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PubMed2026

Subacute and long-term changes in cognitive functioning after administration of classic psychedelics, MDMA and ketamine: A systematic review of clinical and preclinical evidence.

Psychedelic agents induce a window of heightened neuroplasticity that extends beyond acute intoxication, during which neural circuits are more amenable to change. This period may facilitate changes in cognition relevant to the treatment of psychiatric disorders. This systematic review synthesised clinical and preclinical evidence of subacute and long-term (≥1 day) effects of classic and non-classic psychedelics on cognition. MEDLINE, EMBASE, APA PsycInfo and Web of Science were searched to identify human and animal studies investigating psychedelics and cognition (executive function, attention, decision-making). Sixty-seven (47 clinical, 20 preclinical) articles met inclusion criteria. Psilocybin demonstrated the most consistent evidence of subacute and longer-term cognitive improvement, particularly in cognitive flexibility and attention. Ketamine showed enhancement across cognitive domains, although findings were heterogeneous. LSD and DMT showed no consistent subacute changes, while MDMA was associated with transient cognitive impairments that resolved within days. Risk of bias assessments revealed selective outcome reporting, poor reporting of missing data and inadequate methodological detail, limiting the confidence of findings. Current evidence provides preliminary support for subacute changes in cognition following administration of select psychedelic agents. Cognitive improvements were more frequently seen in psychiatric populations than healthy subjects, which may reflect a remediation of existing cognitive deficit rather than enhancement above normal functioning. Adequately powered, controlled studies with standardised reporting of cognitive outcomes are required to determine the magnitude, durability and clinical relevance of psychedelic-associated cognitive change.

Hallucinogens↗

PubMed2026

Prognostic Value of Frailty in Aortic Surgery: A Systematic Review and Meta-Analysis Comparing Frailty Assessment Tools.

BACKGROUND: Frailty is increasingly recognized as an important determinant of outcomes after aortic vascular surgery, but assessment methods vary substantially and the optimal tool for risk stratification remains uncertain. This systematic review and meta-analysis evaluated the prognostic value of preoperative frailty and compared the predictive performance of different frailty instruments in aortic surgery. METHODS: PubMed, Embase, and Cochrane Library were searched from inception to April 27, 2026. Eligible studies included patients undergoing open, endovascular, or hybrid aortic procedures involving abdominal, thoracic, thoracoabdominal, arch, and proximal aortic diseases, including aneurysms and dissections, assessed frailty preoperatively, and reported postoperative outcomes. RESULTS: Thirty studies comprising 419,459 patients were included. Frailty was associated with higher early mortality (odds ratio [OR] 2.20; 95% confidence interval [CI] 1.54-3.14) and late mortality (hazard ratio 2.18; 95% CI 1.64-2.90). Frail patients also had increased risks of major complications (OR 2.52; 95% CI 1.22-5.19), acute kidney injury (OR 1.64; 95% CI 1.34-2.02), and nonhome discharge (OR 5.50; 95% CI 3.05-9.92). Associations were consistent across surgical approaches and aortic segments. Judgment-based or phenotype-like tools yielded higher effect estimates than deficit-accumulation indices, although differences were not statistically significant; among index-based tools, Modified Frailty Index (mFI)-11 outperformed mFI-5. CONCLUSION: Preoperative frailty strongly predicts mortality, morbidity, and loss of functional independence after open, endovascular, and hybrid aortic surgery across different aortic segments and pathologies, including aneurysmal and dissecting aortic disease. Routine frailty assessment may improve risk stratification and perioperative decision-making.

Humans↗

PubMed2026

Parents' Awareness of Their Adolescents' Sexual Behaviors and Experiences: A Concordance Analysis.

PURPOSE: Adolescence is a developmental period during which sexual exploration is normative. Parental awareness of adolescents' sexual behaviors can be protective during this stage; however, research suggests both parents and adolescents tend to avoid open conversations about these sensitive issues. This study aimed to examine concordance between parent proxy-reports and adolescent self-reports across three domains of adolescents' sexual behaviors and experiences. METHODS: Data were collected from a national sample of 522 parent-adolescent dyads (aged 15-17 years) from the AmeriSpeak panel (data collected May-September 2022). Prevalence-adjusted bias-adjusted kappa (PABAK) statistics were calculated to evaluate agreement. RESULTS: Findings revealed weak-to-moderate concordance regarding adolescents sending and receiving sexual photos (PABAKs = 0.54-0.79), whereas stronger concordance was observed for experiences related to nonconsensual sharing of sexual photos (PABAKs = 0.92-0.94), with high agreement largely driven by low reported prevalence of these experiences. Strong concordance regarding whether adolescents had ever had sex (PABAK = 0.80) was largely driven by both parents and adolescents reporting the adolescent had not had sex. Concordance regarding sexually transmitted infection and pregnancy prevention methods varied, ranging from weak to strong agreement across specific methods (or lack thereof; PABAKs = -0.07-0.79). DISCUSSION: Results highlight significant discrepancies in parents' knowledge about their adolescents' sexual behaviors and experiences. Interventions aimed at enhancing trust and open dialogue between parents and adolescents about sexuality-related topics, as well as ensuring adolescents have a variety of trusted sources to consult for sexual information, can help adolescents make informed sexual health decisions.

Humans↗

PubMed2026

Contemporary surgical decision-making for hallux valgus and hallux rigidus in Switzerland: A national cross-sectional survey using standardized clinical scenarios.

BACKGROUND: Surgical management of hallux valgus and hallux rigidus is influenced by deformity severity, surgeon training, and evolving techniques. Previous surveys in Australia (2012), Switzerland (2015), and Israel (2023) using identical hypothetical cases demonstrated marked regional differences and a recent rise in minimally invasive Chevron-Akin (MICA). Whether these advances have altered contemporary Swiss practice remains unclear. METHODS: An electronic survey replicating the original questionnaire was distributed to members of the Swiss Foot and Ankle Society. Three standardized clinical cases were presented: mild hallux valgus, severe hallux valgus, and hallux valgus et rigidus. Respondents selected nonoperative versus operative management and specified procedures and fixation methods. Demographics, subspecialty training, and surgical volume were recorded. Current results were compared with prior Swiss data to assess temporal change. RESULTS: Eighty surgeons completed the survey (94% foot and ankle specialists). For mild hallux valgus, 87.7% recommended surgery; Scarf osteotomy remained most common (49.4%), followed by Chevron (21.0%) and Minimally Invasive Hallux Valgus correction (14.8%). Minimally Invasive adopters were predominantly mid-career (83% aged 41-50), high-volume surgeons. For severe hallux valgus, 95.1% favoured surgery; MTPJ arthrodesis was preferred (50.6% isolated; 11.1% with Lapidus), while Minimally Invasive Hallux Valgus correction was rarely chosen (2.5%). In hallux valgus et rigidus, 96% selected MTPJ fusion, most commonly plate-and-screw fixation (45.1%). Compared with 2015, fixation strategies evolved, yet procedure selection remained largely unchanged. CONCLUSION: Despite global expansion of minimally invasive bunion surgery, Swiss surgeons continue to favour established open techniques, particularly Scarf osteotomy and fusion-based strategies. Adoption of MIS remains limited and concentrated among high-volume, mid-career specialists, indicating a cautious national diffusion pattern. LEVEL OF EVIDENCE: IV, survey study.

Hallux Valgus↗

PubMed2026

Use of Wearable Sensors in Angelman Syndrome: A Systematic Review.

BACKGROUND: Wearable sensors are a promising method for collecting clinical trial outcome data for people with Angelman syndrome (AS). However, there has yet to be a systematic probe into the ways in which wearable sensors have been successfully used in AS. The current study aims to provide a quantitative summary of wearable sensors used in AS, including contexts of use and psychometric properties, and to present key narrative highlights. METHOD: Literature searches were performed in three electronic databases: APA PsycInfo, PubMed and Web of Science Core Collection. Data items were categorized into four categories: sample characteristics, study methodological details, wearable sensor characteristics and psychometric properties assessed. Sample characteristics included sample size, age, biological sex, race/ethnicity and cognitive/developmental functioning. Study methodological details were subdivided into study design and setting. Wearable sensor characteristics included sensor type, placement site, means of attachment, assessed construct and sensor-related data loss. Psychometric properties assessed included reliability and validity of sensor-derived data. RESULTS: We identified 16 articles through our systematic review. Wearable sensors were used to study sleep (n = 10, 62.5%), language (n = 2, 12.5%), gait (n = 2, 12.5%), caregiver proximity (n = 1, 6.3%), EEG power (n = 1, 6.3%), and arousal (n = 1, 6.3%) in AS through actigraphs, vocalization recorders, inertial sensors, radio-frequency identification watches, wireless EEG caps, and functional near-infrared spectroscopy caps, respectively. Findings from these studies broadly indicate that wearable sensors are feasible, reliable and valid for assessing a range of behaviours relevant to AS. CONCLUSIONS: Wearable sensors are a promising solution to enhance assessments in AS. However, with the small extant literature characterized by small sample sizes and restricted focus on a few relevant features in AS, there remains ample opportunities to explore the use of wearable sensors in people with AS. Additional studies will better inform clinical decision-making and ultimately improve the lives of people with AS and their families.

Humans↗

PubMed2026

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74·1 months (IQR 68·3-75·4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0·84 [95% CI 0·79-0·88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11·6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0·41-0·93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0·36-0·48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (≥70·0%; mean absolute improvement 12·1 percentage points [SD 2·8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0·010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

Humans↗

PubMed2026

Perspectives of participating neurologists and study nurses - Mixed-methods process evaluation of a web-based program for relapse management in multiple sclerosis (POWER@M2).

BACKGROUND: Relapsing-remitting multiple sclerosis is a chronic inflammatory disease of the central nervous system and the leading cause of disability in young adults. In Germany, 90% of relapses are treated with high-dose intravenous glucocorticoids, despite limited evidence for long-term benefit and international preference for oral administration. Time constraints often hinder informed decision-making. The multicentre Randomized Controlled Trial (RCT) POWER@MS2 (N = 160, 2020-2023), conducted at 18 German MS-centres, aimed to promote self-determined relapse management through a complex intervention (dialogue-based decision aid, nurse-led webinar, online-chat). OBJECTIVE: While RCTs demonstrate effectiveness, process evaluations are essential to understand implementation, mechanisms of impact and contextual factors. This study explored healthcare professionals' experiences and attitudes toward implementing relapse self-management and self-medication in clinical practice. METHODS: A mixed-methods process evaluation followed the UK Medical Research Council- framework. Quantitative data were collected via validated questionnaires at up to three time points and analysed descriptively. Interview guides were developed based on these results. Qualitative data from neurologist and study nurse interviews were thematically analysed. Results were triangulated using a joint display. RESULTS: Data were collected from 55 neurologists and 17 study nurses (quantitative) and from 7 neurologists and 4 nurses (qualitative) (2020-2024). Most neurologists opposed routine steroid use, reserving it for severe relapses. Some voiced concerns about self-management, but informed patients were generally viewed as capable of safe self-medication. Study nurses gave mixed feedback on the intervention, citing overload and improved guidance. CONCLUSION: Clinicians showed openness toward implementing the intervention. Enhancing accessibility and addressing specific concerns may support broader adoption.

Humans↗

PubMed2026

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

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

artificial intelligence↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

Comparative Efficacy of Different AI Systems for Polyp Detection by Size During Colonoscopy: Systematic Review and Network Meta-Analysis.

BACKGROUND: Colorectal cancer remains a leading cause of death despite being largely preventable through polypectomy. AI systems designed to enhance polyp detection during colonoscopy have shown promise, but the extent to which they improve detection of different-sized polyps remains unclear. OBJECTIVE: This study compared the size-stratified efficacy of AI-assisted colonoscopy vs standard colonoscopy using the Hartung-Knapp-Sidik-Jonkman (HKSJ) method, and generated exploratory rankings while acknowledging all cross-platform comparisons are indirect. METHODS: This systematic review and network meta-analysis (NMA) searched PubMed, Embase, Cochrane CENTRAL, and Web of Science from inception to July 25, 2026, supplemented by citation searching. We included randomized controlled trials (RCTs) comparing AI-assisted vs standard colonoscopy in adults (≥18 years of age), reporting mean polyp detection counts stratified by size (≤5 mm, 6-9 mm, and ≥10 mm). Two reviewers screened studies, extracted data, and assessed risk of bias using the Cochrane Risk of Bias 2.0. We conducted frequentist NMA using the HKSJ method with restricted maximum likelihood estimation, calculated 95% prediction intervals (PIs), and assessed heterogeneity using I2 and τ2. Certainty of evidence was rated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework. RESULTS: A total of 13 RCTs (4156 participants) compared 8 AI systems to standard colonoscopy, forming a network without direct AI comparisons. For diminutive polyps (≤5 mm), AI showed a modest advantage (standardized mean difference [SMD] 0.21, 95% CI 0.07 to 0.35, 95% PI -1.12 to 1.54), but substantial heterogeneity (I2=86.6%) and wide PI crossing the null indicated high uncertainty. EndoScreener showed the most consistent evidence (SMD 0.36, 95% CI 0.18-0.54). For small and large polyps, effects were minimal (SMD 0.02, 95% CI -0.02 to 0.06, 95% PI -0.03 to 0.07; SMD 0.01, 95% CI 0.00-0.02, 95% PI -0.01 to 0.03). GRADE certainty was very low for diminutive polyps and low for small and large polyps. Sensitivity analysis excluding Tianjin YuJin did not materially change findings. CONCLUSIONS: AI may modestly enhance diminutive polyp detection, but effects on small and large polyps are minimal, with no platform superiority. Given very low to low certainty, findings are hypothesis-generating. This exploratory NMA provides size-stratified comparisons that can inform future head-to-head trial design. Unlike prior reviews aggregating all polyp sizes, we show the overall AI benefit is driven by diminutive polyp detection, providing a framework for targeted deployment-prioritizing AI for diminutive polyp screening, with limited value for larger lesions. Head-to-head trials are urgently needed. TRIAL REGISTRATION: PROSPERO International Prospective Register of Systematic Reviews CRD420251266932; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251266932.

Colonoscopy↗

PubMed2026

An exploratory analysis of decision-making in population affinity estimation among forensic anthropology practitioners in the United States.

Population affinity estimation in forensic anthropology often involves the integration of multiple pieces of information, including visual (nonmetric) and metric data. This study examines how practitioners interpret and synthesize visual and metric information and their decision-making processes. A Qualtrics survey was developed using two cases: Case 1 presented clear nonmetric signal but ambiguous metric signal, while Case 2 showed more ambiguous nonmetric signal but clear metric signal. Practitioners were asked to estimate population affinity based on visual assessment, Fordisc data, and provide a final, integrated assessment. A total of 22 valid survey responses were received, with the majority of survey respondents reporting more than 10 years of forensic anthropology experience and holding a PhD degree. Results showed that there is substantial variability in Fordisc use and interpretation. Across both cases, participants synthesized conflicting visual and metric information, converged toward the stronger signal, and came to more consistent final estimates relative to the more ambiguous input. These findings highlight variability in practitioner decision-making but suggest that integration of nonmetric and metric information in population affinity estimation can moderate decision-making uncertainty. The results have implications for forensic anthropology education, training, and proficiency testing.

Humans↗

PubMed2026

Applications of metal-organic frameworks in smart packaging for food freshness indication: a comprehensive review.

Smart packaging is extensively studied for its multifunctional capabilities in antimicrobial activity, preservation, and atmosphere modification. Recently emerged metal-organic frameworks (MOFs) freshness-indicating packaging becomes a key research direction in smart packaging owing to its distinctive functions and physicochemical properties. As multifunctional materials, the unique porous structure and tunable properties of MOFs provide a distinctive approach for developing food packaging applications dedicated to food freshness indication. Existing MOFs-based smart packaging still faces potential safety risks and technical challenges in practical applications, and there remains a lack of integrated discussion that combines synthesis strategies, packaging design, optimization, and safety assessment. This review elaborates on the application of MOFs in freshness-indicating smart packaging, focusing on diverse MOFs synthesis strategies, the formats of smart packaging, types of indicator signals, and qualitative/quantitative analytical methods. It also delves into the methodology concepts of MOFs-based smart packaging and evaluates MOFs safety in food packaging by addressing potential risks. Studies show that MOFs-based smart packaging achieves qualitative and semi-quantitative analysis of food freshness through multiple signal modalities such as visible color change, fluorescence, and photothermal effects. This review emphasizes that safe MOFs design is critically important and should comply with the overall migration limit of <10 mg/dm2 specified in Regulation (EC) No 1935/2004, lanthanide element limit of <0.05 mg/kg, and FDA threshold of 1.5 μg/person/day. Comprehensive safety assessment and intelligent sensing platforms will constitute pivotal directions for advancing MOFs-based smart packaging toward practical application.

Food Packaging↗

PubMed2026

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000 cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT > 2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared↗

PubMed2026

Longitudinal functional trajectory and surgical outcomes after intracranial meningioma resection: implications for surgical decision-making in older patients.

OBJECTIVE: As the population ages, meningiomas are increasingly encountered in older patients, yet longitudinal functional outcomes following surgery across age groups remain incompletely characterized. This study evaluated age-related differences in clinical and tumor characteristics, functional trajectory, and surgical outcomes. METHODS: This was a retrospective cohort study of 396 consecutive patients who underwent surgery for intracranial meningiomas at a single academic center between January 2023 and September 2025. Patients were stratified into 5 age groups (< 65, 65-69, 70-74, 75-79, and ≥ 80 years). Neurological deficits and Karnofsky Performance Status (KPS) were assessed preoperatively, at discharge, and at last follow-up. Logistic regression analyses identified predictors of prolonged length of stay (LOS) (> 5 days) and poor functional outcome at discharge (KPS < 80). RESULTS: Older patients presented with greater comorbidity burden, larger tumors, and lower preoperative KPS (all p < 0.05), while gross-total resection was achieved at comparable rates across all age groups (p = 0.504). A clinically meaningful inflection point was observed around age 75 years, with KPS < 80 at discharge rising from 7.4% and 9.7% in the < 65-year and 70- to 74-year subgroups and to 36.2% and 57.1% in the 75- to 79-year and ≥ 80-year subgroups (p < 0.001), and median LOS increased from 4 days in the younger groups to 9 and 7 days in the 75- to 79-year and ≥ 80-year groups (p < 0.001). However, recovery rates among patients who experienced functional decline at discharge were comparable across age strata. On multivariable analysis, independent predictors of prolonged LOS were age ≥ 75 years (OR 2.31, p = 0.019), diabetes mellitus (OR 2.85, p = 0.004), posterior fossa location (OR 2.1, p = 0.008), tumor diameter (OR 1.33, p < 0.001), postoperative edema (OR 2.58, p = 0.015), and neurosurgical complications (OR 3.18, p = 0.002). Independent predictors of poor functional outcome at discharge were age ≥ 75 years (OR 5.84, p < 0.001), lower preoperative KPS (OR 2.8, p < 0.001), posterior fossa location (OR 3.72, p = 0.003), neurosurgical complications (OR 3.56, p = 0.008), and recurrent meningioma (OR 2.89, p = 0.025). Among 70 endoscopic endonasal approach patients, higher preoperative deficit burden and subtotal resection rates were observed compared to open craniotomy, though overall functional outcomes were comparable. CONCLUSIONS: Surgical risk in meningioma resection increases from age 75 years onwards, yet recovery capacity following initial functional decline remains similar across all age groups. Preoperative functional status, tumor location, comorbidity burden, and recurrence history should guide surgical decision-making rather than age alone.

Humans↗

PubMed2026

The role of simulator immersion on learning and transfer of decision-making skill in sport.

Virtual reality has become popular in sport and other domains because it can immerse the user within a sporting context and solve logistical problems for additional off-field training. There is limited evidence, however, of whether immersion is crucial for learning and transfer. This study compared training of decision-making skill between 360-degree video virtual reality (360VR) and two-dimensional video. Twenty-eight Australian Rules Football players were randomly assigned to one of three training groups: 360VR, two-dimensional video, and control. Across four weeks, participants in the training groups were exposed to decision-making scenarios consisting of visual, contextual and auditory cues. Performance was assessed pre- and post-training with virtual reality and field-based decision-making tests. Results indicated that the two-dimensional video training group showed significantly superior decision-making in the field-based transfer test compared to 360VR and control groups post intervention. There was also indication that two-dimensional video training was superior to the control post intervention in the virtual reality test. Findings indicate that immersion created in virtual reality is not an underpinning mechanism for learning and transfer, rather the use of perceptual information is crucial. 360VR may facilitate uptake through engagement, but two-dimensional video is adequate for learning and transfer of decision-making to the field.

Humans↗

PubMed2026

Assessment of atypical glandular cell interpretation in Pap tests using the Hologic Genius Digital Diagnostics System.

Atypical glandular cells (AGC) are a diagnostic challenge. The aim of this study was to evaluate the efficacy and diagnostic performance of AGC detection on the Hologic Genius Digital Diagnostics System (HGDDS). A retrospective analysis of 451 ThinPrep Pap cases was conducted, including 207 cases of AGC, 27 cases of high-grade squamous intraepithelial lesion (HSIL), 25 cases of low-grade squamous intraepithelial lesion (LSIL), and 192 benign cases. All AGC cases had follow-up histologic diagnoses, with 66 cases subsequently diagnosed as adenocarcinoma. The slides were randomized, scanned, and analyzed by the HGDDS. Patient age and HPV test results were provided to reviewers, an experienced cytologist, who screened the cases, followed by two cytopathologists who independently examined the cases on the HGDDS. Diagnostic concordance between the two cytopathologists indicated strong agreement (κ = 0.829). Sensitivity of AGC on Papanicolaou (Pap) tests for adenocarcinoma detection on HGDDS was 98.5% and 95.5%, respectively, comparable to the original ThinPrep interpretation (OTPI). Specificity for adenocarcinoma detection was significantly higher (84.6% and 85.6%) with the HGDDS than 27.7% with OTPI. Overall, the diagnostic performance for AGC/HSIL interpretation to detect CIN2/3/adenocarcinoma appeared to have improved with HGDDS compared with OTPI, particularly for specificity and positive predictive value (PPV). This is the first study evaluating AGC diagnosis using the HGDDS. The findings demonstrate that the sensitivity of adenocarcinoma detection as AGC on HGDDS is comparable to the ThinPrep Imaging System, but the specificity and PPV are improved. This suggests the potential of artificial intelligence to augment the performance of cervical cancer screening.

Humans↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

PubMed2026

Ictal electroencephalography and heart rate as treatment criteria in electroconvulsive therapy: a systematic review of the literature.

BACKGROUND: Decades before the emergence of precision medicine, psychiatrists raised the question of whether specific seizure characteristics could help optimize electroconvulsive therapy (ECT), as relationships between some of these characteristics and better outcomes were found. From 1990 onward, researchers focused on electroencephalography (EEG) and cardiovascular markers, which were broadly adopted by guidelines worldwide. However, the prognostic value of these markers is still controversial. Here, we provide a systematic summary of the studies on this topic. METHODS: We conducted a literature review on the use of ictal EEG and heart rate as outcome predictors in ECT using the PubMed, EMBASE, Cochrane and PsycINFO databases. RESULTS: Thirty-seven studies addressing more than 100 quality markers fulfilled our inclusion criteria. Single EEG markers were assigned to five categories (postictal inhibition, amplitude, coherence, regularity, and seizure duration). Heart rate and composite markers were considered separately. In contrast to single EEG markers, heart rate and composite markers could be consistently linked to better outcomes in patients with depression. Only a few studies on schizophrenia could be retrieved. CONCLUSION: Multiparametric markers outperformed single markers. Furthermore, changes in heart rate during seizures were related to better outcomes. Although clinical assessment remains the cornerstone of treatment guidance decisions, EEG and cardiac monitoring could help prevent insufficient seizures during the period preceding clinical improvement. Evidence on schizophrenia remains limited. More randomized trials are needed to analyze the role of composite markers as prognostic tools.

Humans↗