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PubMed2026

Definition and prevalence of residual disease in inflammatory arthritis: a systematic literature review and meta-analysis.

OBJECTIVE: To assess how residual disease (i.e., clinically relevant signs/symptoms despite achieving treatment targets) is defined in rheumatoid arthritis (RA), psoriatic arthritis (PsA) or axial spondyloarthritis (axSpA), and estimate the prevalence/severity of residual disease in these diseases. METHODS: Systematic review of original research in RA/PsA/axSpA. Two key residual disease components were extracted: (1) the patient's disease state (often remission/low disease activity) and (2) which residual signs/symptoms were measured, e.g. swollen joints or fatigue (indicators of residual disease). Frequencies of the disease states and indicators were described (Objective 1). Prevalence (%) and severity (absolute score on instrument, e.g. fatigue NRS) of residual disease was analysed by indicator, using random effects meta-analysis (≥4 studies) or descriptively (<4 studies) (Objective 2). RESULTS: Regarding residual disease definitions (59 studies), disease states were almost exclusively disease activity-based (>99%), but with much variation in specific instruments/thresholds. Across diseases, physician-reported (66%) and patient-reported (73%) indicators were used more often than laboratory indicators to define residual disease (46%). Especially peripheral joint counts, pain, physical function and CRP were frequently used (42-56% of studies). The prevalence of residual disease (84 studies) was notable. For example, 5-25% of RA and PsA patients in remission still had swollen joints, and up to one-third reported relevant pain or fatigue. For axSpA, evidence was limited. CONCLUSION: Residual disease definitions in RA/PsA/axSpA are based on various disease activity instruments/thresholds and indicators (signs/symptoms). Residual disease affects up to half of patients. Future research should aim for a consensus-based definition of residual disease.

Humans↗

PubMed2026

Subtle cortical thinning in the temporal pole in middle-aged APOE-ε4 and PICALM (rs3851179) AA/AG carriers without dementia.

The symptoms of Alzheimer's disease (AD) are caused by neurodegeneration and atrophy in particular brain regions, especially in the temporal lobe. However, the influence of genetic risk on cortical thickness prior to dementia onset, remains unclear. This study aimed to explore the relationship between AD genetic risk (related to APOE and PICALM genes) and cortical thickness in selected regions of interest (ROIs) in middle-aged individuals without dementia. Sixty-nine (N = 69) participants (34 females, 35 males; age: 55.45 ± 3.19) underwent magnetic resonance imaging (MRI). They were divided into three groups based on their genetic AD risk: A+ P+ (APOE/PICALM risk variants), A+P- (APOE risk variant, PICALM neutral variants), and the N group (APOE/PICALM neutral alleles). Cortical thickness was analyzed using CAT12 software (surface-based morphometry with the Destrieux atlas) based on T1-weighted MR images in five ROIs referred to as "the cortical signature of AD" in previous studies. The A+P- group had a thinner right temporal pole cortex than non-carriers after controlling for sex, age, and Raven's Progressive Matrices scores. Although this finding did not survive FDR correction across the 10 tested regions, it is consistent with our hypotheses and prior literature. No other differences in cortical thickness were found in the analyzed regions of AD "signature". The observed effect was restricted to single-risk APOE carriers without PICALM risk alleles. Therefore, further research is needed to understand the genetic interplay between these two genes in conferring AD risk.

Humans↗

PubMed2026

Meta-analysis of growth and inactivation kinetics of Legionella.

Quantitative risk assessments intended to inform evidence-based water management plans and public health targets for Legionella in engineered water systems are constrained by fragmented and heterogeneous growth and inactivation kinetics. We conducted a meta-analysis of 25 growth and 39 thermal- and chemical-inactivation studies, fitting microbial persistence models to harmonize parameters. Nonlinear models outperformed first-order formulations, indicating that lag phases and resistant or protected subpopulations are central to Legionella persistence. Random forest analysis identified environmental and methodological drivers of variability based on 226 growth rates and reduction times for thermal (209) and chemical (135) inactivation. Growth was primarily governed by temperature, nutrient availability, and compatible Legionella-host pairings; thermal inactivation by quantification method, temperature, and turbidity; and chemical inactivation by inoculum size, disinfectant type, concentration, and host-associations. Accordingly, temperature-dependent growth parameters and exposure metrics for heat, free-chlorine, and monochloramine, expressed as TT (Temperature×time) and CT (Concentration×time), were derived as condition-specific inputs for predictive models. Growth optima around 37-40 °C, together with lag-time estimates, indicate that hot-water temperature setbacks and energy-saving practices may favor Legionella proliferation under repeated or prolonged lukewarm exposure. Culture- and viability-based TT differences highlight the need to consider viable‑but-non-culturable persistence in monitoring programs. CT comparisons suggest monochloramine may be advantageous because of its lower apparent sensitivity to host-associated protection. Although limited by restricted experimental conditions, the findings show that predictive models should account for microbial ecology, water matrix effects, and quantification endpoints. Future kinetic studies should prioritize realistic multi-host systems, strain pre-adaptation, complementary viability measurements, and standardized protocols and reporting to ensure reproducibility and enable robust system-level predictive modeling.

Legionella↗

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

Continuous theta-burst stimulation over the right DLPFC modulates central executive network connectivity in depression: exploratory analysis of a randomized clinical trial.

Previous studies suggest that transcranial magnetic stimulation exerts antidepressant effects and is associated with alterations in functional connectivity (FC), but the neural correlates remain unclear. This exploratory sham-controlled trial investigated the effect of continuous theta-burst stimulation (cTBS) over the right dorsolateral prefrontal cortex (DLPFC) on FC in major depressive disorder (MDD). Seventy MDD patients were randomized to receive two-week treatment of personalized cTBS or sham stimulation. Resting-state fMRI was performed at baseline and post-treatment. Ultimately, 31 patients in the active cTBS group and 28 patients in the sham group passed imaging quality control and were included in the final analysis. To identify the FC that may have been influenced by cTBS treatment, two complementary FC analyses were conducted: (1) voxel-wise degree centrality (DC) followed by seed-based FC, and (2) an individual FC analysis based on the stimulation targets. Furthermore, correlations between FC changes and clinical symptoms improvement were examined. Both groups exhibited reductions of depression scores, with greater improvement in the active group. Compared to the sham group, active cTBS showed increased DC in the precuneus and elevated FC between the precuneus (within the para-cingulate network) and the right inferior parietal lobule (IPL) and DLPFC. Further stimulation target-based analysis revealed increased FC between stimulation targets and both the precuneus and visual regions following treatment. Our findings reveal neural changes associated with cTBS over the right DLPFC in MDD, notably involving the precuneus and its connectivity with the right IPL/DLPFC, suggesting alterations within the central executive network. TRIAL REGISTRATION: chictr.org.cn; ChiCTR2300068273.

Humans↗

PubMed2026

Chronic postsurgical pain: risk assessment and mitigation.

PURPOSE OF THE REVIEW: Chronic postsurgical pain (CPSP) and persistent postoperative opioid use (PPOU) are two of the most common complications of a number of surgical interventions, which can cause significant personal and economic negative consequences. This review outlines known and potential risk factors for CPSP and PPOU and approaches to reduce these risk factors. RECENT FINDINGS: Modifiable risk factors for developing CPSP include psychological distress, preoperative pain intensity, and perioperative opioid exposure. Although less studied, psychological comorbidities are also risk factors for PPOU. Evidence-based mitigation strategies include psychological interventions and perioperative opioid sparing. SUMMARY: A number of perioperative risk factors for developing CPSP and PPOU have been identified, and anesthesiologists should be cognizant of these risk factors and potential risk mitigation strategies. Additional prospective studies are needed to further develop easily adoptable, evidence-based interventions to reduce the incidence of CPSP and PPOU.

Humans↗

PubMed2026

Integrated transcriptomic and metabolomic analysis of fluoride tolerance-related pathways and differentially expressed genes in silkworm strain XSKD.

XueSong KD (XSKD) silkworm strain exhibits prominent fluoride tolerance, yet the underlying molecular mechanisms of fluoride tolerance remains unclear. In the present study, fourth-instar pre-molting XSKD silkworms were used as experimental materials for integrated transcriptomic and untargeted metabolomic analyses. In total, 572 differentially expressed genes and 90 differential metabolites were screened. GO enrichment and KEGG enrichment based on the hypergeometric distribution model revealed that 13-Hydroxy-9Z,11E-octadecadienoic acid (13-(S)-HODE) acts as the core differential metabolite, which is significantly enriched in the linoleic acid metabolism pathway. Within this pathway, LOC101737302 and CYP338A1 display opposite expression trends and show correlations with pathway metabolites. Based on multi-omics data, this study preliminarily characterizes the lipid metabolic response under fluoride stress, providing omics dataset support for further in-depth exploration of the molecular mechanism of fluoride tolerance in silkworms.

Animals↗

PubMed2026

Effects of permissive hypercapnia on intraoperative cerebral oxygenation and early postoperative cognitive function in older patients with fragile brain function during the non-acute phase undergoing laparoscopic colorectal surgery: A randomized controlled trial.

BACKGROUND AND PURPOSE: Older adults with non-acute fragile brain function (NFBF) may be particularly susceptible to perioperative disturbances in cerebral oxygenation and postoperative neurocognitive decline. Permissive hypercapnia (PHC) may enhance cerebral oxygenation, but its effects in this population remain unclear. We examined whether PHC-based ventilation improves intraoperative regional cerebral oxygen saturation (rSO2) and early postoperative cognitive outcomes in older patients with NFBF undergoing elective laparoscopic colorectal surgery. METHODS: In this single-center, single-blind randomized trial, 76 patients were assigned in a 1:1 ratio to PHC-based or conventional ventilation. The primary outcome was the absolute change in rSO2 from baseline (T0) to the end of surgery (T4). Analyses followed the intention-to-treat principle, with prespecified per-protocol sensitivity analysis. Secondary outcomes included intraoperative rSO2 trajectories, cerebral oxygen extraction-related indices, early postoperative cognitive screening, serum neuron-specific enolase and interleukin-6, and safety outcomes. RESULTS: PHC significantly increased rSO2 relative to conventional ventilation (left: adjusted mean difference [aMD] 10.64, 95% CI 8.96-12.33; right: aMD 10.16, 95% CI 8.22-12.11; both P < 0.001), with consistent sensitivity results. Repeated-measures analyses showed persistently higher intraoperative rSO2 in the PHC group. Cerebral oxygen extraction-related indices were generally lower with PHC. However, early postoperative cognitive outcomes and serum biomarkers did not differ between groups. Emergence time was modestly longer with PHC, whereas adverse events were comparable. CONCLUSIONS: PHC-based ventilation favorably modified intraoperative cerebral oxygenation and oxygen-extraction profiles but did not translate into detectable early postoperative cognitive or biomarker benefits in older adults with NFBF.

Humans↗

PubMed2026

Comparative genomic epidemiology of food- and patient-derived diarrheagenic Escherichia coli from sentinel surveillance in Southeast China.

Diarrheagenic Escherichia coli (DEC) remains an important foodborne pathogen, yet long-term comparative genomic surveillance data jointly characterizing food-derived and patient-derived isolates remain limited. This surveillance-based comparative study integrated antimicrobial susceptibility testing and whole-genome sequencing to characterize diarrheagenic Escherichia coli isolates recovered from food and patient sources in Lishui, Southeast China, during 2018-2025, with emphasis on occurrence, resistance profiles, genomic backgrounds, and plasmid replicon-associated features. Antimicrobial susceptibility testing was performed for 258 selected isolates, and whole-genome sequencing was conducted for a curated analytical subset of 204 isolates. The sequenced subset was used for diversity-oriented comparative genomic analysis rather than for unbiased prevalence estimation of the entire DEC collection. EAEC predominated in both sources, although food-associated occurrence was heterogeneous across categories, with the highest recovery rate observed in raw meat. Patient-derived isolates showed a broader overall resistance burden, whereas food-derived isolates retained substantial resistance to tetracycline, chloramphenicol, and florfenicol. Phylogenetic analysis showed partial overlap in genomic backgrounds between food-derived and patient-derived isolates, while representative resistance determinants displayed both broadly distributed and lineage-enriched patterns. Replicon-based plasmid profiling identified 42 plasmid types, including 12 detected in both sources, with IncF-related replicons predominating among these shared profiles. Several food-derived isolates carried multiple plasmid replicon types that were also observed in patient-derived isolates. Overall, food-derived and patient-derived DEC showed partial overlap in genomic backgrounds, resistance determinants, and replicon-defined plasmid profiles within this surveillance setting, while retaining source-associated heterogeneity. These findings should be interpreted as surveillance-based comparative evidence rather than as evidence of direct source attribution or transmission.

Humans↗

PubMed2026

Use of wearable technologies for physical activity promotion in older adults: A systematic review.

This systematic review, conducted according to PRISMA guidelines and registered in PROSPERO (CRD420251055299), examined the use of wearable technologies for promoting physical activity (PA) in adults aged 60 years and older. Searches across five databases (PubMed, Scopus, Web of Science, CINAHL, Cochrane) identified 2438 records, of which only six randomized controlled trials published between 2021 and 2025 met inclusion criteria, with sample sizes ranging from 36 to 551 participants and mean ages between 65 and 79 years. Given the small number of included studies, findings should be interpreted as preliminary. The studies ranged from the standalone use of commercial trackers (Fitbit, Polar, ActiGraph) to multicomponent interventions combining wearables with physiotherapist feedback, telephone counseling, web-based platforms, or interactive cognitive-motor training. Wearables used alone, as in the REACT trial, produced small or non-significant PA effects. In contrast, interventions integrating devices with personalized feedback, professional support, or digital platforms, such as PROMOTE and TASMANIA, were associated with more consistent improvements in PA, physical function, and cognitive outcomes. Multicomponent programs, such as PEER and ICMT, reported broader benefits, including cognition, balance, and reductions in sedentary behavior, though these findings derive from individual trials and require replication. Risk of bias, assessed with the Cochrane Risk of Bias tool version 2 (RoB 2.0), was rated as "some concerns" for five studies and low for only one, mainly due to gaps in randomization reporting, missing data, and lack of preregistration. Tentatively, and based on a very limited evidence base, wearables may have greater impact when embedded within broader behavioral systems, incorporating feedback, coaching, or interactive components, rather than when used in isolation as passive monitoring tools. Adherence and psychosocial outcomes appeared related to comfort and perceived usefulness among older adults, though larger and more robust trials are needed to confirm these patterns.

Humans↗

PubMed2026

Educational interventions to improve medical students' bad news communication skills: A systematic review and meta-analysis.

OBJECTIVES: This systematic review aimed to both determine whether educational interventions improve medical students' ability and/or confidence in Bad News Communication (BNC), as well as assess the relative efficacy of instructional formats. METHODS: Performed according to the PRISMA guidelines, four databases were searched for articles describing education-based interventions to improve medical student's BNC ability and/or confidence, published in English between 2001 and 2024. Data on students' self-reported or observer-assessed level of competence/ability in BNC (primary outcome), and students' self-assessed confidence in BNC skills (secondary outcomes), were analysed. Meta regression explained the influence of several categorical moderators on heterogeneity in relation to intervention effects on competence/ability. RESULTS: 27 studies met the criteria for inclusion in the systematic review and 17 studies for the meta-analysis. Interventions described in controlled studies were associated with a moderate and significant increase in BNC ability (13 data sets; standardized mean difference [SMD] = 1.09, 95% CI = 0.52 - 1.66). Interventions detailed in pre-post design studies were associated with a significant increase in BNC ability (20 data sets; SMD = 0.92, 95% CI = 0.52 - 1.32), and student confidence/comfort in their BNC skills (12 data sets; SMD = 1.16, 95% CI = 0.57 - 1.75). Subgroup analysis demonstrated better skills/competence outcomes in studies that included simulation-based training (SBT). CONCLUSIONS: Educational interventions improve the BNC ability and confidence of medical students. Interventions should include an SBT element as this leads to greater improvements in BNC ability. Further research is needed to determine to what extent these interventions translate to positive patient outcomes. PRACTICE IMPLICATIONS: Diverse educational programme, especially those including simulation-based training, are effective in improving BNC skills, although the longetivity of these improvements is at present unclear. Therefore, we recommend that refresher courses or practice opportunities should be scheduled throughout students' medical education to ensure retention of BNC skills.

Humans↗

PubMed2026

Clinical accuracy and short-term outcomes of intraoral photogrammetry for complete-arch implant rehabilitation: A retrospective multicentre study on 35 patients.

OBJECTIVES: To evaluate the clinical accuracy and short-term outcomes of complete-arch implant-supported fixed dental prostheses (ISFDPs) fabricated using an intraoral photogrammetry (IPG) based digital workflow in completely edentulous patients. METHODS: This multicenter retrospective clinical study included 35 patients rehabilitated with 52 complete-arch ISFDPs (10 FP1, 18 FP2 and 24 FP3 restorations) supported by 221 implants. All definitive prostheses were designed and fabricated using a fully digital workflow initiated by IPG acquisition with the Aoralscan Elite IPG® (SHINING 3D). The primary outcome was clinical accuracy, assessed at definitive prosthesis delivery through evaluation of passive fit using the Sheffield test and radiographic verification. Secondary outcomes included biologic and prosthetic complications, as well as implant and prosthesis survival rates during the follow-up. RESULTS: Passive fit was achieved in all definitive restorations (100%). Radiographic evaluation confirmed accurate marginal adaptation at the implant-prosthesis interface in all cases. No statistically significant differences in clinical accuracy were observed according to treated arch, number of supporting implants, or prosthetic design (P > .05). During a mean follow-up period of 12.1 ± 3.5 months, biologic and prosthetic complications were limited and generally minor. Implant survival was 99.5%, and prosthesis survival was 100%. CONCLUSIONS: Within the limitations of this retrospective clinical study, the IPG based workflow demonstrated high clinical accuracy and predictable short-term outcomes for complete-arch implant rehabilitation, consistently enabling passive fit and favorable prosthetic performance. CLINICAL RELEVANCE: IPG may represent a clinically reliable and predictable approach for complete-arch digital implant impression acquisition. The high rates of passive fit, together with the low incidence of biologic and prosthetic complications observed in this multicenter clinical study, support the use of IPG based workflows for the fabrication of complete-arch ISFDPs.

Humans↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

"It was good because they have a relationship with us": A qualitative study on low-threshold buprenorphine treatment at syringe services programs.

INTRODUCTION: Syringe service programs (SSPs) reach people who inject drugs with opioid use disorder (OUD) and are novel "low-threshold" venues to initiate buprenorphine treatment. The study investigated patients' experiences with SSP-initiated buprenorphine treatment, which could aid in improving buprenorphine treatment delivery at SSPs. METHODS: The study included 12 participants who completed qualitative exit interviews after a randomized controlled trial of buprenorphine treatment at SSPs. In the parent study, participants received buprenorphine treatment through an onsite model at an SSP or enhanced referral to a community health center based on the randomization sequence. Most participants started taking buprenorphine at home. Exit interviews included participants from both study arms, and the semi-structured interview guide focused on their experiences with clinicians, experiences initiating buprenorphine, prior experiences with OUD treatment, and perceptions about continuing buprenorphine treatment. Four researchers iteratively read, coded, and discussed each transcript, then they derived recurring themes using thematic analysis. RESULTS: Participants were mostly male, middle-aged, and 50% identified as Latino. Four main themes related to buprenorphine treatment initiation: 1) Onsite treatment facilitated buprenorphine prescription, but some participants also expressed a need for additional support; 2) Precipitated withdrawal complicated participants' buprenorphine initiation in both arms; 3) Participants largely experienced the SSPs as affirming and welcoming; and 4) Developing strong relationships with healthcare providers was critical to successful buprenorphine treatment initiation. CONCLUSIONS: The SSP-based model provided rapid access to buprenorphine prescriptions, but precipitated withdrawal was a common complication. Some participants desired additional support and guidance when they started taking buprenorphine at home. The findings point to a "low-threshold, high-touch" approach where participants receive expedited access to buprenorphine providers at SSPs but also additional support throughout the initiation process to avoid and/or manage precipitated withdrawal. Despite some challenges, SSP-based buprenorphine treatment was highly valued by study participants.

Humans↗

PubMed2026

Peptide molecular lock-engineered nanobodies enable an oriented dual-modal immunoassay for reliable detection of Cronobacter sakazakii.

Conventional nanobody ELISAs for trace Cronobacter sakazakii in powdered infant formula suffer from random orientation and low signal output. We developed an oriented dual-modal immunoassay that combines site-specific biotinylation via a C-terminal AviTag and a peptide molecular lock, enabling controlled surface orientation while preserving nanobody structural integrity. This strategy was further integrated with phage-displayed nanobodies for multivalent amplification and both fluorescent and colorimetric readouts. The assay exhibited a broad linear range of 103-106 CFU/mL, with limits of detection (LODs) of 6.70 × 102 CFU/mL for fluorescence and 1.55 × 103 CFU/mL for colorimetry, showing improved sensitivity compared with the conventional passive adsorption-based Nb-ELISA evaluated in this study. XGBoost-based multimodal fusion improved quantitative accuracy, and SHAP analysis elucidated modality contributions. In spiked powdered infant formula samples, recoveries ranged from 92.1% to 118% with coefficients of variation below 5.98%, confirming acceptable matrix tolerance and analytical reliability.

Cronobacter sakazakii↗

PubMed2026

Thermal analysis techniques for microplastic mass quantification: Methodological challenges and standardization needs.

Microplastics (MPs, 1 μm-5 mm) and nanoplastics (NPs, <1 μm) are ubiquitous contaminants requiring standardized quantification methods. This systematic review evaluates thermal analysis techniques for mass-based MP detection, including pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS), thermogravimetry-MS (TGA-MS), thermal extraction desorption-GC-MS (TED-GC-MS), and differential scanning calorimetry (DSC). Database searches (Web of Science, from inception to December 1, 2025) following PRISMA guidelines identified studies across seven environmental matrices (water, soil/sediment, atmosphere, biota, human tissues). We identify critical standardization gaps: inconsistent marker ion selection, unvalidated conversion factors for tire and road wear particles (TRWPs), and the absence of certified reference materials for complex matrices. Py-GC-MS demonstrates versatility but suffers from lipid interference in biological samples; TED-GC-MS offers superior sensitivity (sample capacity ∼200× Py-GC-MS) but lacks real-time chromatographic monitoring. To advance data comparability, we propose: (i) harmonized ion selection hierarchies based on specificity-sensitivity balance, (ii) matrix-specific TRWP quantification protocols, and (iii) inter-laboratory validation using environmental reference materials. This review provides a methodological roadmap for standardizing thermal analysis in MP research.

Humans↗

PubMed2026

Experiences of stigma, bias, and communication challenges among pregnant healthcare workers: A systematic review of qualitative evidence.

BACKGROUND: Healthcare work environments are fraught with occupational hazards that can impact pregnant healthcare workers' health as well as patient care. Despite the feminization of healthcare globally, systematic discrimination against pregnant workers persists across diverse healthcare settings and cultural contexts. The intersection of stigma, bias, and communication challenges creates substantial barriers to career advancement and wellbeing. However, no systematic review has synthesized qualitative evidence on how these three constructs interact across healthcare professions and cultural contexts using an integrated theoretical framework. OBJECTIVE: To systematically review and synthesize qualitative evidence on experiences of stigma, bias, and communication challenges among pregnant healthcare workers across different healthcare settings and cultural contexts using an integrated theoretical framework. DESIGN: Systematic review of qualitative studies following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines with thematic synthesis. DATA SOURCES: Seven databases were searched from inception to January 2026. REVIEW METHODS: Included qualitative studies were appraised using the Critical Appraisal Skills Programme (CASP) checklist and synthesized through theory-guided thematic synthesis. Confidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation-Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) approach. RESULTS: Fourteen studies encompassing 1223 participants across 17 countries revealed four major themes: (1) professional identity stigma and workplace discrimination through systematic labeling and stereotyping; (2) gender-based institutional bias rooted in masculine organizational logic; (3) multilevel communication failures creating fear-based climates; and (4) individual and collective resistance strategies developed despite constraints. Occupational hazards specific to pregnancy included exposure to infectious diseases, imaging, physical tasks, cleaning products, patient violence, and medication administration. Support from coworkers and supervisors was identified as the most critical facilitator for avoiding hazards and making necessary modifications, while the desire to be 'supernurses' and fear of consequences emerged as significant barriers. These patterns were consistent across healthcare professions, settings, and cultural contexts, with specialty culture and healthcare system type moderating discrimination intensity. Confidence in core findings was rated high using GRADE-CERQual. CONCLUSIONS: Pregnant healthcare workers globally experience interconnected stigma, bias, and communication challenges that are systematically embedded within healthcare organizational structures. These challenges operate synergistically, requiring comprehensive multilevel interventions beyond policy compliance. Healthcare organizations must implement evidence-based strategies addressing stigma reduction, bias interruption, and communication transformation simultaneously to retain skilled workers and ensure quality patient care.

Female↗

PubMed2026

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques↗