To investigate the mechanism of action of Syngnathus extract in treating knee osteoarthritis of rats, forty-eight male SD rats were randomly divided into the blank group, model group, positive drug group, as well as low-dose, medium-dose, and high-dose groups of Syngnathus extract. The rat model of knee osteoarthritis was constructed by intra-articular injection of sodium iodoacetate. After successful modeling, celecoxib(18 mg·kg~(-1)·d~(-1)) and Syngnathus extract(0.4, 0.8, and 1.6 g·kg~(-1)·d~(-1)) were given in different groups by gavage intervention for two weeks. Hematoxylin-eosin(HE) staining was used to observe the histopathological changes of cartilage in knee joints, and enzyme-linked immunosorbent assay(ELISA) was used to detect the expression level of inflammatory factors in serum. Real-time fluorescence quantitative PCR, Western blot, and immunohistochemistry were used to detect the levels of phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target protein of rapamycin(mTOR) pathway-related mRNA and protein expression. The results showed that, comparied with the blank group, the cartilage surface of the knee joints of rats in the model group was uneven, with disorganized levels and defective cartilage tissue. The serum levels of interleukin-1β(IL-1β), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α) and the mRNA levels of PI3K, Akt, and mTOR in cartilage tissue, as well as the protein expression levels of phosphorylated PI3K(p-PI3K)/PI3K, phosphorylated Akt(p-Akt)/Akt, phosphorylated mTOR(p-mTOR)/mTOR, and P62 were significantly increased. Beclin1 protein expression was decreased. Comparied with the model group, the number of chondrocytes in the knee joint of rats in each group of Syngnathus extract increased, and the arrangement of chondrocytes was relatively neat. The cartilage layer was restored, and the serum levels of IL-1β, IL-6, and TNF-α, as well as the mRNA expression levels of PI3K, Akt, and mTOR in cartilage tissue were significantly reduced. The protein expression levels of p-PI3K/PI3K, p-Akt/Akt, p-mTOR/mTOR, and P62 were significantly reduced in the rats in the middle-dose and high-dose groups of Syngnathus extract, and the Beclin1 protein expression was significantly increased. The protein expression levels of p-PI3K/PI3K, p-Akt/Akt, and P62 in rats in the low-dose group of Syngnathus extract were significantly reduced. In summary, Syngnathus extract may be used to treat knee osteoarthritis by inhibiting the expression of PI3K/Akt/mTOR signaling pathway, so as to alleviate the inflammatory response in the organism, enhance the autophagy activity of chondrocytes, and reduce the apoptosis of chondrocytes.
Animals ; TOR Serine-Threonine Kinases/genetics* ; Male ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/genetics* ; Rats ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Phosphatidylinositol 3-Kinases/genetics* ; Humans

This study predicts the potential mechanism of Hippocampus in the treatment of knee osteoarthritis(KOA) through network pharmacology, with preliminary verification using molecular docking and animal experiments. The database was used to screen the active chemical components of Hippocampus and the targets of KOA, and Gene Ontology(GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and molecular docking were performed on the relevant core targets to preliminarily explore the potential targets and mechanisms of Hippocampus in the treatment of KOA. A rat KOA model was constructed by intra-articular injection of sodium iodoacetate, and the rats were intervened with different doses of Hippocampus decoction and celecoxib. The expression of relevant targets was detected through hematoxylin-eosin(HE) staining, enzyme-linked immunosorbent assay(ELISA), RT-qPCR, and Western blot to further validate the network pharmacology results. A total of 23 drug-like components of the Hippocampus were screened, and 128 common targets with KOA were identified, involving interleukin-17(IL-17) signaling pathway, transcription factor(FoxO) signaling pathway, tumor necrosis factor(TNF) signaling pathway. Molecular docking results showed that the screened core chemical components exhibited good affinity with key targets. HE staining demonstrated that Hippocampus improved the morphology of the cartilage layer. ELISA confirmed that Hippocampus significantly reduced the levels of IL-6 and TNF-α in the serum of KOA rats. Western blot and RT-qPCR analysis showed that Hippocampus significantly reduced the expression of IL-6, TNF-α, matrix metalloproteinase(MMP) 13, IL-17A, nuclear factor κB activator 1(ACT1), tumor necrosis factor receptor-associated factor 6(TRAF6) and nuclear factor κB(NF-κB) in cartilage tissue. The results suggest that Hippocampus can alleviate the degree of joint damage in the KOA rat model induced by sodium iodoacetate. The mechanism of action is related to the inhibition of the IL-17 signaling pathway, reduction of inflammation, and inhibition of extracellular matrix(ECM) degradation.
Animals ; Molecular Docking Simulation ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Network Pharmacology ; Male ; Osteoarthritis, Knee/metabolism* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Humans ; Interleukin-17/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Hippocampus/chemistry*

OBJECTIVES: To develop and validate a preoperative clinical-radiomics model for predicting overall survival (OS) and disease-free survival (DFS) in patients with extrahepatic cholangiocarcinoma (eCCA) undergoing radical resection. METHODS: In this retrospective study, consecutive patients with pathologically-confirmed eCCA who underwent radical resection at our institution from 2015 to 2022 were included. The patients were divided into a training cohort and a validation cohort according to the chronological order of their CT examinations. Least absolute shrinkage and selection operator (LASSO)-Cox regression was employed to select predictive radiomic features and clinical variables. The selected features and variables were incorporated into a Cox regression model. Model performance for 1-year OS and DFS prediction was assessed using calibration curves, area under receiver operating characteristic curve (AUC), and concordance index (C-index). RESULTS: This study included 123 patients (mean age 64.0 ± 8.4 years, 85 males/38 females), with 86 in the training cohort and 37 in the validation cohort. The OS-predicting model included four clinical variables and four radiomic features. It achieved a training cohort AUC of 0.858 (C-index = 0.800) and a validation cohort AUC of 0.649 (C-index = 0.605). The DFS-predicting model included four clinical variables and four other radiomic features. It achieved a training cohort AUC of 0.830 (C-index = 0.760) and a validation cohort AUC of 0.717 (C-index = 0.616). CONCLUSIONS The preoperative clinical-radiomics models show promise as a tool for predicting 1-year OS and DFS in eCCA patients after radical surgery.
Humans ; Male ; Female ; Retrospective Studies ; Middle Aged ; Cholangiocarcinoma/mortality* ; Prognosis ; Bile Duct Neoplasms/mortality* ; Tomography, X-Ray Computed/methods* ; Aged ; Radiomics

Objective To evaluate the efficacy of double U-stitch and modified"double U-stitch pancreaticojejunostomy"in pancreaticoduodenectomy.Methods We retrospectively analyzed the clinical information of 150 patients who underwent pancreaticoduodenectomy between January 2022 and September 2023 in Wang Wei's team in department of pancreatic surgery,Fudan University Shanghai Cancer Center.The patients were divided into two groups according to the pancreaticojejunostomy method:the double U-stitch 1.0 group(70 cases before modification)and the double U-stitch 2.0 group(80 cases after modification).The postoperative complications of the two groups were compared.Results The overall postoperative complications were significantly lower in the double U-stitch 2.0 group as compared with the double U-stitch 1.0 group(13.8％vs.38.6％,P=0.001).The incidence of clinically relevant pancreatic fistula was 18.6％in the double U-stitch 1.0 group,while this was significantly decreased in the double U-stitch 2.0 group(6.3％)(P=0.021).Postoperative extraluminal hemorrhage occurred in 5 patients in the double U-stitch 1.0 group,while in the double U-stitch 2.0 group,only one patient experienced postoperative intraluminal hemorrhage,the difference was statistically significant between two groups(P=0.007).The median postoperative length of hospital stay was significantly shorter in the double U-stitch 2.0 group than that in the double U-stitch 1.0 group(11d vs.14 d,P=0.001).Conclusions The modified"double U-stitch pancreaticojejunostomy"can significantly reduce the incidence of clinically relevant pancreatic fistula and other relevant severe complications,which helps improve the safety of the procedure.

Objective To propose a deep learning-based method for removing Gaussian and pepper noises of the surgical instrument visual images so as to recover the detailed features of the images.Methods A lightweight multi-task progressive network was constructed involving in a multi-feature fusion encoder-decoder network,an attention-guided network and a detail-recovery progressive network,which used the multi-feature fusion encoder-decoder network to predict and eliminate the noise information in the visual images,the attention-guided network to remove the residual noise and the detail-recovery progressive network to restore the underlying detail features of the denoised images.Some of the regular convolutions in the detail recovery progressive network were replaced with depth separable convolutions to realize lightweight design of the network constructed.Denoising experiments were conducted on the publicly available CBSD68 and Kodak24 datasets and the self-constructed surgical instrument noise dataset so as to compare the denoising effects of the network constructed and the traditional methods and the classification accuracies of ResNet-18 model and ResNet-34 model for the denosied images by the network and to analyze computing power and memory usage before and after the lightweight design.Results The network constructed gained better denoising effect than the classical methods for publicly available datasets,and ResNet-18 model and ResNet-34 model had higher accuracies when used to classify the images denoised by the network for the self-constructed surgical instrument noise dataset.Lightweight design had the parameter number and floating point operations(FLOPs)decreased by approximately 27.27％and 29.81％,respectively.Conclusion The proposed lightweight multi-task progressive network behaves well in denoising surgical instrument visual images with reduced computating power consump-tion and memory usage.[Chinese Medical Equipment Journal,2024,45(2):1-7]

With the outbreak of infectious diseases, more and more attention has been paid to surveillance and early warning work. Timely and accurate monitoring data is the basis of infectious diseases prevention and control. Effective early warning methods for infectious diseases can improve the timeliness and sensitivity of early warning work. This paper briefly introduces the intelligent early warning model of infectious diseases, summarizes the emerging surveillance and early warning methods of infectious diseases, and seeks the possibility of diversified surveillance and early warning in different epidemic stages and different outbreak scenarios of infectious diseases. This paper puts forward the idea of constructing a diversified method system of infectious diseases surveillance and early warning based on multi-stages and multi-scenarios and discusses the future development trend of infectious diseases surveillance and early warning, in order to provide reference for improving the construction level of infectious diseases surveillance and early warning system in China.
Humans ; Population Surveillance/methods* ; Communicable Diseases/epidemiology* ; Disease Outbreaks/prevention & control* ; Epidemics ; China/epidemiology*

With the outbreak of infectious diseases, more and more attention has been paid to surveillance and early warning work. Timely and accurate monitoring data is the basis of infectious diseases prevention and control. Effective early warning methods for infectious diseases can improve the timeliness and sensitivity of early warning work. This paper briefly introduces the intelligent early warning model of infectious diseases, summarizes the emerging surveillance and early warning methods of infectious diseases, and seeks the possibility of diversified surveillance and early warning in different epidemic stages and different outbreak scenarios of infectious diseases. This paper puts forward the idea of constructing a diversified method system of infectious diseases surveillance and early warning based on multi-stages and multi-scenarios and discusses the future development trend of infectious diseases surveillance and early warning, in order to provide reference for improving the construction level of infectious diseases surveillance and early warning system in China.
Humans ; Population Surveillance/methods* ; Communicable Diseases/epidemiology* ; Disease Outbreaks/prevention & control* ; Epidemics ; China/epidemiology*

To solve the problem of real-time detection and removal of EEG signal noise in anesthesia depth monitoring, we proposed an adaptive EEG signal noise detection and removal method. This method uses discrete wavelet transform to extract the low-frequency energy and high-frequency energy of a segment of EEG signals, and sets two sets of thresholds for the low-frequency band and high-frequency band of the EEG signal. These two sets of thresholds can be updated adaptively according to the energy situation of the most recent EEG signal. Finally, we judge the level of signal interference according to the range of low-frequency energy and high-frequency energy, and perform corresponding denoising processing. The results show that the method can more accurately detect and remove the noise interference in the EEG signal, and improve the stability of the calculated characteristic parameters.
Algorithms ; Electroencephalography ; Signal Processing, Computer-Assisted ; Signal-To-Noise Ratio ; Wavelet Analysis

Antibodies, Monoclonal, Humanized/adverse effects* ; Humans ; Immune Checkpoint Inhibitors/adverse effects* ; Myocarditis/drug therapy*

The novel coronavirus disease (COVID-19) pandemic is emerging as a global health threat and shows a higher risk for men than women. Thus far, the studies on andrological consequences of COVID-19 are limited. To ascertain the consequences of COVID-19 on sperm parameters after recovery, we recruited 41 reproductive-aged male patients who had recovered from COVID-19, and analyzed their semen parameters and serum sex hormones at a median time of 56 days after hospital discharge. For longitudinal analysis, a second sampling was obtained from 22 of the 41 patients after a median time interval of 29 days from first sampling. Compared with controls who had not suffered from COVID-19, the total sperm count, sperm concentration, and percentages of motile and progressively motile spermatozoa in the patients were significantly lower at first sampling, while sperm vitality and morphology were not affected. The total sperm count, sperm concentration, and number of motile spermatozoa per ejaculate were significantly increased and the percentage of morphologically abnormal sperm was reduced at the second sampling compared with those at first in the 22 patients examined. Though there were higher prolactin and lower progesterone levels in patients at first sampling than those in controls, no significant alterations were detected for any sex hormones examined over time following COVID-19 recovery in the 22 patients. Although it should be interpreted carefully, these findings indicate an adverse but potentially reversible consequence of COVID-19 on sperm quality.
Adult ; Asthenozoospermia/virology* ; COVID-19/physiopathology* ; China ; Gonadal Steroid Hormones/blood* ; Humans ; Male ; Progesterone/blood* ; Prolactin/blood* ; SARS-CoV-2 ; Semen/physiology* ; Semen Analysis ; Sperm Count ; Sperm Motility ; Spermatozoa/physiology* ; Time Factors