Miracle-dz/UniFAR-FTUs huggingface dataset:
Nonradial solutions of weighted elliptic superlinear problems in bounded symmetric domains

The present work has two objectives. First, we prove that a weight\-ed superlinear elliptic problem has infinitely many nonradial solutions in the unit ball. Second, we obtain the same conclusion in annuli for a more general nonlinearity which also involves a weight. We use a lower estimate of the energy level of radial solutions with $k-1$ zeros in the interior of the domain and a simple counting. Uniqueness results due to Tanaka \cite[2008]{Tanaka1} and \cite[2007]{Tanaka2} are very useful in our approach.
Parallel Knowledge Transfer in Multi-Agent Reinforcement Learning

Multi-agent reinforcement learning is a standard framework for modeling multi-agent interactions applied in real-world scenarios. Inspired by experience sharing in human groups, learning knowledge parallel reusing between agents can potentially promote team learning performance, especially in multi-task environments. When all agents interact with the environment and learn simultaneously, how each independent agent selectively learns from other agents' behavior knowledge is a problem that we need to solve. This paper proposes a novel knowledge transfer framework in MARL, PAT (Parallel Attentional Transfer). We design two acting modes in PAT, student mode and self-learning mode. Each agent in our approach trains a decentralized student actor-critic to determine its acting mode at each time step. When agents are unfamiliar with the environment, the shared attention mechanism in student mode effectively selects learning knowledge from other agents to decide agents' actions. PAT outperforms state-of-the-art empirical evaluation results against the prior advising approaches. Our approach not only significantly improves team learning rate and global performance, but also is flexible and transferable to be applied in various multi-agent systems.
Memorizing Gaussians with no over-parameterizaion via gradient decent on neural networks

We prove that a single step of gradient decent over depth two network, with $q$ hidden neurons, starting from orthogonal initialization, can memorize $\Omega\left(\frac{dq}{\log^4(d)}\right)$ independent and randomly labeled Gaussians in $\mathbb{R}^d$. The result is valid for a large class of activation functions, which includes the absolute value.
Effective scalar-tensor description of regularized Lovelock gravity in four dimensions

We reformulate the recently proposed regularized version of Lovelock gravity in four dimensions as a scalar-tensor theory. By promoting the warp factor of the internal space to a scalar degree of freedom by means of Kaluza-Klein reduction, we show that regularized Lovelock gravity can be described effectively by a certain subclass of the Horndeski theory. Cosmological aspects of this particular scalar-tensor theory are studied. It is found that the background with a scalar charge is generically allowed. The consequences of this scalar charge are briefly discussed.
Radiomics model based on preoperative gadoxetic acid-enhanced MRI for predicting liver failure

BACKGROUND Postoperative liver failure is the most severe complication in cirrhotic patients with hepatocellular carcinoma (HCC) after major hepatectomy. Current available clinical indexes predicting postoperative residual liver function are not sufficiently accurate. AIM To determine a radiomics model based on preoperative gadoxetic acid-enhanced magnetic resonance imaging for predicting liver failure in cirrhotic patients with HCC after major hepatectomy. METHODS For this retrospective study, a radiomics-based model was developed based on preoperative hepatobiliary phase gadoxetic acid-enhanced magnetic resonance images in 101 patients with HCC between June 2012 and June 2018. Sixty-one radiomic features were extracted from hepatobiliary phase images and selected by the least absolute shrinkage and selection operator method to construct a radiomics signature. A clinical prediction model, and radiomics-based model incorporating significant clinical indexes and radiomics signature were built using multivariable logistic regression analysis. The integrated radiomics-based model was presented as a radiomics nomogram. The performances of clinical prediction model, radiomics signature, and radiomics-based model for predicting post-operative liver failure were determined using receiver operating characteristics curve, calibration curve, and decision curve analyses. RESULTS Five radiomics features from hepatobiliary phase images were selected to construct the radiomics signature. The clinical prediction model, radiomics signature, and radiomics-based model incorporating indocyanine green clearance rate at 15 min and radiomics signature showed favorable performance for predicting postoperative liver failure (area under the curve: 0.809-0.894). The radiomics-based model achieved the highest performance for predicting liver failure (area under the curve: 0.894; 95%CI: 0.823-0.964). The integrated discrimination improvement analysis showed a significant improvement in the accuracy of liver failure prediction when radiomics signature was added to the clinical prediction model (integrated discrimination improvement = 0.117, P = 0.002). The calibration curve and an insignificant Hosmer-Lemeshow test statistic (P = 0.841) demonstrated good calibration of the radiomics-based model. The decision curve analysis showed that patients would benefit more from a radiomics-based prediction model than from a clinical prediction model and radiomics signature alone. CONCLUSION A radiomics-based model of preoperative gadoxetic acid–enhanced MRI can be used to predict liver failure in cirrhotic patients with HCC after major hepatectomy.
Prevalence and type distribution of human papillomavirus in a Chinese urban population between 2014 and 2018: a retrospective study

Background Human papilloma virus (HPV) infection is one of the most common sexually transmitted infections among women worldwide. The current study’s main objective is to report the prevalence and distribution of HPV types in an urban population in Beijing, China. Methods All the eligible female participants aged ≥18 years were recruited from the Aerospace Center Hospital in Beijing, China between 2014 and 2018. A total of 21 HPV types were detected by the polymerase chain reaction (PCR) reverse dot blot method and fluorescence quantitative PCR method. Results In total, 12 high risk HPV types and nine low risk HPV types were detected. The HPV-positive rates were 8.85% in 2014, 7.16% in 2015, 7.60% in 2016, 8.31% in 2017, and 7.72% in 2018, respectively, in an urban population in Beijing, China. Overall, no significant differences in the HPV-positive rates were found over the five years. The peak prevalence of HPV infection in all types was observed in age group of 20–24 in all types. HPV52 was the dominant HPV type across the five years . Among all 21 HPV types, HPV66, HPV26, and HPV59 were ranked the top three in coinfection occurrence. Conclusions Our findings are very helpful for HPV screening and vaccination. The associations between gynaecological diseases and the HPV types with high prevalence, particularly HPV52, warrant further investigation.
Genomic analysis of variability in Delta-toxin levels between Staphylococcus aureus strains

Background The delta-toxin (δ-toxin) of Staphylococcus aureus is the only hemolysin shown to cause mast cell degranulation and is linked to atopic dermatitis, a chronic inflammatory skin disease. We sought to characterize variation in δ-toxin production across S. aureus strains and identify genetic loci potentially associated with differences between strains. Methods A set of 124 S. aureus strains was genome-sequenced and δ-toxin levels in stationary phase supernatants determined by high performance liquid chromatography (HPLC). SNPs and kmers were associated with differences in toxin production using four genome-wide association study (GWAS) methods. Transposon mutations in candidate genes were tested for their δ-toxin levels. We constructed XGBoost models to predict toxin production based on genetic loci discovered to be potentially associated with the phenotype. Results The S. aureus strain set encompassed 40 sequence types (STs) in 23 clonal complexes (CCs). δ-toxin production ranged from barely detectable levels to >90,000 units, with a median of >8,000 units. CC30 had significantly lower levels of toxin production than average while CC45 and CC121 were higher. MSSA (methicillin sensitive) strains had higher δ-toxin production than MRSA (methicillin resistant) strains. Through multiple GWAS approaches, 45 genes were found to be potentially associated with toxicity. Machine learning models using loci discovered through GWAS as features were able to predict δ-toxin production (as a high/low binary phenotype) with a precision of . 875 and specificity of . 990 but recall of . 333. We discovered that mutants in the carA gene, encoding the small chain of carbamoyl phosphate synthase, completely abolished toxin production and toxicity in Caenorhabditis elegans. Conclusions The amount of stationary phase production of the toxin is a strain-specific phenotype likely affected by a complex interaction of number of genes with different levels of effect. We discovered new candidate genes that potentially play a role in modulating production. We report for the first time that the product of the carA gene is necessary for δ-toxin production in USA300. This work lays a foundation for future work on understanding toxin regulation in S. aureus and prediction of phenotypes from genomic sequences.
Prevalence and Genotyping of Cryptosporidium parvum in Gastrointestinal Cancer Patients

Gastrointestinal cancers are the most commonly occurring malignancies which contributing to over 1/5 of cancer incidences worldwide. Increasing evidences have shown that Cryptosporidium spp. , an apicomplexan protozoan, is highly associated with gastrointestinal cancers. However, the prevalence of Cryptosporidium spp. infections among gastrointestinal cancer patients in China has not been estimated yet. We here performed a case-control study to evaluate the occurrences of Cryptosporidium spp. in patients with digestive malignancies before chemotherapy and in control population. Nested PCR amplifying 18S rRNA gene was used to detect the presence of Cryptosporidium spp. in each fecal sample. The results herein confirmed the correlation of Cryptosporidium spp. infection with colorectal and liver cancers, while first identified the high frequencies of Cryptosporidium spp. in esophageal cancer and small intestine cancer. The infection rates of Cryptosporidium spp. in colorectal, esophageal, liver and small intestine cancers were 17.24% (20/116, P<0.001), 6.25% (1/16, P=0.029), 14.29% (1/7, P<0.001) and 40% (2/5, P<0.001), respectively. In addition, molecular characterization indicated that all the Cryptosporidium spp. obtained were Cryptosporidium parvum (C. parvum), and the 18S rRNA sequences were identical to the reference sequences isolated from cattle, suggesting potential zoonotic transmission. Furthermore, subtyping analyses revealed that IIaA15G2R1 and IIaA15G2R2 were the predominant subtypes in colorectal cancer, while IIaA13G2R2 subtype was first named and identified in colorectal and liver cancers. Taken together, for the first time, the prevalence of Cryptosporidium spp. infections in digestive cancer patients has been estimated among Chinese. Our results indicated that C. parvum were highly associated with gastrointestinal cancers, supporting that cryptosporidiosis could be a potential risk factor for these diseases.
DUSP6 SUMOylation protects cells from oxidative damage via direct regulation of Drp1 dephosphorylation

Our work uncovers a novel SUMOylation-dependent regulation of DUSP6 stability and its activity, which regulates Drp1 function. Imbalanced mitochondrial fission/fusion, a major cause of apoptotic cell death, often results from dysregulation of Drp1 phosphorylation of two serines, S616 and S637. Whereas kinases for Drp1-S616 phosphorylation are well-described, phosphatase(s) for its dephosphorylation remains unclear. Here, we show that dual-specificity phosphatase 6 (DUSP6) dephosphorylates Drp1-S616 independently of its known substrates ERK1/2. DUSP6 keeps Drp1-S616 phosphorylation levels low under normal conditions. The stability and catalytic function of DUSP6 are maintained through conjugation of small ubiquitin-like modifier-1 (SUMO1) and SUMO2/3 at lysine-234 (K234), which is disrupted during oxidation through transcriptional up-regulation of SUMO-deconjugating enzyme, SENP1, causing DUSP6 degradation by ubiquitin-proteasome. deSUMOylation underlies DUSP6 degradation, Drp1-S616 hyperphosphorylation, mitochondrial fragmentation, and apoptosis induced by H2O2 in cultured cells or brain ischemia/reperfusion in mice. Overexpression of DUSP6, but not the SUMOylation-deficient DUSP6K234R mutant, protected cells from apoptosis. Thus, DUSP6 exerts a cytoprotective role by directly dephosphorylating Drp1-S616, which is disrupted by deSUMOylation under oxidation.
Risks of Novel Coronavirus Disease (COVID-19) in Pregnancy; a Narrative Review

Introduction: The outbreak of the new Coronavirus in China in December 2019 and subsequently in various countries around the world has raised concerns about the possibility of vertical transmission of the virus from mother to fetus. The present study aimed to review published literature in this regard. Methods: In this narrative review, were searched for all articles published in various databases including PubMed, Scopus, Embase, Science Direct, and Web of Science using MeSH-compliant keywords including COVID-19, Pregnancy, Vertical transmission, Coronavirus 2019, SARS-CoV-2 and 2019-nCoV from December 2019 to March 18, 2020 and reviewed them. All type of articles published about COVID-19 and vertical transmission in pregnancy were included. Results: A review of 13 final articles published in this area revealed that COVID-19 can cause fetal distress, miscarriage, respiratory distress and preterm delivery in pregnant women but does not infect newborns. There has been no report of vertical transmission in pregnancy, and it has been found that clinical symptoms of COVID-19 in pregnant women are not different from those of non-pregnant women. Conclusion: Overall, due to lack of appropriate data about the effect of COVID-19 on pregnancy, it is necessary to monitor suspected pregnant women before and after delivery. For confirmed cases both the mother and the newborn child should be followed up comprehensively.
Sex Differences and Adverse Effects between Chemotherapy and Immunotherapy for Non-Small Cell Lung Cancer

Introduction: Lung cancer remains the leading cause of cancer mortality in men and women and around the world. Approximately 90% of cases of lung cancer are caused by smoking and the use of tobacco products. However, other factors such as asbestos, air pollution and chronic infections can contribute to pulmonary carcinogenesis. Lung cancer is divided into two broad histological categories, which develop and spread different small cell lung carcinomas and non-small cell lung carcinomas. The treatment options for lung cancer include surgery, radiotherapy, chemotherapy and targeted treatments. Tumor induced immune suppression is vital for malignant progression. Immunotherapies act by strengthening the patient's innate tendency for an immune response and give positive promise to patients with non-small cell lung cancer and small cell lung cancer. Immune checkpoint inhibitors are a new approach to cancer therapies. Just as immune therapies include a new approach to cancer biology, the toxicities associated with these factors have created new challenges in clinical practice. Materials & Methods: Patients (218) aged 40-80 years were treated with either chemotherapy or immunotherapy. Their response to treatment and any subsequent adverse drug reactions were studied. Results: 69% of patients were treated with chemotherapy and 31% were treated with immunotherapy. The type of treatment had a statistically significant effect on the undesirable effects of the treatment. Conclusions: The type of treatment was statistically significant in responding to the treatment and treatment side effects but not in the rate of death.
Cell reprogramming using extracellular vesicles from differentiating stem cells into white/beige adipocytes

Extracellular vesicles derived during differentiation of stem cells have the potential to induce tissue-specific differentiation. Stem cell–derived extracellular vesicles (EVs) offer alternative approaches to stem cell–based therapy for regenerative medicine. In this study, stem cell EVs derived during differentiation are developed to use as cell-free therapeutic systems by inducing tissue-specific differentiation. EVs are isolated from human adipose-derived stem cells (HASCs) during white and beige adipogenic differentiation (D-EV and BD-EV, respectively) via tangential flow filtration. D-EV and BD-EV can successfully differentiate HASCs into white and beige adipocytes, respectively. D-EV are transplanted with collagen/methylcellulose hydrogels on the backs of BALB/c mice, and they produce numerous lipid droplets in injected sites. Treatments of BD-EV attenuate diet-induced obesity through browning of adipose tissue in mice. Furthermore, high-fat diet–induced hepatic steatosis and glucose tolerance are improved by BD-EV treatment. miRNAs are responsible for the observed effects of BD-EV. These results reveal that secreted EVs during stem cell differentiation into white adipocytes or beige adipocytes can promote cell reprogramming.
Automated endoscopic detection and classification of colorectal polyps using convolutional neural networks

Background: Recently the American Society for Gastrointestinal Endoscopy addressed the ‘resect and discard’ strategy, determining that accurate in vivo differentiation of colorectal polyps (CP) is necessary. Previous studies have suggested a promising application of artificial intelligence (AI), using deep learning in object recognition. Therefore, we aimed to construct an AI system that can accurately detect and classify CP using stored still images during colonoscopy. Methods: We used a deep convolutional neural network (CNN) architecture called Single Shot MultiBox Detector. We trained the CNN using 16,418 images from 4752 CPs and 4013 images of normal colorectums, and subsequently validated the performance of the trained CNN in 7077 colonoscopy images, including 1172 CP images from 309 various types of CP. Diagnostic speed and yields for the detection and classification of CP were evaluated as a measure of performance of the trained CNN. Results: The processing time of the CNN was 20 ms per frame. The trained CNN detected 1246 CP with a sensitivity of 92% and a positive predictive value (PPV) of 86%. The sensitivity and PPV were 90% and 83%, respectively, for the white light images, and 97% and 98% for the narrow band images. Among the correctly detected polyps, 83% of the CP were accurately classified through images. Furthermore, 97% of adenomas were precisely identified under the white light imaging. Conclusions: Our CNN showed promise in being able to detect and classify CP through endoscopic images, highlighting its high potential for future application as an AI-based CP diagnosis support system for colonoscopy.
An Occult HPV-Driven Oropharyngeal Squamous Cell Carcinoma Discovered Through a Saliva Test

Oropharyngeal cancer (OPC) caused by human papillomavirus (HPV) is a rising global concern. Early lesions are small and are often located in difficult to access areas (such as the crypts of the tonsils or base of tongue). Unlike cervical cancer, there is no standard or routine screening program for HPV-driven OPC. HPV DNA from OPC tumors may shed directly into saliva, and this can be used as a biomarker for early diagnosis. In this study, we report the first-ever clinically occult OPC in an asymptomatic patient discovered through a saliva test. This case relied upon serial measurements of HPV-16 DNA in saliva, which fell to undetectable levels following low morbidity, curative treatment.
Cytomegalovirus Latency and Reactivation: An Intricate Interplay With the Host Immune Response

CMV is an ancient herpesvirus that has co-evolved with its host over millions of years. The 236 kbp genome encodes at least 165 genes, four non-coding RNAs and 14 miRNAs. Of the protein-coding genes, 43–44 are core replication genes common to all herpesviruses, while ~30 are unique to betaherpesviruses. Many CMV genes are involved in evading detection by the host immune response, and others have roles in cell tropism. CMV replicates systemically, and thus, has adapted to various biological niches within the host. Different biological niches may place competing demands on the virus, such that genes that are favorable in some contexts are unfavorable in others. The outcome of infection is dependent on the cell type. In fibroblasts, the virus replicates lytically to produce infectious virus. In other cell types, such as myeloid progenitor cells, there is an initial burst of lytic gene expression, which is subsequently silenced through epigenetic repression, leading to establishment of latency. Latently infected monocytes disseminate the virus to various organs. Latency is established through cell type specific mechanisms of transcriptional silencing. In contrast, reactivation is triggered through pathways activated by inflammation, infection, and injury that are common to many cell types, as well as differentiation of myeloid cells to dendritic cells. Thus, CMV has evolved a complex relationship with the host immune response, in which it exploits cell type specific mechanisms of gene regulation to establish latency and to disseminate infection systemically, and also uses the inflammatory response to infection as an early warning system which allows the virus to escape from situations in which its survival is threatened, either by cellular damage or infection of the host with another pathogen. Spontaneous reactivation induced by cellular aging/damage may explain why extensive expression of lytic genes has been observed in recent studies using highly sensitive transcriptome analyses of cells from latently infected individuals. Recent studies with animal models highlight the potential for harnessing the host immune response to blunt cellular injury induced by organ transplantation, and thus, prevent reactivation of CMV and its sequelae.
Significance Assessment of Amphora coffeaeformis in Arsenic-Induced Hemato- Biochemical Alterations of African Catfish (Clarias gariepinus)

Heavy metals have different adverse impacts on different life stages of fish species with attempts to use natural antioxidants to counteract their effects. So, the present study investigated the potential protective effects of Amphora coffeaeformis extract against arsenic-induced hemato-biochemical alterations in African catfish, Clarias gariepinus. The fish exposed to sub-lethal concentrations of arsenic; 19.2 and 38.3 mg/L (1/8 and 1/4 of 96h-LC50 value, 153.17 mg/L) for 15 days. The main effect of arsenic was recorded in some blood parameters such as RBC’s count, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin, and white blood cells. As for biochemical parameters, the main effect of arsenic was significant for alkaline phosphatase, glucose, uric acid, creatinine, albumin, globulin, and albumin/globulin. Also, the residue of arsenic in fish muscles showed significant effects. The majority of these arsenic-induced parameters were improved with dietary supplements of the diatom A. coffeaeformis. So, Amphora extract can be used as detoxification factor on fishes induced by arsenic due to its biologically active components providing protections like antioxidant, antiviral, antibacterial, and anti-inflammatory. Besides, they have excellent contents of proteins and carbohydrates which are supposed to enhance the effect of these compounds.