Polycystic ovary syndrome（PCOS） and its resulting infertility is one of the common diseases of gynecology and reproductive endocrinology. The phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt） signaling pathway is relatively well-studied in the development of intervention in PCOS， and the experiments on PCOS in rats conducted by traditional Chinese medicine through this signaling pathway is also the main direction of mechanistic research. In this paper， 20 articles published in academic journals in the past 5 years were selected through the corresponding criteria， and the objective situation and existing problems of the selected research projects were analyzed from five aspects， namely， baseline data， modeling and treatment， grouping， evaluative indexes， and pharmacodynamic indexes. It is found that there were different degrees of problems in each research project， such as the observation indicators of modeling， criteria for judging the success of the model， the treatment period， the calculation of dosage of prescription/active ingredients and specific dosage were not clearly defined， which could easily lead the bias of the results or reduce the validity of experimental data. Based on this， the list of PCOS rat experimental research operations was formed， involving five categories of experimental rats， model construction， study implementation， outcome measures and analysis and report with a total of 21 operation lists， with a view to provide a reference for the subsequent PCOS experiments related to scientific research and helping to form high-quality results.

ObjectiveTo construct a large language model （LLM）-based intelligent pre-consultation system for traditional Chinese medicine （TCM） to improve efficacy of clinical practice. MethodsA TCM large language model was fine-tuned using DeepSpeed ZeRO-3 distributed training strategy based on YAYI 2-30B. A weighted undirected graph network was designed and an agent-based syndrome differentiation model was established based on relationship data extracted from TCM literature and clinical records. An agent collaboration framework was developed to integrate the TCM LLM with the syndrome differentiation model. Model performance was comprehensively evaluated by Loss function， BLEU-4， and ROUGE-L metrics， through which training convergence， text generation quality， and language understanding capability were assessed. Professional knowledge test sets were developed to evaluate system proficiency in TCM physician licensure content， TCM pharmacist licensure content， TCM symptom terminology recognition， and meridian identification. Clinical tests were conducted to compare the system with attending physicians in terms of diagnostic accuracy， consultation rounds， and consultation duration. ResultsAfter 100 000 iterations， the training loss value was gradually stabilized at about 0.7±0.08， indicating that the TCM-LLM has been trained and has good generalization ability. The TCM-LLM scored 0.38 in BLEU-4 and 0.62 in ROUGE-L， suggesting that its natural language processing ability meets the standard. We obtained 2715 symptom terms， 505 relationships between diseases and syndromes， 1011 relationships between diseases and main symptoms， and 1 303 600 relationships among different symptoms， and constructed the Agent of syndrome differentiation model. The accuracy rates in the simulated tests for TCM practitioners， licensed pharmacists of Chinese materia medica， recognition of TCM symptom terminology， and meridian recognition were 94.09%， 78.00%， 87.50%， and 68.80%， respectively. In clinical tests， the syndrome differentiation accuracy of the system reached 88.33%， with fewer consultation rounds and shorter consultation time compared to the attending physicians （P＜0.01）， suggesting that the system has a certain pre- consultation ability. ConclusionThe LLM-based intelligent TCM pre-diagnosis system could simulate diagnostic thinking of TCM physicians to a certain extent. After understanding the patients' natural language， it collects all the patient's symptom through guided questioning， thereby enhancing the diagnostic and treatment efficiency of physicians as well as the consultation experience of the patients.

Mitochondria, ubiquitous energy-producing organelles in eukaryotic cells, can have their normal functions disrupted by bacterial infections, leading to mitochondrial dysfunction. This dysfunction is closely associated with inflammatory diseases. Periodontitis, a chronic inflammatory disorder of periodontal tissues caused by pathogenic microorganisms, has been increasingly linked to mitochondrial dysfunction in its pathogenesis and progression. Compared to healthy periodontal tissues, inflammatory lesions exhibit more pronounced mitochondrial dysfunction—a pathological process that is strongly correlated with periodontal pathogen infection. Studies reveal that these pathogens disrupt mitochondrial homeostasis in host cells (e.g., gingival epithelial cells and fibroblasts) through multiple mechanisms, including disrupting mitochondrial biogenesis, altering mitochondrial dynamics (promoting excessive fission), inhibiting mitophagy, impairing mitochondrial dysfunction-associated apoptosis, and inducing endogenous oxidative stress, which upregulates pro-inflammatory cytokines. Collectively, these processes drive the establishment and persistence of an inflammatory microenvironment. This review explores how periodontal pathogens affect mitochondrial function and their mechanistic contributions to periodontitis progression, with the goal of providing novel insights for developing mitochondria-targeted therapeutic strategies.

The human oral microbiome harbors one of the most diverse microbial communities in the human body, playing critical roles in oral and systemic health. Recent technological innovations are propelling the characterization and manipulation of oral microbiota. High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes. New long-read platforms improve genome assembly from complex samples. Single-cell genomics provides insights into uncultured taxa. Advanced imaging modalities including fluorescence, mass spectrometry, and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution. Fluorescence techniques link phylogenetic identity with localization. Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification. Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches. Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly, gene expression, metabolites, microenvironments, virulence mechanisms, and microbe-host interfaces in the context of health and disease. However, significant knowledge gaps persist regarding community origins, developmental trajectories, homeostasis versus dysbiosis triggers, functional biomarkers, and strategies to deliberately reshape the oral microbiome for therapeutic benefit. The convergence of sequencing, imaging, cultureomics, synthetic systems, and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict, prevent, diagnose, and treat associated oral diseases.
Humans ; Phylogeny ; Biomimetics ; Dysbiosis ; Homeostasis ; Mass Spectrometry

Aim To research the neuroprotective effect of Haikun Shenxi (HKSX) medicated serum on N2a/ App695 cells and the underlying mechanism. Methods HKSX medicated serum was prepared and carbohydrate components in it was analyzed using high performance thin layer chromatography (HPTLC) . N2a/ App695 cells were intervened with HKSX medicated serum, the cytotoxicity of HKSX medicated serum was measured by MTT; AP[_

Aim To screen and study the expression of long non-coding RNA (IncRNA) in rats with middle cerebral artery occlusion (MCAO) with MCAO treated with Tao Hong Si Wu decoction (THSWD) and determine the possible molecular mechanism of THSWD in treating MCAO rats. Methods Three cerebral hemisphere tissue were obtained from the control group, MCAO group and MCAO + THSWD group. RNA sequencing technology was used to identify IncRNA gene expression in the three groups. THSWD-regulated IncRNA genes were identified, and then a THSWD-regu-lated IncRNA-mRNA network was constructed. MCODE plug-in units were used to identify the modules of IncRNA-mRNA networks. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) were used to analyze the enriched biological functions and signaling pathways. Cis- and trans-regulatory genes for THSWD-regulated IncRNAs were identified. Reverse transcription real-time quantitative pol-ymerase chain reaction (RT-qPCR) was used to verify IncRNAs. Molecular docking was used to identify IncRNA-mRNA network targets and pathway-associated proteins. Results In MCAO rats, THSWD regulated a total of 302 IncRNAs. Bioinformatics analysis suggested that some core IncRNAs might play an important role in the treatment of MCAO rats with THSWD, and we further found that THSWD might also treat MCAO rats through multiple pathways such as IncRNA-mRNA network and network-enriched complement and coagulation cascades. The results of molecular docking showed that the active compounds gallic acid and a-mygdalin of THSWD had a certain binding ability to protein targets. Conclusions THSWD can protect the brain injury of MCAO rats through IncRNA, which may provide new insights for the treatment of ischemic stroke with THSWD.

Objective:To explore the clinical application value of pre-breathing mode in double-low imaging of 320-slices computed tomography(CT)for pulmonary artery.Methods:A total of 100 patients who underwent CT pulmonary angiography(CTPA)for suspected pulmonary embolism(PE)in Liuzhou People's Hospital from July 2021 to September 2022 were prospectively selected as the research subjects and they were randomly divided into observation group and control group,with 50 cases in each group.The patients of the control group adopted conventional breathing mode(the breathing password was activated after reaching the threshold,and the scan was triggered after 6 s),while the patients of the observation group adopted the pre-breathing mode(the breathing password was activated after 1 or 2 seconds,and the scan was triggered after reaching the threshold).Both two groups adopted double low-technique scan of 320 slices CT.The differences in delay time,radiation dose,the points of subjective and objective image quality,and other indicators were compared between the two groups.Results:The volume CT dose index(CTDIvol),dose length product(DLP),effective dose(ED)and delay time of the observation group were significantly lower than those of the control group(t=76.230,30.225,12.282,7.088,P<0.05),respectively.The comparison of the subjective points of image qualities between the two groups indicated that there were 25 cases with 5 points,23 cases with 4 points and 2 cases with 3 points in the observation group,and there were 21 cases with 5 points,26 cases with 4 points and 3 cases with 3 points in the control group.There was no significant difference in the averagely subjective points of image qualities between two groups(P>0.05).The signal-to-noise ratio(SNR)and signal to noise ratio(CNR)of the observation group were significantly lower than those of the control group,and the noise level(SD)of the observation group was significantly higher than that of the control group(t=25.441,23.886、11.426,P<0.05),respectively.The CT values of the artery trunk of right pulmonary,artery branch of right pulmonary,artery trunk of left pulmonary and artery branch of left pulmonary in the observation group were significantly higher than those in the control group(t=2.256,2.225,2.042,2.277,P<0.05),respectively.Conclusion:The pre-breathing mode can effectively improve CTPA image quality,and reduce radiation dose and the dosage of contrast agent,which clinical application effect is significant.It is worth learning.

Objective: To analyze the trends and hotspots in research related to microbiomes and microbes of dental caries; in addition, the study seeks to provide a reference for caries research. Methods: We searched the Web of Science Core Collection (WOSCC) to extract relevant literature in the field of microbiomes and microbes of dental caries published from 2014 to 2023. We used bibliometric visualization evaluation methods such as CiteSpace to conduct visualized analysis of factors that include the number of publications, journals, countries, authors, institutions, co-cited references, and keywords. Results: A total of 3 192 references were extracted, including 2 664 articles and 528 reviews. The number of annual publications is increasing. The United States and China lead the number of publications, with the United States demonstrating a greater capacity for international collaboration. The top 10 journals in percentage of literature are mainly in the field of dentistry followed by the field of microbiology. The author cooperation networks with the highest number of publications include the network led by Zhou Xuedong of Sichuan University, and the network led by Xu Hockin H.K and Weir Michael D of the University of Maryland, Baltimore. The research on microbiomes and microbes of dental caries focuses on the cariogenic toxicity and interaction of microorganisms, oral microbiomes, and the relationship between dental caries and systemic diseases. The articles with high citation frequency mainly involve topics such as dental caries, oral biofilm, oral microbiota, and Streptococcus mutans. Keyword research showed that “dental caries,” “Streptococcus mutans,” “bacteria,” “dental plaque,” and “antibacterial activity” have been the primary focus of research in the last decade. The number of keywords, such as “health” and “oral health,” is on the rise. The latest emergence of “gut microbiome/microbiota” suggests that the oral gut microbiome axis is at the forefront of research in this field, and researchers’ focus is gradually shifting toward the connection between dental caries and systemic diseases. Conclusion Over the last decade, the number of publications in the field microbiomes and microbes of dental caries has increased annually. This research trend will be the multi-omics of the overall oral microbiome, and new research methods and techniques will contribute to the field of cariology.

The human oral microbiome harbors one of the most diverse microbial communities in the human body,playing critical roles in oral and systemic health.Recent technological innovations are propelling the characterization and manipulation of oral microbiota.High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes.New long-read platforms improve genome assembly from complex samples.Single-cell genomics provides insights into uncultured taxa.Advanced imaging modalities including fluorescence,mass spectrometry,and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution.Fluorescence techniques link phylogenetic identity with localization.Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification.Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches.Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly,gene expression,metabolites,microenvironments,virulence mechanisms,and microbe-host interfaces in the context of health and disease.However,significant knowledge gaps persist regarding community origins,developmental trajectories,homeostasis versus dysbiosis triggers,functional biomarkers,and strategies to deliberately reshape the oral microbiome for therapeutic benefit.The convergence of sequencing,imaging,cultureomics,synthetic systems,and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict,prevent,diagnose,and treat associated oral diseases.

The human oral microbiome harbors one of the most diverse microbial communities in the human body,playing critical roles in oral and systemic health.Recent technological innovations are propelling the characterization and manipulation of oral microbiota.High-throughput sequencing enables comprehensive taxonomic and functional profiling of oral microbiomes.New long-read platforms improve genome assembly from complex samples.Single-cell genomics provides insights into uncultured taxa.Advanced imaging modalities including fluorescence,mass spectrometry,and Raman spectroscopy have enabled the visualization of the spatial organization and interactions of oral microbes with increasing resolution.Fluorescence techniques link phylogenetic identity with localization.Mass spectrometry imaging reveals metabolic niches and activities while Raman spectroscopy generates rapid biomolecular fingerprints for classification.Culturomics facilitates the isolation and cultivation of novel fastidious oral taxa using high-throughput approaches.Ongoing integration of these technologies holds the promise of transforming our understanding of oral microbiome assembly,gene expression,metabolites,microenvironments,virulence mechanisms,and microbe-host interfaces in the context of health and disease.However,significant knowledge gaps persist regarding community origins,developmental trajectories,homeostasis versus dysbiosis triggers,functional biomarkers,and strategies to deliberately reshape the oral microbiome for therapeutic benefit.The convergence of sequencing,imaging,cultureomics,synthetic systems,and biomimetic models will provide unprecedented insights into the oral microbiome and offer opportunities to predict,prevent,diagnose,and treat associated oral diseases.