Miracle-dz/UniFAR-FTUs huggingface dataset:
COVID-19, HIV-Associated Cryptococcal Meningitis, Disseminated Tuberculosis and Acute Ischaemic Stroke: A Fatal Foursome

Background Several viral, bacterial and fungal co-infections have been associated with increased morbidity and mortality among patients with COVID-19. We report a fatal case of severe COVID-19 pneumonia in a patient with a recent diagnosis of advanced HIV disease complicated by cryptococcal meningitis, disseminated tuberculosis and acute ischemic stroke. Case Presentation A 37-year-old Ugandan woman was diagnosed with HIV infection 8 days prior to her referral to our center. She was antiretroviral naïve. Her chief complaints were worsening cough, difficulty in breathing, fever and altered mental status for 3 days with a background of a 1-month history of coughing with associated drenching night sweats and weight loss. The reverse transcriptase–polymerase chain reaction for SARS-CoV-2 of her nasopharyngeal swab sample was positive. Chest radiograph demonstrated military pattern involvement of both lungs. The serum and cerebrospinal fluid cryptococcal antigen tests were positive. Urine lipoarabinomannan and sputum GeneXpert were positive for Mycobacterium tuberculosis. Computed tomography of the brain showed a large acute ischemic infarct in the territory of the right middle cerebral artery. Regardless of the initiation of treatment, that is, fluconazole 1200 mg once daily, enoxaparin 60 mg, intravenous (IV) dexamethasone 6 mg once daily, oral fluconazole 1200 mg once daily, IV piperacillin/tazobactam 4.5 g three times daily and oxygen therapy, the patient passed on within 36 hours of admission. Conclusion Co-infections worsen COVID-19 outcomes.
Relationships between constitutive and acute gene regulation, and physiological and behavioral responses, mediated by the neuropeptide PACAP

Since the advent of gene knockout technology in 1987, insight into the role(s) of neuropeptides in centrally- and peripherally-mediated physiological regulation has been gleaned by examining altered physiological functioning in mammals, predominantly mice, after genetic editing to produce animals deficient in neuropeptides or their cognate G-protein coupled receptors (GPCRs). These results have complemented experiments involving infusion of neuropeptide agonists or antagonists systemically or into specific brain regions. Effects of gene loss are typically interpreted as indicating that the peptide and its receptor(s) are required for the physiological or behavioral responses elicited in wild-type mice at the time of experimental examination. These interpretations presume that peptide/peptide receptor gene deletion affects only the expression of the peptide/receptor itself, and therefore impacts physiological events only at the time at which the experiment is conducted. A way to support ‘real-time’ interpretations of neuropeptide gene knock-out is to demonstrate that the wild-type transcriptome, except for the deliberately deleted gene(s), in tissues of interest, is preserved in the knock-out mouse. Here, we show that there is a cohort of genes (constitutively PACAP regulated genes, or cPRGs) whose basal expression is affected by constitutive knock-out of the Adcyap1 gene in C57Bl6/N mice, and additional genes whose expression in response to physiological challenge, in adults, is altered or impaired in the absence of PACAP expression (acutely PACAP-regulated genes, or aPRGs). Distinguishing constitutive and acute transcriptomic effects of neuropeptide deficiency on physiological function and behavior in mice reveals alternative mechanisms of action, and changing functions of neuropeptides, throughout the lifespan.
Named Entity Recognition and Disambiguation with Wikidata on Arbitrary English Text

Named entity recognition and disambiguation (NERD) is the task of identifying and determining the meaning of named entities in a given text, for example, to tell whether the word "Amazon" is referred to the company or the river. This is done by linking the text spans to their corresponding entities in a knowledge base. NERD is an essential technique in many NLP applications including recommendation system and question-answering system, as it helps to extract and understand information from plain text. The task is however challenging, because the same piece of text can refer to diﬀerent entities and the same entity can be referred to in multiple ways. In addition, the variety of texts – length, topic, style – also increases the diﬃculty of recognition and disambiguation. In this thesis, we propose an algorithm with conﬁgurable features for the task of NERD with Wikidata. In the recognition stage, we examine all possible text spans in the pre-generated named entity index, while reducing the complexity to linear scale by utilizing POS tags as a ﬁlter. In the disambiguation stage, we consider the popularity of each candidate entity and its similarity to the context. On top of the base model, we give the algorithm more ﬂexibility in recognition by expanding the synonyms of certain named entities, and leverage Wikipedia abstracts to enrich the knowledge base. We further discard unlikely named entities to decrease false positives. In evaluation, we analyze the contribution of each component as well as the entire NERD system. Results show that synonym expansion and false positive reduction are very eﬀective. In addition, our algorithm performs better and is capable of outputting more named entities on one dataset with shorter documents. On the other dataset consisting of news articles with rich context, our performance is also acceptable in comparison with the other sophisticated system.
The Anesthetic Role of Some Herbal Oils for Zebrafish

Anesthetics have been important in ornamental fishes for transport and restriction of behaviors as well as for surgical applications and studies in science. Also, more economical and appropriate anesthetics can be common choice for these stiuations. In the study, a total of two hundred and fifty two zebrafish (forty two females and forty two males in each group) divided in three groups were studied as group A (Anise oil); group T (Thyme oil); group M (Mint oil). Anesthesia intake and lethal dose values were determined by following the anesthetic entry and recovery times. There was no anesthetic effect in group A, while anesthetic effects occured in groups T and M in concentrations 1, 5, 10, 20 and 30 mg/l. Similarity was found in groups T and M in terms of anesthesia entry and recovery times (P>0.05). Nevertheless, no mortality occured in group M. However, 5mg/l tyme oil anesthesia was determined to cause 50% mortality in male fishes (group T). It was also observed that mint oil has an anesthetic effect on zebrafish with increasing doses determined by anesthesia entry and recorvery times (group M, P<0.05). Thereby, mint oil may be an alternative herbal anesthetic agent for zebrafish. However, further studies are neccessary to show the herbal anesthetics effect on ornamental fishes.
LAI retrieval from multi-angle and hyperspectral observations in an intensively- managed poplar plantation

LAI is retrieved from directional and hyperspectral observations by numerical inversion of coupled leaf and canopy radiative transfer models. In this research the inversion method is applied to airborne hyperspectral and multi-view-angle DAIS data (Digital Airborne Imaging Spectrometer) acquired over an intensively-managed poplar plantation. The effects of LAI and leaf Mean Tilt Angle (MTA) interactions are discussed and the magnitude of the error in LAI estimation associated with fixing the MTA to its mean value is provided by an uncertainty analysis of the inversion method. The effects of the background spectral signature are discussed and a technique for background assignment is proposed. Inversion method results are assessed comparing LAI estimates with field measurements and compared to VI-based semi-empirical regression model results.
Deep learning techniques for physical abuse detection

Physical abuse has become a societal problem. Mostly children, women and old age people are vulnerable to it especially in cases of domestic violence or workplace aggression. Reporting it is in itself a challenge especially if there is a pre-existing relationship between the abuser and victim. In this paper we propose a deep learning technique for human action recognition and human pose identification to tackle physical abuse by detecting it in real time. 3D convolution neural network (CNN) architecture is built using 3D convolution feature extractors which extract both temporal and spatial data in the video. With multiple convolution layer and subsampling layer, the input video has been converted into feature vector. Human pose estimation is done using the detection of key points on the body. Using these points and tracking them from one frame to another gives spatial-temporal features to feed into neural network (NN). We present metrics to measure the accuracies of such systems where real time reporting and fault tolerance capabilities are of utmost importance. Weighted metrics shows accuracy of about 89.42% with precision of about 85.82% and thus shows the effectiveness of the system.
CMAR_A_195654 3351..3360

Hui Wang Xiuqi Wei Bian Wu Jingyu Su Wenbin Tan Kunyu Yang 1Department of Laboratory Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, People’s Republic of China; 2Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430023, People’s Republic of China; 3Department of Cell Biology and Anatomy, University of South Carolina School of Medicine, Columbia, SC 29208, USA Background: Nasopharyngeal carcinoma (NPC) is the common malignant tumor of nasopharynx in southern China and other southeastern Asian countries. MicroRNAs (miRNAs) have been shown to play important roles in carcinogenesis. Recently, miR-34c-3p and miR-18a-5p have been found to be involved in carcinogenesis of NPC. Furthermore, platelets in NPC patients may acquire RNAs from NPC cells and turn into “tumor-educated platelet (TEP)”, which may serve as potential biomarkers for a diagnosis of NPC. However, the expression profiles of TEP miR-34c-3p and miR-18a-5p in NPC patients and their diagnostic values are yet to be determined. Aims: To investigate expression levels of TEP miR-34c-3p and miR-18a-5p and determine their diagnostic values for NPC. Materials and methods: Relative quantitative real-time PCR was used to determine the expression levels of TEP miR-34c-3p and miR-18a-5p in NPC patients (n=54) as compared to normal subjects (n=36). The receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic values of TEP miR-34c-3p and miR-18a-5p for NPC. Results: The expression levels of TEP miR-34c-3p and miR-18a-5p were significantly higher in NPC patients as compared to healthy subjects. The ROC analysis showed that the area under the ROC curve (AUC), sensitivity, specificity and accuracy for TEP miR-34c-3p, miR-18a-5p, or a combination of both miRNAs for NPC diagnostic tests were 0.952, 94.44%, 86.11%, 91.11%, or 0.884, 85.19%, 86.11%, 85.55%, or 0.954, 92.59%, 86.11%, 90.00%, respectively. No correlation was found between expression levels of TEP miR-34c-3p or miR-18a-5p and patients’ demographic variables and their NPC tumor/node/metastasis stages. The positive rates of TEP miR-34c-3p and miR-18a-5p for NPC diagnosis were 93.8% and 87.5%, respectively, which were significantly higher than Epstein-Barr virus DNA with a positive rate of 66.7%. Conclusion: The expression levels of TEP miR-34c-3p and miR-18a-5p are upregulated in NPC, rendering a significant clinical value for NPC diagnosis. The TEP miRNAs might serve as a novel type of liquid biopsies for NPC diagnosis.
Adipose Tissue Radiodensity in Chronic Diseases: A Literature Review of the Applied Methodologies

Background: The concept of adipose tissue radiodensity is emerging and its relationship to disease prognosis has been infrequently explored. The aims of the present study were to evaluate published literature that explored adipose tissue radiodensity in relation to outcomes in health and disease and to summarize methodologies used to evaluate adipose tissue radiodensity by computed tomography (CT). Methods: A comprehensive literature review included all published studies that applied CT imaging of the abdominal region to define adipose tissue radiodensity. The review was performed without regard for study design or quality. Results: We identified 22 studies that evaluated the relationship between adipose tissue radiodensity and outcomes. The literature reviewed highlights significant methodological variation in terms of abdominal region selected, slice thickness, contrast media, dose, software, and radiodensity ranges used to define adipose tissues. This is primarily due to a lack of consensus about the effect such methodological variables have on body composition parameters. Conclusions: Authors should carefully report adipose tissue radiodensity, especially when it comes to prognosis inference. Consensus on methodology will enable meaningful advancement in understanding the importance of adipose tissue radiodensity in different disease conditions.
THE EFFECT OF YOUTUBE BEAUTY VLOGGER CREDIBILITY AND PARA-SOCIAL INTERACTION TO CONSUMER BUYING INTENT FOR FOCALLURE MAKE-UP PRODUCT

This study relies on the persuasion factors related to the beauty vlogger. This research analyze the relationship of, beauty vlogger credibility and para-social interaction – the characteristics that could lead to initiate consumer buying intent. Quantitative analyze was utilized to examine the degree of purchase intention thru scales that have been build before by academism.
Improved Scaling Relationships for Seismic Moment and Average Slip of Strike-Slip Earthquakes Incorporating Fault-Slip Rate, Fault Width, and Stress Drop

We develop a self-consistent scaling model relating magnitude Mw to surface rupture length (LE), surface displacement DE, and rupture width WE, for strike-slip faults. Knowledge of the long-term fault-slip rate SF improves magnitude estimates. Data are collected for 55 ground-rupturing strike-slip earthquakes that have geological estimates of LE, DE, and SF, and geophysical estimates of WE. We begin with the model of Anderson et al. (2017), which uses a closed form equation for the seismic moment of a surface-rupturing strike-slip fault of arbitrary aspect ratio and given stress drop, ΔτC. Using WE estimates does not improve Mw estimates. However, measurements of DE plus the relationship between ΔτC and surface slip provide an alternate approach to study WE. A grid of plausible stress drop and width pairs were used to predict displacement and earthquake magnitude. A likelihood function was computed from within the uncertainty ranges of the corresponding observed Mw and DE values. After maximizing likelihoods over earthquakes in length bins, we found the most likely values of WE for constant stress drop; these depend on the rupture length. The best-fitting model has the surprising form WE∝logLE—a gentle increase in width with rupture length. Residuals from this model are convincingly correlated to the fault-slip rate and also show a weak correlation with the crustal thickness. The resulting model thus supports a constant stress drop for ruptures of all lengths, consistent with teleseismic observation. The approach can be extended to test other observable factors that might improve the predictability of magnitude from a mapped fault for seismic hazard analyses.
Prognostic model of AU-rich genes predicting the prognosis of lung adenocarcinoma

Background AU-rich elements (ARE) are vital cis-acting short sequences in the 3’UTR affecting mRNA stability and translation. The deregulation of ARE-mediated pathways can contribute to tumorigenesis and development. Consequently, ARE-genes are promising to predict prognosis of lung adenocarcinoma (LUAD) patients. Methods Differentially expressed ARE-genes between LUAD and adjacent tissues in TCGA were investigated by Wilcoxon test. LASSO and Cox regression analyses were performed to identify a prognostic genetic signature. The genetic signature was combined with clinicopathological features to establish a prognostic model. LUAD patients were divided into high- and low-risk groups by the model. Kaplan–Meier curve, Harrell’s concordance index (C-index), calibration curves and decision curve analyses (DCA) were used to assess the model. Function enrichment analysis, immunity and tumor mutation analyses were performed to further explore the underlying molecular mechanisms. GEO data were used for external validation. Results Twelve prognostic genes were identified. The gene riskScore, age and stage were independent prognostic factors. The high-risk group had worse overall survival and was less sensitive to chemotherapy and radiotherapy (P < 0.01). C-index and calibration curves showed good performance on survival prediction in both TCGA (1, 3, 5-year ROC: 0.788, 0.776, 0.766) and the GSE13213 validation cohort (1, 3, 5-year ROC: 0.781, 0.811, 0.734). DCA showed the model had notable clinical net benefit. Furthermore, the high-risk group were enriched in cell cycle, DNA damage response, multiple oncological pathways and associated with higher PD-L1 expression, M1 macrophage infiltration. There was no significant difference in tumor mutation burden (TMB) between high- and low-risk groups. Conclusion ARE-genes can reliably predict prognosis of LUAD and may become new therapeutic targets for LUAD.
Gestational diabetes mellitus: Major risk factors and pregnancy-related outcomes: A cohort study

Abstract Background Gestational diabetes mellitus (GDM) is a major pregnancy endocrine problem that has several confirmed risk factors and is associated with adverse pregnancy-related outcomes (PRO). Objective To evaluate the relationship between GDM diagnosis and the associated risk factors of PRO (maternal, intrapartum, perinatal, and neonatal) in accordance with International Association of Diabetes and Pregnancy Study Groups criteria. Materials and Methods This prospective cohort study was performed with 531 singleton parturient (265 GDM and 266 non-GDM). They were selected consecutively from referral hospitals, and the maternal, intrapartum, perinatal, and neonatal outcomes were assessed. Results The major risk factors influencing the GDM diagnosis were maternal age, obesity, family history of diabetes, previous history of GDM, and previous history of macrosomia. In the comparison of PRO between the groups, significant associations were detected for emergency cesarean delivery, preeclampsia, polyhydramnios, premature rupture of membrane, preterm delivery, and neonatal hyperbilirubinemia in the GDM group. In the multivariate logistic regression analysis, a previous history of stillbirth was significantly associated with maternal and perinatal outcomes. The odds ratios (CI 95%) of the PRO in the women with a GDM diagnosis were: maternal = 2.43 (1.51-3.90), intrapartum = 2.05 (1.35-3.11), perinatal = 2.00 (1.29-3.10), and neonatal = 1.68 (1.08-2.62). The PRO was significantly correlated with GDM diagnosis, but not with the risk factors. Conclusion The adverse pregnancy outcomes were significantly correlated with GDM diagnosis, and the outcomes were not directly affected by the risk factors. Given the related adverse outcomes for mothers and offspring, early screening and management of GDM is necessary especially in Asians and in low-/middle-income countries.
Modelling of release kinetics of mebendazole from solid dispersion based formulations in simulted gastric fluid

Mebendazole (MBZ) is the main treatment of human echinococcosis caused by the larval forms of the parasite Echinococcus granulosus or E. multilocuralis, which enter in blood and contaminate internal organs, and has been shown active also in various cancer types. Due to its poor solubility in intestinal fluid, in both cases its bioavailability is a critical factor in determining the extent and duration of effect. Tablets based on solid mebendazole dispersions in polyethylene glycol 6000 (PEG) by melting method were prepared in the ratios of 1: 1 and 1: 2.5, with croscarmellose and Ludiflash as excipients, in order to increase its bioavailability. In vitro release assays were performed in simulated gastric fluid. The release was performed using USP apparatus 2 (paddles) model using an ERWEKA DT800 HH device at a rotational speed of 75 rpm. The resulting samples were quantitatively analyzed using a validated HPLC method. Release kinetics was performed using Noyes-Whitney, Higuchi, Siepmann Peppas, Weibull and Immediate Release in Semi-infinite Medium model (IR-SIM). Swelling and disaggregation excipients led to a release in two, well separated, phases: pre-disaggregation and postdisaggregation. Release after three hours decreased following inclusion of MBZ as solid dispersion in PEG from 100 % in absence of PEG to approximately 50 % in case of 1:1 MBZ-PEG proportion and to some, 20 % in case of 1: 2.5 MBZ-PEG proportion. In both phases, the kinetics of release fitted well the law of the radical and the law of Noyes Whitney. Since the site of the action / absorption of mebendazole is not at the gastric but at the intestinal level, as well as the fact that mebendazole has the tendency to precipitate in the passage from the gastric fluid to the intestine fluid, it was considered that the slower gastric release may partially cancel out its tendency to precipitate. Square root type behavior can appear in case of dissolution of active substance in solvent penetrating the tablet matrix (Higuchi model) or in case of release outside the matrix acting as an infinite reservoir. Since Noyes Whitney model suppose the release in a limit layer outside the matrix, it was considered an argument for IR-SIM model. The conclusion has a general methodological significance in conditions of quasi-total acceptance in literature of Higuchi model even in conditions far of those used in its deduction.
Result of high Fibular Osteotomy (HFO) in Osteoarthritis knee

Ajmal Khan Silro1, Muhammad Faraz Jokhio2, Mohsin Aijaz Soomro3, Raheel Akbar Baloch4, Niaz Hussain Keerio*5, Najeeb Ur Rehman6, Syed Shahid Noor7 1Dibba Hospital, Fujairah, United Arab Emirates 2Liaquat University of Medical and Health Science, Jamshoro, Sindh, Pakistan 3Suleman Roshan Medical Collage, Tando Adam, Sanghar, Pakistan 4Liaquat University Hospital, Hyderabad, Sindh, Pakistan 5Muhammad Medical College and Hospital, Mirpurkhas, Sindh, Pakistan 6Peoples University of health and Sciences for Women, Nawabshah, Sindh, Pakistan 7Department of Orthopedic, Liaquat National Hospital And Medical College Karachi, Sindh, Pakistan