VPatho: a deep learning-based two-stage approach for accurate prediction of gain-of-function and loss-of-function variants.

Determining the pathogenicity and functional impact (i.e. gain-of-function; GOF or loss-of-function; LOF) of a variant is vital for unraveling the genetic level mechanisms of human diseases. To provide a 'one-stop' framework for the accurate identification of pathogenicity and functional impact of variants, we developed a two-stage deep-learning-based computational solution, termed VPatho, which was trained using a total of 9619 pathogenic GOF/LOF and 138 026 neutral variants curated from various databases. A total number of 138 variant-level, 262 protein-level and 103 genome-level features were extracted for constructing the models of VPatho. The development of VPatho consists of two stages: (i) a random under-sampling multi-scale residual neural network (ResNet) with a newly defined weighted-loss function (RUS-Wg-MSResNet) was proposed to predict variants' pathogenicity on the gnomAD_NV + GOF/LOF dataset; and (ii) an XGBOD model was constructed to predict the functional impact of the given variants. Benchmarking experiments demonstrated that RUS-Wg-MSResNet achieved the highest prediction performance with the weights calculated based on the ratios of neutral versus pathogenic variants. Independent tests showed that both RUS-Wg-MSResNet and XGBOD achieved outstanding performance. Moreover, assessed using variants from the CAGI6 competition, RUS-Wg-MSResNet achieved superior performance compared to state-of-the-art predictors. The fine-trained XGBOD models were further used to blind test the whole LOF data downloaded from gnomAD and accordingly, we identified 31 nonLOF variants that were previously labeled as LOF/uncertain variants. As an implementation of the developed approach, a webserver of VPatho is made publicly available at http://csbio.njust.edu.cn/bioinf/vpatho/ to facilitate community-wide efforts for profiling and prioritizing the query variants with respect to their pathogenicity and functional impact.

TransEFVP: A Two-Stage Approach for the Prediction of Human Pathogenic Variants Based on Protein Sequence Embedding Fusion.

Studying the effect of single amino acid variations (SAVs) on protein structure and function is integral to advancing our understanding of molecular processes, evolutionary biology, and disease mechanisms. Screening for deleterious variants is one of the crucial issues in precision medicine. Here, we propose a novel computational approach, TransEFVP, based on large-scale protein language model embeddings and a transformer-based neural network to predict disease-associated SAVs. The model adopts a two-stage architecture: the first stage is designed to fuse different feature embeddings through a transformer encoder. In the second stage, a support vector machine model is employed to quantify the pathogenicity of SAVs after dimensionality reduction. The prediction performance of TransEFVP on blind test data achieves a Matthews correlation coefficient of 0.751, an F1-score of 0.846, and an area under the receiver operating characteristic curve of 0.871, higher than the existing state-of-the-art methods. The benchmark results demonstrate that TransEFVP can be explored as an accurate and effective SAV pathogenicity prediction method. The data and codes for TransEFVP are available at https://github.com/yzh9607/TransEFVP/tree/master for academic use.

Exploring the Multiple Roles of Notch1 in Biological Development: An Analysis and Study Based on Phylogenetics and Transcriptomics.

At present, there is a research gap concerning the specific functions and mechanisms of the Notch gene family and its signaling pathway in jawless vertebrates. In this study, we identified a Notch1 homologue (Lr. Notch1) in the Lethenteron reissneri database. Through bioinformatics analysis, we identified Lr. Notch1 as the likely common ancestor gene of the Notch gene family in higher vertebrates, indicating a high degree of conservation in the Notch gene family and its signaling pathways. To validate the biological function of Lr. Notch1, we conducted targeted silencing of Lr. Notch1 in L. reissneri and analyzed the resultant gene expression profile before and after silencing using transcriptome analysis. Our findings revealed that the silencing of Lr. Notch1 resulted in differential expression of pathways and genes associated with signal transduction, immune regulation, and metabolic regulation, mirroring the biological function of the Notch signaling pathway in higher vertebrates. This article systematically elucidated the origin and evolution of the Notch gene family while also validating the biological function of Lr. Notch1. These insights offer valuable clues for understanding the evolution of the Notch signaling pathway and establish a foundation for future research on the origin of the Notch signaling pathway, as well as its implications in human diseases and immunomodulation.

Evolutionary and functional analysis of metabotropic glutamate receptors in lampreys.

The metabotropic glutamate receptor (mGluR, GRM) family is involved in multiple signaling pathways and regulates neurotransmitter release. However, the evolutionary history, distribution, and function of the mGluRs family in lampreys have not been determined. Therefore, we identified the mGluRs gene family in the genome of Lethenteron reissneri, which has been conserved throughout vertebrate evolution. We confirmed that Lr-GRM3, Lr-GRM5, and Lr-GRM7 encode three types of mGluRs in lamprey. Additionally, we investigated the distribution of Lr-GRM3 within this species by qPCR and Western blotting. Furthermore, we conducted RNA sequencing to investigate the molecular function of Lr-GRM3 in lamprey. Our gene expression profile revealed that, similar to that in jawed vertebrates, Lr-GRM3 participates in multiple signal transduction pathways and influences synaptic excitability in lampreys. Moreover, it also affects intestinal motility and the inflammatory response in lampreys. This study not only enhances the understanding of mGluRs' gene evolution but also highlights the conservation of GRM3's role in signal transduction while expanding our knowledge of its functions specifically within lampreys. In summary, our experimental findings provide valuable insights for studying both the evolution and functionality of the mGluRs family.

Atomic Layers of B2 CuPd on Cu Nanocubes as Catalysts for Selective Hydrogenation.

The search for highly active and selective catalysts with high precious metal atom utilization efficiency has attracted increasing interest in both the fundamental synthesis of materials and important industrial reactions. Here, we report the synthesis of Pd-Cu nanocubes with a Cu core and an ordered B2 intermetallic CuPd shell with controllable atomic layers on the surface (denoted as Cu/B2 CuPd), which can efficiently and robustly catalyze the selective hydrogenation of acetylene (C2H2) to ethylene (C2H4) under mild conditions. The optimized Cu/B2 CuPd with a Pd loading of 9.5 at. % exhibited outstanding performance in the C2H2 semi-hydrogenation with 100% C2H2 conversion and 95.2% C2H4 selectivity at 90 °C. We attributed this outstanding performance to the core/shell structure with a high surface density of active Pd sites isolated by Cu in the B2 intermetallic matrix, representing a structural motif of single-atom alloys (SAAs) on the surface. The combined experimental and computational studies further revealed that the electronic states of Pd and Cu are modulated by SAAs from the synergistic effect between Pd and Cu, leading to enhanced performance compared with pristine Pd and Cu catalysts. This study provides a new synthetic methodology for making single-atom catalysts with high precious metal atom utilization efficiency, enabling simultaneous tuning of both geometric and electronic structures of Pd active sites for enhanced catalysis.

MMPatho: Leveraging Multilevel Consensus and Evolutionary Information for Enhanced Missense Mutation Pathogenic Prediction.

Understanding the pathogenicity of missense mutation (MM) is essential for shed light on genetic diseases, gene functions, and individual variations. In this study, we propose a novel computational approach, called MMPatho, for enhancing missense mutation pathogenic prediction. First, we established a large-scale nonredundant MM benchmark data set based on the entire Ensembl database, complemented by a focused blind test set specifically for pathogenic GOF/LOF MM. Based on this data set, for each mutation, we utilized Ensembl VEP v104 and dbNSFP v4.1a to extract variant-level, amino acid-level, individuals' outputs, and genome-level features. Additionally, protein sequences were generated using ENSP identifiers with the Ensembl API, and then encoded. The mutant sites' ESM-1b and ProtTrans-T5 embeddings were subsequently extracted. Then, our model group (MMPatho) was developed by leveraging upon these efforts, which comprised ConsMM and EvoIndMM. To be specific, ConsMM employs individuals' outputs and XGBoost with SHAP explanation analysis, while EvoIndMM investigates the potential enhancement of predictive capability by incorporating evolutionary information from ESM-1b and ProtT5-XL-U50, large protein language embeddings. Through rigorous comparative experiments, both ConsMM and EvoIndMM were capable of achieving remarkable AUROC (0.9836 and 0.9854) and AUPR (0.9852 and 0.9902) values on the blind test set devoid of overlapping variations and proteins from the training data, thus highlighting the superiority of our computational approach in the prediction of MM pathogenicity. Our Web server, available at http://csbio.njust.edu.cn/bioinf/mmpatho/, allows researchers to predict the pathogenicity (alongside the reliability index score) of MMs using the ConsMM and EvoIndMM models and provides extensive annotations for user input. Additionally, the newly constructed benchmark data set and blind test set can be accessed via the data page of our web server.

Bioinspired Engineering of Fillable Gradient Structure into Flexible Capacitive Pressure Sensor Toward Ultra-High Sensitivity and Wide Working Range.

Tactile sensing is required for electronic skin and intelligent robots to function properly. However, the dielectric layer's poor structural compressibility in conventional pressure sensors results in a limited pressure sensing range and low sensitivity. To solve this issue, a flexible pressure sensor with a crocodile-inspired fillable gradient structure is provided. The fillable gradient structure and grooves in the pressure sensor accommodate the deformed microstructure that permits the enhancement of the media layer compressibility via COMSOL finite element simulation and optimization. The pressure sensor exhibits a high sensitivity of up to 0.97 k Pa-1 (0-4 kPa), a wide pressure detection range (7 Pa-380 kPa), and outstanding repeatability. The sensor can detect Morse code, robotic grabbing, and human motion monitoring. As a result, flexible sensors with a bionic fillable gradient structure pave the way for wearable devices and offer a novel method for achieving highly precise tactile perception.

α-lipoic acid ameliorates hepatotoxicity induced by chronic ammonia toxicity in crucian carp (Carassius auratus gibelio) by alleviating oxidative stress, inflammation and inhibiting ERS pathway.

High environment ammonia (HEA) poses a deadly threat to aquatic animals and indirectly impacts human healthy life, while nutritional regulation can alleviate chronic ammonia toxicity. α-lipoic acid exhibits antioxidative effects in both aqueous and lipid environments, mitigating cellular and tissue damage caused by oxidative stress by aiding in the neutralization of free radicals (reactive oxygen species). Hence, investigating its potential as an effective antioxidant and its protective mechanisms against chronic ammonia stress in crucian carp is highly valuable. Experimental fish (initial weight 20.47 ± 1.68 g) were fed diets supplemented with or without 0.1% α-lipoic acid followed by a chronic ammonia exposure (10 mg/L) for 42 days. The results revealed that chronic ammonia stress affected growth (weight gain rate, specific growth rate, and feed conversion rate), leading to oxidative stress (decreased the activities of antioxidant enzymes catalase, superoxide dismutase, glutathione peroxidase; decreased total antioxidant capacity), increased lipid peroxidation (accumulation of malondialdehyde), immune suppression (decreased contents of nonspecific immune enzymes AKP and ACP, 50% hemolytic complement, and decrease of immunoglobulin M), impaired ammonia metabolism (reduced contents of Glu, GS, GSH, and Gln), imbalance of expression of induced antioxidant-related genes (downregulation of Cu/Zu SOD, CAT, Nrf2, and HO-1; upregulation of GST and Keap1), induction of pro-apoptotic molecules (transcription of BAX, Caspase3, and Caspase9), downregulation of anti-apoptotic gene Bcl-2 expression, and induction of endoplasmic reticulum stress (upregulation of IRE1, PERK, and ATF6 expression). The results suggested that the supplementation of α-lipoic acid could effectively induce humoral immunity, alleviate oxidative stress injury and endoplasmic reticulum stress, and ultimately alleviate liver injury induced by ammonia poisoning (50-60% reduction). This provides theoretical basis for revealing the toxicity of long-term ammonia stress and provides new insights into the anti-ammonia toxicity mechanism of α-lipoic acid.

Metal-Metal Oxide Catalytic Interface Formation and Structural Evolution: A Discovery of Strong Metal-Support Bonding, Ordered Intermetallics, and Single Atoms.

In-depth investigation of metal-metal oxide interactions and their corresponding evolution is of paramount importance to heterogeneous catalysis as it allows the understanding and maneuvering of the structure of catalytic motifs. Herein, using a series of core/shell metal/iron oxide (M/FeOx, M = Pd, Pt, Au) nanoparticles and through a combination of in situ and ex situ electron and X-ray investigations, we revealed anomalous and dissimilar M-FeOx interactions among different systems under reducing conditions. Pd interacts strongly with FeOx after high-temperature reductive treatment, featured by the formation of Pd single atoms in the FeOx matrix and increased Pd-Fe bonding, while Pt transforms into ordered PtFe intermetallics and Pt single atoms immediately upon the coating of FeOx. In contrast, Au does not manifest strong bonding with FeOx. As a proof of concept of tailoring metal-metal oxide interactions for catalysis, optimized Pd/FeOx demonstrates 100% conversion and 86.5% selectivity at 60 °C for acetylene semihydrogenation.

Developing Carbon Dots with Room-Temperature Phosphorescence for the Dual-Signal Detection of Metronidazole.

Room-temperature phosphorescent carbon dots (CDs) show the advanced property owing to their dual signal; howbeit, acquiring the efficient phosphorescence of CDs is still challengeable. Here, we proposed one type of CD doped with nitrogen through the microwave method, which exhibited the obvious blue fluorescence in aqueous solution and green phosphorescence immobilized on filter paper, while diethylenetriamine pentamethylene phosphonic acid provided the source of carbon and nitrogen. Importantly, introducing metronidazole (MNZ) into the CDs leads to their simultaneous decrease in both fluorescence and phosphorescence, and thus, we successfully established a dual-signal strategy for detecting MNZ. Likewise, this fluorescent detection showed the linear range of 2-200 µM and the phosphorescent way of 50-2000 µM. Meanwhile, the corresponding detection mechanism was also explored, and both the quenched fluorescence and phosphorescence of CDs were mainly due to the occurrence of the electron transfer and internal filtration effect between CDs and MNZ. Additionally, we employed these CDs as the fluorescent and phosphorescent inks for painting and information encryption.

Liver tumor F-18 FDG-PET before and immediately after microwave ablation enables imaging and quantification of tumor tissue contraction.

PURPOSE: Poor liver tumor visibility after microwave ablation (MWA) limits direct tumor ablation margin assessments using contrast-enhanced CT or ultrasound (US). Positron emission tomography (PET) or PET/CT may offer improved intraprocedural assessment of liver tumor ablation margins versus current imaging techniques, as 18F-fluorodeoxyglucose (18F-FDG)-avid tumors remain visible on PET immediately following ablation. The purpose of this study was to assess intraprocedural 18F-FDG PET scans before and immediately after PET/CT-guided MWA for visualization and quantification of metabolic liver tumor tissue contraction resulting from MWA. METHODS: This retrospective study, conducted at a large academic medical center after Institutional Review Board approval, included 36 patients (20 men; mean age 63 [range 37-85]) who underwent PET/CT-guided MWA of 42 18F-FDG-avid liver tumors from May 2013 to March 2018. Tumor metabolic diameters (short/long axes) were measured for each tumor on pre- and post-ablation PET images. Tumor metabolic volumes were calculated using tumor diameter measurements and compared with automated volumes using an SUV threshold algorithm. A two-tailed paired t test was used for the analyses. RESULTS: Comparing intraprocedural pre- and post-ablation PET images, mean metabolic tumor short- and long-axis diameters decreased from 21.4 to 14.9 mm [- 29%, p < 0.001, standard deviation (SD) 18%] and from 24.0 to 18.0 mm (- 24%, p < 0.001, SD 16%), respectively. The mean calculated tumor metabolic volume decreased from 10.5 to 4.6 mm3 (- 55%, p < 0.001, SD 26%). The mean automated tumor metabolic volume decreased from 10.6 to 5.8 mm3 (- 45%, p < 0.001, SD 30%). CONCLUSION: Intraprocedural PET images of 18F-FDG-avid liver tumors allow visualization and quantification of MWA-induced metabolic tumor tissue contraction during 18F-FDG PET/CT-guided procedures. The ability to visualize contracted tumor immediately post-MWA may facilitate emerging intraprocedural PET and PET/CT imaging techniques that address a clinical gap in directly assessing the ablation margin.

Rhodium(I) Complex-Based Polymeric Nanomicelles in Water Exhibiting Coexistent Near-Infrared Phosphorescence Imaging and Anticancer Activity in Vivo.

Metal complexes that exhibit both near-infrared (NIR) phosphorescence imaging and chemotherapeutic activity would represent a novel class of anticancer drugs in clinical tumor treatment. In this work, a series of novel rodlike nanomicelles have been fabricated in water by coupling poly(ethylene oxide)-block-poly(sodium acrylate) and [Rh(C≡N-2,6-xylyl)4]+(1/2SO4)-. These nanomicelles exhibit intense NIR phosphorescence and excellent stability. As revealed by in vivo NIR phosphorescence imaging data, the rodlike nanomicelle can selectively stain tumor sites with a long retention time. Moreover, the nanorods demonstrate effective anticancer activity by precisely killing tumor tissues without damaging healthy organs in vivo. To the best of our knowledge, this research provides the first example of metal-based complexes showing simultaneous NIR luminescence imaging and antitumor activity in vivo.

Improving Patient Experience in Radiology: Impact of a Multifaceted Intervention on National Ranking.

Purpose To assess the impact of a patient experience improvement program on national ranking in patient experience in a large academic radiology department. Materials and Methods This Health Insurance Portability and Accountability Act-compliant study was exempted from institutional review board approval. After initiating an electronic patient experience survey, 26 210 surveys and 22 213 comments were received from May 2017 to April 2018. During the study period, a multifaceted quality improvement initiative was instituted, focused on improving patient experience in the radiology department. The primary outcome was national percentile ranking as measured with the survey. Secondary outcome was the change in departmental percentile ranking compared with the overall hospital ranking for patient experience measured with a similar survey. Results The overall raw score for the department increased from 92.8 to 93.6 of 100 (P < .001), and the national ranking improved from the 35th to 50th percentile (P = .001). Improvements in raw scores related to personnel were primarily responsible for the increase in overall raw score and ranking. Of the 22 213 comments received, 3458 (15.6%) were negative. The percentage of negative comments was highly correlated with lower monthly percentile ranking (Pearson correlation coefficient of -0.69; P = .01). Conclusion It is feasible to develop a large-scale electronic survey to assess patient experience in the radiology department, to identify improvement opportunities, and to measurably improve patient experience. Changes in the percentage of negative comments were correlated with changes in a practice's national percentile rank in patient experience. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Kruskal and Sarwar in this issue.

Size-, Shape-, and Composition-Dependent Model for Metal Nanoparticle Stability Prediction.

Although tremendous applications for metal nanoparticles have been found in modern technologies, the understanding of their stability as related to morphology (size and shape) and chemical ordering (e.g., in bimetallics) remains limited. First-principles methods such as density functional theory (DFT) are capable of capturing accurate nanoalloy energetics; however, they are limited to very small nanoparticle sizes (<2 nm in diameter) due to their computational cost. Herein, we propose a bond-centric (BC) model able to capture cohesive energy trends over a range of monometallic and bimetallic nanoparticles and mixing behavior (excess energy) of nanoalloys, in great agreement with DFT calculations. We apply the BC model to screen the energetics of a recently reported 23 196-atom FePt nanoalloys ( Yang et al. Nature 2017 , 542 , 75 - 79 ), offering insights into both segregation and bulk-chemical ordering behavior. Because the BC model utilizes tabulated data (diatomic bond energies and bulk cohesive energies) and structural information on nanoparticles (coordination numbers), it can be applied to calculate the energetics of any nanoparticle morphology and chemical composition, thus significantly accelerating nanoalloy design.

Yield of CT Pulmonary Angiography in the Emergency Department When Providers Override Evidence-based Clinical Decision Support.

Purpose To determine the frequency of, and yield after, provider overrides of evidence-based clinical decision support (CDS) for ordering computed tomographic (CT) pulmonary angiography in the emergency department (ED). Materials and Methods This HIPAA-compliant, institutional review board-approved study was performed at a tertiary care, academic medical center ED with approximately 60 000 annual visits and included all patients who were suspected of having pulmonary embolism (PE) and who underwent CT pulmonary angiography between January 1, 2011, and August 31, 2013. The requirement to obtain informed consent was waived. Each CT order for pulmonary angiography was exposed to CDS on the basis of the Wells criteria. For patients with a Wells score of 4 or less, CDS alerts suggested d-dimer testing because acute PE is highly unlikely in these patients if d-dimer levels are normal. The yield of CT pulmonary angiography (number of positive PE diagnoses/total number of CT pulmonary angiographic examinations) was compared in patients in whom providers overrode CDS alerts (by performing CT pulmonary angiography in patients with a Wells score ≤4 and a normal d-dimer level or no d-dimer testing) (override group) and those in whom providers followed Wells criteria (CT pulmonary angiography only in patients with Wells score >4 or ≤4 with elevated d-dimer level) (adherent group). A validated natural language processing tool identified positive PE diagnoses, with subsegmental and/or indeterminate diagnoses removed by means of chart review. Statistical analysis was performed with the χ2 test, the Student t test, and logistic regression. Results Among 2993 CT pulmonary angiography studies in 2655 patients, 563 examinations had a Wells score of 4 or less but did not undergo d-dimer testing and 26 had a Wells score of 4 or less and had normal d-dimer levels. The yield of CT pulmonary angiography was 4.2% in the override group (25 of 589 studies, none with a normal d-dimer level) and 11.2% in the adherent group (270 of 2404 studies) (P < .001). After adjustment for the risk factor differences between the two groups, the odds of an acute PE finding were 51.3% lower when providers overrode alerts than when they followed CDS guidelines. Comparison of the two groups including only patients unlikely to have PE led to similar results. Conclusion The odds of an acute PE finding in the ED when providers adhered to evidence presented in CDS were nearly double those seen when providers overrode CDS alerts. Most overrides were due to the lack of d-dimer testing in patients unlikely to have PE. © RSNA, 2016.

The placental interleukin-6 signaling controls fetal brain development and behavior.

Epidemiological studies show that maternal immune activation (MIA) during pregnancy is a risk factor for autism. However, mechanisms for how MIA affects brain development and behaviors in offspring remain poorly described. To determine whether placental interleukin-6 (IL-6) signaling is required for mediating MIA on the offspring, we generated mice with restricted deletion of the receptor for IL-6 (IL-6Rα) in placental trophoblasts (Cyp19-Cre+;Il6rafl/fl), and tested offspring of Cyp19-Cre+;Il6rafl/fl mothers for immunological, pathological and behavioral abnormalities following induction of MIA. We reveal that MIA results in acute inflammatory responses in the fetal brain. Lack of IL-6 signaling in trophoblasts effectively blocks MIA-induced inflammatory responses in the placenta and the fetal brain. Furthermore, behavioral abnormalities and cerebellar neuropathologies observed in MIA control offspring are prevented in Cyp19-Cre+;Il6rafl/fl offspring. Our results demonstrate that IL-6 activation in placenta is required for relaying inflammatory signals to the fetal brain and impacting behaviors and neuropathologies relevant to neurodevelopmental disease.

Synergistic activation of peroxymonosulfate by 3D CoNiO2/Co core-shell structure biochar catalyst for sulfamethoxazole degradation.

In this study, a 3D CoNiO2/Co core-shell structure biochar catalyst derived from walnut shell was synthesized by hydrothermal and ion etching methods. The prepared BC@CoNi-600 catalyst exhibited exceptional peroxymonosulfate (PMS) activation. The system achieved 100 % degradation of sulfamethoxazole (SMX). The reactive oxygen species in the BC@CoNi-600/PMS system included SO4-, OH, and O2-. Density functional theory calculations explored the synergistic effects between nickel-cobalt bimetallic and carbon matrix during PMS activation. The unique 3D core-shell structure of BC@CoNi-600 features an outer nickel-cobalt bimetallic layer with exceptional PMS adsorption capacity, while protecting the zero-valence Co of the inner layer from oxidation. Based on the experimental-data, machine learning modeling mechanism, and information theory, a nonlinear modeling method was proposed. This study utilizes a machine learning approach to investigate the degradation of SMX in complex aquatic environments. This study synthesized a novel biochar-based catalyst for activated PMS and provided unique insights into its environmental applications.

Review of Computational Methods and Database Sources for Predicting the Effects of Coding Frameshift Small Insertion and Deletion Variations.

Genetic variations (including substitutions, insertions, and deletions) exert a profound influence on DNA sequences. These variations are systematically classified as synonymous, nonsynonymous, and nonsense, each manifesting distinct effects on proteins. The implementation of high-throughput sequencing has significantly augmented our comprehension of the intricate interplay between gene variations and protein structure and function, as well as their ramifications in the context of diseases. Frameshift variations, particularly small insertions and deletions (indels), disrupt protein coding and are instrumental in disease pathogenesis. This review presents a succinct review of computational methods, databases, current challenges, and future directions in predicting the consequences of coding frameshift small indels variations. We analyzed the predictive efficacy, reliability, and utilization of computational methods and variant account, reliability, and utilization of database. Besides, we also compared the prediction methodologies on GOF/LOF pathogenic variation data. Addressing the challenges pertaining to prediction accuracy and cross-species generalizability, nascent technologies such as AI and deep learning harbor immense potential to enhance predictive capabilities. The importance of interdisciplinary research and collaboration cannot be overstated for devising effective diagnosis, treatment, and prevention strategies concerning diseases associated with coding frameshift indels variations.

In-situ construction of cation vacancies in amphoteric-metallic element-doped NiFe-LDH as ultrastable and efficient alkaline hydrogen evolution electrocatalysts at 1000 mA cm-2.

Developing efficient and stable electrocatalysts at affordable costs is very important for large-scale production of green hydrogen. In this study, unique amphoteric metallic element-doped NiFe-LDH nanosheet arrays (NiFeCd-LDH, NiFeZn-LDH and NiFeAl-LDH) using as high-performance bifunctional electrocatalysts for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) were reported, by tuning electronic structure and vacancy engineering. It was found that NiFeCd-LDH possesses the lowest overpotentials of 85 mV and 240 mV (at 10 mA cm-2) for HER and OER, respectively. Density functional theory (DFT) calculations reveal the synergistic effect of Cd vacancies and Cd doping on improving alkaline HER performance, which promote the achievement of excellent catalytic activity and ultrastable hydrogen production at a large current density of 1000 mA cm-2 within 250 h. Besides, the overall water splitting performance of the as-prepared NiFeCd-LDH requires only 1.580 V to achieve a current density of 10 mA cm-2 in alkaline seawater media, underscoring the importance of modifying the electronic properties of LDH for efficient overall water splitting in both alkaline water/seawater environments.