Standard Methodology Research Articles

Probiotics in Depression Management: Efficacy, Mechanisms and Future Directions

Depression affects approximately 280 million people worldwide, representing a significant public health burden. It is characterized by persistent sadness, anhedonia, fatigue, sleep disturbances, cognitive dysfunction, and in severe cases, suicidal ideation. The pathophysiology is often attributed to neurotransmitter imbalances, hypothalamic-pituitary-adrenal (HPA) axis dysfunction, and inflammation. Recently, the gut-brain axis has garnered attention for its role in mood regulation, suggesting that probiotic supplementation may influence depressive symptoms through gut microbiome modulation. Therefore, this review examines recent findings and research gaps regarding the efficacy of probiotics in managing clinically diagnosed depression. Emerging research demonstrates that daily probiotic supplementation from 3×109 CFU to 9×1011 CFU for four to eight weeks in combination with antidepressants is effective in improving depressive symptoms. Effective formulations commonly included Bifidobacteria, Lactobacilli, Lactococcus lactis, and Streptococcus thermophilus. Nevertheless, significant gaps remain, particularly concerning the mechanistic pathways, comparative effectiveness, and impact across different demographics of the probiotics. Furthermore, the long-term effects of probiotic use with antidepressants, their role in reducing antidepressant side effects, and combined effects with psychotherapy are largely understudied. Addressing these gaps through standardized methodologies will enhance evaluations of probiotic strains to optimize microbiome-based treatment regimens, and ultimately improve mental health outcomes in depression management. Graphical abstract. Summary of research gaps and future directions to determine the efficacy of probiotics in diagnosed depression.

Analysis of Human Resources Assessment in Laboratories of Public Health Organizations Bishkek

This article provides information on the importance of laboratory services for the effective treatment process of patients. At the same time, assessing the human resources potential of laboratory services remains currently an urgent task, the solution of which requires a standardized approach and methodology. To address this issue, documents have been developed that provide guidance for assessing the human resources used to assess the public health laboratory system.

Emerging and Persistent Contaminants in a Remote Coastal Stream System: Five Priority Compounds in Southeast Asia

This study is a preliminary assessment of the emerging and persistent contaminants (EPCs) in the ecologically sensitive Kamphuan Stream in Southern Thailand. The analysis of 15 compounds revealed that EPC concentrations below the main community were significantly elevated during the rainy season, with the highest levels found for sucralose (9070 ng/L), metformin (6250 ng/L), fexofenadine (5110 ng/L), and gabapentin (3060 ng/L). These spatiotemporal patterns highlight the episodic nature of contamination driven by urban stormwater runoff, where rainfall events create temporary pathways that transport EPCs to streams draining into coastal ecosystems. Maximum concentrations of three pharmaceuticals (diclofenac, gemfibrozil, and ibuprofen), as well as sucralose, caffeine, and fenobucarb, exceeded the general predicted no-effect concentrations (PNECs) for marine or fresh waters; however, these concentrations were not persistent. Limited sampling across three campaigns constrained the ability to fully characterize the dynamics of this issue through statistical inference. Furthermore, risk assessments were constrained by the absence of locally derived PNECs for tropical ecosystems and organisms, along with limited standardization in PNEC determination methodologies, making definitive conclusions challenging. A comparative analysis of five priority compounds (diclofenac, gemfibrozil, metformin, naproxen, and fluoxetine) against existing data from East and Southeast Asia underscores the need for further research in Southeast Asia to evaluate the ecological risks posed by EPCs across diverse rivers and streams. Future studies should focus on the contaminants of greatest ecological importance, investigate their transformation products, identify sources and transport pathways, and assess their environmental risks to aquatic ecosystems.

What’s beyond the core? Database coverage in qualitative information reveal

Objective: This study investigates the effectiveness of bibliographic databases to retrieve qualitative studies for use in systematic and rapid reviews in Health Technology Assessment (HTA) research. Qualitative research is becoming more prevalent in reviews and health technology assessment, but standardized search methodologies—particularly regarding database selection—are still in development. Methods: To determine how commonly used databases (MEDLINE, CINAHL, PsycINFO, Scopus, and Web of Science) perform, a comprehensive list of relevant journal titles was compiled using InCites Journal Citation Reports and validated by qualitative researchers at Canada’s Drug Agency (formerly CADTH). This list was used to evaluate the qualitative holdings of each database, by calculating the percentage of total titles held in each database, as well as the number of unique titles per database. Results: While publications on qualitative search methodology generally recommend subject-specific health databases including MEDLINE, CINAHL, and PsycINFO, this study found that multidisciplinary citation indexes Scopus and Web of Science Core Collection not only had the highest percentages of total titles held, but also a higher number of unique titles. Conclusions: These indexes have potential utility in qualitative search strategies, if only for supplementing other database searches with unique records. This potential was investigated via tests on qualitative rapid review search strategies translated to Scopus to determine how the index may contribute relevant literature.

Recent advances in electrochemical sensing and remediation technologies for ciprofloxacin.

Ciprofloxacin (CIP) is an extensively used broad-spectrum, fluoroquinolone antibiotic used for treating diverse bacterial infections. Effluent treatment plants (ETPs) worldwide lack technologies to detect or remediate antibiotics. CIP reaches the aquatic phase primarily due to inappropriate disposal practices, lack of point-of-use sensing, and preloaded activated charcoal filter at ETPs. The co-existence of bacteria and CIP in such aqueous pools has promoted fluoroquinolone resistance in bacteria and should be minimized. The worldwide accepted standard detection methodologies for the detection of CIP are high-performance liquid chromatography and mass spectrometry, which are lab-based, require state-of-the-art equipment, and are expensive. Hence, it is difficult to integrate them for on-site monitoring. Further, the current remediation technologies like conventional sludge-treatment techniques fail to remove antibiotics such as CIP. Several point-of-use technologies for the detection of CIP are being investigated. These typically involve the development of electrochemical sensors where substrates, modifiers, biorecognition elements, and their chemistries are designed and optimized to enable robust, point-of-use detection of CIP. Similarly, remediation techniques like adsorption, membrane filtration, ion exchange, photocatalysis, ozonation, oxidation by Fenton's reagent, and bioremediation are explored, but their onsite use is limited. The use of these sensing and remediation technologies in tandem is possibly the only way the issues related to antimicrobial resistance may be effectively tackled. This article provides a focused critical review on the recent advances in the development of such technologies, laying out the prospects and perspectives of their synergistic use to curb the menace of AMR and preserve antibiotics.

Foodborne Event Detection Based on Social Media Mining: A Systematic Review

Foodborne illnesses represent a significant global health challenge, causing substantial morbidity and mortality. Conventional surveillance methods, such as laboratory-based reporting and physician notifications, often fail to enable early detection, prompting the exploration of innovative solutions. Social media platforms, combined with machine learning (ML), offer new opportunities for real-time monitoring and outbreak analysis. This systematic review evaluated the role of social networks in detecting and managing foodborne illnesses, particularly through the use of ML techniques to identify unreported events and enhance outbreak response. This review analyzed studies published up to December 2024 that utilized social media data and data mining to predict and prevent foodborne diseases. A comprehensive search was conducted across PubMed, EMBASE, CINAHL, Arxiv, Scopus, and Web of Science databases, excluding clinical trials, case reports, and reviews. Two independent reviewers screened studies using Covidence, with a third resolving conflicts. Study variables included social media platforms, ML techniques (shallow and deep learning), and model performance, with a risk of bias assessed using the PROBAST tool. The results highlighted Twitter and Yelp as primary data sources, with shallow learning models dominating the field. Many studies were identified as having high or unclear risk of bias. This review underscored the potential of social media and ML in foodborne disease surveillance and emphasizes the need for standardized methodologies and further exploration of deep learning models.

Emotion recognition deficits in children and adolescents with autism spectrum disorder: a comprehensive meta-analysis of accuracy and response time

BackgroundAutism spectrum disorder is a neurodevelopmental condition characterized by persistent challenges in social communication and restricted, repetitive behaviors. Emotion recognition deficits are a core feature of ASD, impairing social functioning and quality of life. This meta-analysis evaluates emotion recognition accuracy and response time in individuals with autism spectrum disorder compared to neurotypical individuals and those with other neurodevelopmental disorders.MethodsThis systematic review with a meta-analysis was conducted following PRISMA guidelines. A comprehensive literature search across PubMed, Scopus, Cochrane Library, and Web of Science identified 13 studies published between 2006 and 2024. Data on emotion recognition accuracy and response times were synthesized using standardized mean differences in random-effects models. Heterogeneity was assessed using the I2 statistic, and sensitivity analyses were performed to ensure robustness.ResultsIndividuals with ASD exhibited significantly lower overall emotion recognition accuracy compared to TD individuals (SMD = −1.29, 95% CI: −2.20 to −0.39, p < 0.01) and NDDs (SMD = −0.89, 95% CI: −1.23 to −0.55, p = 0.02). Response times were significantly prolonged in ASD compared to TD individuals (SMD = 0.50, 95% CI: 0.36–0.63, p < 0.01) but not when compared to NDDs. Emotion-specific analyses did not consistently reveal significant differences across emotions (fear, anger, happiness, sadness, disgust, surprise), with substantial heterogeneity observed across studies (I2 > 50%).ConclusionsThis systematic review with a meta-analysis highlights significant impairments in emotion recognition accuracy and processing speed among individuals with autism spectrum disorder, particularly compared to neurotypical individuals. These findings underscore the importance of developing targeted interventions to address these deficits, which are foundational to improving social cognition and quality of life in autism spectrum disorder. Future research should prioritize standardized methodologies and explore cultural and contextual factors influencing emotion recognition abilities.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=627339, PROSPERO (CRD42024627339).

Global and Regional Trends in Paediatric Neuroblastoma Incidence and Mortality, 1990-2021: An Inequality and Projection Analysis.

Neuroblastoma stands as the most prevalent extracranial solid tumour in children, yet its epidemiological profile on global, regional, and national scales remains insufficiently explored. Long-term trends in the incidence and mortality of paediatric neuroblastoma from 1990 to 2021 were analysed globally, regionally, and nationally using estimated annual percentage changes. Cross-national disparities in the burden of paediatric neuroblastoma were quantified through standard health equity methodologies, with projections of burden shifts extending to 2035. From 1990 to 2021, the global age-standardised death rate for paediatric neuroblastoma increased from 0.19 (95% UI, 0.16-0.23) to 0.21 (95% UI, 0.14-0.28) per 100 000 population, with an EAPC of 0.2. Regionally, both mortality and incidence rates were highest in low-middle SDI regions and lowest in Oceania. Mortality rates were highest among males aged 12-23 months and females aged 6-11 months, while incidence rates were most pronounced in children aged 2-4 years. Cross-country inequality analyses indicated a reduction in disparities between high and low SDI countries; however, the concentration index revealed an increase in the inequality of burden distribution. The global burden of paediatric neuroblastoma is projected to continue rising through 2035. Over the past 30 years, global incidence and mortality rates for paediatric neuroblastoma have risen, particularly in low-SDI regions, whereas high-SDI regions have witnessed a downward trend. Although disparities between high- and low-SDI countries have diminished, inequality in burden distribution has grown more pronounced. The global burden of paediatric neuroblastoma is expected to continue its upward trajectory over the next 15 years.

Sublethal and lethal toxicity assessment of lanthanum and gadolinium to Daphnia magna in a 7-day test method.

The use of rare earth elements has increased in recent years, leading to a rise in environmental concentrations. Despite the growth in number of studies regarding toxicity, knowledge gaps remain. For Daphnia magna, standardized test methods involve exposure periods of either 48 h or 21 days to assess toxicological effects. In this study, the exposure period was adjusted to 7 days to evaluate sublethal endpoints not measurable in 48-h tests. Additionally, this approach enabled us to obtain results within a shorter time frame than that required for 21-day tests. This study focused on the individual toxicity of lanthanum (La) and gadolinium (Gd) to Daphnia magna. We assessed mortality, feeding rate, somatic growth, and maturity under static conditions, modifying the media by adding MOPS buffer to maintain an initial pH of 6.8 and providing Raphidocelis subcapitata as a daily food source. Results showed that the solubility of La decreased considerably, with the highest recovery rate dropping from 133.33% at the start to 32.73% by the end of the 7-day exposure period. In contrast, Gd solubility remained stable, with a recovery rate of 86.88% at the start and 81.30% at the end of the test. Daily lethal concentrations (LCx) were calculated, revealing LC10 values on the first day, LC20 on the second day, and LC50 by the third day for La and the second day for Gd. By the test's end, the LC10, LC20, and LC50 values were 30.40, 78.96, and 403.67 µg L-1 for La, and 10.67, 33.73, and 241.28 µg L-1 for Gd. For the sublethal endpoints, maturity was the most sensitive endpoint with the EC20 and EC10 corresponding to 0.79 and 0.26 µg L-1 for La and 0.39 and 0.14 µg L-1 for Gd. Gd had a higher toxicity in all endpoints assessed. While a thorough comparison to existing literature remains challenging due to variations in endpoints assessed, the methodology employed in this study yielded a range of informative results. This approach provides a useful range-finding test for Daphnia magna toxicity assessments, particularly for preliminary screening, and may complement standardized methodologies.

The burden of headache disorders among medical students in Vietnam: estimates from a cross-sectional study with a health-care needs assessment

BackgroundIn our previous study, we demonstrated that headaches are highly prevalent among medical students in Vietnam. In the present study, we provide estimates of the associated symptom burden and impaired participation, utilizing these estimates to assess headache-related healthcare needs within this population.MethodsThe study followed the standardized methodology established by the Global Campaign against Headache. Participants included medical students who were randomly selected from two medical universities in Vietnam. Data collection utilized the HARDSHIP questionnaire, which included diagnostic questions based on ICHD-3 criteria, measures of symptom burden, quality of life (QoL) assessments using the WHOQoL-8, evaluations of impaired participation through the HALT index, and questions about headache yesterday (HY). The definition of health care “need” was based on the likelihood of benefit from intervention, including all participants with probable medication-overuse headache (pMOH), other headaches occurring on ≥ 15 days/month (H15+), migraine on ≥ 3 days/month, or migraine or tension-type headache (TTH) meeting at least one of two criteria related to symptom burden and impaired participation.ResultsA total of 1,362 participants (57.3% female) were included, of whom 1,125 students (61.3% female) were diagnosed with a headache disorder, and 165 students (69.1% female) reported experiencing a HY. The mean frequency of any headache was 3.6 days per month, with an average duration of 5.3 h, and 58% of participants reported an intensity of moderate/severe. For all headache, the mean pTIS was 2.8%. The mean number of lost days over a period of 3 months was 4.3 for work/school tasks, 3.8 for household chore, and 1.7 for social or leisure activities. Among those reporting a HY, 35.8% were able to complete less than half of their expected activities, while 9.7% could complete none. QoL of students with any headache was significantly lower than that of students without headache. A mong students with headache, 43.8% fulfilled atleast one of our needs assessment criteria.ConclusionsThis first study on headache burden in Vietnam reveals substantial symptom burden alongside a correspondingly high level of impaired participation among medical students.

Comprehensive Approach for Sequential MALDI-MSI Analysis of Lipids, N-Glycans, and Peptides in Fresh-Frozen Rodent Brain Tissues.

Multiomics analysis of single tissue sections using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) provides comprehensive molecular insights. However, optimizing tissue sample preparation for MALDI-MSI to achieve high sensitivity and reproducibility for various biomolecules, such as lipids, N-glycans, and tryptic peptides, presents a significant challenge. This study introduces a robust and reproducible protocol for the comprehensive sequential analysis of the latter molecules using MALDI-MSI in fresh-frozen rodent brain tissue samples. The optimization process involved testing multiple organic solvents, which identified serial washing in ice-cold methanol, followed by chloroform as optimal for N-glycan analysis. Integrating this optimized protocol into MALDI-MSI workflows enabled comprehensive sequential analysis of lipids (in dual polarity mode), N-glycans, and tryptic peptides within the same tissue sections, enhancing both the efficiency and reliability. Validation across diverse rodent brain tissue samples confirmed the protocol's robustness and versatility. The optimized methodology was subsequently applied to a transgenic Alzheimer's disease (AD) mouse model (tgArcSwe) as a proof of concept. In the AD model, significant molecular alterations were observed in various sphingolipid and glycerophospholipid species, as well as in biantennary and GlcNAc-bisecting N-glycans, particularly in the cerebral cortex. These region-specific alterations are potentially associated with amyloid-beta (Aβ) plaque accumulation, which may contribute to cognitive and memory impairments. The proposed standardized methodology represents a significant advancement in neurobiological research, providing valuable insights into disease mechanisms and laying the foundation for potential preclinical applications. It could aid the development of diagnostic biomarkers and targeted therapies for AD and other neurodegenerative diseases, such as Parkinson's disease.

Protocol for the development of a guideline on post-extubation respiratory support for mechanically ventilated patients in the ICU

Prophylactic respiratory support for patients after extubation is effective in improving their outcomes and prognosis. However, the optimal post-extubation respiratory support for different populations and disease types of mechanically ventilated...

A Systematic Review Of Blue Carbon Potential in Coastal Marshlands: Opportunities For Climate Change Mitigation And Ecosystem Resilience

This systematic review evaluates the blue carbon potential of coastal marshlands, emphasizing their role in climate change mitigation, ecosystem service provision, and economic value within climate finance mechanisms. Drawing on a comprehensive analysis of 198 peer-reviewed articles, this study synthesizes findings on the carbon sequestration dynamics of coastal marshlands, their contributions to biodiversity support, and their capacity to enhance coastal resilience through flood protection and water quality improvement. The review highlights the threats posed by land-use changes, urbanization, and climate change impacts such as sea-level rise and saltwater intrusion, which collectively undermine the ecological integrity and service delivery of these critical ecosystems. It further explores the integration of coastal marshlands into climate finance mechanisms, demonstrating their viability as natural assets within carbon markets and payment for ecosystem services schemes, with restoration projects yielding returns of $7 to $15 for every dollar invested. Despite these advancements, significant knowledge gaps remain, particularly in the standardization of methodologies for quantifying carbon dynamics and the socio-economic benefits of conservation, which limit the scalability of these efforts. By addressing these challenges, this study underscores the necessity of interdisciplinary approaches, robust policy frameworks, and sustained research to maximize the potential of coastal marshlands as a cornerstone of nature-based solutions for climate mitigation and sustainable development.

The Costs of a Multisectoral Nutrition Program Implemented Through a Poultry Value Chain Platform in Burkina Faso

ABSTRACTUndernutrition in women and young children in Burkina Faso is a critical problem. Egg consumption is low despite many households raising poultry. The Soutenir l'Exploitation Familiale pour Lancer l'Élevage des Volailles et Valoriser l'Économie Rurale (SELEVER) project, an integrated agriculture‐nutrition intervention, promoted egg consumption and sales to investigate the impact of poultry production on child nutrition. Multisectoral nutrition‐sensitive agriculture programs address nutrition deficits but lack comparable cost information. This study estimates the costs of the SELEVER program, an integrated poultry and nutrition intervention. The study estimates the program's economic costs using a standardized methodology from the Strengthening Economic Evaluation for Multisectoral Strategies for Nutrition (SEEMS‐Nutrition) consortium, which aligns financial and economic costs along program impact pathways, allocating costs by activities and inputs. We conducted qualitative interviews and focus groups on time allocation and beneficiary out‐of‐pocket costs. Incremental economic costs were calculated by combining expenditures and economic costs. The total incremental program cost was USD$18,084,727.68 over 5 years, with annual incremental costs of USD$209.20 per direct beneficiary and $796.26 per household. Major cost drivers included overhead (18%), poultry extension (17%), training (16%), household counseling (7%), technical assistance (7%) and microcredit (6%). Total input costs were dominated by personnel (51%), supplies (13%), agricultural inputs (10%) and overhead (9%). We present the total incremental costs of a multisectoral nutrition intervention to generate revenue with poultry. The costs per beneficiary were higher than similar interventions, underscoring the need for cost‐effectiveness evaluations of multisectoral nutrition programs. A standardized cost methodology facilitates comparisons with multisectoral nutrition interventions and builds the evidence base.

Methodologies for Mitochondrial Omic Profiling During Spaceflight.

To be able to understand how spaceflight can affect human biology, there is a need for maximizing the amount of information that can be obtained from experiments flown to space. Recently there has been an influx of data obtained from astronauts through multi-omics approaches based on both governmental and commercial spaceflight missions. In addition to data from humans, mitochondrial specific data is gathered for other experiments from rodents and other organisms that are flown in space. This data has started to universally demonstrate that mitochondrial dysfunction is the key regulator associated with increasing health risks associated with spaceflight. This mitochondrial dysfunction can have influence downstream on immune suppression, inflammation, circadian rhythm issues, and more. Due to the space environment, standard methodologies have to be altered for performing mitochondrial specific analysis and in general sample collection for omics. To perform mitochondrial specific analysis and data collection from samples flown to space we will outline the current sample collection methods, processing of the samples, and specific analysis. Specifically we will highlight the different mitochondrial methodologies and challenges involved with research associated with spaceflight.

Design and implementation of a stakeholder consultation process for rapid health technology assessments in Argentina

IntroductionHealth technology assessment (HTA) is a standardized methodology that allows the assessment technologies’ value. By incorporating the perspective of stakeholders in a public consultation process, transparency and quality of decisions can be improved. ObjectiveTo describe the active stakeholder consultation process for rapid HTAs in an Argentinean, independent, academic, non-profit HTA agency, assessing its initial five years. MethodsSince 2017, we have been conducting an active public consultation process for rapid HTA documents, inviting producers, healthcare professionals, and patient organizations to provide comments, and their input may lead to changes in the HTA documents. Changes were classified as major (changes to the coverage recommendation), intermediate (changes in efficacy, net benefit, or cost-effectiveness that did not change coverage recommendations), and minor modifications (other changes). ResultsFrom May 2017–August 2022, 308 rapid HTA (rHTA) reports were published, and 3,438 invitations were sent. 140 rHTA (45.5%) received a total of 228 comments. Comments came from producers in 53% (n = 112) and healthcare professional organizations in 31.2% (n = 66). Technologies evaluated were drugs in 37% (n = 114), procedures in 35.5% (n = 109), diagnostic methods in 15.3% (n = 47), and devices in 12.2% (n = 38). Out of 308 rHTA documents, 120 (39%) were modified—mostly minor adjustments (n = 100; 80%), followed by major (n = 12; 10%) and intermediate modifications (n = 8; 6.4%). ConclusionImplementing an active stakeholder involvement process in HTA is feasible in a low- to middle-income country context and strengthens and improves the HTA process.

Efficacy of platelet-rich plasma injection for pain relief in injured athletes: a systematic review of randomized controlled trials.

Sports injuries involving bi-articular muscles like the hip flexors, hamstrings, quadriceps, and gastrocnemius significantly affect athletes' performance and quality of life. Comprehensive rehabilitation is crucial for a pain-free return to play (RTP). Over the past 15 years, platelet-rich plasma (PRP) has emerged for its potential in tissue regeneration. However, the effects in pain relief and early RTP remained debated. This systematic review of randomized controlled trials (RCTs) aimed to evaluate the efficacy of PRP in pain management for injured athletes. A systematic review searched on PubMed, Scopus, and Web of Science for randomized controlled trials (RCTs) on PRP injections in injured athletes up to May 28, 2024. Studies had to meet the following population, intervention, control and outcome (PICO) criteria: professional athletes treated with leukocyte-rich or leukocyte-poor PRP versus other treatments, with pain measured by visual analogue scale (VAS), numeric rating scale (NRS), or verbal rating scale (VRS) scales. Systematic review registered on PROSPERO (CRD42024552342). Out of total of 1675 articles, we included seven RCTs on PRP treatment for muscle injuries and tendinopathies in athletes. Two studies on hamstring injuries had conflicting results on PRP's efficacy; two studies on different muscles showed significant pain relief and quicker recovery with ultrasound-guided PRP, limited by small sample sizes and lack of double-blind protocols. For tendinopathies, an anterior cruciate ligament reconstruction study with autologous bone-patellar tendon-bone grafts showed significant pain improvements but had a small sample size. Another study on patellar tendinopathy found no PRP benefits over placebo. A third study found long-term improvement with PRP over shockwave therapy for patellar tendinitis, despite design limitations. This systematic review suggested that PRP might aid in pain management for athletes, but high-quality evidence is lacking. Further research with standardized methodologies is needed to confirm the PRP efficacy, which could complement multidisciplinary rehabilitation.

Benefits and harms associated with the use of AI-related algorithmic decision-making systems by healthcare professionals: a systematic review

Despite notable advancements in artificial intelligence (AI) that enable complex systems to perform certain tasks more accurately than medical experts, the impact on patient-relevant outcomes remains uncertain. To address this gap, this systematic review assesses the benefits and harms associated with AI-related algorithmic decision-making (ADM) systems used by healthcare professionals, compared to standard care. In accordance with the PRISMA guidelines, we included interventional and observational studies published as peer-reviewed full-text articles that met the following criteria: human patients; interventions involving algorithmic decision-making systems, developed with and/or utilizing machine learning (ML); and outcomes describing patient-relevant benefits and harms that directly affect health and quality of life, such as mortality and morbidity. Studies that did not undergo preregistration, lacked a standard-of-care control, or pertained to systems that assist in the execution of actions (e.g., in robotics) were excluded. We searched MEDLINE, EMBASE, IEEE Xplore, and Google Scholar for studies published in the past decade up to 31 March 2024. We assessed risk of bias using Cochrane's RoB 2 and ROBINS-I tools, and reporting transparency with CONSORT-AI and TRIPOD-AI. Two researchers independently managed the processes and resolved conflicts through discussion. This review has been registered with PROSPERO (CRD42023412156) and the study protocol has been published. Out of 2,582 records identified after deduplication, 18 randomized controlled trials (RCTs) and one cohort study met the inclusion criteria, covering specialties such as psychiatry, oncology, and internal medicine. Collectively, the studies included a median of 243 patients (IQR 124-828), with a median of 50.5% female participants (range 12.5-79.0, IQR 43.6-53.6) across intervention and control groups. Four studies were classified as having low risk of bias, seven showed some concerns, and another seven were assessed as having high or serious risk of bias. Reporting transparency varied considerably: six studies showed high compliance, four moderate, and five low compliance with CONSORT-AI or TRIPOD-AI. Twelve studies (63%) reported patient-relevant benefits. Of those with low risk of bias, interventions reduced length of stay in hospital and intensive care unit (10.3 vs. 13.0 days, p=0.042; 6.3 vs. 8.4 days, p=0.030), in-hospital mortality (9.0% vs. 21.3%, p=0.018), and depression symptoms in non-complex cases (45.1% vs. 52.3%, p=0.03). However, harms were frequently underreported, with only eight studies (42%) documenting adverse events. No study reported an increase in adverse events as a result of the interventions. The current evidence on AI-related ADM systems provides limited insights into patient-relevant outcomes. Our findings underscore the essential need for rigorous evaluations of clinical benefits, reinforced compliance with methodological standards, and balanced consideration of both benefits and harms to ensure meaningful integration into healthcare practice. This study did not receive any funding.

EEG Microstates in the Study of Attention-Deficit Hyperactivity Disorder: A Review of Preliminary Evidence.

Attention-deficit hyperactivity disorder (ADHD) is a neurobiological condition that affects both children and adults. Microstate (MS) analyses, a data-driven approach that identifies stable patterns in EEG signals, offer valuable insights into the neurophysiological characteristics of ADHD. This review summarizes findings from 13 studies that applied MS analyses to resting-state and task-based brain activity in individuals with ADHD. Relevant research articles were retrieved from electronic databases, including PubMed, Google Scholar, Web of Science, PsychInfo, and Scopus. The reviewed studies applied MS analyses to explore brain activity differences in ADHD populations. Resting-state studies consistently reported alterations in MS organization, with increased duration (MS-D) and changes in temporal dynamics (MS-C), potentially reflecting executive dysfunctions and delayed maturation of the default mode network. Additionally, MS B demonstrated promise in distinguishing between ADHD subtypes based on differences in visual network function. Task-based and event-related potential (ERP) studies, using paradigms like the continuous performance task (CPT) or Go-NoGo Task, identified MS abnormalities (i.e., N2, P2, P3, CNV) linked to inhibition and attentional resource allocation. Preliminary evidence suggests that MS analyses hold potential for distinguishing individuals with ADHD from control groups. The integration of machine learning techniques holds promise for improving diagnostic accuracy and identifying ADHD subtypes, while MS analyses may also help monitor the effects of stimulant medications like methylphenidate by tracking neurophysiological changes. However, this review highlights the need for more standardized methodologies to enhance the generalizability and replicability of findings. These efforts will ultimately contribute to a deeper understanding of the neurobiological mechanisms that underlie ADHD.

A Survey of the Relationship Between Dietary Quality and Metabolic Syndrome

Background: Dietary intake is increasingly recognized as a pivotal factor in the etiology of metabolic syndrome. A substantial body of evidence suggests a discernible correlation between dietary quality indices and the occurrence of metabolic syndrome. Objective: This survey seeks to rigorously evaluate the impact of diet quality indices and demographic variables on the manifestation of metabolic syndrome. Materials and Methods: This case-control study encompassed 175 individuals diagnosed with metabolic syndrome and an equal number of age-matched healthy counterparts (Comprising both genderS) aged between 20 and 65 years. Participants were sourced from diverse laboratories and the general population in Chalous, northern Iran. Dietary intake data were meticulously acquired using a comprehensive Food Frequency Questionnaire (FFQ). Furthermore, dietary quality indices, specifically the Healthy Eating Index (HEI), Dietary Diversity Score (DDS), Nutrient Adequacy Ratio (NAR), and Mean Adequacy Ratio (MAR), were meticulously evaluated employing standardized methodologies. Results: There was no significant diversity in the likelihood of developing metabolic syndrome concerning the Healthy Eating Index (HEI), Nutrient Adequacy Ratio (NAR), and Mean Adequacy Ratio (MAR) when comparing quartile 4 (Maximum scorE) to quartile 1 (Minimum scorE). However, this likelihood diminished following adjustments for confounding variables, including age, sex, dietary energy, education, job, and marital status. In the case of the Dietary Diversity Score (DDS), there was an observed difference in morbidity likelihood between quartile 4 and quartile 1. Nevertheless, after meticulous adjustment for confounding variables, this difference failed to reach statistical significance. No substantial variations (P ≥ 0.05) were detected in the odds ratio across quartiles and models (P trenD) for all dietary quality indices. Conclusion: No significant associations were identified between dietary quality indices and the occurrence of metabolic syndrome.