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Abstract Background Understanding how the COVID-19 pandemic evolved under control measures is crucial to tackle the SARS-CoV-2 virus spread. Laos, a country bordering China but with late occurrence and low burden of COVID-19 compared to its neighbouring countries, was used for a case study. Methods A transmission model with disease reporting was proposed to investigate the impact of control measures on the SARS-CoV-2 virus spread in Laos from April 2021 to May 2022. It was assumed that the transmission rate changed with people’s behaviours, control measures and emerging variants; susceptibility decreased with vaccination and infection. Bayesian inference was used for model calibration to data of confirmed cases, deaths, and recoveries, and the deviance information criterion was used to select the best model variant. Results Our model including Non-pharmaceutical interventions (NPIs), behaviour change, vaccination, and changing variants well explained the three waves in Laos. The Alpha variant was estimated to have a basic reproduction number of 1.55 (95% CrI: 1.47–1.64) and was replaced by the Delta variant from September 2021 which was 1.88 (95% CrI: 1.77–2.01) times more transmissible; the Delta variant was replaced by Omicron variant from March 2022 which was 3.33 (95% CrI: 2.84–3.74) times more transmissible. The Delta variant was the most severe with a case fatality rate of 1.05% (95% CrI: 0.96–1.15%) while the Alpha variant and Omicron variant were much milder. The ascertainment rate was low and variable: first decreasing from 13.2 to 1.8% by 23 May 2021, and then increasing to 23.4% by 15 March 2022. Counterfactual simulations indicated that vaccination played strong roles in reducing infections even under the emergence of immune escape variants while behaviour change delayed but might not flatten the peak of outbreaks. Conclusions The three waves of Laos’ epidemics were due to the invasion of more transmissible and immune escape variants that affected the herd immunity built via vaccination and infection. Even with immunity waning and the escape of new variants, vaccination was still the major contributor to control COVID-19 and combining behaviour changes and vaccination would best suppress future outbreaks of COVID-19.

Low-alloyed magnesium (Mg) alloys have emerged as one of the most promising candidates for lightweight materials. However, their further application potential has been hampered by limitations such as low strength, poor plasticity at room temperature, and unsatisfactory formability. To address these challenges, grain refinement and grain structure control have been identified as crucial factors to achieving high performance in low-alloyed Mg alloys. An effective way for regulating grain structure is through grain boundary (GB) segregation. This review presents a comprehensive summary of the distribution criteria of segregated atoms and the effects of solute segregation on grain size and growth in Mg alloys. The analysis encompasses both single element segregation and multi-element co-segregation behavior, considering coherent interfaces and incoherent interfaces. Furthermore, we introduce the high mechanical performance low-alloyed wrought Mg alloys that utilize GB segregation and analyze the potential impact mechanisms through which GB segregation influences materials properties. Drawing upon these studies, we propose strategies for the design of high mechanical performance Mg alloys with desirable properties, including high strength, excellent ductility, and good formability, achieved through the implementation of GB segregation. The findings of this review contribute to advancing the understanding of grain boundary engineering in Mg alloys and provide valuable insights for future alloy design and optimization.

Abstract RAB3B is essential for the transportation and secretion within cells. Its increased expression is linked to the development and progression of various malignancies. However, understanding of RAB3B’s involvement in carcinogenesis is mostly limited to specific cancer subtypes. Hence, exploring RAB3B's regulatory roles and molecular mechanisms through comprehensive cancer datasets might offer innovative approaches for managing clinical cancer. To examine the potential involvement of RAB3B in the development of cancer, we analyzed data from various sources including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), cBioPortal, HPA, UALCAN, and tissue microarray (TAM). Using bioinformatics techniques, we examined the correlation between RAB3B expression and prognosis, tumor heterogeneity, methylation modifications, and immune microenvironment across different cancer types. Our findings indicate that elevated RAB3B expression can independently predict prognosis in many tumors and has moderate accuracy for diagnosing most cancers. In most cancer types, we identified RAB3B mutations that showed a significant correlation with tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), and microsatellite instability (MSI). Abnormal DNA methylation patterns were also observed in most cancers compared to normal tissues. Additionally, we found significant correlations between RAB3B expression, immune cell infiltration, and immune scores across various cancers. Through pan-cancer analysis, we observed significant differences in RAB3B expression levels between tumors and normal tissues, making it a potential primary factor for cancer diagnosis and prognosis. The IHC results revealed that the expression of RAB3B in six types of tumors was consistent with the results of the pan-cancer analysis of the database. Furthermore, RAB3B showed potential associations with tumor heterogeneity and immunity. Thus, RAB3B can be utilized as an auxiliary diagnostic marker for early tumor detection and a prognostic biomarker for various tumor types.

Abstract Background Gut bacteria are beneficial to the host, many of which must be passed on to host offspring. During metamorphosis, the midgut of holometabolous insects undergoes histolysis and remodeling, and thus risks losing gut bacteria. Strategies employed by holometabolous insects to minimize this risk are obscure. How gut bacteria affect host insects after entering the hemocoel and causing opportunistic infections remains largely elusive. Results We used holometabolous Helicoverpa armigera as a model and found low Lactobacillus load, high level of a C-type lectin (CTL) gene CD209 antigen-like protein 2 (CD209) and its downstream lysozyme 1 (Lys1) in the midgut of the wandering stage. CD209 or Lys1 depletion increased the load of midgut Lactobacillus, which further translocate to the hemocoel. In particular, CD209 or Lys1 depletion, injection of Lactobacillus plantarum, or translocation of midgut L. plantarum into the hemocoel suppressed 20-hydroxyecdysone (20E) signaling and delayed pupariation. Injection of L. plantarum decreased triacylglycerol and cholesterol storage, which may result in insufficient energy and 20E available for pupariation. Further, Lysine-type peptidoglycan, the major component of gram-positive bacterial cell wall, contributed to delayed pupariation and decreased levels of triacylglycerols, cholesterols, and 20E, in both H. armigera and Drosophila melanogaster. Conclusions A mechanism by which (Lactobacillus-induced) opportunistic infections delay insect metamorphosis was found, namely by disturbing the homeostasis of lipid metabolism and reducing 20E production. Moreover, the immune function of CTL − Lys was characterized for insect metamorphosis by maintaining gut homeostasis and limiting the opportunistic infections.

Abstract Thyroid hormone receptor interactor 6 (TRIP6) it is an adaptor protein belonging to the zyxin family of LIM proteins, participating in signaling events through interactions with various molecules. Despite this, TRIP6's role in colorectal cancer (CRC), particularly its correlation with glucose metabolism and immune cell infiltration, remains unclear. Through the TCGA and GEO databases, we obtained RNA sequencing data to facilitate our in-depth study and analysis of TRIP6 expression. To investigate the prognostic value of TRIP6 in CRC, we also used univariate Cox regression analysis. In addition, this study also covered a series of analyses, including clinicopathological analysis, functional enrichment analysis, glycolysis correlation analysis, immunoinfiltration analysis, immune checkpoint analysis, and angiogenesis correlation analysis, to gain a comprehensive and in-depth understanding of this biological phenomenon. It has been found that TRIP6 expression is significantly upregulated in CRC and correlates with the stage of the disease. Its overexpression portends a worse survival time. Functional enrichment analysis reveals that TRIP6 is associated with focal adhesion and glycolysis. Mechanistically, TRIP6 appears to exert its tumorigenic effect by regulating the glycolysis-related gene GPI. A higher level of expression of TRIP6 is associated with an increase in the number of iDC immune cells and a decrease in the number of Th1 immune cells. Also, TRIP6 may promote angiogenesis in tumor cells by promoting the expression of JAG2. Our study uncovers the upregulation of TRIP6 in CRC, illuminating its prognostic and diagnostic value within this context. Furthermore, we examine the relationship between TRIP6 expression levels, glycolysis, angiogenesis and immune cell infiltration. This underscores its potential as a biomarker for CRC treatment and as a therapeutic target.

Abstract Background Lipid management in clinic is critical to the prevention and treatment of Chronic kidney disease (CKD), while the manifestations of lipid indicators vary in types and have flexible association with CKD prognosis. Purpose Explore the associations between the widely used indicators of lipid metabolism and their distribution in clinic and CKD prognosis; provide a reference for lipid management and inform treatment decisions for patients with non-dialysis CKD stage 3–5. Methods This is a retrospective cohort study utilizing the Self-Management Program for Patients with Chronic Kidney Disease Cohort (SMP-CKD) database of 794 individuals with CKD stages 3–5. It covers demographic data, clinical diagnosis and medical history collection, laboratory results, circulating lipid profiles and lipid distribution assessments. Primary endpoint was defined as a composite outcome(the initiation of chronic dialysis or renal transplantation, sustained decline of 40% or more in estimated glomerular filtration rate (eGFR), doubled of serum creatinine (SCr) from the baseline, eGFR less than 5 mL/min/1.73m2, or all-cause mortality). Exposure variables were circulating lipid profiles and lipid distribution measurements. Association were assessed using Relative risks (RRs) (95% confidence intervals (CIs)) computed by multivariate Poisson models combined with least absolute shrinkage and selection operator (LASSO) regression according to categories of lipid manifestations. The best model was selected via akaike information criterion (AIC), area under curve (AUC), receiver operating characteristic curve (ROC) and net reclassification index (NRI). Subgroup analysis and sensitivity analysis were performed to assess the interaction effects and robustness.. Results 255 individuals reached the composite outcome. Median follow-up duration was 2.03 [1.06, 3.19] years. Median age was 58.8 [48.7, 67.2] years with a median eGFR of 33.7 [17.6, 47.8] ml/min/1.73 m2. Five dataset were built after multiple imputation and five category-based Possion models were constructed for each dataset. Model 5 across five datasets had the best fitness with smallest AIC and largest AUC. The pooled results of Model 5 showed that total cholesterol (TC) (RR (95%CI) (per mmol/L) :1.143[1.023,1.278], P = 0.018) and percentage of body fat (PBF) (RR (95%CI) (per percentage):0.976[0.961,0.992], P = 0.003) were significant factors of composite outcome. The results indicated that comprehensive consideration of lipid metabolism and fat distribution is more critical in the prediction of CKD prognosis.. Conclusion Comprehensive consideration of lipid manifestations is optimal in predicting the prognosis of individuals with non-dialysis CKD stages 3–5.

Abstract Micron-sized Si anode promises a much higher theoretical capacity than the traditional graphite anode and more attractive application prospect compared to its nanoscale counterpart. However, its severe volume expansion during lithiation requires solid electrolyte interphase (SEI) with reinforced mechanical stability. Here, we propose a solvent-induced selective dissolution strategy to in situ regulate the mechanical properties of SEI. By introducing a high-donor-number solvent, gamma-butyrolactone, into conventional electrolytes, low-modulus components of the SEI, such as Li alkyl carbonates, can be selectively dissolved upon cycling, leaving a robust SEI mainly consisting of lithium fluoride and polycarbonates. With this strategy, raw micron-sized Si anode retains 87.5% capacity after 100 cycles at 0.5 C (1500 mA g−1, 25°C), which can be improved to >300 cycles with carbon-coated micron-sized Si anode. Furthermore, the Si||LiNi0.8Co0.1Mn0.1O2 battery using the raw micron-sized Si anode with the selectively dissolved SEI retains 83.7% capacity after 150 cycles at 0.5 C (90 mA g−1). The selective dissolution effect for tailoring the SEI, as well as the corresponding cycling life of the Si anodes, is positively related to the donor number of the solvents, which highlights designing high-donor-number electrolytes as a guideline to tailor the SEI for stabilizing volume-changing alloying-type anodes in high-energy rechargeable batteries.