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Polymer precursors for Si(N)OC ceramics have been synthesized by hydrosilylation reaction of polyhydridomethylsiloxane (PHMS) with three different nitrogen containing compounds. The results obtained by combining characterization techniques such as FTIR, 13 C-and 29 Si-NMR confirm the occurrence of the cross-linking reaction between Si-H and vinyl groups. The structural characterization of the corresponding ceramic phase shows that the type of N-containing compounds strongly influences the pyrolytic transformation as well as the crystallization behavior of the final ceramics. Elemental analysis clearly indicates that N is present in the Si(N)OC matrix and the degree of N retention after pyrolysis is related to the type of N-containing starting compound. XPS data show that N-C bonds are present in the Si(N)OC ceramic samples even if only N-Si bonds are present in the starting N-containing precursors. However, if nitrogen atoms form bonds with sp 2 carbon atoms in the preceramic polymer then a larger fraction of C-N bonds is retained in the final Si(N)OC ceramic.

SiOCN ceramics have been prepared by the polymer pyrolysis method. The preceramic polymers were synthesized from a polysiloxane cross‐linked with two different N‐containing compounds: a silazane or a ternary amine. The corresponding SiOCN ceramics were obtained by pyrolysis in nitrogen atmosphere at five different temperatures from 1000°C to 1400°C. The electrical conductivity of the powdered SiOCN ceramic samples was determined by the powder‐solution‐composite technique. The results show an increase in room temperature AC conductivity of three orders of magnitude, from ≈10−5 (S/cm) to ≈10−2 (S/cm), with increasing pyrolysis temperature from 1000°C to 1400°C. Furthermore, the electrical conductivity of the amine‐derived SiOCN is three to five times higher than that of the silazane‐derived ceramic at each pyrolysis temperature. The combined structural study by Raman spectroscopy and chemical analysis suggests that the increase of electrical conductivity with the pyrolysis temperature is due to the sp3‐to‐sp2 transition of the amorphous carbon phase. The higher conductivity of the amine‐derived SiOCN is also discussed considering features like the volume% of the free‐carbon phase and its possible N‐doping.

The scarcity of enzymes having an optimal activity in lignocellulose deconstruction is an obstacle for industrial-scale conversion of cellulosic biomass into biofuels. With the aim of mining novel lignocellulolytic enzymes, a ~9 Gb metagenome of bacteria in Vietnamese native goats' rumen was sequenced by Illumina platform. From the data, 821 ORFs encoding carbohydrate esterases (CEs) and polysaccharide lyases (PLs) serving for lignocellulose pre-treatment, 816 ORFs encoding 11 glycoside hydrolase families (GHs) of cellulases, and 2252 ORFs encoding 22 GHs of hemicellulases, were mined. The carbohydrate binding module (CBM) was also abundant with 763 ORFs, of which 480 ORFs are located with lignocellulolytic enzymes. The enzyme modularity analysis showed that CBMs are usually present in endoglucanase, endo 1,3-beta-D-glucosidase, and endoxylanase, whereas fibronectin 3-like module (FN3) mainly represents in GH3 and immunoglobulin-like domain (Ig) was located in GH9 only. Every domain located in each ORF was analyzed in detail to contribute enzymes' modularity which is valuable for modelling, to study the structure, and for recombinant production. With the aim of confirming the annotated results, a mined ORF encoding CBM63 was highly expressed in E. coli in soluble form. The purified recombinant CBM63 exhibited no cellulase activity, but enhanced a commercial cellulase activity in the destruction of a paper filter.

A borosilicate sol-gel solution is synthesized using a mixture of methyltriethoxysilane, dimethyldiethoxysilane, and boric acid. SiBOC gel fibers are produced from the as-synthesized sol-gel solution using a spinning apparatus. Subsequently, SiBOC glass fibers are prepared through pyrolysis under argon atmosphere at 1000°C and 1200°C. Mechanical properties of the SiBOC glass fibers are studied by measuring the tensile strength and the elastic modulus. The results show a high tensile strength -1300 and 1058 MPa, and a high Young modulus -79 and 95.5 GPa, for the fibers prepared at 1000°C and 1200°C, respectively. Furthermore, alkali resistance of the SiB-OC fibers is investigated by measuring the tensile strength after soaking them for 20 h in NaOH and Ca(OH) 2 solutions at 100°C. For comparison, the same measurements are performed on commercial AR and E glass fibers. The SiBOC fibers show excellent alkaline resistance and perform better than commercial AR fibers. Indeed, SiBOC fibers retain 80%-90% of the initial strength after Ca(OH) 2 attack.

Background Personalized warfarin dosing is influenced by various factors including genetic and non‐genetic factors. Multiple linear regression (LR) is known as a conventional method to develop predictive models. Recently, machine learning approaches have been extensively implemented for warfarin dosing due to the hypothesis of non‐linear association between covariates and stable warfarin dose. Objective To extend the multiple linear regression algorithm for personalized warfarin dosing in a Korean population and compare with a machine learning‐‐based algorithm. Method From this cohort study, we collected information on 650 patients taking warfarin who achieved steady state including demographic information, indications, comorbidities, comedications, habits, and genetic factors. The dataset was randomly split into training set (90%) and test set (10%). The LR and machine learning (gradient boosting machine [GBM]) models were developed on the training set and were evaluated on the test set. Result LR and GBM models were comparable in terms of accuracy of ideal dose (75.38% and 73.85%), correlation (0.77 and 0.73), mean absolute error (0.58 mg/day and 0.64 mg/day), and root mean square error (0.82 mg/day and 0.9 mg/day), respectively. VKORC1 genotype, CYP2C9 genotype, age, and weight were the highest contributors and could obtain 80% of maximum performance in both models. Conclusion This study shows that our LR and GMB models are satisfactory to predict warfarin dose in our dataset. Both models showed similar performance and feature contribution characteristics. LR may be the appropriate model due to its simplicity and interpretability.

Introduction Interruptions in treatment pose risks for people with HIV (PWH) and threaten progress in ending the HIV epidemic; however, the COVID‐19 pandemic's impact on HIV service delivery across diverse settings is not broadly documented. Methods From September 2020 to March 2021, the International epidemiology Databases to Evaluate AIDS (IeDEA) research consortium surveyed 238 HIV care sites across seven geographic regions to document constraints in HIV service delivery during the first year of the pandemic and strategies for ensuring care continuity for PWH. Descriptive statistics were stratified by national HIV prevalence (<1%, 1–4.9% and ≥5%) and country income levels. Results Questions about pandemic‐related consequences for HIV care were completed by 225 (95%) sites in 42 countries with low ( n = 82), medium ( n = 86) and high ( n = 57) HIV prevalence, including low‐ ( n = 57), lower‐middle ( n = 79), upper‐middle ( n = 39) and high‐ ( n = 50) income countries. Most sites reported being subject to pandemic‐related restrictions on travel, service provision or other operations (75%), and experiencing negative impacts (76%) on clinic operations, including decreased hours/days, reduced provider availability, clinic reconfiguration for COVID‐19 services, record‐keeping interruptions and suspension of partner support. Almost all sites in low‐prevalence and high‐income countries reported increased use of telemedicine (85% and 100%, respectively), compared with less than half of sites in high‐prevalence and lower‐income settings. Few sites in high‐prevalence settings (2%) reported suspending antiretroviral therapy (ART) clinic services, and many reported adopting mitigation strategies to support adherence, including multi‐month dispensing of ART (95%) and designating community ART pick‐up points (44%). While few sites (5%) reported stockouts of first‐line ART regimens, 10–11% reported stockouts of second‐ and third‐line regimens, respectively, primarily in high‐prevalence and lower‐income settings. Interruptions in HIV viral load (VL) testing included suspension of testing (22%), longer turnaround times (41%) and supply/reagent stockouts (22%), but did not differ across settings. Conclusions While many sites in high HIV prevalence settings and lower‐income countries reported introducing or expanding measures to support treatment adherence and continuity of care, the COVID‐19 pandemic resulted in disruptions to VL testing and ART supply chains that may negatively affect the quality of HIV care in these settings.