Miracle-dz/UniFAR-FTUs huggingface dataset:
Trends in Comorbidities Among Human Immunodeficiency Virus–Infected Hospital Admissions in New York City from 2006–2016

Background. Due to the advent and success of antiretroviral therapy, the number of people living and aging with human immunodeficiency virus (HIV) has grown substantially. Although people living with HIV (PLHIV) are experiencing longer life expectan-cies, this achievement may be undermined by increasing and disproportionate chronic disease burden among PLHIV. Methods. This study is a retrospective analysis of adult ( ≥ 18 years) inpatient hospital discharges from a large hospital system in the New York City, New York metropolitan area, between 1 January 2006 and 31 December 2016. We aimed to investigate (1) changes in the prevalence of Charlson-defined comorbidities among PLHIV hospitalized between 2006 and 2016 and (2) changes in the unadjusted prevalence ratio (PR) of comorbidities in HIV-positive versus HIV-negative admissions over time. Results. Of 898 139 hospital admissions from 2006–2016, 19 039 (2.1%) were HIV positive. Across all admissions during the study period, the greatest comorbidity disparities between HIV-positive and HIV-negative admissions were mild liver disease (PR, 4.9 [95% confidence interval, 4.8–5.1]), moderate or severe liver disease (PR, 2.2 [2.0–2.4]), and chronic pulmonary disease (PR, 1.8 [1.8–1.8]). Conclusions. The prevalence and relative burden of comorbidities among hospitalized PLHIV are changing over time. Careful monitoring and intensive discharge planning may be effective strategies for addressing the evolving health needs of PLHIV.
Practice of Epidemiology When Is a Complete-Case Approach to Missing Data Valid? The Importance of Effect-Measure Modiﬁcation

When estimating causal effects, careful handling of missing data is needed to avoid bias. Complete-case analysis is commonly used in epidemiologic analyses. Previous work has shown that covariate-stratified effect estimates from complete-case analysis are unbiased when missingness is independent of the outcome conditional on the exposure and covariates. Here, we assess the bias of complete-case analysis for adjusted marginal effects when confounding is present under various causal structures of missing data. We show that estimation of the marginal risk difference requires an unbiased estimate of the unconditional joint distribution of confounders and any other covariates required for conditional independence of missingness and outcome. The dependence of missing data on these covariates must be considered to obtain a valid estimate of the covariate distribution. If none of these covariates are effect-measure modifiers on the absolute scale, however, the marginal risk difference will equal the stratified risk differences and the complete-case analysis will be unbiased when the stratified effect estimates are unbiased. Estimation of unbiased marginal effects in complete-case analysis therefore requires close consideration of causal structure and effect-measure modification.
Common Variants in 8q24 and MYC Oncogene are Associated with Risk for Prostate Cancer and Tumor Aggressiveness in Men of European Ancestry

BACKGROUND— Recent whole genome association studies have independently identified multiple prostate cancer (PC) risk variants on 8q24. We have evaluated association of common variants in this region with PC susceptibility and tumor aggressiveness in a sample of European American men. METHODS— Forty-nine tagging SNPs including three previously reported significant variants (rs1447295, rs6983267, rs16901979) and seven variants in the 5 ′ upstream region of the MYC proto-oncogene were tested for association with susceptibility to PC and tumor aggressiveness in 596 histologically verified PC cases and 567 ethnically matched controls. RESULTS— Significant associations with susceptibility to PC were found at 17 SNPs, four of which (rs1016342, rs1378897, rs871135 and rs6470517) remained significant after adjusting for multiple corrections. One of the associated SNPs, rs871135, is located in the putative gene POU5F1P1 within the 8q24 region. An in slico analysis showed that the associated variant of this SNP alters a transcription factor implicating a plausible regulatory role. Additionally, one of the significantly associated SNPs, rs6470517, with PC susceptibility showed a significant over-representation of the G allele in cases with aggressive tumor. CONCLUSIONS— Although this study does not directly confirm associations of the three specific SNPs (cited above), it corroborates reported signals of association in 8q24 reaffirming that genetic variation on 8q24 influences susceptibility to PC in men of European ancestry. Although our study did not confirm the allelic association of rs1447295, meta-analysis of this SNP provided support to previous reported associations. Further, this study implicates the 8q24 region with aggressive forms of PC.
Influence of Diabetes on Outcomes in Patients After Left Ventricular Assist Device Implantation

, Abstract Background— Despite previous studies, the mortality risk of diabetic patients post left ventricular assist device (LVAD) implant remains unclear. In addition, the relationship between the degree of glycemic control and long-term mortality risk in LVAD patients with diabetes has not been established. Methods— Ninety-five non-diabetic and 96 diabetic patients from the University of Rochester Medical Center, who received a HeartMate II continuous-flow LVAD between May 2008 and June 2014 were included in this study. The primary outcome was all-cause mortality. Secondary outcomes included rates of infection, neurological dysfunction, renal dysfunction, and re-hospitalization. Kaplan-Meier survival analyses and Cox models were utilized. Results— During follow-up, 32 (33%) diabetics and 15 (16%) non-diabetics died following LVAD implantation. Cumulative probability of death was higher in diabetics when compared to non-diabetics (42% vs. 21% at 3 years, p=0.013). There were no significant differences in overall rates of infection, neurological dysfunction, and re-hospitalization between the two groups. However after an initial secondary outcome event, diabetics continued to have a higher mortality rate when compared to non-diabetics. There was no statistically significant difference in the risk of death between diabetics with pre-LVAD hemoglobin A1c < 7.0% and diabetics pre-LVAD hemoglobin 7.0% Conclusions— Diabetics who underwent LVAD implantation had a higher risk of death compared to non-diabetic patients. Adverse event rates did not differ among the two groups. Finally, the degree of glycemic control in diabetics prior to LVAD was not found to influence mortality. of Among Risk factors for development of heart failure include coronary artery disease, hypertension, valvular heart disease, and diabetes [2]. Diabetes itself has been associated with a twofold increased risk of developing symptomatic congestive heart failure [3]. Previous studies have shown that with The total number of individuals with is expected to rise to 366 2030 from 171 we can the accordingly become risk factors for heart development.
Coupling backbone flexibility and amino acid sequence selection in protein design

Using a protein design algorithm that considers side-chain packing quantitatively, the effect of explicit backbone motion on the selection of amino acids in protein design was assessed in the core of the streptococcal protein G PI domain (GPI). Concerted backbone motion was introduced by varying GPl’s supersecondary structure parameter values. The stability and structural flexibility of seven of the redesigned proteins were determined experimentally and showed that core variants containing as many as 6 of 10 possible mutations retain native-like properties. This result demonstrates that backbone flexibility can be combined explicitly with amino acid side-chain selection and that the selection algorithm is sufficiently robust to tolerate perturbations as large as 15% of GPl’s native supersecondary structure parameter values.
Predictors of Hospitalization with Individuals With First-Episode Psychosis: Data From a Two-Year Follow-Up in the RAISE-ETP Study

Objective: Despite treatment advances in other domains, inpatient psychiatric hospitalization rates for individuals with first-episode psychosis remain high. Even with early intervention services, a third or more of individuals are hospitalized over the first 2 years of treatment. Reducing hospitalization is desirable from individuals’ perspectives and for public health reasons as hospitalization costs are a major component of treatment costs. Method: Univariate and multivariate baseline and time-varying covariate analyses were conducted to identify predictors of hospitalization in the RAISE-ETP study, a two-year cluster randomized trial for participants experiencing a first episode of psychosis who were outpatients at study entry. The trial compared an early intervention treatment model (NAVIGATE) to usual community care at 34 clinics across the United States. Results: 34% of NAVIGATE and 37% of usual care participants were hospitalized during the trial. Risk analyses revealed significant predictors of hospitalization to be: the number of hospitalizations before study entry, duration of untreated psychosis, and time-varying days of substance misuse, presence of Positive and Negative Syndrome Scale positive symptoms, and beliefs about the value of medication. Conclusions: These results indicate that hospital use may be decreased by reducing the duration of untreated psychosis and prior hospitalizations, minimizing residual symptoms, preventing substance misuse and facilitating adherence in medication taking. Addressing these factors could enhance the impact of first-episode early intervention treatment models as well as enhance outcomes of first-episode psychosis treated with other models. data covering a 2 follow-up and low hospitalization rates for studies with 2 years of follow-up.
Short Paper

Abortion in sheep and goats causes enormous economic losses. This study revealed the epidemiology of abortion caused by Brucella melitensis, Coxiella burnetii and Salmonella abortusovis in Baluchi sheep in Sistan region. In the autumn of 2015 and winter of 2016, a total of 78 aborted sheep fetuses were collected from all over the Sistan region. Risk factors, including location of livestock, history of abortion, gender of fetus, age of fetus, age of ewe and parity were obtained using a questionnaire. The results showed that 27 fetuses (35%) were infected with these organisms. Infection with B. melitensis, C. burnetii and S. abortusovis were identified respectively in 15 (19.2%), 13 (16.6%) and 1 (1.3%) fetus. Logistic regression analysis showed that infection with B. melitensis in male fetuses is higher than females (OR=3.73, P=0.040), also infection with C. burnetii in ≤2 years’ ewes (OR=0.047, P=0.009) and 2-5 years’ ewes (OR=0.197, P=0.069) is lower than ≥5 years’ ewes.
Selective proliferation of normal human melanocytes in vitro in the presence of phorbol ester and cholera toxin

Cultures consisting almost entirely of human melanocytes were obtained from epidermal single-cell suspensions by using phorbol 12-myristate 13-acetate (10 ng/ml) in the culture medium. At this concentration, phorbol ester is toxic to human keratinocytes but not to melanocytes. When the seeding density was optimal (0.8-2 x 104/cm2) and the medium contained both phorbol ester and cholera toxin, melanocytes proliferated exten-sively. Under these conditions, human melanocytes could be pas- saged serially in vitro and grown in quantity. This cell culture system can thus be used to answer basic questions related to pigment cell biology and may serve as a control for studies of malignant melanocytes.
Investigation of Optical, Structural, Morphological and Electrical Properties of Electrodeposited Cobalt Doped Copper Selenide (Cu_(1-x) Co_x Se) Thin Films

Undoped and cobalt doped copper selenide thin films have been successfully prepared unto fluorine tin oxide (FTO) substrates by electrodeposition method using copper acetate, cobalt nitrate and selenium (IV) oxide as precursors for copper, cobalt and selenium ions respectively. Deposited thin films were subjected to optical, structural, morphological, compositional and electrical analysis using spectrophotometer, x-ray diffractometer, scanning electron microscope (SEM), energy dispersive x-ray spectroscopy (EDS) and 4-point probe. Optical results observed between the wavelength range of 300 nm and 1,000 nm showed that the films have good optical responses. Absorbance values ranged between 0.1 and 0.81 while transmittance lies between 15.59 and 78.68 %. Energy band gap of the films was found to vary from 2.10 to 2.28 eV. These results showed that cobalt as a dopant could be used to modify properties of copper selenide thin films. Structural analysis showed that the deposited films are polycrystalline in nature with hexagonal structural phase. Crystallite sizes of range 27.56 to 34.27 nm were obtained while dislocation density lied between and . Microstrain ranged between and . Micrograph images showed flake-like particles that increased in size as percentage of cobalt increased. Energy dispersive spectroscope (EDS) results confirmed the incorporation of cobalt on the deposited copper selenide films. Electrical resistivity of the films increased from to while conductivity decreased from to as a result of variation in cobalt ion concentration. These properties of the deposited thin films positioned them for solar cell and optoelectronics device applications. HIGHLIGHTS Energy band gap of electrosynthesized cobalt doped copper selenide ranged from 2.10 to 2.28 eV Film thickness values ranged from 48.41 and 176.79 nm. Thickness values of the films were found to increase as concentration of cobalt increase Increase in dopant concentration resulted to shift in diffraction peaks towards larger angles Increase in crystallite size from 27.56 - 34.27 nm was observed as dopant concentration increases SEM images of the films revealed flake - like particles of different sizes GRAPHICAL ABSTRACT
Unified Theory of the Arc Auroras: Formation Mechanism of the Arc Auroras Conforming General Principles of Convection and FAC Generation

The arc aurora can be considered as the visualization of the field‐aligned current (FAC). In various cases, the numerically reproduced FAC morphologically matches well with that of the observed arc aurora. Such example can be seen in the sun‐aligned arc, the fan arc, and the theta aurora under the northward interplanetary magnetic field (IMF), and the substorm, the quiet arc, and the initial brightening under the southward IMF. The FAC reproduced by the global simulation is based on the general principle of the magnetohydrodynamic (MHD). In such general principle, the FAC is transmission of net charge, net charge is divE, and E is equivalent to motion. After all, the FAC is transmission of convection motion. In order to transmit the FAC to the dissipative ionosphere based on the MHD, formations of the dynamo and shear that leads from the magnetosphere to the ionosphere are essential. The dynamo and shear are reproduced so as to properly match with each convection structure. The comparison under various magnetospheric topologies between the global simulation and the arc aurora observation indicates that the arc aurora and the FAC occurs inevitably controlled by convection structure. Such a principle of the FAC and convection holds even for the onset FAC.
Genetic variation of chigger mites in the Republic of Korea

The chigger mite is a known vector for the zoonotic disease, Tsutsugamushi, which affects more than 4,000 patients each year in the Republic of Korea (ROK) since 2004. However, molecular data is only available for a few species of chigger mite, compared to the numbers of known species. This study focused on securing molecular data for six species (Leptotrombidium pallidum, Leptotrombidium scutellare, Leptotrombidium palpale, Leptotrombidium orientale, Neotrombicula gardellai, and Euschoengastia koreaensis) of chigger mites in the ROK from cytochrome c oxidase subunit I (COI) and internal transcribed spacer 2 (ITS2). In the results, there were each two genotypes in L. pallidum and L. palpale, and three genotypes in L. scutellae in the COI, whereas the ITS2 sequence was identical within the species. The other three species were identical from COI and ITS2. This study first revealed the genetic variation in the COI sequences of chigger mites in the ROK. Further studies could determine how this variation is related to ecological behavior and disease transmission.
Electrohydrodynamic Atomization of Graphene Nano-Suspension

In this paper, graphene nanosuspension was spray deposited using electrohydrodynamic atomization (EHDA) technique, and the polydimethylsiloxane (PDMS) was used as the substrate during the EHDA process. The effect of the PDMS substrate before and after oxygen plasma treatment on the characteristics of EHDA was examined. A cone-jet mode of the EHDA of graphene nanosuspension was obtained using the oxygen plasma treated PDMS substrate. In addition graphene films were deposited on the oxygen plasma treated PDMS at different working distances. The lowest sheet resistance of the graphene films is 127Ω·sq-1. Furthermore, graphene lines at the range of 30μm-170μm were fabricated using the template assisted EHDA deposition method.
Volatile compounds from Phyla scaberrima (Juss. ex Pers.) Moldenke and Dysphania ambrosioides (L.) Mosyakin & Clemants as possible SARS-CoV-2 protease inhibitors: Identification and in-silico study

Context: COVID-19 is a pandemic that has affected the entire population, characterized by multisystemic involvement. With around 130 million cases of infection and more than 2.5 million deaths globally. However, the development of a low-efficacy treatment has led to the study of natural products as possible therapeutic alternatives against SARS-CoV-2. Aims: To identify volatile compounds present in two plants in the Colombian Pacific and carry out in-silico studies to search for promising inhibitory molecules against SARS-CoV-2 proteases. Methods: This research carried out the identification of metabolites of two plants identified in the Colombian Pacific, called P. scaberrima (Juss. ex Pers.) Moldenke y D. ambrosioides (L.) Mosyakin & Clemants. Ethanolic extracts were obtained by rotary-evaporation and determinated by GC-MS. Subsequently, in-silico studies were carried out by molecular docking against Mpro and PLpro using Autodock-vina 1.1. Also, a prediction of ADMET properties using SwissADME and GUSAR-Online server was performed. Results: Thus, 15 volatile compounds with similarities greater than 85% were identified from both extracts, mostly sesquiterpenic and monoterpenic compounds. The compounds that showed the highest affinity against Mpro were α-amorphene and phytol for PLpro. Likewise, these were contrasted with co-crystallized molecules such as boceprevir and VIR2-251 as control structures. Finally, the predictions of ADMET properties showed values consistent with the literature. Conclusions: Therefore, the follow-up of in-silico studies with these plants from Colombian pacific are considered as possible tools in the search for active molecules against proteases linked to virus.
ProAll-D: protein allergen detection using long short term memory - a deep learning approach

Background An allergic reaction is the immune system's overreacting to a previously encountered, typically benign molecule, frequently a protein. Allergy reactions can result in rashes, itching, mucous membrane swelling, asthma, coughing, and other bizarre symptoms. To anticipate allergies, a wide range of principles and methods have been applied in bioinformatics. The sequence similarity approach's positive predictive value is very low and ineffective for methods based on FAO/WHO criteria, making it difficult to predict possible allergens. Method This work advocated the use of a deep learning model LSTM (Long Short-Term Memory) to overcome the limitations of traditional approaches and machine learning lower performance models in predicting the allergenicity of dietary proteins. A total of 2,427 allergens and 2,427 non-allergens, from a variety of sources, including the Central Science Laboratory and the NCBI are used. The data was divided 80:20 for training and testing purposes. These techniques have all been implemented in Python. To describe the protein sequences of allergens and non-allergens, five E-descriptors were used. E1 (hydrophilic character of peptides), E2 (length), E3(propensity to form helices), E4(abundance and dispersion), and E5 (propensity of beta strands) are used to make the variable-length protein sequence to uniform length using ACC transformation. A total of eight machine learning techniques have been taken into consideration. Results The Gaussian Naive Bayes as accuracy of 64.14 %, Radius Neighbour's Classifier with 49.2 %, Bagging Classifier was 85.8 %, ADA Boost was 76.9 %, Linear Discriminant Analysis has 76.13 %, Quadratic Discriminant Analysis was 84.2 %, Extra Tree Classifier was 90%, and LSTM is 91.5 %. Conclusion As the LSTM, has an AUC value of 91.5 % is regarded best in predicting allergens. A web server called ProAll-D has been created that successfully identifies novel allergens using the LSTM approach. Users can use the link https://doi.org/10.17632/tjmt97xpjf.1 to access the ProAll-D server and data.
Preoperative brain connectome predicts postoperative changes in processing speed in moyamoya disease

Abstract Moyamoya disease is a rare cerebrovascular disorder associated with cognitive dysfunction. It is usually treated by surgical revascularization, but research on the neurocognitive outcomes of revascularization surgery is controversial. Given that neurocognitive impairment could affect the daily activities of patients with moyamoya disease, early detection of postoperative neurocognitive outcomes has the potential to improve patient management. In this study, we applied a well-established connectome-based predictive modelling approach to develop machine learning models that used preoperative resting-state functional connectivity to predict postoperative changes in processing speed in patients with moyamoya disease. Twelve adult patients with moyamoya disease (age range: 23–49 years; female/male: 9/3) were recruited prior to surgery and underwent follow-up at 1 and 6 months after surgery. Twenty healthy controls (age range: 24–54 years; female/male: 14/6) were recruited and completed the behavioural test at baseline, 1-month follow-up and 6-month follow-up. Behavioural results indicated that the behavioural changes in processing speed at 1 and 6 months after surgery compared with baseline were not significant. Importantly, we showed that preoperative resting-state functional connectivity significantly predicted postoperative changes in processing speed at 1 month after surgery (negative network: ρ = 0.63, Pcorr = 0.017) and 6 months after surgery (positive network: ρ = 0.62, Pcorr = 0.010; negative network: ρ = 0.55, Pcorr = 0.010). We also identified cerebro-cerebellar and cortico-subcortical connectivities that were consistently associated with processing speed. The brain regions identified from our predictive models are not only consistent with previous studies but also extend previous findings by revealing their potential roles in postoperative neurocognitive functions in patients with moyamoya disease. Taken together, our findings provide preliminary evidence that preoperative resting-state functional connectivity might predict the post-surgical longitudinal neurocognitive changes in patients with moyamoya disease. Given that processing speed is a crucial cognitive ability supporting higher neurocognitive functions, this study’s findings offer important insight into the clinical management of patients with moyamoya disease.