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Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends.

Antimicrobial resistance (AMR) constrains effective treatment and carries implications for infection control, surveillance, and public health. The World Health Organization (WHO) priority bacterial pathogen framework has intensified the need for diagnostic innovation by redefining research priorities around organisms combining high disease burden with complex resistance profiles. Molecular diagnostics have accordingly moved beyond culture-based workflows, integrating rapid pathogen identification, resistance-marker detection, genomic surveillance, and clinical decision support. The present study conducted a bibliometric mapping of the literature on WHO priority pathogens. Rather than addressing resistance at a general level or a single pathogen or technology, it integrates priority pathogens, molecular platforms, and resistance markers within a single framework, tracing their joint thematic and temporal evolution along an explicit pathogen-platform-marker axis. Scopus-indexed articles and reviews (2000-2025) were retrieved, yielding 1746 publications after screening adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyses used Bibliometrix/Biblioshiny, R, and VOSviewer. The literature expanded markedly after 2018, led by China and the United States. Methicillin-resistant Staphylococcus aureus (MRSA), Mycobacterium tuberculosis, Enterococcus faecium, and the Enterobacterales-carbapenemase axis constituted the principal thematic cores, whereas conventional polymerase chain reaction (PCR)/nucleic acid amplification testing (NAAT) and whole-genome sequencing were the dominant platforms. Overall, the field has evolved from pathogen detection into an AMR-centered translational domain encompassing resistance prediction, genomic epidemiology, surveillance, and clinical decision support. Diagnostic development, stewardship, and surveillance depend on hybrid workflows coupling rapid marker-targeted assays with genome-based characterization, delivering actionable resistance within clinically meaningful timeframes, and extending coverage to underrepresented pathogens and platforms.

Humans

Functional and Nutritional Potential of Chickpea Protein Hydrolysates: A Systematic Review and Plant-protein Network Analysis.

Chickpea is a protein-rich legume increasingly explored as a substrate for functional plant-based ingredients. Chickpea protein hydrolysates (CPHs) and chickpea-derived peptides (CPs), obtained through enzymatic hydrolysis or simulated gastrointestinal digestion, may provide technological and biological properties while supporting the valorization of chickpea fractions and by-products. This review integrates a network analysis of title-abstract terms from 5,728 unique Scopus and PubMed records on plant protein hydrolysates with a systematic review of 72 studies focused on CPH production, peptide characterization, bioactivity, and translational gaps. The evidence indicates that CPHs and CPs show promising antioxidant, antihypertensive, antidiabetic, anti-inflammatory, lipid-lowering, immunomodulatory, antimicrobial, and anticancer-related activities, mainly supported by biochemical assays, cell models, and animal studies. However, heterogeneous hydrolysis protocols, incomplete peptide characterization, inconsistent bioactivity methods, limited scale-up evidence, and the absence of human intervention trials restrict translation. Future studies should prioritize standardized protocols, mechanistic validation, bioavailability, sensory and regulatory assessment, food-matrix validation, and clinical trials.

Cicer

Effectiveness of artificial intelligence in nursing simulation education: A systematic review, meta-analysis and bibliometric visualization analysis.

OBJECTIVES: To synthesize the roles and core functions of AI in nursing simulation education for nursing students via systematic review, quantitatively evaluate its effects on students' knowledge and skill outcomes through meta-analysis, and map the research landscape and development trends of this field through bibliometric visualization analysis. DESIGN: Systematic review, meta-analysis and bibliometric visualization analysis. DATA SOURCES: Eight electronic databases: PubMed, Web of Science, MEDLINE, ERIC, Academic Search Complete, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Chinese Science and Technology Journal Database (VIP) were employed to search studies from the time of construction to 16 December 2025. REVIEW METHODS: Studies meeting the inclusion criteria were screened. The revised Cochrane Risk of Bias tool (ROB 2) and Joanna Briggs Institute (JBI) critical appraisal checklists were used for quality assessment. Meta-analysis was performed with Review Manager 5.4, and bibliometric visualization analysis was conducted using VOSviewer 1.6.20 and Bibliometrix (based on R4.4.3). RESULTS: A total of 61 studies were included. AI primarily played two roles in nursing simulation education: peer-type new subject (n = 24) and direct mediator (n = 22). Meta-analysis showed that AI interventions significantly improved nursing students' knowledge (SMD = 1.49, 95% CI [0.55,2.43], p = 0.002) and skills (SMD = 0.66, 95% CI [0.02,1.31], p = 0.04). Bibliometric analysis identified that the United States of America and China were the two main contributing countries in this field, and the key motor themes included generative artificial intelligence, virtual patients, and geriatric care. CONCLUSIONS: AI exerts positive effects on nursing students' knowledge acquisition and skill enhancement in simulation education, with peer-type new subject and direct mediator as the dominant roles. Future research should focus on expanding AI applications in multi-specialty simulation scenarios, activating the data-driven value of machine learning, and strengthening international collaboration and standardization construction, so as to promote the sustainable development of AI-integrated nursing simulation education.

Humans

Non-linear predictive modeling and comprehensive meta-analysis of rectal temperature in Santa Inês sheep: a systematic review of thermal challenges and biometerological trends.

A systematic and bibliometric review, combined with a meta-analysis, was used to adjust an equation for estimating the physiological responses of Santa Inês sheep subjected to different thermal challenges. The systematic review compiled data on physiological responses and the thermal environment, which were then used in the meta-analysis to adjust regression models. The bibliometric analysis mapped the relationships among studies, highlighting their usefulness in interpreting research findings and biases. Addressing prior methodological critiques, the core of this study involves replacing the linear approach with a non-linear segmented regression model to accurately define the Thermal Neutral Zone (TNZ). The Segmented Regression Model was crucial, establishing the upper limit of the Thermal Neutral Zone (TNZ) at an air temperature (tair) of 34.64 °C, where trectal begins to increase abruptly. The model, while identifying a biologically significant breakpoint, exhibited a moderate Multiple R-squared of 0.3529, highlighting the high heterogeneity and methodological variability in the current Santa Inês literature. This non-linear approach offers a biologically superior tool for identifying the onset of thermal distress.

Animals

Trends in demographic and health survey publications based on a bibliometric analysis.

BACKGROUND: The Demographic and Health Surveys (DHS) Program, launched in 1984, provides high-quality population health data that underpins a vast body of global health research. However, the scale and growth patterns of DHS-based publications remain underexplored, particularly as donor funding uncertainties threaten program sustainability. OBJECTIVE: We examine temporal trends in DHS-based research output from 1984 to 2025, quantifying growth patterns and publication delays to inform understanding of the program's global research expansion. METHODS: A systematic bibliometric review was conducted following PRISMA guidelines across PubMed, Scopus, Web of Science, Dimensions, Wiley, and CINAHL. Eligible peer-reviewed articles using DHS data between 1984 and 2025 were identified. Annual publication counts were analyzed, segmented regression identified growth inflection points, and timeliness was assessed by calculating lag between survey completion and publication. RESULTS: Over 10,000 DHS-based publications were identified. Annual output rose from isolated studies in the 1980s to several hundred annually by the 2010s. Segmentation analysis revealed two rapid growth phases: a 56-publications/year increase from 2004-2012, and a 71-publications/year increase from 2012 to 2024. Despite this growth, median lag from survey completion to publication remained approximately 5 years, with only a modest recent improvement (Kendall's &#x3c4;&#x2009;=&#x2009; -0.623, p&#x2009;<&#x2009;0.001). CONCLUSION: DHS data have fueled exponential growth in global health research over four decades, confirming their vital role in evidence generation. However, persistent publication delays highlight the need to shorten the pathway from data collection to dissemination through strengthened research capacity in low- and middle-income countries. Sustained funding is essential to maintain this critical evidence source.

Bibliometrics

Theta-range SEEG stimulation for intracranial mapping: extending conventional 1-Hz and 50-Hz protocols.

OBJECTIVE: Electrical brain stimulations (EBS) are central to epileptic network identification and functional mapping during stereo-electroencephalography, yet stimulation frequencies remain empirical, and standardized across patients and brain regions, producing false negatives and false positives, and potentially compromising surgical outcome. We prospectively investigated theta-range EBS (7&#xa0;Hz) in the temporal lobe, a prominent physiological frequency band in this region, and compared it with conventional 1-Hz and 50-Hz protocols. METHODS: We analyzed 1,408 temporal EBS in 25 drug-resistant epileptic patients. Epileptic responses (afterdischarges, seizures) and clinical signs were assessed across the epileptic network and temporal structures (amygdala, hippocampus, neocortex, parahippocampal gyrus, white matter), and confronted to stimulation parameters (frequency, intensity, duration, total charge). RESULTS: At matched intensity and duration, 7-Hz EBS were associated with a higher occurrence of afterdischarges and clinical signs than 1-Hz EBS in several temporal structures. Effects on usual seizure induction were less consistent. Comparisons with 50&#xa0;Hz showed no systematic significant differences, with responses observed at one or both frequencies depending on structure and outcome. When controlling for total charge, frequency-related differences were attenuated. Some effects were sporadically observed at both intermediate frequency and charge quantity. CONCLUSIONS: EBS responses emerge from the interaction between all electrical parameters and anatomical location and local excitability, and can hardly be disentangled. However, 7-Hz EBS can provide complementary clinical information during temporal-lobe mapping, with a targeted approach. SIGNIFICANCE: These findings support targeted evaluation of broader stimulation parameter spaces, including intermediate frequencies, rather than routine reliance on fixed low- and high-frequency protocols alone.

Humans

Journey Mapping of the Patient Experience from Diagnosis to End of Life in Lung Cancer: A Qualitative Meta-Synthesis.

OBJECTIVES: This study aimed to systematically synthesize the lived experiences and journey narratives of lung cancer patients across disease stages, and identify key tasks and pain points during the disease course through patient journey mapping, providing evidence for comprehensive disease management throughout the patient journey. METHODS: Ten databases, including PubMed, Embase, Web of Science, Scopus, PsycINFO, CINAHL, Cochrane Library, CNKI, Wanfang, and SinoMed, were systematically searched, with a search period from database inception to August 15, 2025. The JBI Critical Appraisal Tool for qualitative studies was used to evaluate the quality of studies, and the results were integrated using a meta-aggregative approach. RESULTS: Thirteen studies were included. Based on the patient journey mapping, the lung cancer patient journey comprises four potential stages: evaluation and diagnosis, initial treatment, maintenance therapy, and end-of-life. A total of 30 themes emerged within three dimensions: tasks, emotions, and pain points. Each dimension of each stage consists of 2-3 themes. CONCLUSION: The journey of lung cancer patients is protracted and complex, characterized by stage-specific needs and challenges. Future management strategies should be tailored to these distinct phases, providing precision supportive care to optimize treatment outcomes and enhance patients' quality of life. IMPLICATIONS FOR NURSING PRACTICE: This Patient Journey Map integrates routine clinical pathways with patients' lived experiences across each stage, revealing stage-specific challenges and providing targets for tailored nursing interventions. The framework promotes multidisciplinary, digitally enabled supportive care and indicates the importance of including patients' social circles to enhance patient-centered outcomes.

Humans

[Optical genome mapping analysis of a Chinese pedigree with a complex balanced translocation involving four chromosomes].

OBJECTIVE: To explore the genetic characteristics of a complex balanced translocation involving four non-homologous chromosomes in a Chinese pedigree using optical genomic mapping (OGM). METHODS: A woman with primary infertility and her family members who presented at the Prenatal Diagnosis Center of the Sixth Affiliated Hospital of Sun Yat-sen University in October 2021 were selected as study subjects. Comprehensive analysis and verification of chromosomal abnormalities were conducted through conventional G-band karyotyping analysis, single nucleotide polymorphism microarray (SNP array) and OGM. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: E2022210). RESULTS: G-band karyotyping analysis indicated that the proband, her father, and younger brother have all carried a complex translocation involving four chromosomes. SNP array analysis revealed a duplication of approximately 21.63 Mb in the 9p24.1-p21.1 region in the proband's younger brother, while no abnormality was detected in other family members. OGM confirmed that the complex balanced translocation has involved chromosomes 5, 8, 9, and 10. CONCLUSION: The proband has harbored a complex balanced translocation. OGM has demonstrated certain advantages in characterization of complex chromosomal structural abnormalities.

Humans

Mapping antibody sequences and effector functions across spatial niches.

Antibodies are fundamental to human health but can also drive pathology. Each antibody has a molecular specificity, encoded by their clonally heritable B cell receptor (BCR). Recent advances in spatial transcriptomics coupled with repertoire sequencing have enabled capturing antibody-secreting cells (ASCs) and their clonal BCR within their tissue microenvironment. However, our understanding of antibody production niches remains limited. Furthermore, where antibodies are produced can be distinct from where antibodies exert their effector function. Here, we propose a conceptual spatial framework to distinguish between 'antibody production niches', defined by the ASC, BCR, and niche composition, versus 'antibody functional niches', composed of the antibody, antigen, and effector landscape. We then examine the possibilities and challenges to map and link antibody-encoding sequences and antibody effector functions using current and emerging technologies. Combined, we argue that integrating spatial sequence data with the antibody functional context is essential to decode the architecture of antibody-mediated immunity.

Humans

Quantitative susceptibility mapping in neurodegenerative diseases: An umbrella review of iron-related biomarkers and mechanisms.

Pathological iron accumulation is a common pathophysiological hallmark across multiple neurodegenerative diseases (NDDs), motivating the need for accurate, non-invasive quantification methods. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that enables in vivo measurement of tissue magnetic susceptibility (&#x3c7;), providing a sensitive proxy for iron content. This umbrella review systematically evaluates the diagnostic accuracy, clinical correlations, and distinct iron distribution patterns of QSM in major NDDs, such as Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and atypical Parkinsonism. We included 15 (13/15 were rated Low or Critically Low on AMSTAR 2) systematic reviews and meta-analyses (through July 15, 2026); however, the findings should be interpreted cautiously because of heterogeneity and the low methodological quality. A Corrected Covered Area (CCA) analysis demonstrated only slight overlap of primary studies across the included reviews (CCA&#xa0;=&#xa0;5.42%). Collectively, the evidence indicates that QSM provides comparable or higher diagnostic sensitivity and reliability than conventional R2* and SWI techniques, particularly for deep gray matter structures. The findings support significant iron overload in the substantia nigra, particularly in the pars compacta, as a robust biomarker for PD that correlates with motor severity and disease duration. Furthermore, regional iron profiling in the basal ganglia is critical for differential diagnosis; specifically, elevated &#x3c7; in the putamen and globus pallidus effectively distinguishes multiple system atrophy and progressive supranuclear palsy from idiopathic PD. Distinctively, AD and ALS exhibit specific &#x3c7; alterations in the thalamus, motor cortex, and hippocampus, reflecting divergent iron-related pathophysiological mechanisms, which correlate with cognitive impairment and upper motor neuron signs. Overall, QSM shows diagnostic promise and offers mechanistic insights into iron-related neurodegenerative processes.

Humans

Context-dependent functional diversity of dorsomedial posterior parietal neurons revealed by single-unit fMRI mapping during naturalistic viewing.

The dorsomedial posterior parietal cortex (dmPPC) plays an important role in episodic processing by integrating sensory, cognitive, and motor information across distributed brain systems. However, how individual dmPPC neurons participate in large-scale functional organization during naturalistic experience remains poorly understood. To address this question, we combined single-unit electrophysiology and awake fMRI in five rhesus macaques of both sexes viewing identical naturalistic video stimuli. Using single-unit fMRI mapping, we generated whole-brain neuron-BOLD functional maps by correlating individual neuronal activity with voxel-wise fMRI signals across the brain. We found that neuron-BOLD functional maps exhibited strong context-dependent organization, with neurons recorded during the same video context showing substantially greater similarity than neurons recorded during different video conditions. Compared with neuronal spiking activity or critical fMRI frames alone, neuron-BOLD functional maps more robustly captured contextual structure. Despite this shared large-scale organization, a substantial subset of neighboring neurons recorded simultaneously from the same electrode displayed markedly distinct whole-brain association patterns, revealing substantial local functional heterogeneity within the dmPPC. This local heterogeneity was not readily explained by waveform-based putative cell class or by opposing neuronal firing dynamics. In addition, distributed cortical and medial temporal regions exhibited highly context-dependent neuron-BOLD association patterns during naturalistic viewing. Together, these findings demonstrate that dmPPC neurons participate in dynamic and heterogeneous large-scale functional organization during naturalistic episodic processing. More broadly, this study establishes single-unit fMRI mapping as a framework for linking single-neuron activity to distributed whole-brain dynamics across contextual conditions.Significance Statement Using single-unit fMRI mapping, this study examined how individual dorsomedial posterior parietal cortex (dmPPC) neurons relate to large-scale brain activity during naturalistic video viewing in macaque monkeys. We found that neuron-BOLD functional maps exhibit strong context-dependent organization and capture contextual structure more robustly than neuronal spiking activity or fMRI frames alone. Despite this shared organization, a substantial subset of neighboring dmPPC neurons displayed markedly distinct whole-brain association patterns, revealing local functional heterogeneity that was not readily explained by waveform-based putative cell class or opposing firing dynamics. These findings provide insight into how local neuronal populations participate in distributed brain-wide functional organization during naturalistic episodic processing.

Journal Article

Three-Dimensional Fracture Mapping of the Terrible Triad of the Elbow: Morphological Characteristics and Clinical Implications.

BACKGROUND: The morphology of fractures in the terrible triad of the elbow (TTE) is complex, and precise management relies on a profound understanding of this morphology. This study aims to systematically analyze, for the first time, the distribution and morphological characteristics of TTE fracture lines using three-dimensional (3D) imaging technology. METHODS: Clinical data and thin-slice CT scans of 112 patients with TTE from January 2021 to December 2024 were retrospectively included. 3D fracture models were reconstructed using Mimics software. Virtual reduction and standardized alignment were performed using 3-matic software. Fracture lines were mapped onto standard ulnar and radial templates, and 3D fracture heat maps were generated using the E-3D software to demonstrate the high-frequency distribution zones of the fracture lines visually. Statistical analysis was performed using SPSS software (version 21.0, IBM Corp., Armonk, NY, USA). Continuous variables were compared using one-way analysis of variance (ANOVA), and categorical variables were compared using the chi-square test (&#x3c7;2 test). A two-tailed p&#x2009;<&#x2009;0.05 was considered statistically significant. RESULTS: The study revealed distinct patterns in the distribution of TTE fracture lines. In the coronoid process, the fracture "hot zone" presented as an annular high-density band extending from the lateral middle aspect to the tip. In the radial head, an oblique high-density band was observed in the anterolateral quadrant of the articular surface. The radial neck exhibited a circumferential high-density zone, which was most prominent in the anterolateral aspect. Statistical analysis indicated a significant correlation between age and fracture complexity; the proportion of Regan-Morrey type III coronoid fractures and Mason type III radial head fractures was significantly higher in elderly patients (>&#x2009;60&#x2009;years) (p&#x2009;<&#x2009;0.05), suggesting that advanced age is a significant risk factor for complex fractures. CONCLUSION: This study is the first to visually reveal the Collaborative Distribution Patterns of TTE fracture lines using 3D fracture mapping technology. This model provides morphological evidence for understanding the injury mechanism of TTE and offers an anatomical framework that may assist surgeons in individualizing surgical approaches and fixation strategies.

Humans

Effectiveness of symptom map-based education in the management of premenstrual syndrome: a randomized controlled trial.

PURPOSE: To evaluate the effectiveness of a symptom map-based educational intervention for the non-pharmacological management of premenstrual syndrome (PMS), with a focus on symptom reduction among women with differing baseline symptom severity. METHODS: This randomized controlled study was conducted between May and December 2024. A total of 110 women meeting diagnostic criteria for PMS were randomly assigned to an intervention group (n = 55) or a control group (n = 55) using block randomization, and 101 participants completed follow-up assessments. The intervention comprised structured education based on a PMS symptom map and evidence-based self-care strategies. Outcomes included PMS symptom severity (Premenstrual Syndrome Scale), pain intensity (Visual Analog Scale), psychological symptoms (Depression Anxiety Stress Scale-21), and PMS-specific life satisfaction. CLINICAL TRIAL REGISTRATION: NCT06585475. RESULTS: Compared with the control group, women in the intervention group reported significantly lower pain (adjusted mean 4.21 vs. 6.81, p < .001) and stress levels (8.54 vs. 12.03, p < .001) at follow-up. The intervention was particularly effective in reducing PMS symptom severity and depressive symptoms among participants with higher baseline symptom burden. Improvements in PMS-specific life satisfaction were observed, with reductions in depressive symptoms contributing to this effect. CONCLUSION: A symptom map-based educational intervention is a clinically applicable, non-pharmacological approach for PMS management. This structured education appears especially beneficial for women with more severe baseline symptoms and may be integrated into routine gynecological care to support individualized symptom management.

Humans

Combining neuromelanin-sensitive MRI and quantitative susceptibility mapping for enhanced diagnosis and differentiation of parkinson's disease: A systematic review.

BACKGROUND: Loss of dopaminergic neurones and iron deposition in the substantia nigra pars compacta (SNpc) are two major pathological hallmarks of Parkinson's disease (PD). Such changes can be visualised by advanced techniques including neuromelanin-sensitive MRI (NM-MRI) and quantitative susceptibility mapping (QSM). This systematic review investigates the diagnostic performance and methodological development of the integrated use of NM-MRI and QSM in PD. METHODS: The systematic search was performed in four databases (Scopus, PubMed, ScienceDirect, and Web of Science) according to the PRISMA 2020 guidelines until July 2026. Bias was assessed using QUADAS-2 and certainty of evidence was assessed using GRADE. RESULTS: Seventeen studies with 2228 participants were included. Combined NM-MRI and QSM consistently showed reduced neuromelanin volume/contrast and increased iron deposition in the SNpc of PD patients compared to healthy controls. Multimodal integration yielded a significant improvement in diagnostic accuracy (AUC values 0.86-0.99), and was able to successfully differentiate PD. Recent methodological advances included simultaneous acquisition sequences (e.g. MTC-GRE, STAGE, setMag) and AI-driven automated segmentation, which led to significantly reduced scan times and improved reproducibility. CONCLUSION: The combination of NM-MRI and QSM has a synergistic effect and provides powerful complementary biomarkers for the diagnosis and differential diagnosis of PD.

Humans

Retention strategies and participant retention rates among prospective longitudinal pregnancy cohorts: a systematic mapping review.

Prospective longitudinal pregnancy cohorts can answer questions about fetal and early life exposures and later health outcomes; however, there are challenges to retaining participants in longitudinal studies, particularly over life transitions like the birth of a child. Optimal methods for retaining participants in longitudinal research are unclear. A systematic mapping review was conducted to identify prospective cohort studies and randomized controlled trials that enrolled pregnant participants and their infants. Data on retention rates and 17 retention strategies was extracted. A random effects meta-analysis generated pooled annual retention rates inversely weighted to the number of baseline participants. Spearman rank coefficients were used to assess correlation between strategy use and retention. A random-effects meta-regression was used to determine if select retention strategies were associated with participant retention. We identified 130 studies, involving 472 022 pregnancies. A downward trend in pooled mean retention rates were observed. Studies utilized an average of 6.8 (SD 3.9) retention strategies. Statistically significant associations were not observed between strategy use and retention rates at follow-up (p&#x202f;>&#x202f;0.05). Prospective studies of pregnant people and their infants used multiple retention strategies. Participant retention rates declined over time, suggesting that additional factors may influence study participation in the postpartum period.

Humans

Spatial transcriptomics of Ciona adult brains reveals functional zonalization and insights into neural gland function.

The ascidian Ciona is a pivotal chordate model for illuminating the evolutionary origins of the vertebrate brain. Here, spatial transcriptomics of the adult Ciona neural complex, combined with image-based computational super-resolution mapping, resolved distinct tissue domains including the cerebral ganglion, neural gland, ciliated funnel, neural gland duct/dorsal strand, and body wall muscle. Within the cerebral ganglion, high-resolution mapping revealed clear molecular zonalization separating the cortex and medulla, alongside regional specialization within the cortex itself. The neural gland exhibited localized enrichment of genes associated with extracellular matrix and cell-cell interactions. These spatial features suggest that the neural gland functions as a homeostatic and signaling interface, reminiscent of primitive vertebrate meninges or choroid plexus. Overall, this spatially defined gene expression map provides a foundational framework for understanding functional regionalization in the tunicate brain and its evolutionary relationship to vertebrate nervous systems.

Ciona

Mapping Wastewater Pathogens and Their Associated Environmental and Public Health Risk Factors: A Systematic Review and Meta-Analysis.

BACKGROUND: Wastewater-based epidemiology (WBE) has emerged as a critical tool for public health surveillance, yet its application across diverse pathogens and geographical settings remains inconsistent. This systematic review synthesizes global evidence on wastewater surveillance to identify associated risk factors. METHODS: Following PRISMA 2020 guidelines (PROSPERO: CRD420261297382), a systematic search was conducted across PubMed, Scopus, Google Scholar, and Web of Science for studies published between 2000 and 2025. RESULTS: Thirty-nine peer-reviewed studies were included. The evidence base is geographically skewed toward the European Region (48.7%) and the Americas (23.1%), with significant underrepresentation in LMICs. Viruses were the primary biological target (89.7%), followed by bacteria (7.7%) and parasites (2.6%). A proportion meta-analysis of 31 eligible studies demonstrated a pooled wastewater pathogen detection prevalence of 62% (95% CI: 47.5-74.6%), with the European Region yielding the highest regional estimate (73%) and the African Region the lowest (8.3%). Conventional PCR and sequencing methods showed higher pooled detection rates (92.4% and 90.1%, respectively) than RT-qPCR (47.9%). CONCLUSION: WBE provides a robust early-warning system indicating a need for broader pathogen diversity, incorporating bacterial and parasitic surveillance and expansion into rural and resource-limited regions.

Contamination

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence