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Base excision repair, which is initiated by the DNA N -glycosylase proteins, is the frontline for repairing potentially mutagenic DNA base damage. Several base excision repair genes are deregulated in cancer and affect cellular outcomes to chemotherapy and carcinogenesis. Endonuclease VIII-like 3 (NEIL3) is a DNA glycosylase protein that is involved in oxidative and interstrand crosslink DNA damage repair. Our previous work has showed that NEIL3 is required to maintain replication fork integrity. It is unknown whether NEIL3 overexpression could contribute to cancer phenotypes, and its prognostic value and use as potential drug target remain unexplored. Our analysis of cancer genomics data sets reveals that NEIL3 frequently undergoes overexpression in several cancers. Furthermore, patients who exhibited NEIL3 overexpression with pancreatic adenocarcinoma, lung adenocarcinoma, lower grade glioma, kidney renal clear cell carcinoma, and kidney papillary cell carcinoma had worse overall survival. Importantly, NEIL3 overexpressed tumors accumulate mutation and chromosomal variations. Furthermore, NEIL3 overexpressed tumors exhibit simultaneous overexpression of homologous recombination genes (BRCA1/2) and mismatch repair genes ( MSH2/MSH6 ). However, NEIL3 overexpression is negatively correlated with tumor overexpressing nucleotide excision repair genes ( XPA, XPC, ERCC1 / 2 ). Our results suggest that NEIL3 might be a potential prognosis marker for high-risk patients, and/or an attractive therapeutic target for selected cancers.

Category: Ankle, Hindfoot, Imaging- Ultrasound Introduction/Purpose: Tendinopathy of the foot and ankle is common and can progress to become incapacitating. The most frequently affected tendons in the foot and ankle are the posterior tibial, peroneal, and Achilles. Studies have found a lifetime incidence of 5.9% in sedentary people and as high as 52% in athletes for Achilles tendinopathy. Previous studies demonstrated that ultrasound (US) of the soft tissues of the foot and ankle is a highly effective tool that can evaluate nearly every anatomical structure. Its lack of ionizing radiation, low cost, and painless nature make it a viable tool for foot and ankle evaluation. We sought to utilize US to determine normal values for the Achilles, peroneal, and posterior tibial tendons in patients presenting to the foot and ankle clinic. Methods: Patients were evaluated prospectively via a standardized US examination protocol from 2015-2016. Subjects who agreed to participate received a bilateral lower extremity ultrasound performed by a musculoskeletal ultrasonographer of the posterior tibial, peroneus longus, peroneus brevis, and Achilles tendons. Images were obtained in both the transverse and longitudinal axes above and below the malleoli and saved for analysis and measurement calculations. When indicated, color flow Doppler was utilized to assess for hyperemia and recorded. The imaging for each tendon was acquired with the patients in standardized positions on the examining table. Results: A total of 200 patients with 400 extremities were identified, consented, and participated in the study. Measurements for each patient were recorded above and below the malleoli for each tendon. Most tendons demonstrated a normal distribution as illustrated in the representative Figure 1 of the peroneus brevis above the lateral malleolus. Values and distributions curves were similarly calculated for each tendon at each point of measurement. Patients with suspected tendinopathy frequently had an increase of two standard deviations above the mean. Conclusion: This is the largest studies to characterize the measurements of the posterior tibial tendon, Achilles, and peroneal tendons in patients that present to a foot and ankle clinic. This baseline data can assist clinicians in their diagnostic ability with US. Given its low cost, lack of ionizing radiation and dynamic ability along with an improved understanding of normative data it will likely become an increasingly utilized diagnostic modality.

EoE in children presents with four main symptoms. Most common symptoms exhibited by our clinic population are dysphagia (D) and abdominal pain (AP). Despite similar treatments, we found in an earlier study that the outcomes between these two groups were different. Therefore, we investigated if there exist any histological differences between these groups that could further our knowledge of EoE. Aim. To compare esophageal histology in detail, apart from the eosinophil count, between EoE-D and EoE-AP. Method. Biopsies of patients with EoE-D and EoE-AP were reevaluated for 10 additional histological criteria, in addition to the eosinophil count. Results. Both groups had 67 patients; peak mean eosinophil was 33.9 and 31.55 for EoE-D and EoE-AP (p

Abstract Advancements in genomic and proteomic technologies have powered the creation of large gene and protein networks (“interactomes”) for understanding biological systems. However, the proliferation of interactomes complicates the selection of networks for specific applications. Here, we present a comprehensive evaluation of 45 current human interactomes, encompassing protein-protein interactions as well as gene regulatory, signaling, colocalization, and genetic interaction networks. Our analysis shows that large composite networks such as HumanNet, STRING, and FunCoup are most effective for identifying disease genes, while smaller networks such as DIP, Reactome, and SIGNOR demonstrate stronger performance in interaction prediction. Our study provides a benchmark for interactomes across diverse biological applications and clarifies factors that influence network performance. Furthermore, our evaluation pipeline paves the way for continued assessment of emerging and updated interaction networks in the future.

Abstract Multifunctional composites have been continuously developed for a myriad of applications with remarkable adaptability to external stimuli and dynamic responsiveness. This study introduces a 4D printing method for liquid crystal elastomer (LCE) composites with continuous fibers and unveils their multifunctional actuation and exciting mechanical responses. During the printing process, the relative motion between the continuous fiber and LCE resin generates shear force to align mesogens and enable the monodomain state of the matrix materials. The printed composite lamina exhibits reversible folding deformations that are programmable by controlling printing parameters. With the incorporation of fiber reinforcement, the LCE composites not only demonstrate high actuation forces but also improved energy absorption and protection capabilities. Diverse shape-changing configurations of 4D composite structures can be achieved by tuning the printing pathway. Moreover, the incorporation of conductive fibers into the LCE matrix enables electrically induced shape morphing in the printed composites. Overall, this cost-effective 4D printing method is poised to serve as an accessible and influential approach when designing diverse applications of LCE composites, particularly in the realms of soft robotics, wearable electronics, artificial muscles, and beyond.

The use of natural fibers instead of synthetic fibers has become a hot topic in the reinforced composite manufacturing industry. However, there are considerable differences in the mechanical properties of natural fibers cited in the literature. These differences could be due to the prevalent use of monothetic analysis. In this paper, the use of a simplified Taguchi technique in novel Dioscorea alata stems fiber processing is proposed to allow for simultaneous evaluation of control parameters such as treatment type, harvest condition, gauge length and chemical treatment temperature to determine the optimal conditions for fiber tensile properties. These fibers were extracted from the stem by means of water retting method before chemical treatment. The tensile properties were determined as per ASTM D3822/D3822M-14. Non-destructive examinations were employed to look into the chemical make-up, thermal, crystalline and morphological characteristics of the fibers. The test results showed an optimum tensile strength of 151 MPa and tensile modulus of 5709.5 MPa. Density was 0.4 g/cm3 while cellulose, lignin, moisture, hemicellulose and ash contents were 13.1 %, 10.3 %, 9.7 %, 5.0 % and 8.2 % respectively. The treated fibers were thermally stable till 320 °C. The properties of Dioscorea alata stem fiber (DASF) were found to be promising when compared to existing natural fibers, making it a viable candidate for composite material reinforcement.

In the past 25 years, the world has witnessed outbreaks of illnesses in humans from three different coronaviruses. Both the SARS-CoV outbreak of 2003 and the MERS-CoV outbreak of 2013 resulted in overall low fatalities in part due to inefficient human-to-human spread of each virus. In contrast, SARS-CoV-2, which emerged in 2019, was highly efficient at human-to-human spread and caused a global pandemic resulting in millions of casualties. Zoonotic transmission of viruses, including the three coronaviruses, poses an ongoing threat that cannot be ignored. In this review, we have focused on the diagnostics and therapeutics fronts using SARS-CoV-2 as a model. Specifically, we have selected proteins associated with the virus particles as targets and discussed various platform technologies. These insights hold the potential to inform the development of more effective therapeutics and vaccines not only for SARS-CoV-2 but also for future viral pandemics, thus contributing to global health on a broader scale.

Summary: Background: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. Methods: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). Findings: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. Interpretation: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. Funding: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.

Large amount of wood dust is created as a byproduct of woodworking activities. Every year, there is an increase in wood dust generation, which severely pollutes the environment. Consequently, it becomes imperative to use wood dust in the production of useful products. A Carbonized Wood-Silicon Dioxide Filled Natural Rubber Composite (CWSDFNRC) was therefore created in this work using a compression molding method. The friction and compression properties of the composites were determined. Modeling of the composite's mechanical and friction characteristics was done using artificially intelligent techniques including Response Surface Methodology (RSM), Artificial Neural Network (ANN), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The novel material was thermally analyzed using Dynamic Mechanical Analysis (DMA), Differential Scanning Calorimetry (DSC), Thermogravimetric Analysis (TGA), and Differential Thermal Analysis (DTA). The effectiveness of RSM, ANN, and ANFIS was demonstrated by relevant error indices. The optimization method revealed the ideal level of fitness at particle size, carbonization temperature, filler content, curing temperature, curing pressure, and curing time of 150 μm, 214 °C, 51 phr, 150 °C, 3 Pa, and 10 min respectively. These fitness conditions gave an optimal value of 17.63 MPa for compressive strength and a friction coefficient of 0.96. The novel material's characteristics contrasted well with those of comparable materials described in the literature, suggesting that it has the potential to be used in the manufacture of outer shoe soles and other elastomeric applications.

Objective: The effects of Coronavirus disease 2019 (COVID-19) infection and altered processes of care on nonelective coronary artery bypass grafting (CABG) outcomes remain unknown. We hypothesized that patients with COVID-19 infection would have longer hospital lengths of stay and greater mortality compared with COVID-negative patients, but that these outcomes would not differ between COVID-negative and pre-COVID controls. Methods: The National COVID Cohort Collaborative 2020-2022 was queried for adult patients undergoing CABG. Patients were divided into COVID-negative, COVID-active, and COVID-convalescent groups. Pre-COVID control patients were drawn from the National Surgical Quality Improvement Program database. Adjusted analysis of the 3 COVID groups was performed via generalized linear models. Results: A total of 17,293 patients underwent nonelective CABG, including 16,252 COVID-negative, 127 COVID-active, 367 COVID-convalescent, and 2254 pre-COVID patients. Compared to pre-COVID patients, COVID-negative patients had no difference in mortality, whereas COVID-active patients experienced increased mortality. Mortality and pneumonia were higher in COVID-active patients compared to COVID-negative and COVID-convalescent patients. Adjusted analysis demonstrated that COVID-active patients had higher in-hospital mortality, 30- and 90-day mortality, and pneumonia compared to COVID-negative patients. COVID-convalescent patients had a shorter length of stay but a higher rate of renal impairment. Conclusions: Traditional care processes were altered during the COVID-19 pandemic. Our data show that nonelective CABG in patients with active COVID-19 is associated with significantly increased rates of mortality and pneumonia. The equivalent mortality in COVID-negative and pre-COVID patients suggests that pandemic-associated changes in processes of care did not impact CABG outcomes. Additional research into optimal timing of CABG after COVID infection is warranted.

One main objective of higher education is to provide quality education to its students. One way to achieve the highest level of quality in the higher education system is by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students, and prediction about students’ performance. The knowledge is hidden among the educational data set and is extractable through data mining techniques. The present paper is designed to justify the capabilities of data mining techniques in the context of higher education by offering a data mining model for the higher education system in the university. In this research, the classification task is used to evaluate student’s performance, and as many approaches are used for data classification, the decision tree method is used here. By this, we extract data that describes students’ summative performance at semester’s end, helps to identify the dropouts and students who need special attention, and allows the teacher to provide appropriate advising/counseling.

Objectives To evaluate the effectiveness of COVID-19 vaccinations (initial and booster) during pre-Delta, Delta and Omicron dominant periods among pregnant people via (1) COVID-19 incident and severe infections among pregnant people who were vaccinated versus unvaccinated and (2) post-COVID-19 vaccination breakthrough infections and severe infections among vaccinated females who were pregnant versus non-pregnant.Design Retrospective cohort study using nationally sampled electronic health records data from the National COVID Cohort Collaborative, 10 December 2020 –7 June 2022.Participants Cohort 1 included pregnant people (15–55 years) and cohort 2 included vaccinated females of reproductive age (15–55 years).Exposures (1) COVID-19 vaccination and (2) pregnancy.Main outcome measures Adjusted HRs (aHRs) for COVID-19 incident or breakthrough infections and severe infections (ie, COVID-19 infections with related hospitalisations).Results In cohort 1, 301 107 pregnant people were included. Compared with unvaccinated pregnant people, the aHRs for pregnant people with initial vaccinations during pregnancy of incident COVID-19 were 0.77 (95% CI 0.62 to 0.96) and 0.88 (95% CI 0.73 to 1.07) and aHRs of severe COVID-19 infections were 0.65 (95% CI 0.47 to 0.90) and 0.79 (95% CI 0.51 to 1.21) during the Delta and Omicron periods, respectively. Compared with pregnant people with full initial vaccinations, the aHR of incident COVID-19 for pregnant people with booster vaccinations was 0.64 (95% CI 0.58 to 0.71) during the Omicron period. In cohort 2, 934 337 vaccinated people were included. Compared with vaccinated non-pregnant females, the aHRs of severe COVID-19 infections for people with initial vaccinations during pregnancy was 2.71 (95% CI 1.31 to 5.60) during the Omicron periods.Conclusions Pregnant people with initial and booster vaccinations during pregnancy had a lower risk of incident and severe COVID-19 infections compared with unvaccinated pregnant people across the pandemic stages. However, vaccinated pregnant people still had a higher risk of severe infections compared with non-pregnant females.

Solventogenic Clostridium species are important for establishing the sustainable industrial bioproduction of fuels and important chemicals such as acetone and butanol. The inherent versatility of these species in substrate utilization and the range of solvents produced during acetone butanol–ethanol (ABE) fermentation make solventogenic Clostridium an attractive choice for biotechnological applications such as the production of fuels and chemicals. The functional qualities of these microbes have thus been identified to be related to complex regulatory networks that play essential roles in modulating the metabolism of this group of bacteria. Yet, solventogenic Clostridium species still struggle to consistently achieve butanol concentrations exceeding 20 g/L in batch fermentation, primarily due to the toxic effects of butanol on the culture. Genomes of solventogenic Clostridium species have a relatively greater prevalence of genes that are intricately controlled by various regulatory molecules than most other species. Consequently, the use of genetic or metabolic engineering strategies that do not consider the underlying regulatory mechanisms will not be effective. Several regulatory factors involved in substrate uptake/utilization, sporulation, solvent production, and stress responses (Carbon Catabolite Protein A, Spo0A, AbrB, Rex, CsrA) have been identified and characterized. In this review, the focus is on newly identified regulatory factors in solventogenic Clostridium species, the interaction of these factors with previously identified molecules, and potential implications for substrate utilization, solvent production, and resistance/tolerance to lignocellulose-derived microbial inhibitory compounds. Taken together, this review is anticipated to highlight the challenges impeding the re-industrialization of ABE fermentation, and inspire researchers to generate innovative strategies for overcoming these obstacles.

The growth in applications of Plantain Fibre Reinforced HDPE (PFRHDPE) has increased the importance of understanding the time-dependent viscoelastic properties such as creep resistance. This study focused on the determination of creep behaviour of a novel PFRHDPE designed for elevated temperatures applications. The creep responses of PFRHDPE were experimentally determined in line with ASTM D2290 and modelled for elevated temperature applications using the classical creep models, classical viscoelastic models and the time temperature superposition approach. Creep strain, creep stress, creep modulus and creep stress relaxation were modelled and analyzed. The PFRHDPE exhibited the characteristic of the unrelaxed and relaxed moduli of material to accommodate applications at elevated temperatures. The superposition method showed PFRHDPE to have moduli of 66 MPa and 2.26 MPa for one year and fifty years of operations respectively. The relaxation stresses were also evaluated as 9.24 MPa, 9.15 MPa and 12.96 MPa for the conditions investigated showing the new material as able to accommodate the constant loads of 25 MPa and 35 MPa under the elevated temperatures of 30 °C and 60 °C.