Relationship between four insulin resistance surrogates and regression to normoglycemia from prediabetes among Chinese adults: A longitudinal Cohort Study.

PURPOSE: We aimed to investigate the association of the triglyceride glucose-body mass index(TyG-BMI), metabolic score for insulin resistance (METS-IR) with regression to normoglycaemia, and further to compare the value of the four insulin resistance(IR) related indices(TyG-BMI, METS-IR, TyG and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio) in identifying regressions to normoglycaemia from prediabetes. METHODS: A total of 15,025 patients with prediabetes from the DATA-DRYAD database were included. Cox proportional hazards regression models and restricted cubic spline functions were performed to explore the association and nonlinearity between the indices with the incidence rate of normoglycaemia. Sensitivity and subgroup analyses evaluated the robustness of our findings. RESULTS: Compared with the first quintile, TyG-BMI and METS-IR was negatively linked with the probability of regression to normoglycaemia from prediabetes, the adjusted effect size of the highest quintiles of METS-IR were the most obvious (HR:0.456,95% CI:0.4-0.519), followed by TG/HDL (HR:0.792, 95% CI:0.733-0.856), TyG-BMI (HR:0.816, 95% CI:0.73-0.911) and TyG (HR:0.841, 95% CI: 0.754-0.937) (all p for trend <0.001). A 1.0 SD increase in METS-IR induced a 43% decrease in the probability of regression to normoglycaemia, with 9.8% for TyG-BMI. There were nonlinear associations between TyG-BMI and METS-IR and outcomes, with the inflection point of the TyG-BMI being 218.2 and that of the METS-IR being 37. CONCLUSIONS: The METS-IR might be the most superior indicator among the four non-insulin indices in identifying regressions to normoglycaemia from prediabetes in clinical application. The inflection points of the METS-IR and TyG-BMI may be instructive therapeutic points for assessing the status of prediabetes in advance and making more appropriate management and health care decisions.

Dynamic changes of gut microbiota in mouse models of metabolic dysfunction-associated steatohepatitis and its transition to hepatocellular carcinoma.

Dysbiosis of gut microbiota may account for pathobiology in simple fatty liver (SFL), metabolic dysfunction-associated steatohepatitis (MASH), fibrotic progression, and transformation to MASH-associated hepatocellular carcinoma (MASH-HCC). The aim of the present study is to investigate gut dysbiosis in this progression. Fecal microbial rRNA-16S sequencing, absolute quantification, histopathologic, and biochemical tests were performed in mice fed high fat/calorie diet plus high fructose and glucose in drinking water (HFCD-HF/G) or control diet (CD) for 2, 16 weeks, or 14 months. Histopathologic examination verified an early stage of SFL, MASH, fibrotic, or MASH-HCC progression with disturbance of lipid metabolism, liver injury, and impaired gut mucosal barrier as indicated by loss of occludin in ileum mucosa. Gut dysbiosis occurred as early as 2 weeks with reduced α diversity, expansion of Kineothrix, Lactococcus, Akkermansia; and shrinkage in Bifidobacterium, Lactobacillus, etc., at a genus level. Dysbiosis was found as early as MAHS initiation, and was much more profound through the MASH-fibrotic and oncogenic progression. Moreover, the expansion of specific species, such as Lactobacillus johnsonii and Kineothrix alysoides, was confirmed by an optimized method for absolute quantification. Dynamic alterations of gut microbiota were characterized in three stages of early SFL, MASH, and its HCC transformation. The findings suggest that the extent of dysbiosis was accompanied with MASH progression and its transformation to HCC, and the shrinking or emerging of specific microbial species may account at least in part for pathologic, metabolic, and immunologic alterations in fibrogenic progression and malignant transition in the liver.

Data-driven inverse design of flexible pressure sensors.

Artificial skins or flexible pressure sensors that mimic human cutaneous mechanoreceptors transduce tactile stimuli to quantitative electrical signals. Conventional trial-and-error designs for such devices follow a forward structure-to-property routine, which is usually time-consuming and determines one possible solution in one run. Data-driven inverse design can precisely target desired functions while showing far higher productivity, however, it is still absent for flexible pressure sensors because of the difficulties in acquiring a large amount of data. Here, we report a property-to-structure inverse design of flexible pressure sensors, exhibiting a significantly greater efficiency than the conventional routine. We use a reduced-order model that analytically constrains the design scope and an iterative "jumping-selection" method together with a surrogate model that enhances data screening. As an exemplary scenario, hundreds of solutions that overcome the intrinsic signal saturation have been predicted by the inverse method, validating for a variety of material systems. The success in property design on multiple indicators demonstrates that the proposed inverse design is an efficient and powerful tool to target multifarious applications of flexible pressure sensors, which can potentially advance the fields of intelligent robots, advanced healthcare, and human-machine interfaces.

Effect of glycosylation modification on structure and properties of soy protein isolate: A review.

Soybean protein isolate (SPI) is a highly functional protein source used in various food applications, such as emulsion, gelatin, and food packaging. However, its commercial application may be limited due to its poor mechanical properties, barrier properties, and high water sensitivity. Studies have shown that modifying SPI through glycosylation can enhance its functional properties and biological activities, resulting in better application performance. This paper reviews the recent studies on glycosylation modification of SPI, including its quantification method, structural improvements, and enhancement of its functional properties, such as solubility, gelation, emulsifying, and foaming. The review also discusses how glycosylation affects the bioactivity of SPI, such as its antioxidant and antibacterial activity. This review aims to provide a reference for further research on glycosylation modification and lay a foundation for applying SPI in various fields.

A Clinical Nomogram for Predicting Overall Survival in Patients With T1/T2 Penile Squamous Cell Carcinoma.

BACKGROUND: To evaluate the overall survival (OS) and construct a nomogram to predict the OS of patients with penile squamous cell carcinoma (PSCC). METHODS: This retrospective study analyzed data of patients with PSCC from the First Affiliated Hospital of Soochow University between 2012 and 2022. R software was used to explore factors influencing OS in PSCC. Kaplan-Meier method and log-rank test were employed for OS estimation. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify these factors. A nomogram was created to identify the independent prognostic factors. The model was evaluated by concordance index, receiver operating characteristic (ROC) curves, and calibration plots. RESULTS: A total of 159 patients with T1/T2 PSCC were included in the analysis. Patients with T2/N2 stage, older age, larger tumor size, high preoperative systemic immune-inflammation index (SII), and poor preoperative nutrition had a higher incidence of poor OS. Age, T/N stage, tumor size, and SII were identified as independent prognostic indicators. A prognostic nomogram was formulated, and its predictive accuracy for estimating OS in PSCC patients was validated through ROC curves and calibration plots. CONCLUSION: The nomograms, based on age, T/N stage, tumor size, and high preoperative SII, provide a valuable tool for predicting 1-, 2-, and 3-year OS in patients with T1/T2 PSCC without distant metastases.

Exploring the preventive effects of Jie Geng Tang on pulmonary fibrosis induced in vitro and in vivo: a network pharmacology approach.

Pulmonary fibrosis is a debilitating lung disease marked by excessive fibrotic tissue accumulation, which significantly impairs respiratory function. Given the limitations of current therapies, there is an increasing interest in exploring traditional herbal formulations like Jie Geng Tang (JGT) for treatment. This study examines the potential of JGT and its bioactive component, quercetin, in reversing bleomycin (BLM)-induced pulmonary fibrosis in mice. We employed a BLM-induced MLE-12 cell damage model for in vitro studies and a bleomycin-induced fibrosis model in C57BL/6 mice for in vivo experiments. In vitro assessments showed that JGT significantly enhanced cell viability and reduced apoptosis in MLE-12 cells treated with BLM. These findings underscore JGT's potential for cytoprotection against fibrotic agents. In vivo, JGT was effective in modulating the expression of E-cadherin and vimentin, key markers of the epithelial-mesenchymal transition (EMT) pathway, indicating its role in mitigating EMT-associated fibrotic changes in lung tissue. Quercetin, identified through network pharmacology analysis as a potential key bioactive component of JGT, was highlighted for its role in the regulatory mechanisms underlying fibrosis progression, particularly through the modulation of the IL-17 pathway and Il6 expression. By targeting inflammatory pathways and key processes like EMT, JGT and quercetin offer a potent alternative to conventional therapies, meriting further clinical exploration to harness their full therapeutic potential in fibrotic diseases.

Enhanced photothermoelectric conversion in self-rolled tellurium photodetector with geometry-induced energy localization.

Photodetection has attracted significant attention for information transmission. While the implementation relies primarily on the photonic detectors, they are predominantly constrained by the intrinsic bandgap of active materials. On the other hand, photothermoelectric (PTE) detectors have garnered substantial research interest for their promising capabilities in broadband detection, owing to the self-driven photovoltages induced by the temperature differences. To get higher performances, it is crucial to localize light and heat energies for efficient conversion. However, there is limited research on the energy conversion in PTE detectors at micro/nano scale. In this study, we have achieved a two-order-of-magnitude enhancement in photovoltage responsivity in the self-rolled tubular tellurium (Te) photodetector with PTE effect. Under illumination, the tubular device demonstrates a maximum photovoltage responsivity of 252.13 V W-1 and a large detectivity of 1.48 × 1011 Jones. We disclose the mechanism of the PTE conversion in the tubular structure with the assistance of theoretical simulation. In addition, the device exhibits excellent performances in wide-angle and polarization-dependent detection. This work presents an approach to remarkably improve the performance of photodetector by concentrating light and corresponding heat generated, and the proposed self-rolled devices thus hold remarkable promises for next-generation on-chip photodetection.

Deep learning pneumoconiosis staging and diagnosis system based on multi-stage joint approach.

BACKGROUND: Pneumoconiosis has a significant impact on the quality of patient survival due to its difficult staging diagnosis and poor prognosis. This study aimed to develop a computer-aided diagnostic system for the screening and staging of pneumoconiosis based on a multi-stage joint deep learning approach using X-ray chest radiographs of pneumoconiosis patients. METHODS: In this study, a total of 498 medical chest radiographs were obtained from the Department of Radiology of West China Fourth Hospital. The dataset was randomly divided into a training set and a test set at a ratio of 4:1. Following histogram equalization for image enhancement, the images were segmented using the U-Net model, and staging was predicted using a convolutional neural network classification model. We first used Efficient-Net for multi-classification staging diagnosis, but the results showed that stage I/II of pneumoconiosis was difficult to diagnose. Therefore, based on clinical practice we continued to improve the model by using the Res-Net 34 Multi-stage joint method. RESULTS: Of the 498 cases collected, the classification model using the Efficient-Net achieved an accuracy of 83% with a Quadratic Weighted Kappa (QWK) score of 0.889. The classification model using the multi-stage joint approach of Res-Net 34 achieved an accuracy of 89% with an area under the curve (AUC) of 0.98 and a high QWK score of 0.94. CONCLUSIONS: In this study, the diagnostic accuracy of pneumoconiosis staging was significantly improved by an innovative combined multi-stage approach, which provided a reference for clinical application and pneumoconiosis screening.

Response of N, P, and metal ions in deep soil layers to long-term cultivation of rubber and rubber-based agroforestry systems.

The growing demand for natural rubber products has driven the expansion of rubber plantations in recent decades. While much attention has been given to studying the long-term effects of rubber and rubber-based agroforestry systems on surface soil properties, there has been a tendency to overlook changes in soil properties in deeper layers. Our study addresses this gap by examining alterations in nitrogen (N), phosphorus (P), and metal ion levels in deep soil layers resulting from the prolonged cultivation of rubber and rubber-based agroforestry systems. We found notable shifts in soil NH4+ and NO3- concentrations within the 0-30 cm soil layer across different-aged rubber and rubber-based agroforestry systems. Particularly in mature systems, NO3- and available P levels were close to zero below 30 cm soil depth. Introducing Flemingia macrophylla into young rubber plantations increased soil NH4+ and NO3- in the 0-90 cm soil layer and available P in the 0-10 cm soil layer. Over the long term, cultivation of rubber plantations increased the depletion of total P in the 0-50 cm soil layer, available iron (Fe) and manganese (Mn) in the 30-90 cm soil layer, available copper (Cu) and zinc (Zn) in the 0-90 cm soil layer, accompanied by a decrease in soil pH and increase in exchangeable aluminum (Al) in the 0-90 cm soil layer. Notably, soil exchangeable Al levels exceeding 2.0 cmol kg-1 appeared to induce aluminum toxicity. Furthermore, soil pH below 5.2 triggered a sharp release of exchangeable Al within the 0-90 cm soil layer of rubber plantations, with soil available P nearing zero when exchangeable Al levels assed 7.3 cmol kg-1. Our findings underscore the profound impact of long-term rubber plantation cultivation on surface and deep soil properties. Addressing soil degradation in these deep soil layers poses significant challenges for future soil restoration efforts.

Explicit Margin Equilibrium for Few-Shot Object Detection.

Under low data regimes, few-shot object detection (FSOD) transfers related knowledge from base classes with sufficient annotations to novel classes with limited samples in a two-step paradigm, including base training and balanced fine-tuning. In base training, the learned embedding space needs to be dispersed with large class margins to facilitate novel class accommodation and avoid feature aliasing while in balanced fine-tuning properly concentrating with small margins to represent novel classes precisely. Although obsession with the discrimination and representation dilemma has stimulated substantial progress, explorations for the equilibrium of class margins within the embedding space are still in full swing. In this study, we propose a class margin optimization scheme, termed explicit margin equilibrium (EME), by explicitly leveraging the quantified relationship between base and novel classes. EME first maximizes base-class margins to reserve adequate space to prepare for novel class adaptation. During fine-tuning, it quantifies the interclass semantic relationships by calculating the equilibrium coefficients based on the assumption that novel instances can be represented by linear combinations of base-class prototypes. EME finally reweights margin loss using equilibrium coefficients to adapt base knowledge for novel instance learning with the help of instance disturbance (ID) augmentation. As a plug-and-play module, EME can also be applied to few-shot classification. Consistent performance gains upon various baseline methods and benchmarks validate the generality and efficacy of EME. The code is available at github.com/Bohao-Lee/EME.

Spatiotemporal single-cell analysis decodes cellular dynamics underlying different responses to immunotherapy in colorectal cancer.

Expanding the efficacy of immune checkpoint blockade (ICB) in colorectal cancer (CRC) presses for a comprehensive understanding of treatment responsiveness. Here, we analyze multiple sequential single-cell samples from 22 patients undergoing PD-1 blockade to map the evolution of local and systemic immunity of CRC patients. In tumors, we identify coordinated cellular programs exhibiting distinct response associations. Specifically, exhausted T (Tex) or tumor-reactive-like CD8+ T (Ttr-like) cells are closely related to treatment efficacy, and Tex cells show correlated proportion changes with multiple other tumor-enriched cell types following PD-1 blockade. In addition, we reveal the less-exhausted phenotype of blood-associated Ttr-like cells in tumors and find that their higher abundance suggests better treatment outcomes. Finally, a higher major histocompatibility complex (MHC) II-related signature in circulating CD8+ T cells at baseline is linked to superior responses. Our study provides insights into the spatiotemporal cellular dynamics following neoadjuvant PD-1 blockade in CRC.

Efficient Parameterization of Density Functional Tight-Binding for 5f-Elements: A Th-O Case Study.

Density functional tight binding (DFTB) models for f-element species are challenging to parametrize owing to the large number of adjustable parameters. The explicit optimization of the terms entering the semiempirical DFTB Hamiltonian related to f orbitals is crucial to generating a reliable parametrization for f-block elements, because they play import roles in bonding interactions. However, since the number of parameters grows quadratically with the number of orbitals, the computational cost for parameter optimization is much more expensive for the f-elements than for the main group elements. In this work we present a set of efficient approaches for mitigating the hurdle imposed by the large size of the parameter space. A novel group-by-orbital correction functions for two-center bond integrals was developed. With this approach the number of parameters is reduced, and it grows linearly with the number of elements, maintaining the accuracy and the number of parameters, in the case of f elements, by more than 40%. The parameter optimization step was accelerated by means of the mini-batch BFGS method. This method allows parameter optimizations with much larger training sets than other single batch methods. A stochastic optimizer was employed that helped overcome shallow local minima in the objective function. The proposed algorithm was used to parametrize the DFTB Hamiltonian for the Th-O system, which was subsequently applied to the study of ThO2 nanoparticles. The training set consisted of 6322 unique structures, which is barely feasible with conventional optimization methods. The optimized parameter set, LANL-ThO, displays good agreement with DFT-calculated properties such as energies, forces, and structures for both clusters and bulk ThO2. Benefiting from the fewer number of parameters and lower computational costs for objective function evaluations, this new approach shows its potential applications in DFTB parametrization for elements with high angular momentum, which present a challenge to conventional methods.

The involvement of CgRHIM-containing protein in regulating haemocyte apoptosis after high temperature stress in Pacific oyster Crassostrea gigas.

The interactions induced by RIP homotypic interaction motif (RHIM) are essential for the activation of inflammatory signaling and certain cell death pathways. In the present study, a RHIM-containing protein was identified from Pacific oyster Crassostrea gigas, which harbored a RHIM and a Death domain (designated CgRHIM-containing protein). The mRNA transcripts of CgRHIM-containing protein were constitutively expressed in all the examined tissues of oysters, with the highest expression level in mantle. The CgRHIM-containing protein was mainly distributed in the cytoplasm of oyster haemocytes. After high temperature stress, the expression levels of CgRel and CgBcl-2 increased significantly, and reached the peak level at 12 h, then decreased gradually. The transcripts of CgRHIM-containing protein, Cgcaspase-8 and Cgcaspase-3 in haemocytes up-regulated at 12 h after high temperature stress. Moreover, the protein abundance of CgRHIM-containing protein increased significantly, and the ubiquitination level of CgRHIM-containing protein in haemocytes showed an increasing trend at first and then decreased. After the expression of CgRHIM-containing protein was knocked down by siRNA, the mRNA expression levels of CgRel and CgBcl-2 decreased significantly at 6 h after high temperature stress, and those of CgFADD-like, Cgcaspase-8 and Cgcaspase-3, as well as the apoptosis rate of haemocytes also decreased significantly at 24 h. These results indicated that CgRHIM-containing protein might regulate haemocyte apoptosis in oysters upon high temperature stress via mediating the expression of Rel, Bcl-2 and caspase-8/3.

High-Throughput Covalent Modifier Screening with Acoustic Ejection Mass Spectrometry.

Interests in covalent drugs have grown in modern drug discovery as they could tackle challenging targets traditionally considered "undruggable". The identification of covalent binders to target proteins typically involves directly measuring protein covalent modifications using high-resolution mass spectrometry. With a continually expanding library of compounds, conventional mass spectrometry platforms such as LC-MS and SPE-MS have become limiting factors for high-throughput screening. Here, we introduce a prototype high-resolution acoustic ejection mass spectrometry (AEMS) system for the rapid screening of a covalent modifier library comprising ∼10,000 compounds against a 50 kDa-sized target protein─Werner syndrome helicase. The screening samples were arranged in a 1536-well format. The sample buffer containing high-concentration salts was directly analyzed without any cleanup steps, minimizing sample preparation efforts and ensuring protein stability. The entire AEMS analysis process could be completed within a mere 17 h. An automated data analysis tool facilitated batch processing of the sample data and quantitation of the formation of various covalent protein-ligand adducts. The screening results displayed a high degree of fidelity, with a Z' factor of 0.8 and a hit rate of 2.3%. The identified hits underwent orthogonal testing in a biochemical activity assay, revealing that 75% were functional antagonists of the target protein. Notably, a comparative analysis with LC-MS showcased the AEMS platform's low risk of false positives or false negatives. This innovative platform has enabled robust high-throughput covalent modifier screening, featuring a 10-fold increase in library size and a 10- to 100-fold increase in throughput when compared with similar reports in the existing literature.

Isolated Calf Muscle Venous Thrombosis: A Review of Anticoagulation Strategies.

Deep vein thrombosis (DVT) of the lower extremities is divided into 2 categories according to the extent of thrombosis involvement. Thrombosis involving the popliteal vein, femoral vein, and iliac vein is classified as proximal DVT, while thrombosis involving the anterior tibial vein, posterior tibial vein, peroneal vein, and calf muscles vein is regarded as distal DVT. There are updated guidelines for the anticoagulant treatment for proximal DVT, but the best anticoagulant treatment for distal DVT is still controversial, especially for isolated calf muscular vein thrombosis (CMVT). The risk of isolated CMVT extending to the proximal deep veins and developing into pulmonary embolism is lower than with distal DVT. Some scholars believe that isolated CMVT has the risk of evolving into proximal deep vein thrombosis and pulmonary embolism, and active early anticoagulation therapy can reduce the risk and benefit patients. In addition, based on the characteristics of CMVT and the bleeding risk of anticoagulation therapy, some studies have recommended use of non-anticoagulation methods such as compression therapy. There is still a lack of multicenter, big-data, randomized, controlled trials on the benefits or risks of anticoagulation therapy. Among scholars who support anticoagulation therapy, there is still a lack of consensus on the optimal duration. This article reviews the current evidence on anticoagulant therapy for patients with isolated CMVT and how long the anticoagulation course should be if anticoagulation is required. Our research will provide a theoretical basis for subsequent research. More prospective studies with larger sample sizes are needed to provide more clinical evidence.

Tuning electronic structure of metal-free dual-site catalyst enables exclusive singlet oxygen production and in-situ utilization.

Developing eco-friendly catalysts for effective water purification with minimal oxidant use is imperative. Herein, we present a metal-free and nitrogen/fluorine dual-site catalyst, enhancing the selectivity and utilization of singlet oxygen (1O2) for water decontamination. Advanced theoretical simulations reveal that synergistic fluorine-nitrogen interactions modulate electron distribution and polarization, creating asymmetric surface electron configurations and electron-deficient nitrogen vacancies. These properties trigger the selective generation of 1O2 from peroxymonosulfate (PMS) and improve the utilization of neighboring reactive oxygen species, facilitated by contaminant enrichment at the fluorine-carbon Lewis-acid adsorption sites. Utilizing these insights, we synthesize the catalyst through montmorillonite (MMT)-assisted pyrolysis (NFC/M). This method leverages the role of MMT as an in-situ layer-stacked template, enabling controlled decomposition of carbon, nitrogen, and fluorine precursors and resulting in a catalyst with enhanced structural adaptability, reactive site accessibility, and mass-transfer capacity. The NFC/M demonstrates an impressive 290.5-fold increase in phenol degradation efficiency than the single-site analogs, outperforming most of metal-based catalysts. This work not only underscores the potential of precise electronic and structural manipulations in catalyst design but also advances the development of efficient and sustainable solutions for water purification.

Inhibition of GBP1 alleviates pyroptosis of human pulmonary microvascular endothelial cells through STAT1/NLRP3/GSDMD pathway.

Restoring and maintaining the function of endothelial cells is critical for acute respiratory distress syndrome (ARDS). Guanylate binding protein 1(GBP1) is proved to elevated in ARDS patients, but its role and mechanism remains unclear. The objective of this study is to investigate the internal mechanism of GBP1 in lung injury. Our study showed that when the LPS and IFN-γ induced human Pulmonary Microvascular Endothelial Cells (HPMECs) injury model was established, cell viability was significantly reduced, and the levels of GBP1 levels and inflammatory factors were significantly increased. When transfection with si-GBP1, low expression of GBP1 promoted cell proliferation and migration, and decreased the expression of downstream inflammatory factors. Furthermore, the inhibition of GBP1 significantly reduced the occurrence of cell pyroptosis and the expression of NLRP3 and STAT1. Our study indicated that GBP1 alleviates endothelial pyroptosis and inflammation through STAT1 / NLRP3/GSDMD signaling pathway, and GBP1 may be a new target in the treatment of lung injury in the future.

Multi-omics reveals the molecular mechanism of muscle quality changes in common carp (Cyprinus carpio) under two aquaculture systems.

Preliminary experiments in our laboratory have demonstrated that common carp (Cyprinus carpio) cultivated for two months in land-based container recirculating aquaculture systems (C-RAS) exhibit superior muscle quality compared to those raised in traditional pond systems (TP). To elucidate the molecular mechanisms underlying muscle quality variations in common carp cultured under two aquaculture systems, transcriptomic and metabolomic analyses were performed on muscle tissues of specimens aged 11 to 23 months. Comparison of muscle histological sections between the two groups indicated a significantly lower long diameter of muscle fibers in the C-RAS group compared to the TP group (P < 0.01). Conversely, the muscle fiber density was significantly higher in the C-RAS group than in the TP group (P < 0.05). Transcriptomic and metabolomic analyses identified 3390 differentially expressed genes (DEGs)-1558 upregulated and 1832 downregulated-and 181 differentially expressed metabolites (DEMs)-124 upregulated and 57 downregulated-between the groups. Based on integrated transcriptomic and metabolomic analyses, the significant differences focus on metabolic pathways involving glycolysis/gluconeogenesis, arginine and proline metabolism, arginine biosynthesis, and purine metabolism. The study revealed that the muscle quality of common carp in two aquaculture systems is primarily regulated through improvements in energy metabolism, amino acid metabolism, fatty acid metabolism, and purine metabolism. These metabolic processes play significant roles in promoting muscle fiber hyperplasia and hypertrophy, enhancing muscle flavor, and increasing muscle antioxidant capacity. This study provides new insights into the molecular and metabolic pathways that control muscle quality in common carp under different environmental factors.

A mechanistic study of chestnut starch retrogradation and its effects on in vitro starch digestion.

Starch retrogradation is a mechanism that is associated with the quality of starch-based food products. A thorough understanding of chestnut starch retrogradation behavior plays an important role in maintaining the quality of chestnut foods during processing and storage. In this study, we investigated the effects of storage time on the structural properties and in vitro digestibility of gelatinized chestnut starch by using X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and solid-state 13C nuclear magnetic resonance (NMR). The results showed that the long-range crystallinity and short-range molecular order of retrograded chestnut starch first rapidly increased from 3 h to 3 d and then decreased from 3 d to 7 d, followed by a slight increase from 7 d to 14 d with retrogradation. With the extension of storage time at 4 °C, there were generally obvious increases in single and double helical structures, which were stacked into long-term ordered structure, resulting in increased enthalpy changes as detected by differential scanning calorimetry spectroscopy (DSC) and reduction of the digestion rate of retrograded chestnut starch. Overall, this study may provide important implications for manipulating and improving the quality of chestnut foods.