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.

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.

The circadian clock plays a critical role in regulating various physiological processes, including gene expression, metabolic regulation, immune response, and the sleep-wake cycle in living organisms. Post-translational modifications (PTMs) are crucial regulatory mechanisms to maintain the precise oscillation of the circadian clock. By modulating the stability, activity, cell localization and protein-protein interactions of core clock proteins, PTMs enable these proteins to respond dynamically to environmental and intracellular changes, thereby sustaining the periodic oscillations of the circadian clock. Different types of PTMs exert their effects through distincting molecular mechanisms, collectively ensuring the proper function of the circadian system. This review systematically summarized several major types of PTMs, including phosphorylation, acetylation, ubiquitination, SUMOylation and oxidative modification, and overviewed their roles in regulating the core clock proteins and the associated pathways, with the goals of providing a theoretical foundation for the deeper understanding of clock mechanisms and the treatment of diseases associated with circadian disruption.
Protein Processing, Post-Translational/physiology* ; Circadian Rhythm/physiology* ; Humans ; Animals ; CLOCK Proteins/physiology* ; Circadian Clocks/physiology* ; Phosphorylation ; Acetylation ; Ubiquitination ; Sumoylation

This paper aimed to investigate the therapeutic effect and mechanism of action of the Yiqi Fumai Formula(YQFM), a kind of traditional Chinese medicine(TCM), on mice with experimental heart failure based on the "heart-gut axis" theory. Based on the network pharmacology integrated with the group collaboration algorithm, the active ingredients were screened, a "component-target-disease" network was constructed, and the potential pathways regulated by the formula were predicted and analyzed. Next, the model of experimental heart failure was established by intraperitoneal injection of adriamycin at a single high dose(15 mg·kg~(-1)) in BALB/c mice. After intraperitoneal injection of YQFM(lyophilized) at 7.90, 15.80, and 31.55 mg·d~(-1) for 7 d, the protective effects of the formula on cardiac function were evaluated using indicators such as ultrasonic electrocardiography and myocardial injury markers. Combined with inflammatory factors in the cardiac and colorectal tissue, as well as targeted assays, the relevant indicators of potential pathways were verified. Meanwhile, 16S rDNA sequencing was performed on mouse fecal samples using the Illumina platform to detect changes in gut flora and analyze differential metabolic pathways. The results show that the administration of injectable YQFM(lyophilized) for 7 d significantly increased the left ventricular end-systolic internal diameter, fractional shortening, and ejection fraction of cardiac tissue of mice with experimental heart failure(P<0.05). Moreover, markers of myocardial injury were significantly decreased(P<0.05), indicating improved cardiac function, along with significantly suppressed inflammatory responses in cardiac and intestinal tissue(P<0.05). Additionally, the species of causative organisms was decreased, and the homeostasis of gut flora was improved, involving a modulatory effect on PI3K-Akt signaling pathway-related inflammation in cardiac and colorectal tissue. In conclusion, YQFM can affect the "heart-gut axis" immunity through the homeostasis of the gut flora, thereby exerting a therapeutic effect on heart failure. This finding provides a reference for the combination of TCM and western medicine to prevent and treat heart failure based on the "heart-gut axis" theory.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Heart Failure/microbiology* ; Mice ; Mice, Inbred BALB C ; Male ; Disease Models, Animal ; Gastrointestinal Microbiome/drug effects* ; Heart/physiopathology* ; Humans ; Signal Transduction/drug effects*

By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

This study primarily aimed to investigate the prevalence of human papillomavirus (HPV) and other common pathogens of sexually transmitted infections (STIs) in spermatozoa of infertile men and their effects on semen parameters. These pathogens included Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae, Pseudomonas aeruginosa , and Staphylococcus aureus . A total of 1951 men of infertile couples were recruited between 23 March 2023, and 17 May 2023, at the Department of Reproductive Medicine of The First People's Hospital of Yunnan Province (Kunming, China). Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping. Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs. The overall prevalence of HPV infection was 12.4%. The top five prevalent HPV subtypes were types 56, 52, 43, 16, and 53 among those tested positive for HPV. Other common infections with high prevalence rates were Ureaplasma urealyticum (28.3%), Ureaplasma parvum (20.4%), and Enterococcus faecalis (9.5%). The prevalence rates of HPV coinfection with Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae , and Staphylococcus aureus were 24.8%, 25.4%, 10.6%, 6.4%, 2.4%, 7.9%, 5.9%, 0.9%, and 1.3%, respectively. The semen volume and total sperm count were greatly decreased by HPV infection alone. Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability. Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters, emphasizing the necessity of semen screening for STIs.
Humans ; Male ; Infertility, Male/epidemiology* ; Coinfection/microbiology* ; Papillomavirus Infections/virology* ; Adult ; Sexually Transmitted Diseases/complications* ; China/epidemiology* ; Staphylococcus aureus/isolation & purification* ; Chlamydia trachomatis/isolation & purification* ; Prevalence ; Mycoplasma genitalium/isolation & purification* ; Ureaplasma urealyticum/isolation & purification* ; Neisseria gonorrhoeae/isolation & purification* ; Enterococcus faecalis/isolation & purification* ; Streptococcus agalactiae/isolation & purification* ; Herpesvirus 2, Human/genetics* ; Pseudomonas aeruginosa/isolation & purification* ; Semen/virology* ; Sperm Motility ; Spermatozoa/microbiology* ; Human Papillomavirus Viruses

Objective To investigate the causal relationship between cathepsin(CTS)and thyroid cancer by using Mendelian randomization(MR).Methods Aggregate data for CTS GWAS was obtained from the IEU Open Genome-wide Association Study(GWAS)database(https://gwas.mrcieu.ac.uk/),and thyroid cancer GWAS data was obtained from the EBI database(https://www.ebi.ac.uk/).Five different MR analysis methods were utilized,with the inverse variance-weighted method(IVW)as the main approach,complemented by the weighted median method,MR-Egger regression,simple mode method and weighted majority method.These methods were employed to analyze the relationship between 9 CTS genes and thyroid cancer through 9 double-sample analyses.MR-Egger intercept,MR-PRESSO for gene pleiotropy detection,Cochran Q test,and leave-one-out method were applied to assess pleiotropy and sensitivity,followed by reverse MR analysis.Results MR analysis showed that elevated level of CTS B was positively correlated with the risk of thyroid cancer(IVW OR=1.60,95%CI 1.12-2.30,P=0.01),while elevated CTS O level was negatively correlated with the risk of thyroid cancer(IVW OR=0.65,95%CI 0.45-0.95,P=0.02).Reverse MR analysis revealed no significant causal relationship between thyroid cancer and CTS B and CTS O(P>0.05).Conclusion CTS B may promote the development of thyroid cancer,whereas CTS O may inhibit its progression.

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.