Miracle-dz/UniFAR-FTUs huggingface dataset:
Strategic analyses to identify key structural features of antiviral/antimalarial compounds for their binding interactions with 3CLpro, PLpro and RdRp of SARS-CoV-2: in silico molecular docking and dynamic simulation studies

Abstract Severe acute respiratory syndrome coronavirus (SARS-CoV-2), a novel member of the betacoronavirus family is a single-stranded RNA virus that has spread worldwide prompting the World Health Organization to declare a global pandemic. This creates an alarming situation and generates an urgent need to develop innovative therapeutic agents. In this context, an in silico molecular docking and molecular dynamics (MD) simulation study on the existing 58 antiviral and antimalarial compounds was performed on 3CLpro, PLpro and RdRp SARS-CoV-2 proteins. The antiviral compounds are best fitted in the binding pockets and interact more profoundly with the amino acid residues compared to antimalarial compounds. An HIV protease inhibitor, saquinavir showed a good dock score and binding free energy with varied binding interactions against 3CLpro and PLpro. While, adefovir, a nucleotide HBV DNA polymerase inhibitor exhibited good dock score and binding interactions against RdRp. Although, the antimalarial compounds showed relatively less dock score but were found to be crucial in displaying essential binding interactions with these proteins. The MD simulation runs for 100 ns on 3CLpro–saquinavir, PLpro–saquinavir and RdRp–adefovir complexes using Desmond revealed fairly stable nature of interactions. This study helped in understanding the key interactions of the vital functionalities that provide a concrete base to develop lead molecules effective against SARS-CoV-2. Graphical Abstract Communicated by Ramaswamy H. Sarma
Multiplexed electrokinetic sensor for detection and therapy monitoring of extracellular vesicles from liquid biopsies of non-small-cell lung cancer patients

Liquid biopsies based on extracellular vesicle (EV) protein profiles represent a promising tool for treatment monitoring of tumors, including non-small-cell lung cancers (NSCLC). In this study, we present the development of an electrokinetic sensor for multiplexed surface protein profiling of EVs and analysis of clinical samples. The method detects the difference in the streaming current obtained as a result of EV binding to the inner surface of a functionalized microcapillary, thereby estimating the expression level of a surface marker. Using multiple microchannels functionalized with different antibodies in a parallel fluidic connection, we first demonstrate the capacity for simultaneous detection of multiple surface markers in small EVs (sEVs) from NSCLC cells. To investigate the prospects of liquid biopsies based on EVs, we then apply the method to profile sEVs isolated from the pleural effusion (PE) fluids of three NSCLC adenocarcinoma patients with different genomic alterations (ALK-fusion, KRAS and EGFR) and applied treatments (chemotherapy, EGFR or ALK tyrosine kinase inhibitors). These vesicles were targeted against CD9 tetraspanin, as well as EGFR and PD-L1, two markers of interest in NSCLC. The electrokinetic signals showed detection of these markers on sEVs yet highlighting distinct interpatient differences, e.g., increased EGFR levels in sEVs from a patient with EGFR mutation as compared to an ALK-mutant one. The sensors also detected differences in PD-L1 expressions, in line with those measured by complementary methods. The analysis of sEVs from a patient prior and post crizotinib treatment also revealed a significant increase in the expression of some markers, e.g. EGFR and PD-L1. The obtained results hold promise for the application of the method for tumor treatment monitoring based on sEVs from liquid biopsies.
Effectiveness of Virtual Reality and Interactive Simulators on Dental Education Outcomes: Systematic Review

Abstract In recent years, virtual reality and interactive digital simulations have been used in dental education to train dental students before interacting with real patients. Scientific evidence presented the application of virtual technology in dental education and some recent publications suggested that virtual and haptic technologies may have positive effects on dental education outcomes. The aim of this systematic review was to determine whether virtual technologies have positive effects on dental education outcomes and to explore the attitudes of dental students and educators toward these technologies. A thorough search was conducted in PubMed, Scopus, MEDLINE (via EBSCO), The Cochrane Library (via Wiley), Web of Science Core Collection (via Thomson Reuters), and Dentistry and Oral Science source (via EBSCO) using the keywords (student, dental) AND (education, dental) AND (virtual reality) OR (augmented reality) OR (haptics) OR (simulation) AND (dentistry) OR (dental medicine). The quality of the reported information was assessed following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement for systematic reviews. A total of 73 publications were considered for this review. Fifty-two of the selected studies showed significant improvement in educational outcomes and virtual technologies were positively perceived by all the participants. Within the limitations of this review, virtual technology appears to improve education outcomes in dental students. Further studies with larger samples and longer term clinical trials are needed to substantiate this potential positive impact of various virtual technologies on dental education outcomes.
Comprehensive analysis of alternative splicing profiling reveals novel events associated with prognosis and the infiltration of immune cells in prostate cancer

Background Alternative splicing (AS) is believed to play a vital role in tumor development. Therefore, comprehensive investigation of AS and its biological function in prostate cancer (PCa) is crucial. Methods The AS profiling of 489 patients with PCa was obtained from The Cancer Genome Atlas (TCGA) SpliceSeq database. Bioinformatics tools were used to describe splicing associations and build prognostic models. Unsupervised clustering of the determined prognostic AS events and the relationship with immune characteristics were also explored. Results In total, 20,723 AS events were detected and 2,805 were identified in PCa. In the regulatory networks, the data suggested a significant correlation between splicing factor (SF) expression and AS events. To stratify the progression risk of PCa patients, prognostic models were constructed using splicing patterns. Six AS events were screened out as independent prognostic factors for progression-free survival. Based on the gene features, we constructed the combined prognostic predictors model, and the receiver operating characteristic (ROC) curve for this model reached a high area under the ROC curve (AUC) of 0.729793, indicating a favorable ability to predict patient outcomes. Through unsupervised clustering analysis, the correlations between AS-based clusters and prognosis as well as immune characteristics were revealed. The correlation analysis on TIMER revealed the relationship between gene expression and immune cell infiltration. Conclusions This in-depth genome-wide analysis of the AS profiling in PCa revealed unique AS events associated with cancer progression and the infiltration of immune cells, with potential for predicting outcomes and therapeutic responses.
Relating sinking and suspended microbial communities in the California Current Ecosystem: Digestion resistance and the contributions of phytoplankton taxa to export.

We used 16S, 18S, plastid and ITS (for Synechococcus strains) sequencing to quantify relative microbial abundances in water-column samples and on sediment-trap-collected particles across an environmental gradient in the California Current Ecosystem (CCE) spanning a > 60-fold range of surface chlorophyll. Most mixed-layer dominant eukaryotes and prokaryotes were consistently underrepresented on sinking particles. Diatoms were the only phototrophic taxa consistently overrepresented. Even within this class, however, one genus (Thalassiosira) was a particle-enriched dominant, while a similarly abundant species was poorly represented. Synechococcus was significantly enriched on sinking particles at only one of four sites, but clade I was disproportionately abundant on sinking particles throughout the region compared to clade IV, the euphotic-zone co-dominant. The most abundant microbes on particles across the CCE were organisms with distributional maxima close to the sediment-trap depth (rhizarians), microbes associated with metazoans or sinking particles as a nutritional habitat (certain aveolates, Gammaproteobacteria), and organisms that resist digestive degradation of their DNA (Thalassiosira, Synechococcus). For assessing taxon contributions of phytoplankton to carbon export, our results highlight the need for sequence-based quantitative approaches that can be used to integrate euphotic-zone abundances, compute rates and account for taxon differences in preservation of sequence markers through trophic processing. This article is protected by copyright. All rights reserved.
Weight and body composition changes affect resting energy expenditure predictive equations during a 12‐month weight‐loss intervention

Mathematical equations that predict resting energy expenditure (REE) are widely used to derive calorie prescriptions during weight‐loss interventions. Although such equations are known to introduce group‐ and individual‐level error into REE prediction, their validity has largely been assessed in weight‐stable populations. Therefore, this study sought to characterize how weight change affects the validity of commonly used REE predictive models throughout a 12‐month weight‐loss intervention.
Discordant humoral and T cell immune responses to SARS-CoV-2 vaccination in people with multiple sclerosis on anti-CD20 therapy

Background: Sphingosine-1-phosphate receptor (S1P) modulators and antiCD20 therapies impair humoral responses to SARS-CoV-2 mRNA vaccines. Whether disease modifying therapies (DMTs) for multiple sclerosis (MS) also impact T cell immune response to vaccination is unknown. Methods: In 101 people with MS, we measured humoral responses via an immunoassay to measure IgG against the COVID-19 spike S1 glycoprotein in serum. We also measured T cell responses using FluoroSpot assay for interferon gamma (IFN-gamma; Mabtech,Sweden) using cryopreserved rested PBMCs and then incubated in cRPMI with 1microg/ml of pooled peptides spanning the entire spike glycoprotein (Genscript, 2 pools; 158 peptides each). Plates were read on an AID iSpot Spectrum to determine number of spot forming cells (SFC)/10 6 PBMCs. We tested for differences in immune responses across DMTs using linear models. Findings: Humoral responses were detected in 22/39 (56.4%) participants on anti-CD20 and in 59/63 (93.6%) participants on no or other DMTs. In a subset with immune cell phenotyping (n=88; 87%), T cell responses were detected in 76/88 (86%), including 32/33 (96.9%) participants on anti-CD20 therapies. AntiCD20 therapies were associated with an increase in IFN-gamma; SFC counts relative to those on no DMT or other DMTs (for antiCD20 vs. no DMT: 425.9% higher [95%CI: 109.6%, 1206.6%] higher; p<0.001; for antiCD20 vs. other DMTs: 289.6% [95%CI: 85.9%, 716.6%] higher; p<0.001). Interpretation: We identified a robust T cell response in individuals on anti-CD20 therapies despite a reduced humoral response to SARS-CoV-2 vaccination. Follow up studies are needed to determine if this translates to protection against COVID-19 infection.
Quantum-enhanced rubidium atomic magnetometer based on Faraday rotation via 795 nm stokes operator squeezed light

With the help of Stokes operator Ŝ2 squeezed state (also called polarization squeezed state (PSS)) of 795 nm light, rubidium-87 (87Rb) atomic magnetometer based on Faraday rotation (FR) has been implemented and characterized. The PSS of Stokes operator Ŝ2 of 795 nm light has been prepared by means of coherently combining the polarization coherent state (PCS) of a linearly p-polarized bright 795 nm light beam and a linearly s-polarized squeezed vacuum state (SVS) generated by a 397.5 nm ultraviolet laser pumped sub-threshold optical parametric oscillator (OPO) with a PPKTP bulk crystal inside the OPO cavity. PSS with a squeezing level of −3.7 ± 0.3 dB has been achieved around the analysis frequency of 10 kHz. At different transitions of D1 line, various frequency detuning, and reasonable atomic vapor cell’s temperature, FR has been measured and compared. To decrease absorption (scattering) losses and the back-action from atomic spin noise to the probe beam’s polarization noise for maintaining the quantum properties of PSS of Stokes operator Ŝ2 of 795 nm light, we had to run our magnetometer with 87Rb vapor cell’s temperature below 60 °C, at which the PSS was almost destroyed. The sensitivities of magnetic field measurement were characterized via measuring signal-to-noise ratio of the alternating current calibrated magnetic field signal with a balanced polarimeter. Under the conditions of the atomic number density of ∼5.8 × 1010 cm−3 (T ∼ 40 °C) and the probe beam with a detuning of ∼−400 MHz relative to the 5S1/2 (F g = 2) − 5P1/2 (F e = 1) transition of 87Rb D1 line, a typical sensitivity of ∼19.5 pT (Hz1/2)−1 has been achieved employing PSS of Stokes operator Ŝ2 as the probe, compared with a sensitivity of ∼28.3pT (Hz1/2)−1 using PCS as the probe. We preliminarily demonstrated that the quantum-enhanced sensitivity in a Faraday-rotation-based 87Rb atomic magnetometer with the help of PSS of 795 nm light.
Secure Outsourced Top-k Selection Queries against Untrusted Cloud Service Providers

As cloud computing reshapes the global IT industry, an increasing number of business owners have outsourced their datasets to third-party cloud service providers (CSP), which in turn answer data queries from end users on their behalf. A well known security challenge in data outsourcing is that the CSP cannot be fully trusted, which may return inauthentic or unsound query results for various reasons. This paper considers top-k selection queries, an important type of queries widely used in practice. In a top-k selection query, a user specifies a scoring function and asks for the k objects with the highest scores. Despite several recent efforts, existing solutions can only support a limited range of scoring functions with explicit forms known in advance. This paper presents three novel schemes that allow a user to verify the integrity and soundness of any top-k selection query result returned by an untrusted CSP. The first two schemes support monotone scoring functions, and the third scheme supports scoring functions comprised of both monotonically non-decreasing and non-increasing subscoring functions. Detailed simulation studies using a real dataset confirm the efficacy and efficiency of the proposed schemes and their significant advantages over prior solutions.
A WIHIC exploration of secondary school science classrooms: A case study from Trinidad & Tobago

In this work the WIHIC (What is Happening In this Classroom) instrument was used to assess the types of interactions, from students’ perspectives, that occur in two science classrooms in Trinidad & Tobago. It was the first attempt to use the WIHIC instrument in the research context. An exploratory case study research design in the quantitative paradigm was employed in the assessment. The findings reveal that classroom interactions were dominated by student-centered interactions that mapped onto the student cohesiveness and cooperation scales of the WIHIC instrument. A high level of interaction in the investigation and involvement scales was also determined. What was surprising however, was the low level of teacher supportive interactions and interactions which demonstrated teacher impartiality as reported from students’ perspective.
Sequential UV-C and Thermal Decontamination for Reuse of N95 Face Masks during the COVID19 Pandemic

The COVID-19 global pandemic has led to widespread shortages of personal protective equipment (PPE), particularly N95 masks in healthcare facilities. N95 masks are intended to be single-use items. However, the severe shortage of such masks has necessitated their reuse over extended periods of time. There is an urgent need for methods to decontaminate such masks for reuse while keeping them intact and functional. A review of published literature suggests that N95 masks can be decontaminated by UV-C or by elevated temperature. However, neither method is definitively effective. By evaluating UV-C penetration through a specific model of an N95 mask, we found significant reduction of UV-C dosage in inner layers of the mask. Therefore, it is recommended that UV-C treatment followed by a thermal inactivation step be used for decontamination of N95 masks during a pandemic when adequate supplies of masks are not available.
Adiyaman, Turkey ============================================================================== SOURCES OF MATHEMATICS SELF-EFFICACY OF GIFTED AND NON-GIFTED STUDENTS IN HIGH SCHOOL

Sources of mathematics self-efficacy (SMS), which foster the development of self-efficacy belief, can develop differently in students with different cognitive characteristics. The objective of this study was to compare SMS of gifted and nongifted students after controlling for mathematics achievement. Participants of the study consisted of 106 gifted and 118 non-gifted students in high schools. The study was a causal-comparative design. The data was collected through the Sources of Mathematics Self-Efficacy Scale, and students’ self-reported previous fall mathematical grades. The results of the study revealed that after controlling for mathematics grades, while SMS of gifted children sharply decreased, SMS in the nongifted group slightly increased. In addition, only vicarious experience dimensions of SMS were significantly different between gifted and non-gifted children. In conclusion, being gifted or non-gifted has an impact on the vicarious experience dimensions of SMS after controlling for mathematics achievement. Mathematics grade positively affects SMS in the gifted group and negatively affects the non-gifted group. Teachers are suggested to use achievement as a reinforcer for gifted students but not for non-gifted students.
A Machine Learning Study on the Thermostability Prediction of (R)-ω-Selective Amine Transaminase from Aspergillus terreus

Artificial intelligence technologies such as machine learning have been applied to protein engineering, with unique advantages in protein structure, function prediction, catalytic activity, and other issues in recent years. Screening better mutants is still a bottleneck in protein engineering. In this paper, a new sequence-activity relationship method was analyzed for its application in improving the thermal stability of Aspergillus terreus (R)-ω-selective amine transaminase. The experimental data from 6 single-point mutated enzymes were used as a learning dataset to build models and predict the thermostability of 26 mutants. Based on digital signal processing (DSP), this method digitized the amino acid sequence of proteins by fast Fourier transform (FFT) and then established the best model applying partial least squares regression (PLSR) to screen out all possible mutants, especially those with high performance. In protein engineering, the innovative sequence activity relationship (ISAR) method can make a reasonable prediction using limited experimental data and significantly reduce the experimental cost. The half-life (T1/2) of (R)-ω-transaminase was fitted with the amino acid sequence by the ISAR algorithm, resulting in an R2 of 0.8929 and a cvRMSE of 4.89. At the same time, the mutants with higher T1/2 than the existing ones were predicted, laying the groundwork for better (R)-ω-transaminase in the later stage. The ISAR algorithm is expected to provide a new technique for protein evolution and screening.
Brief Admission for Patients with Self-Harm from the Perspective of Outpatient Healthcare Professionals

Abstract The aim of the study was to describe the role of brief-admission (BA) in treating high-risk patients with self-harm from the perspective of outpatient healthcare staff in Sweden. Ten outpatient healthcare professionals from three psychiatric clinics were interviewed. Data were analyzed using a conventional content analysis. The findings of this study help support the role of BA as an acute crisis management intervention, and describe how BA serves as a useful adjunct to outpatient treatment, especially for patients with complementarily psychotherapeutic interventions. The findings also suggest that implementing BA may increase treatment opportunities for outpatient staff and strengthen the concept of person-centered care.
Transforming growth factor β3 deficiency promotes defective lipid metabolism and fibrosis in murine kidney

ABSTRACT Glomerulosclerosis and tubulointerstitial fibrosis are pathological features of chronic kidney disease. Transforming growth factor β (TGFβ) is a key player in the development of fibrosis. However, of the three known TGFβ isoforms, only TGFβ1 has an established role in fibrosis, and the pathophysiological relevance of TGFβ2 and TGFβ3 is unknown. Because Tgfb3 deficiency in mice results in early postnatal lethality, we analyzed the kidney phenotype of heterozygous Tgfb3-knockout mice (Tgfb3+/−) and compared it with that of matched wild-type mice. Four-month-old Tgfb3+/− mice exhibited incipient renal fibrosis with epithelial–mesenchymal transition, in addition to glomerular basement membrane thickening and podocyte foot process effacement associated with albuminuria. Also evident was insulin resistance and oxidative stress at the renal level, together with aberrant renal lipid metabolism and mitochondrial function. Omics analysis revealed toxic species, such as diacylglycerides and ceramides, and dysregulated mitochondrial metabolism in Tgfb3+/− mice. Kidneys of Tgfb3+/− mice showed morphological alterations of mitochondria and overactivation of non-canonical MAPK ERK1/2 and JNK cascades. Our study indicates that renal TGFβ3 might have antifibrotic and renoprotective properties, opposing or counteracting the activity of TGFβ1. This article has an associated First Person interview with the first author of the paper.
What causes prostate cancer-learning from a tragedy.

The detoxifying gene π -class glutathione S -transferase (GSTP1) is inactivated in the vast majority of clinical prostate tumors (1,2). It is a pathologic and diagnostic marker of prostate cancer. In the absence of the GSTP1 protein, a detoxifying phase 2 enzyme the presence of carcinogens, cancer causing agents, could not be effectively removed, resulting in diminished cytoprotection. It is likely a cause of oxidative damage and inflammation at tumor initiation. However, whether cancer causing agents could ini-tiate prostate cancer and what is the mechanism have largely unresolved. Now investigations of the health effects from the 9/11 World Trade Center (WTC) collapse have reported that prostate cancer in the first responders was the result of exposure to the dust from the building collapse. Corroborating with the GSTP1 inactivation has hence allowed us to postulate an initiating mechanism of the cancer causing agents. multiple inflammation events including immune responses, aberrant gene regulation and gene damage during carcino- genesis.