Triple-negative breast cancer (TNBC) represents a distinctive subtype, characterized by the absence of estrogen receptors, progesterone receptors, and human epidermal growth factor receptor 2 (HER2). Due to its high inter-tumor and intra-tumor heterogeneity, TNBC poses significant chanllenges for personalized diagnosis and treatment. The advant of clustered regular interspaced short palindromic repeats (CRISPR) technology has profoundly enhanced our understanding of the structure and function of the TNBC genome, providing a powerful tool for investigating the occurrence and development of diseases. This review focuses on the application of CRISPR/Cas technology in the personalized diagnosis and treatment of TNBC. We begin by discussing the unique attributes of TNBC and the limitations of current diagnostic and treatment approaches: conventional diagnostic methods provide limited insights into TNBC, while traditional chemotherapy drugs are often associated with low efficacy and severe side effects. The CRISPR/Cas system, which activates Cas enzymes through complementary guide RNAs (gRNAs) to selectively degrade specific nucleic acids, has emerged as a robust tool for TNBC research. This technology enables precise gene editing, allowing for a deeper understanding of TNBC heterogeneity by marking and tracking diverse cell clones. Additionally, CRISPR facilitates high-throughput screening to promptly identify genes involved in TNBC growth, metastasis, and drug resistance, thus revealing new therapeutic targets and strategies. In TNBC diagnostics, CRISPR/Cas was applied to develop molecular diagnostic systems based on Cas9, Cas12, and Cas13, each employing distinct detection principles. These systems can sensitively and specifically detect a variety of TNBC biomarkers, including cell-specific DNA/RNA and circulating tumor DNA (ctDNA). In the realm of precision therapy, CRISPR/Cas has been utilized to identify key genes implicated in TNBC progression and treatment resistance. CRISPR-based screening has uncovered potential therapeutic targets, while its gene-editing capabilities have facilitated the development of combination therapies with traditional chemotherapy drugs, enhancing their efficacy. Despite its promise, the clinical translation of CRISPR/Cas technology remains in its early stages. Several clinical trials are underway to assess its safety and efficacy in the treatment of various genetic diseases and cancers. Challenges such as off-target effects, editing efficiency, and delivery methods remain to be addressed. The integration of CRISPR/Cas with other technologies, such as 3D cell culture systems, human induced pluripotent stem cells (hiPSCs), and artificial intelligence (AI), is expected to further advance precision medicine for TNBC. These technological convergences can offer deeper insights into disease mechanisms and facilitate the development of personalized treatment strategies. In conclusion, the CRISPR/Cas system holds immense potential in the precise diagnosis and treatment of TNBC. As the technology progresses and becomes more costs-effective, its clinical relevance will grow, and the translation of CRISPR/Cas system data into clinical applications will pave the way for optimal diagnosis and treatment strategies for TNBC patients. However, technical hurdles and ethical considerations require ongoing research and regulation to ensure safety and efficacy.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

ObjectiveTo compare the hepatic bile acid profile between a mouse model of metabolic-associated steatohepatitis （MASH） induced by a high-fat， high-sugar， and high-cholesterol diet combined with intraperitoneal injection of 10% carbon tetrachloride （CCl₄） and MASH cases in clinical practice， and to investigate the feasibility of this model in studying drug interventions on bile acid profile in MASH. MethodsA total of 30 male C57BL/6J mice were randomly divided into control group and model group， with 15 mice in each group. The mice in the control group were given normal diet and drinking water and weekly injections of olive oil， and those in the model group were given a high-fat， high-sugar， and high-cholesterol diet， high-sugar drinking water， and weekly injections of CCl₄+olive oil. At the end of weeks 8， 12， and 16， 5 mice were selected from each group to collect samples. Behavioral assessments were performed， and body weight and liver wet weight were measured； liver pathology and lipid deposition were evaluated by HE staining， SAF scoring， oil Red O staining， the semi-quantitative analysis of stained area， the serum levels of alanine aminotransferase （ALT） and aspartate aminotransferase （AST）， and liver triglyceride （TG） content； Sirius Red staining was performed for liver tissue to assess liver fibrosis； ultra-performance liquid chromatography-tandem mass spectrometry and targeted metabolomics were used to measure the hepatic bile acid profile， including cholic acid （CA）， glycocholic acid （GCA）， chenodeoxycholic acid （CDCA）， glycochenodeoxycholic acid （GCDCA）， ursodeoxycholic acid （UDCA）， tauroursodeoxycholic acid （TUDCA）， hyodeoxycholic acid （HDCA）， and glycodeoxycholic acid （GDCA）. The independent-samples t test was used for comparison of normally distributed continuous data between two groups， and the Wilcoxon rank-sum test was used for comparison of non-normally distributed continuous data between two groups. ResultsCompared with the control group at the same time point， the model group had disheveled and dull fur， reduced activity， and relatively slow reactions at weeks 8， 12， and 16， as well as significant increases in liver wet weight （P<0.05）， the serum level of ALT （P<0.05）， the content of TG in the liver （P<0.05）， and SAF score （P<0.05）. As for the differentially expressed bile acids in liver tissue， compared with the control group at week 8， the model group had significantly higher levels of CA and CDCA and significantly lower levels of UDCA， TUDCA， HDCA， and GDCA （all P<0.05）； compared with the control group at week 12， the model group had significantly higher levels of CA， GCA， CDCA， and GCDCA and significantly lower levels of UDCA and HDCA （all P<0.05）； compared with the control group at week 16， the model group had significantly higher levels of CA， GCA， CDCA， GCDCA， and TUDCA and significantly lower levels of UDCA， HDCA， and GDCA （all P<0.05）. As for the differentially expressed bile acids in the bile acid pool of liver tissue， compared with the control group at week 8， the model group had significantly higher levels of CA and CDCA and significantly lower levels of UDCA， TUDCA， GDCA， and HDCA （all P<0.05）； compared with the control group at weeks 12 and 16， the model group had significantly higher levels of GCA and GCDCA and significantly lower levels of UDCA， GDCA， and HDCA （all P<0.05）. ConclusionThere are significant changes in the hepatic bile acid profile in a mouse model of MASH induced by a high-fat， high-sugar， and high-cholesterol diet combined with CCl₄， which are similar to the changes in bile acids in MASH cases in clinical practice， suggesting that this model can be used to explore the interventional effect of drugs on the bile acid profile in MASH.

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.

The pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a serious impact on global public health and the economy. SARS-CoV-2 infiltrates host cells via its surface spike protein, which binds to angiotensin-converting enzyme 2 on the host cell membrane. As a result, small molecules targeting spike protein have emerged as a hotspot in anti-SARS-CoV-2 drug research. Activity screening is an important step in seeking small molecule drugs. Therefore, this article aims to review the biological activity evaluation methods of small molecule inhibitors targeting SARS-CoV-2 spike protein, with the goal of laying the foundation for the discovery of new anti-SARS-CoV-2 drugs.

To investigate the differences in methylation levels of cuproptosis related genes in cervical cancer and their effects on clinical prognosis.Methods:The methylation data of 310 cervical tissue specimens were acquired from public databases. The UALCAN database was used to analyze the methylation level differences of 12 cuproptosis-related genes and study their level in different stages or grades of cervical cancer. Genes with statistically significant differences were selected for prognosis analysis using the EWAS datahub. Finally, gene-enrichment analysis, pathway analysis, immune infiltration analysis, the mutation rate and tumor mutation burden (TMB) of the genes in cervical cancer were analyzed using the cBioportal database. Two independent samples rank-sum test was used for differences in methylation levels and immune cell infiltration; comparative analyses of overall survival were performed using KM survival curves and Log-rank two-sided tests. TMB analyses were performed using the Wilcoxon Test for statistical analyses; Pearson correlation analysis was used for assessment in GSEA and pathway analyses.Results:The methylationβvalue of Cyclin Dependent Kinase Inhibitor 2A (CDKN2A gene) in the cervical cancer tissues of patients was 0.075 which was significantly higher than the methylationβvalue of 0.049 in normal human tissues ( P=0.008). Dihydrolipoamide S-Acetyltransferase (DLAT gene) methylation with a β value of 0.102 was significantly higher than normal human tissue methylation with a β value of 0.08 ( P=0.002), and the methylation level β value of Lipoyltransferase 1 (LIPT1 gene) in cervical cancer tissues was 0.06,which was significantly lower than normal human tissue methylation value of 0.092 ( P=0.009). Patients with CDKN2A gene methylation levels≥0.199 had an overall survival of 14.75 years, which was lower than that of patients with methylation levels<0.199 (17.56 years) ( P=0.034).The results of gene enrichment analysis indicated that it mainly involves biological processes such as the response to type I interferon and DNA replication. The expression of CDKN2A gene is positively correlated with the number of neutrophils and dendritic cells in the tumor microenvironment( P<0.05), and negatively correlated with the number ofmacrophages( P<0.05). TMB was higher in the group of variants of the CDKN2A gene than in the group of non-variants ( P=0.019). Conclusion:CDKN2A methylation is a potential biomarker for predicting the prognosis of cervical cancer.