Glaucoma is a multifactorial degenerative optic neuropathy, and its irreversible and blinding pathological characteristics mainly come from the damage to the optic nerve, namely glaucomatous optic neuropathy(GON). The difficulty in the treatment of GON lies in the early intervention, and currently there is no optic neuroprotective drug for the treatment of all types of GON. The death of retinal ganglion cells(RGCs)is the core pathological change caused by various pathogenic mechanisms of GON. Recent studies have found that the widespread second messenger cyclic adenosine 3', 5' -monophosphate(cAMP)and its downstream effector protein kinase A(PKA)signal cascade play an important role in the pathogenesis of GON. It can also inhibit the apoptosis of RGCs and play a protective and therapeutic role in glaucoma. Therefore, this article reviews the role of cAMP/PKA pathway in the pathophysiological development of GON, focusing on its effects on glaucoma intraocular pressure regulation, oxidative stress, neuroinflammation and optic nerve degeneration, in order to find a common central regulatory target for the optic nerve damage caused by different pathological mechanisms of GON and promote the further understanding and clinical treatment of this disease.

Artificial intelligence (AI) technology enhances the function of acupuncture clinical decision support system (CDSS) by promoting the accuracy of its diagnosis, assisting the formulation of personalized therapeutic regimen, and realizing the scientific and precise evaluation of its therapeutic effect. This paper deeply analyzes the unique advantages of AI-based acupuncture CDSS, including the intelligence and high efficiency. Besides, it points out the challenges of data security, the lack of model interpretation and the complexity of interdisciplinary cooperation in the development of acupuncture CDSS. With the continuous development and improvement of AI technology, acupuncture CDSS is expected to play a more important role in the fields of personalized medicine, telemedicine and disease prevention, and to further advance the efficiency and effect of acupuncture treatment, drive the modernization of acupuncture, and enhance its position and influence in the global healthcare system.
Humans ; Acupuncture Therapy ; Artificial Intelligence ; Decision Support Systems, Clinical

BACKGROUND: Temozolomide (TMZ) resistance is a significant challenge in treating glioblastoma (GBM). Collagen remodeling has been shown to be a critical factor for therapy resistance in other cancers. This study aimed to investigate the mechanism of TMZ chemoresistance by GBM cells reprogramming collagens. METHODS: Key extracellular matrix components, including collagens, were examined in paired primary and recurrent GBM samples as well as in TMZ-treated spontaneous and grafted GBM murine models. Human GBM cell lines (U251, TS667) and mouse primary GBM cells were used for in vitro studies. RNA-sequencing analysis, chromatin immunoprecipitation, immunoprecipitation-mass spectrometry, and co-immunoprecipitation assays were conducted to explore the mechanisms involved in collagen accumulation. A series of in vitro and in vivo experiments were designed to assess the role of the collagen regulators prolyl 4-hydroxylase subunit alpha 1 (P4HA1) and yes-associated protein (YAP) in sensitizing GBM cells to TMZ. RESULTS: This study revealed that TMZ exposure significantly elevated collagen type I (COL I) expression in both GBM patients and murine models. Collagen accumulation sustained GBM cell survival under TMZ-induced stress, contributing to enhanced TMZ resistance. Mechanistically, P4HA1 directly binded to and hydroxylated YAP, preventing ubiquitination-mediated YAP degradation. Stabilized YAP robustly drove collagen type I alpha 1 ( COL1A1) transcription, leading to increased collagen deposition. Disruption of the P4HA1-YAP axis effectively reduced COL I deposition, sensitized GBM cells to TMZ, and significantly improved mouse survival. CONCLUSION P4HA1 maintained YAP-mediated COL1A1 transcription, leading to collagen accumulation and promoting chemoresistance in GBM.
Temozolomide ; Humans ; Glioblastoma/drug therapy* ; Animals ; Mice ; Cell Line, Tumor ; Drug Resistance, Neoplasm/genetics* ; YAP-Signaling Proteins ; Hydroxylation ; Dacarbazine/pharmacology* ; Adaptor Proteins, Signal Transducing/metabolism* ; Transcription Factors/metabolism* ; Collagen/biosynthesis* ; Collagen Type I/metabolism* ; Prolyl Hydroxylases/metabolism* ; Antineoplastic Agents, Alkylating/therapeutic use*

OBJECTIVE: To review the research progress of strontium (Sr) modified β-tricalcium phosphate composite biomaterials (SrTCP) promoting osteogenesis through immune regulation, and provides reference and theoretical support for the further development and research of SrTCP bone repair materials in bone tissue engineering in the future. METHODS: The literature about SrTCP promoting osteogenesis through immune regulation at home and abroad in recent years was extensively reviewed, and the preparation methods, immune mechanism and application of promoting osteogenesis were summarized and analyzed. RESULTS: The preparation methods of SrTCP include solid-state reaction sintering method, solution combustion quenching method, direct doping method, ion substitution method, etc. SrTCP has immune regulatory effects, which can play an immune regulatory role in inducing macrophage polarization, inducing angiogenesis and anti oxidative stress to promote osteogenesis. CONCLUSION At present, studies have shown that SrTCP can promote bone defect repair through immune regulation. Subsequent studies can start from the control of the optimal repair concentration and release rate of Sr, and further clarify the specific mechanism of SrTCP in promoting angiogenesis and anti oxidative stress, which is helpful to develop new materials for bone defect repair.
Calcium Phosphates/pharmacology* ; Strontium/pharmacology* ; Biocompatible Materials/pharmacology* ; Humans ; Osteogenesis/drug effects* ; Tissue Engineering/methods* ; Bone Substitutes/pharmacology* ; Bone Regeneration/drug effects* ; Animals ; Tissue Scaffolds/chemistry* ; Neovascularization, Physiologic/drug effects* ; Macrophages/immunology*

Food-derived bioactive peptides (FBPs), particularly those with ten or fewer amino acid residues and a molecular weight below 1300 Da, have gained increasing attention for their safe, diverse structures and specific biological activities. The development of FBP-based functional foods and potential medications depends on understanding their structure‒activity relationships (SARs), stability, and bioavailability properties. In this review, we provide an in-depth overview of the roles of FBPs in treating various diseases, including Alzheimer's disease, hypertension, type 2 diabetes mellitus, liver diseases, and inflammatory bowel diseases, based on the literature from July 2017 to Mar. 2023. Subsequently, attention is directed toward elucidating the associations between the bioactivities and structural characteristics (e.g., molecular weight and the presence of specific amino acids within sequences and compositions) of FBPs. We also discuss in silico approaches for FBP screening and their limitations. Finally, we summarize recent advancements in formulation techniques to improve the bioavailability of FBPs in the food industry, thereby contributing to healthcare applications.
Humans ; Peptides/therapeutic use* ; Structure-Activity Relationship ; Functional Food ; Diabetes Mellitus, Type 2/drug therapy* ; Biological Availability ; Alzheimer Disease/drug therapy* ; Inflammatory Bowel Diseases/drug therapy* ; Hypertension/drug therapy* ; Liver Diseases/drug therapy* ; Bioactive Peptides, Dietary

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Objective:To explore the genetic etiology of a fetus with cryptophthalmos detected by prenatal ultrasonography.Methods:A fetus undergoing induced labor at 32nd gestational week due to absence of bilateral eye fissures detected by prenatal ultrasonography in January 2017 was selected as the study subject. Umbilical cord blood sample from the fetus and peripheral blood samples from its parents were collected for the extraction of genomic DNA. Pathogenic variants were screened through whole exome sequencing (WES) and verified by Sanger sequencing. Pathogenicity of candidate variants was verified by bioinformatic analysis and protein structure simulation. Based on the results of genetic testing, prenatal diagnosis was provided to the couple upon their subsequent pregnancy.Results:The couple had four adverse pregnancies previously. The aborted fetus was the fifth, with fused bilateral upper and lower eyelids, poorly developed eyeballs, adhesion of the cornea with the upper eyelid, low-set ears, and abnormal plantar creases, and was diagnosed with cryptophthalmos. WES and Sanger sequencing revealed that the fetus has harbored compound heterozygous variants of the FREM2 gene, namely c. 4537G>A (p.D1513N) and c.7292C>T (p.T2431M). Both variants were unreported associated with cryptophthalmos previously. Protein structure simulation showed that they may lead to loss of hydrogen bonds in the protein product. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), both variants were predicted to be likely pathogenic (PM1_Supporting+ PM2_Supporting+ PM5+ PP3+ PP4; PM2_Supporting+ PM3+ PP3+ PP4). The mother was performed prenatal diagnosis in her sixth pregnancy based on the variants detected in this family, and delivered a daughter with normal phenotype. Conclusion:The FREM2: c. 4537G>A and c. 7292C>T compound heterozygous variants probably underlay the pathogenesis of cryptophthalmos in this fetus. Above finding has enriched the mutational spectrum of the FREM2 gene.

In recent years, the incidence of cancer in China has been increasing steadily. Advancing primary prevention measures for cancers could be an effective strategy to curb this trend. Diet has been considered a modifiable and shared risk factor for various cancers. Studying dietary patterns, with consideration of the interactions between foods and nutrients, has a practical implication for cancer prevention. This study provided an overview of dietary pattern extraction methods, summarized the research findings on the association between dietary patterns and cancers in the digestive system, respiratory system, and genitourinary system, and elucidated the potential mechanisms underlying these associations, in order to provide scientific references for future research in this field.

Identifying the compound formulae-related xenobiotics in bio-samples is full of challenges.Conventional strategies always exhibit the insufficiencies in overall coverage,analytical efficiency,and degree of automation,and the results highly rely on the personal knowledge and experience.The goal of this work was to establish a software-aided approach,by integrating ultra-high performance liquid chromatography/ion-mobility quadrupole time-of-flight mass spectrometry(UHPLC/IM-QTOF-MS)and in-house high-definition MS2 library,to enhance the identification of prototypes and metabolites of the compound formulae in vivo,taking Sishen formula(SSF)as a template.Seven different MS2 acquisition methods were compared,which demonstrated the potency of a hybrid scan approach(namely high-definition data-independent/data-dependent acquisition(HDDIDDA))in the identification precision,MS1 coverage,and MS2 spectra quality.The HDDIDDA data for 55 reference compounds,four component drugs,and SSF,together with the rat bio-samples(e.g.,plasma,urine,feces,liver,and kidney),were acquired.Based on the UNIFI? platform(Waters),the efficient data processing workflows were estab-lished by combining mass defect filtering(MDF)-induced classification,diagnostic product ions(DPIs),and neutral loss filtering(NLF)-dominated structural confirmation.The high-definition MS2 spectral li-braries,dubbed in vitro-SSF and in vivo-SSF,were elaborated,enabling the efficient and automatic identification of SSF-associated xenobiotics in diverse rat bio-samples.Consequently,118 prototypes and 206 metabolites of SSF were identified,with the identification rate reaching 80.51％and 79.61％,respectively.The metabolic pathways mainly involved the oxidation,reduction,hydrolysis,sulfation,methylation,demethylation,acetylation,glucuronidation,and the combined reactions.Conclusively,the proposed strategy can drive the identification of compound formulae-related xenobiotics in vivo in an intelligent manner.