Direct electrical stimulation of the human cortex can produce subjective visual sensations, yet these sensations are unstable. The underlying mechanisms may stem from differences in electrophysiological activity within the distributed network outside the stimulated site. To address this problem, we recruited 69 patients who experienced visual sensations during invasive electrical stimulation while intracranial electroencephalography (iEEG) data were recorded. We found significantly flattened power spectral slopes in distributed regions involving different brain networks and decreased integrated information during elicited visual sensations compared with the non-sensation condition. Further analysis based on minimum information partitions revealed that the reconfigured network interactions primarily involved the inferior frontal cortex, posterior superior temporal sulcus, and temporoparietal junction. The flattened power spectral slope in the inferior frontal gyrus was also correlated with integrated information. Taken together, this study indicates that the altered electrophysiological signatures provide insights into the neural mechanisms underlying subjective visual sensations.
Humans ; Male ; Female ; Adult ; Visual Perception/physiology* ; Electric Stimulation ; Middle Aged ; Young Adult ; Electrocorticography ; Electroencephalography ; Brain Mapping

This study investigated the mechanism of Chaishao Kaiyu Decoction in improving hippocampal neuroinflammation in depressed rats based on complement component 3(C3)/C3 receptor(C3aR). A total of 60 SD rats were randomly divided into a blank group, a model group, high, medium, and low dose groups of Chaishao Kaiyu Decoction, and a positive drug group, with 10 rats in each group. Except for the blank group, chronic unpredictable mild stress(CUMS) was used to construct depression models in other groups. Sucrose preference, open-field experiment, forced swimming, and water maze were used to detect the changes in depression-like behavior in each group. Enzyme-linked immunosorbent assay(ELISA) was used to detect the serum inflammatory factor level in rats, and hematoxylin-eosin(HE) staining and Nissl staining were employed to observe the pathological damage of hippocampal neurons. Golgi-Cox staining was used to observe the dendritic spine damage of hippocampal neurons, and immunofluorescence and Western blot were utilized to detect the expression of microglial marker Iba-1 and C3/C3aR protein in the hippocampus of rats. The behavioral results showed that compared with the model group, Chaishao Kaiyu Decoction could significantly strengthen the sugar water preference, increase the distance and number of voluntary activities, shorten the immobility time in forced swimming and the successful incubation period of positioning navigation, and prolong the stay time of space exploration in the target quadrant. ELISA results showed that the content of inflammatory factors in the hippocampus of depressed rats was significantly higher than that of the blank group, and the content of inflammatory factors decreased significantly after the intervention of Chaishao Kaiyu Decoction. In addition, Chaishao Kaiyu Decoction could relieve pathological damage such as cell swelling and loose arrangement of hippocampus tissue. In the Western blot experiment, the expression levels of C3 and C3aR proteins in the model group were higher than those in the blank group, while the expression of C3 and C3aR in Chaishao Kaiyu Decoction could be down-regulated. Immunofluorescence results showed that compared with the model group, the fluorescence intensity of microglia marker Iba-1 decreased significantly after the intervention of Chaishao Kaiyu Decoction and positive drugs. The antidepressant effect of Chaishao Kaiyu Decoction may be related to the down-regulation of C3/C3aR signaling pathway-related proteins, thus alleviating hippocampal inflammation.
Animals ; Hippocampus/metabolism* ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Male ; Depression/metabolism* ; Complement C3/metabolism* ; Receptors, Complement/metabolism* ; Humans ; Neuroinflammatory Diseases/genetics*

OBJECTIVE: To investigate the safety and efficacy of avatrombopag（AVA） combined with rhIL-11 in treating thrombocytopenia induced by chemotherapy in acute myeloid leukemia. METHODS: The clinical information of 8 patients in the real world who received avatrombopag combined with rhIL-11 in cancer treatment-induced thrombocytopenia(CTIT) after AML chemotherapy were retrospectively analyzed, and at the same time, 8 patients who received rhIL-11 only in CTIT after AML chemotherapy served as the control group, A preliminary observation was to summarize and compare the therapeutic efficacy and adverse effects between the two groups. RESULTS: D3 and D7 platelet counts were not significantly different between the observation group and the control group after treatment. The platelet counts in the observation group was significantly higher than those of the control group on the 10th day after treatment (P < 0.01). The adverse reactions, such as weakness, abdominal pain, fatigue, nausea and edema after treatment were mild in the observation group and the control group. Except for one patient in the observation group who had a history of cerebral infarction before the onset of the disease and was routinely taking antiplatelet drugs, no thrombosis events occurred in the patients in the observation and control groups during the period of administration of the drug, and the total incidence rate of adverse reactions was not significantly different between the two groups. CONCLUSION The combination of AVA and rhIL-11 can enhance platelet recovery in CTIT of AML patients after chemotherapy. Compared with the rhIL-11 alone group, the platelet recovery time in AVA+rhIL-11 group was significantly shorter, the platelet count on the 10th day after drug administration was significantly higher. No statistically significant difference in the total incidence rate of adverse reactions was observed between rhIL-11 alone group and AVA+rhIL-11 group.
Humans ; Leukemia, Myeloid, Acute/drug therapy* ; Thrombocytopenia/chemically induced* ; Interleukin-11/therapeutic use* ; Retrospective Studies ; Adult ; Thiophenes/therapeutic use* ; Platelet Count ; Female ; Male ; Middle Aged ; Thiazoles

Objective:Analyze the influencing factors of postoperative recurrence of common bile duct stones in patients with gallstones and multiple common bile duct stones,and evaluate the application value of nomogram predic-tion models.Methods:Collected clinical data of 587 patients with gallstones and multiple common bile duct stones who underwent surgical treatment at Beijing Fengtai Hospital from January 2022 to January 2024.They were divided into a training cohort(n=410)and a validation cohort(n=177)according to a 7∶3 ratio.Analyzed the influencing factors of postoperative recurrence of common bile duct stones in patients with gallstones and multiple common bile duct stones,and constructed a nomogram prediction model based on this.Results:The recurrence rate of postoperative common bile duct stones in the training queue was 38.05％(156/410).Age,BMI,intrahepatic bile duct stones,initial course of dis-ease,duodenal diverticulum,biliary tract infection,history of biliary surgery,thickness of the common bile duct wall,num-ber of multiple stones in the common bile duct,diameter of the common bile duct,and dysfunction of the Oddis sphincter in the duodenal papilla during ERCP examination are independent risk factors for postoperative recurrence in patients with gallbladder stones combined with multiple stones in the common bile duct(P＜0.05).The AUC of the constructed nomo-gram prediction model in the training queue and validation queue were 0.854 and 0.889,respectively.The Hosmer Lem-eshow fitting test results showed that there was no statistically significant difference between the predicted probability and the actual probability of the prediction model(x2=3.952,P=0.865),indicating that this model has good predictive abil-ity.Conclusion:The nomogram prediction model based on various risk factors can effectively predict the risk of post-operative common bile duct stone recurrence in patients with gallstones and multiple common bile duct stones.

Objective To analyze the relationship between obesity indicators,muscle mass indices and hypertension in Dongxiang adults,and establish and evaluate a Nomogram model based on these indicators used to predict the risk of hypertension in this population.Methods A total of 1209 Dongxiang adults from Linxia Prefecture,Gansu Province were selected,11 obesity indicators and 5 muscle mass indicators,including neck circumference(NC),waist-to-hip ratio(WHR),BMI,ponderal index(PI),conicity index(CI),a body shape index(ABSI),body roundness index(BRI),abdominal volume index(AVI),hip index(HI),body adiposity index(BAI),and the ratio of limb fat mass to body weight(LFWR),appendicular skeletal muscle mass(ASM),appendicular skeletal muscle mass index(ASMI),appendicular skeletal muscle mass to BMI ratio(ASMBMI),skeletal muscle index(SMI),and trunk muscle mass to body weight ratio(TMWR)were measured.Logistic regression analysis was used to explore the relationship between each indicator and hypertension.Nomogram prediction model was constructed and validated by using R language.Results Among Dongxiang males,the NC,BMI,PI,WHR,CI,AVI,BRI,BAI,ASM,ASMI,and LFWR were lower in the normal and high-normal blood pressure groups compared to the hypertensive group,while SMI,ASMBMI,and TMWR were higher.Among females,similar trends were observed,with lower NC,BMI,PI,WHR,CI,AVI,BRI,BAI,and LFWR in the normal blood pressure and high-normal blood pressure groups compared to the hypertensive group,but SMI,ASMBMI,and TMWR higher than the hypertensive group(P＜0.05).Results of multivariate Logistic regression analysis indicated that age,NC,and WHR were risk factors for hypertension in Dongxiang adults,while was protective factor(P＜0.05).The area under curve(AUC)of the Nomogram model constructed based on these factors was 0.796,and the Bootstrap internal validation C-index was 0.7957,indicating good calibration of the model.Conclusion The Nomogram model constructed based on obesity and muscle mass indicators has good predictive efficiency for predicting the risk of hypertension in Dongxiang adults.

AIM To study the chemical constituents from the buds of Aralia chinensis L.var.nuda Nakai and their in vitro anti-inflammatory activities.METHODS The 70％ethanol extract from the buds of A.chinensis var.nuda was isolated and purified by silica gel,Sephadex LH-20,ODS and semi-preparative HPLC,then the structures of compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities in vitro were evaluated by RAW264.7 model.RESULTS Sixteen compounds were isolated and identified as 4-(2,2-dibutoxyethyl)phenol(1),trans-linalool-3,7-oxide-6-O-β-D-glucopyranoside(2),2'-O-(9Z,12Z,15Z-octadecatrienoyl)glyceryl β-D-galactopyranoside(3),quercetin-3-O-β-D-glucopyranoside(3'→ O-3''')quercetin-3-O-β-D-galactopyranoside(4),syringaresinol-4'-O-β-D-glucopyranoside(5),p-hydroxybenzaldehyde(6),7α-hydroxystigmasterol 3-O-β-D-glucopyranoside(7),trans-p-hydroxy cinnamic acid methyl ester(8),funingensin A(9),3,4-dihydroxy-acetophenone(10),N-acetyltyramine(11),3,4-di-O-caffeoyl quinic acid(12),chlorogenic acid(13),aralia cerebroside(14),caffeic acid methyl ester(15),tetradecanoic acid(16).The IC50values of compounds 8,10,12 and 13 were(22.19±1.59),(35.25±1.30),(13.38±0.72),(15.73±1.16)μmol/L,respectively.CONCLUSION Compound 1 is a new compound,2-13 are isolated from genus Aralia for the first time.Compounds 8,10,12,13 exhibit significant in vitro anti-inflammatory activities.

AIM To study the chemical constituents from the leaves of Drynaria fortunei(Kunze)J.Sm.and their antioxidant activity.METHODS ODS-AG-HG,Sephadex LH-20 and semi-preparative HPLC were used for separation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH mothod.RESULTS Fifteen compounds were isolated and identified as kaempferol-3-O-neohesperidoside(1),dihydrodehydrodiconiferyl alcohol(2),kaempferol-3,7-di-O-α-L-rahmnoside(3),astragalin(4),loliolid(5),trichothecene analogue(6),2,2-[bis-4-(2,3-dihydroxypropoxy)phenyl]propane(7),maculatin(8),trichothecin(9),4-[(Z)-but-2-enoyloxy]-8-chloro-12-hydroxy-7,13-epoxytrichothec-9-ene(10),8-deoxy-trichotecin(11),β-sitosterol(12),daucosterol(13),afzelin(14),samwinol(15).The IC50 values of the leaf and rhizome extracts against DPPH free radicals were(0.072±0.005),(0.287±0.012)mg/mL,respectively.CONCLUSION Compounds 1,2,5-11,15 are isolated from this plant for the first time.The leaves of D.fortunei exhibit strong antioxidant activity.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]