Kennedyhirsch0898

The presence of the previous history of SARS-CoV-2 infection (

< 0.001), the presence of flu-like symptoms within the last 6 months (

< 0.001), and the presence of positive contact history (

=0.002) were statistically significant with the presence of the antibody among HCWs.

Healthcare workers carry a high burden of SARS-CoV-2 infection and are at risk of acquiring infection from their workplace. Anti-SARS-CoV-2 antibody screening among healthcare workers is highly recommended in multiple healthcare settings as it can help in monitoring transmission dynamics and evaluation of infection control policies.

Healthcare workers carry a high burden of SARS-CoV-2 infection and are at risk of acquiring infection from their workplace. Anti-SARS-CoV-2 antibody screening among healthcare workers is highly recommended in multiple healthcare settings as it can help in monitoring transmission dynamics and evaluation of infection control policies.The drones can be used to detect a group of people who are unmasked and do not maintain social distance. In this paper, a deep learning-enabled drone is designed for mask detection and social distance monitoring. A drone is one of the unmanned systems that can be automated. This system mainly focuses on Industrial Internet of Things (IIoT) monitoring using Raspberry Pi 4. This drone automation system sends alerts to the people via speaker for maintaining the social distance. This system captures images and detects unmasked persons using faster regions with convolutional neural network (faster R-CNN) model. When the system detects unmasked persons, it sends their details to respective authorities and the nearest police station. The built model covers the majority of face detection using different benchmark datasets. OpenCV camera utilizes 24/7 service reports on a daily basis using Raspberry Pi 4 and a faster R-CNN algorithm.Water pollution caused by various natural and artificial sources such as expansion of industrialization, rapid increment in population size, the threat of climate change, and development in urbanization takes a serious attention. Due to this fact, various protocols and techniques were adopted for the treatment of such polluted water. In the present findings, TiO2 nanoparticles (NPs) and TiO2/rGO nanocomposites (NCs) were synthesized using titanium tetra butoxide in the presence of Citrus sinensis (CS) and Musa acuminata (MA) peel waste extract as a capping, reducing, and stabilizing agent. The synthesized NPs and NCs were characterized using thermogravimetric-differential thermal analysis (TGA/DTA), X-ray diffraction (XRD), scanning electron microscope (SEM), high resolution transmission electron microscopy (HR-TEM), selected area electron diffraction (SAED) pattern, ultraviolet diffuse reflectance spectroscopy (UV-DRS), and Fourier transform infrared (FTIR) spectroscopy. The synthesized NPs and NCs were inve confirmed the purity of the corresponding nanocatalysts. In addition, TEM, HRTEM, and SAED analysis confirmed that the structures of the synthesized nanocatalysts were spherical in shape and the catalysts were too crystalline and the result was found to fit with the XRD result. Among the synthesized various volume ratios of TiO2 nanocatalysts, high percentage of degradation (62% and 58.2%) was achieved using TiO2-2c and TiO2-2 m, respectively. Moreover, 94.28% and 94.25% of MB degradation were achieved in the presence of TiO2/rGO-1.5c and TiO2/rGO-1.5c nanocomposite photocatalysts, respectively.Iron oxide and titania-based composite nanoparticles (NPs) populated with core-shell structures, as part of the mixture of the monometallic NPs, were prepared in water medium by the two-fluence LASER ablation technique by applying 30 and 60 mJ/cm2 LASER energy irradiations. The prepared monometallics, composite, and core-shell NPs structures were confirmed from the XRD, TEM, and EDX analyses, followed by the FE-SEM and UV absorptions. Optically, the NPs exhibited an increase in the energy gap from 3.27 eV to 3.75 eV as LASER fluence increased from 30 mJ/cm2 to 60 mJ/cm2. PF-04965842 concentration The average NPs core size distributions for the core-shell material ranged at ∼70 nm with the shell thickness around 20 nm. The biggest NPs were of ∼170 nm size which were sparsely distributed. The magnetization behaviors of the NPs were also investigated using the vibrating sample magnetometer (VSM). The NPs showed antimicrobial activities against the pathogenic species Escherichia coli and Staphylococcus aureus. The antimicrobial activities potential as antimicrobial and also as anti-lung-cancer agents as tested in vitro. These NPs can also be part of combined chemotherapy in different oncological interventions, as well as a sonosensitizer in sonomagnetic heating-based therapy, especially for cancers.[This corrects the article DOI 10.3389/fgene.2021.768041.].Background Recurrence is still a major obstacle to the successful treatment of gliomas. Understanding the underlying mechanisms of recurrence may help for developing new drugs to combat gliomas recurrence. This study provides a strategy to discover new drugs for recurrent gliomas based on drug perturbation induced gene expression changes. Methods The RNA-seq data of 511 low grade gliomas primary tumor samples (LGG-P), 18 low grade gliomas recurrent tumor samples (LGG-R), 155 glioblastoma multiforme primary tumor samples (GBM-P), and 13 glioblastoma multiforme recurrent tumor samples (GBM-R) were downloaded from TCGA database. DESeq2, key driver analysis and weighted gene correlation network analysis (WGCNA) were conducted to identify differentially expressed genes (DEGs), key driver genes and coexpression networks between LGG-P vs LGG-R, GBM-P vs GBM-R pairs. Then, the CREEDS database was used to find potential drugs that could reverse the DEGs and key drivers. Results We identified 75 upregulated and 130 downregulated genes between LGG-P and LGG-R samples, which were mainly enriched in human papillomavirus (HPV) infection, PI3K-Akt signaling pathway, Wnt signaling pathway, and ECM-receptor interaction. A total of 262 key driver genes were obtained with frizzled class receptor 8 (FZD8), guanine nucleotide-binding protein subunit gamma-12 (GNG12), and G protein subunit β2 (GNB2) as the top hub genes. By screening the CREEDS database, we got 4 drugs (Paclitaxel, 6-benzyladenine, Erlotinib, Cidofovir) that could downregulate the expression of up-regulated genes and 5 drugs (Fenofibrate, Oxaliplatin, Bilirubin, Nutlins, Valproic acid) that could upregulate the expression of down-regulated genes. These drugs may have a potential in combating recurrence of gliomas. Conclusion We proposed a time-saving strategy based on drug perturbation induced gene expression changes to find new drugs that may have a potential to treat recurrent gliomas.Circular RNAs (circRNAs) are non-coding RNAs with covalent closed-loop structures and are widely distributed in eukaryotes, conserved and stable as well as tissue-specific. Malignant solid tumors pose a serious health risk to children and are one of the leading causes of pediatric mortality. Studies have shown that circRNAs play an important regulatory role in the development of childhood malignant solid tumors, hence are potential biomarkers and therapeutic targets for tumors. This paper reviews the biological characteristics and functions of circRNAs as well as the research progress related to childhood malignant solid tumors.Background Balanced chromosomal aberrations, especially balanced translocations, can cause infertility, recurrent miscarriage or having chromosomally defective offspring. Preimplantation genetic testing for structural rearrangement (PGT-SR) has been widely implemented to improve the clinical outcomes by selecting euploid embryos for transfer, whereas embryos with balanced translocation karyotype were difficult to be distinguished by routine genetic techniques from those with a normal karyotype. Method In this present study, we developed a clinically applicable method for reciprocal translocation carriers to reduce the risk of pregnancy loss. In the preclinical phase, we identified reciprocal translocation breakpoints in blood of translocation carriers by long-read Oxford Nanopore sequencing, followed by junction-spanning polymerase chain reaction (PCR) and Sanger sequencing. In the clinical phase of embryo diagnosis, aneuploidies and unbalanced translocations were screened by comprehensive chromosomal screenich were totally consistent with the fetal karyotypes. Conclusions In summary, these investigations in our study illustrated that chromosomal reciprocal translocations in embryos can be accurately diagnosed. Long-read Nanopore sequencing and breakpoint analysis contributes to precisely evaluate the genetic risk of disrupted genes, and provides a way of selecting embryos with normal karyotype, especially for couples those without a reference.In-silico classification of the pathogenic status of somatic variants is shown to be promising in promoting the clinical utilization of genetic tests. Majority of the available classification tools are designed based on the characteristics of germline variants or the combination of germline and somatic variants. Significance of somatic variants in cancer initiation and progression urges for development of classifiers specialized for classifying pathogenic status of cancer somatic variants based on the model trained on cancer somatic variants. We established a gold standard exclusively for cancer somatic single nucleotide variants (SNVs) collected from the catalogue of somatic mutations in cancer. We developed two support vector machine (SVM) classifiers based on genomic features of cancer somatic SNVs located in coding and non-coding regions of the genome, respectively. The SVM classifiers achieved the area under the ROC curve of 0.94 and 0.89 regarding the classification of the pathogenic status of coding and non-coding cancer somatic SNVs, respectively. Our models outperform two well-known classification tools including FATHMM-FX and CScape in classifying both coding and non-coding cancer somatic variants. Furthermore, we applied our models to predict the pathogenic status of somatic variants identified in young breast cancer patients from METABRIC and TCGA-BRCA studies. The results indicated that using the classification threshold of 0.8 our "coding" model predicted 1853 positive SNVs (out of 6,910) from the TCGA-BRCA dataset, and 500 positive SNVs (out of 1882) from the METABRIC dataset. Interestingly, through comparative survival analysis of the positive predictions from our models, we identified a young-specific pathogenic somatic variant with potential for the prognosis of early onset of breast cancer in young women.Lynch syndrome (LS) is a cancer-predisposing genetic disease mediated by pathogenic mutations in DNA mismatch repair (MMR) genes MLH1, MSH2, MSH6, and PMS2. Accumulating evidence demonstrates that there is significant biological heterogeneity across MMR genes. Compared to MLH1 and MSH2, PMS2 variant carriers have a much lower risk for LS-related cancers. Tumors in MLH1 and MSH2 variant carriers often display MMR deficiency (dMMR) and/or high microsatellite instability (MSI-H), two predictive biomarkers for immunotherapy efficacy. However, tumors in PMS2 variant carriers are largely microsatellite stable (MSS) instead of MSI. Therefore, the optimal management of cancer patients with LS requires the integration of disease stage, MMR gene penetrance, dMMR/MSI status, and tumor mutational burden (TMB). In this work, we presented a locally advanced lung cancer patient with dMMR/MSI-H/TMB-H tumor and selective loss of PMS2 by immunohistochemistry. Germline testing revealed a rare PMS2 splicing variant (c.1144+1G>A) in the proband and his healthy daughter.