Objective To provide a scientific basis for vector prevention and control in port areas, vector monitoring has been conducted continuously to characterize the composition, density, and seasonal fluctuations of vectors across 21 port-areas of Shandong province from 2017 to 2023. Methods In accordance with the Regional Vector Monitoring Plan for Frontier Ports, vector surveillance of mosquitoes, flies, cockroaches, rodents, and other disease vectors was performed. Data were analyzed to describe vector community composition and identify seasonal fluctuations. Results A total of 601 rodents belonging to 1 family, 4 genera, and 4 species were captured. Three dominant rodent species inhabit port areas. In addition, 88 104 mosquitoes were captured and classified into 3 subfamilies, 4 genera, and 12 species; 38 959 flies were trapped and classified into 8 families,31 genera, and 51 species, including 9 dominant fly species in port-areas; and 54 672 captured cockroaches were classified into 2 families,4 genera, and 4 species, with Blattella germanica as the dominant species. Conclusions Significant vector community changes(P＜0.005)have been identified after the epidemic. To improve the pertinence and efficacy of port health quarantine work, continuous and strong attention should be paid to vector compositions and population densities at Shandong ports.

This study aims to investigate the antipyretic effects and mechanisms of ethanol extracts from Arisaematis Rhizoma fermented with bile from different sources on a rat model of fever induced by a dry-yeast suspension. The rat model of fever was established by subcutaneous injection of 20% dry-yeast suspension into the rat back. The levels of tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), interleukin-6(IL-6) in the serum, as well as prostaglandin E_2(PGE_2) and cyclic adenosine monophosphate(cAMP) in the hypothalamus, were determined by ELISA. Metabolomics analysis was then performed on serum and hypothalamus samples based on UPLC-Q-TOF MS to explore the potential biomarkers and metabolic pathways. The results showed that the body temperatures of rats significantly rose 4 h after modeling. After oral administration of high-dose ethanol extracts of Arisaematis Rhizoma fermented with bovine bile(NCH) and porcine bile(ZCH), the body temperatures of rats declined(P<0.05), and the NCH group showed better antipyretic effect than the ZCH group. Additionally, compared with the model group, the NCH and ZCH groups showed lowered levels of IL-1β, IL-6, TNF-α, PGE_2, and cAMP(P<0.01). The results of serum and hypothalamus metabolomics analysis indicated that both NCH and ZCH exerted antipyretic effects by regulating phenylalanine metabolism, sphingolipid metabolism, arachidonic acid metabolism, and steroid hormone biosynthesis. Collectively, both NCH and ZCH can play an obvious antipyretic role in the rat model of dry yeast-induced fever, and the underlying mechanism might be closely associated with inhibiting inflammation and regulating metabolic disorders. Moreover, NCH demonstrates better antipyretic effect.
Animals ; Rats ; Male ; Fermentation ; Rats, Sprague-Dawley ; Rhizome/metabolism* ; Drugs, Chinese Herbal/chemistry* ; Bile/chemistry* ; Antipyretics/chemistry* ; Fever/metabolism* ; Cattle ; Swine ; Tumor Necrosis Factor-alpha/metabolism* ; Ethanol/chemistry* ; Interleukin-6/blood* ; Interleukin-1beta/blood*

Based on the high-fat diet-induced hyperlipidemia rat model, this study aimed to evaluate the lipid-lowering effect of Arisaema Cum Bile and explore its mechanisms, providing experimental evidence for its clinical application. Biochemical analysis was used to detect serum levels of alanine aminotransferase(ALT), aspartate aminotransferase(AST), high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-C), triglycerides(TG), and total cholesterol(TC) to assess the lipid-lowering activity of Arisaema Cum Bile. Additionally, 16S rDNA sequencing and metabolomics techniques were employed to jointly elucidate the lipid-lowering mechanisms of Arisaema Cum Bile. The experimental results showed that high-dose Arisaema Cum Bile(PBA-H) significantly reduced serum ALT, AST, LDL-C, TG, and TC levels(P<0.01), and significantly increased HDL-C levels(P<0.01). The effect was similar to that of fenofibrate, with no significant difference. Furthermore, Arisaema Cum Bile significantly alleviated hepatocyte ballooning and mitigated fatty degeneration in liver tissues. As indicated by 16S rDNA sequencing results, PBA-H significantly enhanced both alpha and beta diversity of the gut microbiota in the model rats, notably increasing the relative abundance of Akkermansia and Subdoligranulum species(P<0.01). Liver metabolomics analysis revealed that PBA-H primarily regulated pathways involved in arachidonic acid metabolism, vitamin B_6 metabolism, and steroid biosynthesis. In summary, Arisaema Cum Bile significantly improved abnormal blood lipid levels and liver pathology induced by a high-fat diet, regulated hepatic metabolic disorders, and improved the abundance and structural composition of gut microbiota, thereby exerting its lipid-lowering effect. The findings of this study provide experimental evidence for the clinical application of Arisaema Cum Bile and the treatment of hyperlipidemia.
Animals ; Gastrointestinal Microbiome/drug effects* ; Rats ; Male ; Metabolomics ; Hyperlipidemias/microbiology* ; Drugs, Chinese Herbal/administration & dosage* ; Rats, Sprague-Dawley ; Hypolipidemic Agents/pharmacology* ; Liver/metabolism* ; Humans ; Alanine Transaminase/metabolism* ; Triglycerides/metabolism* ; Aspartate Aminotransferases/metabolism*

Objective To analyze the development trends,research status,and hotspots in the field of gut microbiota and cognitive dysfunction from 2015 to 2025,providing a more comprehensive reference for researchers in this field and exploring cutting-edge research directions.Methods Liter-ature in relevant research fields was retrieved from the WoSCC database.Bibliometric and visualiza-tion analyses were conducted using VOSviewer,CiteSpace,ScimangoGraphica,and the R package"bibliometrix".Results A total of 665 eligible English articles were retrieved from the WoSCC data-base.The analysis revealed that the number of publications has shown an increasing trend annually since 2018.China and the United States had the leading roles globally in terms of the number of pub-lications and collaborative relationships.Huazhong University of Science and Technology are the most influential research institution in this field,with NUTRIENTS(IF=4.8)being the journal with the highest number of publications,and KIM D H ranking first in outstanding contributions and influ-ence.Keyword co-occurrence analysis indicated that"neuronal apoptosis","SCFAs","synaptic dysfunction",and"dementia prevention"were the research hotspots in this field.Furthermore,trend analysis revealed that short-chain fatty acids(SCFAs),important metabolites of gut microbiota,insulin resistance,and neuroinflammation were the research frontiers in this field,highlighting insulin resistance as a mediating hub in microbiota-cognition research.Additionally,traditional Chinese medicine interventions(such as electroacupuncture)were identified as an emerging characteristic direction in this field.Conclusion Through bibliometric research,the current status and develop-ment trends of gut microbiota and cognitive dysfunction research are analyzed from multiple perspec-tives in the paper.Comprehensive insights into the cutting-edge dynamics of this research field are provided,offering valuable references for further in-depth research by more scholars in this area.

Objective To investigate the effects of peripheral blood neutrophil infiltration on the polarization regulation of cerebral resident microglia under a permanent ischemic stroke model.Methods Fifty-eight C57BL/6 mice were divided into two groups.One group was sham group,and the other group of mice was subjected to permanent middle cerebral artery occlusion surgery.Mice were euthanized 48 hours,7 days,14 days,and 30 days after surgery for tissue collection.Western blotting was used to detect expression levels of M1 microglia markers CD 16,M2 microglia marker arginase 1(Arg1),inflammatory cytokine interleukin-1 β(IL-1β),and neutrophil marker myeloperoxidase(MPO)in brain tissue.Immunofluorescence histochemical staining was used to assess neutrophil infiltration and M2 microglial distribution around the infarct area in brain sections.In vitro,purified neutrophils were co-cultured with BV2 microglial cells.After lipopolysaccharide stimulation,the phagocytosis of neutrophils by BV2 cells was observed,and the expression levels of CD16 and Arg1 proteins in BV2 cells were detected.Results Western blotting showed that the levels of CD16(P＜0.05),IL-1β(P＜0.001),and MPO(P＜0.05)in brain tissue increased significantly 48 hours and 7 days after surgery,then decreased,with MPO expression returning to normal levels 30 days after surgery.Immunofluorescence showed a significant increase of MPO-positive cells around the infarct area of the mouse cerebral cortex 48 hours after surgery(P＜0.001),followed by a decrease(P＜0.05).The number of ionized calcium binding adapter molecule 1(Iba1)and MPO double-positive cells gradually increased after surgery,and reached their peak at 14 days(P＜0.05).Iba1 and Arg1 double-positive cells also increased significantly 7 days(P＜0.05)and 14 days(P＜0.01)after surgery.In vitro,co-culture experiments showed that after BV2 phagocytosing neutrophils,CD 16(P＜0.05)significantly decreased and Arg1 significantly upregulated(P＜0.05).Conclusion In a permanent ischemic stroke model,microglia transition from M1 to M2 type after phagocytosing neutrophils,and the injured brain area changes from pro-inflammatory state to anti-inflammatory state.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To investigate the accuracy of next-generation sequencing technology(NGS)in detecting the polymorphisms of HLA-DRB1,DQB1,DQA1,DRB3,DRB4,DRB5,DPA1 and DPB1 alleles in randomly-selected unrelated healthy individuals from Shenzhen Han population,investigate the potential reason for HLA-DRB1 allele dropout in routine NGS,and establish an internal quality control system.Methods:NGS-based HLA class Ⅱ genotyping was performed on 1 012 samples using the MiSeqDxTM platform.The suspected missed alleles indicated by the quality control software and HLA-DRB1 homozygotes were confirmed by PCR-SSOP or PCR-SBT methods.Results:A total of 139 alleles were detected,including HLA-DRB1(45),DRB3(7),DRB4(5),DRB5(7),DQA1(17),DQB1(21),DPA1(10)and DPB1(27).HLA-DRB 1*09:01(17.09％),15:01(10.72％);DRB3*02:02(25.99％),03:01(10.18％);DRB4*01:03(36.46％);DRB5*01:01(15.42％);DQA1*01:02(20.01％),03:02(17.19％);DQB1*03:01(19.47％),03:03(17.98％),05:02(11.66％),06:01(10.67％);DPA1*02:02(54.45％),01:03(31.18％)and DPB1*05:01(39.13％),02:01(16.90％)alleles were the most common alleles in Shenzhen Han population(frequencies＞10％).There was no statistical difference between the gene frequencies of HLA-DRB1 and DQB1 loci in our study.The HLA Common and Well-Documented Alleles in China(CWD2.4)(x2=12.68,P＞0.05).94 cases of HLA-DRB1 homozygous samples detected by NGS were retested by PCR-SSOP or SBT method,and one case of allele dropout at HLA-DRB1 locus was found.SBT method confirmed that the allele of DRB1*04:03 was missed.The laboratory internal quality control system was established.Two cases of new alleles were detected and named by WHO Nomenclature Committee for Factors of the HLA System.Conclusion:The HLA genotyping results based on NGS showed a significantly lower ambiguity rate.The HLA class Ⅱ alleles exhibit genetic polymorphism in the Han population of unrelated healthy individuals in Shenzhen.The independent method based on NGS in clinical histocompatibility testing has limitations and requires internal quality control strategies to avoid allele-dropout events.

Objective:To explore the clinical characteristics and prognosis of patients with diffuse large B-cell lymphoma(DLBCL)of the breast.Methods:The clinical data of 28 DLBCL patients admitted to Shanxi Provincial Cancer Hospital from January 2013 to January 2023 were retrospectively analysed,including 13 cases of primary breast DLBCL(PB-DLBCL)and 15 cases of secondary breast DLBCL(SB-DLBCL),and the data of their clinical manifestations,laboratory tests,pathological examinations,treatment protocols,and follow-up were statistically analyzed.Results:There were significant differences in IPI score,LDH level and β2-microglobulin between PB-DLBCL and SB-DLBCL patients(P＜0.05).Among the 23 patients with breast DLBCL who received regular treatment,13 patients achieved complete remission(9 patients with PB-DLBCL and 4 patients with SB-DLBCL)after initial treatment.By the end of follow-up,11 patients relapsed or progressed(5 patients with PB-DLBCL and 6 patients with SB-DLBCL)and 9 patients died(3 patients with PB-DLBCL and 6 patients with SB-DLBCL).The 5-year OS rate was(75.0±15.3)％in PB-DLBCL group and(32.3±17.1)％in SB-DLBCL group.The 5-year PFS rate was(59.1±19.8)％in PB-DLBCL and 0％in SB-DLBCL group.The 5-year OS rate and PFS rate of PB-DLBCL patients were higher than those of SB-DLBCL patients(P＜0.05);the 5-year OS rate of the combined central preventive treatment group was higher than that of the chemotherapy group(P＜0.05).Conclusion:Breast DLBCL is divided into two categories:PB-DLBCL and SB-DLBCL.Compared with SB-DLBCL,PB-DLBCL has the characteristics of lower IPI score,LDH,and β2-microglobulin levels.PB-DLBCL patients have a longer survival period.In addition,the prognosis of patients receiving central preventive treatment is more optimistic.

Objective To explore the analgesic effect of different doses of dezocine combined with ropivacaine for thoracic paravertebral block(TPVB)on patients undergoing thoracoscopic radical resection of lung cancer and the influence on hemodynamics and immune function of patients.Methods Patients with lung cancer who underwent thoracoscopic radical resection were divided into low-dose group and high-dose group according to random number table method.Both groups of patients were given total intravenous anesthesia to complete the surgery.At 15 min before general anesthesia induction,the low-dose group was given TPBV with 0.1 mg·kg-1 dezocine+0.375％ropivacaine for a total of 20 mL,and the high-dose group was given TPBV with 0.15 mg·kg-1 dezocine+0.375％ropivacaine for a total of 20 mL.Comparisons were performed on both groups in terms of analgesic effect,hemodynamic parameters,immune function and occurrence of adverse drug reactions.Results There were 48 cases in low-dose group and 46 cases in high-dose group.In low-dose group,the heart rate values before TPVB,before skin incision,at 5 min after sectioning and at the end of surgery were(78.52±6.54),(70.79±7.07),(74.48±6.68)and(76.69±7.29)beat·min-1,the mean arterial pressure values were(93.16±5.72),(86.38±7.51),(92.15±6.36)and(91.14±6.13)mmHg.In high-dose group,the heart rate values at the above time points were(79.36±7.11),(71.68±6.49),(74.76±7.06)and(76.57±6.52)beat·min-1;the mean arterial pressure values were(93.89±7.18),(85.27±7.41),(90.34±6.52)and(92.43±6.34)mmHg,there were no statistical differences between the two groups(all P＞0.05).The resting state scores at 2,6 and 12 h after surgery were(1.38±0.19),(1.54±0.21)and(1.72±0.16)points,the pain scores at motion state were(1.88±0.15),(2.36±0.37)and(3.26±0.38)points in low-dose group;in high-dose group,the resting state scores were(1.32±0.17),(1.58±0.22)and(1.81±0.18)points,the pain scores at motion state were(1.81±0.13),(2.11±0.31)and(3.03±0.36)points,respectively,there were no statistical differences between the two groups(all P＞0.05).The number of analgesic pump compressions at 24 h after surgery and the number of cases with analgesic remedy were(5.12±1.26)times and 15 cases in low-dose group and were(4.74±1.03)times and 10 cases in high-dose group,with no statistical differences between the groups(all P＞0.05).The percentages of CD3+cells in low-dose group at the end of surgery and at 12 h and 24 h after surgery were(68.51±6.76)％,(54.22±5.43)％and(51.47±6.58)％,the percentages of CD4+cells were(40.29±5.02)％,(34.94±4.79)％and(30.48±5.11)％,CD4+/CD8+ratios were 1.54±0.34,1.36±0.28 and 1.16±0.23;the percentages of CD3+cells in high-dose group were(67.92±7.11)％,(56.58±6.36)％and(54.47±6.89)％,percentages of CD4+cells were(41.33±5.75)％,(35.86±5.21)％and(32.27±4.78)％,the CD4+/CD8+were 1.53±0.35,1.40±0.30 and 1.22±0.26,all with no significant difference(all P＞0.05).The incidence of postoperative adverse drug reactions in high-dose group and low-dose group were 32.61％and 14.58％,with significant difference(P＜0.05).Conclusion When TPVB regimen of dezocine combined with ropivacaine is used in thoracoscopic radical resection of lung cancer,the analgesic effect of low-dose dezocine is comparable to that of high-dose dezocine,with lower risk of adverse drug reactions.