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PubMed2026

Effects of carbohydrate mouth rinse on psychophysiological responses, kinematic variables and technical actions during small-sided soccer games.

BACKGROUND: This study investigated the effects of carbohydrate mouth rinsing (CHOMR) on various psychophysiological, kinematic, and technical actions during 4-a-side small-sided soccer games (SSGs). METHODS: In a randomized, crossover, double-blind design, 16 young male soccer players (age: 15 ± 1 years; height: 172.6 ± 7.0 cm; body mass: 57.8 ± 7.9 kg) participated in two 4-a-side SSGs separated by one week following either CHOMR or placebo (PLA). During each SSGs, heart rate (HRmean, %HR, and HRmax), rating of perceived exertion (RPE), enjoyment, visual analogue scale (VAS) to perceived mental fatigue, mood states, total distance (TD), high-speed running distance (HSRD), average metabolic power (AMP), high metabolic load distance (HMLD), sprint distance (SD), acceleration (ACC), deceleration (DEC), and technical actions (e.g. passing, tackling, shooting, and interceptions) were assessed. RESULTS: Compared with PLA, CHOMR resulted in significantly higher RPE (p = 0.025, g = 0.86) and significantly lower VAS scores (p = 0.010, g = -0.71). In addition, the CHOMR condition showed significantly higher values for interceptions, successful tackles, unsuccessful tackles, unsuccessful shots, and goals (p < 0.05, g = 0.96-2.02), whereas block values were significantly higher in the PLA condition. There were no statistically significant differences in HRmean, %HR, HRmax, enjoyment, TD, HSRD, AMP, HMLD, SD, ACC, DEC, successful passes, unsuccessful passes, successful shots, or mood states between the conditions (p > 0.05). CONCLUSION: The current study findings suggest that CHOMR may enhance selected technical actions and lower VAS scores during 4-a-side SSGs, although it was also associated with higher RPE and did not alter the kinematic responses. In conclusion, CHOMR was associated with higher RPE, lower mental fatigue, and selective improvements in technical actions, with no significant effects on kinematic variables or HR.

Humans↗

PubMed2026

Functional neuroimaging subtypes of obsessive-compulsive disorder: A systematic review and meta-analysis.

Obsessive-compulsive disorder (OCD) exhibits substantial clinical heterogeneity that may reflect underlying neurobiological diversity. Neuroimaging-based subtyping may advance precision psychiatry by identifying biologically distinct subgroups with differential treatment responses. This study systematically synthesized evidence from functional neuroimaging subtyping studies in OCD to identify reproducible neurobiological subtypes, characterize their clinical profiles, and establish a consensus-based classification framework. We reviewed 40 original studies employing machine learning, clustering, normative modeling, or classification approaches, encompassing approximately 8,150 patients. Consensus clustering identified three reproducible neurobiological subtypes. The Limbic-Hyperactive subtype, comprising approximately 40% of patients, exhibited amygdala and insula hyperconnectivity, elevated anxiety levels, predominant contamination and washing symptoms, and favorable response to cognitive-behavioral therapy. The Fronto-Striatal-Hypoconnected subtype, comprising approximately 35% of patients, demonstrated reduced orbitofrontal-striatal connectivity, cognitive inflexibility, predominant checking and ordering symptoms, and a favorable response to selective serotonin reuptake inhibitors. The Global-Disrupted subtype, comprising approximately 25% of patients, exhibited widespread connectivity disruption, greater symptom severity, and poor treatment response. Support vector machine classification achieved 81.5% accuracy for subtype assignment, though classification of OCD versus healthy controls showed limited generalizability in multisite settings (AUC 0.567-0.673). These findings support a neuroimaging-based framework for personalized treatment selection but require prospective validation.

Humans↗

PubMed2026

Efficacy and safety of ferric citrate tablets in Chinese patients with hyperphosphatemia undergoing maintenance hemodialysis: a multicenter, randomized, open-label, active-controlled, phase III trial.

BACKGROUND: This study aimed to evaluate the efficacy and safety of ferric citrate tablets in Chinese patients with hyperphosphatemia undergoing maintenance hemodialysis (MHD). METHODS: In this phase III, multicenter, randomized, open-label, non-inferiority trial, patients with hyperphosphatemia on maintenance hemodialysis were randomly assigned to receive either ferric citrate or sevelamer carbonate tablets for 12 weeks. The primary endpoint was the change in serum phosphorus levels from baseline to week 12, with a non-inferiority margin of 0.32 mmol/L. Secondary endpoints included changes in serum calcium, intact parathyroid hormone, and safety assessments. RESULTS: A total of 239 patients were randomized to the ferric citrate group (n = 119) or the sevelamer carbonate group (n = 120). The mean change in serum phosphorus levels was -0.70 ± 0.50 mmol/L in the ferric citrate group and -0.61 ± 0.59 mmol/L in the sevelamer carbonate group (least squares mean difference, -0.09 mmol/L; 95% CI, -0.24 to 0.05 mmol/L; non-inferiority margin, 0.32 mmol/L). No significant inter-group differences were found in the percentage of patients achieving target phosphorus levels (49.09% vs. 48.28%, p = 0.902). Ferric citrate significantly improved iron-related parameters and hemoglobin levels. Most treatment-emergent adverse events were mild, with gastrointestinal disorders being the most common. CONCLUSIONS: Ferric citrate tablets were non-inferior to sevelamer carbonate in reducing serum phosphorus levels in hyperphosphatemia patients on maintenance hemodialysis, with the added benefit of improving iron-related anemia and a favorable safety profile.

Adult↗

PubMed2026

Gut microbiota and metabolic alterations in participants with flatulence identify Faecalibacterium prausnitzii as a key microbial target for clinical intervention.

Flatulence is closely associated with gut dysbiosis, yet the characteristic microbial signatures, metabolic alterations, and actionable intervention targets remain unclear. This limited mechanistic understanding has hindered the development of precise microbiota-based strategies for managing flatulence. Here, we found that participants with flatulence exhibited marked shifts in gut microbial functions and fecal metabolic profiles compared with healthy controls, characterized by enhanced abnormal fermentation, enrichment of oxidative stress-related functions, elevated low-grade inflammatory signatures, and reduced anti-inflammatory and mucosal-protective metabolic features. Faecalibacterium prausnitzii was significantly negatively associated with the high-gas-producing phenotype. In vitro replenishment experiments further validated the role of F. prausnitzii in reducing gas production, promoting butyrate generation, and remodeling butyrate-associated microbial communities. Based on microbial interaction analysis, we identified Bifidobacterium longum CCFM1319 as a candidate strain for targeting F. prausnitzii. In a double-blind, randomized, placebo-controlled clinical trial, supplementation with B. longum CCFM1319 significantly increased intestinal F. prausnitzii abundance and improved flatulence-related symptoms. Collectively, these findings reveal the microbiota and metabolic dysbiosis underlying flatulence, highlight the key regulatory role of F. prausnitzii, and lays the foundation for targeted microbiota-based intervention strategies for flatulence.

Humans↗

PubMed2026

Comparative profiling of microbial community structure, enzyme potential, metabolic features, and volatile composition in craft and Jiafan Huangjiu processes.

Craft Huangjiu and Jiafan Huangjiu represent two distinct industrial Huangjiu product outcomes with contrasting volatile profiles. This study compared craft Huangjiu (L70) and Jiafan Huangjiu (L79) to characterize their physicochemical, microbial, gene-level functional, metabolic, and volatile features. Because L70 involved mid-fermentation addition of finished Huangjiu, this comparison was not intended to isolate the sole effect of fermentation interruption versus continued fermentation. L79 showed more extensive carbon and nitrogen utilization, with lower residual substrates and higher ethanol and acetic acid contents than L70, whereas L70 retained a less complete fermentation state. At the volatile level, GC-MS and volatile metabolomics consistently showed an ester-enriched profile in L79 and a more alcohol-dominant profile in L70. FlavorDB-based putative annotation and threshold-based OAV analysis further indicated distinct database-assigned descriptor distributions and potential odor-active compounds, with more OAV > 1 ester-related compounds in L79. Metagenomic analysis showed that L70 was dominated by Lactobacillus acetotolerans, whereas L79 contained higher relative abundances of Saccharomyces cerevisiae, Aspergillus oryzae, Aspergillus flavus, and Fructilactobacillus fructivorans. Metagenomic functional annotation showed higher representation of hydrolysis-related CAZy genes and ester-related enzyme annotations in L79. KEGG-based pathway mapping further indicated greater gene-level potential for ethanol-, acetate-, and acetyl-CoA-related metabolism in L79. Accordingly, the L70 profile should be interpreted as the integrated final-product outcome of process intervention, exogenous input, and subsequent fermentation. The findings provide a comparative basis for future flavor regulation and process optimization in Huangjiu and other fermented alcoholic beverages.

Volatile Organic Compounds↗

PubMed2026

Implementing a novel digital health platform for self-management of postmenopausal osteoporosis: A qualitative study of user experiences, perspectives and implementation outcomes.

BACKGROUND: Osteoporosis self-management requires scalable support, and digital health platforms may meet this need. This study aimed to characterise the experiences and perspectives of postmenopausal women who participated in a 12-month randomised controlled trial (RCT) of a digital voice assistant (DVA) delivered osteoporosis self-management intervention, and to assess key implementation outcomes. METHODS: This was a qualitative analysis of interviews with postmenopausal women from the intervention arm (DVA group) of the RCT. The DVA program broadcast education videos, medication reminders, home-based exercise, nutrition advice and monthly quizzes through a DVA device. Semi-structured interviews were recorded, transcribed and managed in NVivo through reflexive thematic analysis, guided by the Practical Planning for Implementation and Scale-Up and Proctor's implementation outcome taxonomy frameworks. Evidence weighting summarised participant coverage and code density. RESULTS: Twenty-two of 25 (88%) DVA group participants completed semi-structured interviews. Thematic analysis identified seven themes mapped to Proctor's implementation outcomes. Evidence weighting indicated strong support for the intervention's appropriateness and acceptability, moderate support for its adoption, fidelity, feasibility and sustainability, and limited support for costs. Participants valued clear audiovisual guidance, conversation-based interactions with natural language, and flexible home-based access to self-management. CONCLUSION: Digital health platforms for osteoporosis self-management appear feasible, acceptable and sustainable among postmenopausal women. Findings indicate that these platforms are approaching readiness for evaluation in implementation-focused settings, contingent on streamlined content, reliable delivery modalities, accessible user support, clear privacy regulations and pragmatic pricing models.

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

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

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

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↗