Temperature rise in shear bands in a simulated metallic glass

Temperature rise ($\Delta T$) associated with shear-banding of metallic glasses is of great importance for their performance. However, experimental measurement of $\Delta T$ is difficult due to temporal and spatial localization of shear bands and, as a result, our understanding of the mechanism of $\Delta T$ is limited. Here, based on molecular dynamics simulations we observe a spectrum of $\Delta T$, which depends on both sample size and strain rate, in the shear bands of CuZr metallic glass under tension. More importantly, we find that the maximum sliding velocity of the shear bands correlates linearly with the corresponding $\Delta T$, ranging from $\sim$25 K up to near the melting point for the samples studied. Taking heat diffusion into account, we expect $\Delta T$ to be lower than 25 K for the lower end of sliding velocity. At high temperature, shear band bifurcation and/or multiplication can occur as a negative feedback mechanism that prevents temperature rising well above the melting point

Experimental and analytic study of a hybrid solar/biomass rural heating system

© 2019 Elsevier Ltd This paper presents a dedicated analytic and experimental study of a hybrid solar/biomass space heating system incorporating a micro-channel solar thermal panels-array, a biomass boiler and a dedicated control algorithm. This system enables the smart and joint use of solar and biomass energies to provide a comfortable indoor environment. The in-situ testing of the system was undertaken and the data obtained from the testing were analysed using Grubbs method to formulate the experimental thermal efficiency equation for the solar panels-array and the heat conversion factor equation for the combined heat storage/exchanging water tank. The annual energy performance of the hybrid system was investigated using a professional building energy simulation program (EnergyPlus), which can predict the heat load profile of house, the ratio of energy usage from solar/biomass sources and the primary energy/exergy efficiencies. The thermal efficiency of the solar thermal panels-array is in the range of 60%–70%. The heat storage water tank has a heat conversion factor in the range of 0.94–0.98. The heat load index per unit area is 46.86 W/m2 and cumulative heating energy consumption with 100 m2 house is 24.3 GJ during a heating season. The total annual energy demand of the solar/biomass heating system is around 35.91 GJ, of which the sun provides 63.31% and biomass provides 36.69%. The primary energy and exergy efficiencies of the solar/biomass rural heating system are 67.66% and 16.17% respectively. However, when the total input electrical exergy is traced back to its primary energy source, i.e. a coal-fired power plant, the exergy efficiency falls from 23.14% to 7.27%. Compared to the traditional primary energy supply system, the energy conversion effect and effective utilization degree of the solar/biomass heating system are relatively higher

Effectiveness and safety of anti-BCMA chimeric antigen receptor T-cell treatment in relapsed/refractory multiple myeloma: a comprehensive review and meta-analysis of prospective clinical trials

Background: Chimeric antigen receptor T cells treatment targeting B cell maturation antigen (BCMA) is an emerging treatment option for relapsed/refractory multiple myeloma (RRMM) and has demonstrated outstanding outcomes in clinical studies.Objective: The aim of this comprehensive review and meta-analysis was to summarize the effectiveness and safety of anti-BCMA CAR-T treatment for patients with relapsed/refractory multiple myeloma (RRMM). Our research identifies variables influencing outcome measures to provide additional evidence for CAR-T product updates, clinical trial design, and clinical treatment guidance.Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standard was followed for conducting this comprehensive review and meta-analysis, which was submitted to PROSPERO (CRD42023390037). From the inception of the study until 10 September 2022, PubMed, Web of Science, EMBASE, the Cochrane Library, CNKI, and WanFang databases were searched for eligible studies. Stata software (version 16.0) was used to assess effectiveness and safety outcomes.Results: Out of 875 papers, we found 21 relevant trials with 761 patients diagnosed as RRMM and were given anti-BCMA CAR-T treatment. The overall response rate (ORR) for the entire sample was 87% (95% CI: 80–93%) complete response rate (CRR) was 44% (95% CI: 34–54%). The minimal residual disease (MRD) negativity rate within responders was 78% (95% CI: 65–89%). The combined incidence of cytokine release syndrome was 82% (95% CI: 72–91%) and neurotoxicity was 10% (95% CI: 5%–17%). The median progression-free survival (PFS) was 8.77 months (95% CI: 7.48–10.06), the median overall survival (OS) was 18.87 months (95% CI: 17.20–20.54) and the median duration of response (DOR) was 10.32 months (95% CI: 9.34–11.31).Conclusion: According to this meta-analysis, RRMM patients who received anti-BCMA CAR-T treatment have demonstrated both effectiveness and safety. Subgroup analysis confirmed the anticipated inter-study heterogeneity and pinpointed potential factors contributing to safety and efficacy, which may help with the development of CAR-T cell studies and lead to optimized BCMA CAR-T-cell products.Systematic Review Registration:Clinicaltrials.gov, PROSPERO, CRD42023390037

Nomograms predict prognosis and hospitalization time using non-contrast CT and CT perfusion in patients with ischemic stroke

BackgroundStroke is a major disease with high morbidity and mortality worldwide. Currently, there is no quantitative method to evaluate the short-term prognosis and length of hospitalization of patients.PurposeWe aimed to develop nomograms as prognosis predictors based on imaging characteristics from non-contrast computed tomography (NCCT) and CT perfusion (CTP) and clinical characteristics for predicting activity of daily living (ADL) and hospitalization time of patients with ischemic stroke.Materials and methodsA total of 476 patients were enrolled in the study and divided into the training set (n = 381) and testing set (n = 95). Each of them owned NCCT and CTP images. We propose to extract imaging features representing as the Alberta stroke program early CT score (ASPECTS) values from NCCT, ischemic lesion volumes from CBF, and TMAX maps from CTP. Based on imaging features and clinical characteristics, we addressed two main issues: (1) predicting prognosis according to the Barthel index (BI)–binary logistic regression analysis was employed for feature selection, and the resulting nomogram was assessed in terms of discrimination capability, calibration, and clinical utility and (2) predicting the hospitalization time of patients–the Cox proportional hazard model was used for this purpose. After feature selection, another specific nomogram was established with calibration curves and time-dependent ROC curves for evaluation.ResultsIn the task of predicting binary prognosis outcome, a nomogram was constructed with the area under the curve (AUC) value of 0.883 (95% CI: 0.781–0.985), the accuracy of 0.853, and F1-scores of 0.909 in the testing set. We further tried to predict discharge BI into four classes. Similar performance was achieved as an AUC of 0.890 in the testing set. In the task of predicting hospitalization time, the Cox proportional hazard model was used. The concordance index of the model was 0.700 (SE = 0.019), and AUCs for predicting discharge at a specific week were higher than 0.80, which demonstrated the superior performance of the model.ConclusionThe novel non-invasive NCCT- and CTP-based nomograms could predict short-term ADL and hospitalization time of patients with ischemic stroke, thus allowing a personalized clinical outcome prediction and showing great potential in improving clinical efficiency.SummaryCombining NCCT- and CTP-based nomograms could accurately predict short-term outcomes of patients with ischemic stroke, including whose discharge BI and the length of hospital stay.Key ResultsUsing a large dataset of 1,310 patients, we show a novel nomogram with a good performance in predicting discharge BI class of patients (AUCs > 0.850). The second nomogram owns an excellent ability to predict the length of hospital stay (AUCs > 0.800)

Revealing the biological mechanism of acupuncture in alleviating excessive inflammatory responses and organ damage in sepsis: a systematic review

Sepsis is a systemic inflammation caused by a maladjusted host response to infection. In severe cases, it can cause multiple organ dysfunction syndrome (MODS) and even endanger life. Acupuncture is widely accepted and applied in the treatment of sepsis, and breakthroughs have been made regarding its mechanism of action in recent years. In this review, we systematically discuss the current clinical applications of acupuncture in the treatment of sepsis and focus on the mechanisms of acupuncture in animal models of systemic inflammation. In clinical research, acupuncture can not only effectively inhibit excessive inflammatory reactions but also improve the immunosuppressive state of patients with sepsis, thus maintaining immune homeostasis. Mechanistically, a change in the acupoint microenvironment is the initial response link for acupuncture to take effect, whereas PROKR2 neurons, high-threshold thin nerve fibres, cannabinoid CB2 receptor (CB2R) activation, and Ca2+ influx are the key material bases. The cholinergic anti-inflammatory pathway of the vagus nervous system, the adrenal dopamine anti-inflammatory pathway, and the sympathetic nervous system are key to the transmission of acupuncture information and the inhibition of systemic inflammation. In MODS, acupuncture protects against septic organ damage by inhibiting excessive inflammatory reactions, resisting oxidative stress, protecting mitochondrial function, and reducing apoptosis and tissue or organ damage

Molecular epidemiological characteristics of Mycobacterium leprae in highly endemic areas of China during the COVID-19 epidemic

ObjectivesThe present study analyzed the impact of the COVID-19 pandemic on the prevalence and incidence of new leprosy cases, as well as the diversity, distribution, and temporal transmission of Mycobacterium leprae strains at the county level in leprae-endemic provinces in Southwest China.MethodsA total of 219 new leprosy cases during two periods, 2018–2019 and 2020–2021, were compared. We genetically characterized 83 clinical isolates of M. leprae in Guizhou using variable number tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). The obtained genetic profiles and cluster consequences of M. leprae were compared between the two periods.ResultsThere was an 18.97% decrease in the number of counties and districts reporting cases. Considering the initial months (January–March) of virus emergence, the number of new cases in 2021 increased by 167% compared to 2020. The number of patients with a delay of >12 months before COVID-19 (63.56%) was significantly higher than that during COVID-19 (48.51%). Eighty-one clinical isolates (97.60%) were positive for all 17 VNTR types, whereas two (2.40%) clinical isolates were positive for 16 VNTR types. The (GTA)9, (TA)18, (TTC)21 and (TA)10 loci showed higher polymorphism than the other loci. The VNTR profile of these clinical isolates generated five clusters, among which the counties where the patients were located were adjacent or relatively close to each other. SNP typing revealed that all clinical isolates possessed the single SNP3K.ConclusionCOVID-19 may have a negative/imbalanced impact on the prevention and control measures of leprosy, which could be a considerable fact for official health departments. Isolates formed clusters among counties in Guizhou, indicating that the transmission chain remained during the epidemic and was less influenced by COVID-19 preventative policies

Polyploidy underlies co-option and diversification of biosynthetic triterpene pathways in the apple tribe

Whole-genome duplication (WGD) plays important roles in plant evolution and function, yet little is known about how WGD underlies metabolic diversification of natural products that bear significant medicinal properties, especially in nonmodel trees. Here, we reveal how WGD laid the foundation for co-option and differentiation of medicinally important ursane triterpene pathway duplicates, generating distinct chemotypes between species and between developmental stages in the apple tribe. After generating chromosome-level assemblies of a widely cultivated loquat variety and Gillenia trifoliata, we define differentially evolved, duplicated gene pathways and date the WGD in the apple tribe at 13.5 to 27.1 Mya, much more recent than previously thought. We then functionally characterize contrasting metabolic pathways responsible for major triterpene biosynthesis in G. trifoliata and loquat, which pre- and postdate the Maleae WGD, respectively. Our work mechanistically details the metabolic diversity that arose post-WGD and provides insights into the genomic basis of medicinal properties of loquat, which has been used in both traditional and modern medicines