Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrin α5 Is Regulated by miR-218-5p in Endothelial Progenitor Cells

Significance Statement Kidney endothelial cells are sensitive to hypoxic injury. This cell type expresses integrin α5 (ITGA5), which is essential to the Tie2 signaling cascade. The microRNA miR-218 is known to increase after hypoxia, but the microRNA’s role in regulating ITGA5 protein synthesis is unclear. In this study, the authors found that miR-218-5p specifically binds to ITGA5 mRNA in human kidney-derived endothelial progenitor cells (EPCs). In an animal model of ischemia/reperfusion injury, cells pretreated with an miR-218-5p mimic were delivered efficiently, whereas an animal model containing an miR-218-2 deletion specific to angioblasts resulted in kidney dysgenesis and impaired migration of mouse kidney-derived EPCs. Understanding the regulation of prominent signaling pathways in EPCs may inform optimization of therapeutic techniques for addressing kidney endothelial cell injury. Visual Abstract Background Endothelial cell injury is a common nidus of renal injury in patients and consistent with the high prevalence of AKI reported during the coronavirus disease 2019 pandemic. This cell type expresses integrin α5 (ITGA5), which is essential to the Tie2 signaling pathway. The microRNA miR-218-5p is upregulated in endothelial progenitor cells (EPCs) after hypoxia, but microRNA regulation of Tie2 in the EPC lineage is unclear. Methods We isolated human kidney-derived EPCs (hkEPCs) and surveyed microRNA target transcripts. A preclinical model of ischemic kidney injury was used to evaluate the effect of hkEPCs on capillary repair. We used a genetic knockout model to evaluate the effect of deleting endogenous expression of miR-218 specifically in angioblasts. Results After ischemic in vitro preconditioning, miR-218-5p was elevated in hkEPCs. We found miR-218-5p bound to ITGA5 mRNA transcript and decreased ITGA5 protein expression. Phosphorylation of 42/44 MAPK decreased by 73.6% in hkEPCs treated with miR-218-5p. Cells supplemented with miR-218-5p downregulated ITGA5 synthesis and decreased 42/44 MAPK phosphorylation. In a CD309-Cre/miR-218-2-LoxP mammalian model (a conditional knockout mouse model designed to delete pre-miR-218-2 exclusively in CD309+ cells), homozygotes at e18.5 contained avascular glomeruli, whereas heterozygote adults showed susceptibility to kidney injury. Isolated EPCs from the mouse kidney contained high amounts of ITGA5 and showed decreased migratory capacity in three-dimensional cell culture. Conclusions These results demonstrate the critical regulatory role of miR-218-5p in kidney EPC migration, a finding that may inform efforts to treat microvascular kidney injury via therapeutic cell delivery.
Stem cells to reverse aging

Abstract As human life expectancy continues to increase and the birth rate continues to decline, the phenomenon of aging is becoming more prominent worldwide. Therefore, addressing the problems associated with global aging has become a current research focus. The main manifestations of human aging are structural degeneration and functional decline of aging tissues and organs, quality of life decline, decreased ability to resist diseases, and high incidence rates of a variety of senile degenerative diseases. Thus far, no ideal treatments have been found. Stem cell (SC) therapies have broad application prospects in the field of regenerative medicine due to the inherent biological characteristics of SCs, such as their plasticity, self-renewal, and multidirectional differentiation potential. Thus, SCs could delay or even reverse aging. This manuscript reviews the causes of human aging, the biological characteristics of SCs, and research progress on age reversal.
Understanding the preterm human heart: What do we know so far?

Globally, preterm birth affects more than one in every 10 live births. Although the short‐term cardiopulmonary complications of prematurity are well known, long‐term health effects are only now becoming apparent. Indeed, preterm birth has been associated with elevated cardiovascular morbidity and mortality in adulthood. Experimental animal models and observational human studies point toward changes in heart morphology and function from birth to adulthood in people born preterm that may contribute to known long‐term risks. Moreover, recent data support the notion of a heterogeneous cardiac phenotype of prematurity, which is likely driven by various maternal, early, and late life factors. This review aims to describe the early fetal‐to‐neonatal transition in preterm birth, the different structural and functional changes of the preterm human heart across developmental stages, as well as potential factors contributing to the cardiac phenotype of prematurity.
The Effect of Low‐level Laser Therapy on VEGF, IL‐6 Expression and Viability of Oral Squamous Cell Carcinoma Cells

Low‐level laser therapy has shown successful results in the prevention and treatment of oral mucositis. One of the concerns about low‐level lasers is their effects on remaining malignant cells in the area. Interleukin‐6 is a multifunctional cytokine that plays an important role in a wide range of biological activities in increasing tumor functions, decreasing survival and resistance to chemo‐radiotherapy. Vascular‐endothelial growth factor increases tumor vascularization. It has been shown in the previous studies that LLLT can cause an increase of IL‐6 and VEGF in some cells. The present thesis aims to study the effects of LLLT on IL‐6 and VEGF expression, as well as cell viability on OSCC cells. Tumorigenic cells of an oral squamous cell carcinoma cell line were irradiated with 3 different diode lasers, and were compared to the control group (660 nm–200 mW–4 J cm−2, 810 nm–200 mW–4 J cm−2, 940 nm–200 mW–4 J cm−2). MTT assay, ELISA and RT‐PCR were used to measure cell viability, IL‐6 and VEGF expression. Cell viability of all laser‐irradiated groups was significantly lower than the control group. VEGF expression increased in laser‐irradiated groups. This was only significant in the 810 nm group. IL‐6 protein secretion was significantly higher in all laser‐irradiated groups compared to the control group.
Social risk factors predicting outcomes of cervical myelopathy surgery.

OBJECTIVE Combinations of certain social risk factors of race, sex, education, socioeconomic status (SES), insurance, education, employment, and one's housing situation have been associated with poorer pain and disability outcomes after lumbar spine surgery. To date, an exploration of such factors in patients with cervical spine surgery has not been conducted. The objective of the current work was to 1) define the social risk phenotypes of individuals who have undergone cervical spine surgery for myelopathy and 2) analyze their predictive capacity toward disability, pain, quality of life, and patient satisfaction-based outcomes. METHODS The Cervical Myelopathy Quality Outcomes Database was queried for the period from January 2016 to December 2018. Race/ethnicity, educational attainment, SES, insurance payer, and employment status were modeled into unique social phenotypes using latent class analyses. Proportions of social groups were analyzed for demonstrating a minimal clinically important difference (MCID) of 30% from baseline for disability, neck and arm pain, quality of life, and patient satisfaction at the 3-month and 1-year follow-ups. RESULTS A total of 730 individuals who had undergone cervical myelopathy surgery were included in the final cohort. Latent class analysis identified 2 subgroups: 1) high risk (non-White race and ethnicity, lower educational attainment, not working, poor insurance, and predominantly lower SES), n = 268, 36.7% (class 1); and 2) low risk (White, employed with good insurance, and higher education and SES), n = 462, 63.3% (class 2). For both 3-month and 1-year outcomes, the high-risk group (class 1) had decreased odds (all p < 0.05) of attaining an MCID score in disability, neck/arm pain, and health-related quality of life. Being in the low-risk group (class 2) resulted in an increased odds of attaining an MCID score in disability, neck/arm pain, and health-related quality of life. Neither group had increased or decreased odds of being satisfied with surgery. CONCLUSIONS Although 2 groups underwent similar surgical approaches, the social phenotype involving non-White race/ethnicity, poor insurance, lower SES, and poor employment did not meet MCIDs for a variety of outcome measures. This finding should prompt surgeons to proactively incorporate socially conscience care pathways within healthcare systems, as well as to optimize community-based resources to improve outcomes and personalize care for populations at social risk.
Teasing apart the unique contributions of cognitive and affective predictors of math performance

Math permeates everyday life, and math skills are linked to general educational attainment, income, career choice, likelihood of full‐time employment, and health and financial decision making. Thus, researchers have attempted to understand factors predicting math performance in order to identify ways of supporting math development. Work examining individual differences in math performance typically focuses on either cognitive predictors, including inhibitory control and the approximate number system (ANS; a nonsymbolic numerical comparison system), or affective predictors, like math anxiety. Studies with children suggest that these factors are interrelated, warranting examination of whether and how each uniquely and independently contributes to math performance in adulthood. Here, we examined how inhibitory control, the ANS, and math anxiety predicted college students’ math performance (n = 122, mean age = 19.70 years). Using structural equation modeling, we find that although inhibitory control and the ANS were closely related to each other, they did not predict math performance above and beyond the effects of the other while also controlling for math anxiety. Instead, math anxiety was the only unique predictor of math performance. These findings contradict previous results in children and reinforce the need to consider affective factors in our discussions and interventions for supporting math performance in college students.
Effectiveness of repetitive transcranial magnetic stimulation on poststroke dysphagia: a meta-analysis of randomized-controlled trials

Dysphagia is a common functional impairment after stroke, resulting in aspiration of liquids, ingested foods, or oral secretions and influencing the quality of life. Noninvasive repetitive transcranial magnetic stimulation has been widely used for rehabilitation of dysphagia. The purpose of this meta-analysis was to investigate the efficacy of repetitive transcranial magnetic stimulation on poststroke swallowing impairment. Four databases were systematically searched for eligible studies from their inception to 31 September 2021. Review Manager 5.4 software was used for this meta-analysis. The bias of included randomized controlled trials was assessed using the version 2 of the Cochrane risk-of-bias tool for randomized trials. Nine randomized controlled trials involving 393 patients were included according to the selection criteria. The results revealed significant benefit of repetitive transcranial magnetic stimulation as a treatment of dysphagia following the onset of stroke, when compared with intervention without repetitive transcranial magnetic stimulation. Applying repetitive transcranial magnetic stimulation on different stimulation sites effectively improved the dysphagia of poststroke patients, and no significant difference was observed among the different stimulation sites subgroups. Our findings support repetitive transcranial magnetic stimulation as an effectively treatment of the poststroke dysphagia, especially in unilateral hemispheric stroke patients.
Respiratory support status from EHR data for adult population: classification, heuristics, and usage in predictive modeling

Abstract Objective Respiratory support status is critical in understanding patient status, but electronic health record data are often scattered, incomplete, and contradictory. Further, there has been limited work on standardizing representations for respiratory support. The objective of this work was to (1) propose a practical terminology system for respiratory support methods; (2) develop (meta-)heuristics for constructing respiratory support episodes; and (3) evaluate the utility of respiratory support information for mortality prediction. Materials and Methods All analyses were performed using electronic health record data of COVID-19-tested, emergency department-admit, adult patients at a large, Midwestern healthcare system between March 1, 2020 and April 1, 2021. Logistic regression and XGBoost models were trained with and without respiratory support information, and performance metrics were compared. Importance of respiratory-support-based features was explored using absolute coefficient values for logistic regression and SHapley Additive exPlanations values for the XGBoost model. Results The proposed terminology system for respiratory support methods is as follows: Low-Flow Oxygen Therapy (LFOT), High-Flow Oxygen Therapy (HFOT), Non-Invasive Mechanical Ventilation (NIMV), Invasive Mechanical Ventilation (IMV), and ExtraCorporeal Membrane Oxygenation (ECMO). The addition of respiratory support information significantly improved mortality prediction (logistic regression area under receiver operating characteristic curve, median [IQR] from 0.855 [0.852—0.855] to 0.881 [0.876—0.884]; area under precision recall curve from 0.262 [0.245—0.268] to 0.319 [0.313—0.325], both P < 0.01). The proposed generalizable, interpretable, and episodic representation had commensurate performance compared to alternate representations despite loss of granularity. Respiratory support features were among the most important in both models. Conclusion Respiratory support information is critical in understanding patient status and can facilitate downstream analyses.
The generalized continuous multiple step (GCMS) potential: model systems and benchmarks

The generalized continuous multiple step (GCMS) potential is presented in this work. Its flexible form allows for repulsive and/or attractive contributions to be encoded through adjustable energy and length scales. The GCMS interaction provides a continuous representation of square-well, square-shoulder potentials and their variants for implementation in computer simulations. A continuous and differentiable energy representation is required to derive forces in conventional simulation algorithms. Molecular dynamics simulations are of particular interest when considering the dynamic properties of a system. The GCMS potential can mimic other interactions with a judicious choice of parameters due to the versatile sigmoid form. In this study, our benchmarks for the GCMS representation include triangular, Yukawa, Franzese, and Lennard-Jones potentials. Comparisons made with published data on volumetric phase diagrams, liquid structure, and diffusivity from model systems are in excellent agreement.
Ontology-aware neural network: a general framework for pattern mining from microbiome data

Abstract With the rapid accumulation of microbiome data around the world, numerous computational bioinformatics methods have been developed for pattern mining from such paramount microbiome data. Current microbiome data mining methods, such as gene and species mining, rely heavily on sequence comparison. Most of these methods, however, have a clear trade-off, particularly, when it comes to big-data analytical efficiency and accuracy. Microbiome entities are usually organized in ontology structures, and pattern mining methods that have considered ontology structures could offer advantages in mining efficiency and accuracy. Here, we have summarized the ontology-aware neural network (ONN) as a novel framework for microbiome data mining. We have discussed the applications of ONN in multiple contexts, including gene mining, species mining and microbial community dynamic pattern mining. We have then highlighted one of the most important characteristics of ONN, namely, novel knowledge discovery, which makes ONN a standout among all microbiome data mining methods. Finally, we have provided several applications to showcase the advantage of ONN over other methods in microbiome data mining. In summary, ONN represents a paradigm shift for pattern mining from microbiome data: from traditional machine learning approach to ontology-aware and model-based approach, which has found its broad application scenarios in microbiome data mining.
Impact of bacterial infection and intestinal microbiome on colorectal cancer development

Abstract Accumulating evidence suggests that intestinal bacteria play an important role in the pathogenesis of colorectal cancer (CRC). Due to the complexity of the intestinal microbiome, identification of the specific causative microbial agents in CRC remains challenging, and the search for the causative microbial agents is intense. However, whether bacteria or their products can induce inflammation that results in tumorigenesis or directly causes CRC in humans is still not clear. This review will mainly focus on the progress of bacterial infection and CRC, and introduce the microbial contribution to the hallmarks of cancer. This article uses Salmonella and its chronic infection as an example to investigate a single pathogen and its role in the development of CRC, based on laboratory and epidemiological evidence. The bacterial infection leads to an altered intestinal microbiome. The review also discusses the dysfunction of the microbiome and the mechanism of host–microbial interactions, for example, bacterial virulence factors, key signaling pathways in the host, and microbial post-translational modifications in the tumorigenesis. Colonic carcinogenesis involves a progressive accumulation of mutations in a genetically susceptible host leading to cellular autonomy. Moving forward, more human data are needed to confirm the direct roles of bacterial infection in CRC development. Insights into the inhibiting infection will help to prevent cancer and develop strategies to restore the balance between host and microorganisms.
Elucidating the Size‐dependent FRET Efficiency in Interfacially Engineered Quantum Dots Attached to PBSA Sunscreen

Applying sunscreen on human skin provides photoprotection against the harmful ultraviolet (UV) radiation of the sun. Sunscreen absorbs UV radiations and dissipates the absorbed energy through various radiative and nonradiative pathways. The attachment of functionalized quantum dots (QDs) to the sunscreen component is a novel idea to enhance the absorption cross‐section of UV radiations. Therefore, the attachment of the sunscreen component to the ligand functionalized biocompatible QDs and the absorbed energy transfer from sunscreen to the QDs could work as a model system to overall improve the efficiency of the sunscreen. This study elucidates the mechanism of size‐dependent Förster resonance energy transfer (FRET) efficiency and its rate between 2‐phenylbenzimidazole‐5‐sulfonic acid (PBSA) and mercaptoacetic acid (MAA) functionalized CdS QDs. In the PBSA‐QDs dyad, the PBSA (donor) dissipates UV‐absorbed energy to the CdS QDs (acceptor). Following excitation at 306 nm, the steady‐state photoluminescence (SSPL) and time‐resolved photoluminescence (TRPL) techniques measurements demonstrate that both the nonradiative energy transfer efficiency and rate are QDs size‐dependent in addition to donor‐acceptor distance, and suggest that bigger sized‐QDs result in an increase of the FRET efficiency.
Correlation between the elastic modulus of anterior cruciate ligament (ACL) and quantitative ultrashort echo time (UTE) magnetic resonance imaging

Conventional magnetic resonance imaging (MRI) often acquires no signal in anterior cruciate ligament (ACL) due to the short apparent transverse relaxation time of ACL. Ultrashort echo time (UTE) MRI is capable of imaging ACL with high signal which enables quantitative ACL assessment. This study aimed to investigate the correlations of the mechanical and microstructural properties of human ACL specimens with quantitative three‐dimensional UTE Cones (3D‐UTE‐Cones) MRI measures. ACL specimens were harvested from cadaveric knee joints of 13 (50.9 ± 21.1 years old, 11 males and 2 female) donors. Specimens were scanned using a series of quantitative 3D‐UTE‐Cones T2* (UTE‐T2*), T1 (UTE‐T1), Adiabatic T1ρ (UTE‐Adiab‐T1ρ), and magnetization transfer (UTE‐MT) sequences in a wrist coil on a clinical 3T scanner. ACL elastic modulus was measured using a uniaxial tensile mechanical test. Histomorphometry analysis was performed to measure the average fascicle specific surface, fascicle size, and number of cells per unit area. Spearman's rank correlations of UTE‐MRI biomarkers with mechanical and histomorphometry measures were investigated. The elastic modulus of ACL showed significant moderate correlations with UTE‐Adiab‐T1ρ (R = −0.59, p = 0.01), macromolecular fraction from MT modeling (R = 0.54, p = 0.01), magnetization transfer ratio (R = 0.53, p = 0.01), UTE‐T2* (R = −0.53, p = 0.01), and average fascicle specific surface (R = 0.54, p = 0.01). UTE‐MRI showed nonsignificant correlations with histomorphometry measures. UTE‐MRI biomarkers may be useful noninvasive tools for the ACL mechanical assessment.
Research on the Risk Evaluation Index System for Collection in Air Transport of Dangerous Goods

Collection is one of the important parts in the process of safe carriage of dangerous goods;therefore,a good collection-finding problems before the danger occurs-is of significance to the safe transport of dangerous goods by air.This paper builds the risk evaluation index system,based on the factors which affect the collection,for the collection in air transport of dangerous goods through the analysis of historical data,and uses analytic hierarchy process(AHP) to determine the specific weight of each index.Then the paper gives the appropriate measures.
Current trends and opportunities in the methodology of electrodermal activity measurement

Electrodermal activity (EDA) has been measured in the laboratory since the late 1800s. Although the influence of sudomotor nerve activity and the sympathetic nervous system on EDA is well established, the mechanisms underlying EDA signal generation are not completely understood. Owing to simplicity of instrumentation and modern electronics, these measurements have recently seen a transfer from the laboratory to wearable devices, sparking numerous novel applications while bringing along both challenges and new opportunities. In addition to developments in electronics and miniaturization, current trends in material technology and manufacturing have sparked innovations in electrode technologies, and trends in data science such as machine learning and sensor fusion are expanding the ways that measurement data can be processed and utilized. Although challenges remain for the quality of wearable EDA measurement, ongoing research and developments may shorten the quality gap between wearable EDA and standardized recordings in the laboratory. In this topical review, we provide an overview of the basics of EDA measurement, discuss the challenges and opportunities of wearable EDA, and review recent developments in instrumentation, material technology, signal processing, modeling and data science tools that may advance the field of EDA research and applications over the coming years.
Statistical analysis of fundamental data on component reliability for power systems

By using the internationally universal methods,the power system component reliability data issued by the Reliability Management Center of China Electricity Council(CEC) were analyzed and calculated,and the average reliability indices of power system components in China in recent 5 years are given,including that of the generating units,transmission and distribution equipment,and HVDC transmission systems.Considering the characteristics of hybrid AC/DC system reliability analysis,the defects in the statistical content and method for DC system reliability data are discussed,and suggestions are proposed.