Miracle-dz/UniFAR-FTUs huggingface dataset:
Case Report: A Novel In-Frame Deletion of GLIS2 Leading to Nephronophthisis and Early Onset Kidney Failure

Variants in the GLIS family zinc finger protein 2 (GLIS2) are a rare cause of nephronophthisis-related ciliopathies (NPHP-RC). A reduction in urinary concentration and a progressive chronic tubulointerstitial nephropathy with corticomedullary cysts are the major characteristic features of NPHP. NPHP demonstrates phenotypic and genetic heterogeneity with at least 25 different recessive genes associated with the disease. We report a female, from a consanguineous family, who presented age 9 years with echogenic kidneys with loss of cortico-medullary differentiation and progressive chronic kidney disease reaching kidney failure by 10 years of age. A novel homozygous in-frame deletion (NM_032,575.3: c.560_574delACCATGTCAACGATT, p.H188_Y192del) in GLIS2 was identified using whole exome sequencing (WES) that segregated from each parent. The five amino acid deletion disrupts the alpha-helix of GLIS2 zinc-finger motif with predicted misfolding of the protein leading to its predicted pathogenicity. This study broadens the variant spectrum of GLIS2 variants leading to NPHP-RC. WES is a suitable molecular tool for children with kidney failure suggestive of NPHP-RC and should be part of routine diagnostics in kidney failure of unknown cause, especially in consanguineous families.
Upregulation of IRF9 Contributes to Pulmonary Artery Smooth Muscle Cell Proliferation During Pulmonary Arterial Hypertension

Abnormal proliferation of pulmonary artery smooth muscle cells (PASMCs) is a critical pathological feature in the pathogenesis of pulmonary arterial hypertension (PAH), but the regulatory mechanisms remain largely unknown. Herein, we demonstrated that interferon regulatory factor 9 (IRF9) accelerated PASMCs proliferation by regulating Prohibitin 1 (PHB1) expression and the AKT-GSK3β signaling pathway. Compared with control groups, the rats treated with chronic hypoxia (CH), monocrotaline (MCT) or sugen5416 combined with chronic hypoxia (SuHx), and mice challenged with CH had significantly thickened pulmonary arterioles and hyperproliferative PASMCs. More importantly, the protein level of IRF9 was found to be elevated in the thickened medial wall of the pulmonary arterioles in all of these PAH models. Notably, overexpression of IRF9 significantly promoted the proliferation of rat and human PASMCs, as evidenced by increased cell counts, EdU-positive cells and upregulated biomarkers of cell proliferation. In contrast, knockdown of IRF9 suppressed the proliferation of rat and human PASMCs. Mechanistically, IRF9 directly restrained PHB1 expression and interacted with AKT to inhibit the phosphorylation of AKT at thr308 site, which finally led to mitochondrial dysfunction and PASMC proliferation. Unsurprisingly, MK2206, a specific inhibitor of AKT, partially reversed the PASMC proliferation inhibited by IRF9 knockdown. Thus, our results suggested that elevation of IRF9 facilitates PASMC proliferation by regulating PHB1 expression and AKT signaling pathway to affect mitochondrial function during the development of PAH, which indicated that targeting IRF9 may serve as a novel strategy to delay the pathological progression of PAH.
Targeted On-Demand Screening of Pesticide Panel in Soil Runoff

Using pesticides is a common agricultural and horticultural practice to serve as a control against weeds, fungi, and insects in plant systems. The application of these chemical agents is usually by spraying them on the crop or plant. However, this methodology is not highly directional, and so only a fraction of the pesticide actually adsorbs onto the plant, and the rest seeps through into the soil base contaminating its composition and eventually leaching into groundwater sources. Electrochemical sensors which are more practical for in situ analysis used for pesticide detection in soil runoff systems are still in dearth, while the ones published in the literature are attributed with complex sensor modification/functionalization and preprocessing of samples. Hence, in this work, we present a highly intuitive electroanalytical sensor approach toward rapid (10 min), on-demand screening of commonly used pesticides—glyphosate and atrazine—in soil runoff. The proposed sensor functions based on the affinity biosensing mechanism driven via thiol cross-linker and antibody receptors that holistically behaves as a recognition immunoassay stack that is specific and sensitive to track test pesticide analytes. Then, this developed sensor is integrated further to create a pesticide-sensing ecosystem using a front-end field-deployable smart device. The method put forward in this work is compared and validated against a standard laboratory potentiostat instrument to determine efficacy, feasibility, and robustness for a point-of-use (PoU) setting yielding LoD levels of 0.001 ng/ml for atrazine and 1 ng/ml for glyphosate. Also, the ML model integration resulted in an accurate prediction rate of ≈80% in real soil samples. Therefore, a universal pesticide screening analytical device is designed, fabricated, and tested for pesticide assessment in real soil runoff samples.
A predictive model for Arias intensity at multiple sites and consideration of spatial correlations

Arias intensity, Ia, has been identified as an efficient intensity measure for the estimation of earthquake‐induced losses. In this paper, a new model for the prediction of Arias intensity, which incorporates nonlinear site response through the use of the average shear‐wave velocity and a heteroskedastic variance structure, is proposed. In order to estimate the effects of ground motions on spatially‐distributed systems, it is important to take into account the spatial correlation of the intensity measure. However, existing loss‐estimation models, which use Ia as an input, do not take this aspect of the ground motion into account. Therefore, the potential to model the spatial correlation of Arias intensity is also investigated. The empirical predictive model is developed using recordings from the Pacific Earthquake Engineering Research Center Next Generation of Attenuation database whereas the model for spatial correlation makes use of the well‐recorded events from this database, that is the Northridge and Chi‐Chi earthquakes. Copyright © 2011 John Wiley & Sons, Ltd.
Link Prediction Between Structured Geopolitical Events: Models and Experiments

Often thought of as higher-order entities, events have recently become important subjects of research in the computational sciences, including within complex systems and natural language processing (NLP). One such application is event link prediction. Given an input event, event link prediction is the problem of retrieving a relevant set of events, similar to the problem of retrieving relevant documents on the Web in response to keyword queries. Since geopolitical events have complex semantics, it is an open question as to how to best model and represent events within the framework of event link prediction. In this paper, we formalize the problem and discuss how established representation learning algorithms from the machine learning community could potentially be applied to it. We then conduct a detailed empirical study on the Global Terrorism Database (GTD) using a set of metrics inspired by the information retrieval community. Our results show that, while there is considerable signal in both network-theoretic and text-centric models of the problem, classic text-only models such as bag-of-words prove surprisingly difficult to outperform. Our results establish both a baseline for event link prediction on GTD, and currently outstanding challenges for the research community to tackle in this space.
A Computed Tomography Radiomics-Based Prediction Model on Interstitial Lung Disease in Anti-MDA5-Positive Dermatomyositis

Objectives: Anti-melanoma differentiation-associated gene 5-positive dermatomyositis-associated interstitial lung disease (MDA5+ DM-ILD) is a life-threatening disease. The current study aimed to quantitatively assess the pulmonary high-resolution computed tomography (HRCT) images of MDA5+ DM-ILD by applying the radiomics approach and establish a multidimensional risk prediction model for the 6-month mortality. Methods: This retrospective study was conducted in 228 patients from two centers, namely, a derivation cohort and a longitudinal internal validation cohort in Renji Hospital, as well as an external validation cohort in Guangzhou. The derivation cohort was randomly divided into training and testing sets. The primary outcome was 6-month all-cause mortality since the time of admission. Baseline pulmonary HRCT images were quantitatively analyzed by radiomics approach, and a radiomic score (Rad-score) was generated. Clinical predictors selected by univariable Cox regression were further incorporated with the Rad-score, to enhance the prediction performance of the final model (Rad-score plus model). In parallel, an idiopathic pulmonary fibrosis (IPF)-based visual CT score and ILD-GAP score were calculated as comparators. Results: The Rad-score was significantly associated with the 6-month mortality, outperformed the traditional visual score and ILD-GAP score. The Rad-score plus model was successfully developed to predict the 6-month mortality, with C-index values of 0.88 [95% confidence interval (CI), 0.79–0.96] in the training set (n = 121), 0.88 (95%CI, 0.71–1.0) in the testing set (n = 31), 0.83 (95%CI, 0.68–0.98) in the internal validation cohort (n = 44), and 0.84 (95%CI, 0.64–1.0) in the external validation cohort (n = 32). Conclusions: The radiomic feature was an independent and reliable prognostic predictor for MDA5+ DM-ILD.
The Insulin-Sensitizer Pioglitazone Remodels Adipose Tissue Phospholipids in Humans

The insulin-sensitizer pioglitazone exerts its cardiometabolic benefits in type 2 diabetes (T2D) through a redistribution of body fat, from ectopic and visceral areas to subcutaneous adipose depots. Whereas excessive weight gain and lipid storage in obesity promotes insulin resistance and chronic inflammation, the expansion of subcutaneous adipose by pioglitazone is associated with a reversal of these immunometabolic deficits. The precise events driving this beneficial remodeling of adipose tissue with pioglitazone remain unclear, and whether insulin-sensitizers alter the lipidomic composition of human adipose has not previously been investigated. Using shotgun lipidomics, we explored the molecular lipid responses in subcutaneous adipose tissue following 6months of pioglitazone treatment (45mg/day) in obese humans with T2D. Despite an expected increase in body weight following pioglitazone treatment, no robust effects were observed on the composition of storage lipids (i.e., triglycerides) or the content of lipotoxic lipid species (e.g., ceramides and diacylglycerides) in adipose tissue. Instead, pioglitazone caused a selective remodeling of the glycerophospholipid pool, characterized by a decrease in lipids enriched for arachidonic acid, such as plasmanylethanolamines and phosphatidylinositols. This contributed to a greater overall saturation and shortened chain length of fatty acyl groups within cell membrane lipids, changes that are consistent with the purported induction of adipogenesis by pioglitazone. The mechanism through which pioglitazone lowered adipose tissue arachidonic acid, a major modulator of inflammatory pathways, did not involve alterations in phospholipase gene expression but was associated with a reduction in its precursor linoleic acid, an effect that was also observed in skeletal muscle samples from the same subjects. These findings offer important insights into the biological mechanisms through which pioglitazone protects the immunometabolic health of adipocytes in the face of increased lipid storage.
Dynamics and Determinants of Market Integration of Green, Clean, Dirty Energy Investments and Conventional Stock Indices

We examine market integration across and clean and green investments, crude oil, and conventional stock indices covering technology stocks, and United States and European stocks. Using daily data covering the period December 1, 2008—October 8, 2020, we first apply the dynamic equicorrelation (DECO) model and make inferences regarding the time-varying level of market integration. Then, we use several regression models and uncover the driving factors of market integration under lower and upper quantiles of the distribution of the equicorrelation. The results show that return equicorrelation varies with time and is shaped by the COVID19 outbreak. Various uncertainty measures are the main drivers of market integration, especially at high levels of market integration. During the COVID-19 outbreak period, the United States Dollar index, the term spread, and the Chinese stock market index have significantly increased market integration.
The Sorghum (Sorghum bicolor) Brown Midrib 30 Gene Encodes a Chalcone Isomerase Required for Cell Wall Lignification

In sorghum (Sorghum bicolor) and other C4 grasses, brown midrib (bmr) mutants have long been associated with plants impaired in their ability to synthesize lignin. The brown midrib 30 (Bmr30) gene, identified using a bulk segregant analysis and next-generation sequencing, was determined to encode a chalcone isomerase (CHI). Two independent mutations within this gene confirmed that loss of its function was responsible for the brown leaf midrib phenotype and reduced lignin concentration. Loss of the Bmr30 gene function, as shown by histochemical staining of leaf midrib and stalk sections, resulted in altered cell wall composition. In the bmr30 mutants, CHI activity was drastically reduced, and the accumulation of total flavonoids and total anthocyanins was impaired, which is consistent with its function in flavonoid biosynthesis. The level of the flavone lignin monomer tricin was reduced 20-fold in the stem relative to wild type, and to undetectable levels in the leaf tissue of the mutants. The bmr30 mutant, therefore, harbors a mutation in a phenylpropanoid biosynthetic gene that is key to the interconnection between flavonoids and monolignols, both of which are utilized for lignin synthesis in the grasses.
Calcium Ions Aggravate Alzheimer’s Disease Through the Aberrant Activation of Neuronal Networks, Leading to Synaptic and Cognitive Deficits

Alzheimer’s disease (AD) is a neurodegenerative disease that is characterized by the production and deposition of β-amyloid protein (Aβ) and hyperphosphorylated tau, leading to the formation of β-amyloid plaques (APs) and neurofibrillary tangles (NFTs). Although calcium ions (Ca2+) promote the formation of APs and NFTs, no systematic review of the mechanisms by which Ca2+ affects the development and progression of AD has been published. Therefore, the current review aimed to fill the gaps between elevated Ca2+ levels and the pathogenesis of AD. Specifically, we mainly focus on the molecular mechanisms by which Ca2+ affects the neuronal networks of neuroinflammation, neuronal injury, neurogenesis, neurotoxicity, neuroprotection, and autophagy. Furthermore, the roles of Ca2+ transporters located in the cell membrane, endoplasmic reticulum (ER), mitochondria and lysosome in mediating the effects of Ca2+ on activating neuronal networks that ultimately contribute to the development and progression of AD are discussed. Finally, the drug candidates derived from herbs used as food or seasoning in Chinese daily life are summarized to provide a theoretical basis for improving the clinical treatment of AD.
Active Learning Performance in Labeling Radiology Images Is 90% Effective

To train artificial intelligence (AI) systems on radiology images, an image labeling step is necessary. Labeling for radiology images usually involves a human radiologist manually drawing a (polygonal) shape onto the image and attaching a word to it. As datasets are typically large, this task is repetitive, time-consuming, error-prone, and expensive. The AI methodology of active learning (AL) can assist human labelers by continuously sorting the unlabeled images in order of information gain and thus getting the labeler always to label the most informative image next. We find that after about 10%, depending on the dataset, of the images in a realistic dataset are labeled, virtually all the information content has been learnt and the remaining images can be automatically labeled. These images can then be checked by the radiologist, which is far easier and faster to do. In this way, the entire dataset is labeled with much less human effort. We introduce AL in detail and expose the effectiveness using three real-life datasets. We contribute five distinct elements to the standard AL workflow creating an advanced methodology.
An Integrated Gut Microbiota and Network Pharmacology Study on Fuzi-Lizhong Pill for Treating Diarrhea-Predominant Irritable Bowel Syndrome

Diarrhea-predominant irritable bowel syndrome (IBS-D) is one of the most common chronic functional gastrointestinal diseases with limited treatments. Gut microbiota play an important role in chronic gastrointestinal diseases. In traditional Chinese medicine (TCM), Spleen–Yang deficiency (SYD) is one of the root causes of IBS-D. Fuzi-Lizhong pill (FLZP) is well known for its powerful capacity for treating SYD and has a good clinical effect on IBS-D. However, the mechanism of FLZP on the gut microbiota of IBS-D has not been fully clarified. Our present study aimed to reveal the mechanism of FLZP regulating gut microbiota of IBS-D. The body mass, CCK, MTL, and Bristol fecal character score were used to verify the establishment of the IBS-D model. IL-6, TNF, IL-1β, and IFN-γ were crucial targets screened by network pharmacology and preliminarily verified by ELISA. Eighteen gut microbiota were important for the treatment of IBS-D with FLZP. Bacteroidetes, Blautia, Turicibacter, and Ruminococcus_torques_group were the crucial gut microbiota that FLZP inhibits persistent systemic inflammation in the IBS-D model. Lactobacillus is the crucial gut microbiota that FLZP renovates intestinal immune barrier in the IBS-D model. In summary, FLZP can affect bacterial diversity and community structures in the host and regulate inflammation and immune system to treat IBS-D.
The Role of Oxidative Stress in Suicidal Behaviour Among Bipolar Patients: A Cross-Sectional Study in a Malaysian Sample

Background: Oxidative stress markers are found to be linked with depression and suicide attempts in bipolar disorder (BD), although the role of DNA damage as a marker of suicidal ideation and attempt has yet to be determined. We aim to investigate the association between DNA damage and suicidal behaviour, i.e., suicidal ideation and suicide attempt, among suicidal ideators in BD patients while accounting for clinical and psychosocial risk factors. Methods: A cross-sectional study was conducted in the Universiti Kebangsaan Malaysia Medical Centre on 62 consecutive BD patients diagnosed using the M.I. N.I. Neuropsychiatric Interview and 26 healthy control participants. Socio-demographic and clinical assessments were performed using the Columbia Suicide Severity Rating Scale (C-SSRS) for lifetime suicidal ideation and attempt, Quick Inventory of Depressive Symptomatology (QIDS) for depression severity, Clinical Global Impression for Bipolar Disorder (CGI-BD) for illness severity [both mania (CGI-Mania) and major depressive episode (CGI-MDE)], Social Readjustment Rating Scale (SRRS) for change in life events, and Barratt Impulsiveness Scale (BIS) for behavioural impulsivity. The degree of DNA damage in peripheral blood samples was determined using a standard protocol of comet assay. Results: Multivariable logistic regression revealed higher scores of CGI-MDE as the sole significant factor for lifetime suicidal ideation (OR = 1.937, 95% CI = 1.799–2.076). Although initial bivariate analysis showed a significant association between DNA damage, malondialdehyde (MDA), catalase (CAT), and suicidal behaviour, the findings were not seen in multivariable logistic regression. Bivariate subgroup analysis showed that moderate and severe DNA damage (p = 0.032 and p = 0.047, respectively) was significantly associated with lifetime suicide attempts among lifetime suicidal ideators. The study is the first to look at the connexion between DNA damage and suicidal risk in bipolar patients. It is limited by the small sample size and lack of information on illicit substance use. Conclusions: More severe DNA damage was significantly associated with lifetime suicide attempts among lifetime suicidal ideators in BD. However, the severity of depression was found to be independently associated with lifetime suicidal ideation per se rather than DNA damage in BD. Larger prospective studies are required to ascertain the potential of DNA damage as a biomarker for the transition from suicidal ideation to a suicide attempt.
Hong Kong Children’s School Readiness in Times of COVID-19: The Contributions of Parent Perceived Social Support, Parent Competency, and Time Spent With Children

School readiness is an important but challenging issue of child development, especially during COVID-19 when most of the traditional offline activities that could promote school readiness (e.g., on-site visit) have been canceled. There is a gap between the knowledge needed to promote children’s school readiness in times of pandemic and the limited understanding of this topic so far. This gap could be particularly concerning in the social contexts where examinations are stressed and educational competition is high (e.g., Hong Kong). In this study, we examined how well children were ready for primary school, the extent to which parent perceived social support was related to children’s school readiness, and whether parent competence and their time spent with children would moderate the said link. A cross-sectional design survey with total population sampling (supplemented with convenience sampling) was conducted. Massive e-mails were sent to all kindergartens in Hong Kong inviting them to join the study by distributing the survey link to the parents of their K3 students. A total of 643 Hong Kong parents whose children were about to transition to primary school (87.1% mother) participated, answering measures specifically designed for this study online about how well they thought their children were ready for school, their competence to help with children’s school transition, and how much time they spent with children. Data were analyzed with PROCESS macro (model 3) in SPSS. The results found that most parents considered that their children were not fully ready for school, especially in terms of academic skills, self-management, and mental preparation. Furthermore, moderation analyses showed that after controlling for a number of demographic variables, parent perceived social support was positively related to better school readiness in children and this link was jointly moderated by parent competence and time spent with children. Specifically, children were rated most ready when parent perceived stronger social support, felt more competent, and spent more time with children. By contrast, the link between perceived social support and children’s school readiness was insignificant for parent who felt more competent but spent less time with children. Implications of how to enhance children’s school readiness are discussed.