ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

ObjectiveTo observe the effects of Dihuang Yinzi （DY） on motor dysfunction in rats with advanced Parkinson's disease （PD） and to investigate the mechanisms by which DY improves advanced PD symptoms through the "gut microbiota-short-chain fatty acids （SCFAs）-inflammation-neuroprotection pathway". MethodsAn advanced PD rat model was induced by rotenone. Rats were divided into a normal group， model group， positive drug group （levodopa， 50 mg·kg^-1）， and DY low-， medium-， and high-dose groups （5.2， 10.4， 20.8 g·kg^-1）. After 7 days of administration， motor function was evaluated using the open-field， pole-climbing， and inclined plate tests. Hematoxylin-eosin （HE） staining was used to observe pathological changes in the substantia nigra and colon， and immunohistochemistry was performed to detect α-Synuclein （α-Syn） and tyrosine hydroxylase （TH） expression in the substantia nigra. Enzyme-linked immunosorbent assay （ELISA） was used to measure levels of dopamine （DA）， 5-hydroxytryptamine （5-HT）， 3，4-dihydroxyphenylacetic acid （DOPAC）， Levodopa， homovanillic acid （HVA）， tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， and interleukin-1β （IL-1β）. Western blot analysis was used to detect the expression of zonula occludens-1 （ZO-1） and occludin. Gut microbiota diversity was analyzed by 16S rRNA sequencing， and gas chromatography （GC） was used to determine the content of SCFAs in colonic contents. ResultsCompared with the normal group， the model group showed significantly decreased movement speed and distance in the open-field test， prolonged pole-climbing time， and reduced retention angle on the inclined plate （P<0.01）， accompanied by increased α-Syn expression （P<0.01） and decreased TH expression （P<0.01） in the brain. Compared with the model group， all DY dose groups improved motor dysfunction in advanced PD rats to varying degrees （P<0.05， P<0.01） and alleviated pathological damage in the brain and colon. High-dose DY significantly reduced α-Syn aggregation in the substantia nigra （P<0.01） and increased TH expression （P<0.01）. ELISA and Western blot results showed that， compared with the normal group， the model group exhibited decreased levels of DA， 5-HT， DOPAC， Levodopa， and HVA in the striatum （P<0.01）， increased levels of TNF-α， IL-6， and IL-1β in the colon and striatum （P<0.01）， and significantly reduced expression of ZO-1 （P<0.05） and occludin in the colon （P<0.01）. Compared with the model group， all DY dose groups increased the levels of DA， 5-HT， DOPAC， Levodopa， and HVA in the striatum to varying degrees （P<0.05， P<0.01）. In the high-dose DY group， the levels of TNF-α， IL-6， and IL-1β in the colon and striatum were reduced （P<0.01）， while the expression of ZO-1 （P<0.05） and occludin in the intestine was increased. The 16S rRNA sequencing results indicated that the relative abundances of Actinobacteriota， Enterobacteriaceae， and Erysipelotrichaceae were increased in the model group， whereas the relative abundances of Bacteroidota， class Clostridia， Lachnospiraceae， and Akkermansia muciniphila were decreased. These changes were effectively reversed after high-dose DY intervention. GC analysis showed that the content of SCFAs in the colonic contents of rats in the model group was decreased （P<0.05， P<0.01）， while after high-dose DY intervention， the levels of acetate， propionate， isobutyrate， and butyrate were significantly increased （P<0.05， P<0.01）. ConclusionDY may exert therapeutic effects in advanced PD by regulating the gut microbiota-SCFAs-inflammation pathway.

BACKGROUND: Telesurgery has the potential to overcome spatial limitations for surgeons, which depends on surgical robot and the quality of network communication. However, the influence of network latency and bandwidth on telesurgery is not well understood. METHODS: A telesurgery system capable of dynamically adjusting image compression ratios in response to bandwidth changes was established between Beijing and Sanya (Hainan province), covering a distance of 3000 km. In total, 108 animal operations, including 12 surgical procedures, were performed. Total latency ranging from 170 ms to 320 ms and bandwidth from 15-20 Mbps to less than 1 Mbps were explored using designed surgical tasks and hemostasis models for renal vein and internal iliac artery rupture bleeding. Network latency, jitter, frame loss, and bit rate code were systemically measured during these operations. National Aeronautics and Space Administration Task Load Index (NASA-TLX) and a self-designed scale measured the workload and subjective perception of surgeons. RESULTS: All 108 animal telesurgeries, conducted from January 2023 to June 2023, were performed effectively over a total duration of 3866 min. The operations were completed with latency up to 320 ms and bandwidths as low as 1-5 Mbps. Hemostasis for vein and artery rupture bleeding models was effectively achieved under these low bandwidth conditions. The NASA-TLX results indicated that latency significantly impacted surgical performance more than bandwidth and image clarity reductions. CONCLUSIONS This telesurgery system demonstrated safety and reliability. A total of 320 ms latency is acceptable for telesurgery operations. Reducing image clarity can effectively mitigate the potential latency increase caused by decreased bandwidth, offering a new method to reduce the impact of latency on telesurgery.
Animals ; Robotic Surgical Procedures/methods* ; Laparoscopy/methods*

BACKGROUND: Pancreatic cancer is a lethal malignancy prone to gemcitabine resistance. The single-strand selective monofunctional uracil DNA glycosylase (SMUG1), which is responsible for initiating base excision repair, has been reported to predict the outcomes of different cancer types. However, the function of SMUG1 in pancreatic cancer is still unclear. METHODS: Gene and protein expression of SMUG1 as well as survival outcomes were assessed by bioinformatic analysis and verified in a cohort from Fudan University Shanghai Cancer Center. Subsequently, the effect of SMUG1 on proliferation, cell cycle, and migration abilities of SMUG1 cells were detected in vitro . DNA damage repair, apoptosis, and gemcitabine resistance were also tested. RNA sequencing was performed to determine the differentially expressed genes and signaling pathways, followed by quantitative real-time polymerase chain reaction and Western blotting verification. The cancer-promoting effect of forkhead box Q1 (FOXQ1) and SMUG1 on the ubiquitylation of myelocytomatosis oncogene (c-Myc) was also evaluated. Finally, a xenograft model was established to verify the results. RESULTS: SMUG1 was highly expressed in pancreatic tumor tissues and cells, which also predicted a poor prognosis. Downregulation of SMUG1 inhibited the proliferation, G1 to S transition, migration, and DNA damage repair ability against gemcitabine in pancreatic cancer cells. SMUG1 exerted its function by binding with FOXQ1 to activate the Protein Kinase B (AKT)/p21 and p27 pathway. Moreover, SMUG1 also stabilized the c-Myc protein via AKT signaling in pancreatic cancer cells. CONCLUSIONS SMUG1 promotes proliferation, migration, gemcitabine resistance, and c-Myc protein stability in pancreatic cancer via protein kinase B signaling through binding with FOXQ1. Furthermore, SMUG1 may be a new potential prognostic and gemcitabine resistance predictor in pancreatic ductal adenocarcinoma.
Humans ; Pancreatic Neoplasms/pathology* ; Forkhead Transcription Factors/genetics* ; Signal Transduction/genetics* ; Animals ; Cell Line, Tumor ; Proto-Oncogene Proteins c-akt/metabolism* ; Cell Proliferation/physiology* ; Mice ; Uracil-DNA Glycosidase/genetics* ; Female ; Male ; Gemcitabine ; Mice, Nude ; Apoptosis/physiology* ; Deoxycytidine/analogs & derivatives* ; Cell Movement/genetics*

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

To address the challenges faced by current brain midline segmentation techniques, such as insufficient accuracy and poor segmentation continuity, this paper proposes a deep learning network model based on a two-stage framework. On the first stage of the model, prior knowledge of the feature consistency of adjacent brain midline slices under normal and pathological conditions is utilized. Associated midline slices are selected through slice similarity analysis, and a novel feature weighting strategy is adopted to collaboratively fuse the overall change characteristics and spatial information of these associated slices, thereby enhancing the feature representation of the brain midline in the intracranial region. On the second stage, the optimal path search strategy for the brain midline is employed based on the network output probability map, which effectively addresses the problem of discontinuous midline segmentation. The method proposed in this paper achieved satisfactory results on the CQ500 dataset provided by the Center for Advanced Research in Imaging, Neurosciences and Genomics, New Delhi, India. The Dice similarity coefficient (DSC), Hausdorff distance (HD), average symmetric surface distance (ASSD), and normalized surface Dice (NSD) were 67.38 ± 10.49, 24.22 ± 24.84, 1.33 ± 1.83, and 0.82 ± 0.09, respectively. The experimental results demonstrate that the proposed method can fully utilize the prior knowledge of medical images to effectively achieve accurate segmentation of the brain midline, providing valuable assistance for subsequent identification of the brain midline by clinicians.
Humans ; Brain/diagnostic imaging* ; Deep Learning ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Magnetic Resonance Imaging/methods* ; Neural Networks, Computer

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

OBJECTIVE: The role of cold spells of different intensities in the economic burden of death is crucial for health adaptation to climate change, especially in a multi-site setting. The objective of the study was to explore the economic burden of mortality attributable to cold spells. METHODS: We performed a two-stage time-series analysis using the Value of Statistical Life (VSL) approach to evaluate the economic impact of mortality related to cold spells of varying lengths and intensities. This analysis employed a case-crossover design, with a distributed lag nonlinear model (DLNM) used for analysis. Analysis was stratified according to age, sex, and region of origin. The results of the assessment show that cold spells have an enormous impact on the economic losses of mortality due to climate change and aging. RESULTS: Totally, 8.3% (95% CI: 0.0%, 16.0%) to 13.8% (95% CI: 1.0%, 24.8%) of VSL were ascribed to cold spells, accounting for economic losses of 4.71 (95% CI: 0.34, 8.47) to 11.45 (95% CI: 0.00, 21.00) billion CNY, in the cold season. The population aged over 65 y and females are particularly vulnerable. Economic impacts in warmer regions, such as the southern and subtropical zones, are more extensive than those in the northern and temperate zones. CONCLUSION Customizing cold spell prevention measures for vulnerable populations or regions is vital to alleviating the socioeconomic burden.
China/epidemiology* ; Humans ; Female ; Male ; Cold Temperature/adverse effects* ; Aged ; Middle Aged ; Adult ; Mortality ; Infant ; Child ; Adolescent ; Child, Preschool ; Young Adult ; Climate Change ; Aged, 80 and over ; Cost of Illness ; Infant, Newborn