Objective: To evaluate the long-term effectiveness of an intelligent blood transfusion system in intraoperative blood management by comparing its performance with clinicians' decisions. Methods: A retrospective analysis of 26 760 surgical cases (2017-2024) was conducted, comparing pre- and post-implementation (2017-2019 vs 2020-2024) metrics, including transfusion prediction accuracy, rationality of blood use, and clinical outcomes. The system, powered by XGBoost, integrated patient demographics, laboratory results, and surgical data to predict red blood cell transfusion needs. Results: The intelligent blood transfusion systems achieved an accuracy of 80.62% in predicting transfusion necessity, significantly outperforming clinicians (24.83%, P<0.001). Its blood-use rationality rate was 83.92% vs 18.02% for clinicians (P<0.001). Post-implementation, major surgeries (grades Ⅲ-Ⅳ) increased while the requested blood units decreased. High physician compliance (>75%) correlated with 88.18% rationality. Conclusion: The intelligent blood transfusion system significantly improves the accuracy of transfusion decision-making, reduces excessive red blood cell use, optimizes perioperative transfusion management, and enhances the utilization of blood medical resources.

Objective:To investigate the influencing factors for sarcopenia in hospitalized patients,to construct a risk prediction model for sarcopenia in elderly hospitalized patients,and to provide a quantitative tool for early screening and intervention of sarcopenia based on the integration of multi-dimensional indicators.Methods:A retrospective analysis was performed for the data of 2105 elderly patients who were hospitalized in The First Affiliated Hospital of Chongqing Medical University from March 2016 to June 2023.The least absolute shrinkage and selection operator analysis was used for the screening of variables,and the logistic regression analysis was used to investigate the influencing factors for sarcopenia.A predictive model was constructed,and internal and external validation was performed.The Shapley additive explanations model was used to analyze feature contributions,and a nomogram model was constructed to visualize and interpret the results.Results:The 1259 patients from March 2016 to December 2020 were randomly divided into a training set with 882 patients and an internal test set with 377 patients at a ratio of 7∶3,and the 846 patients from January 2021 to June 2023 were established as the external validation set.A total of 489 cases of sarcopenia(55.44%)were detected in the training set.The logistic regression analysis based on the training set showed that asthenia,dependence on Activity of Daily Living,malnutrition,and in-creasing age were risk factors for sarcopenia(odds ratio[OR]>1,P<0.05),and male sex,normal body mass index,and overweight were protective factors against sarcopenia(OR<1,P<0.05).The model had an AUC of 0.876(95%CI=0.854-0.899)in the training set,0.883(95%CI=0.849-0.918)in the internal test set,and 0.750(95%CI=0.717-0.783)in the external validation set,suggesting that the model had good performance.The decision curve analysis showed that the nomogram model had a good clinical value.Conclu-sion:The predictive model for sarcopenia has good performance and holds promise for clinical application.

Objective:To summarize the clinicopathologic characteristics of malignant hypertension (MHT) patients with acute kidney injury (AKI) and application of renin-angiotensin-aldosterone system inhibitor (RAASi).Methods:It was a retrospective cohort study. The adult patients with MHT and AKI admitted to Peking University First Hospital from January 1, 2012 to July 14, 2022. The patients were categorized into RAASi group and non-RAASi group based on RAASi administration from AKI onset to discharge. The clinicopathological data between the two groups were compared, and application of RAASi was analyzed.Results:A total of 179 patients were enrolled with age of 31 (26, 37) years and 148 males (82.7%). Ninety-five patients (53.1%) received dialysis treatment. The common causes of MHT were essential hypertension (125 patients, 69.8%), renal hypertension (39 patients, 21.8%) and endocrine hypertension (7 patients, 3.9%). AKI severity distribution showed 41 patients (22.9%) in stage 1, 1 patient (0.5%) in stage 2 and 137 patients (76.5%) in stage 3. Among MHT patients, 94 patients (52.5%) had been treated with RAASi before AKI, and 13 patients (7.3%) discontinued RAASi after AKI. Among 85 patients (47.5%) without receiving RAASi treatment before AKI, 68 new patients (38.0%) received RAASi treatment after AKI, and 40 patients (22.3%) were treated with the support of dialysis. Compared with non-RAASI group ( n=30), proportions of chronic kidney disease ( χ2=6.324, P=0.012) and post-AKI hyperkalemia ( χ2=4.048, P=0.044) in RAASi group ( n=149) were lower, and the proportion of dialysis treatment ( χ2=5.638, P=0.018), admission diastolic blood pressure ( Z=-3.609, P<0.001) and maximum diastolic blood pressure during hospitalization ( Z=-1.978, P=0.048) were higher. There were no statistically significant differences in the rates of target blood pressure control and renal function recovery between the two groups during hospitalization (all P>0.05). During hospitalization, 64 patients received renal biopsies, of which 50 patients (78.1%) had typical MHT vascular lesions such as "onion skin" in renal arterioles. Twenty-seven patients (42.2%) were complicated with glomerular diseases, and IgA nephropathy was the most common type (85.2%, 23/27). The proportions of glomerular ischemia and sclerosis, endothelial cell proliferation and acute renal tubular injury in RAASi group ( n=54) were lower than those in non-RAASi group ( n=10), and proportions of thrombosis and "onion skin" change were higher than those in RAASi group ( n=10), but the differences were not statistically significant (all P>0.05). Renal function recovery occurred in 47 patients (26.3%) by discharge. Among 95 dialysis patients, 26 patients (27.4%) achieved dialysis independence at discharge. Conclusions:MHT patients with AKI exhibit severe renal pathology and short-term poor prognosis. RAASi is primarily prescribed to those with relatively better kidney function or those receiving dialysis support.

Gliomas, with their infiltrative growth and malignant potential, present considerable therapeutic challenges. Maximal safe resection is essential for optimizing patient survival and quality of life. Despite this, existing intraoperative visualization techniques suffer from limited sensitivity and accuracy. Label-free Raman spectroscopy has emerged as a non-invasive, rapidly diagnostic, and highly accurate technique. It accurately diagnoses tumors, identifies infiltration margins, and classifies molecular subtypes, enhancing the precision of glioma surgery. This review summarizes the latest advances and applications of label-free Raman spectroscopy in glioma surgery.

Objective:To quantify thoracic and abdominal movements during breathing using inertial measurement units (IMUs) and to build a machine learning model which identifies the abdominal breathing (AB) pattern.Methods:Ten rehabilitation therapists formed the study′s professional group, while 15 patients receiving AB training comprised the validation group. Two synchronized IMUs were applied to capture breathing motions during natural breathing (NB), deep breathing (DB) and AB. Six kinematic features were extracted from each respiratory cycle, and inter-group and inter-pattern differences were analyzed. Correlation analysis was also performed with manually measured changes in thoracic and abdominal circumferences. A support vector classification model for AB pattern detection was then developed using data from the professional and validation groups.Results:A total of 1113 respiratory cycles were extracted and analyzed. The breathing pattern significantly influenced all of the kinematic features studied (0.21≤partial η 2≤0.65, all P≤0.001). The ranges of the angles in medial-lateral axis of the IMUs showed strong correlation with the changes in abdominal and thoracic circumferences (ρ1=0.928, ρ2=0.807, P≤0.001 in both cases). A greater range of abdominal angles was found during AB compared to the other patterns. The best of the models achieved an F1 score of 0.970 (sensitivity: 0.983, specificity: 0.980) in validation. Conclusions:AB generates the greatest abdominal movement. Combining IMUs and machine learning can provide real-time quantification of chest movement and accurate detection of AB during breathing training.

The importance of gait assessment in the rehabilitation of cancer patients is gradually being recognized. However, quantitative analysis of balance ability in cancer patients is still limited. A total of 102 cancer patients meeting the inclusion criteria were recruited from Hefei Cancer Hospital, Chinese Academy of Sciences. Their balance ability was evaluated using the Berg Balance Scale (BBS). Gait data were collected by an electronic walkway and an IMU sensor system, including spatial-temporal and kinematic gait features such as step length, cadence, support time, and range of motion. Recursive feature elimination was used for feature selection. Ridge, Elastic Net, SVR, RF, and AdaBoost models were used to predict balance ability scores. Five-fold cross-validation was used to evaluate the performance of these models. Results show that the SVR model achieves the best performance with fifteen features (RMSE=3.22, R ²=0.91), followed by Ridge (RMSE=3.63, R ²=0.89). A method for evaluating balance ability based on gait features is proposed, providing a quantitative tool for personalized rehabilitation interventions in cancer patients.
Humans ; Postural Balance ; Neoplasms/rehabilitation* ; Gait ; Gait Analysis ; Biomechanical Phenomena ; Female

Objective:To investigate the feasibility and safety of implementing a domestic vehicle-mounted remote mobile robotic surgical system in thyroid surgery applications, integrated with 5G communication technology.Methods:Using the main system located on the vehicle-mounted mobile robot operating platform of the 960th Hospital of PLA Joint Logistics Support Force and the slave system of Weifang Traditional Chinese Hospital, the remote radical thyroidectomy 5G communication technology, and analyze the clinical and information transmission data of two female patients who underwent remote mobile robot thyroid cancer surgery on October 21, 2024 at Weifang Traditional Chinese Medicine Hospital.Results:The remote radical thyroidectomy was conducted by the robosurgeons utilizing a vehicle-mounted mobile robotic surgical system, and the procedure was successfully completed without necessitating intermediate open surgery. The operation durations for patient 1 and patient 2 were 135 minutes and 108 minutes, respectively, with 7 and 13 lymph nodes dissected, respectively. The average delay in surgical data transmission was recorded at 61.9 milliseconds, with no instances of signal interruption or frame loss. The procedure proceeded smoothly, without any jamming, and the audio and video transmissions were consistently clear. Follow up for 21 days after surgery showed no complications such as hoarseness, skin damage, or lymphatic fistula.Conclusion:The implementation of a vehicle-mounted remote mobile robotic surgery system for thyroid surgery has demonstrated safety and feasibility. Furthermore, the utilization of the 5G network offers rapid data transmission and minimal latency, closely approximating the therapeutic efficacy of traditional robotic thyroidectomy.

High mobility group box 1 (HMGB1), when released extracellularly, plays a pivotal role in the development of spinal cord synapses and exacerbates autoimmune diseases within the central nervous system. In experimental autoimmune encephalomyelitis (EAE), a condition that models multiple sclerosis, the levels of extracellular HMGB1 and interleukin-33 (IL-33) have been found to be inversely correlated. However, the mechanism by which IL-33 deficiency enhances HMGB1 release during EAE remains elusive. Our study elucidates a potential signaling pathway whereby the absence of IL-33 leads to increased binding of P300/CBP-associated factor with HMGB1 in the nuclei of astrocytes, upregulating HMGB1 acetylation and promoting its release from astrocyte nuclei in the spinal cord of EAE mice. Conversely, the addition of IL-33 counteracts the TNF-α-induced increase in HMGB1 and acetylated HMGB1 levels in primary astrocytes. These findings underscore the potential of IL-33-associated signaling pathways as a therapeutic target for EAE treatment.
Animals ; Encephalomyelitis, Autoimmune, Experimental/metabolism* ; Astrocytes/metabolism* ; Interleukin-33/metabolism* ; HMGB1 Protein/metabolism* ; Acetylation ; Mice, Knockout ; Mice, Inbred C57BL ; p300-CBP Transcription Factors/metabolism* ; Mice ; Spinal Cord/metabolism* ; Cells, Cultured ; Female ; Signal Transduction

Atopic dermatitis (AD) is a prevalent inflammatory skin disorder in which patients experience recurrent eczematous lesions and intense itching. The colonization of Staphylococcus aureus (S. aureus) is correlated with the severity of the disease, but its role in AD development remains elusive. Using single-cell RNA sequencing, we uncovered that keratinocytes activate a distinct immune response characterized by induction of Il24 when exposed to methicillin-resistant S. aureus (MRSA). Further experiments using animal models showed that the administration of recombinant IL-24 protein worsened AD-like pathology. Genetic ablation of Il24 or the receptor Il20rb in keratinocytes alleviated allergic inflammation and atopic march. Mechanistically, IL-24 acted through its heterodimeric receptors on keratinocytes and augmented the production of IL-33, which in turn aggravated type 2 immunity and AD-like skin conditions. Overall, these findings establish IL-24 as a critical factor for onset and progression of AD and a compelling therapeutic target.
Dermatitis, Atopic/genetics* ; Interleukins/metabolism* ; Animals ; Methicillin-Resistant Staphylococcus aureus/immunology* ; Mice ; Keratinocytes/microbiology* ; Humans ; Interleukin-33/immunology* ; Inflammation/microbiology* ; Staphylococcal Infections/microbiology* ; Disease Models, Animal ; Hypersensitivity/microbiology* ; Mice, Inbred C57BL

Objective:To analyze the status quo of medical resources allocation of midwifery institutions in Shenzhen,to measure the spatial accessibility of the midwifery institutions,to give the optimal location of new midwifery institutions,and to optimize the allocation of midwifery medical resources.Methods:The spatial accessibility of midwifery institutions was accurately measured using the two-step moving search method,and the spatial layout optimization analysis was carried out using the model of maximum coverage site selection problem.Results:(1)There is obvious spatial heterogeneity in the accessibility of midwifery institutions in Shenzhen,with the accessibility of the western region higher than that of the eastern region,and that of the urban center higher than the peripheral region;(2)the accessibility of midwifery institutions in Shenzhen is obviously affected by factors such as demography,economy,topography,and road network;(3)after simulating the addition of new midwifery institutions by using the maximal-coverage siting model,the accessibility of midwifery institutions in various districts of Shenzhen rises significantly.Conclusion:(1)to formulate urban maternal and child health care resource plans based on accurate portraits of regional populations;(2)to use the advantages of digital intelligence technology to drive the optimization of the layout and radiation of high-quality maternal and child health care resources;(3)and to give priority to establish maternal and child medical institutions in low-accessibility areas and special medical bus lines.