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A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals

Chlorfenapyr-pyrethroid nets for pyrethroid-resistant malaria vectors: efficacy, resistance risks, and policy implications.

The Global Technical Strategy for Malaria 2016-2030 aims to reduce malaria incidence and mortality by 90%, yet widespread pyrethroid resistance among major malaria vectors in sub-Saharan Africa threatens this goal. Thus, the World Health Organization recommends chlorfenapyr-pyrethroid combination nets as a priority intervention where pyrethroid resistance undermines vector control. This systematic review synthesizes evidence on the performance, emerging resistance risks, and policy implications of these next-generation insecticide-treated nets. A structured search of literature from 2010 to 2024 across PubMed, Embase, WHO IRIS, and Google Scholar identified 31 eligible studies from 113 records. Evidence shows that chlorfenapyr-pyrethroid nets consistently outperform pyrethroid-only nets against resistant Anopheles populations, demonstrating a 1.8-fold increase in mosquito mortality (95% CI: 1.5-2.1). Community trials report 40-60% reductions in malaria infection incidence and entomological inoculation rates following deployment. However, early signs of chlorfenapyr resistance have emerged in Anopheles gambiae populations in Central Africa (RR: 2.4, p&#x2009;=&#x2009;0.01), linked to CYP6P4 metabolic overexpression. A significant correlation was also observed between agricultural pesticide use and vector resistance patterns (r&#x2009;=&#x2009;0.62, p&#x2009;<&#x2009;0.05). Although chlorfenapyr-pyrethroid nets provide an important short-term tool for managing pyrethroid resistance, their long-term effectiveness depends on integrated resistance management. Rotational deployment with other insecticide classes, strengthened genetic and phenotypic surveillance, and a coordinated 'One Health' approach involving both public health and agriculture are essential to sustain gains and advance progress toward the 2030 malaria targets.

Pyrethrins

A Meta-learning-driven strategy for adulteration detection in sweet potato starch and vermicelli using Raman spectroscopy.

To address the widespread adulteration of sweet potato starch and its vermicelli with cheaper starches and overcome conventional supervised learning's dependency on large labeled datasets, this study developed a few-shot discrimination method integrating Raman spectroscopy with meta-learning. We constructed a meta-learning framework using cassava- and wheat-adulterated sweet potato starch as the source domain for training, with potato-adulterated sweet potato starch and cassava-adulterated sweet potato vermicelli as two target domains for testing. Raman spectra showed high consistency between sweet potato vermicelli and its raw starch, laying the foundation for cross-domain detection. Testing yielded comprehensive classification accuracies of 95.33% and 98.00% for the two target domains, significantly outperforming SVM, RF, and CNN (max. 85.24%). This approach effectively identifies subtle starch variety differences in complex adulteration, providing novel food quality inspection solutions and verifying the feasibility of raw material-to-finished product cross-domain detection.

Ipomoea batatas

Environmentally relevant concentrations of DCOIT impaired lifespan and healthspan in Caenorhabditis elegans.

DCOIT (4,5-dichloro-2-n-octyl-4-isothiazolin-3-one) is an antifouling biocide widely used as an alternative to organotin compounds. While previous studies had focused on its effects on energy production, endocrine disruption, and lipid metabolism, its impact on aging and underlying mechanisms remained unclear. Here, we demonstrated that environmentally relevant concentrations of DCOIT (37, 370 and 3700 ng/L) significantly impaired both lifespan and healthspan in Caenorhabditis elegans. RNA-seq and validation assays revealed that DCOIT upregulated comt-4, a key gene in dopamine metabolism, leading to dopamine depletion and subsequent induction of oxidative stress. This redox imbalance critically contributed to accelerated aging phenotypes. Importantly, both genetic (comt-4 RNAi) and pharmacological (opicapone) interventions restored dopamine levels, alleviated oxidative stress, and reversed DCOIT-induced aging deficits. Our study established the comt-4/dopamine/oxidative stress axis as a central mechanism in DCOIT toxicity, suggesting dopamine modulation as a potential countermeasure against environmental toxicant-induced aging.

Animals

Xerophthalmia and ocular manifestations of vitamin A deficiency in children in high-income countries: A systematic review.

Xerophthalmia is a vision-threatening eye condition caused by vitamin A deficiency (VAD). Cases of xerophthalmia in high-income countries (HICs) are vulnerable to misdiagnosis, causing delays in treatment and adverse visual outcomes. We define the features, causes and complications of VAD and xerophthalmia in children of HICs. Our study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines (CRD42024492023). We performed a search for eligible articles on Scopus, Web of Science, Cochrane, PubMed and Medline. Cases reporting on children under 18 years of age residing in HICs with ocular features of VAD were eligible for inclusion. The search yielded 2474 results; 43 case reports and case series met the inclusion criteria consisting of a total of 61 cases (mean age 9.9&#x202f;&#xb1;&#x202f;4.2 years, range 3-17 years). Xerophthalmia was graded according to the most advanced finding for each case: 21.3% had night blindness only; 29.5% had conjunctival xerosis or Bitot spots; 29.5% had corneal xerosis, ulceration or scarring; 1.6% had xerophthalmia fundus only; and 18.0% had ocular manifestations associated with VAD that are not encompassed under the WHO classification. These features included swollen optic discs, optic neuropathy, or ocular dryness. Restrictive dietary practises were the most common mechanism of deficiency (75%), and autism was the most common underlying condition (49%). This shows that VAD remains a cause of severe visual impairment in HICs, especially when associated with delays in diagnosis and treatment. Further research is required to establish the prevalence of xerophthalmia in HICs.

Humans

Pelvic lymph node dissection in prostate cancer: current evidence, controversies, and future directions.

BACKGROUND: Pelvic lymph node dissection (PLND) remains controversial in the management of prostate cancer. Although it provides the most accurate pathological staging, its therapeutic value beyond staging has long been debated due to conflicting evidence and concerns regarding procedure-related morbidity. OBJECTIVE: To critically evaluate the contemporary role of PLND, particularly extended pelvic lymph node dissection (ePLND), in prostate cancer management in the context of modern imaging, risk stratification tools, and evolving oncologic endpoints. EVIDENCE ACQUISITION: A narrative review of recent literature was conducted, focusing on high-level evidence including randomized trials, observational studies, and contemporary guideline recommendations addressing the indications, extent, oncologic outcomes, and complications of PLND. EVIDENCE SYNTHESIS: Recent randomized and observational studies suggest that ePLND improves nodal staging accuracy and may be associated with modest improvements in metastasis-free survival (MFS) in selected patients with intermediate- and high-risk prostate cancer, although the absolute benefit remains limited and causality is not definitively established. Advances in molecular imaging, particularly prostate-specific membrane antigen (PSMA) PET/CT, together with multiparametric MRI, validated nomograms, and emerging genomic classifiers, now allow more precise identification of patients most likely to benefit from ePLND. The integration of these tools supports a more individualized surgical strategy, including image-guided and sentinel lymph node approaches designed to maximize staging accuracy while minimizing unnecessary dissection. CONCLUSIONS: In the contemporary PSMA imaging era, ePLND continues to play an important role in nodal staging and may contribute to improved oncologic outcomes in carefully selected patients.

Humans

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 &#x3bc;g/person/day. Comprehensive safety assessment and intelligent sensing platforms will constitute pivotal directions for advancing MOFs-based smart packaging toward practical application.

Food Packaging

Comprehensive study on pesticide residues and mycotoxins in freeze-dried strawberries and raspberries.

Freeze-dried fruit has gained popularity because it preserves the flavour and nutritional value of fresh fruit while providing extended shelf life. Despite this, there are concerns regarding its chemical safety. This study evaluated 58 freeze-dried fruit products from the Czech retail market, focusing on potential contamination. Pesticide residues and mycotoxins were determined using LC-MS/MS and GC-MS/MS. Overall, 111 pesticide residues (or their metabolites) and 3 mycotoxins were quantified. After applying processing factors, 12 pesticide residues exceeded EU maximum residue limits. Prohibited substances, including carbofuran, omethoate, and haloxyfop, were detected. Tenuazonic acid was found in 71% of samples, while alternariol and tentoxin were detected less frequently. More than half (54%) of strawberry samples contained 10 or more pesticide residues, indicating potential cumulative exposure concerns, particularly for children with lower body weight. These findings highlight the need for continued monitoring of freeze-dried fruits and further assessment of dietary exposure.

Pesticide Residues

A review on the environmental distribution, toxic effects, bioaccumulation characteristics and risk assessment of short-chain chlorinated paraffins.

Chlorinated paraffins (CPs) are synthetic chemicals, widely used as flame retardants and plasticizers. As emerging contaminants, short chain chlorinated paraffins (SCCPs) have attracted tremendous attention due to their persistence, chronic toxicity, long-range transport potential and bioaccumulation potential. This review synthesizes global data on SCCPs' environmental occurrence, toxicological impacts, and bioaccumulation characteristics. SCCPs are ubiquitously detected in various environmental media, including water, sediment, air, soil, and biota. Ecotoxicological studies reveal that SCCPs have lethality, carcinogenicity, growth and developmental toxicities, organs toxicities and endocrine-disrupting effects across species, which pose risks to ecological systems and human health. In addition, the bioaccumulation effects of SCCPs in terrestrial and aquatic ecosystems were analyzed, and proposed the key factors affecting the bioaccumulation of SCCPs. Finally, the risk assessment of SCCPs contamination in the surface water and the soil was carried out, and all soil and most water bodies were found to be low risk. The present study could provide scientific basis and reference for environmental management of CPs products.

Paraffin

Functional role and regulatory network of miR-22-3p in chicken hepatic lipid metabolism.

Although microRNA-22-3p (miR-22-3p) is abundantly expressed in the avian liver, its epigenetic role in lipid homeostasis remains largely uncharacterized. To elucidate its in vivo function, 14-day-old female Qingyuan Partridge chickens were intravenously injected with lentiviral vectors to establish miR-22-3p overexpression and knockdown models. Phenotypic analysis demonstrated that miR-22-3p knockdown significantly elevated hepatic triglyceride (TG) levels (p&#xa0;<&#xa0;0.05) and drove marked steatosis, whereas its overexpression reduced TG content. Transcriptome sequencing (RNA-Seq) revealed profound metabolic remodeling, identifying 23 core lipid-associated genes (e.g., ELOVL6, FADS2, ACSBG2, and PTGIS) heavily enriched in steroid biosynthesis, fatty acid metabolism, and elongation pathways. In conclusion, miR-22-3p functions as a bidirectional epigenetic rheostat that negatively regulates hepatic lipid deposition by orchestrating a multilayered polygenic network, providing novel molecular targets for mitigating avian metabolic disorders and optimizing production traits in indigenous poultry breeds.

Animals

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

Boosting domestic wastewater treatment with quorum signal-augmented heterotrophic nitrification-aerobic denitrification bacterial-algal aerobic granular sludge.

The aerobic bacterial-algal granular sludge (ABGS) enhanced with heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria, as a novel symbiotic technology, exhibits fluctuating treatment efficiency and unstable performance primarily due to the unstable symbiotic relationship. This study proposes an innovative approach to strengthening the bacteria-algae symbiosis by introducing exogenous signaling molecules. Concurrently, high-throughput, correlation analysis of environmental factors and metagenomic sequencing techniques are employed to elucidate the enhancement mechanisms of the signaling molecules. The results demonstrate that signaling molecule enhancement boosted total nitrogen (TN) removal efficiency by 24.51 % in the bacteria-algae symbiotic system (X1). Scanning electron microscopy (SEM) characterization revealed that the addition of signaling molecules resulted in more compact aerobic granular sludge (AGS) and markedly improved stability. High-throughput sequencing showed signaling molecules enriched denitrifying bacteria (Hydrogenophaga, Pseudoxanthomonas, Thauera, Zoogloea) and organic-degrading Desulfomicrobium, optimizing microbial diversity and enhancing nitrogen/organic removal. Correlation analysis of environmental factors indicate that the addition of C8-HSL facilitates the enrichment and functional activation of specific genera. Metagenomic analysis revealed that signaling molecules enhanced the system's denitrification performance by modulating gene expression and associated metabolic pathways. Quantitative polymerase chain reaction (qPCR) analysis further confirmed that the signaling molecules upregulated the expression of the napA, nirK, and nirS genes. An increased abundance of the napA gene facilitated aerobic denitrification (NO&#x2083;&#x207b;-N&#x2192;NO&#x2082;&#x207b;-N), while upregulated abundance of the nirK and nirS genes accelerated nitrite reduction (NO&#x2082;&#x207b;-N&#x2192;N&#x2082;). This study aims to provide theoretical and practical foundations for implementing advanced bacteria-algae symbiotic technologies.

Denitrification

Dual-tasking reveals severity-dependent reorganization of cortical beta energy landscapes in Parkinson's disease.

Dual-task impairment is a hallmark of Parkinson's disease (PD), yet the large-scale neural mechanisms underlying postural-motor interference remain poorly understood. In particular, it is unclear how cortical network dynamics reorganize across disease severity when postural control competes with concurrent task demands. This study investigated EEG-derived beta-band cortical energy landscapes in healthy older adults, early-stage PD, and mid-stage PD during single- and dual-task conditions. Dual-task behavioral cost increased with disease severity for concurrent manual performance (p&#xa0;<&#xa0;0.001), whereas a quadratic pattern was observed for postural performance. Energy landscape analysis revealed severity-dependent reconfiguration of cortical beta dynamics. Dual-task-related landscape changes in effective network flexibility (&#x394;Neff), landscape geometry (&#x394;Evar and &#x394;Gmag), and dominant low-energy attractor organization (&#x394;Low mass and &#x394;Low area) showed significant monotonic trends (p&#xa0;<&#xa0;0.05), reflecting progressive constrained cortical network dynamics with advancing PD severity. In addition, dual-task-related landscape alterations were associated with clinical severity, as indexed by Hoehn and Yahr stage (|r|&#xa0;=&#xa0;0.353-0.423, p&#xa0;=&#xa0;0.016-0.048), and showed associations with motor impairment, as measured by MDS-UPDRS part III scores (|r|&#xa0;=&#xa0;0.333-0.455, p&#xa0;=&#xa0;0.009-0.063). These findings demonstrate that dual-task demands induce severity-dependent reconfiguration of cortical beta energy landscapes in PD. Energy landscape geometry may capture systems-level neural constraints associated with dual-task susceptibility in PD, providing a physiologically grounded framework to characterize disease-related functional vulnerability.

Humans

Cognitive-metabolic relationship in temporal lobe epilepsy: A systematic review.

OBJECTIVE: To summarize the current literature on neurometabolic dysfunction identified through brain imaging and its cognitive correlates in temporal lobe epilepsy (TLE). BACKGROUND: Cognitive decline contributes to chronic disability in TLE. The pathophysiology of cognitive decline in TLE is poorly understood, limiting therapeutic advances. Characterizing metabolic changes in patients with TLE and cognitive impairment may identify biomarkers and inform new treatment strategies. DESIGN/METHODS: We conducted a systematic review of five major databases, gathering studies published through December 2024, in accordance with PRISMA guidelines. We included all observational studies describing associations between metabolic imaging findings and cognitive measures in TLE. RESULTS: Of 1449 reports, 38 met the inclusion criteria, encompassing 1161 patients with TLE aged 5-66&#xa0;years. Twenty-two studies applied fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) to assess interictal brain glucose metabolism. Two studies utilized PET with other tracers to assess more specific metabolic aspects. Fourteen studies used proton magnetic resonance spectroscopy (1H-MRS) to quantify local concentrations of brain metabolites. Impairment of verbal memory was consistently associated with left temporal lobe metabolite changes. Non-memory cognitive impairments correlated with changes in glucose metabolism, N-acetylaspartate, and gamma-aminobutyrate in both temporal and extratemporal areas. CONCLUSION: 18F-FDG PET remains the most widely used imaging modality to assess cognitive-metabolic correlates in TLE, while other PET tracers and 1H-MRS are potentially underexplored. Verbal memory impairment correlates robustly with left temporal dysmetabolism. Cognitive impairment in TLE is multifaceted and correlates with measurable changes in metabolism in both temporal and extratemporal regions. While our synthesis was restricted by some methodological limitations, these neurometabolic signatures may hold promise as potential biomarkers for identifying risk of cognitive decline and highlight avenues for future research.

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

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans

The impact of artificial intelligence on critical thinking and clinical reasoning in health professions education: A systematic review and meta-analysis.

BACKGROUND: Critical thinking and clinical reasoning underpin healthcare professionals' ability to navigate uncertainties and deliver safe and effective care. With artificial intelligence (AI) advancement and growing adoption, AI-based educational tools are increasingly used to support these cognitive competencies' development. OBJECTIVE: To synthesize randomised and controlled clinical trials on AI-based educational tools in health professions education and examine their effects on critical thinking and clinical reasoning among health professions students. METHODS: Six electronic databases were searched from January 1, 2014 to July 28, 2025 was reviewed: PubMed, Cochrane Central Register of Controlled Trials, CINAHL, Scopus, Embase and Web of Science. Two independent reviewers performed data extraction and quality assessment using standardized JBI checklists. The GRADE approach was used to assess the certainty of evidence. Studies were pooled via random-effects meta-analyses or narrative syntheses. RESULTS: Fourteen randomised controlled trials and seven controlled clinical trials were included (n&#xa0;=&#xa0;21). Meta-analyses revealed small to medium effect sizes for the surrogate clinical reasoning outcomes of performance-based assessment scores (SMD 0.68; 95% CI [0.38, 0.98], p-value&#xa0;=&#xa0;0.00; I2&#xa0;=&#xa0;38%) and knowledge test scores (SMD 0.39; 95% CI [0.09, 0.69], p-value&#xa0;=&#xa0;0.01; I2&#xa0;=&#xa0;79%). Critical thinking and clinical reasoning skills and dispositions were narratively synthesized, with majority of included studies favouring AI-based interventions but the evidence had low to very low certainty. CONCLUSION: AI-based educational interventions may improve critical thinking and clinical reasoning among health profession students, but the evidence is very uncertain. This review offers preliminary insights but does not allow identification of optimal interventions or discipline-specific recommendations due to small sample sizes and substantial intervention heterogeneity. Further research is required to draw definitive conclusions. PROTOCOL REGISTRATION: CRD42025634074.

Humans