Objective: To examine the effect of intracellular vesicles (IVs) and extracellular vesicles (EVs) that originated from periodontal ligament stem cells (PDLSCs) on the osteogenic differentiation of PDLSCs within a lipopolysaccharide (LPS)-simulated inflammatory microenvironment, and to provide new insights for the application of IVs in the repair and regeneration of periodontal tissue in periodontitis. Methods: Ethical approval was obtained from the institution. Human-origin PDLSCs were extracted, and the IVs and EVs from PDLSCs at the 3rd-6th passages were gathered and identified using transmission electron microscopy, nano flow cytometry (Nano FCM) analysis, and Western Blot. The 3rd-6th generations of PDLSCs were categorized into the following groups: Control group, LPS group, LPS + 100 μg/mL EVs group (LPS+EVs group), and LPS + 100 μg/mL IVs group (LPS+IVs group). The effects of the IVs and EVs on the anti-inflammatory and osteogenic differentiation of PDLSCs in an inflammatory microenvironment were assessed by using a Cell Counting Kit-8 (CCK-8), enzyme-linked immunosorbent assay (ELISA), quantitative real-time polymerase chain reaction (qRT-PCR), Western Blot, alkaline phosphatase (ALP) staining, and alizarin red staining (ARS). Results: Under transmission electron microscopy, the IVs and EVs derived from PDLSCs displayed a double-layer membrane structure. NanoFCM analysis revealed that the average diameters of the IVs and EVs were 79.6 nm and 82.1 nm, respectively. Western Blot analysis indicated that the surface proteins CD9, CD63, and CD81 of the IVs and EVs were positively expressed, while calnexin was negatively expressed, indicating that IVs and EVs were successfully obtained. Compared with the Control group, the proliferation of PDLSCs in the LPS group was reduced, while the levels of inflammatory cytokine interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in the cell supernatant were increased, the mRNA expressions of osteogenic differentiation-related genes, including osteoblast-related genes runt-related transcription factor 2 (RUNX2), alkaline phosphatase (ALP), osteocalcin (OCN) of PDLSCs were reduced, the protein expressions of RUNX2 and osteopontin (OPN) were also decreased (P<0.05); compared with the LPS group, the proliferation of PDLSCs in the LPS+EVs group and LPS+IVs group were significantly increased, while the levels of IL-6, TNF-α were significantly reduced, and the mRNA expressions of RUNX2, ALP, OCN were significantly increased, the protein expressions of RUNX2 and OPN were also significantly increased (P<0.05). Further, in the inflammatory microenvironment, Compared with EVs, IVs more significantly promote the proliferation of PDLSCs, inhibit TNF-α expression, enhance the expression of RUNX2 mRNA, upregulate the expression of RUNX2 and OPN proteins, increase ALP activity, and promote the formation of mineralized nodules (P<0.05). Conclusion IVs and EVs derived from PDLSCs can boost the proliferation of PDLSCs in an inflammatory microenvironment, inhibit the expression of inflammatory factors, and advance the osteogenic differentiation of PDLSCs. The anti-inflammatory and osteogenic effects of IVs are superior to those of EVs.

The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

As the number of patients with compromised immune function increases and fungal resistance develops, so does the risk of contracting deadly fungi in humans. Both fungi and humans are eukaryotes, so identifying unique targets for antifungal drug development is difficult. In addition, the existing antifungal drugs are limited by toxicity, drug interaction and drug resistance in practical application, which leads to the increasing incidence and fatal rate of fungal infections. Therefore, it is urgent to develop new antifungal drugs. The semi-synthetic technology using microbial fermentation products from natural sources as lead compounds has become the most used method in structural modification of antifungal drugs due to its advantages of few reaction steps and easy operation. This paper will introduce the current status of natural antifungal drugs in clinical use, as well as the latest progress in the research and development of new semi-synthetic antifungal drugs, and summarize their mechanism of action, structural modifications, advantages and disadvantages, so as to provide reference for the subsequent development of new antifungal drugs.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveBased on transcriptomics， to explore the mechanism of Hei Xiaoyaosan regulating the phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt） signaling pathway to improve the learning and memory ability of insomnia rats with liver depression syndrome. MethodsSixty 8-week-old male SD rats were randomly divided into the blank group， model group， eszopiclone group （0.09 mg·kg^-1）， and low， medium， and high dose groups of Hei Xiaoyaosan （3.82， 7.65， 15.30 g·kg^-1）， with ten rats in each group. Except for the blank group， the other groups were induced insomnia rat model with liver depression by chronic restraint， tail clamping stimulation and intraperitoneal injection of p-chlorophenylalanine （PCPA）. Each treatment group received intragastric administration according to the specified dosage， once a day for 14 consecutive days. The pentobarbital sodium cooperative sleep test， open field test， and Morris water maze test were used to test the sleep quality， depressive-like behavior， and learning and memory abilities of rats. Additionally， enzyme-linked immunosorbent assay （ELISA） was used to detect the contents of 5-hydroxytryptamine （5-HT）， γ-aminobutyric acid （GABA）， brain-derived neurotrophic factor （BDNF）， glial cell line-derived neurotrophic factor （GDNF） and nitric oxide （NO） in hippocampus. Hematoxylin-eosin （HE） staining was performed to observe pathological changes of the hippocampal tissue， while terminal deoxynucleotidyl transferase deoxyuridine triphosphate （dUTP） nick end labeling （TUNEL） was used to evaluate apoptosis of hippocampal neurons. Transcriptomic sequencing technology was employed to identify differentially expressed genes in hippocampus between the model group and the blank group， as well as between the medium-dose group of Hei Xiaoyaosan and the model group. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analysis were performed on the intersecting genes. Subsequently， the enriched key genes and signaling pathways were analyzed and verified. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） was utilized to assess the mRNA expression levels of phosphatase and tensin homolog （PTEN）， B-cell lymphoma-2 （Bcl-2）-like protein 11 （BCL2L11）， and mitogen-activated protein kinase 1 （MAPK1） in hippocampus， and Western blot was employed to evaluate the protein expressions of PI3K， phosphorylation （p）-PI3K， Akt， p-Akt， Bcl-2， Bcl-2-associated X protein （Bax）， and cleaved Caspase-3 in the same tissue. ResultsCompared with the blank group， the model group exhibited a reduction in body weight， an increase in sleep latency， and a decrease in sleep duration （P<0.01）. Additionally， rats showed obvious depression-like behavior， and their learning and memory abilities decreased. Furthermore， the contents of 5-HT， GABA， NO， BDNF and GDNF in hippocampus decreased （P<0.01）. Histological examination revealed a disorganized cell arrangement in the CA1 region of the hippocampus， characterized by irregular cell shapes， a reduced cell count， deeply stained and pyknotic nuclei， increased vacuolar degeneration， and an elevated apoptosis rate （P<0.01）. Compared with the model group， the body weight of the high and medium dose groups of Hei Xiaoyaosan increased， the sleep latency shortened and the sleep time prolonged （P<0.05， P<0.01）. Additionally， depression-like behavior and learning and memory abilities of rats were significantly improved， the levels of 5-HT， GABA， NO， BDNF and GDNF in the hippocampus increased （P<0.05， P<0.01）. These interventions also ameliorated pathological damage in the hippocampal CA1 area and reduced the apoptosis of hippocampal neurons （P<0.01）. Transcriptomic sequencing results indicated that Hei Xiaoyaosan might exert a therapeutic effect by regulating PI3K/Akt pathway through key mRNAs such as PTEN， BCL2L11， and MAPK1. The roles of these key mRNAs and proteins within PI3K/Akt pathway were further validated. In comparison to the blank group， the expression levels of PTEN， BCL2L11 and MAPK1 mRNA in the hippocampus of rats in the model group were increased （P<0.01）， while the protein expression levels of p-PI3K， p-Akt and Bcl-2 were decreased （P<0.01）， and the protein expression levels of PTEN， Bax and cleaved Caspase-3 were increased （P<0.01）. Compared with the model group， the high-dose and medium-dose groups of Hei Xiaoyaosan could down-regulate the expressions of PTEN， BCL2L11 and MAPK1 mRNAs （P<0.01）， up-regulate the expressions of p-PI3K， p-Akt and Bcl-2 proteins （P<0.01）， and down-regulate the protein expressions of PTEN， Bax and cleaved Caspase-3 （P<0.05， P<0.01）. ConclusionHei Xiaoyaosan may regulate PI3K/Akt signaling pathway by down-regulating expressions of key genes such as PTEN， BCL2L11 and MAPK1， and thus improve the learning and memory abilities of insomnia rats with liver depression syndrome.

Cognitive impairment （CI） is a clinical syndrome characterized by progressive decline in advanced cognitive functions such as memory， thinking， and judgment. Its etiology and pathogenesis are complex， and there is currently a lack of specific drug interventions. Metformin， as a first-line hypoglycemic drug for type 2 diabetes， not only lowers blood glucose levels but also improves CI. This article reviews and summarizes the pharmacological effects and mechanisms of metformin in improving Alzheimer’s disease， diabetes cognitive impairment， cognitive impairment after chemotherapy， in order to provide novel insights and approaches for the treatment of CI-related diseases. Studies have shown that the mechanism by which MET intervenes in CI mainly includes regulating β-amyloid protein and tau protein metabolism， reducing insulin resistance， inhibiting neuroinflammation， improving synaptic plasticity， improving mitochondrial dysfunction， regulating gut microbiota and lipid metabolism， etc. Future research needs to be conducted through interdisciplinary collaboration， fully integrating multiple omics data， and combining advanced technologies to further reveal their mechanisms of effect.