Hasil untuk "Medicine (General)"

E. Berner, M. Graber

D. Roden, J. Pulley, M. Basford et al.

Nghia Nhu Nguyen, Bao The Nguyen, Huyen Thi Ngoc Le et al.

Background Liver fibrosis is a significant health burden in Vietnamese male adults, driven by high rates of hepatitis B and hepatitis C, excessive alcohol consumption, and genetic and environmental factors. Despite progress in diagnostic tools, there is a pressing need for cost-effective screening methods tailored to this high-risk group, particularly in resource-limited settings. Methods This study enrolled 952 Vietnamese male adults over 40 years old undergoing FibroScan, excluding those with conditions affecting test accuracy. Data on demographics, clinical history, and anthropometrics were collected, and fibrosis stages were classified using the METAVIR system. Model development combined Bayesian model averaging and forward stepwise methods, with predictive performance validated via receiver operating characteristic (ROC) analysis and area under the curve (AUC) estimation in the R environment. Results Among 952 male participants, the prevalence of liver fibrosis was 19.9%, with most cases classified as mild (F1). Multivariate analysis identified significant risk factors, including advanced age (odds ratio (OR) = 1.6; 95% confidence interval (CI) [1.02–2.51]), alcohol abuse (OR = 4.44; 95% CI [2.65–7.42]), hepatitis B (OR = 6.76; 95% CI [3.14–14.54], hepatitis C (OR = 33.04; 95% CI [5.26–207.42]), family history of cirrhosis (OR = 16.14; 95% CI [3.28–79.55]), and hepatic steatosis (OR = 4.02; 95% CI [2.57–6.28]). The predictive model demonstrated good discriminative performance with an AUC of 0.769 (95% CI [0.734–0.800]) and showed satisfactory calibration through bootstrap resampling, indicating close agreement between predicted and observed risks. Conclusion The current prevalence of liver fibrosis among Vietnamese male adults was found to be 19.9%, and the developed risk prediction model effectively identifies high-risk individuals, enabling early diagnosis and targeted prevention, particularly in resource-limited settings. However, the lack of external validation and the sample restricted to Vietnamese male adults limit the generalizability of the model, which should be further evaluated in other populations.

Alex Ferreira da Silva, Franciele Jesus Lima, Alyne Riani Moreira et al.

Aberrant Rho-associated kinase function could be associated with increased bone fragility. Since cigarette smoke (CS) exposure promotes the increase in bone fragility due to changes in bone tissue components, this study aimed to investigate how CS exposure could modulate the Rho kinase-associated bone structural changes. Mice were assigned to four groups: control; smoke; control with Rho kinase inhibitor administration; and smoke with a Rho kinase inhibitor. Bone samples were obtained to assess bone histomorphometry analysis, type I collagen composition, and MEPE expression in trabeculae. We observed that CS exposure induced decreased trabecular and osteoid thickness. A concomitant increase in the osteoclastic and erosion surfaces and a decrease in the mineralization surface were observed. Additionally, CS exposure decreased the type I collagen and MEPE expression. Rho kinase inhibitor administration recovered the bone mineralization and the collagen type I deposition. Conclusions: CS exposure increases Rho kinase activity in bone cells, leading to structural changes. The administration of a Rho GTPases inhibitor partially reverses these effects, likely due to the recovery in osteoblast activity.

Yutaro Hama, Yuko Fujioka, Hayashi Yamamoto et al.

In mammals, autophagosome formation, a central event in autophagy, is initiated by the ULK complex comprising ULK1/2, FIP200, ATG13, and ATG101. However, the structural basis and mechanism underlying the ULK complex assembly have yet to be fully clarified. Here, we predicted the core interactions organizing the ULK complex using AlphaFold, which proposed that the intrinsically disordered region of ATG13 engages the bases of the two UBL domains in the FIP200 dimer via two phenylalanines and also binds the tandem microtubule-interacting and transport domain of ULK1, thereby yielding the 1:1:2 stoichiometry of the ULK1–ATG13–FIP200 complex. We validated the predicted interactions by point mutations and demonstrated direct triad interactions among ULK1, ATG13, and FIP200 in vitro and in cells, wherein each interaction was additively important for autophagic flux. These results indicate that the ULK1–ATG13–FIP200 triadic interaction is crucial for autophagosome formation and provides a structural basis and insights into the regulation mechanism of autophagy initiation in mammals.

Majed Alluqmani, Abdulfatah M. Alayoubi, Jamil A. Hashmi et al.

BackgroundVariants in a gene encoding sodium voltage-gated channel alpha subunit 1 (SCN1A) are known to cause a broad clinical spectrum of epilepsy and associated features, including Dravet syndrome (MIM 607208), non-Dravet developmental and epileptic encephalopathy (MIM 619317), familial febrile seizures (MIM 604403), familial hemiplegic migraine (MIM 609634), and generalized epilepsy with febrile seizures (MIM 604403).MethodsIn this study, we examined a patient with Parkinson’s disease (PD) without any clinical manifestations of epilepsy and associated features. Genomic nucleic acid was extracted, and a complete coding sequence of the human genome (whole-exome sequencing) was sequenced. Moreover, Sanger sequencing of variants of interest was performed to validate the exome-discovered variants.ResultsWe identified a heterozygous pathogenic missense mutation (c.1498C>T; p.Arg500Trp) in the SCN1A gene in the patient using the whole-exome sequencing approach. The onset of PD features in our patient occurred at the age of 30 years. Biochemical investigations were carried out to rule out any secondary cause of the disease, including Wilson's disease or another metabolic disorder. MRI of the brain and spinal images were unremarkable. Moreover, a dramatic response to carbidopa–levodopa treatment was also observed in the patient.ConclusionOur results suggest that the pathogenic variant in SCN1A may lead to PD features without epilepsy.

Wentao HU, Hui LAO, Ao QIU et al.

In recent years, silicon photomultipliers (SiPMs) have emerged as preferred photoelectric conversion devices in positron emission tomography (PET) due to their outstanding performance. SiPMs possess single-photon resolution capability and time resolution below 100 ps, enabling precise photon arrival time measurements. These advances paved the way for emerging applications such as time-of-flight PET (TOF-PET), photon counting CT, and positron emission lifetime imaging, presenting new challenges to SiPM performance, the advancing of which to their physical limits has become a key focus area in next-generation SiPM research. In traditional SiPM architectures, signal processing and analog-to-digital conversion introduce noise and degrade time performance, thereby limiting the full SiPM potential. With the recent and rapid development of semiconductor manufacturing processes, SiPMs could be manufactured on standard CMOS process nodes, which marks a significant breakthrough in the SiPM field, allowing for the integration of digital logic within SiPM devices. This advancement opens the possibility of achieving more precise time, energy, and position information within a single SiPM, thereby providing potential possibilities to push SiPMs to their performance limits. In this study, we reviewed the development history, working principles, and performance parameters of SiPMs. We analyzed the limitations of traditional SiPMs, outlined key aspects of digital SiPM research, and introduced various current digital SiPM architectures. Finally, we summarized and anticipated key technologies in digital SiPMs.

Shota Ikeda, Keisuke Shinohara, Koshiro Tagawa et al.

Abstract Electrocardiographic left ventricular hypertrophy (LVH) could predict adverse renal outcomes in patients with hypertension. This study aimed to investigate the association between electrocardiographic LVH and future decline in renal function in the general population using a dataset of population-based health checkups from 2010 to 2019 including 19,825 participants. Electrocardiographic LVH was defined according to the Minnesota code. Renal function decline was defined as a decrease of ≥ 25% in the estimated glomerular filtration rate from baseline to < 60 mL/min/1.73 m2. Electrocardiographic LVH was found in 1263 participants at the baseline visit. The mean follow-up period was 3.4 ± 1.9 years. The incidence rates of renal function decline were 0.30 and 0.78 per 100 person-years in the non-LVH group and LVH groups, respectively. Electrocardiographic LVH was associated with the risk for renal function decline in the adjusted analysis (hazard ratio 1.69, 95% confidence interval 1.14–2.50, P = 0.009). This association was comparable across subgroups stratified by age, sex, body mass index, diagnosed hypertension, systolic blood pressure, hemoglobin A1c, and urinary protein. This study underscores the usefulness of electrocardiographic LVH to detect high-risk individuals for renal function decline in the setting of health checkups in the general population.

Lubos Kubicek, Radek Vitasek, David Schwarz et al.

Background: The acute phase of the COVID-19 pandemic requires a redefinition of healthcare system to increase the number of available intensive care units for COVID-19 patients. This leads to the postponement of elective surgeries including the treatment of abdominal aortic aneurysm (AAA). The probabilistic rupture risk index (PRRI) recently showed its advantage over the diameter criterion in AAA rupture risk assessment. Its major improvement is in increased specificity and yet has the same sensitivity as the maximal diameter criterion. The objective of this study was to test the clinical applicability of the PRRI method in a quasi-prospective patient cohort study. Methods: Nineteen patients (fourteen males, five females) with intact AAA who were postponed due to COVID-19 pandemic were included in this study. The PRRI was calculated at the baseline via finite element method models. If a case was diagnosed as high risk (PRRI > 3%), the patient was offered priority in AAA intervention. Cases were followed until 10 September 2021 and a number of false positive and false negative cases were recorded. Results: Each case was assessed within 3 days. Priority in intervention was offered to two patients with high PRRI. There were four false positive cases and no false negative cases classified by PRRI. In three cases, the follow-up was very short to reach any conclusion. Conclusions: Integrating PRRI into clinical workflow is possible. Longitudinal validation of PRRI did not fail and may significantly decrease the false positive rate in AAA treatment.

Zhang S, Wang L, Wang L et al.

Shouping Zhang, Lei Wang, Lirong Wang, Nan Yu, Yongjun Dong, Jianhe Hu College of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang, 453003, People’s Republic of ChinaCorrespondence: Lei Wang, Jianhe Hu, College of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Eastern HuaLan Avenue, Xinxiang, 453003, People’s Republic of China, Tel +86-373-3040718, Email wlei_007@163.com; vet_jianhe@sina.comIntroduction: Porcine circovirus type 2 (PCV2) causes immune repression and intercurrent infections in pigs, resulting in a huge economic loss to the pig breeding industry. Additionally, the spread of PCV2 in pig farms can pollute the living environment of the residents in the farm’s vicinity, which increases the rate of infections. Therefore, rapid and sensitive detection methods are needed for disease prevention and timely environmental cleaning.Methods: This research describes a highly sensitive sandwich enzyme-linked immunosorbent assay (ELISA) that utilizes gold nanoparticles (AuNPs) in a functional, specific antibody labeled probe for the detection of PCV2. Due to their high specific surface area and histocompatibility, AuNPs were used as carriers of HRP labeled anti-PCV2 antibodies to amplify the detection signal.Results: Compared to conventional sandwich ELISA procedures, this method resulted in higher sensitivity (51-fold) and a shorter assay time with a limit of detection of 195 TCID50/mL. The cross-reactivity assay demonstrated that this assay was PCV2 specific.Conclusion: The amplified Ab (HRP) labeled AuNPs probe provides a sensitive analytical approach for the determination of the traces of the PCV2 antigen in early diagnosis.Keywords: PCV2, gold nanoparticles, ELISA, amplification, detection

Jane Cooley Fruehwirth, Siddhartha Biswas, Krista M Perreira

<h4>Purpose</h4>The Covid-19 pandemic has brought unprecedented stress to students and educational institutions across the world. We aimed to estimate the effect of the pandemic on the mental health of college students.<h4>Methods</h4>We used data on 419 first-year students (ages 18-20) at a large public university in North Carolina both before (October 2019-February 2020) and after (June/July 2020) the start of the Covid-19 pandemic. After evaluating descriptive data on mental health and stressors by students' demographic characteristics, we estimated the associations between Covid-19 stressors (including work reductions, health, distanced learning difficulties and social isolation) and mental health symptoms and severity controlling for students' pre-pandemic mental health, psychosocial resources, and demographic characteristics.<h4>Results</h4>We found that the prevalence of moderate-severe anxiety increased from 18.1% before the pandemic to 25.3% within four months after the pandemic began; and the prevalence of moderate-severe depression increased from 21.5% to 31.7%. White, female and sexual/gender minority (SGM) students were at highest risk of increases in anxiety symptoms. Non-Hispanic (NH) Black, female, and SGM students were at highest risk of increases in depression symptoms. General difficulties associated with distanced learning and social isolation contributed to the increases in both depression and anxiety symptoms. However, work reductions as well as Covid-19 diagnosis and hospitalization of oneself, family members or friends were not associated with increases in depression or anxiety symptoms.<h4>Conclusion</h4>Colleges may be able to reduce the mental health consequences of Covid-19 by investing in resources to reduce difficulties with distance learning and reduce social isolation during the pandemic.

Salma M Abdalla, MBBS, MPH, Shui Yu, MPH, Sandro Galea, MD, DrPH

Introduction: Income inequality between the richest 20% and the poorest 80% in the United States has been increasing over the past two decades. Emerging evidence indicates widening disparities between the two groups in cardiovascular disease prevalence as well. However, the mechanisms behind this trend remains unclear. This analysis examines whether a similar trend exists in the levels of biomarkers and risk factors of cardiovascular disease in the United States. Methods: We conducted a serial cross-sectional analysis of a nationally representative data from the National Health and Nutrition Examination Survey (NHANES) for participants age 20 or older between 1999 and 2018. We calculated trends in age-standardized means of body mass index (BMI), systolic blood pressure (SBP), and high-density lipoproteins (HDL) and the trend in prevalence of obesity, high SBP, and low HDL by income group. Results: This analysis included 49,764 participants. Age-standardized mean BMI increased every two years by an average of 0.15 kg/m 2 among the richest 20% and by an average of 0.21 kg/m 2 among the poorest 80%. Age-standardized mean SBP decreased every two years by an average of 0.13 mm Hg among the richest 20% and by an average of 0.10 mm Hg among the poorest 80%. Age-standardized mean HDL increased every two years by an average of 0.39 mg/dL among the richest 20% and by an average of 0.19 mg/dL among the poorest 80%. When adjusted for demographic factors and time, the richest 20% had lower mean BMI (OR = −0.67, 95% CI: −0.89, - 0.44), lower mean SBP (OR = −0.72, 95% CI: −1.24, −0.20), and higher mean HDL (OR = 3.04, 95% CI: 2.46, 3.62) compared to the poorest 80% Conclusion: There are increasing disparities in cardiovascular disease biomarkers by income in the US. Between 1999 and 2018, improvement in biomarkers overwhelmingly occurred among the richest 20%

Yangling Ma, Yixin Luo

Automated fracture detection is an essential part in a computer-aided tele-medicine system. Fractures often occur in human's arbitrary bone due to accidental injuries such as slipping. In fact, many hospitals lack experienced surgeons to diagnose fractures. Therefore, computer-aided diagnosis (CAD) reduces the burden on doctors and identifies fracture. We present a new classification network, Crack-Sensitive Convolutional Neural Network (CrackNet), which is sensitive to fracture lines. In this paper, we propose a new two-stage system to detect fracture. Firstly, we use Faster Region with Convolutional Neutral Network (Faster R-CNN) to detect 20 different types of bone regions in X-ray images, and then we recognize whether each bone region is fractured by using CrackNet. Total of 1052 images are used to test our system, of which 526 are fractured images and the rest are non-fractured images. We assess the performance of our proposed system with X-ray images from Haikou People's Hospital, achieving 90.11% accuracy and 90.14% F-measure. And our system is better than other two-stage systems.

Inese Polaka, Danute Razuka-Ebela, Jin Young Park et al.

Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data are not always necessary; more often, membership to a specific group (e.g. diet, social ‘bubble’, living area) is enough to build a successful machine learning or data mining model without overfitting it. Therefore, in this article we propose an approach to building taxonomies using clustering to replace detailed data from large heterogenous data sets from different sources, while improving interpretability. We used the GISTAR study data base that holds exhaustive self-assessment questionnaire data to demonstrate this approach in the task of differentiating between H. pylori positive and negative study participants, and assessing their potential risk factors. We have compared the results of taxonomy-based classification to the results of classification using raw data. Results Evaluation of our approach was carried out using 6 classification algorithms that induce rule-based or tree-based classifiers. The taxonomy-based classification results show no significant loss in information, with similar and up to 2.5% better classification accuracy. Information held by 10 and more attributes can be replaced by one attribute demonstrating membership to a cluster in a hierarchy at a specific cut. The clusters created this way can be easily interpreted by researchers (doctors, epidemiologists) and describe the co-occurring features in the group, which is significant for the specific task. Conclusions While there are always features and measurements that must be used in data analysis as they are, the use of taxonomies for the description of study subjects in parallel allows using membership to specific naturally occurring groups and their impact on an outcome. This can decrease the risk of overfitting (picking attributes and values specific to the training set without explaining the underlying conditions), improve the accuracy of the models, and improve privacy protection of study participants by decreasing the amount of specific information used to identify the individual.

Florian Köhler, Felix Bormann, Günter Raddatz et al.

Abstract Background Hutchinson-Gilford progeria syndrome (HGPS) is a progeroid disease characterized by the early onset of age-related phenotypes including arthritis, loss of body fat and hair, and atherosclerosis. Cells from affected individuals express a mutant version of the nuclear envelope protein lamin A (termed progerin) and have previously been shown to exhibit prominent histone modification changes. Methods Here, we analyze the possibility that epigenetic deregulation of lamina-associated domains (LADs) is involved in the molecular pathology of HGPS. To do so, we studied chromatin accessibility (Assay for Transposase-accessible Chromatin (ATAC)-see/-seq), DNA methylation profiles (Infinium MethylationEPIC BeadChips), and transcriptomes (RNA-seq) of nine primary HGPS fibroblast cell lines and six additional controls, two parental and four age-matched healthy fibroblast cell lines. Results Our ATAC-see/-seq data demonstrate that primary dermal fibroblasts from HGPS patients exhibit chromatin accessibility changes that are enriched in LADs. Infinium MethylationEPIC BeadChip profiling further reveals that DNA methylation alterations observed in HGPS fibroblasts are similarly enriched in LADs and different from those occurring during healthy aging and Werner syndrome (WS), another premature aging disease. Moreover, HGPS patients can be stratified into two different subgroups according to their DNA methylation profiles. Finally, we show that the epigenetic deregulation of LADs is associated with HGPS-specific gene expression changes. Conclusions Taken together, our results strongly implicate epigenetic deregulation of LADs as an important and previously unrecognized feature of HGPS, which contributes to disease-specific gene expression. Therefore, they not only add a new layer to the study of epigenetic changes in the progeroid syndrome, but also advance our understanding of the disease’s pathology at the cellular level.

Matheus Melo Pithon, Leticia Sant'Anna, Ana Andrade et al.

Introdução: os modelos digitais são alternativas para o uso de modelos ortodônticos em gesso. Devido a sua importância no dignostico, faz-se necessário averiguar a precisão dos softwares modelos ortodônticos digitais disponiveis.  Objetivo: evidenciar qual software de modelos ortodônticos digitais possui maior confiabilidade. Material e métodos: foi realizada busca sistemática nas seguintes bases de dados eletrônicas: Scopus, PubMed, Web of Science, Embase e Cochrane, Grey Literature e Clinical Trials, sem limitações quanto ao ano de publicação ou idioma. Foram incluídos estudos laboratoriais que utilizaram softwares destinados a geração de modelos ortodônticos digitais, comparando-os com modelos ortodônticos em gesso. Após seleção por título e resumo, os artigos potencialmente elegíveis foram lidos na íntegra. A qualidade metodológica e o risco de viés dos artigos incluídos foram avaliados de acordo com as descrições dos modelos, técnicas de medição e análises estatísticas. A qualidade metodológica foi classificada em alta, moderada ou baixa. Resultados: 13.333 artigos foram encontrados nas bases de dados utilizadas. Após a aplicação dos critérios de elegibilidade e remoção de duplicações, restaram apenas 41 artigos. 29 foram considerados de qualidade moderada e 12 de alta qualidade. A classificação quanto à confiabilidade variou de menos confiaveis, equivalentes e a mais confiaveis. Apresentando diferenças estatisticas em suas mensurações (p<0.05), sem significância clínica. Conclusão: os modelos ortodônticos digitais apresentaram mensurações acuradas, reprodutíveis e confiáveis quando comparado ao método convencional utilizando modelos de gesso.

Bilgin Timuralp, Baki Komşuoğlu

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R. E. Lane, D. Korbie, M. M. Hill et al.

Abstract Extracellular vesicles (EVs) are small, lipid-bound particles containing nucleic acid and protein cargo which are excreted from cells under a variety of normal and pathological conditions. EVs have garnered substantial research interest in recent years, due to their potential utility as circulating biomarkers for a variety of diseases, including numerous types of cancer. The following review will discuss the current understanding of the form and function of EVs, their specific role in cancer pathogenesis and their potential for non-invasive disease diagnosis and/or monitoring. This review will also highlight several key issues for this field, including the importance of implementing robust and reproducible sample handling protocols, and the challenge of extracting an EV-specific biomarker signal from a complex biological background.

H. Crebolder, J. Heyrman

S. Skootsky, B. Jaeger, R. Oye