Dry eye disease(DED)is a common ocular surface disorder worldwide, primarily characterized by a loss of homeostasis of the tear film, and frequently associated with meibomian gland dysfunction(MGD), decreased tear film stability, ocular discomfort, and visual impairment. In recent years, factors such as the widespread use of digital devices,the aging population, and environmental changes have contributed to a significant increase in its global prevalence, making it a major public health concern. Red light therapy(RLT), also known as low-level laser therapy(LLLT)or photobiomodulation(PBM), is a non-invasive treatment that utilizes low-energy red or near-infrared light to irradiate tissues. It exerts photobiomodulatory effects to promote cellular repair and functional recovery. This therapy has demonstrated considerable potential in treating various ocular conditions. Its broader clinical application could improve therapeutic outcomes, alleviate patient discomfort and financial burden, and reduce the consumption of healthcare resources, thereby yielding significant socio-economic benefits. This paper systematically reviews the multifaceted mechanisms and application prospects of RLT in managing DED, including its anti-inflammatory effects, improvement of meibomian gland function, promotion of conjunctival goblet cell repair, and alleviation of visual fatigue, aiming to provide a theoretical foundation and practical reference for its clinical adoption.

ObjectiveThis paper aims to analyze the variety characteristics and prescription patterns of marketed traditional Chinese patent medicines for treating abortion and provide references for new medicine development and clinical application. MethodsRelevant information of traditional Chinese patent medicines for treating abortion was systematically retrieved and collected. Microsoft Excel 2021 software was used to sort and statistically analyze the medicine syndrome types， quantity， market situation， and status of package inserts. Based on the Ancient and Modern Medical Case Cloud Platform （V2.3.9）， the medicine properties， flavors， meridian tropism， and medication characteristics of standardized prescriptions were analyzed. ResultsA total of 39 marketed traditional Chinese patent medicines for treating abortion in China were included. According to disease type， these medicines were categorized as therapeutic medicines for threatened abortion and recurrent spontaneous abortion. According to clinical function， they were categorized into three groups： fetus stabilization， blood nourishment， and adjunctive conditioning. They were also categorized into pre-pregnancy conditioning and post-pregnancy fetal maintenance by clinical intervention stage. Post-marketing research showed that only three products had undergone safety evaluations and one involved pharmacoeconomic research， indicating a general lack of standardized evidence-based data. Dosage forms were mainly pills and granules. Package insert analysis revealed that 15 products listed "contraindications"， while 28 included "precautions". Based on prescription inclusion and exclusion criteria， 25 products were selected for further analysis. Their therapeutic effects were mainly concentrated on "tonifying the kidney and spleen， replenishing Qi， and nourishing blood"， with core medicines including Paeoniae Radix Alba， Angelicae Sinensis Radix， and Atractylodis Macrocephalae Rhizoma. Most medicines were warm or neutral in nature， predominantly sweet and pungent in flavor， and mainly entered the spleen， liver， and kidney meridians. ConclusionTraditional Chinese patent medicines for treating abortion demonstrate clear clinical value. However， shortcomings remain， including insufficient post-marketing research， prescription homogeneity， and incomplete package inserts. Future efforts should establish a clinically value-oriented modern development pathway， strengthen safety surveillance and evidence evaluation， improve package inserts， and promote precision use to further enhance clinical value.

ObjectiveTo investigate the effects of Chaihu and Longgu Mulitang （CLMT） on hippocampal neural damage in the mouse model of depression via the extracellular signal-regulated protein kinase （ERK）/cAMP-response element-binding protein （CREB） signaling pathway. MethodsSeventy-eight male C57BL/6 mice were randomly allocated into normal control， model， low/medium/high-dose （2.89， 5.78， and 11.56 g·kg^-1， respectively） CLMT， and paroxetine （10 mg·kg^-1） groups. A depression model was established by chronic unpredictable mild stress （CUMS） combined with social isolation. Behavioral tests were carried out to evaluate depressive-like behaviors. Hematoxylin-eosin staining and Nissl staining were performed to assess hippocampal morphology and neuronal damage. Immunofluorescence was employed to detect glial fibrillary acidic protein （GFAP） and ionized calcium-binding adapter molecule 1 （Iba1）. Real-time PCR was employed to measure the mRNA levels of ERK and CREB. Western blot was employed to determine the expression of ERK/CREB pathway proteins and brain-derived neurotrophic factor （BDNF） in the hippocampal tissue. Molecular Operating Environment （MOE） software was used for molecular docking to evaluate the interactions between CLMT components and target proteins. ResultsCompared with the normal control group， the model group showed decreased sucrose preference （P0.01）， increased tail-suspension immobility time （P0.01）， decreased activity in the central region of the open field test （P0.01）， and decreased activity in the middle and open-arm region of the elevated plus maze test （P0.01）. The hippocampal area in the model group showed wrinkled cells and a reduction in the number of cells， neurons with reduced sizes and Nissl bodies， enhanced fluorescence intensity of GFAP and Iba1 （P0.01）， and down-regulated expression of phosphorylated （p）-ERK， p-CREB， and BDNF （P0.05， P0.01） and mRNA levels of ERK and CREB （P0.01）. Compared with the model group， the CLMT group showed increased body weight （P0.05， P0.01）， restored cell morphology， with only a small number of ruptured cells， normal neuronal structure and morphology with obvious nuclei and abundant Nissl bodies， weakened fluorescence intensity of GFAP and Iba1 （P0.05， P0.01）， up-regulated mRNA levels of ERK and CREB （P0.05， P0.01） and protein levels of phosphorylated （p）-ERK， p-CREB， and BDNF in the hippocampal tissue （P0.05， P0.01）. The results of molecular docking indicated that nine active ingredients in CLMT had good binding affinity with ERK and CREB. ConclusionCLMT may ameliorate the hippocampal nerve injury in the mouse model of depression by regulating the ERK/CREB pathway.

ObjectiveTo investigate the protective effects and mechanisms of Bushen Zhuyun prescription （BSZY） on abortion rats with kidney deficiency-corpus luteum inhibition syndrome. MethodsAn abortion rat model with kidney deficiency-corpus luteum inhibition syndrome was constructed. Pregnant mice aged 8-10 weeks were randomly divided into a control group （Control）， a model group （Model）， low-dose BSZY （BSZY-L）， medium-dose BSZY （BSZY-M）， and high-dose BSZY （BSZY-H） groups （2.57， 5.14， 10.28 g·kg^-¹）， and a Zishen Yutai Pill （ZSYT） group （1.575 g·kg^-¹）. Hematoxylin-eosin （HE） staining was used to evaluate histopathological changes in ovarian and decidual tissue of rats in each group. Enzyme-linked immunosorbent assay （ELISA） was employed to measure levels of estrogen （E₂）， progesterone （P）， luteinizing hormone （LH）， prolactin （PRL）， and follicle-stimulating hormone （FSH） in serum. The candidate targets of BSZY were obtained from the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） and Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine （TCMIP） v2.0 databases， while disease targets for recurrent spontaneous abortion （RSA） were retrieved from GeneCards， DrugBank， Online Mendelian Inheritance in Man （OMIM）， and Therapeutic Target Database （TTD）. The intersection targets were identified by the Venny 2.1.0 platform. Pathway enrichment analysis was conducted based on the Metascape database to predict the potential mechanisms of BSZY. Additionally. Western blot was used to verify the effects of BSZY on the expression of estrogen receptor （ERα）， phosphatidylinositol 3-kinase （PI3K）， and protein kinase B （Akt） and explore its protective mechanism on RSA rats. ResultsCompared with the control group， the model group exhibited significantly decreased uterine， ovarian， and embryonic wet weights （P<0.05， P<0.01）， with an abortion rate of 57.18%. The ovarian tissue showed varying degrees of reduction in primordial follicles， primary follicles， mature follicles， and corpora lutea， along with a large number of atretic follicles. The endometrium was thinner， and decidual tissue exhibited cellular edema and disorganized arrangement. In contrast， compared with the model group， the BSZY groups at all doses and the ZSYT group demonstrated increased uterine， ovarian， and embryonic wet weights， along with a reduced abortion rate. The number of primordial follicles， primary follicles， mature follicles， and corpora lutea increased， while atretic follicles decreased. The endometrium thickened， and decidual tissue displayed normal cellular structure with tight arrangement. Additionally， the model group showed significantly decreased levels of E₂， P， PRL， and FSH in serum （P<0.05， P<0.01）， along with a decreasing trend in LH level. In contrast， the BSZY groups at all doses exhibited significantly elevated levels of E₂， P， LH， PRL， and FSH in serum （P<0.05， P<0.01）. Network pharmacology predictions suggested that BSZY may exert protective effects against abortion in rats by activating the ERα/PI3K/Akt signaling pathway. Western blot results confirmed that BSZY significantly upregulated the expression of ERα， PI3K， and p-Akt proteins （P<0.05， P<0.01）. ConclusionBSZY has a protective effect on the abortion rats with kidney deficiency-corpus luteum inhibition syndrome， possibly by activating the ERα/PI3K/Akt signaling pathway to reduce ovarian apoptosis and regulate endocrine function， thereby lowering the abortion rate.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve

Glioma represents the most prevalent malignant tumor of the central nervous system, with chemotherapy serving as an essential adjunctive treatment. However, most chemotherapeutic agents exhibit limited ability to penetrate the blood-brain barrier (BBB). This study introduced a novel dual-targeting strategy for glioma therapy by modulating the formation of nanobody-driven protein coronas to enhance the brain and tumor-targeting efficiency of hydrophobic cisplatin prodrug-loaded lipid nanoparticles (C8Pt-Ls). Specifically, nanobodies (Nbs) with fibrinogen-binding capabilities were conjugated to the surface of C8Pt-Ls, resulting in the generation of Nb-C8Pt-Ls. Within the bloodstream, Nb-C8Pt-Ls could bound more fibrinogen, forming the protein corona that specifically interacted with LRP-1, a receptor highly expressed on the BBB. This interaction enabled a "Hitchhiking Effect" mechanism, facilitating efficient trans-BBB transport and promoting effective brain targeting. Additionally, the protein corona interacted with LRP-1, which is also overexpressed in glioma cells, achieving precise tumor targeting. Computational simulations and SPR detection clarified the molecular interaction mechanism of the Nb-fibrinogen-(LRP-1) complex, confirming its binding specificity and stability. Our results demonstrated that this strategy significantly enhanced C8Pt accumulation in brain tissues and tumors, induced apoptosis in glioma cells, and improved therapeutic efficacy. This study provides a novel framework for glioma therapy and underscores the potential of protein corona modulation-based dual-targeting strategies in advancing treatments for brain tumors.

Objective: To identify core acupoint patterns and elucidate the molecular mechanisms of acupuncture for primary depressive disorder (PDD) through data mining and network analysis. Methods: A comprehensive literature search was conducted across PubMed, Embase, Ovid Technologies (OVID), Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), China National Knowledge Infrastructure Database (VIP), Wanfang Data, and SinoMed Database from database foundation to January 31, 2025, for clinical studies on acupuncture treatment of PDD. Descriptive statistics, high-frequency acupoint analysis, degree and betweenness centrality evaluation, and core acupoint prescription mining identified predominant therapeutic combinations for PDD. Network acupuncture was used to predict therapeutic target for the core acupoint prescription. Subsequent protein-protein interaction (PPI) network and molecular complex detection (MCODE) analyses were conducted to identify the key targets and functional modules. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses explored the underlying biological mechanisms of the core acupoint prescription in treating PDD. Results: A total of 57 acupoint prescriptions underwent systematic analysis. The core therapeutic combinations comprised Baihui (GV20), Yintang (GV29), Neiguan (PC6), Hegu (LI4), and Shenmen (HT7). Network acupuncture analysis identified 88 potential therapeutic targets (79 overlapping with PDD), while PPI network analysis revealed central regulatory nodes, including interleukin (IL)-6, IL-1β, tumor necrosis factor (TNF)-α, toll-like receptor 4 (TLR4), IL-10, brain-derived neurotrophic factor (BDNF), transforming growth factor (TGF)-β1, C-X-C motif chemokine ligand 10 (CXCL10), mitogen-activated protein kinase 3 (MAPK3), and nitric oxide synthase 1 (NOS1). MCODE-based modular analysis further elucidated three functionally coherent clusters: inflammation-homeostasis (score = 6.571), plasticity-neurotransmission (score = 3.143), and oxidative stress (score = 3.000). GO and KEGG analyses demonstrated significant enrichment of the MAPK, phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), and hypoxia-inducible factor (HIF)-1 signaling pathways. These mechanistic insights suggested that the antidepressant effects mediated through mechanisms of neuroinflammatory regulation, neuroplasticity restoration, and immune-oxidative stress homeostasis. Conclusion This study reveals that acupuncture alleviates depression through a multi-level mechanism, primarily involving the neuroinflammation suppression, neuroplasticity enhancement, and oxidative stress regulation. These findings systematically clarify the underlying mechanisms of acupuncture’s antidepressant effects and identify novel therapeutic targets for further mechanistic research.

Objective To construct risk models for predicting the occurrence of high altitude de-acclimatization syndrome(HADAS)in the population returning from the plateau to the plain based on different machine learning algorithms and validate the predicting efficiency of these models.Methods Field or online surveys were conducted on the individuals who had ended their high-altitude living and returned to the plain areas from November 2020 to February 2024.Basic information,chronic mountain sickness(CMS),HADAS symptoms and other data were collected.With the inclusion and exclusion criteria,totally 1 095 individuals were subjected and assigned into the modeling group.Positive events were defined as HADAS score>5.Then the modelling group was divided into a training set(n=766)and an internal test set(n=329)in a 7∶3 ratio.Least absolute shrinkage and selection operator(LASSO)regression was used to select independent variables.Risk prediction models for high-altitude adaptation symptoms were built based on 8 machine learning methods,including multiple factor logistic regression(LR),decision tree(DT),random forest(RF),eXtreme gradient boosting(XGB),support vector machine(SVM),K-nearest neighbor(KNN),light gradient boosting(LGB)and na?ve bayes(NB).The models were compared and evaluated using receiver operating characteristic(ROC)curves,calibration curves and confusion matrices in the internal test set.The final model was presented using a nomogram or Shapley additive explanations(SHAP)algorithm.In August 2024,another 132 individuals who returned to the plains and met the same criteria were recruited and served as the external validation group.Results There were 549 individuals(50.14%)out of the 1 095 subjects having HADAS symptoms.LASSO regression identified CMS score,age and duration of high-altitude residence as significant predictors.Among the 8 machine learning algorithms,the LR model was identified as the best,with an area under the curve(AUC)value of 0.819(95%CI:0.789～0.850)and 0.841(95%CI:0.799～0.884),and an F1 score of 0.801 in the internal test set,respectively,and the AUC value and F1 score of the LR model were the largest among the 8 models in the internal test set.Spiegelhalter Z test of the calibration curve of the LR model indicated that its P=0.703 in the training set while P=0.281 in the internal test set.The AUC value of the LR model was 0.867(95%CI:0.765～0.969)in the external validation set.Conclusion The LR model constructed based on indicators including CMS score,age and duration of high-altitude residence has a good overall performance in the internal test set,and good discriminating effect in the external validation set.The constructed nomogram is convenient for application.

Objective To explore the repair effect and mechanism of human amniotic mesenchymal stem cells(hAMSCs)on endometrial injury.Methods hAMSCs were isolated using a two-enzyme digestion and then cultured.The third-passage(P3)cells were harvested to detect the surface markers by flow cytometry and to identify their trilineage differentiation potentials.Eighteen nulliparous female SD rats(8～9 weeks old,weighing 250～280 g)were randomly divided into 3 groups(n=6):normal control group,model group,and hAMSCs group.A rat model of intrauterine adhesions(IUA)was established in SD rats by using curettage combined with lipopolysaccharide(LPS)infection.In 2 weeks after modeling,the hAMSCs group received a bilateral uterine horn transplantation of 0.2 mL hAMSCs(1.0×10? cells/mL),while the model group received a same volume of PBS into both uterine horns.All rats were sacrificed in 2 weeks after transplantation.HE and Masson staining was used to observe endometrial thickness and gland number as well as endometrial fibrosis area.RT-qPCR and Western blotting were performed to detect the mRNA and protein levels of TGF-β1,Smad3,Smad7,epithelial-mesenchymal transition(EMT)markers(E-cadherin,Vimentin),fibrosis factor α-SMA,and endometrial estrogen receptor(ER)and progesterone receptor(PR)in endometrial tissues.Results The obtained cells were identified as hAMSCs due to the characteristics of surface markers and differentiation potentials.Compared with the normal control group,the model group showed decreased endometrial thickness,reduced gland number,increased fibrosis area,and enhanced mRNA and protein levels of fibrosis-related factors TGF-β1,Smad3,Vimentin,and α-SMA(P<0.01),while down-regulation of fibrosis-inhibiting molecule Smad7,the EMT marker E-cadherin,and endometrial receptors ER and PR at both mRNA and protein levels(P<0.01).hAMSCs transplantation increased endometrial thickness and gland number,decreased fibrosis area,and down-regulated mRNA expression of the aforementioned fibrosis-related factors(P<0.01),and up-regulated the mRNA expression levels of Smad7,E-cadherin,ER,and PR(P<0.01).The hAMSCs group also exhibited obviously down-regulated protein levels of TGF-β1,Smad3,and α-SMA(P<0.05),while enhanced protein levels of Smad7 and PR(P<0.05).Conclusion Intrauterine transplantation of hAMSCs can promote the repair of endometrial injury,and inhibits endometrial EMT and fibrosis through the TGF-β1/Smad7 signaling pathway.

Objective: To explore the role of N6-methyladenosine(m6A) modification of RNA and Methyltransferase like Protein 14 methyltransferase(METTL14) in the pathogenesis of early-onset preeclampsia(ePE). Methods: Placental tissues of 15 pregnant women with early-onset preeclampsia and 15 normal pregnant women were collected. The level of m6A was determined by colorimetry, and the expression of METTL14 was determined by RT-qPCR, Western blot and immunohistochemistry(IHC) experiments. By transfecting siRNA and plasmid, METTL14 levels of trophoblast cells were knocked down and overexpressed, and cell phenotype experiments were carried out in vitro. The effects of METTL14 on the proliferation, migration and invasion of trophoblast cells were investigated by CCK-8, scratch assay, Transwell assay and invasion assay. Results: The level of m6A in placental tissue of ePE was lower than that of normal pregnancy. METTL14 was mainly expressed in the nuclei of trophoblast cells. Compared with normal pregnancy, the expression of METTL14 in placental tissue of ePE decreased, and thelevel of METTL14 mRNA was positively correlated with the level of m6A in placental tissue. The results of the CCK-8 experiment showed that compared with the control group, knockdown of METTL14 expression in trophoblast cells significantly reduced the cell proliferation rate, while the proliferation ability of trophoblast cells with overexpressed METTL14 was enhanced. The results of the scratch test showed that compared with the control group, the relative healing rate of scratches was significantly reduced after METTL14 knockdown, while it increased after the overexpression of METTL14. The results of the Transwell assay and invasion assay showed that compared with the control group, after knockdown of METTL14, the number of trophoblast cells passing through the chamber was significantly reduced, while the number of trophoblast cells with overexpressed METTL14 passing through the chamber increased. Conclusion The total RNA m6A modification level in placental tissue of ePE is lower than that in the normal pregnancy group. The down-regulation of methyltransferase METTL14 is involved in the regulation of the total RNA m6A modification level. The overexpression of METTL14 can enhance the proliferation, migration and invasion abilities of trophoblast cells. It provides a new perspective for exploring the pathogenesis of early-onset preeclampsia.