ObjectiveTo explore the mechanism of Hei Xiaoyaosan in improving the cognitive function in Alzheimer's disease （AD） from cell apoptosis mediated by the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/nuclear factor kappa B （NF-κB） signaling pathway. MethodsFour-month-old SD male rats were randomly assigned into a blank group， a sham group， a model group， a donepezil hydrochloride （0.45 mg·kg^-1） group， and high-， medium-， and low-dose （15.30， 7.65， and 3.82 g·kg^-1， respectively） Hei Xiaoyaosan groups， with 10 rats in each group. The sham group received bilateral hippocampal injection of 1 μL normal saline， while the other groups received bilateral hippocampal injection of 1 μL beta-amyloid 1-42 （Aβ_1-42） solution for the modeling of AD. Rats were administrated with corresponding agents once a day for 42 consecutive days. The Morris water maze test was carried out to assess the learning and memory abilities of rats. Hematoxylin-eosin staining was employed to observe pathological changes in the hippocampus of rats. Enzyme-linked immunosorbent assay was employed to measure the levels of cysteinyl aspartate-specific proteinase-3 （Caspase-3）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. Western blot was employed to determine the protein levels of PI3K， Akt， and NF-κB. A cell model of AD was established by co-culturing Aβ_1-42 and PC12 cells in vitro. Cell viability and apoptosis were detected by the cell-counting kit 8 （CCK-8） assay and flow cytometry （FC）， respectively. ResultsAnimal experiments showed that compared with the blank group， the model group had a prolonged escape latency （P<0.01）， a reduced number of crossing platforms （P<0.01）， disarrangement and a reduced number of hippocampal neurons， up-regulated expression of Bax and Caspase-3， down-regulated expression of Bcl-2 （P<0.01）， decreased p-PI3K/PI3K and p-Akt/Akt levels， and an increased p-NF-κB/NF-κB level （P<0.01）. Compared with the model group， donepezil hydrochloride and high- and medium-dose Hei Xiaoyaosan shortened the escape latency and increased the number of crossing platforms （P<0.05， P<0.01）， improved the arrangement and increased the number of hippocampal neurons， down-regulated the expression levels of Bax and Caspase-3， up-reguated the expression level of Bcl-2 （P<0.05， P<0.01）， increased the p-PI3K/PI3K and p-Akt/Akt levels （P<0.05， P<0.01）， and reduced the p-NF-κB/NF-κB level （P<0.05， P<0.01）. Cell experiments showed that compared with the blank group， the model group exhibited an increased apoptosis rate （P<0.01）. Compared with the model group， the serum containing Hei Xiaoyaosan at various doses improved the cell viability （P<0.01）， and the serum containing Hei Xiaoyaosan at the high dose decreased the cell apoptosis （P<0.01）. ConclusionHei Xiaoyaosan may improve the learning and memory abilities of AD model rats by regulating cell apoptosis， while increasing the vitality and reducing the apoptosis rate of AD model cells via the PI3K/Akt/NF-κB signaling pathway.

ObjectiveTo understand the infection characteristics of multidrug-resistant organisms (MDROs) in hospitalized patients in a tertiary sentinel hospital in Shanghai, so as to provide an evidence for the development of targeted prevention and control measures. MethodsData of MDROs strains and corresponding medical records of some hospitalized patients in a hospital in Shanghai from 2021 to 2023 were collected, together with an analysis of the basic information, clinical treatment, underlying diseases and sources of sample collection. ResultsA total of 134 strains of MDROs isolated from hospitalized patients in this hospital were collected from 2021 to 2023 , including 63 strains of methicillin-resistant Staphylococcus aureus (MRSA), 57 strains of carbapenem-resistant Acinetobacter baumannii (CRAB), and 14 strains of carbapenem-resistant Klebsiella pneumoniae (CRKP). Of the 134 strains, 30 strains were found in 2021, 47 strains in 2022 and 57 strains in 2023. The male-to-female ratio of patients was 2.05∶1, with the highest percentage (70.90%) in the age group of 60‒<90 years. The primary diagnosis was mainly respiratory disease, with lung and respiratory tract as the cheif infection sites. There was no statistically significant difference in the distribution of strains between different genders and infection sites (P>0.05). However, the differences in the distribution of strains between different ages and primary diagnosis were statistically significant (P<0.05). Patients who were admitted to the intensive care unit (ICU), had urinary tract intubation, were not artery or vein intubated, were not on a ventilator, were not using immunosuppresants or hormones, and were not applying radiotherapy or chemotherapy were in the majority. There was no statistically significant difference in the distribution of strains for whether received radiotherapy or chemotherapy or not (P>0.05), while the differences in the distribution of strains with ICU admission history, urinary tract intubation, artery or vein intubation, ventilator use, and immunosuppresants or hormones use or not were statistically significant (all P<0.05). The type of specimen was mainly sputum, the hospitalized ward was mainly comprehensive ICU, the sampling time was mainly in the first quarter throughout the year, the number of underlying diseases was mainly between 1 to 2 kinds, the application of antibiotics ≥4 kinds, and those who didn’t receive any surgery recently accounted for the most. There were statistically significant differences in the distribution of strains between different specimen types, wards occupied and history of ICU stay (P<0.05), but no statistically significant difference in the distribution of strains between different sampling times, number of underlying diseases and types of antibiotics applied (P>0.05). ConclusionThe situation of prevention and control on MDROs in this hospital is still serious. Focus should be placed on high-risk factors’ and infection monitoring and preventive measures should be strengthened to reduce the incidence rate of MDROs infection.

Fermented traditional Chinese medicine(TCM) has a long history of medicinal use, such as Sojae Semen Praeparatum, Arisaema Cum Bile, Pinelliae Rhizoma Fermentata, red yeast rice, and Jianqu. Fermentation technology was recorded in the earliest TCM work, Shen Nong's Classic of the Materia Medica. Microorganisms are essential components of the fermentation process. However, the contamination of fermented TCM by toxigenic fungi and mycotoxins due to unstandardized fermentation processes seriously affects the quality of TCM and poses a threat to the life and health of consumers. In this paper, the characteristics, microbial composition, and mycotoxin profile of fermented TCM are systematically summarized to provide a theoretical basis for its quality and safety control.
Fermentation ; Mycotoxins/analysis* ; Drugs, Chinese Herbal/analysis* ; Fungi/classification* ; Bacteria/genetics* ; Drug Contamination ; Medicine, Chinese Traditional

Meditation aims to guide individuals into a state of deep calm and focused attention, and in recent years, it has shown promising potential in the field of medical treatment. Numerous studies have demonstrated that electroencephalogram (EEG) patterns change during meditation, suggesting the feasibility of using deep learning techniques to monitor meditation states. However, significant inter-subject differences in EEG signals poses challenges to the performance of such monitoring systems. To address this issue, this study proposed a novel model-calibrated multi-source adversarial adaptation network (CMAAN). The model first trained multiple domain-adversarial neural networks in a pairwise manner between various source-domain individuals and the target-domain individual. These networks were then integrated through a calibration process using a small amount of labeled data from the target domain to enhance performance. We evaluated the proposed model on an EEG dataset collected from 18 subjects undergoing methamphetamine rehabilitation. The model achieved a classification accuracy of 73.09%. Additionally, based on the learned model, we analyzed the key EEG frequency bands and brain regions involved in the meditation process. The proposed multi-source domain adaptation framework improves both the performance and robustness of EEG-based meditation monitoring and holds great promise for applications in biomedical informatics and clinical practice.
Humans ; Electroencephalography/methods* ; Meditation ; Calibration ; Neural Networks, Computer ; Brain/physiology* ; Rest/physiology* ; Deep Learning ; Signal Processing, Computer-Assisted

Current studies on electroencephalogram (EEG) emotion recognition primarily concentrate on discrete stimulus paradigms under controlled laboratory settings, which cannot adequately represent the dynamic transition characteristics of emotional states during multi-context interactions. To address this issue, this paper proposes a novel method for emotion transition recognition that leverages a cross-modal feature fusion and global perception network (CFGPN). Firstly, an experimental paradigm encompassing six types of emotion transition scenarios was designed, and EEG and eye movement data were simultaneously collected from 20 participants, each annotated with dynamic continuous emotion labels. Subsequently, deep canonical correlation analysis integrated with a cross-modal attention mechanism was employed to fuse features from EEG and eye movement signals, resulting in multimodal feature vectors enriched with highly discriminative emotional information. These vectors are then input into a parallel hybrid architecture that combines convolutional neural networks (CNNs) and Transformers. The CNN is employed to capture local time-series features, whereas the Transformer leverages its robust global perception capabilities to effectively model long-range temporal dependencies, enabling accurate dynamic emotion transition recognition. The results demonstrate that the proposed method achieves the lowest mean square error in both valence and arousal recognition tasks on the dynamic emotion transition dataset and a classic multimodal emotion dataset. It exhibits superior recognition accuracy and stability when compared with five existing unimodal and six multimodal deep learning models. The approach enhances both adaptability and robustness in recognizing emotional state transitions in real-world scenarios, showing promising potential for applications in the field of biomedical engineering.
Humans ; Emotions/physiology* ; Electroencephalography ; Neural Networks, Computer ; Eye Movements ; Perception

Objective To construct a library of human-derived anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) single-chain variable fragments (scFv) and screen for broad-spectrum neutralizing antibodies to identify candidate molecules for the development of diagnostic and therapeutic agents. Methods Peripheral blood mononuclear cells (PBMCs) were isolated from the peripheral blood of patients who had recovered from novel coronavirus infection. Total RNA was extracted from these PBMCs and reverse transcribed into cDNA, which was used as a template for constructing a human anti-SARS-CoV-2 scFv library. Phage display technology was used to screen for scFv antibodies specific to the SARS-CoV-2 S protein. Full-length IgG antibodies were synthesized through sequence analysis and human IgG expression, and their binding capacity and neutralizing activity against SARS-CoV-2 were evaluated. Results A human-derived scFv antibody library against SARS-CoV-2 with a capacity of 1.56×10⁷ CFU was successfully constructed. Two specific scFv antibodies were screened from this library and expressed as full-length IgG antibodies (IgG-A10 and IgG-G6). IgG-A10 exhibited strong neutralizing activity against both the original SARS-CoV-2 strain (WT) and the XBB subvariant of the Omicron variant. However, the neutralizing activity of this antibody against the JN.1 sub lineage of the Omicron BA.2.86 variant was moderate. Conclusion This study has successfully constructed a human anti-SARS-CoV-2 scFv antibody library from the peripheral blood of recovered patients, and screened and expressed anti-SARS-CoV-2 IgG antibodies with neutralizing activity, laying a foundation for the prevention, diagnosis, and treatment of SARS-CoV-2 infection.
Humans ; Single-Chain Antibodies/genetics* ; SARS-CoV-2/immunology* ; COVID-19/immunology* ; Immunoglobulin G/genetics* ; Antibodies, Viral/genetics* ; Peptide Library ; Spike Glycoprotein, Coronavirus/immunology* ; Antibodies, Neutralizing/immunology* ; Leukocytes, Mononuclear/immunology* ; Broadly Neutralizing Antibodies/immunology*

OBJECTIVES: To assess the preliminary efficacy and safety of a dose-intensified C5VD regimen (cisplatin, 5-fluorouracil, vincristine, and doxorubicin) in children with locally advanced hepatoblastoma. METHODS: This prospective study enrolled 24 children with newly diagnosed, locally advanced hepatoblastoma who received the dose-intensified C5VD regimen at Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, and Shanghai Children's Hospital between January 2020 and December 2023. Clinical characteristics, treatment outcomes, and chemotherapy-related toxicities were analyzed. RESULTS: Of the 24 patients, 13 were male and 11 were female, with a median age at diagnosis of 18.7 months (range: 3.5-79.4 months). All patients achieved complete macroscopic resection of hepatic lesions without liver transplantation. Serum alpha-fetoprotein levels decreased significantly after two chemotherapy cycles. During a median follow-up of 38.4 months (range: 15.8-50.7 months), all patients maintained continuous complete remission, with 3-year event-free survival and overall survival rates of 100%. Across 144 chemotherapy cycles, the incidence rates of grade 3-4 neutropenia, thrombocytopenia, and infections were 97%, 77%, and 71%, respectively; no treatment-related deaths occurred. Notably, 5 patients (21%) developed Brock grade ≥3 hearing loss, of whom 1 required a hearing aid. CONCLUSIONS The dose-intensified C5VD regimen demonstrates significant efficacy with an overall favorable safety profile in the treatment of newly diagnosed, locally advanced pediatric hepatoblastoma. Grade 3-4 myelosuppression and infection are the predominant toxicities. However, high‑dose cisplatin-induced ototoxicity remains a concern, highlighting the need for improved otoprotective strategies.
Humans ; Hepatoblastoma/pathology* ; Male ; Female ; Infant ; Liver Neoplasms/pathology* ; Antineoplastic Combined Chemotherapy Protocols/therapeutic use* ; Child, Preschool ; Prospective Studies ; Doxorubicin/adverse effects* ; Child ; Cisplatin/adverse effects* ; Vincristine/adverse effects* ; Fluorouracil/adverse effects*

OBJECTIVE: To investigate the predictive value of the prognostic nutritional index (PNI) and systemic inflammatory response index (SIRI) for short-term efficacy and prognosis in newly treated patients with peripheral T-cell lymphoma (PTCL). METHODS: The general data, laboratory indicators, disease stage and other clinical data of 91 newly treated PTCL patients admitted to the Affiliated Hospital of Xuzhou Medical University from January 2015 to December 2023 were retrospectively analyzed. The optimal cutoff values for PNI and SIRI were determined using receiver operating characteristic (ROC) curves, and the patients were stratified into groups based on these cutoffs to compare clinical features and short-term efficacy between the different groups. Kaplan-Meier method was used to plot survival curves, and univariate and multivariate analyses were performed to identify the factors affecting overall survival (OS). RESULTS: The optimal cutoff values for PNI and SIRI were 45.30 and 1.74×10⁹/L, respectively. Patients in different PNI groups showed statistically significant differences in age, Ann Arbor stage, lactate dehydrogenase (LDH) level, international prognostic index (IPI), prognostic index for PTCL-not otherwise specified (PIT), pathological subtypes, and complete response (CR) rate (P < 0.05). PTCL patients in different SIRI groups exhibited significant differences in Ann Arbor stage, LDH level, IPI score, PIT score, and CR rate (P < 0.05). Logistic regression analysis showed that age ≥60 years old (OR =2.750), Ann Arbor stage Ⅲ-Ⅳ (OR =5.200), IPI score ≥2 (OR =7.650), low PNI (OR =3.296), and high SIRI (OR =3.130) were independent risk factors affecting treatment efficacy in PTCL patients (P < 0.05). Cox proportional hazards regression model analysis showed that low PNI and elevated β₂-microglobulin (β₂-MG) levels were independent risk factors affecting OS (P < 0.05). CONCLUSION PNI and SIRI have certain application value in evaluating short-term efficacy and prognosis in patients with PTCL. Compared with SIRI, PNI demonstrates greater predictive value for patient prognosis.
Humans ; Prognosis ; Lymphoma, T-Cell, Peripheral/therapy* ; Retrospective Studies ; Nutrition Assessment ; Male ; Female ; Middle Aged ; ROC Curve ; Inflammation

Computer-assisted methods for pathological image analysis can improve doctor's efficiency of image reading and diagnostic accuracy, effectively addressing the shortage of pathology diagnostic manpower. With the rapid development of artificial intelligence and digital pathology, deep learning technology has spurred a wealth of research in the field of histopathology. This article reviews the various applications of deep learning in digital pathological image analysis, such as pathological image segmentation, cancer auxiliary diagnosis, and cancer prognosis prediction, and discusses the challenges and solutions in its application. Furthermore, it predicts future trends in deep learning for pathological image analysis and proposes potential research directions.
Deep Learning ; Humans ; Image Processing, Computer-Assisted/methods* ; Artificial Intelligence ; Neoplasms