ObjectiveTo investigate the possible mechanism of Jishe Qushi Capsule （脊蛇祛湿胶囊， JQC） in treating rheumatoid arthritis （RA） from the perspective of macrophage polarization mediated by neutrophil extracellular traps （NETs）. MethodsTwenty-four female SD rats were randomly divided into four groups， blank control group， model group， JQC group， and peptidylarginine deiminase 4 （PAD4） inhibitor group with 6 rats in each group. All groups but the blank control group were subjected to the induction of collagen-induced arthritis （CIA）. After successful model establishment， rats in the JQC group received intragastric administration of JQC 1.47 g/kg daily； rats in the PAD4 inhibitor group received intraperitoneal injections of the PAD4 inhibitor 4 mg/kg weekly. Rats in the blank， model， and PAD4 inhibitor groups received 2 ml of pure water daily by gavage. All treatments lasted 4 weeks. Joint lesions of each group were assessed on day 7， 14， 21， 28， and 35 after model establishment， and arthritis index （AI） scores were recorded. At 24 h after the final administration， histopathology of knee joints， including HE staining， safranin O-fast green staining， and TRAP staining， was performed. Flow cytometry was used to detect the counts of M1 and M2 macrophages in peripheral blood. ELISA was used to determine serum levels of TRACP， NETs， TNF-α， IL-1β， and iNOS. Western Blotting and qRT-PCR were used to measure MPO， NE， RANKL， OPG， and p65 protein and mRNA expression in knee cartilage tissue. ResultsCompared with the blank control group， the model group showed increased AI scores （P＜0.05）， marked synovial inflammatory infiltration， angiogenesis， and bone-cartilage destruction， increased TRAP-positive osteoclasts， increased M1 macrophages and decreased M2 macrophages， elevated serum TRACP， NETs， TNF-α， IL-1β， and iNOS （P＜0.05）， elevated MPO， NE， RANKL， and p65 protein/mRNA expression and decreased OPG protein/mRNA expression in knee cartilage tissue （P＜0.05）. Compared with the model group， the JQC group exhibited improved synovial inflammation， angiogenesis， and bone-cartilage damage， reduced AI scores on day 21， 28， and 35， decreased osteoclast counts， decreased M1 macrophages and increased M2 macrophages， reduced serum TRACP， NETs， TNF-α， IL-1β， and iNOS （P＜0.05）， decreased MPO， NE， RANKL， and p65 protein/mRNA expression and increased OPG expression （P＜0.05）. Compared with the PAD4 inhibitor group， the JQC group showed significantly lower AI scores， reduced M1 macrophages， increased M2 macrophages （P＜0.05）， reduced serum TRACP， TNF-α， IL-1β， and iNOS， decreased MPO， RANKL， and p65 expression， and increased OPG levels （P＜0.05）. ConclusionThe therapeutic mechanism of JQC for RA may involve inhibition of NETs formation， downregulation of the RANKL/NF-κB signaling pathway， and regulation of macrophage M1/M2 polarization imbalance， thereby suppressing osteoclastogenesis and inflammatory bone destruction.

OBJECTIVE To investigate the effects and mechanisms of Lycium ruthenicum Murr. in improving sleep. METHODS Network pharmacology was employed to identify the active components of L. ruthenicum and their associated disease targets， followed by enrichment analysis. A caffeine‑induced zebrafish model of sleep deprivation was established ， and the zebrafish were treated with L. ruthenicum Murr. extract （LRME） at concentrations of 0.1， 0.2 and 0.4 mg/mL， respectively； 24 h later， behavioral changes of zebrafish and pathological alterations in brain neurons were subsequently observed. The levels of inflammatory factors [interleukin-6 （IL-6）， IL-1β， IL-10， tumor necrosis factor-α （TNF-α）]， oxidative stress markers [superoxide dismutase （SOD）， malondialdehyde （MDA）， glutathione peroxidase （GSH-Px）， catalase （CAT）]， and neurotransmitters [5- hydroxytryptamine （5-HT）， γ-aminobutyric acid （GABA）， glutamic acid （Glu）， dopamine （DA）， and norepinephrine （NE）] were measured. The protein expression levels of protein kinase B1 （AKT1）， phosphorylated AKT1 （p-AKT1）， epidermal growth factor receptor （EGFR）， B-cell lymphoma 2 （Bcl-2）， sarcoma proto-oncogene，non-receptor tyrosine kinase （SRC）， and heat shock protein 90α family class A member 1 （HSP90AA1） in the zebrafish were also determined. RESULTS A total of 12 active components and 176 intersecting disease targets were identified through network pharmacology analysis. Among these， apigenin， naringenin and others were recognized as core active compounds， while AKT1， EGFR and others served as key targets； EGFR tyrosine kinase inhibitor resistance signaling pathway was identified as the critical pathway. The sleep improvement rates in zebrafish of LRME low-， medium-， and high-dose groups were 54.60%， 69.03% and 77.97%， 开发。E-mail：hjp_yft@163.com respectively， while the inhibition ratios of locomotor distance were 0.57， 0.83 and 0.95， respectively. Compared with the model group， the number of resting counts， resting time and resting distance were significantly increased/extended in LRME medium- and high-dose groups （P＜0.05）. Neuronal damage in the brain was alleviated. Additionally， the levels of IL-6， IL-1β， TNF-α， MDA， Glu， DA and NE， as well as the protein expression levels of AKT1， p-AKT1， EGFR， SRC and HSP90AA1， were markedly reduced （P＜0.05）， while the levels of IL-10， SOD， GSH-Px， CAT， 5-HT and GABA， as well as Bcl-2 protein expression， were significantly elevated （P＜0.05）. CONCLUSIONS L. ruthenicum Murr. demonstrates sleep-improving effects， and its specific mechanism may be related to the regulation of inflammatory responses， oxidative stress， neurotransmitter balance， and the EGFR tyrosine kinase inhibitor resistance signaling pathway.

Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

Objective To explore the technical process and clinical application of laparoscopic combined upper midline incision minimally invasive liver transplantation. Methods A retrospective analysis was conducted on 30 cases of laparoscopic combined upper midline incision minimally invasive liver transplantation. The cases were divided into cirrhosis group (15 cases) and liver failure group (15 cases) based on the primary disease. The surgical and postoperative conditions of the two groups were compared. Results All patients successfully underwent laparoscopic "clockwise" liver resection, with no cases of passive conversion to open surgery or intolerance to pneumoperitoneum. In 6 cases, the right lobe was relatively large, and the right hepatic ligaments could not be completely mobilized. One case required an additional reverse "L" incision during open surgery. All patients successfully completed the liver transplantation, with no major intraoperative bleeding, cardiovascular events, or other occurrences in the 30 patients. The model for end-stage liver disease (MELD) score in the cirrhosis group was lower than that in the liver failure group (P<0.001). There were no statistically significant differences between the two groups in terms of age, surgical time, blood loss, anhepatic phase, or cold ischemia time (all P>0.05). During the perioperative period, there was 1 case of hepatic artery embolism, 1 case of portal vein anastomotic stenosis, no complications of hepatic vein and inferior vena cava, and 3 cases of biliary anastomotic stenosis, all of which occurred in the liver failure group. Conclusions In strictly selected cases, the minimally invasive liver transplantation technique combining laparoscopic hepatectomy with upper midline incision for graft implantation has the advantages of smaller incisions, less bleeding, relatively easier operation, and faster postoperative recovery, which is worthy of clinical promotion and application.

Objective To explore the feasibility and clinical experience of the middle hepatic vein splitting-reconstruction technique in split liver transplantation from low-age donor livers. Methods A retrospective analysis was conducted on the cases of two low-age donor livers that underwent middle hepatic vein splitting-reconstruction, which were transplanted into four child recipients at the Liver Transplantation Center of the Third Affiliated Hospital of Sun Yat-sen University from January 2017 to July 2023. The surgical and postoperative conditions were summarized and analyzed. Results Donor 1 was a 6-year-old and 4-month-old girl with a body weight of 21 kg, and the obtained donor liver weighed 496 g. After splitting, the left and right liver weights were 201 g and 280 g, and transplanted into a 9-month-old boy weighing 6.5 kg and a 9-month-old boy weighing 7.5 kg, respectively. The graft to recipient weight ratio (GRWR) was 3.09% and 3.73%, respectively. Donor 2 was a 5-year-old and 8-month-old boy with a body weight of 19 kg, and the donor liver weighed 673 g. After splitting, the left and right liver weights were 230 g and 400 g, and transplanted into a 13-month-old girl weighing 9.5 kg and a 15-month-old boy weighing 12 kg. The GRWR was 2.42% and 3.33%, respectively. Both donor livers were split ex vivo, with the middle hepatic vein being completely split in the middle and reconstructed using allogeneic iliac vein and iliac artery vascular patches. According to GRWR, none of the 4 transplant livers were reduced in volume. Among the 4 recipients, one died due to postoperative portal vein thrombosis and non-function of the transplant liver, while the other three cases recovered smoothly without early or late complications. Regular follow-up was conducted until July 31, 2023, and liver function recovered well. Conclusions Under the premise of detailed assessment of the donor liver and meticulous intraoperative operation, as well as matching with suitable child recipients, low-age donor livers may be selected for splitting. The complete splitting and reconstruction of the middle hepatic vein in the middle may effectively ensure the adequate venous return of the left and right liver and provide sufficient functional liver volume.

To review the randomized controlled trials (RCTs) at home and abroad on digital intelligence (DI)-driven rehabilitation in patients of neuromuscular disease, compare the effects of DI-driven rehabilitation with traditional rehabilitation, summarize the special needs and challenges faced by patients in rehabilitation of rare neuromuscular diseases, and provide evidence for the development and quality improvement of rehabilitation for rare neuromuscular diseases.

To provide references to and give suggestions to the development and optimiza-tion of Digital Intelligence (DI) technology in management of non-hospitalized patients by systematical review the application of digital technology in non-hospital settings.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Objective To investigate the correlation between spread through air space (STAS) of sub-centimeter non-small cell lung cancer and clinical characteristics and radiological features, constructing a nomogram risk prediction model for STAS to provide a reference for the preoperative planning of sub-centimeter non-small cell lung cancer patients. Methods The data of patients with sub-centimeter non-small cell lung cancer who underwent surgical treatment in Nanjing Drum Tower Hospital from January 2022 to October 2023 were retrospectively collected. According to the pathological diagnosis of whether the tumor was accompanied with STAS, they were divided into a STAS positive group and a STAS negative group. The clinical and radiological data of the two groups were collected for univariate logistic regression analysis, and the variables with statistical differences were included in the multivariate analysis. Finally, independent risk factors for STAS were screened out and a nomogram model was constructed. The sensitivity and specificity were calculated based on the Youden index, and area under the curve (AUC), calibration plots and decision curve analysis (DCA) were used to evaluate the performance of the model. Results A total of 112 patients were collected, which included 17 patients in the STAS positive group, consisting of 11 males and 6 females, with a mean age of (59.0±10.3) years. The STAS negative group included 95 patients, with 30 males and 65 females, and a mean age of (56.8±10.3) years. Univariate logistic regression analysis showed that male, anti-GAGE7 antibody positive, mean CT value and spiculation were associated with the occurrence of STAS (P＜0.05). Multivariate regression analysis showed that associations between STAS and male (OR=5.974, 95%CI 1.495 to 23.872), anti-GAGE7 antibody positive (OR=11.760, 95%CI 1.619 to 85.408) and mean CT value (OR=1.008, 95%CI 1.004 to 1.013) were still significant (P＜0.05), while the association between STAS and spiculation was not significant anymore (P=0.438). Based on the above three independent predictors, a nomogram model of STAS in sub-centimeter non-small cell lung cancer was constructed. The AUC value of the model was 0.890, the sensitivity was 76.5%, and the specificity was 91.6%. The calibration curve was well fitted, suggesting that the model had a good prediction efficiency for STAS. The DCA plot showed that the model had a good clinically utility. Conclusion Male, anti-GAGE7 antibody positive and mean CT value are independent predictors of STAS positivity of sub-centimeter non-small cell lung cancer, and the nomogram model established in this study has a good predictive value and provides reference for preoperative planning of patients.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.