Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

OBJECTIVE: To evaluate the impact of a history of vaginal delivery on anesthesia management of patients undergoing hysteroscopic surgery under intravenous general anesthesia without tracheal intubation. METHODS: Ninety-nine patients undergoing hysteroscopic surgery under intravenous general anesthesia were enrolled in this study, including 43 patients with (VD group) and 56 patients without a history of vaginal delivery (NVD group). For all the patients, blood pressure, heart rate (HR), blood oxygen saturation (SpO₂) and bispectral index (BIS) were recorded before anesthesia (T1), after anesthesia (T2), after cervical dilation (T3), and at 3 min after cervical dilation (T4). Propofol and etomidate doses during anesthesia induction, the total dose of propofol administered, additional intraoperative bolus dose and times of propofol, intraoperative body movement, total operation time and surgeons' satisfaction feedback scores were compared between the two groups. The postoperative awake time, recovery time, VAS score at 30 min after operation, and postoperative nausea and vomiting (PONV) were also compared. RESULTS: There was no significant differences in SBP, DBP, HR, SpO₂, or BIS between the two groups at T1 and T2, but at T3 and T4, SBP and DBP were significantly higher in NVD group than in VD group (P < 0.01); HR was significantly higher in NVD group only at T3 (P < 0.01). The application of vasoactive drugs did not differ significantly between the two groups. The total dose of propofol, additional intraoperative dose and times of propofol were all greater in NVD group than in VD group (P < 0.01). More body movements of the patients were observed in NVD group (P < 0.01), which also had lower surgeons' satisfaction score for anesthesia (P < 0.01), higher postoperative VAS score (P < 0.05), and shorter postoperative awake time (P < 0.05) and recovery time (P < 0.01). CONCLUSION A history of vaginal delivery has a significant impact on anesthesia management of patients undergoing hysteroscopic surgery under intravenous general anesthesia without tracheal intubation in terms of hemodynamic changes, anesthetic medication, and postoperative recovery quality, suggesting the necessity of individualized anesthesia management for these patients.
Anesthesia, General ; Anesthesia, Intravenous ; Anesthetics, Intravenous ; Cohort Studies ; Delivery, Obstetric ; Female ; Humans ; Hysteroscopy ; Pregnancy ; Propofol

Objective: To analyze the clinical epidemiological characteristics including composition of pathogens , clinical characteristics, and disease prognosis acute bacterial meningitis (ABM) in Chinese children. Methods: A retrospective analysis was performed on the clinical and laboratory data of 1 610 children <15 years of age with ABM in 33 tertiary hospitals in China from January 2019 to December 2020. Patients were divided into different groups according to age,<28 days group, 28 days to <3 months group, 3 months to <1 year group, 1-<5 years of age group, 5-<15 years of age group; etiology confirmed group and clinically diagnosed group according to etiology diagnosis. Non-numeric variables were analyzed with the Chi-square test or Fisher's exact test, while non-normal distrituction numeric variables were compared with nonparametric test. Results: Among 1 610 children with ABM, 955 were male and 650 were female (5 cases were not provided with gender information), and the age of onset was 1.5 (0.5, 5.5) months. There were 588 cases age from <28 days, 462 cases age from 28 days to <3 months, 302 cases age from 3 months to <1 year of age group, 156 cases in the 1-<5 years of age and 101 cases in the 5-<15 years of age. The detection rates were 38.8% (95/245) and 31.5% (70/222) of Escherichia coli and 27.8% (68/245) and 35.1% (78/222) of Streptococcus agalactiae in infants younger than 28 days of age and 28 days to 3 months of age; the detection rates of Streptococcus pneumonia, Escherichia coli, and Streptococcus agalactiae were 34.3% (61/178), 14.0% (25/178) and 13.5% (24/178) in the 3 months of age to <1 year of age group; the dominant pathogens were Streptococcus pneumoniae and the detection rate were 67.9% (74/109) and 44.4% (16/36) in the 1-<5 years of age and 5-<15 years of age . There were 9.7% (19/195) strains of Escherichia coli producing ultra-broad-spectrum β-lactamases. The positive rates of cerebrospinal fluid (CSF) culture and blood culture were 32.2% (515/1 598) and 25.0% (400/1 598), while 38.2% (126/330)and 25.3% (21/83) in CSF metagenomics next generation sequencing and Streptococcus pneumoniae antigen detection. There were 4.3% (32/790) cases of which CSF white blood cell counts were normal in etiology confirmed group. Among 1 610 children with ABM, main intracranial imaging complications were subdural effusion and (or) empyema in 349 cases (21.7%), hydrocephalus in 233 cases (14.5%), brain abscess in 178 cases (11.1%), and other cerebrovascular diseases, including encephalomalacia, cerebral infarction, and encephalatrophy, in 174 cases (10.8%). Among the 166 cases (10.3%) with unfavorable outcome, 32 cases (2.0%) died among whom 24 cases died before 1 year of age, and 37 cases (2.3%) had recurrence among whom 25 cases had recurrence within 3 weeks. The incidences of subdural effusion and (or) empyema, brain abscess and ependymitis in the etiology confirmed group were significantly higher than those in the clinically diagnosed group (26.2% (207/790) vs. 17.3% (142/820), 13.0% (103/790) vs. 9.1% (75/820), 4.6% (36/790) vs. 2.7% (22/820), χ²=18.71, 6.20, 4.07, all P<0.05), but there was no significant difference in the unfavorable outcomes, mortility, and recurrence between these 2 groups (all P>0.05). Conclusions: The onset age of ABM in children is usually within 1 year of age, especially <3 months. The common pathogens in infants <3 months of age are Escherichia coli and Streptococcus agalactiae, and the dominant pathogen in infant ≥3 months is Streptococcus pneumoniae. Subdural effusion and (or) empyema and hydrocephalus are common complications. ABM should not be excluded even if CSF white blood cell counts is within normal range. Standardized bacteriological examination should be paid more attention to increase the pathogenic detection rate. Non-culture CSF detection methods may facilitate the pathogenic diagnosis.
Adolescent ; Brain Abscess ; Child ; Child, Preschool ; Escherichia coli ; Female ; Humans ; Hydrocephalus ; Infant ; Infant, Newborn ; Male ; Meningitis, Bacterial/epidemiology* ; Retrospective Studies ; Streptococcus agalactiae ; Streptococcus pneumoniae ; Subdural Effusion ; beta-Lactamases

We reported a case of irreducible indirect inguinal hernia caused by sigmoid colon cancer entering the right groin.The patient complained about a right groin mass for more than 60 years with progressive enlargement for 3 years and pain for half a month.Abdominal CT examination at admission showed rectum and sigmoid colon hernia in the right inguinal area and thickening of sigmoid colon wall.Electronic colonoscopy and pathological diagnosis showed sigmoid colon cancer.Therefore,the result of preliminary diagnosis was irreducible indirect inguinal hernia caused by sigmoid colon cancer entering the right groin.We converted laparoscopic exploration to laparotomy followed by radical sigmoidectomy and employed end-to-end anastomosis of descending colon and rectum in combination with repair of right inguinal hernia.The patient recovered well after operation and was discharged.
Colon, Sigmoid/surgery* ; Groin ; Hernia, Inguinal/surgery* ; Humans ; Laparoscopy ; Sigmoid Neoplasms/surgery*

The current document is based on a consensus reached by a panel of experts from the Chinese Society of Allergy and the Chinese Society of Otorhinolaryngology-Head and Neck Surgery, Rhinology Group. Chronic rhinosinusitis (CRS) affects approximately 8% of Chinese adults. The inflammatory and remodeling mechanisms of CRS in the Chinese population differ from those observed in the populations of European descent. Recently, precision medicine has been used to treat inflammation by targeting key biomarkers that are involved in the process. However, there are no CRS guidelines or a consensus available from China that can be shared with the international academia. The guidelines presented in this paper cover the epidemiology, economic burden, genetics and epigenetics, mechanisms, phenotypes and endotypes, diagnosis and differential diagnosis, management, and the current status of CRS in China. These guidelines—with a focus on China—will improve the abilities of clinical and medical staff during the treatment of CRS. Additionally, they will help international agencies in improving the verification of CRS endotypes, mapping of eosinophilic shifts, the identification of suitable biomarkers for endotyping, and predicting responses to therapies. In conclusion, these guidelines will help select therapies, such as pharmacotherapy, surgical approaches and innovative biotherapeutics, which are tailored to each of the individual CRS endotypes.
Adult ; Asian Continental Ancestry Group ; Biomarkers ; China ; Consensus ; Diagnosis ; Diagnosis, Differential ; Drug Therapy ; Eosinophils ; Epidemiology ; Epigenomics ; Genetics ; Humans ; Hypersensitivity ; Inflammation ; International Agencies ; Medical Staff ; Neck ; Phenotype ; Precision Medicine

ObjectivecircRNAs play an important role in tumor development, but the relationship between circRNAs and hepatocellular carcinoma remains to be further explored. The present study aimed to bioinformatically analyze the target gene of microRNA-1. Another aim was to screen circRNAs that are associated with target genes and differentially expressed in hepatocellular carcinoma cells, as well as provide theoretical basis for clinical screening of molecular markers and targeted therapies related to hepatocellular carcinoma.MethodsThe miRNA related database used for the prediction of microRNA-1 target genes, and the bioinformatic analysis of the target genes of microRNA-1 involved functional enrichment analysis and signal transduction pathway enrichment. Then, the circRNAs, which are related to the downstream target genes of microRNA-1, are screened through the circRNA database.ResultsThe number of microRNA-1 target genes was 230 in miRNA related database. Through GO analysis, it was found that the target genes of microRNA-1 had a strong tendency in regulation, and were mainly enriched in three aspects: biological function, biological process and cell localization.The target genes of microRNA-1 are involved in the function of proteins, regulation of biosynthesis, cofactor binding, enzyme regulation and other biological processes. Predicted target genes of miRNA-1 were significantly enriched in cancer signaling pathways, hepatitis B occurrence, endocytosis and splicing pathways. Further, 21 circRNAs related to the target gene of microRNA-1 were found in three circRNA databases, wherein hsa_circ_0004651 was highly expressed in hepatocellular carcinoma cell line HepG2 and its pavent gene was hnRNPD.ConclusionMicroRNA-1 influence the occurrence of hepatocellular carcinoma development through the regulation of protein and enzyme. Hsa_circ_0004651 may affect the development of hepatocellular carcinoma with microRNA-1 and its parental gene hnRNPD.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

Objective: To discuss the effect of Peiyuan Tongnao capsules on neurological impairment of patients with ischemic stroke at convalescence, and discuss the mechanism of action in microcirculation improvement, anti-inflammation and neuroprotection. Method: One hundred and thirty one patients were randomly divided into control group (66 cases) and observation group (65 cases) by random number table. Patients in control group were given aspirin enteric-coated tablets, 0.1 g/day, simvastatin tablets, 10 mg/days, and treated by percutaneous nerve electrical stimulator for 30 times, 30 min/time, 1 time/day, 5 times/week. In addition of the therapy in control group, patients in observation group were also given Peiyuan Tongnao capsules, 3 grains/time, 3 times/days. A course of treatment was 12 weeks. Before treatment, and at the 4^th, 8^th and 12^th weeks, neurological deficits in the national institutes of health (NIHSS), activity of daily life scale (ADL), berg balance scale (BBA), fugl-meyer scale (FMA) and traditional Chinese medicine (TCM) syndromes were scored. And levels of brain-derived neurotrophic factor (BDNF), neuron-specific enolase (NSE), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), homocysteine (Hcy) and serum cystatin C (Cys-C) and hemorheological indicators whole blood viscosity, high shear rate, low shear rate, reduced viscosity, plasma viscosity, platelet aggregation rate, fibrinogen (FIB) and blood sedimentation rate (ESR)were detected. Result: At the 8^th and 12^th week after treatment, score of NIHSS in observation group was lower than that in control group (P<0.01), and NIHSS in observation group declined more than that in control group (P<0.01). Scores of ADL, BBA and FMA and levels of BDNF were higher than those in control group (P<0.01), while scores of TCM syndromes and levels of NSE, IL-6, TNF-α, Hcy, Cys-C and hemorheological indices were all lower than those in control group (P<0.01). And by rank sum test, the clinical effect in observation group was superior to that in control group (P<0.05). Conclusion: Peiyuan Tongnao capsules can promote the recovery of neurological impairment at recovery period of ischemic stroke, regulate inflammatory factors, improve blood rheology, protect neural function, and improve the effect of routine western medicine rehabilitation therapy.

The laterodorsal tegmentum (LDT) is a brain structure involved in distinct behaviors including arousal, reward, and innate fear. How environmental stimuli and top-down control from high-order sensory and limbic cortical areas converge and coordinate in this region to modulate diverse behavioral outputs remains unclear. Using a modified rabies virus, we applied monosynaptic retrograde tracing to the whole brain to examine the LDT cell type specific upstream nuclei. The LDT received very strong midbrain and hindbrain afferents and moderate cortical and hypothalamic innervation but weak connections to the thalamus. The main projection neurons from cortical areas were restricted to the limbic lobe, including the ventral orbital cortex (VO), prelimbic, and cingulate cortices. Although different cell populations received qualitatively similar inputs, primarily via afferents from the periaqueductal gray area, superior colliculus, and the LDT itself, parvalbumin-positive (PV) GABAergic cells received preferential projections from local LDT neurons. With regard to the different subtypes of GABAergic cells, a considerable number of nuclei, including those of the ventral tegmental area, central amygdaloid nucleus, and VO, made significantly greater inputs to somatostatin-positive cells than to PV cells. Diverse inputs to the LDT on a system-wide level were revealed.