Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “interpretive description”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

243 records · Page 8Linked to original sources
PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗
PubMed2026

Symptoms of Anxiety in Adults with ADHD: A Systematic Review and Meta-Analysis of Case-Control Studies.

OBJECTIVE: Research suggests there is a higher prevalence of anxiety in individuals with ADHD compared to those without ADHD. However, estimated prevalence rates vary greatly due to differences in methodologies used across studies. This study is the first meta-analysis investigating differences in anxiety measure scores between adults with and without ADHD, and possible moderators of this effect. METHOD: Our analysis included 58 studies that compared anxiety scores in adults with/without ADHD (N = 18,821; k = 112). RESULTS: The average effect size (Hedges's g) of anxiety scores in those with ADHD relative to controls was 0.77 (SE = 0.066); a medium effect. The only significant moderator was the type of comparison group used, with comparisons to non-clinical control groups (g = 0.954, SE = 0.08) yielding significantly larger effects than comparisons to clinical control groups (g = 0.437, SE = 0.09). None of the other moderator variables examined (Method of characterising ADHD, Anxiety Measure Type, Anxiety Measure Focus, Age or Gender) moderated the effect. There was some evidence of publication bias, therefore results should be interpreted with this in mind. CONCLUSION: Overall, this study indicates that ADHD is associated with higher levels of anxiety symptomology. This has important implications in the diagnosis and treatment of individuals presenting with ADHD or anxiety, including the consideration and screening of each of these conditions as potentially co-occurring with the other. Adaptions made to clinical practice in line with this would better support this population, improve symptom management and overall quality of life. Suggestions for future research are discussed.

Humans↗
PubMed2026

Association between fruit and vegetable intake and risk of depression: A systematic review and meta-analysis of prospective cohort studies.

Depression is a leading cause of global disability, and identifying modifiable lifestyle factors is a public health priority. We conducted a systematic review and dose-response meta-analysis of prospective cohort studies examining the association between fruit and vegetable intake and incident depression. PubMed, Web of Science, Scopus, Embase, and Google Scholar were searched through November 2025. Data on study characteristics, dietary assessment, outcomes, effect estimates, and covariates were independently extracted by two reviewers. Random-effects models were used to calculate pooled relative risks (RRs), and linear and non-linear dose-response relationships were assessed. Heterogeneity was evaluated using I2, and evidence certainty was rated with GRADE. Thirteen cohorts with 385,449 participants and 26,592 depression cases were included. Highest versus lowest combined fruit and vegetable intake was associated with a 37% lower risk of depression (RR: 0.63; 95% CI: 0.50, 0.80). Each 200 g/day increase corresponded to a 16% risk reduction (RR: 0.84; 95% CI: 0.74-0.94). Separate analyses showed that fruit and vegetable intake reduced depression risk by 16% and 12%, respectively, with a non-linear dose-response for vegetables. These findings indicate that higher consumption of fruits and vegetables is associated with lower depression risk, supporting dietary strategies as a potential approach for mental health prevention. However, given the observational nature of the included studies, these results should be interpreted with caution, as residual confounding may partially account for the observed associations. Registration: This study was registered at PROSPERO (CRD420261279998).

Humans↗
PubMed2026

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

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

Volatile Organic Compounds↗
PubMed2026

Care navigation for older adults after stroke - A systematic review and meta-analyses to guide social prescribing.

INTRODUCTION: Stroke affects many older people worldwide, and patient navigation and social prescribing (e.g., care navigation) may help recovery. We aimed to synthesize evidence on the effect of care navigation for people living with the effects of a stroke (PLWS) on anxiety, depression, quality of life, and well-being. Our secondary focus was to explore these models in rural settings. METHODS: We conducted a systematic review following guidelines, and searched for peer-reviewed randomized controlled trials for older adults (60 years+ or group mean age in this range) who had a stroke and received patient navigation or social prescribing. Two authors independently screened citations at Level 1 (title and abstract) and Level 2 (full text). The date of the last updated search was December 5, 2025. We synthesized data quantitatively using meta-analyses (random effects model and standard mean difference). RESULTS: We identified 11 studies using patient navigation, but no social prescribing interventions. The total number of PLWS participants at baseline was 7829 with an average mean age of 68 years (43% women). There were no differences between groups for anxiety or quality of life for PLWS, but there was a difference favouring the intervention for depression, although the findings were no longer significant with sensitivity analyses. Thus, results should be interpreted with caution. Only two studies provided data for caregivers, with mixed findings. No studies focused on well-being or rural settings. CONCLUSIONS: Care navigation for PLWS needs more research, including testing social prescribing within stroke rehabilitation in rural and urban locations. SYSTEMATIC REVIEW REGISTRATION: PROSPERO 2025 CRD420251077958.

Aged↗
PubMed2026

Heterogeneity in Teriflunomide Treatment Arms: A Systematic Review and Meta‑Regression of Randomised Multiple Sclerosis Trials.

BACKGROUND: Teriflunomide is widely used as an active comparator in Phase 3 randomised trials for relapsing multiple sclerosis (RMS). Temporal changes in disease activity within teriflunomide-treated cohorts have not been systematically examined. OBJECTIVES: To assess temporal trends in relapse and disability outcomes across teriflunomide arms of Phase 3 multiple sclerosis (MS) trials and identify predictors of between-trial heterogeneity. METHODS: We performed a systematic review and meta-analysis of Phase 3 randomised controlled trials including a teriflunomide arm. PubMed, Scopus, and ClinicalTrials.gov were searched up to October 2025. Annualised relapse rate (ARR) and 12- and 24-week confirmed disability worsening (CDW) were extracted together with baseline characteristics. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. Random-effects meta-analyses, meta-regression, and sensitivity analyses were performed. RESULTS: Twelve teriflunomide cohorts from eight trials involving 4,900 adults with RMS were included. ARR ranged from 0.11 to 0.37 with substantial heterogeneity (I2 = 94%). Trial start year was inversely associated with ARR and explained a large proportion of between-study variability in exploratory meta-regression analyses. Confirmed disability worsening outcomes also showed substantial heterogeneity with a weaker trend toward lower event rates in more recent trials. CONCLUSION: Teriflunomide-treated trial populations have shifted toward lower relapse activity over time, and trial start year was the principal predictor of between-trial heterogeneity in ARR in exploratory analyses. These findings most plausibly reflect evolving recruitment and diagnostic practices rather than changes in drug efficacy. Accounting for these temporal dynamics is essential when interpreting outcomes from RMS trial using teriflunomide as comparator.

Humans↗
PubMed2026

The Statistical Fragility of Saline Nasal Irrigation for Rhinosinusitis: A Systematic Review.

OBJECTIVE: To assess the statistical fragility of randomized controlled trials (RCTs) evaluating high-volume saline nasal irrigation (SNI) for rhinosinusitis using fragility analysis. DATA SOURCES: PubMed, MEDLINE, and Embase were searched for RCTs published between May 1976 and January 2026. REVIEW METHODS: This study was reported as per PRISMA guidelines. RCTs that compared high-volume SNI to non-irrigation standard care for acute, recurrent, or chronic rhinosinusitis, and reported ≥ 1 dichotomous outcome, were included. Fragility index (FI), the minimum number of event reversals needed to alter statistical significance, and fragility quotient (FQ), FI normalized to sample size, were calculated for statistically significant dichotomous outcomes. Reverse FI (rFI) and reverse FQ (rFQ) were calculated for non-significant outcomes. RESULTS: Eight RCTs were included, yielding 38 dichotomous outcomes. Eight outcomes (21.1%) were statistically significant. The overall combined median FI was 5 (FQ 0.062), with similar FI values between significant and non-significant outcomes. In over one-fifth of outcomes, loss to follow-up exceeded FI. Analysis of principal dichotomous outcomes from studies demonstrated a median FI of 6 (FQ 0.092), with five of eight (62.5%) outcomes non-significant. CONCLUSION: RCTs evaluating SNI for rhinosinusitis exhibit moderate-to-high statistical fragility, with small outcome changes capable of reversing study conclusions. Because fragility analysis was limited to dichotomous outcomes while many primary endpoints were continuous, our findings should be interpreted as complementary rather than comprehensive appraisals of RCTs. Future RCTs with larger sample sizes, reduced bias, and pre-specified fragility considerations are needed to better define the clinical role of SNI.

Rhinosinusitis↗
PubMed2026

Comparative effectiveness and safety of pharmacological interventions for sleep outcomes in chronic non-cancer pain: a systematic review and network meta-analysis.

Sleep disturbances are highly prevalent among individuals with chronic non-cancer pain and are associated with worse pain severity and poorer prognosis. The comparative trade-offs between the effectiveness and safety of available pharmacotherapies for sleep outcomes in this population remain poorly defined. Ninety-eight RCTs involving 28,920 participants (mean age 53.2 years, 71.2% female) were included. Moderate-certainty evidence demonstrated that melatonin significantly improved sleep quality compared with placebo (standardized mean difference [SMD] = -0.60, 95%CI: -0.98, -0.22). Ten agents (e.g., amitriptyline, oxycodone, gabapentin, pregabalin, duloxetine) also showed statistically significant improvements in subjective sleep quality (SMD = -0.24 to -1.07), but most effects were supported by low-certainty evidence and were accompanied by an increased risk of adverse events (odds ratio [OR] = 1.90 to 37.00). Conversely, melatonin was not associated with an increased risk (OR = 0.88, 95%CI: 0.19, 3.94). Our findings indicate that melatonin shows promise as a safe, adjunctive option for improving sleep quality in this population, but larger, condition-specific trials are warranted to confirm these effects. Other pharmacological agents are limited by lower-certainty and unfavorable safety profiles. These results should be interpreted cautiously given limited direct comparisons, heterogeneous chronic pain populations, the high proportion of trials at high risk of bias, and the predominance of subjective sleep outcomes.

Humans↗
PubMed2026

Self-selected goals outperform assigned goals in reducing mobile phone usage: Evidence from a randomized controlled trial.

Excessive smartphone use is increasingly recognized as a public-health concern, yet scalable approaches to help individuals regulate daily use remain limited. We examine whether allowing individuals to self-select reduction goals improves behavioral and psychological outcomes when incentives and average goal levels are held constant across conditions. In a twelve-week randomized controlled trial, (N = 149; over 9000 person-day observations), participants were assigned to (i) a self-selected condition (choosing a 10%, 20%, or 30% reduction in daily phone use), (ii) an assigned condition (assigned a 14% reduction goal), or (iii) a no-goal control condition. Participants who selected their own goals reduced phone use by 26 min more per day (73% larger reduction) and achieved their goals 11 percentage points more often than those assigned goals, despite identical incentives and average goal levels. Reductions in phone use and higher goal achievement were associated with improvements in perceived addiction, depressive, and anxiety symptoms. These psychological outcomes were secondary endpoints. Although the between-group estimates generally followed the same directional pattern as the behavioral outcomes, the sample size for these analyses was limited and the between-group differences were not statistically significant. These findings should therefore be interpreted with caution. Overall, the results provide causal field evidence that self-selection under this goal-setting design can improve behavioral outcomes. Allowing individuals to choose their own goals may strengthen engagement and support healthier digital behavior. Incorporating opportunities for goal-selection may represent a simple addition to digital-health and public-health interventions aimed at helping individuals moderate smartphone use and improve well-being.

Humans↗
PubMed2026

An introductory practical guide to secondary data analysis in pediatric urology.

INTRODUCTION: Secondary data analysis (SDA) has become an increasingly important approach in pediatric urology, enabling the study of long-term outcomes, care variation, and disparities in populations with chronic or congenital urologic conditions. With the growing availability of large datasets, a structured approach to designing and conducting SDA studies is increasingly relevant. OBJECTIVES: To provide an introductory, practical guide to SDA in pediatric urology by (1) summarizing commonly used data sources with representative studies, (2) outlining a stepwise approach to designing and executing SDA studies, and (3) highlighting key methodological considerations, limitations, and opportunities for future work. STUDY DESIGN: Narrative review of existing literature and commonly used datasets relevant to pediatric urology, including administrative claims, hospital encounter databases, clinical registries, electronic health record networks, and population-based surveys. RESULTS: Data sources differ in scope, clinical granularity, longitudinal follow-up, and representativeness, and each is suited to specific research questions. We present a practical workflow for SDA, including dataset selection, cohort definition, and analytic planning. Linkage across datasets can provide a more comprehensive view of care patterns and outcomes, although feasibility is influenced by legal, technical, and data-quality constraints. DISCUSSION: SDA enables population-level analyses and the study of rare conditions that are challenging to evaluate through single-center or prospective designs. However, careful cohort definition, feasibility assessment, and awareness of data limitations are essential to ensure validity and interpretability. CONCLUSION: SDA provides a scalable, cost-efficient framework for generating meaningful evidence in pediatric urology. Continued efforts to harmonize data elements, improve linkage infrastructure, and support cross-institution collaboration will enhance the quality and impact of future research. This article provides a practical framework and examples to support the design and execution of SDA studies.

Humans↗
PubMed2026

The effects of visuomotor training and tDCS stimulation on visuomotor integration and visual processing: an electrophysiological approach.

BACKGROUND: Visuomotor integration coordinates visual and motor cortical activity to produce goal-directed responses and can be indexed by Rolandic Mu-rhythm suppression and visual evoked potential (VEP) P100 parameters. Perceptual-motor training improves visuomotor performance, and transcranial direct current stimulation (tDCS) over primary motor cortex (M1) has been reported to enhance motor learning when paired with training. This study examined whether anodal M1 tDCS augments the effects of Senaptec visuomotor training in healthy adults. METHODS: Sixty participants were randomized to active anodal tDCS (five 10-minute sessions, 1 mA; n = 31) or sham (n = 29) over M1 immediately before each Senaptec training session; 53 completed all sessions and post-testing. Outcomes were Mu-suppression ratios, VEP P100 latency and amplitude, and Senaptec measures of visual sensitivity and visuomotor control. RESULTS: Active tDCS produced no augmentation of any outcome, with no significant group × time interaction for any measure, consistent across composite and task-level analyses. Training alone produced no change in Mu suppression or visuomotor control. By contrast, both groups showed significant training-related gains in visual sensitivity, including near-far quickness and stereopsis, accompanied by shorter P100 latencies and larger amplitudes, indicating more efficient early visual processing. CONCLUSIONS: A clear dissociation emerged: training produced robust improvements in early visual processing, whereas neither tDCS nor training altered sensorimotor (Mu) or visuomotor-control measures. The tDCS results should be interpreted cautiously given the modest dose and limited power to detect small effects, rather than as evidence of inefficacy. Tablet-based perceptual training enhanced visual processing independent of neuromodulation.

Humans↗
PubMed2026

Medication safety in older adults in India: an integrative PhD synthesis of direct evidence and contextual implementation evidence.

BACKGROUND: Unsafe medication practices among older adults are an important global health concern, particularly in low- and middle-income countries where multimorbidity, fragmented care, self-medication, and informal healthcare provision intersect. OBJECTIVE(S): To synthesize direct evidence on medication safety among older adults in India and contextual evidence on deprescribing and community-level provider interventions relevant to safer medication use. METHODS: This PhD synthesis integrates four studies: a record-based cross-sectional study on polypharmacy and cardiovascular autonomic function in Kolkata; a six-city community study of 600 Indian older adults; a systematic review and meta-analysis on deprescribing preventive medications in frail or end-of-life older adults; and a systematic review of informal healthcare provider interventions in low- and middle-income countries. Studies I-II provided direct Indian older-adult evidence, while Studies III-IV provided indirect contextual evidence for their optimization and implementation. RESULTS: Polypharmacy was associated with higher anticholinergic burden and numerically higher cardiac autonomic neuropathy although residual confounding limits causal interpretation. In the multicity study, one-third had polypharmacy, while potentially inappropriate medications, prescribing omissions, and self-medication were common. Risks were higher with multimorbidity, recent hospitalization, care transitions, or living alone. Deprescribing showed no statistically significant increase in mortality, hospitalization, or major cardiovascular events, but heterogeneity was high and certainty low to very low. Informal-provider interventions showed the potential to improve knowledge, referral, case management, and medication-related practices. CONCLUSIONS: Medication safety among older adults in India requires an integrated continuum approach, but direct evidence supports only some components and implementation strategies that need prospective evaluation.

Humans↗
PubMed2026

Adolescents' Growing Sensitivity to Psychosocial Stressors: Evidence From Two Decades of Health Behaviour in School-aged Children (HBSC) Data in the Nordic Countries.

PURPOSE: We tested a perception-based explanation for rising psychosomatic complaints among adolescents in the Nordic countries. Specifically, we examined whether adolescents have become more sensitive to psychosocial stressors, reflected in stronger associations between stressors and psychosomatic complaints in 2022 than in 2002. METHODS: Data were drawn from the 2002 to 2022 waves of the Health Behaviour in School-aged Children survey among 15-year-olds in five Nordic countries (N = 7,263 in 2002 and 6,739 in 2022). Psychosomatic complaints were examined in relation to stressors in the following three domains: interpersonal relationships, school-related strain, and body- and activity-related factors. Moderated regression analyses tested whether associations between stressors and complaints differed between survey years. Sex and perceived family finances were included as covariates. RESULTS: Four of five psychosocial stressors showed stronger associations with psychosomatic complaints in 2022 than in 2002. Perceived poor family finances, although less prevalent in 2022, were more strongly related to complaints. Girls consistently reported higher levels of psychosomatic complaints, and the association between school pressure and complaints was stronger among girls. DISCUSSION: Although several psychosocial stressors declined in prevalence, their associations with psychosomatic complaints strengthened over time. These findings suggest that rising complaints may reflect changes in how psychosocial stressors are linked to adolescents' psychosomatic symptoms, rather than increases in exposure to those stressors. This shift highlights the importance of considering how adolescents interpret and respond to everyday stress when addressing population trends in mental health.

Humans↗
PubMed2026

Eating Experiences During Cancer Treatment in Adolescents and Young Adults: A Systematic Literature Review and Meta-Synthesis.

Adolescents and young adults (AYAs) aged 15-39 with cancer face distinct challenges during treatment, with eating consistently emerging as one of the most distressing and underrecognized concerns. At a critical life stage, AYAs must navigate illness-related consequences that profoundly affect well-being. Eating reflects these broader challenges and is identified as a key issue requiring health care attention. To address this, we synthesized evidence on AYAs' eating experiences and well-being during mealtime-related activities to inform health care practice. Qualitative and mixed-method studies were identified through searches across CINAHL, Embase, PubMed, Scopus, and Web of Science for studies published up to May 2025, supplemented by snowball searches. Of 3214 records, 74 full-text articles were reviewed, and 18 met the inclusion criteria. These represented 302 AYAs, 73 relatives, and 88 health care professionals. Studies were analyzed using Joanna Briggs Institute review methods and GRADE-CERQual to support clinical interpretability. The meta-synthesis identified one core theme: "Eating as an embodied struggle and act of agency," with three subthemes: (a) living through physical and sensory disruption, (b) carrying the weight of new emotions and shifting relations, and (c) finding ways through gaps in support. Eating emerged as a disrupted, emotionally charged, yet agentic act requiring sensitive, individualized approaches. Thirteen evidence-informed recommendations were developed to guide clinical application. These emphasize early nutritional screening, dietetic support, flexible meal options, respectful family involvement, and psychosocially attuned care. Future research should codevelop and evaluate tailored interventions that address AYAs' embodied, emotional, and social needs to improve eating-related quality of life during cancer treatment.

Humans↗
PubMed2026

Effect of transcutaneous auricular vagus nerve stimulation on postoperative pain in patients undergoing thoracoscopic partial lung resection: a randomized, double-blind, controlled clinical trial.

BACKGROUND: Postoperative pain after thoracic surgery remains common and challenging. Transcutaneous auricular vagus nerve stimulation (taVNS) is a noninvasive neuromodulation technique with potential analgesic effects. This study aimed to evaluate the efficacy and safety of taVNS for postoperative pain management in patients undergoing thoracoscopic partial lung resection. METHODS: Adults undergoing thoracoscopic partial lung resection were randomized to active or sham taVNS. The primary outcome was cough pain intensity at 48h post-surgery, assessed by Numeric Rating Scale (NRS). Secondary outcomes included cough pain at 24h and 72h, resting pain, moderate-to-severe pain incidence,&#xa0;opioid consumption, quality of recovery, postoperative pulmonary complications , chest tube duration, hospital stay, postoperative nausea/vomiting, and adverse events. RESULTS: Among 119 analyzed patients (active n&#x2009;=&#x2009;60, sham n&#x2009;=&#x2009;59), active taVNS reduced cough pain scores at 24h, 48h, and 72h postoperatively, as well as resting pain (p < 0.05). It also lowered the incidence of moderate-to-severe cough pain at 24h and 48h, reduced cumulative postoperative opioid use at 24h and 72h, and decreased rescue analgesia on postoperative day 3 (p < 0.05). Active taVNS was associated with a lower incidence of postoperative pneumothorax (p < 0.05). No serious adverse events occurred. CONCLUSION: Perioperative taVNS was associated with a modest analgesic benefit and reduced postoperative opioid requirements after thoracoscopic partial lung resection. The observed reduction in postoperative pneumothorax requires cautious interpretation, and further multicenter trials are needed to determine its clinical utility.

Humans↗
PubMed2026

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↗
PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗
PubMed2026

Measurement of low-density lipoprotein cholesterol and other circulating lipids in Brazil: a systematic literature review.

Accurate laboratory assessment of circulating lipids underpins cardiovascular risk stratification, yet clinical interpretation depends not only on the assays but on the formula chosen to estimate low-density lipoprotein cholesterol (LDL-C). This review integrates the 2019-2025 evidence on laboratory methods for triglycerides (TG), total cholesterol (TC), and high-density lipoprotein cholesterol (HDLC), and on the formulas estimating LDL-C, VLDL-C, and non-HDL cholesterol, to determine how these should be measured, reported, and harmonized in Brazil, where lipid thresholds are adapted from international consensus. A PRISMA 2020 systematic search (PROSPERO CRD420251241064) of PubMed/MEDLINE, Scopus, SciELO, LILACS, Web of Science, and Embase retrieved 57,915 records; after removing 38,210 duplicates, 19,705 titles/abstracts were screened, 312 full texts assessed, and 25 sources included. Enzymatic colorimetric assays remain standard for TG, TC, and HDLC. For LDL-C, Martin/Hopkins classifies more accurately than Friedewald (89.6% vs 83.2% correct categorization in 5,051,467 patients), particularly at high TG and low LDL-C, while Sampson/NIH and modified Sampson/NIH extend reliable estimation into hypertriglyceridemia and very low LDL-C; direct measurement is reserved for TG beyond the validated range. Although the review centers on the Friedewald, Martin/Hopkins, and Sampson/NIH families that dominate guideline practice, other published equations exist and are addressed in context. In Brazil, atherogenic-lipid thresholds are risk-based decision limits rather than reference intervals; national surveys describe lipid distributions but were not designed to establish them. Analytical standardization through traceability programs, multicenter validation of formulas, and-where the distribution-based construct applies (HDLC, pediatrics)-nationally derived reference intervals are priorities for equitable cardiovascular risk assessment in Brazil.

Humans↗