Population-based heteropolymer design to mimic protein mixtures.

Biological fluids, the most complex blends, have compositions that constantly vary and cannot be molecularly defined1. Despite these uncertainties, proteins fluctuate, fold, function and evolve as programmed2-4. We propose that in addition to the known monomeric sequence requirements, protein sequences encode multi-pair interactions at the segmental level to navigate random encounters5,6; synthetic heteropolymers capable of emulating such interactions can replicate how proteins behave in biological fluids individually and collectively. Here, we extracted the chemical characteristics and sequential arrangement along a protein chain at the segmental level from natural protein libraries and used the information to design heteropolymer ensembles as mixtures of disordered, partially folded and folded proteins. For each heteropolymer ensemble, the level of segmental similarity to that of natural proteins determines its ability to replicate many functions of biological fluids including assisting protein folding during translation, preserving the viability of fetal bovine serum without refrigeration, enhancing the thermal stability of proteins and behaving like synthetic cytosol under biologically relevant conditions. Molecular studies further translated protein sequence information at the segmental level into intermolecular interactions with a defined range, degree of diversity and temporal and spatial availability. This framework provides valuable guiding principles to synthetically realize protein properties, engineer bio/abiotic hybrid materials and, ultimately, realize matter-to-life transformations.

Plasma campesterol and ABCG5/ABCG8 gene loci on the risk of cholelithiasis and cholecystitis: evidence from Mendelian randomization and colocalization analyses.

The causal relationships between plasma metabolites and cholelithiasis/cholecystitis risks remain elusive. Using two-sample Mendelian randomization, we found that genetic proxied plasma campesterol level showed negative correlation with the risk of both cholelithiasis and cholecystitis. Furthermore, the increased risk of cholelithiasis is correlating with the increased level of plasma campesterol. Lastly, genetic colocalization study showed that the leading SNP, rs4299376, which residing at the ABCG5/ABCG8 gene loci, was shared by plasma campesterol level and cholelithiasis, indicating that the aberrant transportation of plant sterol/cholesterol from the blood stream to the bile duct/gut lumen might be the key in preventing cholesterol gallstone formation.

XAF1 prevents hyperproduction of type I interferon upon viral infection by targeting IRF7.

Interferon regulatory factor (IRF) 3 and IRF7 are master regulators of type I interferon (IFN-I)-dependent antiviral innate immunity. Upon viral infection, a positive feedback loop is formed, wherein IRF7 promotes further induction of IFN-I in the later stage. Thus, it is critical to maintain a suitably low level of IRF7 to avoid the hyperproduction of IFN-I. In this study, we find that early expression of IFN-I-dependent STAT1 promotes the expression of XAF1 and that XAF1 is associated specifically with IRF7 and inhibits the activity of XIAP. XAF1-knockout and XIAP-transgenic mice display resistance to viral infection, and this resistance is accompanied by increases in IFN-I production and IRF7 stability. Mechanistically, we find that the XAF1-XIAP axis controls the activity of KLHL22, an adaptor of the BTB-CUL3-RBX1 E3 ligase complex through a ubiquitin-dependent pathway. CUL3-KLHL22 directly targets IRF7 and catalyzes its K48-linked ubiquitination and proteasomal degradation. These findings reveal unexpected functions of the XAF1-XIAP axis and KLHL22 in the regulation of IRF7 stability and highlight an important target for antiviral innate immunity.

Development of an Ultrasensitive Competitive Double-Enzyme Cascade Fluorescence Signal Amplification Method for Factor XIa Inhibitor Screening.

Coagulation factor XIa (FXIa) is associated with a low risk of bleeding and has been identified as an effective and safe target for the development of novel anticoagulant drugs. In this study, we established an ultrasensitive competitive dual-enzyme cascade signal amplification method for the quantitative analysis and screening of FXIa inhibitors. Due to the specific recognition of FXIa's active site by the aptamer AptE40, the AptE40-QDs-EK recognition probe modified with enterokinase (EK) and the aptamer AptE40, was attached to the MNPs-FXIa capture probe. When FXIa inhibitor was present, it competed with AptE40 for binding to FXIa, resulting in the detachment of AptE40-QDs-EK from MNPs-FXIa. After magnetic separation, the enterokinase of AptE40-QDs-EK in the supernatant hydrolyzed N-terminal hexapeptide of trypsinogen, leading to the production of a large amount of trypsin as part of the first-stage signal cascade amplification. Next, trypsin could hydrolyze the hexameric arginine peptide (RRRRRR, R6), leading to the dissociation of RQDs from the R6-RQDs signal probe; this resulted in a dramatic increase in the fluorescence intensity of the supernatant as the second-stage signal cascade was amplified. The feasibility of the method was investigated using the FXIa inhibitor aptamer FELIAP as a positive model drug. Furthermore, the method was applied to screen the FXIa inhibitors in Eupolyphaga sinensis Walker. Two fractions with more active anticoagulated ingredients were successfully identified and validated via the conventional method, and the results were consistent. The established method provides a key technique for the sensitive detection, high-throughput analysis, and screening of the FXIa inhibitors.

Can uric acid affect the immune microenvironment in bladder cancer? A single-center multi-omics study.

Metabolic abnormalities are one of the important factors in bladder cancer (BCa) progression and microenvironmental disturbance. As an important product of purine metabolism, uric acid's (UA) role in BCa metabolism and immunotherapy remains unclear. In this study, we conducted a retrospective analysis of a cohort comprising 39 BCa patients treated with PD-1 and 169 patients who underwent radical cystectomy at Shanghai Tenth People's Hospital. Kaplan-Meier curves and Cox regression analysis showed that the prognosis of patients with high UA is worse (p = 0.007), and high UA is an independent risk factor for cancer specific survival in patients with BCa (p = 0.025). We established a hyperuricemia mouse model with BCa subcutaneous xenografts in vivo. The results revealed that the subcutaneous tumors of hyperuricemia mice had a greater weight and volume in comparison with the control group. Through flow cytometric analysis, the proportion of CD8+ and CD4+ T cells in these subcutaneous tumors was seen to decline significantly. We also evaluated the relationship of UA and BCa by muti-omic analysis. UA related genes were significantly increased in the CD8+ T cell of non-responders to immunotherapy by single-cell sequencing. An 11-gene UA related signature was constructed and the risk score negatively correlated with various immune cells and immune checkpoints. Finally, a nomogram was established using a UA related signature to forecast the survival rate of patients with BCa. Collectively, this study demonstrated that UA was an independent prognostic biomarker for BCa and was associated with worse immunotherapy response.

Identifying disulfidptosis subtypes in hepatocellular carcinoma through machine learning and preliminary exploration of its connection with immunotherapy.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly prevalent and deadly cancer, with limited treatment options for advanced-stage patients. Disulfidptosis is a recently identified mechanism of programmed cell death that occurs in SLC7A11 high-expressing cells due to glucose starvation-induced disintegration of the cellular disulfide skeleton. We aimed to explore the potential of disulfidptosis, as a prognostic and therapeutic marker in HCC. METHODS: We classified HCC patients into two disulfidptosis subtypes (C1 and C2) based on the transcriptional profiles of 31 disulfrgs using a non-negative matrix factorization (NMF) algorithm. Further, five genes (NEIL3, MMP1, STC2, ADH4 and CFHR3) were screened by Cox regression analysis and machine learning algorithm to construct a disulfidptosis scoring system (disulfS). Cell proliferation assay, F-actin staining and PBMC co-culture model were used to validate that disulfidptosis occurs in HCC and correlates with immunotherapy response. RESULTS: Our results suggests that the low disulfidptosis subtype (C2) demonstrated better overall survival (OS) and progression-free survival (PFS) prognosis, along with lower levels of immunosuppressive cell infiltration and activation of the glycine/serine/threonine metabolic pathway. Additionally, the low disulfidptosis group showed better responses to immunotherapy and potential antagonism with sorafenib treatment. As a total survival risk factor, disulfS demonstrated high predictive efficacy in multiple validation cohorts. We demonstrated the presence of disulfidptosis in HCC cells and its possible relevance to immunotherapeutic sensitization. CONCLUSION: The present study indicates that novel biomarkers related to disulfidptosis may serve as useful clinical diagnostic indicators for liver cancer, enabling the prediction of prognosis and identification of potential treatment targets.

Graphyne-based 3D porous structure and its sandwich-type graphene structure for alkali metal ion battery anode materials.

In order to develop candidate materials for more metal ion battery anodes, a three-dimensional (3D) porous structure 3D-PGY was designed based on graphyne, and a sandwich structure graphene/PGY/graphene (G/PGY/G) was constructed by adjusting the distance between two layers of graphene with 3D-PGY as the middle layer. Systematic calculations have shown that 3D-PGY is thermally and mechanically stable even at temperatures up to 1000 K. Li can migrate in multiple diffusion directions in two structures because of its smaller radius while Na and K ions can only migrate through the larger pores. The energy barriers of Li, Na and K ions in 3D-PGY are 0.18, 0.43 and 0.27 eV respectively. After forming the sandwich structure with graphene, the minimum energy barriers of Li, Na and K ions are decreased to 0.12, 0.37 and 0.24 eV, respectively. As the anode for Li, Na, and K ion batteries, the theoretical specific capacities of 3D-PGY are about 558 mA h g-1, and the average open circuit voltages of 3D-PGY and G/PGY/G are about 0.48/0.52/0.29 and 1.08/1.04/1.39 V, respectively. Finally, using ab initio molecular dynamics simulations, the diffusion coefficients for 3D-PGY at different temperatures, as well as for G/PGY/G at 400 K were obtained. The Li, Na and K ions in both structures can diffuse rapidly and have good rate capabilities. These excellent performances show that the graphyne-based 3D porous structure and its sandwich-type graphene structure are very promising for the development of new battery materials.

Interventions for Postextubation Dysphagia in Critically Ill Patients: A Systematic Review and Meta-analysis.

OBJECTIVE: This review evaluates the efficacy and safety of dysphagia interventions for patients with prolonged endotracheal intubation (⩾48 h) in critical care units. DATA SOURCES: We systematically searched PubMed, Cochrane Library, Medline, Embase, OVID, CINAHL, Wanfang (China), CNKI (China), and ProQuest Dissertations for studies published up to December 31, 2023. STUDY SELECTION: Inclusion criteria encompassed randomized controlled trials (RCTs), quasi-randomized trials, and cohort studies comparing dysphagia rehabilitation - such as swallowing stimulation, swallowing and respiratory muscle exercise, and neuromuscular electrical stimulation - with standard care or no treatment. The primary outcomes assessed were dysphagia severity, time to resume oral intake, and incidence of aspiration and aspiration pneumonia. DATA EXTRACTION: Detailed information on study design, setting, participant demographics, interventions, and outcomes was systematically extracted. DATA SYNTHESIS: Our analysis included ten studies with a total of 1031 participants. The findings demonstrate a significant reduction in dysphagia severity, time to oral intake and the risk of aspiration pneumonia, and an improvement in quality of life among patients receiving swallowing therapy. However, no substantial difference was found in nutritional status. Limited data availability necessitated a descriptive presentation of outcomes like the risk of aspiration, ICU/hospital stay duration, pharyngeal/oral residue severity, and intervention-related adverse events. CONCLUSION: The current evidence for the effectiveness of dysphagia interventions in critically ill patients with prolonged endotracheal intubation is limited. There is a pressing need for future research, particularly high-quality RCTs employing standardized outcome measures, to substantiate these findings.

Associations between short-term exposure to ambient PM2.5 and incident cases of cardiovascular disease in Yantai, China.

There are limited studies investigating the association between short-term exposure to PM2.5 and incident cardiovascular disease (CVD) cases in China. This study aims to examine the short-term effects of PM2.5 on the incidence of cardiovascular diseases. A combination of Poisson-distribution generalized linear model and distributed lag non-linear model was used to examine the association between short-term exposure to PM2.5 and incident cases of CVD. The results revealed that per 10 µg/m3 increment of PM2.5 would increase the incident CVD cases by 0.147% (Relative Risk: 1.00147, 95% Confidence Interval: 1.00008-1.00286) at a lag of 2 days. The stratified analyses showed higher effects risk in females, older residents (aged 60-75 years), and acute myocardial infarction group (p-value for difference <0.05). This study indicates that short-term exposure to PM2.5 may increase the risk of CVD and highlights the necessity for a higher air quality standard in Yantai, China.

Association between PM2.5 and hypertension among the floating population in China: a cross-sectional study.

Few studies have investigated the association between PM2.5 and hypertension among floating populations. We therefore examined the relationship using binary logistic regression. Each grade of increment in the annual average PM2.5 (grade one: ≤15 µg/m3; grade two: 15-25 µg/m3; grade three: 25-35 µg/m3 [Excluding 25]; grade four: ≥35 µg/m3) was associated with an increased risk of hypertension (odds ratio [OR] = 1.081, 95% confidence interval (CI): 1.034-1.129). Among the female floating population (OR = 1.114, 95% CI: 1.030-1.204), those with education level of primary school and below (OR = 1.140, 95% CI: 1.058-1.229), construction workers (OR = 1.228, 95% CI: 1.058-1.426), and those living in the eastern region of China (OR = 1.241, 95% CI: 1.145-1.346) were more vulnerable to PM2.5. These results indicate that PM2.5 is positively associated with hypertension in floating populations. Floating populations who are female, less educated, construction workers, and living in the eastern region of China are more vulnerable to the adverse impacts of PM2.5.

Discovering Electrochemistry with an Electrochemistry-Informed Neural Network (ECINN).

Machine learning is increasingly integrated into chemistry research by guiding experimental procedures, correlating structure and function, interpreting large experimental datasets, to distill scientific insights that might be challenging with traditional methods. Such applications, however, largely focus on gaining insights via big data and/or big computation, while neglecting the valuable chemical prior knowledge dwelling in chemists' minds. In this paper, we introduce an Electrochemistry-Informed Neural Network (ECINN) by explicitly embedding electrochemistry priors including the Butler-Volmer (BV), Nernst and diffusion equations on the backbone of neural networks for multi-task discovery of electrochemistry parameters. We applied the ECINN to voltammetry experiments of F e 2 + / F e 3 + ${{\rm F}{{\rm e}}^{2+}/{\rm F}{{\rm e}}^{3+}}$ and R u N H 3 6 2 + / R u N H 3 6 3 + ${{\rm R}{\rm u}{\left({\rm N}{{\rm H}}_{3}\right)}_{6}^{2+{\rm \ }}/{\rm R}{\rm u}{\left({\rm N}{{\rm H}}_{3}\right)}_{6}^{3+{\rm \ }}}$ redox couples to discover electrode kinetics and mass transport parameters. Notably, ECINN seamlessly integrated mass transport with BV to analyze the entire voltammogram to infer transfer coefficients directly, so offering a new approach to Tafel analysis by outdating various mass transport correction methods. In addition, ECINN can help discover the nature of electron transfer and is shown to refute incorrect physics if imposed. This work encourages chemists to embed their domain knowledge into machine learning models to start a new paradigm of chemistry-informed machine learning for better accountability, interpretability, and generalization.

Rotating Disk Electrodes beyond the Levich Approximation: Physics-Informed Neural Networks Reveal and Quantify Edge Effects.

Physics-informed neural networks are used to characterize the mass transport to the rotating disk electrode (RDE), the most widely employed hydrodynamic electrode in electroanalysis. The PINN approach was first quantitatively verified via 1D simulations under the Levich approximation for cyclic voltammetry and chronoamperometry, allowing comparison of the results with finite difference simulations and analytical equations. However, the Levich approximation is only accurate for high Schmidt numbers (Sc > 1000). The PINN approach allowed consideration of smaller Sc, achieving an analytical level of accuracy (error <0.1%) comparable with independent numerical evaluation and confirming that the errors in the Levich equation can be as high as 3% when Sc = 1000 for rapidly diffusing species in aqueous solution. Entirely novel, the PINNs permit the solution of the 2D diffusion equation under cylindrical geometry incorporating radial diffusion and reveal the rotating disk electrode edge effect as a consequence of the nonuniform accessibility of the disc with greater currents flowing near the extremities. The contribution to the total current is quantified as a function of the rotation speed, disk radius, and analyte diffusion coefficient. The success in extending the theory for the rotating disk electrode beyond the Levich equation shows that PINNs can be an easier and more powerful substitute for conventional methods, both analytical and simulation based.

Reversible Cyclic Voltammetry and Non-Unity Stoichiometry: The Ag/AgBr/Br- Redox Couple.

The voltammetry of electrochemically reversible couples in which a soluble reactant is converted into an insoluble product is investigated computationally via simulation and, in the context of the Ag/AgBr/Br-redox couple, experimentally. The voltammetric waveshape is characterized and, when analyzed via apparent transfer coefficient analysis, shown to give rise to apparent transfer coefficients very considerably in excess of unity, leading to the generic insight for the characterization of electrode reactions involving solution and solid phase reactants.

Field trial of concurrent co-cable and co-trench optical fiber online identification based on ensemble learning.

The co-route optical fibers, comprising both co-cable and co-trench fibers, pose a significant potential risk to network service quality assurance by operators. They are incapable of achieving high-precision recognition and visual state management. In this study, we gathered both static and dynamic optical fiber data using a linewidth tunable light source (LTLS) and introduced a multimodal detection architecture that applies ensemble learning to the collected data. This constitutes what we believe to be the first field trial of concurrent recognition of optical fibers found both in co-cables and co-trenches. To identify co-cable fibers, we employed a double-layer cascaded Random Forest (DLC-RF) model based on the static features of fibers. For co-trench fiber, the dynamic characteristics of fiber vibrations are utilized in combination with multiple independent curve similarity contrast learners for classifying tasks. The proposed architecture is capable of automatically detecting the condition of the optical fiber and actively identifying the same routing segment within the network, eliminating the need for human intervention and enabling the visualization of passive optical fiber resources. Finally, after rigorous testing and validation across 11 sites in a typical urban area, including aggregation and backbone scenarios within the operator's live network environments, we have confirmed that the solution's ability to identify co-routes is accurate, exceeding 95%. This provides strong empirical evidence of its effectiveness.

Trends and prediction in the incidence rate of hepatitis C in Shandong Province in China from 2004 to 2030.

BACKGROUND: Hepatitis C threatens human health and brings a heavy economic burden. Shandong Province is the second most populous province in China and has uneven regional economic development. Therefore, we analyzed the incidence rate trend and regional differences of hepatitis C in Shandong Province from 2004 to 2021. METHODS: The monthly and annual incidence rates of hepatitis C in Shandong Province from 2022 to 2030 were predicted by fitting Autoregressive Integrated Moving Average model (ARIMA), Long Short-Term Memory (LSTM) and ARIMA-LSTM combined model. RESULTS: From 2004 to 2021, annual new cases of hepatitis C in Shandong Province increased from 635 to 5834, with a total of 61,707 cases. The incidence rate increased from 0.69/100 thousand in 2004 to 6.40/100 thousand in 2019, with a slight decrease in 2020 and 2021. The average annual incidence rate was 3.47/100 thousand. In terms of regional distribution, the hepatitis C incidence rate in Shandong Province was generally high in the west and low in the east. It is estimated that the hepatitis C incidence rate in Shandong Province will be 9.21 per 100 thousand in 2030. CONCLUSION: The hepatitis C incidence rate in Shandong Province showed an increasing trend from 2004 to 2019 and a decreasing trend in 2020 and 2021. Significant regional variations in incidence rate existed. An upward trend in incidence rate is predicted from 2022 to 2030. It is necessary to strengthen the prevention and control of hepatitis C to achieve the goal of eliminating viral hepatitis by 2030.

Phosphatase and tensin homologue determine inflammatory status by differentially regulating the expression of Akt1 and Akt2 in macrophage alternative polarization of periodontitis.

AIM: Macrophages are closely involved in periodontitis. However, the molecular mechanism by which macrophages influence periodontitis is not well understood. We investigated the effects of phosphatase and tensin homologue (PTEN) on macrophage polarization, the underlying mechanism and the regulatory roles in periodontium regeneration. MATERIALS AND METHODS: PTEN expression in periodontitis macrophages was detected ex vivo. The effects of PTEN on macrophage polarization and the underlying mechanisms were investigated in vitro. We also analysed the ability of PTEN inhibitors to repair periodontitis in vivo in a ligature-induced mouse model of periodontitis. RESULTS: Macrophage PTEN expression in periodontitis patients was significantly higher than that of controls. PTEN inhibition in macrophages induced alternative macrophage polarization, whereas PTEN overexpression facilitated classical polarization. PTEN inhibition facilitated activation of Akt1 while inhibiting expression of Akt2. Furthermore, Akt2 overexpression could rescue the effects of PTEN inhibition on NF-κB. Treatment with a PTEN inhibitor significantly attenuated the local inflammatory status and prevented alveolar bone resorption in the mouse model. CONCLUSIONS: Our findings suggest that PTEN inhibition could induce alternative macrophage polarization by differentially regulating Akt1 and Akt2. This also changed a pro-inflammatory microenvironment to an anti-inflammatory environment by subsequently regulating the expression of NF-κB, thereby attenuating inflammatory alveolar bone resorption induced by ligature.

Prostate cancer-derived small extracellular vesicle proteins: the hope in diagnosis, prognosis, and therapeutics.

Current diagnostic tools for prostate cancer (PCa) diagnosis and risk stratification are insufficient. The hidden onset and poor efficacy of traditional therapies against metastatic PCa make this disease a heavy burden in global men's health. Prostate cancer-derived extracellular vesicles (PCDEVs) have garnered attention in recent years due to their important role in communications in tumor microenvironment. Recent advancements have demonstrated PCDEVs proteins play an important role in PCa invasion, progression, metastasis, therapeutic resistance, and immune escape. In this review, we briefly discuss the applications of sEV proteins in PCa diagnosis and prognosis in liquid biopsy, focus on the roles of the PCa-derived small EVs (sEVs) proteins in tumor microenvironment associated with cancer progression, and explore the therapeutic potential of sEV proteins applied for future metastatic PCa therapy.

Lower serum Klotho level and higher systemic immune-inflammation index: an inverse correlation.

OBJECTIVES: Klotho, an anti-aging protein, has been identified to control tissue inflammatory responses. The objective of this research is to determine the linkage between soluble Klotho (S-Klotho) level and systemic immune-inflammation index (SII). METHODS: Eligible participants with complete information of S-Klotho level and SII were selected from the National Health and Nutrition Examination Surveys (NHANES). Subsequently, weighted multivariate linear regression and subgroup analysis were carried out to evaluate the association. RESULTS: Totally, 11,108 adults with complete data on S-Klotho level, SII and other important covariates were included in final analysis. Multivariate liner regression revealed that high level of S-Klotho was associated with low level of SII after multivariate adjustments (ß=-0.08, 95%CI:-0.10- -0.05, P < 0.01). When classifying S-Klotho into tertiles, participants in S-Klotho tertile 3 (Q3) showed a decrease in SII level compared with those in the lowest tertile (Q1) (ß=-45.44, 95%CI:-64.41- -26.47, P < 0.01 ). The negative associations remained significant regardless of age and gender, and varied depending on smoking status and BMI subgroups. CONCLUSION: S-Klotho level was negatively related to SII after controlling for covariates. Further studies need to validate current findings and explore the fundamental mechanisms.

Enhancing efficiency and capacity of telehealth services with intelligent triage: a bidirectional LSTM neural network model employing character embedding.

BACKGROUND: The widespread adoption of telehealth services necessitates accurate online department selection based on patient medical records, a task requiring significant medical knowledge. Incorrect triage results in considerable time wastage for both patients and medical professionals. To address this, we propose an intelligent triage model based on a Bidirectional Long Short-Term Memory (Bi-LSTM) neural network with character embedding to enhance the efficiency and capacity of telehealth services. METHODS: We gathered a 1.3 GB medical dataset comprising 200,000 records, each including medical history, physical examination data, and other pertinent information found on the electronic medical record homepage. Following data preprocessing, a clinical corpus was established to train character embeddings with a medical context. These character embeddings were then utilized to extract features from patient chief  complaints, and a 2-layer Bi-LSTM neural network was trained to categorize these complaints, enabling intelligent triage for telehealth services. RESULTS: 60,000 chief complaint-department data pairs were extracted from clinical corpus and divided into the training, validation, and test sets of 42,000, 9,000, and 9,000, respectively. The character embedding based Bi-LSTM neural network achieved a macro-precision of 85.50% and an F1 score of 85.45%. CONCLUSION: The telehealth triage model developed in this study demonstrates strong implementation outcomes and significantly improves the efficiency and capacity of telehealth services. Character embedding outperforms word embedding, and future work will incorporate additional features such as patient age and gender into the chief complaint feature to future enhance model performance.