Establishment of replication-competent vesicular stomatitis virus recapitulating SADS-CoV entry.

Zoonotic coronaviruses pose a continuous threat to human health, with newly identified bat-borne viruses like swine acute diarrhea syndrome coronavirus (SADS-CoV) causing high mortality in piglets. In vitro studies indicate that SADS-CoV can infect cell lines from diverse species, including humans, highlighting its potential risk to human health. However, the lack of tools to study viral entry, along with the absence of vaccines or antiviral therapies, perpetuates this threat. To address this, we engineered an infectious molecular clone of Vesicular Stomatitis Virus (VSV), replacing its native glycoprotein (G) with SADS-CoV spike (S) and inserting a Venus reporter at the 3' leader region to generate a replication-competent rVSV-Venus-SADS S virus. Serial passages of rVSV-Venus-SADS S led to the identification of an 11-amino-acid truncation in the cytoplasmic tail of the S protein, which allowed more efficient viral propagation due to increased cell membrane anchoring of the S protein. The S protein was integrated into rVSV-Venus-SADS SΔ11 particles, susceptible to neutralization by sera from SADS-CoV S1 protein-immunized rabbits. Additionally, we found that TMPRSS2 promotes SADS-CoV spike-mediated cell entry. Furthermore, we assessed the serum-neutralizing ability of mice vaccinated with rVSV-Venus-SADS SΔ11 using a prime-boost immunization strategy, revealing effective neutralizing antibodies against SADS-CoV infection. In conclusion, we have developed a safe and practical tool for studying SADS-CoV entry and exploring the potential of a recombinant VSV-vectored SADS-CoV vaccine.IMPORTANCEZoonotic coronaviruses, like swine acute diarrhea syndrome coronavirus (SADS-CoV), pose a continual threat to human and animal health. To combat this, we engineered a safe and efficient tool by modifying the Vesicular Stomatitis Virus (VSV), creating a replication-competent rVSV-Venus-SADS S virus. Through serial passages, we optimized the virus for enhanced membrane anchoring, a key factor in viral propagation. This modified virus, rVSV-Venus-SADS SΔ11, proved susceptible to neutralization, opening avenues for potential vaccines. Additionally, our study revealed the role of TMPRSS2 in SADS-CoV entry. Mice vaccinated with rVSV-Venus-SADS SΔ11 developed potent neutralizing antibodies against SADS-CoV. In conclusion, our work presents a secure and practical tool for studying SADS-CoV entry and explores the promise of a recombinant VSV-vectored SADS-CoV vaccine.

Adaptive cascaded transformer U-Net for MRI brain tumor segmentation.

OBJECTIVE: Brain tumor segmentation on magnetic resonance imaging (MRI) plays an important role in assisting the diagnosis and treatment of cancer patients. Recently, cascaded U-Net models have achieved excellent performance via conducting coarse-to-fine segmentation of MRI brain tumors. However, they still suffer from obvious global and local differences among various brain tumors, which are difficult to solve with conventional convolutions. APPROACH: To address the issue, this work proposes a novel Adaptive Cascaded Transformer U-Net (ACTransU-Net) for MRI brain tumor segmentation, which simultaneously integrates Transformer and dynamic convolution into a single cascaded U-Net architecture to adaptively capture global information and local details of brain tumors. ACTransU-Net first cascades two 3D U-Nets into a two-stage network to segment brain tumors from coarse to fine. Subsequently, it integrates omni-dimensional dynamic convolution modules into the second-stage shallow encoder and decoder, thereby enhancing the local detail representation of various brain tumors through dynamically adjusting convolution kernel parameters. Moreover, 3D Swin-Transformer modules are introduced into the second-stage deep encoder and decoder to capture image long-range dependencies, which helps adapt the global representation of brain tumors. MAIN RESULTS: Extensive experiment results evaluated on the public BraTS 2020 and BraTS 2021 brain tumor datasets demonstrate the effectiveness of ACTransU-Net, with average DSC of 84.96% and 91.37%, and HD95 of 10.81 mm and 7.31 mm, proving competitiveness with the state-of-the-art methods. SIGNIFICANCE: The proposed method focuses on adaptively capturing both global information and local details of brain tumors, aiding physicians in their accurate diagnosis. Additionally, it has the potential to extend ACTransU-Net for segmenting other types of lesions. The source code is available at: https: //github.com/chenbn266/ACTransUnet.

Application of ionic liquid ultrasound-assisted extraction (IL-UAE) of lycopene from guava (Psidium guajava L.) by response surface methodology and artificial neural network-genetic algorithm.

Lycopene-rich guava (Psidium guajava L.) exhibits significant economic potential as a functional food ingredient, making it highly valuable for the pharmaceutical and agro-food industries. However, there is a need to enhance the extraction methods of lycopene to fully exploit its beneficial uses. In this study, we evaluated various ionic liquids to identify the most effective one for extracting lycopene from guava. Among thirteen ionic liquids with varying carbon chains or anions, 1-butyl-3-methylimidazolium chloride demonstrated the highest productivity. Subsequently, a single-factor experiment was employed to test the impact of several parameters on the efficiency of lycopene extraction using this selected ionic liquid. These parameters included extraction time, ultrasonic power, liquid-solid ratio, concentration of the ionic liquid, as well as material particle size. Moreover, models of artificial neural networks using genetic algorithms (ANN-GA) and response surface methodology (RSM) were employed to comprehensively assess the first four key parameters. The optimized conditions for ionic liquid ultrasound-assisted extraction (IL-UAE) were determined as follows: 33 min of extraction time, 225 W of ultrasonic power, 22 mL/g of liquid-solid ratio, 3.0 mol/L of IL concentration, and extraction cycles of three. Under these conditions, lycopene production reached an impressive yield of 9.35 ± 0.36 mg/g while offering advantages such as high efficiency, time savings, preservation benefits, and most importantly environmental friendliness.

scMoresDB: A comprehensive database of single-cell multi-omics data for human respiratory system.

The human respiratory system is a complex and important system that can suffer a variety of diseases. Single-cell sequencing technologies, applied in many respiratory disease studies, have enhanced our ability in characterizing molecular and phenotypic features at a single-cell resolution. The exponentially increasing data from these studies have consequently led to difficulties in data sharing and analysis. Here, we present scMoresDB, a single-cell multi-omics database platform with extensive omics types tailored for human respiratory diseases. scMoresDB re-analyzes single-cell multi-omics datasets, providing a user-friendly interface with cross-omics search capabilities, interactive visualizations, and analytical tools for comprehensive data sharing and integrative analysis. Our example applications highlight the potential significance of BSG receptor in SARS-CoV-2 infection as well as the involvement of HHIP and TGFB2 in the development and progression of chronic obstructive pulmonary disease. scMoresDB significantly increases accessibility and utility of single-cell data relevant to human respiratory system and associated diseases.

Bibliometric analysis: Hot spots and frontiers in acupuncture treatment of cerebral infarction.

OBJECTIVE: CiteSpace6.1.R2 is used to analyze the research status of acupuncture in the treatment of cerebral infarction, and to find relevant hot spots and frontiers. METHODS: The researchers searched the Web of Science Core Collection database. The search date is from the establishment of the database to August 31, 2023. The search terms and expressions are: ("Cerebral Infarction" OR "Ischemic stroke") AND ("Acupuncture" OR "fire needle"). The researchers used CiteSpace software to draw a knowledge map to explore the hot spots and frontiers of acupuncture in treating cerebral infarction. RESULTS: We screened 414 articles in the Web of Science Core Collection database. China is the country with the largest number of publications, with a total of 343 papers published. China's institutions cooperate most closely, and cooperation between countries is less and more scattered. The author with the highest number of published articles is Chen L, with a total of 31 published articles. The research focus mainly revolves around the mechanism of acupuncture treatment of cerebral infarction and electroacupuncture treatment of cerebral infarction. Among them, acupuncture treatment of cerebral infarction is the most. CONCLUSION: According to CiteSpace's analysis results, China is at the forefront of this research field, while other countries have less research in this field and little cooperation among countries. At present, the mainstream aspect of research is the mechanism of acupuncture treatment of cerebral infarction electroacupuncture and acupuncture points. Therefore, in future research, we should pay more attention to the treatment of cerebral infarction mechanism of acupuncture, problems with the type of acupuncture used, and acupuncture points.

Rational design of NiO/Ti3C2Tx nanocomposites with enhanced triethylamine sensing performance.

MXenes with excellent conductivity and abundant surface functional groups have displayed great advantages as platforms for sensing materials. NiO also has drawn much attention for gas detection due to its unique merits of excellent catalytic activity. Herein, NiO nanoparticles are incorporated with multilayer Ti3C2Tx-MXene to develop excellent triethylamine sensors. Due to the larger specific surface area and formed p-p heterojunctions, the response of the NiO/Ti3C2Tx gas sensor is endowed with a response value of 950% to 50 ppm triethylamine gas and is much higher than that of the pristine NiO sensor. Moreover, the NiO/Ti3C2Tx sensor displays a fast response time of 8 s (50 ppm triethylamine), excellent reproducibility, and reliable long-term stability. This study proves that NiO/Ti3C2Tx sensors have potential for the effective detection of triethylamine gas.

Fully Transient 3D Origami Paper-Based Ammonia Gas Sensor Obtained by Facile MXene Spray Coating.

Developing high-performance chemiresistive gas sensors with mechanical compliance for environmental or health-related biomarker monitoring has recently drawn increasing research attention. Among them, two-dimensional MXene materials hold great potential for room-temperature hazardous gas (e.g., NH3) monitoring regardless of the complicated fabrication process, insufficient 2D/3D flexibilities, and poor environmental sustainability. Herein, a Ti3C2Tx MXene/gelatin ink was developed for patterning electrodes through a facile spray coating. Particularly, the patterned Ti3C2Tx-based coating exhibited good adhesion on the paper substrate against repeated peeling-off and excellent mechanical flexibility against 1000 cyclic stretching. The porous morphology of the coating facilitated the NH3 sensing ability. As a result, the 2D kirigami-shaped NH3 sensor exhibited a good response of 7% to 50 ppm of NH3 with detectable concentrations ranging from 5-500 ppm, decent selectivity over interferences, etc., which could be well-maintained even at 50% stretched state. In addition, with the help of mechanically guided compressive buckling, 3D mesostructured MXene origamis could be obtained, holding promise for detecting the coming direction and height distribution of hazardous gas, e.g., the NH3. More importantly, the as-fabricated MXene/gelatin origami paper could be fully degraded in PBS/H2O2/cellulase solution within 19 days, demonstrating its potential as a high-performance, shape morphable, and environmentally friendly wearable gas sensor.

Preparation of a high-performance H2S gas sensor based on CuO/Co3O4composite derived from bimetallic MOF.

The bimetallic metal-organic frameworks (MOFs), Cu/Co-MOF, was synthesized through a solvothermal method and calcined to obtain CuO/Co3O4composites. By adjusting the molar ratio between Cu and Co ions, a composite material of CuO/Co3O4(Cu:Co = 1:1) was developed and showed excellent sensing capabilities, and the response reached as high as 196.3 for 10 ppm H2S detection. Furthermore, the optimal operating temperature as low as 40 °C was found. In comparison with the sensors prepared by pristine CuO and pristine Co3O4, the sensor based on CuO/Co3O4composite exhibited a significant response. Additionally, the sensor can detect H2S gas down to 300 ppb. The gas sensing mechanism is discussed in depth from the perspective of p-p heterojunction formation between the p-type CuO and p-type Co3O4. The as-prepared CuO/Co3O4composite-based sensor is expected to find practical application in the low-power monitoring of H2S.

Drug recommendation for optimization on treatment outcome for MDR/RR-TB based on a multi-center, large scale, retrospective cohort study in China.

OBJECTIVE: With the change in drug-resistant pattern, MDR/RR-TB was faced with underlying changes in regimens. A multi-center, large-scale, retrospective study performed aims to provide a recommendation of drug selection on optimization of outcome for the patients. METHOD: The study was conducted in six TB-specialized hospitals in China. Patients were included from 2018-2021 and followed up throughout the treatment. Using a multivarariable and propensity score-matched logistic regression analysis, we evaluated associations between outcomes and drug use, as well as clinical characteritics. RESULTS: Of 3112 patients, 74.29% had treatment sucess, 14.52% lost to follow-up, 9.67% failure, and 1.51% died. Treatment success was positively associated with Bedaquiline(Bdq), Linezolid(Lzd), and Cycloserin(Cs). Capreomycin(Cm) increased the risk of unfavorable outcomes. other drugs such as Amikacin(Amk) and clofazimine had no significant effect on outcomes. If isolates were susceptible to fluoroquinolones(FQs), FQs could decrease the risk of unfavorable outcomes. CONCLUSIONS: The recommendation order for the treatment of MDR/RR-TB is Bdq, Lzd, and Cs. FQs were decreased in use intensity. Injection drugs, whether Amk or Cm, are not recommended.

Effects of altitude on thyroid disorders according to Chinese three-rung, ladder-like topography: national cross-sectional study.

BACKGROUND: Chinese topography appears a three-rung ladder-like distribution of decreasing elevation from northwest to southeast, which is divided by two sloping edges. Previous studies have reported that prevalence of thyroid diseases differed by altitude, and geographical factors were associated with thyroid disorders. To explore the association between three-rung ladder-like regions and thyroid disorders according to unique Chinese topographic features, we conducted an epidemiological cross-sectional study from 2015-2017 that covered all 31 mainland Chinese provinces. METHODS: A total of 78,470 participants aged ≥ 18 years from a nationally representative cross-sectional study were included. Serum thyroid peroxidase antibody, thyroglobulin antibody, and thyroid-stimulating hormone levels; urine iodine concentration; and thyroid volume were measured. The three-rung ladder-like distribution of decreasing elevation from northwest to southeast in China was categorized into three topographic groups according to elevation: first ladder, > 3000 m above sea level; second ladder, descending from 3000-500 m; and third ladder, descending from 500 m to sea level. The third ladder was further divided into groups A (500-100 m) and B (< 100 m). Associations between geographic factors and thyroid disorders were assessed using linear and binary logistic regression analyses. RESULTS: Participants in the first ladder group were associated with lower thyroid peroxidase (ß = -4.69; P = 0.00), thyroglobulin antibody levels (ß = -11.08; P = 0.01), and the largest thyroid volume (ß = 1.74; P = 0.00), compared with the other groups. The second ladder group was associated with autoimmune thyroiditis (odds ratio = 1.30, 95% confidence interval [1.18-1.43]) and subclinical hypothyroidism (odds ratio = 0.61, 95%confidence interval [0.57-0.66]) (P < 0.05) compared with the first ladder group. Group A (third ladder) (500-100 m) was associated with thyroid nodules and subclinical hypothyroidism (P < 0.05). Furthermore, group B (< 100 m) was positively associated with autoimmune thyroiditis, thyroid peroxidase and thyroglobulin antibody positivity, and negatively associated with overt hypothyroidism, subclinical hypothyroidism, and goiter compared with the first ladder group(P < 0.05). CONCLUSION: We are the first to investigate the association between different ladder regions and thyroid disorders according to unique Chinese topographic features. The prevalence of thyroid disorders varied among the three-rung ladder-like topography groups in China, with the exception of overt hyperthyroidism.

Effects of iodine intake on gut microbiota and gut metabolites in Hashimoto thyroiditis-diseased humans and mice.

Hashimoto thyroiditis (HT) is an organ-specific autoimmune disease linked to iodine intake. Emerging evidence highlights the gut microbiota's role in HT pathogenesis via the microbiota-gut-thyroid axis. However, the process through which iodine intake modifies the microbiota and triggers HT remains unclear. This study examines how iodine affects gut dysbiosis and HT, recruiting 23 patients with HT and 25 healthy individuals to assess gut microbiota composition and metabolic features. Furthermore, we establish a spontaneously developed thyroiditis mouse model using NOD.H-2h4 mice highlighting the influence of iodine intake on HT progression. The butanoate metabolism significantly differs between these two groups according to the enrichment results, and butyric acid is significantly decreased in patients with HT compared with those in healthy individuals. Gut dysbiosis, driven by excessive iodine intake, disrupts TH17/Treg balance by reducing butyric acid. In summary, iodine intake alters intestinal microbiota composition and metabolic changes influencing the microbiota-gut-thyroid axis.

Insights into the roles of biochar pores toward alleviating antibiotic resistance genes accumulation in biofiltration systems.

Biofiltration systems would harbor and spread various antibiotic resistance genes (ARGs) when treating antibiotic micro-pollution, constituting a potential ecological risk. This study aimed to investigate the effects of biochar pores on ARG emergence and related microbial response mechanisms in bench-scale biofiltration systems. Results showed that biochar pores effectively reduced the absolute copies of the corresponding ARGs sul1 and sul2 by 54.1% by lowering the sorbed-SMX's bioavailability compared to non-porous anthracite. An investigation of antimicrobial resistomes revealed a considerable decrease in the abundance and diversity of ARGs and mobile gene elements. Metagenomic and metaproteomic analysis demonstrated that biochar pores induced the changeover of microbial defense strategy against SMX from blocking SMX uptake by EPS absorbing to SMX biotransformation. Microbial SOS response, antibiotic efflux pump, EPS secretion, and biofilm formation were decreased. Functions related to SMX biotransformation, such as sadABC-mediated transformation, xenobiotics degradation, and metabolism, were significantly promoted.

FastCellpose: A Fast and Accurate Deep-Learning Framework for Segmentation of All Glomeruli in Mouse Whole-Kidney Microscopic Optical Images.

Automated evaluation of all glomeruli throughout the whole kidney is essential for the comprehensive study of kidney function as well as understanding the mechanisms of kidney disease and development. The emerging large-volume microscopic optical imaging techniques allow for the acquisition of mouse whole-kidney 3D datasets at a high resolution. However, fast and accurate analysis of massive imaging data remains a challenge. Here, we propose a deep learning-based segmentation method called FastCellpose to efficiently segment all glomeruli in whole mouse kidneys. Our framework is based on Cellpose, with comprehensive optimization in network architecture and the mask reconstruction process. By means of visual and quantitative analysis, we demonstrate that FastCellpose can achieve superior segmentation performance compared to other state-of-the-art cellular segmentation methods, and the processing speed was 12-fold higher than before. Based on this high-performance framework, we quantitatively analyzed the development changes of mouse glomeruli from birth to maturity, which is promising in terms of providing new insights for research on kidney development and function.

MAU-Net: Mixed attention U-Net for MRI brain tumor segmentation.

Computer-aided brain tumor segmentation using magnetic resonance imaging (MRI) is of great significance for the clinical diagnosis and treatment of patients. Recently, U-Net has received widespread attention as a milestone in automatic brain tumor segmentation. Following its merits and motivated by the success of the attention mechanism, this work proposed a novel mixed attention U-Net model, i.e., MAU-Net, which integrated the spatial-channel attention and self-attention into a single U-Net architecture for MRI brain tumor segmentation. Specifically, MAU-Net embeds Shuffle Attention using spatial-channel attention after each convolutional block in the encoder stage to enhance local details of brain tumor images. Meanwhile, considering the superior capability of self-attention in modeling long-distance dependencies, an enhanced Transformer module is introduced at the bottleneck to improve the interactive learning ability of global information of brain tumor images. MAU-Net achieves enhancing tumor, whole tumor and tumor core segmentation Dice values of 77.88/77.47, 90.15/90.00 and 81.09/81.63% on the brain tumor segmentation (BraTS) 2019/2020 validation datasets, and it outperforms the baseline by 1.15 and 0.93% on average, respectively. Besides, MAU-Net also demonstrates good competitiveness compared with representative methods.

Development and validation of age-specific risk prediction models for primary ovarian insufficiency in long-term survivors of childhood cancer: a report from the Childhood Cancer Survivor Study and St Jude Lifetime Cohort.

BACKGROUND: Female survivors of childhood cancer are at risk for primary ovarian insufficiency (POI), defined as the cessation of gonadal function before the age of 40 years. We aimed to develop and validate models to predict age-specific POI risk among long-term survivors of childhood cancer. METHODS: To develop models to predict age-specific POI risk for the ages of 21-40 years, we used data from the Childhood Cancer Survivor Study (CCSS). Female survivors aged 18 years or older at their latest follow-up, with self-reported menstrual history information and free of subsequent malignant neoplasms within 5 years of diagnosis, were included. We evaluated models that used algorithms based on statistical or machine learning to consider all predictors, including cancer treatments. Cross-validated prediction performance metrics (eg, area under the receiver operating characteristic curve [AUROC]) were compared to select the best-performing models. For external validation of the models, we used data from 5-year survivors in the St Jude Lifetime Cohort (SJLIFE) with ovarian status clinically ascertained using hormone measurements (menopause defined by follicle stimulating hormone >30 mIU/mL and oestradiol <17 pg/mL) and medical chart or questionnaire review. We also evaluated an SJLIFE-based polygenic risk score for POI among 1985 CCSS survivors with genotype data available. FINDINGS: 7891 female CCSS survivors (922 with POI) were included in the development of the POI risk prediction model, and 1349 female SJLIFE survivors (101 with POI) were included in the validation study. Median follow-up from cancer diagnosis was 23·7 years (IQR 18·3-30·0) in CCSS and 15·1 years (10·4-22·9) in SJLIFE. Between the ages of 21 and 40 years, POI prevalence increased from 7·9% (95% CI 7·3-8·5) to 18·6% (17·3-20·0) in CCSS and 7·3% (5·8-8·9) to 14·9% (11·6-19·1) in SJLIFE. Age-specific logistic regression models considering ovarian radiation dosimetry or prescribed pelvic and abdominal radiation dose, along with individual chemotherapy predictors, performed well in CCSS. In the SJLIFE validation, the prescribed radiation dose model performed well (AUROC 0·88-0·95), as did a simpler model that considered any exposures to pelvic or abdominal radiotherapy or alkylators (0·82-0·90). Addition of the polygenic risk predictor significantly improved the average positive predictive value (from 0·76 [95% CI 0·63-0·89] to 0·87 [0·80-0·94]; p=0·029) among CCSS survivors treated with ovarian radiation and chemotherapy. INTERPRETATION: POI risk prediction models using treatment information showed robust prediction performance in adult survivors of childhood cancer. FUNDING: Canadian Institutes of Health Research, US National Cancer Institute.

Preparation of a Stable Superhydrophobic Mortar Surface Using a One-Step Method.

Research efforts have intensified on developing superhydrophobic surfaces on concrete structures to limit the damage caused by the natural porosity and hydrophilicity of cementitious materials. However, the feasibility idea is impeded by the complex preparation process and weak adhesion/stability performance. Therefore, superhydrophobic coatings were rapidly prepared on mortar surfaces by a straightforward and effective one-step method using zinc oxide (ZnO) modified with stearic acid and epoxy resin. The microstructure, physical/chemical properties, hydrophobic properties, and stability of the coatings were systematically investigated. The experimental results showed that the water contact angle of the samples reached a maximum value of 164.2° and a sliding angle of 4.6° when the stearic acid content was 0.5 g. The water absorption of the coated superhydrophobic mortar was reduced by approximately 61% compared to that of ordinary mortar, and neither particulate pollutants nor liquid pollutants could contaminate the superhydrophobic mortar. The coating maintained a superhydrophobic state and exhibited good physical durability after sandpaper abrasion, tape peeling, and high-temperature resistance tests. The water cluster diffusion coefficient on surface of the ordinary coating was 0.1645 × 10-4 and 0.0328 × 10-4 cm2/s on surface of the modified coating after molecular dynamics simulation.

Multi-omic analysis characterizes molecular susceptibility of receptors to SARS-CoV-2 spike protein.

In the post COVID-19 era, new SARS-CoV-2 variant strains may continue emerging and long COVID is poised to be another public health challenge. Deciphering the molecular susceptibility of receptors to SARS-CoV-2 spike protein is critical for understanding the immune responses in COVID-19 and the rationale of multi-organ injuries. Currently, such systematic exploration remains limited. Here, we conduct multi-omic analysis of protein binding affinities, transcriptomic expressions, and single-cell atlases to characterize the molecular susceptibility of receptors to SARS-CoV-2 spike protein. Initial affinity analysis explains the domination of delta and omicron variants and demonstrates the strongest affinities between BSG (CD147) receptor and most variants. Further transcriptomic data analysis on 4100 experimental samples and single-cell atlases of 1.4 million cells suggest the potential involvement of BSG in multi-organ injuries and long COVID, and explain the high prevalence of COVID-19 in elders as well as the different risks for patients with underlying diseases. Correlation analysis validated moderate associations between BSG and viral RNA abundance in multiple cell types. Moreover, similar patterns were observed in primates and validated in proteomic expressions. Overall, our findings implicate important therapeutic targets for the development of receptor-specific vaccines and drugs for COVID-19.

Negative enrichment strategy combined with site-specific derivatization for the C-terminomics.

Protein C-termini containing valuable biological information plays a vital role in various physiological processes, such as protein localization, protein recognition, and signal transduction in organisms. However, C-terminal peptide identification is still challenging due to their low abundance and similar physicochemical properties to other digested peptides. Herein, we developed a simple and mild strategy for the enrichment of C-terminal peptides that incorporates selectively 2-pyridinecarbaldehyde (2-PCA) derivatization of α-amine with negative enrichment by NHS resin. Two synthesized peptides were utilized to evaluate the efficiency of 2-PCA derivatization and optimize the coupling conditions of NHS resin. The feasibility of the method was further validated by enriching the C-terminus of the bovine serum albumin (BSA). Finally, this method was successfully applied to the C-terminus analysis of mouse brain tissue, identifying 404 protein C-termini with physicochemical properties unbiasedly. Additionally, the GO and KEGG analyses revealed that these identified proteins are crucial for proper brain function. In summary, our proposed method is effective and has the potential to facilitate comprehensive C-terminal analysis of proteins. SIGNIFICANCE: Effective enrichment methods are essential for the identification of the proteins C-terminus. In this study, a mild and simple method for negative C-terminal enrichment combined with site-specific derivatization was developed. The enrichment process was simplified and minimized sample loss simultaneously, using 2-PCA derivatization which has high α-amino specificity. Up to 346C-terminal proteins were identified in mouse brain tissue unbiasedly and reliably. This approach has the potential to facilitate comprehensive analysis of protein C-termini in a variety of biological contexts.

The Association of Surrogates of Insulin Resistance with Hyperuricemia among Middle-Aged and Older Individuals: A Population-Based Nationwide Cohort Study.

The triglyceride-glucose (TyG) index, triglyceride-to-high-density-lipoprotein-cholesterol (TG/HDL-C) ratio, metabolic score for insulin resistance (METS-IR) and TyG with body mass index (TyG-BMI) have been proposed as indicators of insulin resistance (IR). This study aimed to explore the association between these IR surrogates and their longitudinal variation with the development of hyperuricemia in a middle-aged and older Chinese population. Data from the China Health and Retirement Longitudinal Study (CHARLS) was used to identify 5269 participants aged ≥45 years. Logistic regression was used to assess the effect of IR surrogates and their variations on the risk of hyperuricemia. After four years of follow-up, 517 (9.81%) participants developed incident hyperuricemia. Increased baseline values of TyG, TG/HDL, METS-IR, and TyG-BMI were all significantly associated with higher risks of hyperuricemia. Compared to individuals with maintained low levels of IR surrogates, those with low-to-high and maintained high variation patterns had a significantly higher risk of hyperuricemia. These four IR surrogates have comparable predictive ability for hyperuricemia. This study provides evidence of the associations between IR and hyperuricemia. Early intervention among middle-aged and elderly Chinese individuals with high IR levels may effectively reduce the burden of hyperuricemia.

Rapid and High-Sensitive Phosphoproteomics Elucidated the Spatial Dynamics of the Mouse Brain.

Recent developments in phosphoproteomics have enabled signaling studies where over 10,000 phosphosites can be routinely identified and quantified. Yet, current analyses are limited in sample size, reproducibility, and robustness, hampering experiments that involve low-input samples such as rare cells and fine-needle aspiration biopsies. To address these challenges, we introduced a simple and rapid phosphorylation enrichment method (miniPhos) that uses a minimal amount of the sample to get enough information to decipher biological significance. The miniPhos approach completed the sample pretreatment within 4 h and high effectively collected the phosphopeptides in a single-enrichment format with an optimized enrichment process and miniaturized system. This resulted in an average of 22,000 phosphorylation peptides quantified from 100 µg of proteins and even confidently localized over 4500 phosphosites from as little as 10 µg of peptides. Further application was carried out on different layers of mouse brain micro-sections; our miniPhos method provided quantitative information on protein abundance and phosphosite regulation for the most relevant neurodegenerative diseases, cancers, and signaling pathways in the mouse brain. Surprisingly, the phosphoproteome exhibited more spatial variations than the proteome in the mouse brain. Overall, spatial dynamics of phosphosites are integrated with proteins to gain insights into crosstalk of cellular regulation at different layers, thereby facilitating a more comprehensive understanding of mouse brain development and activity.