Health Concern Research Articles

Personal noise exposure patterns and health implications in urban work environments

Noise-induced hearing loss remains a preventable occupational health concern, contingent on timely detection and mitigation of excessive workplace noise. However, the lack of effective identification of at-risk workers often results in the neglect of safety measures that could prevent hearing loss. To address this, personal noise exposure measurements, using noise dosimeters, were conducted on 50 individuals across diverse urban work environments, including work from home, offices, outdoor settings, and mixed-use spaces. The results demonstrated significant variations in noise exposure levels among different environments. Outdoor and mixed-use environments exhibited the highest average dose percentages, while home-based workers had the lowest exposure. A strong correlation between noise levels above 80 dB and increased dose percentages emphasized the need to reduce high-noise exposure times. Additionally, the study integrated quantitative dosimeter measurements with qualitative data from a questionnaire survey to provide a holistic understanding of the participants' perception on noise pollution. Traffic emerged as the primary source of noise pollution, with a substantial number of respondents experiencing stress and ear infections attributed to noise exposure. The research underscores the importance of personalized noise dosimetry in assessing health implications, emphasizing the need for awareness and preventative measures to mitigate health risks in urban work environments.

Re-emerging Chandipura vesiculovirus: A cause of concern for global health

Re-emerging Chandipura vesiculovirus: A cause of concern for global health

Host diversity of Aedes albopictus in relation to invasion history: a meta-analysis of blood-feeding studies

BackgroundThe invasive mosquito Aedes albopictus is a major concern for human and animal health given its high potential to spread over large geographical distances, adapt to various habitats and food sources, and act as a vector for pathogens. It is crucial to understand how this species establishes ecological relationships at different locations, as it determines its role in transmission of diseases.MethodsBased on published blood meal surveys, a meta-analysis was performed to investigate how host diversity changes along the process of invasion at a large scale. For 48 independent localities, the Shannon diversity index was calculated and was then assessed against several moderator variables describing invasion status, habitat type, methodology, survey year and the year of introduction for invasive populations.ResultsDiet diversity was higher in the invasive than in the native populations when the strong habitat effects were held constant. Furthermore, the year of introduction also had a significant role, as invasive populations that had been established earlier had wider diet diversity than more recent populations.ConclusionsInvasive Ae. albopictus has considerable ecological flexibility. The species’ ability to adapt to various food sources goes hand in hand with its successful worldwide dispersion, which has strong implications for its role in pathogen transmission.Graphical

Trends in the hormone and antibiotic use for cattle fattening in Bangladesh

The study was conducted to identify trends in the use of hormones and antibiotics, and traditional practices in cattle fattening in the southwest coastal region of Bangladesh. Data were collected from 150 farmers involved in beef cattle fattening through a survey questionnaire. The average numbers of cattle and beef cattle per household were 4.27 ± 1.94 and 3.54 ± 1.31, respectively. An average of 44.67 percent of the beef farmers selected indigenous (zebu) cattle and the rest of the farmers kept a variety of crossbred cattle for fattening. The average age of cattle at the start of fattening was 21.61 ± 8.07 months, the average duration of fattening was 9.71 ± 4.29 months, and farmers marketed cattle at an average weight of 285.50 ± 50.80 kg. The highest percentage (34.67%) of farmers ate beef once a week and 5.33 percent of farmers never ate beef. Among beef farmers, 53.33% and 62.67% applied hormones and antibiotics, respectively, to their beef cattle. The highest percentage of farmers used hormones (33.87%) and antibiotics (29.79%) once a week and the rest of the farmers used them at various intervals. The majority of farmers did not follow any withdrawal period before slaughtering beef cattle for application of hormones (85.48%) and antibiotics (83.58%), whereas the remaining farmers maintained different withdrawal periods. It can be concluded that more than half of the farmers applied hormones and about two-thirds of the farmers used antibiotics for beef fattening, and most of the farmers did not follow the recommended withdrawal periods before slaughter, which is of public health concern.

Fall Detection Based on Data-Adaptive Gaussian Average Filtering Decomposition and Machine Learning

Falls are a significant health concern leading to increased morbidity and healthcare costs, especially for the elderly. Early and accurate detection of fall events is critical for timely intervention and preventing severe complications. This study presents a novel approach to triaxial accelerometer signals by employing data-adaptive Gaussian average filtering (DAGAF) decomposition in conjunction with machine learning techniques for fall detection. The triaxial accelerometer signals from the FallAllD dataset were decomposed into intrinsic mode functions (IMFs) and a residual component, from which feature vectors were extracted to train support vector machine (SVM) and k-nearest neighbor (kNN) classifiers. Experimental results demonstrate that the combination of the first and the third IMFs with the residual component yields the highest classification accuracy of 96.34%, with SVM outperforming kNN across all performance metrics. This approach significantly improves fall detection accuracy compared to using raw accelerometer signals, highlighting its potential in enhancing wearable fall detection systems. The proposed DAGAF decomposition method not only enhances feature extraction but also provides a promising advancement in the field, suggesting its potential to increase the reliability and accuracy of fall detection in practical applications.

Estimating the impact of physician risky-prescribing on the network structure underlying physician shared-patient relationships

Social network analysis and shared-patient physician networks have become effective ways of studying physician collaborations. Assortative mixing or “homophily” is the network phenomenon whereby the propensity for similar individuals to form ties is greater than for dissimilar individuals. Motivated by the public health concern of risky-prescribing among older patients in the United States, we develop network models and tests involving novel network measures to study whether there is evidence of homophily in prescribing and deprescribing in the specific shared-patient network of physicians linked to the US state of Ohio in 2014. Evidence of homophily in risky-prescribing would imply that prescribing behaviors help shape physician networks and would suggest strategies for interventions seeking to reduce risky-prescribing (e.g., strategies to directly reduce risky prescribing might be most effective if applied as group interventions to risky prescribing physicians connected through the network and the connections between these physicians could be targeted by tie dissolution interventions as an indirect way of reducing risky prescribing). Furthermore, if such effects varied depending on the structural features of a physician’s position in the network (e.g., by whether or not they are involved in cliques—groups of actors that are fully connected to each other—such as closed triangles in the case of three actors), this would further strengthen the case for targeting groups of physicians involved in risky prescribing and the network connections between them for interventions. Using accompanying Medicare Part D data, we converted patient longitudinal prescription receipts into novel measures of the intensity of each physician’s risky-prescribing. Exponential random graph models were used to simultaneously estimate the importance of homophily in prescribing and deprescribing in the network beyond the characteristics of physician specialty (or other metadata) and network-derived features. In addition, novel network measures were introduced to allow homophily to be characterized in relation to specific triadic (three-actor) structural configurations in the network with associated non-parametric randomization tests to evaluate their statistical significance in the network against the null hypothesis of no such phenomena. We found physician homophily in prescribing and deprescribing. We also found that physicians exhibited within-triad homophily in risky-prescribing, with the prevalence of homophilic triads significantly higher than expected by chance absent homophily. These results may explain why communities of prescribers emerge and evolve, helping to justify group-level prescriber interventions. The methodology may be applied, adapted or generalized to study homophily and its generalizations on other network and attribute combinations involving analogous shared-patient networks and more generally using other kinds of network data underlying other kinds of social phenomena.

Predominance of enterotoxigenic Escherichia coli among ESBL/plasmid-mediated AmpC-producing strains isolated from diarrheic foals: a public health concern

BackgroundThe upsurge of diarrheagenic E. coli pathotypes carrying extended-spectrum beta-lactamases (ESBLs)/plasmid-mediated AmpC β-lactamase (pAmpC) among animals constitutes an emerging threat for humans and animals. This study investigated the burden of ESBL-/pAmpC-producing diarrheagenic E. coli among diarrheic foals and its potential public health implications. Rectal swabs were collected from 80 diarrheic foals. These swabs were processed to isolate and identify ESBL/pAmpC-producing E. coli using a selective culture medium, biochemical tests, phenotypic identification, and molecular identification of ESBL- and pAmpC-encoding genes. Moreover, all ESBL-/pAmpC-producing E. coli isolates were examined for different virulence genes related to diarrheagenic E. coli pathotypes.ResultsOut of 80 examined foals, 26 (32.5%) were confirmed as ESBL-/pAmpC-producing E. coli, of which 14 (17.5%) animals carried only ESBL-producing E. coli, whereas 12 (15%) animals possessed ESBL-pAmpC-producing E. coli. The only detected diarrheagenic pathotype was enterotoxigenic, encoded by the heat-stable enterotoxin gene (ST) with a prevalence rate of 80.8% (21/26). The ST gene was further characterized where STa, STb, and STa + STb were found in one, four, and 16 strains, respectively. Moreover, all enterotoxigenic E. coli (ETEC) isolates exhibited a multidrug-resistance pattern. The phylogenetic analysis of 3 obtained partial STb sequences revealed high genetic relatedness to ETEC isolates retrieved from humans, conferring such sequences' public health significance.ConclusionsThese findings highlight that diarrheic foals could serve as a potential reservoir for multidrug-resistant ESBL-/pAmpC-producing enterotoxigenic E. coli.

Myopic shift in female mice after ovariectomy

Myopia is a global public health concern, with a higher prevalence in women than that in male. As the relationship between sex hormone and myopia remains unclear, we aimed to reveal the relationship between sex hormone and myopia by removing the ovaries of mice and measuring changes in ocular parameters related to myopia. Lens-induced myopia (LIM) surgeries were performed on 3-week-old male mice and age-matched female mice to evaluate the effects of sex on myopia development, which indicated a high degree of myopia and rapid progression of axial elongation in male mice. Bilateral ovariectomy (OVX) performed on 4-week-old female mice induced myopic refraction status in ovariectomized mice. Although axial length elongation was larger in ovariectomized mice than that in sham control mice, the result was insignificant. To further reveal the relationship between female sex hormones and myopia, LIM combined with OVX was performed, which revealed a magnified myopic refraction status in ovariectomized mice. Nevertheless, elongation of the anterior chamber depth in the − 30 D lens-treated eyes significantly increased in LIM + OVX mice compared with the frame-treated eyes in LIM + OVX mice and − 30 D lens-treated eyes in LIM + Sham surgery mice. Sex hormones play a role in regulating myopia development in female mice.

Strengthening Fungal Infection Diagnosis and Treatment: An In-depth Analysis of Capabilities in Honduras

Abstract Background Invasive fungal infections (IFI) are a major public health concern in low- and middle-income countries (LMICs) due to limited diagnostic and treatment resources, leading to high morbidity and mortality. Despite their significant global burden, IFI are under-recognized and under-diagnosed in LMICs. This study evaluates the diagnostic and therapeutic capacities for managing IFI in Honduras, a country with unique healthcare challenges. Methods From March to December 2023, a comprehensive survey was conducted across multiple healthcare centers in Honduras. The survey, reviewed for content and clarity by local medical institutions, targeted medical microbiologists and clinicians to assess various aspects of fungal disease diagnosis and treatment. Data collected included the availability and use of diagnostic tools and antifungal therapies, identifying gaps and limitations in current practices. Results The survey revealed that Candida spp. (97.4%) and Aspergillus spp. (35.9%) were the most concerning pathogens. Although microscopy and culture methods were available in most institutions, their application in suspected IFI cases was inconsistent, and antifungal susceptibility testing was rarely performed. Advanced diagnostic techniques, such as antigen detection, were available in only a few institutions, while antibody detection and PCR testing were entirely absent. All hospitals had access to at least one triazole antifungal, typically fluconazole, but there was a notable scarcity of more potent antifungals, including amphotericin B formulations and echinocandins. The limited use of available diagnostic tools and the restricted availability of essential antifungals were identified as major barriers to effective IFI management. Conclusions This study highlights significant gaps in the diagnostic and therapeutic capabilities for managing IFI in Honduras. The underutilization of basic diagnostic tools, the inaccessibility of advanced testing methods, and the limited availability of essential antifungal medications underscore the urgent need for capacity-building initiatives, infrastructure improvements, and policy reforms. Addressing these deficiencies is critical for enhancing the management of IFI in Honduras, with broader implications for similar LMIC settings. These findings can inform targeted interventions and resource allocation to improve outcomes for patients suffering from IFI.

Global, regional, and national burden of pancreatitis in children and adolescents.

Pancreatitis poses a growing public health concern among children and adolescents, yet comprehensive data on its prevalence, incidence, mortality, and disability-adjusted life years (DALYs) remain scarce. This study aims to analyze global, regional, and national trends in pancreatitis burden over the past 3decades. Using data from the Global Burden of Disease (GBD) 2019 database spanning 1990-2019, we assessed pancreatitis prevalence, incidence, mortality, and DALYs, reporting on numbers, rates, age-standardized prevalence rate (ASPR), age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), age-standardized DALYs rate (ASDR), and average annual percentage changes (AAPCs). Trends were analyzed by age, sex, region, and socio-demographic index (SDI) using jointpoint analysis and predictive modeling. Globally, pancreatitis prevalence and incidence rates have increased (AAPC prevalence=0.13, 95% CI: 0.11-0.16; AAPC incidence=0.30, 95% CI: 0.28-0.32), while mortality and DALYs rates have decreased (AAPC mortality=-1.30, 95% CI: -1.53, -1.07; AAPC DALYs=-1.21, 95% CI: -1.41, -1.01). Both genders showed similar trends. Children under 5 and adolescents 15-19 had higher mortality and DALYs rates. Low SDI regions experienced the greatest increase in ASIR. Eastern Europe exhibited high and rising ASIR, ASMR, and ASDR. Projections indicate continued rise in prevalence with declining mortality and DALYs. Pancreatitis burden in children and adolescents has surged globally, especially in lower SDI regions. These findings underscore the urgent need for targeted interventions and healthcare resources in affected areas.

Assessing subgroup differences and underlying causes of ozone-associated mortality burden in China using multi-source data

Long-term ozone exposure is a significant public health concern. To mitigate its impact, it is crucial to identify diseases, populations, and regions that are particularly sensitive to ozone. In this study, we used high-quality data and updated relative risk estimates to investigate subgroup differences in mortality burden due to ozone exposure in China. In 2020, nationwide ozone-associated deaths totaled 276,800 (95 % CI: 106,700–451,900), representing 3.2 % of all deaths, with respiratory and cardiovascular diseases accounting for 16.8 % and 83.2 %, respectively. The per capita ozone-associated mortality in China was 20 per 100,000 person-years, with a significantly higher rate observed in elderly individuals aged ≥75 years (189 deaths per 100,000) compared to young individuals aged 30–44 years (1 death per 100,000). There were notable spatial patterns of ozone-associated deaths among the regions, indicating a critical response to ozone levels and population density. Interestingly, urban areas exhibited a 22.4 % lower mortality rate related to ozone compared to rural areas. This difference was attributed to the combined influence of ozone exposure (+19.9 %), population size (+17.7 %), age structure (−39.2 %), and baseline mortality (−20.8 %). By emphasizing subgroup differences and driving factors, these findings significantly enhance the understanding of the ozone-associated mortality burden, providing valuable insights for policymakers.

Implementation and validation of MICaFVi: A highly efficient nanotechnology-based method for coronaviruses detection

Coronaviruses have emerged as a significant public health concern due to the global impact of Middle East respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which cause COVID-19. The development of sensitive and accurate detection methods is critical for early diagnosis, disease management, and outbreak control. In a previous study, we developed and optimized a nanobased detection methodology called Magnetic Immuno-Capture Followed by Flow Virometry (MICaFVi) using virus-mimicking silica nanoparticles and MERS-CoV/SARS-CoV-2 pseudoviral particles. In the present study, we have extended this methodology to evaluate its specificity and sensitivity for detecting wild-type MERS-CoV and SARS-CoV-2 in human and camel samples. Our results demonstrated that MICaFVi successfully detected MERS-CoV and SARS-CoV-2 viruses with high sensitivity and specificity, although it showed reduced performance for samples with Ct values of 30 or lower compared to qPCR. Despite some limitations in detection speed and sensitivity, MICaFVi represents a significant advancement in diagnostic methodologies by combining nanotechnology with flow cytometry. Additionally, we adapted the MICaFVi methodology to simultaneously detect MERS-CoV and SARS-CoV-2 in a single multiplex assay. The successful implementation of this advanced detection approach has important implications for improving early detection, surveillance, and control of both current and future viral or bacterial pandemics. Our results underscore the potential of MICaFVi as a valuable tool for monitoring the spread of these viruses and highlight its role in advancing diagnostic technologies. This extension of our earlier work offers new insights into the application of nanotechnology and flow cytometry for viral detection.

Mortality Patterns of Esophageal Cancer in the United States: A 21-Year Retrospective Analysis.

Esophageal cancer (EC) is the sixth leading cause of cancer-related deaths in the United States, with a mere 20% survival rate in the first 5 years, making it a significant public health concern. Considering the lack of comprehensive evaluations of mortality trends, this study aims to provide an update on the mortality rates of esophageal cancer and its trends in the United States. The mortality trends among adults with EC were analyzed using data from the CDC WONDER database. Crude and age-adjusted mortality rates (AAMRs) per 100,000 people were extracted. Annual percent changes (APCs) in AAMRs with 95% CI were obtained using joinpoint regression analysis across different demographic (sex, race/ethnicity, and age) and geographic (state, urban-rural, and regional) subgroups. Between 1999 and 2020, 309,725 documented deaths were attributed to esophageal cancer. The overall AAMR decreased from 1999 to 2020 (6.69 to 5.68). Males had higher consistently higher AAMRs than females (10.96 vs. 2.24). NH White had the highest overall AAMR (6.88), followed by NH Black (6.46), NH American Indian (4.95), Hispanic or Latino (3.31), and NH Asian or Pacific Islander (2.57). AAMR also varied by region (overall AAMR: Midwest: 7.18; Northeast: 6.75; South: 6.07; West: 5.76), and nonmetropolitan areas had higher AAMR (non-core areas: 7.09; micropolitan areas: 7.19) than metropolitan areas (large central metropolitan areas: 5.75; large fringe areas: 6.33). The states in the upper 90th percentile of esophageal cancer-related AAMR were Vermont, District of Columbia, West Virginia, Ohio, New Hampshire, and Maine, and exhibited an approximately two-fold increase in AAMRs, compared with states falling in the lower 10th percentile. Over the last 2 decades, there has been an overall decline in mortality related to EC in the United States. However, demographic and geographic discrepancies in EC-related mortality persist, necessitating additional exploration and development of specifically directed treatments.

Salvia miltiorrhiza in osteoporosis: a review of its phytochemistry, traditional clinical uses and preclinical studies (2014–2024)

Osteoporosis becomes a global public health concern due to its rising prevalence and substantial impact on life quality. Salvia miltiorrhiza Bunge (Salviae Miltiorrhizae Radix et Rhizoma, SM) has been firstly recorded in Shen Nong’s Herbal Classic, and is frequently prescribed in conjunction with other herbs for the management of osteoporosis. This systematic review aims to comprehensively analyze the recent advances of SM on osteoporosis in traditional Chinese clinical uses and preclinical investigations. Literature encompassing pertinent studies were systematically retrieved across multiple databases, including the PubMed, Web of Science, Chinese National Knowledge Infrastructure, Chinese VIP Database, and Chinese Biomedical Literature Database. Original investigations spanning from February 2014 to March 2024, including traditional Chinese medicine (TCM) clinical trials and preclinical studies, were employed to analyze the effects and actions of SM on osteoporosis. Thirty-eight TCM clinical trials were identified to employ SM in combination with other herbs for the management of primary and secondary osteoporosis. The overall efficacy was between 77% and 96.67%. Forty preclinical studies were identified to investigate the effects and actions of SM and/or its ingredients on osteoporosis. The anti-osteoporosis actions of this herb may be attributed to inhibit osteoclastogenesis/bone resorption and promote osteoblastogenesis/osteogenesis. The ethanol extracts and its ingredients (tanshinones) inhibit osteoclastogenesis/bone resorption by inhibiting the MAPK/NF-κB/NFATc1 signaling pathway and cathepsin K-induced collagen degradation. Both ethanol extracts (tanshinones) and water extracts (Sal B and tanshinol) contribute to osteoblastogenesis by promoting osteogenesis and angiogenesis via activation of the Wnt/β-catenin/VEGF and ERK/TAZ pathways, and eliminating ROS production targeting Nrf2/ARE/HO-1 pathway. In conclusions, SM may offer a novel strategy for osteoporosis management. Well-designed clinical trials are still needed to evaluate the actions of this herb and its ingredients on bone remodeling.

A New Era in Stress Monitoring: A Review of Embedded Devices and Tools for Detecting Stress in the Workplace

Detection of stress and the development of innovative platforms for stress monitoring have attracted significant attention in recent years due to the growing awareness of the harmful effects of stress on mental and physical health. Stress is a widespread issue affecting individuals and often goes unnoticed as a health concern. It can lead to various negative physiological conditions, including anxiety, depression, cardiovascular diseases and cognitive impairments. The aim of this paper is to provide an overview of studies focusing on embedded devices for non-invasive stress detection, primarily in the form of a modified computer mouse or keyboard. This study not only fills a critical gap in the literature but also provides valuable insights into the design and implementation of hardware-based stress-detection methods. By focusing on embedded devices, specifically computer peripherals, this research highlights the potential for integrating stress monitoring into everyday workplace tools, thereby offering practical solutions for improving occupational health and well-being.

Assessment of groundwater quality in the eastern part of tehran plain: Implications for human health.

Groundwater quality is a critical concern for human health, particularly in urban areas like the eastern part of Tehran Plain, where geological features and anthropogenic activities contribute to contamination risks. This study aimed to assess the quality of groundwater in this region, focusing on its implications for public health. The objectives of the study were to identify factors influencing hydrogeochemistry, evaluate environmental risk based on metal(loid)s using water quality indices, and conduct a health risk assessment. Groundwater samples were collected and analyzed for chemistry, water quality, heavy metal contamination, and associated health risks. The results indicated a relatively stable pH condition and a wide variation in the concentration of dissolved solids. The Water Quality Index (WQI) was employed to evaluate the overall water quality, revealing that approximately 50% of the samples fell into the poor and very poor quality categories, with two samples deemed unsuitable for drinking. Heavy metal contamination varied across different metals, with some indicating low levels while others showed moderate to very high levels. Priority pollutants such as mercury and arsenic were identified as having a greater potential impact on water quality deterioration. Exposure and health risk assessments indicated a negligible risk associated with aluminum exposure but high risks associated with arsenic, chromium, and mercury exposure. Carcinogenic risk assessments for arsenic, chromium, and mercury exceeded acceptable thresholds, emphasizing the urgent need for further investigation into contamination sources and strategies for mitigation. These findings highlight the importance of continuous monitoring and sustainable groundwater management practices, providing valuable insights for other regions facing similar challenges in groundwater quality and public health.

A-102 Clinical Evaluation of Novel Markers in Brain Injury

Abstract Background Traumatic brain injury (TBI) is a significant health concern affecting individuals of all ages, demanding precise diagnostic methodologies to guide effective clinical management. According to the 2010 definition, a TBI results from an external force causing an alteration in brain function or other evidence of brain pathology. Current diagnostic tools, i.e. CT scans and the Glasgow Coma Scale (GCS), are inefficient because they are time and labor intensive. The need for rapid diagnostic tools is underscored by the drawbacks of existing methods, such as CT scans, which are expensive, expose patients to large amounts of radiation, and lead to delayed treatment. Recent advances in TBI diagnosis involve novel biomarkers, such as Glial Fibrillary Acidic Protein (GFAP) and Ubiquitin C-Terminal Hydrolase L1 (UCH-L1), which have shown promise in revolutionizing the assessment of head traumas. GFAP, a glial-specific protein, is elevated in circulation after a TBI, distinguishing it from multi-trauma patients without brain injuries. UCH-L1, found in neurons, is significantly elevated in TBI patients compared to uninjured controls. A 2021 study further supports the clinical effectiveness of these biomarkers, demonstrating their capacity to exclude CT-positive injury in acute TBI cases. The primary aim of this study is to explore the clinical utility of the Abbott Alinity TBI assay, specifically biomarkers GFAP and UCH-L1, in emergency department patients with a history of head trauma. Methods A retrospective study involving 238 emergency department patients with a history of head trauma and noncontrast CT scans was conducted using the Abbott Alinity TBI assay. Serum samples were collected, and biomarker values were established and compared to CT scan results. The study was comprised of 94 females and 144 males spanning various age groups. The GFAP and UCH-L1 cutoffs used were FDA approved, at 35.0 ng/L and 400.0 ng/L, respectively. If either marker was above the cutoff the patient ruled at risk for TBI. Results Results demonstrated the assay correctly identified all CT-positive cases (100% sensitivity), placing them in the rule-in group, while identifying 44 patients with a 0 chance of TBI. The negative predictive value for the TBI overall was 100% (95% CI: 91.96%-100%). The GFAP assay alone identified 30/31 positive CT scans, reporting a 98.77% (95% CI: 92.03%-99.82%) negative predictive value. The UCH-L1 assay reported 26/31 positive CT scans with a negative predictive value of 94.68% (95% CI: 88.71-97.58%). Analyzing the data revealed the TBI assay would have reduced CT scans by 18.5%. Conclusions The results of this study did show a potential reduction in the number of patients sent to CT making it a valuable tool for triaging patients presenting with head trauma; however, the complexity of neurological problems may lead to increased false positives, reducing assay specificity. Despite this limitation, this study concludes that the GFAP and UCH-L1 markers could be used to triage patients into CT rule-out and rule-in groups, thereby streamlining clinical management. In conclusion, this assay, incorporating GFAP and UCH-L1 biomarkers, presents as a promising diagnostic tool for emergency departments.

Application of machine learning based genome sequence analysis in pathogen identification

Infectious diseases caused by pathogenic microorganisms pose a serious threat to human health. Despite advances in molecular biology, genetics, computation, and medicinal chemistry, infectious diseases remain a significant public health concern. Addressing the challenges posed by pathogen outbreaks, pandemics, and antimicrobial resistance requires concerted interdisciplinary efforts. With the development of computer technology and the continuous exploration of artificial intelligence(AI)applications in the biomedical field, the automatic morphological recognition and image processing of microbial images under microscopes have advanced rapidly. The research team of Institute of Microbiology, Chinese Academy of Sciences has developed a single cell microbial identification technology combining Raman spectroscopy and artificial intelligence. Through laser Raman acquisition system and convolutional neural network analysis, the average accuracy rate of 95.64% has been achieved, and the identification can be completed in only 5 min. These technologies have shown substantial advantages in the visible morphological detection of pathogenic microorganisms, expanding anti-infective drug discovery, enhancing our understanding of infection biology, and accelerating the development of diagnostics. In this review, we discuss the application of AI-based machine learning in image analysis, genome sequencing data analysis, and natural language processing (NLP) for pathogen identification, highlighting the significant role of artificial intelligence in pathogen diagnosis. AI can improve the accuracy and efficiency of diagnosis, promote early detection and personalized treatment, and enhance public health safety.

Simultaneous In Vivo Imaging of Neutrophil Elastase and Oxidative Stress in Atherosclerotic Plaques Using a Unimolecular Photoacoustic Probe

AbstractAtherosclerosis, a major global health concern with high morbidity and mortality rates, involves complex interactions of chronic inflammation, oxidative stress, and proteolytic enzymes. Conventional imaging methods struggle to capture the dynamic biochemical processes in atherosclerotic plaques. Here, we introduce a novel unimolecular photoacoustic probe (UMAPP) designed with specific binding sites for neutrophil elastase (NE) and the redox pair O2⋅−/GSH, enabling real‐time monitoring of oxidative stress and activated neutrophils in plaques. UMAPP, comprising a boron‐dipyrromethene (BODIPY) core linked to a hydrophilic NE‐cleavable tetrapeptide and dual oxidative stress‐responsive catechol moieties, facilitates NE‐mediated modulation of photoinduced electron transfer impacting photoacoustic intensity at 685 nm (PA685). Furthermore, oxidation and reduction of catechol groups by O2⋅− and GSH induce reversible, ratiometric changes in the photoacoustic spectrum (PA745/PA685 ratio). Initial UMAPP applications successfully distinguished atherosclerotic and healthy mice, evaluated pneumonia‘s effect on plaque composition and verified the probe‘s effectiveness in drug‐treatment studies by detecting molecular alterations before visible histopathological changes. The integrated molecular imaging capabilities of UMAPP offer promising advancements in atherosclerosis diagnosis and management, enabling early and accurate identification of vulnerable plaques.

PDOC-12 PEDIATRIC BRAIN TUMOR INCIDENCE, AND TREATMENT MODALITY AT KILIMANJARO CHRISTIAN MEDICAL CENTER

Abstract INTRODUCTION Pediatric brain tumors (PBT) a significant health concern, they are the primary cause of cancer-related deaths among children. PBTs in Low- and Middle-Income Countries are diagnosed late due to insufficient resources. This abstract describes Pediatric Brain tumor incidence and treatment modalities at Kilimanjaro Christian Medical Center (KCMC) Cancer Care Center (CCC), Moshi, Tanzania from December 2016 to March 2024. METHOD Data on pediatric patients treated at the CCC between Dec. 2016 and March 2024, were analyzed. Inclusion criteria were a primary brain tumor and patients aged 0-19 at the time of diagnosis. All patients were previously diagnosed by computer tomography/ magnetic resonance imaging. Variables retrospectively collected from patient’s medical records were: demographic characteristics (age, gender, Place of residence, and insurance status), previous history of malignant diseases, incidence date, and treatment modality. RESULTS Total of 748 cases of pedeatric cancer were diagnosed at CCC. Of all the pediatric cancers diagnosed, brain cancer accounted for 22(2.9%). Out of these cases of brain cancer, 63.6% were males and 36.4% were females.Majority of them came within the Kilimanjaro region. 41% were palliated while 59% had a curative intent at the time of diagnosis, 22.7% died between December 2016 to March 2024.Embryonal tumors were (40.9%) with a breakdown that includes 6 Medulloblastoma and 3 cases of Craniopharyngioma (teratoid/rhabdoid), gliomas (36.4%) with sub-types such as Ependymoma, Anaplastic Astrocytoma, Pilocytic Astrocytoma, Pineocytoma, Stem glioma, and Tectal glioma, unspecified cases (13.6%), and Pineoblastoma were (9.1%). Surgery was used in 40.9% of cases, radiotherapy in 31.8%, and chemotherapy in 72.7%. Chemoradiotherapy was used in 31.8% of cases. 13.6% of cases utilized a combined approach, including chemotherapy, radiotherapy, and surgery. CONCLUSION PBT incidence at KCMC is 2.9%, improving access to screening, accurate diagnosis and treatment modalities are essential in identifying and managing PBT in our setting.