Supercooling preservation technology, as a groundbreaking innovation in the field of organ preservation, significantly reduces the metabolic rate of cells and inhibits ice crystal formation by placing organs in a low-temperature environment near or below the freezing point. This technology extends the preservation time of organs and maintains their biological activity. Compared with the traditional low-temperature preservation at 4 °C, supercooling preservation effectively avoids cell damage and the accumulation of metabolic products, demonstrating significant advantages in the preservation of cells, tissues and organs. In recent years, important progress has been made in the optimization of cryoprotectants, the application of antifreeze proteins, the improvement of vitrification technology, and the development of nanotechnology-based rewarming techniques. These advancements provide new pathways to address the challenges of toxicity, ice crystal formation and uneven rewarming rates during supercooling preservation. This review summarizes the basic principles of supercooling preservation, the application of key technologies, and their practical effects in organ transplantation. It also analyzes the challenges of toxicity and rewarming efficiency, aiming to provide theoretical support and research directions for the future optimization of organ low-temperature preservation technology and its clinical application.

As a cheap and effective antibiotic,sulfonamides are often used in animal husbandry.However,their residues in animal-derived foodstuffs will threaten human health.Consequently,a high-performance liquid chromatography(HPLC)method integrated with supramolecular solvent microextraction was successfully established for simultaneous quantification of sulfonamide residues sulfachlorpyridazine,sulfamethoxazole,sulfamethoxypyridazine and sulfadimethoxine in milk matrices.This approach exhibited prominent characteristics of operational simplicity,environmental sustainability,and high extraction efficiency.The supramolecular solvents prepared by tributyl octylphosphine tetrafluoroborate and tetrahydrofuran were employed as extraction solvents.The analytes underwent isolation and concentration via dispersive liquid-liquid microextraction(DLLME)prior to quantitative determination using high-performance liquid chromatography(HPLC).The composition and microscopic morphology of the supramolecular solvent were characterized through a series of analytical techniques,including phase diagram,Fourier transform infrared spectroscopy,scanning electron microscopy,and inverted fluorescence microscopy and so on.The density and pH value of supramolecular solvents were determined.The extraction conditions were optimized through the one-factor experiments.The experimental results demonstrated that under the optimal extraction conditions,the four kinds of sulfonamide antibiotics exhibited excellent linearity within respective detection range(R2 ≥ 0.9998)and the limits of detection(LOD)were 0.67-1.45 μg/L.Compared with literature methods,this approach offered some advantages such as simplicity of operation and less reagent consumption,and could be used for analysis and detection of sulfonamide antibiotic residues in milk samples.The present method provided technical support for food safety regulation and paved a new way for the application of supramolecular solvents in the field of extraction and separation.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

Objective In this preliminary survey,we sought to determine the composition of mosquito species inhabiting the Emeifeng Nature Reserve,Fujian Province,China.Methods Mosquito larvae were collected by straw and spoon trapping,and adult mosquitoes were collected by lamp trapping at selected breeding sites in the reserve.The specimens were initially identified based on morphology,with subsequent verification using molecular biology methods.Results A total of 34 mosquito species in 13 genera were collected,among which,there were 4 species of Anopheles(Genus Anopheles Meigen,1818),2 species of Lutzia(Genus Lutzia Theobald,1903),15 species of Culex(Genus Culex Linnaeus,1758),4 species of Stegomyia(Genus Stegomyia Theobald,1901),and single species of Hulecoeteomyia(Genus Hulecoeteomyia Theobald,1904),Luius(Genus Luius Reinert,Harbach et Kitching,2008),Aedes(Genus Aedes Meigen,1818),Downsiomyia(Genus Downsiomyia Vargas,1950),Collessius(Genus Collessius Reinert,Harbach et kitching,2006),Uranotaenia(Genus Uranotaenia Lynch 1891),Armigeres(Genus Armigeres Theobald,1901),Toxorhynchites(Genus Toxorhynchites Theobald,1901),and pestle mosquito(Genus Tripteroides Giles,1904).Conclusions The species composition of mosquitoes sampled in the Emeifeng Nature Reserve will provide a basis for further research on mosquito vectors and contribute to measures for local mosquito control.

Objective To investigate the association between D-dimer levels within 2 hours of admission and in-hospital major adverse events (MAEs) in patients with acute type A aortic dissection (ATAAD) who underwent total arch replacement combined with frozen elephant trunk (FET) implantation. Methods This retrospective study included patients with ATAAD who underwent total arch replacement with FET implantation at Fuwai Yunnan Cardiovascular Hospital from September 2017 to December 2022. Patients were divided into two groups based on the occurrence of in-hospital MAEs: a MAEs group and a non-MAEs group (control). Perioperative data were compared between the two groups. Univariate and multivariate logistic regression analyses were performed to identify risk factors for in-hospital MAEs, which included in-hospital death, gastrointestinal bleeding, paraplegia, acute kidney injury, low cardiac output syndrome, stroke, respiratory failure, multiple organ dysfunction syndrome, and severe infection. The predictive value of D-dimer was evaluated using the area under the receiver operating characteristic curve (AUC). Results A total of 218 patients were included (157 males, 61 females), with a mean age of (51.54±9.79) years. There were 152 patients in the non-MAEs group and 66 in the MAEs group. The overall incidence of in-hospital MAEs was 30.3%, and the in-hospital mortality rate was 2.8% (6/218). Compared to the non-MAEs group, the MAEs group had significantly higher levels of D-dimer and lactate, as well as longer cardiopulmonary bypass time, aortic cross-clamp time, and ICU length of stay (all P<0.05). Multivariate logistic regression analysis identified D-dimer as an independent risk factor for in-hospital MAEs [OR=1.077, 95%CI (1.020, 1.137), P=0.013]. The AUC for the D-dimer level within 2 hours of admission to predict in-hospital MAEs was 0.83 [95%CI (0.736, 0.870), P<0.001]. The optimal cutoff value was 2.2 μg/mL, with a sensitivity of 84.8% and a specificity of 73.0%. Conclusion The serum D-dimer level is an independent risk factor for in-hospital MAEs in patients with ATAAD following total arch replacement with FET implantation. D-dimer levels on admission can help clinicians optimize risk stratification and perioperative management, potentially reducing the incidence of early adverse events.

The interest in covalent drugs has resurged in recent decades, spurring the development of numerous specialized computational docking tools to facilitate covalent ligand design and screening. Herein, we present CarsiDock-Cov, a new paradigm distinguishing itself as the first deep learning (DL)-guided approach for covalent docking. CarsiDock-Cov retains the core components of its non-covalent predecessor, leveraging a DL model pretrained on millions of docking complexes to predict protein-ligand distance matrices, along with a dedicated-designed geometric optimization procedure to convert these distances into refined binding poses. Additionally, it incorporates several key enhancements specifically tailored to optimize the protocol for covalent docking applications. Our approach has been extensively validated on multiple public datasets regarding the docking and screening of covalent ligands, and the results indicate that our approach not only achieves comparably improved applicability compared to its non-covalent predecessor, but also exhibits competitive performance against various state-of-the-art covalent docking tools. Collectively, our approach represents a significant advance in covalent docking methodology, offering an automated and efficient solution that shows considerable promise for accelerating covalent drug discovery and design.

Gene regulation relies on the precise binding of transcription factors (TFs) at regulatory elements, but simultaneously detecting hundreds of TFs on chromatin is challenging. We developed cFOOT-seq, a cytosine deaminase-based TF footprinting assay, for high-resolution, quantitative genome-wide assessment of TF binding in both open and closed chromatin regions, even with small cell numbers. By utilizing the dsDNA deaminase SsdAtox, cFOOT-seq converts accessible cytosines to uracil while preserving genomic integrity, making it compatible with techniques like ATAC-seq for sensitive and cost-effective detection of TF occupancy at the single-molecule and single-cell level. Our approach enables the delineation of TF footprints, quantification of occupancy, and examination of chromatin influences on TF binding. Notably, cFOOT-seq, combined with FootTrack analysis, enables de novo prediction of TF binding sites and tracking of TF occupancy dynamics. We demonstrate its application in capturing cell type-specific TFs, analyzing TF dynamics during reprogramming, and revealing TF dependencies on chromatin remodelers. Overall, cFOOT-seq represents a robust approach for investigating the genome-wide dynamics of TF occupancy and elucidating the cis-regulatory architecture underlying gene regulation.
Transcription Factors/genetics* ; Humans ; Chromatin/genetics* ; Animals ; Binding Sites ; Mice ; DNA Footprinting/methods*

In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods* ; Drugs, Chinese Herbal/administration & dosage* ; Machine Learning ; Algorithms ; Humans ; Quality Control

This study aims to integrate data mining techniques of single cell transcriptomics and spatial transcriptomics, along with animal experiment validation, so as to systematically characterize the protective effects of Jianpi Tongluo Formula(JTF) on the cartilage in knee osteoarthritis(KOA) and elucidate the underlying molecular mechanisms. Single cell transcriptomics and spatial transcriptomics datasets(GSE254844 and GSE255460) of the cartilage tissue obtained from KOA patients were analyzed to map the single cell-spatial heterogeneity and identify key pathogenic factors. After that, a KOA rat model was established via knee joint injection of papain. The intervention effects of JTF on the expression features of these key factors were assessed through real-time quantitative polymerase chain reaction(PCR), Western blot, and immunohistochemical staining. As a result, the integrated single cell and spatial transcriptomics data identified distinct cell subsets with different pathological changes in different regions of the inflamed cartilage tissue in KOA, and their differentiation trajectories were closely related to the inflammatory fibrosis-like pathological changes of chondrocytes. Accordingly, the expression levels of the two key effect targets, namely nuclear receptor coactivator 4(NCOA4) and high mobility group box 1(HMGB1) were significantly reduced in the articular surface and superficial zone of the inflamed joints when JTF effectively alleviated various pathological changes in KOA rats, thus reversing the abnormal chondrocyte autophagy level, relieving the inflammatory responses and fibrosis-like pathological changes, and promoting the repair of chondrocyte function. Collectively, this study revealed the heterogeneous characteristics and dynamic changes of inflamed cartilage tissue in different regions and different cell subsets in KOA patients. It is worth noting that NCOA4 and HMGB1 were crucial in regulating chondrocyte autophagy and inflammatory reaction, while JTF could reverse the regulation of NCOA4 and HMGB1 and correct the abnormal molecular signal axis in the target cells of the inflamed joints. The research can provide a new research idea and scientific basis for developing a personalized therapeutic schedule targeting the spatiotemporal heterogeneity characteristics of KOA.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Osteoarthritis, Knee/pathology* ; Humans ; Male ; Cartilage, Articular/metabolism* ; Chondrocytes/metabolism* ; Rats, Sprague-Dawley ; Female ; Protective Agents/administration & dosage* ; Single-Cell Analysis ; Middle Aged ; HMGB1 Protein/metabolism*