ObjectiveTo predict the mechanism through which Shasheng Maidong Tang enhances the efficacy of chemotherapy for lung cancer via network pharmacology and validate the prediction results in animal experiments. MethodsThe potential mechanism through which Shasheng Maidong Tang enhances the efficacy of chemotherapy for lung cancer was predicted by network pharmacology， liquid chromatography-mass spectrometry （LC-MS）， and molecular docking methods. C57/BL6 mice were assigned into normal， model， cisplatin， and Shasheng Maidong Tang+cisplatin groups. In addition to the normal group， the remaining groups were injected subcutaneously with 0.2 mL of 1×10⁷ cells·mL^-1 Lewis lung cancer cells to establish the Lewis lung cancer model. The daily gavage dose of Shasheng Maidong Tang was 3.58 g·kg^-1， and the concentration of cisplatin intraperitoneally injected on every other day was 2 mg·kg^-1. Drugs were administered for 14 d. The changes in the tumor volume and the rate of tumor suppression were monitored， and the tumor histopathological changes were observed by hematoxylin-eosin （HE） staining. Enzyme-linked immunosorbent assay was employed to measure the interleukin （IL）-6 and interferon （IFN）-γ levels in peripheral blood. Real-time PCR was performed to quantify the mRNA levels of Janus kinase 2 （JAK2）， signal transducer and activator of transcription 1 （STAT1）， and signal transducer and activator of transcription 3 （STAT3） in the tumor tissue of mice. Western blot was employed to determine the protein levels of JAK2， STAT3， B-cell lymphoma-2 （Bcl-2）， cysteinyl aspartate-specific proteinase-3 （Caspase-3）， and Pim-1 proto1 （PIM1） in the tumor tissue. Immunohistochemistry was employed to detect the expression of Bcl-2 and PIM1 in the tumor tissue. ResultsNetwork pharmacological predictions indicated that Shasheng Maidong Tang might enhance the efficacy of chemotherapy for lung cancer by regulating nitrogen metabolism， AGE-RAGE signaling pathway， cancer pathway， and JAK/STAT signaling pathway. The experimental results demonstrated that tumor volume in the cisplatin group and Shasheng Maidong Tang+cisplatin group was reduced compared with the model group， with statistically distinct differences observed on days 14， 17， 20 post modeling （P<0.05）. Notably， the Shasheng Maidong Tang+cisplatin therapy further decreased tumor volume compared with the cisplatin group， showing marked reductions on days 17 and 20 （P<0.05）， consistent with trends visualized in tumor volume comparison charts. The Shasheng Maidong Tang+cisplatin group exhibited higher tumor inhibition rate than the cisplatin group （P<0.05）. Histopathological analysis via HE staining revealed that the tumors in the model group displayed frequent nuclear mitosis， densely arranged cells， hyperchromatic nuclei， and no necrosis. Cisplatin treatment induced partial necrosis and vacuolization， while the Shasheng Maidong Tang+cisplatin group exhibited extensive necrotic regions， maximal vacuolization， disarranged tumor cells， and minimal mitotic activity. Compared with the model group， the cisplatin group and the Shasheng Maidong Tang+cisplatin group showed elevated level of IFN-γ （P<0.01） and declined level of IL-6 （P<0.01） in the peripheral blood. Compared with the cisplatin group， the Shasheng Maidong Tang+cisplatin group presented elevated level of IFN-γ （P<0.01） and lowered level of IL-6 （P<0.01） in the peripheral blood. Compared with the model group， the cisplatin group and the Shasheng Maidong Tang+cisplatin groups showed down-regulated mRNA levels of JAK2 and STAT3 （P<0.01） and up-regulated mRNA level STAT1 （P<0.01）. Compared with the cisplatin group， the Shasheng Maidong Tang+cisplatin group presented down-regulated mRNA levels of JAK2 and STAT3 （P<0.01） and up-regulated mRNA level of STAT1 （P<0.01）. Compared with the model group， the cisplatin group and the Shasheng Maidong Tang+cisplatin group showed down-regulated protein levels of JAK2 （P<0.01）， Bcl-2 （P<0.01）， PIM1 （P<0.01）， and STAT3 （P<0.05）， and up-regulated protein level of Caspase-3 （P<0.01）. Compared with the cisplatin group， Shasheng Maidong Tang+cisplatin group presented down-regulated protein levels of JAK2 （P<0.01）， Bcl-2 （P<0.01）， PIM1 （P<0.01）， STAT3 （P<0.05）， and up-regulated protein level of Caspase-3 （P<0.01）. The Bcl-2 and PIM1 expression results obtained by immunohistochemistry were consistent with those of Western blot. ConclusionShasheng Maidong Tang may enhance the efficacy of chemotherapy in the mouse model of Lewis lung cancer by regulating the JAK2/STAT3 signaling pathway.

Objective: To analyze the cause of discrepancy between ABO genotype B102/O01 and serological results in one case by PCR-SSP, to clarify the serological characteristics of this special blood group, and to explore relevant blood transfusion strategies. Methods: Blood group serological tests were performed on blood donor in August and December 2024, including forward and reverse ABO typing using tube method, H antigen identification, direct anti-human globulin test by tube method, red blood cell absorption-elution test, and determination of ABH blood group substance in saliva. Exons 1-7 of the ABO gene were amplified by PCR-SSP and sequenced. Results: The two separate serological tests consistently identified the donor as having an A B phenotype, but the results of gene sequencing indicated a B102/O01 genotype, showing an discrepancy between serological and genetic results. Conclusion: It is very likely that the blood type of the blood donor is B102/O01 with a microchimerism of type A, or an AB type masked by A type reference gene.

Objective: To prepare the erythrocyte-liposome drug delivery system to enhance the therapeutic effect of drugs on tumors and inhibit tumor metastasis. Methods: This study prepared and characterized paclitaxel (PTX)-plerixafor (AMD3100) liposomes (Lips), developed the erythrocyte-liposome drug delivery system, and evaluated its targeting efficiency and therapeutic efficacy through a series of in vitro cellular and in vivo animal experiments. Results: The particle size of PTX-AMD-Lips was (186.4±0.83) nm. Drug encapsulation efficiency of PTX-AMD-Lips was (75.50±5.27)% for PTX and (88.31±2.45)% for AMD. The Binding efficiency between RBC and liposomes in the drug delivery system was (69.93±2.55)%. Vitro cellular experiments revealed that PTX-AMD-Lips significantly inhibited tumor cell migration. In vivo animal experiments, the erythrocyte-liposome drug delivery system significantly increased drug accumulation in the lungs. At the experimental endpoint, the quantitative fluorescence signal of tumor size measured (4.04±0.44)×10 for the PTX-Lips group, and (5.14±3.40)×10 for the RBC-PTX-AMD-Lips group. Conclusion: The erythrocyte-liposome drug delivery system could enhance the lung-specific targeting capability of liposomes, kill tumor cells and suppress further metastasis effectively.

Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Objective: To determine 17 types of phthalic acid esters (PAEs) in drinking water using solid-phase extraction coupled with gas chromatography-mass spectrometry (GC-MS) in multiple reaction monitoring (MRM) mode. Methods: One litre of commercially available bottled water was purified using an HLB solid-phase extraction column, and was eluted with ethyl acetate, dichloromethane and average methanol. Seventeen types of PAEs were detected using a triple quadrupole gas chromatography-mass spectrometer in MRM mode. By optimizing the temperature programming and adjusting the mass spectrometry collision energy, collection efficiency was improved and matrix interference was reduced. The precision and accuracy of this method were assessed by determining the standard curves, detection limits, quantification limits, relative standard deviations (RSD) and average spiked recovery rates for the 17 types of PAEs. Results: The 17 types of PAEs showed good linear relationships between mass concentration and chromatographic peak areas in the range of 0.02 to 1.0 mg/L, with correlation coefficients all greater than 0.999 1. The detection limits ranged from 0.002 9 to 0.009 7 mg/kg, the quantification limits ranged from 0.008 7 to 0.029 1 mg/kg, the RSD ranged from 0.8% to 3.0%, and the average spiked recovery rates ranged from 88.8% to 111.8%. Conclusion Solid-phase extraction coupled with MRM of GC-MS can better determine low concentrations of PAEs in drinking water.

Children， as a special group， frequently experience of off-label drug use worldwide. Common reasons for off-label drug use in children include the lack of data on pediatric patients during the clinical trial stage of drug development， delayed updates to drug instructions， and the non-standard professional behavior of some doctors. Off-label drug use in children is a double-edged sword. It could save lives and provide a way to explore additional functions of drugs， while it may also lead to the phenomenon of hyper-indication abuse， increasing the risk of adverse drug events. Regulating off-label drug use in children can safeguard the best treatment rights and interests of children. It is recommended to encourage pharmaceutical enterprises to conduct research and development of pediatric new drugs， simplify the approval process for drug instructions amendments， accumulate evidence-based medical evidence for off-label drug use in children， standardize the process of off-label drug use in children in medical institutions， continuously improve the standardized diagnosis and treatment capabilities of pediatricians， and actively cooperate with the families of pediatric patients in diagnosis and treatment， so as to comprehensively safeguard the rights and interests of both doctors and patients.

ObjectiveTo investigate the anti-Alzheimer's disease （AD） effect of Dipsacus asper（DA） in the Caenorhabditis elegans model， and decipher the underlying mechanism via the peroxisome proliferator-activated receptor α （PPARα）/transcription factor EB （TFEB） pathway. MethodsFirst， transgenic AD C. elegans individuals were assigned into the blank control， model， positive control （WY14643， 20 µmol·L^-1）， and low-， medium-， and high-dose （100， 200， and 400 mg·L^-1， respectively） DA groups. The amyloid β-42 （Aβ₄₂） formation in the muscle cells， the paralysis time， and the deposition of amyloid β-protein （Aβ） in the head were detected. The lysosomal autophagy in the BV2 cell model was examined by Rluc-LC3wt/G120A. The expression levels of lysosomal autophagy-related proteins LC3Ⅱ， LC3I， LAMP2， and TFEB were detected by Western blot. Real-time quantitative polymerase chain reaction （Real-time PCR） was employed to determine the mRNA levels of autophagy-related genes beclin1 and Atg5 and lysosome-related genes LAMP2 and CLN2 downstream of PPARα/TFEB. A reporter gene assay was used to detect the transcriptional activities of PPARα and TFEB. Immunofluorescence was used to detect the fluorescence intensity of PPARα， and the active components of the ethanol extract of DA were identified by UPLC-MS. RCSB PDB， Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， and Autodock were used to analyze the binding between the active components and PPARα-ligand-binding domain （LBD）. ResultsCompared with the model group， the positive control group and 200 and 400 mg·L^-1 DA groups showed prolonged paralysis time （P<0.05）， and all the treatment groups showed decreased Aβ deposition in the head （P<0.01）. DA within the concentration range of 50-500 mg·L^-1 did not affect the viability of BV2 cells. In addition， DA enhanced the autophagy flux （P<0.05）， up-regulated the mRNA levels of beclin1， Atg5， LAMP2， and CLN2 （P<0.05， P<0.01）， promoted the nuclear translocation of TFEB （P<0.05）， increased LAMP2 expression and autophagy flux （P<0.05， P<0.01）， and enhanced the transcriptional activities of PPARα and TFEB （P<0.01）. The positive control group and 200 and 400 mg·L^-1 DA groups showed enhanced fluorescence intensity of PPARα in the BV2 nucleus （P<0.01）. UPLC-MS detected nine known compounds of DA， from which 8 active components of DA were screened out. The docking results suggested that a variety of components in DA could bind to PPARα-LBD and form stable hydrogen bonds. ConclusionDA may reduce the pathological changes in AD by regulating the PPARα-TFEB pathway.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.

Anopheles stephensi is an important malaria vector in many Southeast Asian countries, and is also a widely distributed Anopheles species in parts of Asia. As a potential vector of malaria and other mosquito-borne diseases, Anopheles stephensi had a relative wide distribution in China. This review gives a brief overview of the morphological characteristics and geographical distribution of Anopheles stephensi, which has been reported in South China, Southwest China and East China, including but not limited to Guangdong, Guangxi, Hainan, Guizhou, Sichuan, Xizang, Yunnan, Fujian and other provinces. Thanks to the continuous and effective disease surveillance and mosquito control strategies, the risk of malaria epidemic in China has been greatly reduced. However, Anopheles stepheni is highly invasive and adaptable, in addition to its rapid spread in global distribution, together with global climate anomalies and other factors, there still exists a certain transmission risk of the diseases related to Anopheles stepheni in some parts of China. In order to consolidate the achievements of malaria prevention and control, it is still necessary to conduct continuous monitoring of Anopheles stephensi and other malaria vectors, and to consolidate the implementation of malaria control measures in China.

Purpose: Gold-standard urodynamic examination is widely used in the diagnosis and treatment of lower urinary tract dysfunction. The purpose of urodynamic quality control is to standardize urodynamic examination and ensure its clinical reference value. In our study, we attempted to use a deep learning (DL) algorithm model, mainly for the recognition of typical urodynamic signal, to help physicians complete high-quality urodynamic examinations. Methods: Urodynamic image data from 2 cohorts of adult patients with neurogenic bladder were used: (1) 300 patients with neurogenic bladder in our center from 2012 to 2018 (1,960 images used to train and validate the DL model); and (2) 100 patients with neurogenic bladder from 2020 to 2021 (695 images used to test the performance of the DL model). This resulted in a total of 2,655 images to train, validate and test the DL algorithm to predict the urdynamic signals. Results: Yolov5l had the best detection performance and the highest comprehensive index score (F1, 0.81; mean average precision, 0.83). Our study is a retrospective single-center study, and the generalization ability of the model has not been verified. Conclusions DL algorithms can help operators identify typical urodynamic signals in real time, improve the interpretation and quality of urodynamic examination, and benefit patients.