ObjectiveThis study aims to explore the potential of different orders of magnitude single-nucleotide polymorphism (SNP) locus combinations for predicting distant kinship relationships. A high-density SNP locus set was constructed, and a comprehensive assessment of its inference capability was conducted. MethodsFirstly, we selected three commercial chip panels, CGA (Chinese genotyping array, Illumina), GSA (Global screening array, Illumina), Affy (23MF_V2 high-density SNP array, Affymetrix) and merged them after quality control, forming a high-density SNP locus panel(1 180 k). Secondly, we selected 161 samples and collected their peripheral blood samples by using whole-genome sequencing technology. Within this sample population, the levels of kinship relationships fully covered the range from level 1 to level 9, and the number of kinship pairs at each level was consistently maintained at over 50 pairs. From 161 samples data of whole-genome sequencing, the 1 180 k locus set was extracted, which is referred to as the high-density SNP locus set in the following text. The kinship inference was conducted using the identity-by-descent (IBD) algorithm with the selected optimal parameters. To comprehensively evaluate the performance of the high-density SNP locus set in kinship inference, we compared it with the three commercial chip panels, the intersection of these three chip loci, and the control sets constructed by randomly reducing the number of the high-density SNP locus set. Based on the changes in the IBD lengths, as well as the dynamic trends in prediction accuracy, we conducted a scientific assessment of the kinship inference capability of the high-density SNP locus set. ResultsAfter screening, a set of 1 184 334 autosomal SNPs was obtained. During the process of screening the optimal IBD length threshold, the result revealed that 0 cM, 1 cM, and 2 cM all demonstrated good applicability. However, to avoid the issue of a large amount of redundant information caused by setting a too low IBD length threshold, this study ultimately selected 2 cM as the optimal threshold. Compared with the average results of three chip panels, the high-density SNP locus set increased the total IBD length and the average IBD length across levels 1-9; the accuracy of the confidence interval for level 8 was 70.97%, which represented a 3.50% improvement; the average confidence interval accuracy for levels 1-8 was 91.39%, representing a 1.00% increase; and the false negative rates at levels 8 and 9 were reduced by 2.42% and 6.76%, respectively. The system efficacy of the high-density SNP locus set for kinship inference of first to eighth degree relationships reached 98.91%. Through random reduction of the high-density SNP locus set results, it is found that increasing the number of SNPs with the panel, the detection efficiency of IBD length showed a significant upward trend. At the same time, the overall trend in the accuracy of kinship relationship prediction as well as the confidence interval accuracy also indicated that both metrics steadily increased with the addition of more loci. ConclusionThe results show that the high-density SNPs panel significantly enhances the efficacy of distant kinship inference, accurately covering kinship degrees, with the average confidence interval accuracy for first to eighth degree relationships stably above 90%. The study finds that increasing the number of SNPs panel can improve the ability to predict distant kinship.

Inflammatory diseases (IDs) are a general term of diseases characterized by chronic inflammation as the primary pathogenetic mechanism, which seriously affect the quality of patient′s life and cause significant social and medical burden. Current drugs for IDs include nonsteroidal anti-inflammatory drugs, corticosteroids, immunomodulators, biologics, and antioxidants, but these drugs may cause gastrointestinal side effects, induce or worsen infections, and cause non-response or intolerance. Given the outstanding performance of metal polyphenol network (MPN) in the fields of drug delivery, biomedical imaging, and catalytic therapy, its application in the diagnosis and treatment of IDs has attracted much attention and significant progress has been made. In this paper, we first provide an overview of the types of IDs and their generating mechanisms, then sort out and summarize the different forms of MPN in recent years, and finally discuss in detail the characteristics of MPN and their latest research progress in the diagnosis and treatment of IDs. This research may provide useful references for scientific research and clinical practice in the related fields.

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.

Chronic kidney disease(CKD)is a chronic disease characterized by renal structural damage and dysfunction.At present,there is still a lack of effective therapeutic drugs and prevention and treatment methods for CKD in clinical practice.More and more studies have shown that necroptosis,as a new type of programmed cell death,plays a vital role in the onset and progression of CKD.Targeting key molecules in the necroptosis pathway,such as RIPK1,RIPK3 and MLKL,the development of small molecule inhibitors has become an emerging strategy for the treatment of CKD,and has shown significant potential to pro-tect the kidneys and alleviate renal fibrosis in a variety of in vitro and in vivo models.Therefore,this article summarizes the re-search progress of the mechanism of necroptosis in recent years,and focuses on the potential role of necroptosis in the pathogene-sis of CKD and the therapeutic potential of targeting this path-way,providing a new perspective and research direction for the prevention and treatment of CKD in the future.

Depression is a heterogeneous mental disorder in which the interaction between genetic susceptibility and environ-mental factors plays a key role in its pathogenesis.Although the specific mechanisms of the disease still need to be thoroughly studied and elucidated,there is now a broad consensus that epi-genetic markers have a central influence on its mechanism of ac-tion.DNA methylation of brain-derived neurotrophic factor(BD-NF)is not only regarded as a promising epigenetic biomarker of pathology,but may also help predict the efficacy of antidepres-sants.In this paper we reviewed the gene structure of BDNF and its DNA methylation regulation mechanism,and also analyzed the changes of DNA methylation of this factor in depression pa-tients and animal models,aiming to provide new ideas and theo-retical support for clinical research.

Aim To explore the mechanism of ligustil-ide(LIG)improving demyelination by inhibiting in-flammatory response in mice with distal middle cerebral artery occlusion(dMCAO)through AIM2/caspase-1 signal pathway.Methods Thirty C57BL/6N male mice were randomly divided into three groups:sham operation group(Sham group,n=10),model group(dMCAO group,n=10)and treatment group(LIG group,n=10).The dMCAO mouse model was estab-lished by electrocoagulation in dMCAO group and LIG group.The mice were scored by Longa after waking up,and the changes of cerebral blood flow were moni-tored by laser speckle blood flow imaging system after dMCAO.One hour after modeling,LIG(30 mg·kg-1·d-1)was injected intraperitoneally in LIG group,and the same amount of normal saline was injected in sham group and dMCAO group for one week until the end of the experiment.The mice in each group were stained with TTC,and the brain injury was observed pathologically.Fatigue turning bar test and open field test were used to evaluate the motor function and anxie-ty degree of mice,and then the brain tissues of mice were taken for black gold staining to compare the chan-ges of myelin sheath in each group.Immunofluores-cence staining was used to detect the average fluores-cence intensity of MBP,IBA1 and GFAP in CC,CPU and CX regions of mouse brains.ELISAwas used to de-tect the contents of TNF-α,IL-6,IL-1 β,IL-17A and BDNF in brain tissue proteins of mice.Western blot-ting was used to detect the protein expressions of AIM2,caspase-1 and ASC-in each group.Results Compared with the dMCAO group,the infarct area was reduced,the behavior was significantly improved and the demyelination was reduced in the LIG group.The expression of MBP protein in CC,CPU and CX regions increased(P＜0.05),the expression of IBA1 in CX decreased(P＜0.01),and the expression of GFAP in-creased in CC,CPU and CX regions(P＜0.01).The results of ELISA showed that the levels ofTNF-α(P＜0.01),IL-6(P＜0.01),IL-1β(P＜0.05)and IL-17A(P＜0.01)significantly decreased,while the ex-pression of BDNF increased(P＜0.05).The protein expression levels of AIM2,caspase-1 and ASC in mouse brain decreased after treatment(P＜0.01).Conclusion LIG has a protective effect on demyelina-tion in dMCAO mice,which may be related to the inhi-bition of AIM2/caspase-1 signaling pathway and in-flammation and to the promotion of BDNF secretion.

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.

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics.Similarities and variations of components present significant analytical challenges.A two-dimensional(2D)liquid chromatography-mass spectrometry(LC-MS)method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium(CMS).A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated.For efficient and high-accuracy screening of CMS,a targeted method based on a self-constructed high resolution(HR)mass spectrum database of CMS components was established.The database was built based on the commercial MassHunter Personal Compound Database and Library(PCDL)software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening.On this basis,the unknown peaks in the CMS chromatograms were deduced and assigned.The molecular formula,group composition,and origins of a total of 99 compounds,of which the combined area percentage accounted for more than 95％of CMS components,were deduced by this 2D-LC-MS method combined with the MassHunter PCDL.This profiling method was highly efficient and could distinguish hundreds of components within 3 h,providing reliable results for quality control of this kind of complex drugs.