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Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (&#x394;AUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans

Pilot Distractions and Interruptions in Airlines: Ranking of Sources by Analytic Hierarchy Process.

ObjectiveThis work establishes a methodological framework for sources of pilot distraction and interruptions in a structured model that can be used as a tool for cockpit design/procedure assessment.BackgroundPilots must complete complex tasks, and distractions can impair performance and lead to errors that can cause aircraft accidents. Although various cockpit distractors are examined individually, there is no integrated approach.MethodDistraction and interruption sources were identified through a literature review and confirmed/extended by interviews with airline pilots. Associated weights were determined through pairwise comparisons, yielding a hierarchical model using the Analytic Hierarchy Process.Results26 sources of pilot distraction and interruptions were quantified and categorized into four categories: communication, head-down time, responding to abnormal conditions & unexpected situations, and searching for traffic.ConclusionA taxonomic structure for assessment is achieved with the top 5 sources identified as communications, technical interruptions, experience in type, environmental factors, operational irregularities, and airspace high terrain, accounting for 63.07%.ApplicationThe structured system is a flexible assessment scale that provides a taxonomic framework for airline risk management, supports future research, and cockpit design efforts.

Humans

Impact of Contact Lens Use on Clinical Profile and Outcomes of Fungal Keratitis: An 8-Year Retrospective Study.

PURPOSE: To compare clinical characteristics, microbiological profiles, treatment strategies, and outcomes between contact lens-associated (CL) and noncontact lens-associated (non-CL) fungal keratitis. DESIGN: Retrospective, comparative clinical cohort study. METHODS: A review of culture-proven fungal keratitis treated at a tertiary referral center between 2018 and 2025 was conducted. Cases were categorized as CL or non-CL-associated. Demographic, clinical, microbiological, treatment, and outcome data were analyzed and compared between groups. RESULTS: Thirty-seven eyes were included, comprising 16 CL and 21 non-CL cases. CL users presented earlier than non-CL patients (median 7 vs 14 days, P = .007) and had fewer associated ocular risk factors (31% vs 81%, P = .001). Baseline visual acuity and infiltrate size did not differ significantly between groups. Candida species were isolated in 21% cases, Fusarium in 16% and Aspergillus in 8%. Fusarium (19% vs 13%) and Candida (24% vs 19%) infections were slightly more frequent in non-CL cases. Overall, filamentous fungi were the predominant organism group. Topical voriconazole was the most frequently used antifungal agent (78%). All CL-associated cases resolved with medical therapy alone, with a median time to resolution of 38 days (IQR 22-58). In contrast, 76% of non-CL cases resolved medically (median 42 days, IQR 32-76), while 23% required therapeutic keratoplasty (P = .04). Final visual acuity was comparable between groups (logMAR 0.2 vs 0.5, P = .56). CONCLUSION: Contact lens-associated fungal keratitis is characterized by earlier presentation and fewer underlying ocular comorbidities, with favorable outcomes achieved through medical therapy alone. Despite similar microbiological profiles and treatment approaches, noncontact lens-associated fungal keratitis more frequently follows a complicated course requiring surgical intervention.

Humans

The Factors That Contribute to Dysfunctional Behavior in Active Military Personnel: An Umbrella Review.

Dysfunctional behavior in active military personnel is a complex and challenging issue for military forces worldwide. Effective management of this issue requires a comprehensive understanding of the factors that contribute to dysfunctional behavior in military populations. The current study presents an umbrella review that synthesized and analyzed the existing literature on contributory factors to dysfunctional behavior in active military personnel using a systems thinking-based framework. Eleven systematic reviews were identified as eligible for inclusion in the umbrella review. The synthesis identified 14 contributory factors to the following types of dysfunctional behavior: suicidal behavior, substance misuse, domestic violence perpetration, and destructive leadership. The analysis indicated that existing literature focuses on contributory factors relating to the military personnel themselves and not influences in the broader military system or wider society. Additionally, few studies have sought to understand how factors interact to create dysfunctional behavior. Future research would benefit from the use of systems thinking-based frameworks and methods to investigate the factors, across the broader military system and society, that contribute to dysfunctional behavior in active military personnel.

Humans

Systematic Review of Symptoms of Catatonia in Autism Spectrum Disorder.

Catatonia is a complex neuropsychiatric syndrome characterized by disturbances in mood, motor function, behavior and speech. It is increasingly recognized in individuals with autism spectrum disorder (ASD), although its identification remains challenging due to the overlapping clinical features of the two conditions. Shared characteristics, such as echophenomena, mannerisms, social indifference and repetitive behaviors can obscure accurate diagnosis. Although reports suggest a significant prevalence of catatonia among individuals with ASD, the condition remains poorly understood and frequently under recognized, leading to substantial diagnostic and treatment challenges. A systematic review was conducted to characterize the symptoms of catatonia in individuals with ASD. The literature search included peer-reviewed journal articles published in English from 1980 onward, focusing on studies examining co-occurring catatonia and ASD. A qualitative framework analysis was implemented to evaluate 45 peer-reviewed studies, with findings interpreted in relation to, and extending beyond, the diagnostic criteria for catatonia outlined in the International Classification of Diseases, 11th revision (ICD-11). The objective was to identify symptom patterns extending beyond current diagnostic frameworks and to support improved clinical recognition and diagnostic precision in ASD populations. The review identified six primary symptom clusters associated with catatonia in individuals with ASD: (1) psychomotor activity, (2) speech disturbances, (3) changes in behavior/skills/functions, (4) mental health symptoms, (5) physiological symptoms, and (6) symptoms related to arousal and awareness. Notably, several symptoms observed within these clusters are not currently included in the ICD-11 diagnostic criteria for catatonia. These additional symptoms include tics, motor compliance, incoherent speech, self-injury, impaired cognition, and appetite changes, suggesting a broader clinical presentation of catatonia in ASD populations than is presently captured in existing diagnostic frameworks. The findings of this review highlight the significance of enhancing clinicians' awareness and understanding of how catatonia manifests in individuals with ASD. Most notably, six symptom clusters, psychomotor changes, speech disturbances, behavioral and functional regression, affective and psychiatric symptoms, physiological symptoms, and arousal/awareness disturbances, were observed. Several symptoms identified in this review are not included in the current diagnostic criteria, and their recognition may facilitate in earlier identification and timely intervention, potentially preventing the severe consequences of untreated catatonia in this population.

Humans

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence

An overview of the use of proteomics and peptidomics to characterize alternative protein foods.

The global protein transition is accelerating the development of alternative protein foods, mainly derived from plants, insects, algae, fungi, and cellular agriculture. Ensuring the authenticity, safety, and nutritional adequacy of these emerging protein matrices requires molecular-level characterization beyond traditional compositional analyses. Proteomics and peptidomics have emerged as transformative analytical platforms capable of decoding the molecular signatures that define protein origin, structural integrity, digestibility, functionality, and health potential. The review comprehensively examines the application of proteomics, and peptidomics for profiling alternative protein foods. Further, the source authentication strategies based on species-specific protein and peptide biomarkers, detection of adulteration in complex matrices, and allergenicity assessment is discussed. Special attention is also given to nutritional proteomics with protein digestibility, gastrointestinal peptide release, and identification of bioactive sequences. SIGNIFICANCE: The importance of this review is that proteomics and peptidomics are becoming central in the management of the fast-growing environment of alternative protein foods, such as plant-based, insect, algal, fungal, and cultured meat products. It provides an explanation of the application of mass spectrometry-based processes to decode molecular signatures defining the origin of proteins, their structural integrity, digestibility, allergenicity, and bioactive properties, and thus directly contribute to safety, nutritional analysis, and authenticity of the product. Presentation of the article includes the integration of the knowledge of traditional muscle foods with alternative systems of proteins, where validated protein and peptide biomarkers are used in authentication, fraud detection, and allergy risk assessment in a wide variety of matrices. It also indicates the role of nutritional proteomics and peptidomics in informing the formulation strategy to promote digestibility and release of health-promoting peptides. In general, this review will guide scientists, the food industry, and regulatory bodies to use modern proteomic technologies in quality assurance, and decision-making, for the advancementof sustainable protein-based foods.

Proteomics

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

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

Journal Article

Complementary feeding patterns in preterm and term infants.

Complementary feeding is essential for infants' nutritional status and development, marking the transition to solid foods when breast milk or formula alone is insufficient. Despite its importance, clear recommendations on which foods to introduce when initiating complementary feeding in preterm infants are lacking. By using data from our previously published randomized controlled trial on the timing of complementary feeding in preterm infants, the current study explores the complementary feeding patterns of preterm infants and compares them with those of term-born infants, providing insights into parental decision-making and potential long-term health impacts. Complementary feeding practices differed significantly between preterm (n&#x202f;=&#x202f;255) and term (n&#x202f;=&#x202f;159) infants, with preterm infants more often receiving vegetables as their first solid food (85.4% versus 68.8%, difference 17.6% with 95% CI 12-35%). The group with early introduction of vegetables had a lower BMI-for-age z-scores (&#x3b2; -0.28 [95% CI -0.55 - 0.02]) and weight-for-height z-scores (&#x3b2; -0.27 [95% CI -0.53 to -0.01]) at two years of age. Additionally, preterm infants showed a greater variety in the numbers of different fruits and vegetables consumed by six months (corrected) age than term-born counterparts (8.29 (SD 3.65) versus 6.26 (SD 3.47), p&#x202f;<&#x202f;0.001). These results indicate that complementary feeding patterns in preterm infants differ from term-born infants, with potential positive implications on growth. These data contribute to the development of accurate feeding protocols for preterm infants. Given that feeding practices are culturally influenced, further multinational research is essential to refine complementary feeding guidelines for preterm infants and support caregivers in informed decision-making.

Humans

Ventriculostomy-Related Infections by Country-Income Level: A Systematic Review and Bayesian Hierarchical Meta-analysis.

Our objective was to perform a systematic review and meta-analysis of published literature on ventriculostomy-related infection (VRI) and evaluate temporal and global trends. We conducted a systematic review and Bayesian hierarchical random-effects meta-analysis of VRI rates in adults, stratified by country-income level (high-income countries [HIC]; low- or middle-income countries [LMIC]), study design, sample size, enrollment period, VRI intervention, and VRI definition. We identified 159 articles published between 1989 and 2025 that included 523,704 patients with 7293 VRIs. The pooled VRI rate was 8.64% [95% CI: 7.44-9.97], with moderate heterogeneity and good model fit. The leave-one-out sensitivity analysis showed a mean absolute change of 0.06% and a maximum change of 0.2%, indicating robust analysis. Five of the 33 represented countries had VRI rates below the global pooled rate of 8.64%. Four were HICs: Singapore (VRI rate 3.3% [0.8-7]), the United States (VRI rate 4.6% [3.4-5.9]), Germany (VRI rate 6.1% [1.1-18.9]), Norway (8.3% [0.3-68.4]), with 1 LMIC: China (8.5% [5.4-12.4]). VRI was significantly higher in studies using definitions beyond CSF culture alone for VRI (+3.16% [0.11- 6.52]) and in those from Europe (+7.29% [4.62-10.10]) and the Western Pacific (+4.09% [1.55-6.98]). No other subgroup demonstrated significant differences. This Bayesian meta-analysis provides global estimates and factors associated with VRI. Standardization of VRI definitions is critical for future benchmarking of VRI rates.

Humans

Coordinated use of three homocysteine methyltransferases supports l-methionine biosynthesis and environmental adaptation among plant-associated bacteria.

Plant pathogens colonize multiple plant-associated habitats throughout their life cycle, encountering distinct nutrient conditions and microbial communities. l-methionine is required for bacterial growth and environmental adaptation. However, how plant pathogens coordinate l-methionine biosynthetic pathways to adapt to different plant-associated environments remains poorly understood. Here, using the plant pathogen Xanthomonas campestris pv. campestris strain XC1 as a model, we show that three homocysteine methyltransferase pathways allow XC1 to catalyze the final step of l-methionine biosynthesis using different methyl donors and cofactors under different environmental conditions. Bioinformatic and transcriptional analyses identified three homocysteine methyltransferase-associated operons in XC1, mesMXD, mmuPM, and metHRHaHb, corresponding to the MesD-, MmuM-, and MetHaHb-dependent pathways, respectively. MesD uses an endogenously synthesized methyl donor and functions as the dominant homocysteine methyltransferase under l-methionine-limiting conditions, supporting bacterial growth, intracellular l-methionine accumulation, and full virulence. Furthermore, MmuM enables XC1 to use plant-derived S-methylmethionine for l-methionine biosynthesis, whereas MetHaHb enables XC1 to use vitamin B12 supplied by a neighboring bacterium for l-methionine biosynthesis in co-culture. Expression analyses showed that mesMXD was the only homocysteine methyltransferase-associated operon that responded to l-methionine availability, and its expression also decreased when S-methylmethionine- or vitamin B12-dependent pathways supported l-methionine biosynthesis. Comparative genomic analysis further showed that the three-homocysteine methyltransferase configuration is conserved in Xanthomonas and is also present in other plant-associated bacteria. Together, these findings show that a plant pathogen can coordinate endogenous, plant-derived, and microbially supported homocysteine methyltransferase pathways to maintain l-methionine biosynthesis, providing a metabolic strategy for adaptation to plant-associated environments.

Methionine

Comparison of short-term clinical outcomes and patient satisfaction between intraoral scanning and conventional impressions for complete-arch implant prostheses: a pilot RCT.

OBJECTIVE: To compare framework passive fit, subjective evaluations, and short-term clinical outcomes between conventional impressions (CI) and intraoral scanning (IOS) for complete-arch implant-supported fixed dental prostheses (CIFDPs). METHODS: In this randomized controlled trial, 22 patients were allocated to the CI or IOS groups. All participants received a definitive one-piece CIFDP. The primary outcome was framework passive fit, assessed using the Vision and Tactile Score (V&T score), which included framework lift-off, the single-screw test, the full-screw test, smoothness of screw insertion, and radiographic gap assessment. Secondary outcomes included operator evaluation, patient satisfaction using a visual analog scale (VAS), early implant survival, marginal bone loss (MBL), modified Plaque Index (mPII), and complications at the 6-month follow-up. RESULTS: Twenty-two patients were enrolled (CI: n = 11; IOS: n = 11), and one patient in the CI group was lost to follow-up. No statistically significant difference in the V&T score was observed between the CI and IOS groups (4.66 &#xb1; 0.17 vs. 4.65 &#xb1; 0.28; P = 0.93). The operator reported greater nervousness during the CI procedure than during IOS (21.82 &#xb1; 15.69 vs. 8.64 &#xb1; 7.47; P < 0.05). Patients in the CI group reported significantly greater discomfort, including nausea and anxiety, than those in the IOS group (P < 0.05). At the 6-month follow-up, the early implant survival rate was 100% in both groups. No significant differences were found between the groups in MBL (0.09 &#xb1; 0.09 vs. 0.06 &#xb1; 0.10 mm; P = 0.43) or mPII (0.10 &#xb1; 0.12 vs. 0.10 &#xb1; 0.28; P = 0.99). CONCLUSION: IOS and CI achieved comparable short-term clinical outcomes in patients who met the predefined inclusion criteria, including controlled implant number, spacing, and angulation. IOS provided a more favorable experience for both operators and patients. CLINICAL SIGNIFICANCE: In complete-arch implant restorations, intraoral scanning may provide clinical outcomes comparable to those of conventional impressions while improving patient comfort.

Humans

To longevity and beyond: A systems view of aging and stress resilience.

Aging is a dynamic and time-dependent process characterized by progressive functional decline across biological systems. Key hallmarks, including genomic instability, telomere attrition, loss of proteostasis, mitochondrial dysfunction, and immunosenescence, have been widely described, each reflecting distinct yet interconnected mechanistic frameworks. Rather than acting in isolation, these processes arise from complex interactions among cellular stressors, impaired repair mechanisms, and the cumulative burden of maladaptive responses. This system-level perspective explains the inter-individual variability in aging trajectories. Centenarians represent an extreme and informative model of successful aging, in which the balance between damage accumulation and repair is shifted toward the maintenance of physiological function. Their exceptional longevity is supported by coordinated genetic, epigenetic, metabolic, and immunological adaptations that enhance resilience to age-related stressors. Here, we summarize the biological drivers and theoretical frameworks of aging within an integrative context, focusing on mechanisms associated with extended healthspan in centenarians. We also examine the contribution of major animal models, highlighting their complementary roles in elucidating conserved and species-specific aging pathways. Overall, aging outcomes reflect a dynamic equilibrium between damage and repair processes. Understanding how this balance is modulated in long-lived individuals may inform strategies to promote healthy aging and delay the onset of age-related diseases.

Humans

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans

How to assess different types of abstract concepts in brain disorders: A systematic review.

The clinical evaluation of semantic knowledge has predominantly relied on tools targeting concrete concepts, whereas abstract knowledge has historically received limited attention despite its importance in everyday communication. Only a few instruments have explored the internal subdivision of abstract knowledge, likely due to the intrinsic difficulty of defining specific types of concepts or dimensions, resulting in a fragmented and heterogeneous neuropsychological assessment framework that limits our understanding of this domain. This systematic review examined the tools used to assess various types of abstract concepts in clinical populations. A literature search has been performed on the electronic databases of PubMed and Google Scholar (last update: October 2025). A total of 17 tests is reviewed, differing in the test characteristics, i.e. ranging from automatic to controlled processes and varying in ecological validity, the type of stimuli employed, and the abstract dimensions explored. Most studies have focused on neurodegenerative patients, while comparatively few have examined other clinical conditions. The risk of bias of the reviewed studies was assessed using an ad hoc developed instrument. This review highlights the need for future research to extend investigations to additional abstract domains and clinical populations, while also identifying key challenges related to stimulus selection and the determination of the most appropriate assessment framework.

Humans

BRAIN-Diabetes: Acceptability of an adapted FINGER multidomain intervention among adults living with type 2 diabetes in rural border regions across the island of Ireland.

BackgroundIndividuals with type 2 diabetes mellitus (T2DM) face increased risk of cognitive decline and dementia. Multidomain lifestyle interventions offer a non-pharmacological strategy to support brain health in this high-risk group.ObjectiveThis study examined the acceptability of a culturally adapted FINGER-based intervention among adults living with T2DM in rural border regions of Ireland (BRAIN-Diabetes Trial).MethodsA 6-month pilot randomized controlled trial was conducted. The intervention group received a multidomain program targeting diet, physical activity, and computerized cognitive training (CCT). The control group received standard care. Acceptability was assessed using questionnaires (all participants) and semi-structured interviews (intervention participants). Quantitative data were analyzed descriptively and qualitative data using template analysis, guided by four a-priori themes: trial participation and engagement, dietary behavior change, exercise behavior change, and CCT behavior change.ResultsQuestionnaire data (intervention: n&#x2009;=&#x2009;28; control: n&#x2009;=&#x2009;36) indicated high overall acceptability. Dietary and exercise components were rated most positively, while CCT component was less well received. Interviews (n&#x2009;=&#x2009;25) highlighted facilitators to trial engagement, including perceived health improvements, and social connection, with time constraints and limited personalization as barriers. Dietary change was supported by tailored guidance but hindered by cost and availability. Facilitators for exercise included accessible resources and perceived benefits, with barriers including competing priorities. CCT engagement was mixed, with challenges including digital access and repetitiveness.ConclusionsThe Brain-Diabetes intervention was acceptable and feasible among adults with T2DM. Personalized support and accessible resources were key to engagement. Future work should refine delivery to enhance scalability and long-term adherence among high-risk groups.

Humans

Chemical and sensory profiling of fermented, washed, and artificially flavored coffee beans: Insights into flavour quality, authenticity, and food safety implications.

This study establishes an integrated framework combining chemical profiling, sensory analysis, and molecular mechanism evaluation to compare flavour quality and authenticity among fermented, washed, and artificially flavored coffees. GC&#xa0;&#xd7;&#xa0;GC-TOF-MS and UHPLC-HRMS showed that fermented samples had markedly higher ester and aromatic alcohol levels (total esters 74.5&#xa0;&#xb1;&#xa0;7.8&#xa0;mg&#xa0;kg-1; phenylethanol 27.5&#xa0;&#xb1;&#xa0;3.2&#xa0;mg&#xa0;kg-1, p&#xa0;<&#xa0;0.01), enhancing fruity-floral notes. Washed coffees contained the highest organic acid concentrations (45.2&#xa0;&#xb1;&#xa0;3.8&#xa0;mg&#xa0;kg-1, p&#xa0;<&#xa0;0.01), supporting brightness and umami. Artificially flavored coffees exhibited elevated exogenous aromatics (vanillin 21.5&#xa0;&#xb1;&#xa0;3.1&#xa0;mg&#xa0;kg-1) but significantly fewer Maillard products (p&#xa0;<&#xa0;0.05) and reduced flavour retention (55% after 14 days). Molecular docking revealed higher theoretical binding affinities for naturally generated compounds, suggesting a potential molecular basis for their greater sensory persistence. The framework supports constructing coffee quality fingerprints and verifying flavour authenticity.

Flavoring Agents

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