Pervasive mislocalization of pathogenic coding variants underlying human disorders.

Widespread sequencing has yielded thousands of missense variants predicted or confirmed as disease causing. This creates a new bottleneck: determining the functional impact of each variant-typically a painstaking, customized process undertaken one or a few genes and variants at a time. Here, we established a high-throughput imaging platform to assay the impact of coding variation on protein localization, evaluating 3,448 missense variants of over 1,000 genes and phenotypes. We discovered that mislocalization is a common consequence of coding variation, affecting about one-sixth of all pathogenic missense variants, all cellular compartments, and recessive and dominant disorders alike. Mislocalization is primarily driven by effects on protein stability and membrane insertion rather than disruptions of trafficking signals or specific interactions. Furthermore, mislocalization patterns help explain pleiotropy and disease severity and provide insights on variants of uncertain significance. Our publicly available resource extends our understanding of coding variation in human diseases.

Tenofovir versus entecavir on the prognosis of hepatitis B virus-related hepatocellular carcinoma: a reconstructed individual patient data meta-analysis.

Background: Hepatitis B, often leading to Hepatocellular carcinoma (HCC), poses a major global health challenge. While Tenofovir (TDF) and Entecavir (ETV) are potent treatments, their comparative effectiveness in improving recurrence-free survival (RFS) and overall survival (OS) rates in HBV-related HCC is not well-established. Methods: We conducted an individual patient data meta-analysis using survival data from randomized trials and high-quality propensity score-matched studies to compare the impact of Tenofovir (TDF) and Entecavir (ETV) on RFS and OS in HBV-related HCC patients. Data from six databases and gray literature up to 30 August 2023, were analyzed, utilizing Kaplan-Meier curves, stratified Cox models, and shared frailty models for survival rate assessment and to address between-study heterogeneity. The study employed restricted mean survival time analysis to evaluate differences in RFS and OS between TDF-treated and ETV-treated patients. Additionally, landmark analyses compared early (<2 years) and late (≥2 years) tumor recurrence in these cohorts. Results: This study incorporated seven research articles, covering 4,602 patients with HBV-related HCC (2,082 on TDF and 2,520 on ETV). Within the overall cohort, TDF recipients demonstrated significantly higher RFS (p = 0.042) and OS (p < 0.001) than those on ETV. The stratified Cox model revealed significantly improved OS for the TDF group compared to the ETV group (hazard ratio, 0.756; 95% confidence interval, 0.639-0.896; p = 0.001), a result corroborated by the shared frailty model. Over a follow-up period of 1-8 years, no significant difference was noted in the mean time to death between the TDF and ETV groups. The rates of early recurrence did not significantly differ between the groups (p = 0.735). However, TDF treatment was significantly associated with a reduced risk of late recurrence compared to ETV (p < 0.001). In the HCC resection subgroup, the disparities in OS, early, and late recurrence rates between the two treatments paralleled those seen in the overall cohort. Conclusion: Compared to ETV, TDF may enhance OS and reduce late tumor recurrence risk in HBV-related HCC patients receiving curative treatment. However, there was no statistically significant distinction in the timing of tumor recurrence and mortality between patients administered TDF and those prescribed ETV. Systematic Review Registration: http://www.crd.york.ac.uk/prospero/.

Cardiovascular and venous thromboembolism risks in cancer patients treated with immune checkpoint inhibitors compared to non-users- a multi-center retrospective study.

BACKGROUND: Immune Checkpoint Inhibitors (ICIs) have revolutionized cancer therapy. This study examines the cardiovascular risks of ICIs compared to non-ICI therapies. METHODS: Utilizing the Chang Gung Research Database (CGRD) of Taiwan, this retrospective study analyzed 188,225 cancer patients, with 1,737 undergoing ICI treatment from January 1, 2008, to June 30, 2021. Through 1:1 propensity score matching (PSM), we compared specific outcomes between patients treated with ICIs and those who were not. The analysis also accounted for the competing risk of mortality in assessing the results after PSM. The observation period spanned from this index date to whichever came first: the date of the specific outcomes, the last follow-up recorded, or the end date of the study on June 30, 2022. RESULTS: The study found no significant increase in the risk of cardiac death, non-fatal myocardial infarction, heart failure hospitalization, deep vein thrombosis, or pulmonary embolism in patients treated with ICIs as compared to those receiving non-ICI therapy. Interestingly, ICI treatment was linked to a lower risk of non-fatal stroke (0.27% per year vs. 0.46% per year; subdistribution hazard ratio = 0.59; 95% confidence interval = 0.35-0.98; P = 0.0430). Furthermore, subgroup analysis revealed that the ICI group had a decreased risk of cardiac death in patients with cancers other than head and neck cancer, and a reduced risk of stroke among diabetic patients. CONCLUSIONS: ICIs do not significantly elevate the risk of cardiovascular events in cancer patients and may lower the stroke risk, underscoring the need for additional prospective studies to clarify these findings.

Fe-N co-doped carbon nanofibers with Fe3C decoration for water activation induced oxygen reduction reaction.

Proton activity at the electrified interface is central to the kinetics of proton-coupled electron transfer (PCET) reactions in electrocatalytic oxygen reduction reaction (ORR). Here, we construct an efficient Fe3C water activation site in Fe-N co-doped carbon nanofibers (Fe3C-Fe1/CNT) using an electrospinning-pyrolysis-etching strategy to improve interfacial hydrogen bonding interactions with oxygen intermediates during ORR. In situ Fourier transform infrared spectroscopy and density functional theory studies identified delocalized electrons as key to water activation kinetics. Specifically, the strong electronic perturbation of the Fe-N4 sites by Fe3C disrupts the symmetric electron density distribution, allowing more free electrons to activate the dissociation of interfacial water, thereby promoting hydrogen bond formation. This process ultimately controls the PCET kinetics for enhanced ORR. The Fe3C-Fe1/CNT catalyst demonstrates a half-wave potential of 0.83 V in acidic media and 0.91 V in alkaline media, along with strong performance in H2-O2 fuel cells and Al-air batteries.

Wet-dry or freeze-thaw alternation can regulate the impacts of farmland plastic pollution on soil bacterial communities and functions.

The persistence of farmland plastic pollution has raised significant concerns regarding its potential long-term impacts on soil health in the context of global climate change. However, there are still gaps in the understanding of the impacts of plastic residues on soil microbial communities and functions in agricultural environments under unstable and extreme climatic conditions. In this study, the effects of plastic residues (two types and three shapes) on farmland soil bacterial communities and functions across varying environmental conditions were investigated through microscopic experiments. The results revealed that plastic residues subjected to wet-dry or freeze-thaw alternations exhibited greater degradation compared to those under natural conditions. The effects of plastic residue types and shapes on soil bacterial diversity and function were regulated by environmental factors. The plastic residues significantly reduced the stability of the bacterial network under natural condition (P < 0.05), whereas the opposite phenomenon was observed under wet-dry or freeze-thaw alternating conditions. Compared to under natural condition, lower numbers of bacterial functional pathways exhibiting significant differences due to plastic residues were observed under wet-dry or freeze-thaw alternating conditions. Significant associations were observed between soil bacterial communities and functions and various soil physicochemical properties under natural conditions (P < 0.05), and most of these associations were attenuated in the wet-dry or freeze-thaw alternations. This study demonstrated the potential impacts of plastic pollution on farmland soil microbiomes, which could be modulated by both residue characteristics and climatic conditions. Specifically, extreme environments could mitigate plastic-pollution-driven influences on soil microbiomes.

No evidence of genetic causation between iron and infertility: a Mendelian randomization study.

Background: Observational studies have explored the impact of iron homeostasis on infertility; however, establishing definitive causal relationships remains challenging. This study utilized a two-sample Mendelian randomization approach to investigate the potential causal relationship between iron status and infertility. Materials and methods: Four indicators of iron status-serum iron, ferritin, transferrin saturation, and total iron binding capacity, were considered as exposure factors. Infertility was the outcome variable for both men and women. Robust causality was assessed using the primary inverse-variance-weighted method, complemented by three supplementary Mendelian randomization approaches. Sensitivity analyses were performed to enhance the precision and reliability of the results. Results: No statistically significant associations were identified between the four indicators of iron status and infertility. These results remained consistent across multiple Mendelian randomization methodologies. Conclusion: In conclusion, there is no evidence of a genetic causal relationship between iron status and infertility. Nevertheless, this does not preclude the possibility of a connection between iron status and infertility at different mechanistic levels.

Liver stiffness in hepatocellular carcinoma and chronic hepatitis patients: Hepatitis B virus infection and transaminases should be considered.

BACKGROUND: Liver condition is a crucial prognostic factor for patients with hepatocellular carcinoma (HCC), but a convenient and comprehensive method to assess liver condition is lacking. Liver stiffness (LS) measured by two-dimensional shear wave elastography may help in assessing liver fibrosis and liver condition. Chronic hepatitis B (CHB) is an important risk factor for HCC progression, but LS was found to be less reliable in assessing liver fibrosis following hepatitis viral eradication. We hypothesize that the status of hepatitis virus infection would affect the accuracy of LS in assessing the liver condition. AIM: To test the feasibility and impact factors of using LS to assess liver condition in patients with HCC and CHB. METHODS: A total of 284 patients were retrospectively recruited and classified into two groups on the basis of serum CHB virus hepatitis B virus (HBV)-DNA levels [HBV-DNA ≥ 100.00 IU/mL as Pos group (n = 200) and < 100.00 IU/mL as Neg group (n = 84)]. Correlation analyses and receiver operating characteristic analyses were conducted to evaluate the relationship between LS and liver condition. RESULTS: A significant correlation was found between LS and most of the parameters considered to have the ability to evaluate liver condition (P < 0.05). When alanine aminotransferase (ALT) concentrations were normal (≤ 40 U/L), LS was correlated with liver condition indices (P < 0.05), but the optimal cutoff of LS to identify a Child-Pugh score of 5 was higher in the Neg group (9.30 kPa) than the Pos group (7.40 kPa). When ALT levels were elevated (> 40 U/L), the correlations between LS and liver condition indices were not significant (P > 0.05). CONCLUSION: LS was significantly correlated with most liver condition indices in patients with CHB and HCC. However, these correlations varied according to differences in HBV-DNA and transaminase concentrations.

A Shape-Consistent Deep-Learning Segmentation Architecture for Low-Quality and High-Interference Myocardial Contrast Echocardiography.

OBJECTIVE: Myocardial contrast echocardiography (MCE) plays a crucial role in diagnosing ischemia, infarction, masses and other cardiac conditions. In the realm of MCE image analysis, accurate and consistent myocardial segmentation results are essential for enabling automated analysis of various heart diseases. However, current manual diagnostic methods in MCE suffer from poor repeatability and limited clinical applicability. MCE images often exhibit low quality and high noise due to the instability of ultrasound signals, while interference structures can further disrupt segmentation consistency. METHODS: To overcome these challenges, we proposed a deep-learning network for the segmentation of MCE. This architecture leverages dilated convolutions to capture high-scale information without sacrificing positional accuracy and modifies multi-head self-attention to enhance global context and ensure consistency, effectively overcoming issues related to low image quality and interference. Furthermore, we also adapted the cascade application of transformers with convolutional neural networks for improved segmentation in MCE. RESULTS: In our experiments, our architecture achieved the best Dice score of 84.35% for standard MCE views compared with that of several state-of-the-art segmentation models. For non-standard views and frames with interfering structures (mass), our models also attained the best Dice scores of 83.33% and 83.97%, respectively. CONCLUSION: These studies proved that our architecture is of excellent shape consistency and robustness, which allows it to deal with segmentation of various types of MCE. Our relatively precise and consistent myocardial segmentation results provide fundamental conditions for the automated analysis of various heart diseases, with the potential to discover underlying pathological features and reduce healthcare costs.

Advancing Metallic Lithium Anodes: A Review of Interface Design, Electrolyte Innovation, and Performance Enhancement Strategies.

Lithium (Li) metal is one of the most promising anode materials for next-generation, high-energy, Li-based batteries due to its exceptionally high specific capacity and low reduction potential. Nonetheless, intrinsic challenges such as detrimental interfacial reactions, significant volume expansion, and dendritic growth present considerable obstacles to its practical application. This review comprehensively summarizes various recent strategies for the modification and protection of metallic lithium anodes, offering insight into the latest advancements in electrode enhancement, electrolyte innovation, and interfacial design, as well as theoretical simulations related to the above. One notable trend is the optimization of electrolytes to suppress dendrite formation and enhance the stability of the electrode-electrolyte interface. This has been achieved through the development of new electrolytes with higher ionic conductivity and better compatibility with Li metal. Furthermore, significant progress has been made in the design and synthesis of novel Li metal composite anodes. These composite anodes, incorporating various additives such as polymers, ceramic particles, and carbon nanotubes, exhibit improved cycling stability and safety compared to pure Li metal. Research has used simulation computing, machine learning, and other methods to achieve electrochemical mechanics modeling and multi-field simulation in order to analyze and predict non-uniform lithium deposition processes and control factors. In-depth investigations into the electrochemical reactions, interfacial chemistry, and physical properties of these electrodes have provided valuable insights into their design and optimization. It systematically encapsulates the state-of-the-art developments in anode protection and delineates prospective trajectories for the technology's industrial evolution. This review aims to provide a detailed overview of the latest strategies for enhancing metallic lithium anodes in lithium-ion batteries, addressing the primary challenges and suggesting future directions for industrial advancement.