Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence, Predictive Factors, and Outcomes of Respiratory Failure in Children With Pneumonia Admitted in a Developing Country

Background Pneumonia has been the leading infectious cause of morbidity and mortality in children under 5 years of age for the last several decades. Although most of these deaths occur due to respiratory failure, published data are limited regarding predicting factors and outcomes of respiratory failure in children hospitalized with pneumonia or severe pneumonia. Objective This study aimed to explore the prevalence, predicting factors, and outcomes of respiratory failure in children under-five with pneumonia or severe pneumonia. Methods In this retrospective chart analysis, we enrolled children under 5 years of age hospitalized with pneumonia or severe pneumonia in the Dhaka Hospital of International Centre for Diarrheal Disease Research, Bangladesh (icddr,b) between August 2013 and December 2017. Comparisons were made between children with respiratory failure (n = 212) and those without respiratory failure (n = 4,412). Respiratory failure was defined when the oxygen saturation/fraction of inspired oxygen (SpO2/FiO2) was <315. Results A total of 4,625 children with pneumonia or severe pneumonia were admitted during this study period. Among them, 212 (4.6%) children developed respiratory failure and formed the case group. A total of 4,412 (95.3%) children did not develop respiratory failure and formed the comparison group. In logistic regression analysis, after adjusting with potential confounders, severe sepsis [adjusted odds ratio (aOR): 12.68, 95% CI: 8.74–18.40], convulsion (aOR: 4.52, 95% CI: 3.06–6.68), anemia (aOR: 1.76, 95% CI: 1.20–2.57), and severe underweight (aOR: 1.97, 95% CI: 1.34–2.89) were found to be independently associated with respiratory failure. As expected, children with respiratory failure more often had fatal outcome than without respiratory failure (74, 1%, p < 0.001). Conclusion The results of our analyses revealed that prevalence of respiratory failure was 4.6% among under-five children hospitalized for pneumonia or severe pneumonia. Severe sepsis, convulsion, anemia, and severe underweight were the independent predictors for respiratory failure in such children and their case-fatality rate was significantly higher than those without respiratory failure. Early recognition of these predicting factors of respiratory failure may help clinicians imitating prompt treatment that may further help to reduce deaths in such children, especially in resource-limited settings.
Inflammatory Mediators in Atherosclerotic Vascular Remodeling

Atherosclerotic vascular disease remains the most common cause of ischemia, myocardial infarction, and stroke. Vascular function is determined by structural and functional properties of the arterial vessel wall, which consists of three layers, namely the adventitia, media, and intima. Key cells in shaping the vascular wall architecture and warranting proper vessel function are vascular smooth muscle cells in the arterial media and endothelial cells lining the intima. Pathological alterations of this vessel wall architecture called vascular remodeling can lead to insufficient vascular function and subsequent ischemia and organ damage. One major pathomechanism driving this detrimental vascular remodeling is atherosclerosis, which is initiated by endothelial dysfunction allowing the accumulation of intimal lipids and leukocytes. Inflammatory mediators such as cytokines, chemokines, and modified lipids further drive vascular remodeling ultimately leading to thrombus formation and/or vessel occlusion which can cause major cardiovascular events. Although it is clear that vascular wall remodeling is an elementary mechanism of atherosclerotic vascular disease, the diverse underlying pathomechanisms and its consequences are still insufficiently understood.
Discrete Biochemical Systems Theory

Almost every biomedical systems analysis requires early decisions regarding the choice of the most suitable representations to be used. De facto the most prevalent choice is a system of ordinary differential equations (ODEs). This framework is very popular because it is flexible and fairly easy to use. It is also supported by an enormous array of stand-alone programs for analysis, including many distinct numerical solvers that are implemented in the main programming languages. Having selected ODEs, the modeler must then choose a mathematical format for the equations. This selection is not trivial as nearly unlimited options exist and there is seldom objective guidance. The typical choices include ad hoc representations, default models like mass-action or Lotka-Volterra equations, and generic approximations. Within the realm of approximations, linear models are typically successful for analyses of engineered systems, but they are not as appropriate for biomedical phenomena, which often display nonlinear features such as saturation, threshold effects or limit cycle oscillations, and possibly even chaos. Power-law approximations are simple but overcome these limitations. They are the key ingredient of Biochemical Systems Theory (BST), which uses ODEs exclusively containing power-law representations for all processes within a model. BST models cover a vast repertoire of nonlinear responses and, at the same time, have structural properties that are advantageous for a wide range of analyses. Nonetheless, as all ODE models, the BST approach has limitations. In particular, it is not always straightforward to account for genuine discreteness, time delays, and stochastic processes. As a new option, we therefore propose here an alternative to BST in the form of discrete Biochemical Systems Theory (dBST). dBST models have the same generality and practicality as their BST-ODE counterparts, but they are readily implemented even in situations where ODEs struggle. As a case study, we illustrate dBST applied to the dynamics of the aryl hydrocarbon receptor (AhR), a signal transduction system that simultaneously involves time delays and stochasticity.
Particle Size and Internal Structure of Deformed Coal: Microstructure and Adsorption/Desorption Characteristics of CO2 and CH4

Structural deformation has a very important effect on the particle size and adsorption/desorption properties of coal, which is widely distributed in China, but there are few studies in this area. The effects of particle size and internal structure on the pores and adsorption properties of deformed coal were studied, and the influence of structural deformation was analyzed. Eight undeformed and deformed coal samples were progressively crushed from 0.12 to 0.15 mm (100–120 mesh), 0.18–0.25 mm (60–80 mesh), and 0.42–0.84 mm (20–40 mesh), and subsequently, adsorption/desorption characteristics of CO2 and CH4 and pore structure analyses were performed on all the grain size fractions. The coal size fraction has a slightly smaller influence on CO2 adsorption than on CH4 adsorption. Deformation can promote gas desorption, which increases as the deformation increases. Moreover, deformation can reduce the effect of granularity and internal structure on gas adsorption capacities. The 60–80 mesh is suggested to be the optimal size for deformed coal to achieve the ideal adsorption/desorption effect without eliminating the influence of structural deformation. However, below 100–120 mesh is recommended to reduce the impact of structural deformation on data processing and analysis when the sample contains both deformed and undeformed coals.
Preferences for Income Redistribution in Unequal Contexts: Changes in Latin America Between 2008 and 2018

In a developing and highly unequal region like Latin America, it is crucial to understand the determinants that affect people's support for redistribution of resources from the state. A series of theories focused on self-interest have continuously established a negative link between people's income and their support for the reduction of inequalities through redistribution. Despite this, the evidence is scarce and sometimes contradictory while its study in Latin America is almost non-existent. Using data from the LAPOP Survey between 2008 and 2018, a longitudinal dimension is considered for the first time in the measurement of Latin American redistributive preferences, using hybrid multilevel regression models. In contrast to the evidence from studies conducted in other regions, the results reveal that in Latin America it is not possible to detect a clear association between income and redistributive preferences at specific times, but it is possible when changes occur in countries' levels of inequality and economic development. Likewise, other elements that consistently affect preferences are evident, such as educational level, political ideology, and confidence in the political system. In light of this evidence, comparisons are made with previous research findings in industrialized countries, challenging rationalist theories of justice and solidarity.
Altered EEG Microstates Dynamics During Cue-Induced Methamphetamine Craving in Virtual Reality Environments

Background Cue-induced craving is widely considered to be the most important risk factor for relapse during abstinence from methamphetamine (Meth). There is limited research regarding electroencephalography (EEG) microstates of Meth-dependent patients under exposure to drug-related cues. Our objective was to investigate whether EEG microstate temporal characteristics could capture neural correlates of cue-induced Meth craving in virtual reality (VR) environments. Methods EEG recordings of 35 Meth-dependent patients and 30 healthy controls (HCs) were collected during eyes-open state and cue-induced state, respectively. Group differences and condition differences in temporal parameters of four microstate classes were compared. Results The results demonstrated the greater presence of microstate B in both Meth-dependent patients and HCs during the cue-induced condition, compared to resting state. In addition, for Meth-dependent patients, microstate C occurred significantly less frequently, along with a tendency of increased occurrence for class D during the cue-induced condition, compared to resting state. However, the change direction of class C and class D in HCs was completely opposite to that of Meth-dependent patients. The cue-induced condition also elicited different changes in transition probability between Meth-dependent patients and HCs. Conclusion This study explored the features of EEG microstates in Meth-dependent patients during the cue-induced condition, which can improve our understanding of Meth addiction and contribute to the development of effective assessments and intervention tools.
Deep Learning Model for Classifying Metastatic Epidural Spinal Cord Compression on MRI

Background Metastatic epidural spinal cord compression (MESCC) is a devastating complication of advanced cancer. A deep learning (DL) model for automated MESCC classification on MRI could aid earlier diagnosis and referral. Purpose To develop a DL model for automated classification of MESCC on MRI. Materials and Methods Patients with known MESCC diagnosed on MRI between September 2007 and September 2017 were eligible. MRI studies with instrumentation, suboptimal image quality, and non-thoracic regions were excluded. Axial T2-weighted images were utilized. The internal dataset split was 82% and 18% for training/validation and test sets, respectively. External testing was also performed. Internal training/validation data were labeled using the Bilsky MESCC classification by a musculoskeletal radiologist (10-year experience) and a neuroradiologist (5-year experience). These labels were used to train a DL model utilizing a prototypical convolutional neural network. Internal and external test sets were labeled by the musculoskeletal radiologist as the reference standard. For assessment of DL model performance and interobserver variability, test sets were labeled independently by the neuroradiologist (5-year experience), a spine surgeon (5-year experience), and a radiation oncologist (11-year experience). Inter-rater agreement (Gwet’s kappa) and sensitivity/specificity were calculated. Results Overall, 215 MRI spine studies were analyzed [164 patients, mean age = 62 ± 12(SD)] with 177 (82%) for training/validation and 38 (18%) for internal testing. For internal testing, the DL model and specialists all showed almost perfect agreement (kappas = 0.92–0.98, p < 0.001) for dichotomous Bilsky classification (low versus high grade) compared to the reference standard. Similar performance was seen for external testing on a set of 32 MRI spines with the DL model and specialists all showing almost perfect agreement (kappas = 0.94–0.95, p < 0.001) compared to the reference standard. Conclusion A DL model showed comparable agreement to a subspecialist radiologist and clinical specialists for the classification of malignant epidural spinal cord compression and could optimize earlier diagnosis and surgical referral.
Comparison of a Personalized Prostate Biopsy Pattern With Traditional Transrectal Prostate Biopsy: Different Cancer Detection Rate

Background: In terms of prostate biopsy approaches, it is difficult to reach the ventral central region of the prostate with the traditional transrectal prostate biopsy, while with the transperineal biopsy, the tumor in the dorsolateral region of the prostate is easily missed. However, until now, no studies have investigated the biopsy accuracy in the selective application of transrectal or transperineal biopsies according to the lesion site. Methods: We developed a personalized prostate biopsy pattern and the biopsy approach was selected individually according to the lesion site. We compared it with the traditional transrectal prostate biopsy method to evaluate the efficiency. Patients (n = 351) who underwent prostate biopsy at Qilu Hospital of Shandong University from January 2018 to October 2020 were divided into two groups, including the traditional transrectal prostate biopsy group (n = 236) and the personalized group (n = 115). The data from patients, including clinical characteristics, biopsy results, and complications, were analyzed. Results: The clinical characteristics of the two groups were similar. The total detection rate of prostate cancer in the personalized group was 49.6%, which was significantly higher than 38.1% in the traditional group (p = 0.023). When prostate-specific antigen was <20 ng/ml, the detection rates of the two groups were 30.4 and 19.3%, respectively (p = 0.039). The PI-RADS was positively associated with high-grade prostate cancer in the personalized group. Patients with complications in the traditional transrectal systematic method group accounted for 6.8%, and those in the personalized group complications through the transrectal and transperineal approaches accounted for 7.1 and 4.1%, respectively. The most common complications in the transrectal group were fever and rectal bleeding, and those in the transperineal group were hematuria and urinary retention. Conclusion: Compared with traditional transrectal prostate biopsy, the personalized biopsy pattern improved the detection rate of prostate cancer. The complications of the transrectal approach were much higher than those in the transperineal approach.
Responsive Behaviors and Pain Management in Hospital Dementia Care: A Before and After Comparison of the “Serial Trial Intervention”

Purpose Responsive behavior, often referred to as behavioral and psychological symptoms of dementia (BPSD), is among the most critical disorders in dementia whereby nursing personnel in hospitals are increasingly confronted with such symptoms. The purpose was to reduce the level of BPSD in an acute hospital environment through a stepwise procedure followed by the initiation of a needs-oriented treatment. Methods An open, prospective, interventional study with before-after comparisons was used to implement “Serial Trial Intervention” (STI) in three hospital wards (internal medicine, surgery, geriatric) after its adaption for hospital setting which was supplemented with a detailed pain assessment. Participants were 65 years and older. Potential causes of BPSD were clarified in a stepwise procedure and, if possible, eliminated. The primary outcome was the reduction in BPSD measured by the Neuropsychiatric Inventory (NPI-Q-12) while secondary outcomes were through the use of non-pharmacological and pharmacological interventions. Results No significant reduction in NPI-Q-12 could be found. However, significantly more mobilizations and changes of position were carried out. Higher antipsychotic use was seen in the after-groups presumably due to the higher rates of delirium and cognitive impairment. Furthermore, the data showed no increase in analgesic use. Conclusion No significant reduction in NPI-Q-12 was observed in the before-after study. The use of antipsychotics even increased most probably due to a higher incidence of deliriousness in the after-group. However, STI seemed to improve attention to underlying causes of BPSD as well as pain. Proof that STI leads to NPI-Q-12 reduction in hospitals is still pending.
Comparative Gut Microbiome in Trachypithecus leucocephalus and Other Primates in Guangxi, China, Based on Metagenome Sequencing

The Trachypithecus leucocephalus (white-headed langur) is a highly endangered, karst-endemic primate species, inhabiting the karst limestone forest in Guangxi, Southwest China. How white-headed langurs adapted to karst limestone and special dietary remains unclear. It is the first time to study the correlation between the gut microbiome of primates and special dietary, and environment in Guangxi. In the study, 150 fecal samples are collected from nine primates in Guangxi, China. Metagenomic sequencing is used to analyze and compare the gut microbiome composition and diversity between white-headed langurs and other primates. Our results indicate that white-headed langurs has a higher diversity of microbiome than other primates, and the key microbiome are phylum Firmicutes, class Clostridia, family Lachnospiraceae, and genera Clostridiates and Ruminococcus, which are related to the digestion and degradation of cellulose. Ten genera are significantly more abundant in white-headed langurs and François’ langur than in other primates, most of which are high-temperature microbiome. Functional analysis reveals that energy synthesis-related pathways and sugar metabolism-related pathways are less abundant in white-headed langurs and François’ langur than in other primates. This phenomenon could be an adaptation mechanism of leaf-eating primates to low-energy diet. The gut microbiome of white-headed langurs is related to diet and karst limestone environment. This study could serve as a reference to design conservation breeding, manage conservation units, and determine conservation priorities.
Necroptosis and Viral Myocarditis: Tumor Necrosis Factor α as a Novel Biomarker for the Diagnosis of Viral Myocarditis

Programmed cell death (PCD), including necroptosis, has emerged as a significant pathway in cardiovascular diseases. The infection of viral myocarditis (VMC) could cause cardiomyocytes degeneration, necrosis, and immune-inflammatory myocardial response. In this review, we summarized and evaluated the available evidence on the pathogenesis, molecule mechanism, diagnosis, and potential treatment strategies of viral myocarditis, with a special focus on the novel mechanism of necroptosis for cardiomyocytes death. Studies have shown that tumor necrosis factor-alpha (TNF-α) is an important cytokine involved in the activation of necroptosis; an elevated level of TNF-α is continually reported in patients suffering from VMC, implicating its involvement in the pathogenesis of VMC. It is of great interest to explore the clinical implication of TNF-α. We subsequently conducted a meta-analysis on the efficacy of serum TNF-α expression level and its diagnostic accuracy on acute viral myocarditis detection. Taken together, the review demonstrates a compelling role of necroptosis involved in the pathogenesis of VMC. Further, applying TNF-α as a serological marker for the diagnosis of VMC may be a useful strategy.
Performance Monitoring, Subordinate’s Felt Trust and Ambidextrous Behavior; Toward a Conceptual Research Framework

The present research proposes an electronic performance monitoring framework based on ambidextrous leadership and social exchange theories in a dynamic environment. It reviews and integrates essential literature on electronic performance management (EPM), trust, and ambidextrous behavior. For this, authors have reviewed relevant literature on various themes and underpinned them for managing EPM. The study emphasizes individuals’ psychological foundations that demonstrate trust behavior and relationship with their leaders. Eventually, through an ambidextrous approach, managers gain steady performance and relationships with their subordinates through EPM. The study shows that ambidexterity benefits organizations; it enhances employees’ resources, resulting in enhanced performance that leads to the performance of an organization. The authors discuss the theoretical as well as practical implications of this study.
Autoantibody Landscape Revealed by Wet Protein Array: Sum of Autoantibody Levels Reflects Disease Status

Autoantibodies are found in various pathological conditions such as autoimmune diseases, infectious diseases, and malignant tumors. However their clinical implications have not yet been fully elucidated. Herein, we conducted proteome-wide autoantibody screening and quantification with wet protein arrays consisting of proteins synthesized from proteome-wide human cDNA library (HuPEX) maintaining their three-dimensional structure. A total of 565 autoantibodies were identified from the sera of three representative inflammatory disorders (systemic sclerosis, psoriasis, and cutaneous arteritis). Each autoantibody level either positively or negatively correlated with serum levels of C-reactive protein, the best-recognized indicator of inflammation. In particular, we discovered total levels of a subset of autoantibodies correlates with the severity of clinical symptoms. From the sera of malignant melanoma, 488 autoantibodies were detected. Notably, patients with metastases had increased overall autoantibody production compared to those with tumors limiting to the primary site. Collectively, proteome-wide screening of autoantibodies using the in vitro proteome can reveal the “autoantibody landscape” of human subjects and may provide novel clinical biomarkers.