at follow-up. CONCLUSIONS: In this small, selected cohort, AHCL therapy was associated with a nominally lower fear-of-hypoglycaemia score and better performance on selected mobility-related tests over 12 months. The fear-of-hypoglycaemia finding did not remain statistically significant after correction for multiple comparisons or additional adjustment for sex. Six-minute walk distance and Timed Up and Go remained statistically significant in the exploratory sex-adjusted sensitivity analyses, whereas the gait-speed difference did not. No measurable between-group deterioration in global cognition or processing speed was observed. These exploratory findings require confirmation in larger studies with balanced representation by sex and direct measurement of physical activity. These findings also support a person-centred clinical message: older age alone should not be regarded as a barrier to AHCL when treatment is introduced with individualised education and appropriate ongoing support.

Humans↗

PubMed2026

Changes in sexual behavior among women in studies evaluating the dapivirine vaginal ring for HIV prevention.

BACKGROUND: Access to novel HIV prevention technologies often raise concerns of risk compensation. This analysis examined changes in the sexual behaviors of MTN 020/ASPIRE participants, a placebo controlled randomized control trial, who subsequently enrolled in MTN-025/HOPE, an open-label extension using the dapivirine vaginal ring. METHODS: Both studies enrolled healthy, sexually active, HIV-negative women from Malawi, South Africa, Uganda and Zimbabwe. Longitudinal data on participants' sexual behaviors, specifically sex with a nonprimary partner (past 3 months), and use of male or female condoms at the last vaginal sex act were compared between ASPIRE and HOPE. Conditional and mixed ordinal logistic regression models evaluated associations between study and sexual behaviors at enrollment, and quarterly over the first 12 months. RESULTS: Of the 2629 individuals enrolled in ASPIRE, 1456 (55%) participated in HOPE. At enrollment, the proportion of participants who reported sex with a nonprimary partner and condom use at last vaginal sex act did not differ by study. Across all quarterly follow-up visits, sex with a nonprimary partner was more common in HOPE (13.9-18.7%) than ASPIRE (10.7-12.6%); adjusted OR 1.47, 95% CI 1.24-1.75, P < 0.001. There was no difference in condom use at the last vaginal act across all quarterly follow-up visits between ASPIRE (36.5-42.7%) and HOPE (43.6-46.7%); adjusted OR 1.05, 95% CI 0.94-1.18. CONCLUSION: More women reported sex with nonprimary partners in HOPE, with little change in condom use over time between the two studies. Understanding behavior changes during PrEP use allows for tailored, holistic reproductive health programming.

Humans↗

PubMed2026

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans↗

PubMed2026

Driving Under the Influence of Cannabis Among U.S. Young Adults Who Use Cannabis: Evidence From the 2021-2024 National Survey on Drug Use and Health.

PURPOSE: To estimate the prevalence of driving under the influence of cannabis (DUIC) and identify associated factors among U.S. young adult drivers reporting past-year cannabis use. METHODS: This cross-sectional study analyzed pooled 2021-2024 National Survey on Drug Use and Health. The analytic data were restricted to drivers aged 18-25 years who reported past-year cannabis use (N = unweighted 17,141; weighted N = 10,814,381). The outcome was self-reported past-year DUIC. Independent variables included demographics, substance use, mental health, cannabis-related perceptions, and driving behaviors. These relationships were assessed by modified Poisson regression. RESULTS: The weighted prevalence of DUIC was 28.0%, representing approximately over three million young adults. DUIC prevalence increased with cannabis use frequency, from 2.51 times higher among those using cannabis 12-49 days (adjusted prevalence ratio [APR]: 2.51; 95% confidence interval [CI]: 2.29-2.75) to 3.63 times higher among those reporting use on 300-365 days (APR: 3.63; 95% CI: 3.60-3.76), compared with those using cannabis 1-11 days. Cannabis use disorder (APR: 2.34; 95% CI: 2.06-2.65), simultaneous alcohol and cannabis use (APR: 1.29; 95% CI: 1.28-1.30), and perceived easy cannabis availability (APR: 2.36; 95% CI: 2.33-2.39) were also associated with higher prevalence of DUIC. Nonenrollment in school and living in a state with a medical cannabis law were associated with lower DUIC prevalence. DISCUSSION: DUIC is highly prevalent among U.S. young adults who use cannabis, with a clear graded association across categories of cannabis use frequency. Public health interventions should address frequent use, cannabis use disorder, alcohol-cannabis co-use, and perceived cannabis availability.

Humans↗

PubMed2026

Therapeutic Exercise Protocol During Hospitalization in Pediatric Oncohematological Patients: Randomized Clinical Trial.

BACKGROUND: Leukemias, lymphomas, and central nervous system tumors are among the most common pediatric cancers and may lead to motor deficits, impaired balance, reduced muscle strength, fatigue, and decreased functional capacity. Early physiotherapy during hospitalization may help prevent inactivity and support functional preservation in this population. OBJECTIVE: To evaluate the effects of a therapeutic exercise program on quality of life, muscle strength, fatigue, and functional capacity in hospitalized pediatric oncohematological patients. METHODS: Thirty participants aged 8-17 years with oncohematological diseases were randomized to an intervention group (IG) or a minimal active physiotherapy comparator group (CG). Assessments included the 6-min walk test, handgrip dynamometry, the PedsQL Multidimensional Fatigue Scale, and the PedsQL Cancer Module at admission and discharge. The IG performed daily 25-min supervised sessions including aerobic, resistance, and breathing exercises with ambulation guidance, whereas the CG received breathing exercises and ambulation guidance. RESULTS: No significant group × time interactions were observed for total fatigue or its domains, overall quality of life or its assessed domains, handgrip strength, or six-minute walk test distance. Time-related changes were observed for some outcomes, but these occurred without evidence of differential change between groups and were not interpreted as effects of the structured exercise protocol. No intervention-related adverse events requiring permanent protocol discontinuation were recorded. CONCLUSION: The structured in-hospital therapeutic exercise protocol could be delivered under close clinical supervision without recorded intervention-related adverse events requiring permanent discontinuation. However, the structured protocol did not demonstrate superiority over the minimal active physiotherapy comparator for fatigue, quality of life, muscle strength, or functional capacity. These findings should be interpreted cautiously because of the small sample size, clinical heterogeneity, variable intervention exposure, and limited intervention-fidelity data. TRIAL REGISTRATION: Brazilian Registry of Clinical Trials (ReBEC), RBR-8sxnfyd.

Humans↗

PubMed2026

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans↗

PubMed2026

Efficacy of a high-frequency repetitive transcranial magnetic stimulation for craving reduction in adolescents with gaming disorder: a 4-week randomized control trial with 24-week follow-up.

BACKGROUND: With the widespread popularity of online gaming, gaming addiction has come under scrutiny. While there is ongoing research on the diagnosis and treatment of gaming disorder among adolescents, the clinical robustness and reliability of intervention strategies remain uncertain. METHODS: A 4-week, double-blind, randomized, sham-controlled clinical trial was conducted to evaluate the efficacy of noninvasive, high-frequency repetitive transcranial magnetic stimulation (rTMS) in alleviating psychological craving in adolescents diagnosed with gaming disorder. Sham rTMS was administered to the control group using the tilted-coil method. Both groups of participants were treated with SSRI medications. A total of 80 adolescents with gaming disorder participated in this study, and 73 ultimately completed the 24-week follow-up. The primary outcome was the change in craving levels before and after the rTMS intervention, as assessed by the Visual Analogue Scale (VAS). Secondary outcomes included changes in anxiety and depression levels before and after the intervention, as assessed by the HAMA and HAMD. RESULTS: We assessed levels of psychological craving, anxiety, and depression among adolescents with gaming disorder at baseline, after completing a 4-week intervention, and at a 24-week follow-up post-intervention. Our repeated-measures MANOVA results, adjusted for course variables, revealed a significant main effect of rTMS intervention on psychological craving levels in adolescents addicted to online games (F(11, 781) = 11.238, P < 0.001, partial η² = 0.142), as well as significant main effects on time (F(11, 781) = 6.809; P < 0.001, partial η² = 0.091) and group effects (F(1, 71) = 26.707, P < 0.001, partial η² = 0.282). In addition, repeated-measures ANOVA results showed significant time effects for anxiety (F(2, 142) = 20.747, P < 0.001, partial η² = 0.234) and depression levels (F(2, 142) = 22.277, P < 0.001, partial η² = 0.285) among adolescents with gaming disorder, with nonsignificant between-group effects and no intergroup interaction. In the active stimulation group, changes in psychological craving levels after 4 weeks of treatment were significantly and positively correlated with changes in anxiety levels after 4 weeks of treatment in adolescents addicted to online games (r = 0.335, P < 0.05). CONCLUSION: Our findings indicate that high-frequency rTMS targeting the left dorsolateral prefrontal cortex may be a promising approach for reducing psychological craving in adolescents with gaming disorder. TRIAL REGISTRATION: ChiCTR2500102979 in chictr.org.cn, registered on May 22, 2025.

Humans↗

PubMed2026

Prevalence of Slowly Expanding Lesions in Patients With Multiple Sclerosis: A Systematic Review and Meta-Analysis.

BACKGROUND AND OBJECTIVES: Chronic active lesions (CALs) reflect chronic inflammation in multiple sclerosis (MS). Slowly expanding lesions (SELs) are CALs identified on conventional MRI by linear, concentric expansion over time, while paramagnetic rim lesions (PRLs) are CALs characterized by a paramagnetic rim on susceptibility-sensitive MRI. However, the prevalence of SELs and their overlap with PRLs remain unclear. The aims of this study were to (1) estimate the proportion of SELs among all T2 lesions and the proportion of patients with at least 1 SEL and (2) assess the proportion of SELs overlapping with PRLs. METHODS: We systematically searched PubMed, Scopus, Web of Science, and Embase on February 1, 2026, for studies evaluating SELs in MS. At least 2 authors independently assessed study eligibility. Primary outcomes were the pooled proportion of SELs among T2 lesions and the proportion of patients with at least 1 SEL. We estimated mean per-patient volumes of SELs and total T2 lesions and the proportion of SELs overlapping with PRLs. Random-effects generalized linear mixed-effects models and inverse-variance methods were used, with between-study heterogeneity assessed using τ2 and I2 and robustness using sensitivity analyses. Univariable meta-regression explored heterogeneity. PROSPERO: CRD42024603778. RESULTS: Of 5,980 records, 20 studies comprising 4,786 patients with MS were included (mean age: 43.6 ± 6.3 years; 63.7% female). Sample sizes varied by outcome. SELs accounted for 14% (95% CI 10-21) of all T2 lesions, and 78% (67-85) of patients had at least 1 SEL. After sensitivity analysis, per-patient mean volumes were 1.42 mL (0.79-2.06) for SELs and 10.6 mL (8.53-12.67) for total T2 lesions. In total, 11% (6-20) of SELs overlapped with PRLs. In subgroup analyses, proportions of SELs were similar in relapsing-remitting and progressive MS (15%), but the proportion of patients with at least 1 SEL was higher in progressive MS. Between-study heterogeneity was high across analyses with no significant sources identified. DISCUSSION: Although SELs represent a minority of T2 lesions, most patients have at least 1 SEL and a subset overlaps with PRLs, suggesting a partial correspondence between these 2 imaging markers of chronic inflammatory activity. Limitations include possible publication bias, high unexplained heterogeneity, differences in SEL identification methods, and differences in MRI time point number/timing.

Humans↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

Furanic compounds in different coffee extraction systems: Analysis of the main influencing factors and correlation with acrylamide.

This study investigates how different coffee types representative of distinct roast profiles and brewing methods jointly affect the occurrence of furanic compounds and acrylamide in brewed coffee. Coffees were prepared using eight extraction methods (AeroPress, Clever, Chemex, French Press, Moka, Pure Brew, Turkish and V60). Five furanic compounds (furfural, furfuryl acetate, 5-methylfurfural, furfuryl alcohol and 5-hydroxymethylfurfural) were quantified in coffee powders and brews by HS-SPME-GC-MS, while acrylamide was determined by UHPLC-MS/MS. Moka and Turkish brews consistently exhibited the highest concentrations of furanic compounds, whereas paper-filtered pour-over methods (V60 and Chemex) showed the lowest levels. Pearson correlation analysis revealed coffee-dependent relationships between furanic compounds, acrylamide and extraction parameters with the strongest associations observed in dark-roasted coffee, reflecting advanced Maillard reaction chemistry. Overall, these results demonstrate that contaminant levels arise from the combined effects of intrinsic coffee chemistry and brewing mechanics and support targeted mitigation strategies: such as roast selection and brewing method optimization.

Acrylamide↗

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↗

PubMed2026

Design of an innovative framework based hybrid catalyst for simultaneous and sensitive monitoring of food additive and preservative of vanillin and nitrite in direct samples.

As vanillin (VAN) and nitrite (NIT) contamination in the food chain poses substantial threats to environmental and public health, rapid and portable detection is essential. The present study presents the first electrochemical sensor report based on a hybrid composite of Ni-TPA-MOF and MoS2/Co3O4. The oxidation of VAN and NIT exhibited sharp peaks and less over-potential on Ni-TPA-MOF/MoS2/Co3O4/GCE than on control electrode surfaces. On modified composite electrode surfaces, pH and scan rate were investigated for VAN and NIT. Further, the oxidation current exhibited high linearity at VAN and NIT concentrations of 5 nM-1000 μM and 3 nM-1250 μM, with detection limits of 0.102 nM and 0.073 nM (S/N = 3). We also applied anti-interfering ability (five/ten-fold excess of co-interfering compounds) and practical tests to various food-based real samples, with high recoveries of 98.85-102.41%. This study highlights the catalytic properties of Ni-TPA-MOF/MoS2/Co3O4 and demonstrates the sensor as a promising tool for food safety.

Benzaldehydes↗

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

Targeted Nanoparticle Delivery CRISPR/Cas9: overcoming biological barriers, enhancing stability, and improving therapeutic precision.

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has emerged as a promising gene-editing platform for genetic disorders; however, its in vivo application remains limited by low delivery efficiency and biological barriers. Many CRISPR payloads fail to reach target sites due to extracellular degradation, immune clearance, and intracellular trafficking limitations. This review examines the interplay between biological barriers and nanoparticle engineering strategies for CRISPR/Cas9 delivery. A barrier-oriented engineering approach is proposed as a central framework, encompassing ligand-based surface modification for enhanced targeting and uptake, improved circulation stability via PEGylation and biomimetic coatings, and optimized payload release through endosomal escape strategies. Stimulus-responsive nanoparticle systems further enable spatiotemporal control over payload release. Nuclear targeting strategies, including optimization of nuclear localization signals (NLS) and exploitation of endogenous trafficking pathways, are highlighted as key factors for improving genome-level editing efficiency. Despite these advances, major challenges-including limited intracellular delivery efficiency, insufficient targeting precision, and safety concerns-continue to hinder clinical translation. Future directions highlight artificial intelligence-driven nanoparticle design, personalized delivery systems, and next-generation CRISPR platforms. Overall, an integrated, barrier-oriented engineering strategy is essential for advancing CRISPR/Cas9 delivery toward clinical applications, ultimately advancing global good health and well-being.

CRISPR/Cas9↗