Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

To guide transfusion practice in critically ill children who often need plasma and platelet transfusions, the Transfusion and Anemia Expertise Initiative-Control/Avoidance of Bleeding (TAXI-CAB) developed Recommendations and Expert Consensus for Plasma and Platelet Transfusion Practice in Critically Ill Children. This guideline addresses 53 recommendations related to plasma and platelet transfusion in critically ill children with 8 kinds of diseases, laboratory testing, selection/treatment of plasma and platelet components, and research priorities. This paper introduces the specific methods and results of the recommendation formation of the guideline.

ObjectiveTo analyze the changes in the degree of coordination of China's major epidemic prevention and control efforts before and after the outbreak of the Corona Virus Disease 2019 (COVID-19), so as to explore the impact of epidemic prevention and control measures on coordination dynamics. MethodsA total of 3 864 policy documents related to epidemic prevention and control from January 2000 to December 2020 across 31 provinces (autonomous regions, and municipalities) in China were systematically collected. Contents specific to collaborative and cooperative efforts were extracted, and the extent of interdepartmental coordination were quantified to assess the effectiveness of epidemic prevention and control efforts. Wilcoxon signed-rank test was adopted to statistically analyze the differences between the indicators before and after the epidemic. ResultsThe average overall coordination level for major epidemic prevention and control in 31 provinces (autonomous regions, and municipalities) increased from 43.06% to 97.62%, and the average coordination levels in the eastern, central, and western China soared from 42.29%, 37.50%, and 47.46%, to 98.81%, 96.20%, and 97.46%, respectively, with statistically significant differences (all P<0.05). In terms of department categorization, coordination levels in the professional departments and the key support departments peaked at 100.00%, while other support departments rose to 95.43%, with an increase of 77.15%, 181.85%, and 139.89%, respectively, exhibiting noteworthy statistically significant differences (all P<0.001). ConclusionThe scope of coordination departments of China’s major epidemic prevention and control exists a remarkable surge following the COVID-19 outbreak, notable heightened coordination is particularly observed among the key support departments. Future endeavors should prioritize the roles played by diverse departments in epidemic prevention and control, enhancing both the clarity of departmental responsibilities and the effectiveness of interdepartmental coordination.

ObjectiveTo systematically evaluate the public health governance capacity of 40 cities in Jiangsu, Zhejiang, and Anhui Provinces, providing a scientific evaluation basis for building a "Healthy Yangtze River Delta". MethodsA comprehensive collection of policy documents, public information reports, and research literature related to public health governance capacity in Jiangsu, Zhejiang, and Anhui Provinces was conducted, totaling 6 920 policy documents, 1 720 information reports, and 1 200 literature pieces. Based on the evaluation standards for an appropriate public health system established by the research team, the basic status of public health governance capacity was assessed to identify the strengths and weaknesses of the 40 cities. ResultsIn 2022, the public health governance capacity score for the 40 cities in Jiangsu, Zhejiang, and Anhui Provinces was (562.5±38.0) points. In terms of specific areas, the emergency response field received the highest score of (791.4±49.7) points, while the chronic disease prevention and control field received the lowest score of (368.2±29.6) points. The Jiangsu-Zhejiang-Anhui region has largely achieved the strategic priority of health, gradually improved public health legal regulations, and established a basic organizational framework with a solid foundation for information and data infrastructure. However, challenges still need to be addressed, such as unstable government funding for public health, unclear departmental responsibilities, and barriers to information interoperability. ConclusionThe public health governance capacity of the 40 cities in Jiangsu, Zhejiang, and Anhui Province has been at a moderate level, but disparities have still existed across regions and fields. In the future, while continuing to deepen existing advantages, it is essential to accurately identify the causes of problems, establish a long-term and stable investment mechanism, enhance information connectivity mechanisms, further clarify departmental responsibilities, and promote the achievement of the "Healthy Yangtze River Delta" goal.

ObjectiveIn nature, objects cast shadows due to illumination, forming the basis for stereoscopic perception. Birds need to adapt to changes in lighting (meaning they can recognize stereoscopic shapes even when shadows look different) to accurately perceive different three-dimensional forms. However, how neurons in the key visual brain area in birds handle these lighting changes remains largely unreported. In this study, pigeons (Columba livia) were used as subjects to investigate how neurons in pigeon’s ventrolateral mesopallium (MVL) represent stereoscopic shapes consistently, regardless of changes in lighting. MethodsVisual cognitive training combined with neuronal recording was employed. Pigeons were first trained to discriminate different stereoscopic shapes (concave/convex). We then tested whether and how light luminance angle and surface appearance of the stereoscopic shapes affect their recognition accuracy, and further verify whether the results rely on specify luminance color. Simultaneously, neuronal firing activity of neurons was recorded with multiple electrode array implanted from the MVL during the presentation of difference shapes. The response was finally analyzed how selectively they responded to different stereoscopic shapes and whether their selectivity was affected by the changes of luminance condition (like lighting angle) or surface look. Support vector machine (SVM) models were trained on neuronal population responses recorded under one condition (light luminance angle of 45°) and used to decode responses under other conditions (light luminance angle of 135°, 225°, 315°) to verify the invariance of responses to different luminance conditions. ResultsBehavioral results from 6 pigeons consistently showed that the pigeons could reliably identify the core 3D shape (over 80% accuracy), and this ability wasn’t affected by changes in light angle or surface appearance. Statistical analysis of 88 recorded neurons from 6 pigeons revealed that 83% (73/88) showed strong selectivity for specific 3D shapes (selectivity index>0.3), and responses to convex shapes were consistently stronger than to concave shapes. These shape-selective responses remained stable across changes in light angle and surface appearance. Neural patterns were consistent under both blue and orange lighting. The decoding accuracy achieves above 70%, suggesting stable responses under different conditions (e.g., different lighting angles or surface appearance). ConclusionNeurons in the pigeon MVL maintain a consistent neural encoding pattern for different stereoscopic shapes, unaffected by illumination or surface appearance. This ensures stable object recognition by pigeons in changing visual environments. Our findings provide new physiological evidence for understanding how birds achieve stable perception (“invariant neural representations”) while coping with variations in the visual field.

OBJECTIVE: To compare the accuracy and effectiveness of orthopaedic robot-assisted minimally invasive surgery versus open surgery for limb osteoid osteoma. METHODS: A clinical data of 36 patients with limb osteoid osteomas admitted between June 2016 and June 2023 was retrospectively analyzed. Among them, 16 patients underwent orthopaedic robot-assisted minimally invasive surgery (robot-assisted surgery group), and 20 patients underwent tumor resection after lotcated by C-arm X-ray fluoroscopy (open surgery group). There was no significant difference between the two groups in the gender, age, lesion site, tumor nidus diameter, and preoperative pain visual analogue scale (VAS) scores ( P>0.05). The operation time, lesion resection time, intraoperative blood loss, intraoperative fluoroscopy frequency, lesion resection accuracy, and postoperative analgesic use frequency were recorded and compared between the two groups. The VAS scores for pain severity were compared preoperatively and at 3 days and 3 months postoperatively. RESULTS: Compared with the open surgery group, the robot-assisted surgery group had a longer operation time, less intraoperative blood loss, less fluoroscopy frequency, less postoperative analgesic use frequency, and higher lesion resection accuracy ( P<0.05). There was no significant difference in lesion resection time ( P>0.05). All patients were followed up after surgery, with a follow-up period of 3-24 months (median, 12 months) in the two groups. No postoperative complication such as wound infection or fracture occurred in either group during follow-up. No tumor recurrence was observed during follow-up. The VAS scores significantly improved in both groups at 3 days and 3 months after surgery when compared with preoperative value ( P<0.05). The VAS score at 3 days after surgery was significantly lower in robot-assisted surgery group than that in open surgery group ( P<0.05). However, there was no significant difference in VAS scores at 3 months between the two groups ( P>0.05). CONCLUSION Compared with open surgery, robot-assisted resection of limb osteoid osteomas has longer operation time, but the accuracy of lesion resection improve, intraoperative blood loss reduce, and early postoperative pain is lighter. It has the advantages of precision and minimally invasive surgery.
Humans ; Robotics ; Osteoma, Osteoid/surgery* ; Orthopedics ; Blood Loss, Surgical ; Retrospective Studies ; Neoplasm Recurrence, Local ; Minimally Invasive Surgical Procedures ; Bone Neoplasms/surgery* ; Analgesics ; Treatment Outcome

Intermittent theta burst stimulation (iTBS), a time-saving and cost-effective repetitive transcranial magnetic stimulation regime, has been shown to improve cognition in patients with Alzheimer's disease (AD). However, the specific mechanism underlying iTBS-induced cognitive enhancement remains unknown. Previous studies suggested that mitochondrial functions are modulated by magnetic stimulation. Here, we showed that iTBS upregulates the expression of iron-sulfur cluster assembly 1 (ISCA1, an essential regulatory factor for mitochondrial respiration) in the brain of APP/PS1 mice. In vivo and in vitro studies revealed that iTBS modulates mitochondrial iron-sulfur cluster assembly to facilitate mitochondrial respiration and function, which is required for ISCA1. Moreover, iTBS rescues cognitive decline and attenuates AD-type pathologies in APP/PS1 mice. The present study uncovers a novel mechanism by which iTBS modulates mitochondrial respiration and function via ISCA1-mediated iron-sulfur cluster assembly to alleviate cognitive impairments and pathologies in AD. We provide the mechanistic target of iTBS that warrants its therapeutic potential for AD patients.
Humans ; Mice ; Animals ; Transcranial Magnetic Stimulation ; Alzheimer Disease/therapy* ; Cognitive Dysfunction/therapy* ; Cognition ; Sulfur ; Iron ; Iron-Sulfur Proteins ; Mitochondrial Proteins

Adaptive immunity is a critical component of the human immune system, playing an essential role in identifying antigens and orchestrating a tailored immune response. This review delves into the significant strides made in the development of epitope prediction tools, their integration into vaccine design, and their pivotal role in enhancing immunotherapy strategies. The review emphasizes the transformative potential of these tools in refining our understanding and application of immune responses. Adaptive immunity distinguishes itself from innate immunity by its ability to recognize specific antigens and remember past infections, leading to quicker and more effective responses upon subsequent exposures. This facet of immunity involves complex interactions between various cell types, primarily B cells and T cells, which recognize distinct epitopes presented by antigens. Epitopes are small sequences or configurations on antigens that are recognized by the immune receptors on B cells and T cells, acting as the focal points of immune recognition and response. Epitopes can be broadly classified into two types: linear (or sequential) epitopes and conformational (or discontinuous) epitopes. Linear epitopes consist of a sequence of amino acids in a protein that are recognized by B cells and T cells in their primary structure form. Conformational epitopes, on the other hand, are formed by spatially distinct amino acids that come together in the tertiary structure of the protein, often recognized by the immune system only when the protein folds into its native conformation. The role of epitopes in the immune response is critical as they are the primary triggers for the activation of B cells and T cells. When an epitope is recognized, it can stimulate B cells to produce antibodies, mobilize helper T cells to secrete cytokines, or prompt cytotoxic T cells to kill infected cells. These actions form the basis of the adaptive immune response, tailored to eliminate specific pathogens or infected cells effectively. The prediction of B cell and T cell epitopes has evolved with advances in computational biology, leading to the development of several sophisticated tools that utilize a variety of algorithms to predict the likelihood of epitope regions on antigens. Tools employing machine learning methods, such as support vector machines (SVMs), XGBoost, random forest, analyze large datasets of known epitopes to classify new sequences as potential epitopes based on their similarity to known data. Moreover, deep learning has emerged as a powerful method in epitope prediction, leveraging neural networks capable of learning high-dimensional data from vast amounts of immunological inputs to identify patterns that may not be evident to other predictive models. Deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs) and ESM protein language model have demonstrated superior accuracy in mapping the nonlinear relationships inherent in protein structures and epitope interactions. The application of epitope prediction tools in vaccine design is transformative, enabling the development of epitope-based vaccines that can elicit targeted immune responses against specific parts of the pathogen. These vaccines, by focusing the immune response on highly specific regions of the pathogen, can offer high efficacy and reduced side effects. Similarly, in cancer immunotherapy, epitope prediction tools help identify tumor-specific antigens that can be targeted to develop personalized immunotherapeutic strategies, thereby enhancing the precision of cancer treatments. The future of epitope prediction technology appears promising, with ongoing advancements anticipated to enhance the precision and efficiency of these tools further. The integration of broader immunological data, such as patient-specific immune profiles and pathogen variability, along with advances in AI and machine learning, will likely drive the development of more adaptive, robust, and clinically relevant prediction models. This will not only improve the effectiveness of vaccines and immunotherapies but also contribute to our broader understanding of immune mechanisms, potentially leading to breakthroughs in the treatment and prevention of multiple diseases. In conclusion, the development and refinement of epitope prediction tools stand as a cornerstone in the advancement of immunological research and therapeutic design, highlighting a path toward more precise and personalized medicine. The ongoing integration of computational models with experimental immunology holds the promise of revolutionizing our approach to combating infectious diseases and cancer.

ObjectiveSpatial working memory (SWM) is an important function in cognitive behavior, and working memory impairment can seriously affect the patient’s life and cause great stress to the patient. Intermittent theta burst stimulation (iTBS) has been shown to regulate working memory function by entrainment of neural oscillations in different frequencies of the brain, but its regulation of working memory-related neural oscillations and their synchronization is not clear. The purpose of this study was to study the effect of iTBS on neural oscillation and synchronization in local and transbrain regions of rats, and to explore the mechanism of iTBS in regulating working memory. MethodsTwenty-four rats were randomly divided into four groups according to their age and whether they received iTBS stimulation (AS: adult stimulation group, AC: adult control group, ES: elderly stimulation group, EC: elderly control group). Using the methods of time-frequency distribution, phase synchronization and phase-amplitude coupling analysis, the changes of local field potential signal neural oscillations in the prefrontal and hippocampal brain regions of theta and gamma bands in the process of spatial working memory behavioral tasks in each group of rats were compared and analyzed, and the relationship between the changes of neural oscillations in the two brain regions and the changes in spatial working memory ability of rats was judged based on the Pearson correlation coefficient. ResultsWith the increase of age, the time taken by the elderly rats to learn the spatial working memory task rules increased significantly (P=0.005 6), and the time taken by iTBS stimulation to learn the SWM task rules in adult rats (P=0.001 1) and elderly rats(P=0.009 0) was shortened. At the same time, compared with adult rats, the time-frequency energy of theta and gamma band neural oscillations in the prefrontal and hippocampal brain regions of elderly rats (theta: P<0.000 1; gamma: P<0.000 1) and phase-amplitude coupling across brain regions (PFC-HPC: P=0.000 2; HPC-PFC:P=0.027 7) decreased to a certain extent, and iTBS stimulation could increase the time-frequency energy of neural oscillations of adult rats (theta: P<0.000 1; gamma: P<0.000 1) and elderly rats (theta: P=0.014 4; gamma:P=0.000 6) and the phase-amplitude coupling effect across brain regions in elderly rats (PFC-HPC: P=0.018 0; HPC-PFC: P=0.022 1). In addition, the time-frequency energy and phase-amplitude coupling of signals in each frequency band of the two brain regions were positively correlated with the behavioral accuracy of rats, while the phase synchronization of theta band and gamma band neural oscillations in the two brain regions during working memory was not correlated with the behavioral accuracy. ConclusioniTBS can enhance SWM ability and cognitive function in elderly rats, and this improvement is associated with increased coupling of time-frequency energy and cross-brain phase amplitude of neural oscillations across theta and gamma bands during SWM tasks. Similarly, in adult rats, iTBS enhances SWM ability and cognitive function by increasing the time-frequency energy of theta and gamma band neural oscillations in both brain regions during SWM tasks. Furthermore, in addition to the main findings, this study provides evidence supporting the state-dependent effects of iTBS stimulation to some extent.