Cardiometabolic disease is one of the leading causes of morbidity and mortality in adults. In recent years, the prevalence of cardiometabolic disease has increased year by year, becoming a major problem in the global disease burden. The occurrence and development of cardiometabolic risk are affected by many factors. Shift work as an occupational hazard has been widely concerned. Nurses are a typical population for shift work, but few studies have looked at the association between their shift work and cardiometabolic risk. This article reviewed the current situation of cardiometabolic risk and the research progress on the association between shift work and cardiometabolic risk among nurses. The results showed that cardiometabolic risk is prevalent in the nurse population. Shift work is associated with cardiometabolic risks such as metabolic syndrome, cardiovascular disease, diabetes, and dyslipidemia, and is mediated by circadian rhythm disorder, hormone secretion disorder, and stress response. However, the causal relationship between shift work and cardiometabolic risk is still unclear, and further prospective cohort studies should be conducted to improve the understanding of the impact of shift work on cardiometabolic risk in order to improve the cardiometabolic health status of nurses.

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.

ObjectiveTo observe and analyze the plasma metabolite differences among colorectal cancer patients with spleen-qi deficiency， damp-heat stasis-toxin syndrome（SRYD）， non-spleen-qi deficiency， damp-heat stasis-toxin syndrome（non-SRYD）， and normal human beings（Normal）， aiming to identify unique metabolites specific to SRYD colorectal cancer patients and their potential biomarkers. MethodsBased on the diagnostic criteria of SRYD and non-SRYD colorectal cancer， 30 patients were included， including 10 patients with SRYD colorectal cancer and 20 patients with non-SRYD colorectal cancer， while 10 individuals were recruited for the Normal group. Metabolome sequencing of plasma from the three groups was performed by ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap mass spectrometry（UPLC-Q-Exactive-Orbitrap-MS）. Multivariate statistical analysis were performed by principal component analysis（PCA） and partial least squares-discriminant analysis（PLS-DA）， and the intergroup differential metabolites were identified based on variable importance in the projection（VIP） value>1 and t-test P<0.05. And pathway enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes（KEGG） was performed to explore the metabolites and metabolic pathways specific to SRYD colorectal cancer patients. ResultsMetabolome sequencing results showed some differences in metabolic profiles between the groups. A total of 111 plasma differential metabolites were found in the SRYD group and the Normal group， of which 31 were up-regulated and 80 were down-regulated， mainly including stearoyl lysophosphatidylcholine， indole-3-acrylic acid， and dehydroepiandrosterone sulfate（P<0.05）. The non-SRYD group exhibited 97 differentially expressed metabolites compared to the Normal group， with 36 up-regulated and 61 down-regulated， mainly including stearoyl lysophosphatidylcholine， sphingosine， and palmitoyl lysophosphatidylcholine（P<0.05）. And the SRYD group exhibited 19 differentially expressed metabolites compared to the non-SRYD group， of which 5 were up-regulated and 14 were down-regulated， mainly including dihydrosphingosine， palmitic acid， and linoleoylethanolamide（P<0.05）. The significant differential metabolites were subjected to KEGG analysis to obtain significantly enriched metabolic pathways in each group， and the results showed that 11 metabolic pathways such as primary bile acid synthesis， cholesterol metabolism and bile secretion were differential signaling pathways specific to SRYD colorectal cancer. Further retrieval of the above key signaling pathways showed that bile acids were up-regulated in both bile secretion and primary bile acid synthesis pathways， and there was a trend of up-regulation of glycochenodeoxycholic acid， taurochenodeoxycholic acid， and chenodeoxycholic acid. ConclusionPrimary bile acid synthesis， cholesterol metabolism， and bile secretion-related pathways may be differential signaling pathways specific to SRYD colorectal cancer， and bile acid is a core molecule in the metabolic pathway， which can serve as potential biomarkers closely related to the development and progression of SRYD colorectal cancer.

ObjectiveTo observe and analyze the plasma metabolite differences among colorectal cancer patients with spleen-qi deficiency， damp-heat stasis-toxin syndrome（SRYD）， non-spleen-qi deficiency， damp-heat stasis-toxin syndrome（non-SRYD）， and normal human beings（Normal）， aiming to identify unique metabolites specific to SRYD colorectal cancer patients and their potential biomarkers. MethodsBased on the diagnostic criteria of SRYD and non-SRYD colorectal cancer， 30 patients were included， including 10 patients with SRYD colorectal cancer and 20 patients with non-SRYD colorectal cancer， while 10 individuals were recruited for the Normal group. Metabolome sequencing of plasma from the three groups was performed by ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap mass spectrometry（UPLC-Q-Exactive-Orbitrap-MS）. Multivariate statistical analysis were performed by principal component analysis（PCA） and partial least squares-discriminant analysis（PLS-DA）， and the intergroup differential metabolites were identified based on variable importance in the projection（VIP） value>1 and t-test P<0.05. And pathway enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes（KEGG） was performed to explore the metabolites and metabolic pathways specific to SRYD colorectal cancer patients. ResultsMetabolome sequencing results showed some differences in metabolic profiles between the groups. A total of 111 plasma differential metabolites were found in the SRYD group and the Normal group， of which 31 were up-regulated and 80 were down-regulated， mainly including stearoyl lysophosphatidylcholine， indole-3-acrylic acid， and dehydroepiandrosterone sulfate（P<0.05）. The non-SRYD group exhibited 97 differentially expressed metabolites compared to the Normal group， with 36 up-regulated and 61 down-regulated， mainly including stearoyl lysophosphatidylcholine， sphingosine， and palmitoyl lysophosphatidylcholine（P<0.05）. And the SRYD group exhibited 19 differentially expressed metabolites compared to the non-SRYD group， of which 5 were up-regulated and 14 were down-regulated， mainly including dihydrosphingosine， palmitic acid， and linoleoylethanolamide（P<0.05）. The significant differential metabolites were subjected to KEGG analysis to obtain significantly enriched metabolic pathways in each group， and the results showed that 11 metabolic pathways such as primary bile acid synthesis， cholesterol metabolism and bile secretion were differential signaling pathways specific to SRYD colorectal cancer. Further retrieval of the above key signaling pathways showed that bile acids were up-regulated in both bile secretion and primary bile acid synthesis pathways， and there was a trend of up-regulation of glycochenodeoxycholic acid， taurochenodeoxycholic acid， and chenodeoxycholic acid. ConclusionPrimary bile acid synthesis， cholesterol metabolism， and bile secretion-related pathways may be differential signaling pathways specific to SRYD colorectal cancer， and bile acid is a core molecule in the metabolic pathway， which can serve as potential biomarkers closely related to the development and progression of SRYD colorectal cancer.

The prevalence rate of metabolic associated fatty liver disease （MAFLD） is steadily increasing worldwide， and MAFLD is now considered a significant risk factor for a wide range of metabolic comorbidities. However， current clinical management strategies often address MAFLD from a single-disease perspective， lacking a comprehensive understanding of the central role and systemic impact of MAFLD in the prevention and control of metabolic comorbidities. This article reviews the current evidence supporting MASLD as both a trigger and a key node in systemic metabolic dysfunction and elaborates on how hepatic insulin resistance， lipotoxic injury， inflammatory responses， and dysregulation of hepatokines mediate organ-specific metabolic disorders including cardiovascular disease， chronic kidney disease， and diabetes. With reference to the latest national and international guidelines， this article proposes an integrated multidisciplinary management strategy， including liver-glucose joint intervention and a cross-organ “cardio-renal-hepatic” strategy， and it also advocates for a paradigm shift from conventional liver-focused management toward liver-centered systemic metabolic control， in order to effectively delay the progression of MAFLD and its related multisystem complications.

OBJECTIVES: To explore the underlying pharmacological mechanisms and its potential effects of Chinese medicine herbal formula Sini Powder (SNP) on hepatocellular carcinoma (HCC). METHODS: The active components of SNP and their in vivo distribution were identified using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Construction of component-target-disease networks, protein-protein interaction network, Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and molecular docking were employed to analyze the active components and anti-HCC mechanisms of SNP. Cell viability assay and wound healing assay were utilized to confirm the effect of SNP-containing serum (2.5%, 5.0%, 10%, 20%, and 40%), isoprenaline or propranolol (both 10, 100, and 1,000 µ mol/L) on proliferation and migration of HepG 2 or Huh7 cells. Meanwhile, the effect of isoprenaline or propranolol on the β 2 adrenergic receptor (ADRB2) mRNA expression on HepG2 cells were measured by real-time quantitative reverse transcription (RT-qPCR). Mice with subcutaneous tumors were either subjected to chronic restraint stress (CRS) followed by SNP administration (364 mg/mL) or directly treated with SNP (364 mg/mL). These two parallel experiments were performed to validate the effects of SNP on stress responses. Stress-related proteins and hormones were quantified using RT-qPCR, enzyme-linked immunosorbent assay, and immunohistochemistry. Metagenomic sequencing was performed to confirm the influence of SNP on the gut microbiota in the tumor-bearing CRS mice. RESULTS: The distribution of the 12 active components of SNP was confirmed in various tissues and feces. Network pharmacology analysis confirmed the anti-HCC effects of the 5 active components. The potential anti-HCC mechanisms of SNP may involve the epidermal growth factor receptor (EGFR), proto-oncogene tyrosine-protein kinase Src (SRC) and signal transducer and activator of transcription 3 (STAT3) pathways. SNP-containing serum inhibited the proliferation of HepG2 and Huh7 cells at concentrations of 2.5% and 5.0%, respectively, after 24 h of treatment. Furthermore, SNP suppressed tumor progression in tumor-bearing mice exposed to CRS. SNP treatment also downregulated the expressions of stress-related proteins and pro-inflammatory cytokines, primarily by modulating the gut microbiota. Specifically, the abundance of Alistipes and Prevotella, which belong to the phylum Bacteroidetes, increased in the SNP-treated group, whereas Lachnospira, in the phylum Firmicutes, decreased. CONCLUSION SNP can combat HCC by alleviating stress responses through the regulation of gut microbiota.
Animals ; Gastrointestinal Microbiome/drug effects* ; Liver Neoplasms/microbiology* ; Carcinoma, Hepatocellular/microbiology* ; Humans ; Drugs, Chinese Herbal/therapeutic use* ; Powders ; Cell Proliferation/drug effects* ; Mice ; Molecular Docking Simulation ; Cell Line, Tumor ; Hep G2 Cells ; Receptors, Adrenergic, beta-2/genetics* ; Stress, Physiological/drug effects* ; Cell Movement/drug effects* ; Male ; Protein Interaction Maps/drug effects* ; Cell Survival/drug effects* ; Proto-Oncogene Mas