Acori Tatarinowii Rhizoma is the dried rhizome of Acorus tatarinowii in the family of Tennantiaceae, which has the efficacy of opening up the orifices and expelling phlegm, awakening the mind and wisdom, and resolving dampness and opening up the stomach. Modern studies have shown that volatile oil is the main active ingredient of Acori Tatarinowii Rhizoma, and α-asarone and β-asarone have been proved to be the active ingredients in the volatile oil of Acori Tatarinowii Rhizoma, with pharmacological effects such as anti-Alzheimer's disease, antiepileptic, anti-Parkinson's disease, antidepressant, anticerebral ischemia/reperfusion injury, anti-thrombosis, lipid-lowering, and antitumor. By summarising and outlining the pharmacological effects of α-asarone and β-asarone and elucidating the possible mechanisms of their pharmacological effects, we can provide theoretical basis for the further research and clinical application of Acori Tatarinowii Rhizoma.
Allylbenzene Derivatives ; Acorus/chemistry* ; Anisoles/chemistry* ; Rhizome/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Humans ; Animals

This study primarily investigates the effect of Liuwei Dihuang Pills on the activation and proliferation of female germline stem cells(FGSCs) in the ovaries and cortex of mice with premature ovarian failure(POF), and how it improves ovarian function. ICR mice were randomly divided into the control group, model group, Liuwei Dihuang Pills group, Liuwei Dihuang Pills double-dose group, and estradiol valerate group. A mouse model of POF was established by intraperitoneal injection of cyclophosphamide. After successful modeling, the mice were treated with Liuwei Dihuang Pills or estradiol valerate for 28 days. Vaginal smears were prepared to observe the estrous cycle and body weight. After the last administration, mice were sacrificed and sampled. Serum levels of estradiol(E_2), follicle-stimulating hormone(FSH), luteinizing hormone(LH), and anti-Müllerian hormone(AMH) were measured by enzyme-linked immunosorbent assay(ELISA). Hematoxylin-eosin(HE) staining was used to observe ovarian morphology and to count follicles at all stages to evaluate ovarian function. Immunohistochemistry was used to detect the expression of mouse vasa homolog(MVH), a marker of ovarian FGSCs. Immunofluorescence staining, using co-labeling of MVH and proliferating cell nuclear antigen(PCNA), was used to detect the expression and localization of specific markers of FGSCs. Western blot was employed to assess the protein expression of MVH, octamer-binding transcription factor 4(Oct4), and PCNA in the ovaries. The results showed that compared with the control group, the model group exhibited disordered estrous cycles, decreased ovarian index, increased atretic follicles, and a reduced number of follicles at all stages. FSH and LH levels were significantly elevated, while AMH and E_2 levels were significantly reduced, indicating the success of the model. After treatment with Liuwei Dihuang Pills or estradiol valerate, hormone levels improved, the number of atretic follicles decreased, and the number of follicles at all stages increased. MVH marker protein and PCNA proliferative protein expression in ovarian tissue also increased. These results suggest that Liuwei Dihuang Pills regulate estrous cycles and hormone disorders in POF mice, promote the proliferation of FGSCs, improve follicular development in POF mice, and enhance ovarian function.
Animals ; Female ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Cell Proliferation/drug effects* ; Mice, Inbred ICR ; Ovary/cytology* ; Primary Ovarian Insufficiency/genetics* ; Follicle Stimulating Hormone/metabolism* ; Humans ; Anti-Mullerian Hormone/blood* ; Antineoplastic Agents/adverse effects* ; Luteinizing Hormone/metabolism* ; Cyclophosphamide/adverse effects*

OBJECTIVE: To elucidate the specific mechanisms by which electroacupuncture (EA) alleviates anxiety and fear behaviors associated with posttraumatic stress disorder (PTSD), focusing on the role of lipocalin-2 (Lcn2). METHODS: The PTSD mouse model was subjected to single prolonged stress and shock (SPS&S), and the animals received 15 min sessions of EA at Shenmen acupoint (HT7). Behavioral tests were used to investigate the effects of EA at HT7 on anxiety and fear. Western blotting and enzyme-linked immunosorbent assay were used to quantify Lcn2 and inflammatory cytokine levels in the prefrontal cortex (PFC). Additionally, the activity of PFC neurons was evaluated by immunofluorescence and in vivo electrophysiology. RESULTS: Mice subjected to SPS&S presented increased anxiety- and fear-like behaviors. Lcn2 expression in the PFC was significantly upregulated following SPS&S, leading to increased expression of the proinflammatory cytokines tumor necrosis factor-α and interleukin-6 and suppression of PFC neuronal activity. However, EA at HT7 inhibited Lcn2 release, reducing neuroinflammation and hypoexcitability in the PFC. Lcn2 overexpression mitigated the effects of EA at HT7, resulting in anxiety- and fear-like behaviors. CONCLUSION EA at HT7 can ameliorate PTSD-associated anxiety and fear, and its mechanism of action appears to involve the inhibition of Lcn2-mediated neural activity and inflammation in the PFC. Please cite this article as: Yang YD, Zhong W, Chen M, Tang QC, Li Y, Yao LL, et al. Electroacupuncture alleviates behaviors associated with posttraumatic stress disorder by modulating lipocalin-2-mediated neuroinflammation and neuronal activity in the prefrontal cortex. J Integr Med. 2025; 23(5):537-547.
Electroacupuncture ; Stress Disorders, Post-Traumatic/metabolism* ; Animals ; Lipocalin-2/metabolism* ; Prefrontal Cortex/physiopathology* ; Male ; Mice ; Neurons/physiology* ; Disease Models, Animal ; Fear ; Behavior, Animal ; Mice, Inbred C57BL ; Neuroinflammatory Diseases/metabolism* ; Anxiety/therapy* ; Acupuncture Points

PURPOSE: We carried out the study aiming to explore and analyze the risk factors, the distribution of pathogenic bacteria, and their antibiotic-resistance characteristics influencing the occurrence of surgical site infection (SSI), to provide valuable assistance for reducing the incidence of SSI after traumatic fracture surgery. METHODS: A retrospective case-control study enrolling 3978 participants from January 2015 to December 2019 receiving surgical treatment for traumatic fractures was conducted at Tangdu Hospital of Air Force Medical University. Baseline data, demographic characteristics, lifestyles, variables related to surgical treatment, and pathogen culture were harvested and analyzed. Univariate analyses and multivariate logistic regression analyses were used to reveal the independent risk factors of SSI. A bacterial distribution histogram and drug-sensitive heat map were drawn to describe the pathogenic characteristics. RESULTS: Included 3978 patients 138 of them developed SSI with an incidence rate of 3.47% postoperatively. By logistic regression analysis, we found that variables such as gender (males) (odds ratio (OR) = 2.012, 95% confidence interval (CI): 1.235 - 3.278, p = 0.005), diabetes mellitus (OR = 5.848, 95% CI: 3.513 - 9.736, p < 0.001), hypoproteinemia (OR = 3.400, 95% CI: 1.280 - 9.031, p = 0.014), underlying disease (OR = 5.398, 95% CI: 2.343 - 12.438, p < 0.001), hormonotherapy (OR = 11.718, 95% CI: 6.269 - 21.903, p < 0.001), open fracture (OR = 29.377, 95% CI: 9.944 - 86.784, p < 0.001), and intraoperative transfusion (OR = 2.664, 95% CI: 1.572 - 4.515, p < 0.001) were independent risk factors for SSI, while, aged over 59 years (OR = 0.132, 95% CI: 0.059 - 0.296, p < 0.001), prophylactic antibiotics use (OR = 0.082, 95% CI: 0.042 - 0.164, p < 0.001) and vacuum sealing drainage use (OR = 0.036, 95% CI: 0.010 - 0.129, p < 0.001) were protective factors. Pathogens results showed that 301 strains of 38 species of bacteria were harvested, among which 178 (59.1%) strains were Gram-positive bacteria, and 123 (40.9%) strains were Gram-negative bacteria. Staphylococcus aureus (108, 60.7%) and Enterobacter cloacae (38, 30.9%) accounted for the largest proportion. The susceptibility of Gram-positive bacteria to Vancomycin and Linezolid was almost 100%. The susceptibility of Gram-negative bacteria to Imipenem, Amikacin, and Meropenem exceeded 73%. CONCLUSION Orthopedic surgeons need to develop appropriate surgical plans based on the risk factors and protective factors associated with postoperative SSI to reduce its occurrence. Meanwhile, it is recommended to strengthen blood glucose control in the early stage of admission and for surgeons to be cautious and scientific when choosing antibiotic therapy in clinical practice.
Humans ; Surgical Wound Infection/epidemiology* ; Male ; Female ; Risk Factors ; Retrospective Studies ; Middle Aged ; Adult ; Case-Control Studies ; Fractures, Bone/surgery* ; Aged ; Drug Resistance, Bacterial ; Logistic Models ; Anti-Bacterial Agents/therapeutic use* ; Incidence ; Bacteria/drug effects*

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Objective To analyze the distribution characteristics of the single nucleotide polymorphism (SNP) site rs76206423 in the promoter region of the interleukin-2 receptor (IL-2R) β gene among Han males in a high radiation background area (HBRA) in Yangjiang City. Methods A total of 48 male participants from Tangkou Town, Yangxi County, Yangjiang City (HBRA group), and 51 male participants from Hengpo Town, Enping City (control group) were selected as the research subjects using the random number table method. Peripheral venous blood samples of participants from both groups were collected, and genomic DNA was extracted. The genotyping and allele frequency distribution of the rs76206423 (A/G) site in the IL-2R β promoter region was detected among the participants in both groups using the SNP detection method. The difference of allele frequencies between population in HBRA group and five area of East Asia, South Asia, Africa, Europe, and the Americas published in the Human Genome Project database from National Center for Biotechnology Information were analyzed. Results The allele frequencies of rs76206423 of population in both groups conformed to Hardy-Weinberg equilibrium (P>0.05). In the HBRA group, the AA genotype was predominant (64.6%), while the AG genotype was the most common in the control group (51.0%), with a significant difference (P<0.05). Population in both groups showed a predominance of the variant allele A (78.1% and 72.5%, respectively), with no significant difference (P>0.05). The frequency of the G allele of rs76206423 in the population in HBRA group was higher than those in South Asian, African, European, and American populations (all P<0.01), but showed no significant difference compared with East Asian populations (P>0.05). Conclusion In the Han male population from the HBRA in Yangjiang City, the rs76206423 site in the IL-2R β gene promoter region is predominantly composed of the wild-type A allele and AA genotype, indicating genetic stability and a relatively high degree of variation at this locus.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Fluorescent probes L1 to L5 containing two recognition sites based on Schiff base were prepared for detection of Al3+.The probes were constituted by introducing two salicylaldehyde derivatives through hydrazide groups on isophthalic hydrazide.Among them,a fast turn-on fluorescence probe L1 for Al3+with high fluorescence quantum yield was found.The recognition performance and mechanism of probe L1 to Al3+were studied by multiple analysis methods.The results showed that probe L1 could rapidly and highly selectively recognize Al3+by fluorescent enhancement at 446 nm and the detection limit was as low as 4.65 nmol/L,and it was found that L1 complexed with Al3+in the molar ratio of 1:1.In addition,the calculation results of density functional theory(DFT)showed that two binding sites in the probe molecule connected two different Al3+,and each Al3+connected two adjacent probe molecules.Using quinine sulfate as a reference,the fluorescence quantum yield of L1-Al3+complex was as high as 30%.Probe L1 could also be applied to the detection of Al3+in real water samples.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.