ObjectiveTo systematically compare the differential regulation of the maternal-fetal interface cell lineages and communication networks in the CBA/J×DBA/2 mouse model of recurrent pregnancy loss （RPL） by the two classic therapeutic methods-tonifying the kidney to stabilize the fetus and invigorating the spleen to stabilize the fetus （Shoutai Wan， Juyuan Jian）-of traditional Chinese medicine （TCM） at the single-cell resolution and clarify their modern scientific connotations. MethodsFemale non-pregnant CBA/J mice were caged with male BALB/c （blank group） and DBA/2 （modeling group） mice separately. Pregnant mice in the modeling group were randomly grouped as follows： high/low-dose Shoutai Wan， high/low-dose Juyuan Jian， model （RPL）， and positive control （dydrogesterone）， with 10 mice in each group. Starting from the day after the detection of the vaginal plug， mice were administrated with drugs or an equal volume of normal saline by gavage for 10 consecutive days. After the intervention， the following indicators were measured. ① Macroscopic evaluation： general conditions， uterine wet weight， embryo loss rate， four coagulation parameters ［prothrombin time （PT）， activated partial thromboplastin time （APTT）， fibrinogen （FIB）， and thrombin time （TT）］， and peripheral blood estradiol （E₂） and progesterone （Pg） levels. The decidua with embryos was stained with hematoxylin-eosin （HE） and evaluated by transmission electron microscopy （TEM）. The expression of B-cell lymphoma-2 （Bcl-2）， vascular endothelial growth factor （VEGF）， angiotensin Ⅱ （AngⅡ）， matrix metalloproteinase-2 （MMP-2）， interleukin-6 （IL-6）， leukemia inhibitory factor （LIF）， CXC chemokine ligand 12 （CXCL12）， and microtubule-associated protein 1 light chain 3 homolog （LC3）Ⅰ/Ⅱ was quantified by Western blot. ② Mechanism analysis at the single-cell level： The decidua with embryos from the blank， model， high-dose Shoutai Wan， and high-dose Juyuan Jian groups （6 mice per group， with 3 single-cell samples per group， totaling 24 mice） were analyzed by the BD Rhapsody™ platform， and the whole-cell atlas was drawn by uniform manifold approximation and projection （UMAP） dimensionality reduction clustering combined with the single-cell mouse cell atlas （scMCA）. The differentially expressed genes （DEGs） and cell interaction networks were analyzed via Gene Ontology （GO）， Kyoto Encyclopedia of Genes and Genomes （KEGG）， and CellChat， and the protein-protein interaction （PPI） map of subtype cells was constructed. The CytoTRACE pseudo-temporal analysis was performed to explore the developmental trajectories of core immune cells （natural killer cells， NK cells） from maternal and fetal sources. Results① Pathological and Western blot results indicated that compared with the blank group， the RPL group showed an increase in the embryo loss rate （P<0.01）， down-regulated expression of Bcl-2， LIF， MMP-2， and Vegf in the decidua with embryos （P<0.05）， up-regulated protein levels of CXCL-12， AngⅡ， and IL-6 （P<0.05）， blocked angiogenesis， apoptosis-inflammation imbalance， and coagulation dysfunction. Both prescriptions dose-dependently reduced the abortion rate and restored the angiogenesis-inflammation balance， and Shoutai pill showed superior performance in restoring the E₂ level to the Pg level （P<0.05）. ② Single-cell transcriptome analysis indicated that compared with the blank group， the RPL group showed differences in multiple key cell populations such as decidual cells， trophoblast cells， endothelial cells， erythroblasts， NK cells， and macrophages at the maternal-fetal interface. Immunity and angiogenesis were the key links in RPL. Compared with the RPL group， high-dose Shoutai Wan reversed the changes of NK cells in the embryonic layer （upregulating the mRNA levels of 17 genes and downregulating the mRNA levels of 29 genes） and macrophages （upregulating the mRNA levels of 117 genes and downregulating the mRNA levels of 53 genes） through the regulation of gene expression. High-dose Shoutai pill regulated the immune cells to affect unfolded proteins， cell adhesion， and programmed cell death， thereby promoting decidualization and angiogenesis and modulating embryo-membrane development. High-dose Juyuan Jian regulated the key subgroups of NK cells （up-regulating the mRNA levels of 9 genes and down-regulating the mRNA levels of 17 genes） and macrophages （up-regulating the mRNA levels of 110 genes and down-regulating the mRNA levels of 81 genes）， which affected decidual inflammation and apoptosis and intervened in glycolysis. ③ The pseudo-temporal analysis and communication network indicated that the communication frequency of the RPL group decreased. High-dose Shoutai Wan restored maternal-fetal tolerance through pathways such as NKG2D， CDH5， GDF， and FASLG. High-dose Juyuan Jian enhanced the IL-6/LIFR/JAK/signal transducer and activator of transcription 3 （STAT3） and desmosome/SEMA6/tumor necrosis factor-like weak inducer of apoptosis （TWEAK） signaling to improve endometrial receptivity. The RPL group showed an increased proportion of toxic dNK7， a decreased proportion of reparative dNK4， and blocked embryo fNK1. High-dose Shoutai Wan down-regulated dNK7 and up-regulated dNK4. High-dose Juyuan Jian inhibited the terminal differentiation of dNK7 and up-regulated LILRB1， thus restoring the balance of cytotoxicity and repair. ConclusionBoth the kidney-tonifying and spleen-invigorating methods are effective in treating RPL. NK and macrophages are the key immune cells in the interaction between the embryo and the membrane. The kidney-tonifying method （Shoutai Wan） has an advantage in regulating the phenotypes of unfolded protein， cell adhesion， and programmed cell death， and shows expression characteristics closer to the physiological state in the regulation of NKG2D and CDH5 signals. The spleen-invigorating method （Juyuan Jian） has an advantage in regulating epithelial-mesenchymal transition （EMT）， angiogenesis， and glycolysis and shows higher communication intensity in the IL-6 and LIFR pathways.

Neonatal diabetes mellitus （NDM） is a rare monogenic disorder primarily caused by insufficient insulin secretion resulting from mutations in the KCNJ11 and ABCC8 genes. Sulfonylureas， represented by glibenclamide， have become the standard therapy for this type of NDM by precisely closing the mutated ATP-sensitive potassium channels in pancreatic β cells， thereby restoring insulin secretion. Clinical studies confirm that sulfonylureas enable over 90% of patients to successfully transition from insulin to oral treatment， achieving long-term stable glycemic control and improving neurological outcomes to a certain extent. In terms of safety， severe hypoglycemia induced by sulfonylureas is relatively rare and gastrointestinal reactions are mild； moreover， sulfonylureas show good long-term tolerability， and have no adverse effects on child growth and development. In the future， by further refining the full-chain management pathway of “rapid genetic diagnosis-early intervention-specialized dosage forms-long-term follow-up”， the clinical application of sulfonylureas is expected to provide NDM patients with an optimized treatment regimen and maximize their health benefits.

Objective To explore the number of peripheral blood regulatory T cells (Treg) in patients with chronic kidney disease (CKD) and its correlation with vascular calcification. Methods This was a single-center, cross-sectional, and observational study. Non-dialysis patients with CKD treated at Zhongshan Hospital, Fudan University from March 2021 to March 2022 were enrolled. Abdominal aortic calcification (AAC) was assessed using lateral abdominal X-ray. Number of Treg and cytokine levels were measured by flow cytometry. Logistic regression analysis was performed to evaluate the related factors for AAC in CKD patients. Results A total of 83 patients were included, aged 17–86 years, with 57 males (68.7%). The distribution of CKD stages was as follows: stage G1 in 7 patients (8.4%), stage G2 in 17 patients (20.5%), stage G3 in 21 patients (25.3%), stage G4 in 19 patients (22.9%), and stage G5 in 19 patients (22.9%). No AAC was observed in patients with stages G1 and G2, while the prevalence of AAC in patients with stages G3, G4, and G5 was 23.8%, 21.1%, and 26.3%, respectively. Compared with stage G1 patients, those with stages G3–5 showed decreased number of peripheral blood Treg and elevated levels of interleukin (IL)-6 and IL-17F (P＜0.05). The area under the receiver operating characteristic curve for number of peripheral blood Treg in predicting AAC in CKD patients was 0.766 (95%CI 0.652–0.879, P＝0.002). Logistic regression analysis showed that decreased number of Treg was related factor for AAC in CKD patients (OR＝0.957, 95%CI 0.922–0.992, P＝0.018). Conclusion As CKD progresses, number of peripheral blood Treg significantly decreases, which is correlated with AAC in CKD patients.

Disrupted bone morphogenetic protein type 2 receptor (BMPR2) signaling in endothelial cells drives pulmonary arterial hypertension (PAH). However, targeted recovery of this signaling pathway by lipid nanoparticles (LNPs) has not been explored as a therapy. Here, we employed Design of Experiments to optimize the delivery efficiency of LNPs targeting pulmonary endothelial cells developed by our laboratory, resulting in a remarkable 35-fold increase in a simplified three-component formulation without helper lipids. Administration of BMPR2 mRNA LNPs effectively reversed established PAH in two experimental rat models (monocrotaline or SU5416-hypoxia) by reversing pulmonary vascular remodeling. Specifically, BMPR2 mRNA LNPs replenished the expression of BMPR2 protein and subsequently activated downstream pathways, as confirmed by elevated levels of p-SMAD1/5/9 and ID1 proteins. The relief of pulmonary arterial occlusion was demonstrated by thinned pulmonary arterial media and decreased proportion of full muscularized vessels. Alleviation of right ventricular hypertrophy was indicated by declined Fulton index, the cross-sectional area of right ventricular cardiomyocytes as well as collagen deposition. Effective recovery of right ventricular function was evidenced by increased pulmonary artery flow acceleration time/pulmonary artery flow ejection time ratio. These findings underscore the potential of restoring BMPR2 signaling through pulmonary endothelial cell-specific LNPs for treating PAH.

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Acute lower respiratory infections in infants and young children, caused by respiratory syncytial virus (RSV), represent a significant global public health challenge, characterized by a substantial disease burden. During the winter and spring seasons, various respiratory viruses tend to co-circulate, leading to increased pressure on pediatric healthcare services due to heightened rates of visits and hospitalizations. Currently, there is no approved RSV vaccine available for children worldwide; however, the development and application of long-acting monoclonal antibodies present a promising avenue for the prevention of RSV in this vulnerable population. In June 2024, Tianjin released"Guidelines for the monoclonal antibody of respiratory syncytial virus in Tianjin (2024 version)", which outlines the promotion of monoclonal antibody administration in vaccination clinics throughout the region. The objective of this paper is to provide reference information that may assist in the formulation and implementation of a national RSV immunization strategy.

Metabolomics covers a wide range of applications in life sciences,biomedicine,and phytology.Data acquisition(to achieve high coverage and efficiency)and analysis(to pursue good classification)are two key segments involved in metabolomics workflows.Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups.However,insufficient feature extraction,inappropriate feature selection,overfitting,or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused.Using two ginseng varieties,namely Panax japonicus(PJ)and Panax japonicus var.major(PJvm),containing the similar ginsenosides,we integrated pseudo-targeted metabolomics and deep neural network(DNN)modeling to achieve accurate species differentiation.A pseudo-targeted metabolomics approach was optimized through data acquisition mode,ion pairs generation,comparison between multiple reaction monitoring(MRM)and scheduled MRM(sMRM),and chromatographic elution gradient.In total,1980 ion pairs were monitored within 23 min,allowing for the most comprehensive ginseng metabolome analysis.The established DNN model demonstrated excellent classification performance(in terms of accuracy,precision,recall,F1 score,area under the curve,and receiver operating characteristic(ROC))using the entire metabolome data and feature-selection dataset,exhibiting superior advantages over random forest(RF),support vector ma-chine(SVM),extreme gradient boosting(XGBoost),and multilayer perceptron(MLP).Moreover,DNNs were advantageous for automated feature learning,nonlinear modeling,adaptability,and generalization.This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples.This established approach holds promise for plant metabolomics and is not limited to ginseng.

OBJECTIVE: To assess the value of chromosomal microarray analysis (CMA) for the detection of low-level mosaicisms in amniotic fluid samples, and to retrospectively analyze the rare cases of mosaicisms. METHODS: Chromosomal karyotype of the fetus was determined by G-banding analysis of cultured amniotic fluid cells. CMA was used to detect copy number variation of fetal chromosomes, and fluorescence in situ hybridization (FISH) was used to determine the proportion of fetal chromosomal mosaicisms in uncultured amniotic fluid cells. RESULTS: Among 825 prenatal samples, 4 cases of true fetal mosaicisms were detected, which yielded an incidence of 0.48%. Two cases were sex chromosomal mosaicisms, and two were autosomal mosaicisms, which involved chromosomes 8 and 9, respectively. All cases were verified by G-banding analysis of cultured amniotic fluid cells, CMA, and/or FISH. CONCLUSION CMA has a great value for detecting low-level mosaicisms in amniotic fluid samples, though the positive results need to be verified by other techniques and should be interpreted with caution. The review of rare cases can provide a basis for prenatal genetic counseling.
Humans ; Female ; Amniotic Fluid/metabolism* ; Pregnancy ; Mosaicism/embryology* ; Prenatal Diagnosis/methods* ; Adult ; In Situ Hybridization, Fluorescence ; Microarray Analysis/methods* ; Karyotyping ; Retrospective Studies ; Male

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.

Objective:To develop PixelSIFT-UNet, a novel semantic segmentation model that integrates deep learning with scale-invariant feature transform (SIFT) algorithm to improve the segmentation accuracy of oral mucosal lesions.Methods:This investigation utilized 838 standard clinical white light images of oral mucosal diseases acquired from January 2020 to December 2022 at the Stomatology Hospital Zhejiang University School of Medicine. Randomization was achieved through Python′s random.seed function implementation. The random sample function was subsequently applied for sampling distribution. The dataset was stratified into three subsets with a 6∶2∶2 ratio: training ( n=506), validation ( n=166), and testing ( n=166). Lesion boundaries were annotated using Labelme software, and a PixelSIFT-UNet-based deep learning model was developed with VGG-16 and ResNet-50 backbone networks. Model parameters were optimized using the validation set, and performance metrics [including Dice coefficient, mean intersection over union (mIoU), mean pixel accuracy (mPA), and Precision] were assessed on the test set. The model′s performance was benchmarked against conventional semantic segmentation frameworks (U-Net and PSPNet). Results:The developed PixelSIFT-UNet model could achieve precise segmentation of three common oral mucosal lesions: oral lichen planus, oral leukoplakia, and oral submucous fibrosis. Utilizing VGG-16 as the backbone network, the model achieved Dice coefficient, mIoU, mPA, and Precision values of 0.642, 0.699, 0.836, and 0.792, respectively. Implementation with ResNet-50 backbone network yielded metrics of 0.668, 0.733, 0.872 and 0.817, demonstrating significant improvements across all performance indicators compared to conventional U-Net model (relevant metrics: 0.662, 0.717, 0.861 and 0.809) and PSPNet model (relevant metrics: 0.671, 0.721, 0.858 and 0.813).Conclusions:The proposed PixelSIFT-UNet architecture demonstrates superior performance in oral mucosal lesion segmentation tasks, surpassing conventional semantic segmentation models and providing robust quantitative improvements in segmentation accuracy.