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Predictive model for feeding intolerance in neonates with hypoxic ischemic encephalopathy during therapeutic hypothermia
Ventilatory response and delirium risk in hospitalised patients with acute hypoxia due to COVID-19
Comparison of IL-10 gene promoter polymorphisms and haplotypes between high-grade squamous intraepithelial lesions or cervical cancer and negative cervical cytology
Effect of iPS cell culture medium on the differentiation potential of induced cardiac tissues
Abstract The present study focused on the culture medium of induced pluripotent stem cells (iPSCs) prior to the use of cardiomyocytes differentiation induction medium (pre-culture medium). Seven types (Nos. 1-7) of StemFit AK03 medium (Ajinomoto) for clinical iPSCs with varying compositions were prepared as pre-culture medium. The cardiac muscle troponin T (cTnT) positivity of No. 1 (StemFit AK03 medium) was 84%, No. 3 (similar to E8 medium) was 89%, No. 2 (similar to E8 medium) was 91%, No. 5 (similar to EB Formation medium) was 95%, when using differentiation induction medium prepared with known components available for clinical cell production. The formation of cardiac tissues was assessed by evaluating the expression levels of specific markers, including cTnT, atrial natriuretic peptides (ANP), and pro-B-type natriuretic peptide (proBNP). The results demonstrated that cardiac tissue with high protein expression levels of cTnT and ANP was formed when similar to E8 medium as pre-culture medium.
Heatwave types and frequency alter multigenerational ecological response of wheat aphids
Abstract Heatwaves are predicted to become more frequent under climate change. However, how different heatwave types and frequencies are linked to multigenerational ecological response remains unclear. Thus, using three heatwave types (34 °C/180 min, 36 °C/30 min, and 38 °C/10 min) and three frequencies (1, 3, and 5 days), we tested the effects of heat stress on the life history traits of Sitobion avenae. Both heatwave type and frequency altered aphid fitness in a generation-specific manner. In maternal generations, at a 1-day frequency, 34℃/180 min exhibited the greatest effects on reproduction and longevity. However, as frequency increased, differences across various heat stress treatments diminished. Conversely, in offspring, 34℃/180 min had minimal effects on demographic parameters. Offspring performance was poorest at the 3-day frequency, indicating that a longer frequency for the mother does not necessarily mean a greater effect on the offspring. Changes in aphid fitness due to heatwave type and frequency are driven by asymmetric effects of heatwaves on aphid life history. Furthermore, understanding how heat stresses affect the life history of aphids is important for predicting the impacts of climate change at the generational level because climate effects on natural populations cannot be predicted simply through changes in mean temperature.
A sustainable Ru catalyzed aerobic oxidation based on high loading magnetic ionic nanoparticles network
Vitamin and trace elements imbalance are very common in adult patients with newly diagnosed Celiac disease
High-throughput sequencing-based study on bacterial community structure and functional prediction of fermented bean curd from different regions in China
Enzymeless electrochemical detection of hydrogen peroxide using NiO octahedron decorated 3D graphene hydrogel
Abstract Nowadays, electrochemical biosensors have gained extensive consensus to detect a wide variety of analytes such as hydrogen peroxide (H2O2), glucose, dopamine, uric acid, and so on. However, the detection of H2O2 is more and more important because H2O2 plays a vital role in our daily life. Hence, a new nonenzymatic H2O2 biosensor was developed by decorating NiO octahedrons on the 3-dimensional graphene hydrogel (3DGH). The NiO octahedrons were prepared using a mesoporous silica SBA-15 as a hard template. Then, different amounts of NiO octahedrons self-assembled with 3DGH during hydrothermal method. The performance of different prepared nanostructures as H2O2 biosensors electrodes was determined by the cyclic voltammetry and chronoamperometry tests. Various physicochemical methods such as FE-SEM, HR-TEM, XRD, TGA and Raman were utilized to characterize the morphology and structure properties of the as-prepared samples. The electrochemical sensing of H2O2 for the proposed biosensor electrodes are investigated, and the 3DGH/NiO nanocomposite electrode with NiO content of 25% displays high sensitivity with wide linear range and low detection limit, as well as good selectivity, reproducibility and long-term stability. Finally, the analytical utilities of the 3DGH/NiO25 proposed electrode were conducted to detect H2O2 in real products of milk samples.
School engagement and student burnout among medical and health science students in Saudi Arabia-cross-sectional study
Abstract School engagement and burnout are contributing factors influencing academic student performance. Student burnout is a serious concern in higher education, where it can result in poor mental and physical health and school dropout. Although recent studies indicate the significance of the relationship between academic engagement and achievement, little is known about how academic engagement and burnout affect medical sciences students in the Madinah region of Saudi Arabia. We aimed to assess the level of school engagement and student burnout among medical and health science students in Madinah, Saudi Arabia. Factors associated with school engagement and student burnout were also explored. A cross-sectional data of 297 students last year medical and health science undergraduate students who were recruited from Taibah University, Madinah. The online survey was shared with students to collect data on sample characteristics, school engagement (using the modified version of the University Student Engagement Inventory), and student burnout (using the modified version of the Maslach Burnout Inventory Student Survey). The data showed that 57.5% of medical science students in the sample were academically engaged, and 55.9% experienced burnout, indicating a moderate to high level of student engagement and burnout. However, there was no correlation between school engagement and student burnout (r = 0.27) among the sample in this study. Nevertheless, school engagement was affected by factors such as student living status (p = 0.036), dropout thoughts (p = 0.008), and cumulative GPA (p = 0.001). In addition to dropout thoughts and GPA, the student burnout level was also predicted by the college (p = 0.012), program duration (p < 0.001), sex (p = 0.016), and average sleeping hours per day (p = 0.019). These results imply that school engagement and burnout may not be directly related or opposites and can interact in a variety of ways depending on factors including student personality and lifestyle, as well as academic and institutional influences. Many factors were linked to school engagement and student burnout. Interventions that aim to reduce student burnout should be tailored based on many factors including program duration and sex of students.
The central lymph node dissection using carbon nanoparticle in transoral vestibular approach endoscopic thyroid surgery
HCF-1 as a key modulator of OGT function and O-GlcNAcylation in the liver
A multinational cross-sectional study on the prevalence and predictors of long COVID across 33 countries
Abstract The symptoms of long COVID (LC) can be debilitating and may be associated with anxiety, social stigma, and quality of life deterioration. Identifying patients at risk of LC is important to offer follow-up care and plan population-level public health measures. The current multinational study aimed to assess the prevalence and predictors of LC in the general population. We conducted an online, multinational, cross-sectional survey between April 2022 and January 2023, targeting participants 18 years and older with a previously confirmed COVID-19 infection. We used convenience sampling to recruit participants through an online Google form. We collected demographic data, past medical history, infection details, post-COVID-19 symptoms, and quality of life. Responses were then translated into English. LC was defined as per the World Health Organization. A single-variable analysis was conducted to identify factors significantly associated with LC development. Following the removal of multicollinear variables, a generalized linear model was established to estimate the contribution of different predictors to LC occurrence. A total of 11,801 respondents from 33 countries were included in the analysis. The mean age for participants was 32.7 ± 12.8 years, with 61% being females. BMI averaged 25.2 ± 4.8 across participants, and 14.8% of them were smokers. Seventy-eight percent of participants reported receiving the COVID-19 vaccine. Respondents with PCR-confirmed COVID-19 were then categorized into those with LC (N = 2335, 19.8%) and without LC (N = 9466 individuals, 80.2%). Our model identified 25 significant predictors. The predictors of higher LC risk included ICU admission (OR 2.08; 95% CI 1.36, 3.18; P = 0.001), female sex (OR 1.8; 95% CI 1.61, 2.02; P < 0.001), fatigue during the infection (OR 1.6; 95% CI 1.43, 1.78; P < 0.001), identifying as Hispanic (OR 1.53; 95% CI 1.26, 1.85; P < 0.001), and pre-existing gastrointestinal disease (OR 1.48; 95% CI 1.22, 1.8; P < 0.001). In conclusion, we identified key LC predictors, including ICU admission, female sex, and acute fatigue as primary risk factors, while African American and Asian ethnicities and receiving even one dose of vaccination demonstrated protective effects.
Rhizosphere effects on cadmium fractionation in contaminated soils: a comparative study of ultisols and alfisols
Melanin-like nanofibers with highly ordered structures achieve ultrahigh specific electromagnetic interference shielding efficiency
Open-source, high performance miniature 2-photon microscopy systems for freely behaving animals
Abstract Here we describe the UCLA 2P Miniscope, an open-source miniature 2-photon microscope capable of recording calcium dynamics from neurons in deep structures and from dendrites over a 445 µm × 380 µm field of view. The system utilizes two on-board silicon-based photon detectors for approximately 4-fold greater light collection compared to an optical fiber bundle-based approach. The microscope can electronically focus within a 150 µm range at a native working distance of 720 µm. To test the 2P Miniscope, we recorded calcium dynamics from place cells in hippocampus, resolved calcium transients from dendrites in retrosplenial cortex and we recorded dentate granule cell activity at a depth of over 620 µm, through an intact hippocampus during open field behavior. The miniature microscope itself and all supporting equipment are open-source and all files needed for building the scope can be accessed through the Golshani Lab GitHub repository.
Using an ordinary differential equation model to separate rest and task signals in fMRI
Abstract Cortical activity results from the interplay between network-connected regions that integrate information and stimulus-driven processes originating from sensory motor networks responding to specific tasks. Separating the information due to each of these components has been challenging, and the relationship as measured by fMRI in each of these cases Rest (network) and Task (stimulus-driven) remains a significant open question in the study of large-scale brain dynamics. In this study, we develop a network ordinary differential equation (ODE) model using advanced system identification tools to analyze fMRI data from both rest and task conditions. We demonstrate that task-specific ODEs are essentially a subset of rest-specific ODEs across four different tasks from the Human Connectome Project. By assuming that task activity is a relative complement of rest activity, our model significantly improves predictions of reaction times on a trial-by-trial basis, leading to a 9% increase in explanatory power ( R 2 ) across the 14 sub-tasks tested. We have additionally shown that these results hold for predicting missing trials and accuracy on a per individual basis as well as classifying Tasks trajectories or resulting dynamic Task functional connectivity. Our findings establish the principle of the Active Cortex Model, which posits that the cortex is always active and that Rest State encompasses all processes, while certain subsets of processes get elevated to perform specific task computations. Thus, this study is an important milestone in the development of the fMRI equation - to causally link large-scale brain activity, brain structural connectivity, and behavioral variables within a single framework.
Voltage sensor conformations induced by LQTS-associated mutations in hERG potassium channels
Abstract Voltage sensors are essential for electromechanical coupling in hERG K + channels, critical to cardiac rhythm. These sensors respond to membrane potential changes by moving within the transmembrane electric field. Mutations in hERG voltage-sensing arginines, associated with Long-QT syndrome, alter channel gating, though underlying mechanisms remain unclear. Using live-cell fluorescence lifetime imaging microscopy, transition metal FRET, an improved dual stop-codon-mediated strategy for noncanonical amino-acid incorporation, and molecular dynamics simulations, we identify intermediate voltage-sensor conformations induced by neutralizing key arginines in the charge transfer center. Phasor plot analysis of lifetime data reveals multiple voltage-dependent FRET states in these mutants, in contrast to the single high-FRET state observed in controls. These intermediate FRET states reflect distinct conformations of the voltage sensor, corresponding to predicted structures of voltage sensors in molecular dynamics simulations. This study provides insights into cardiac channelopathies, highlighting a structural mechanism that impairs voltage sensing in cardiac arrhythmias.