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.

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

AIM To explore the effects of Rosa roxburghii Radix on ulcerative colitis(UC)in rats based on pyroptosis and neutrophil extracellular traps(NETs).METHODS Rats were randomly divided into the normal group and the model group.The successfully established UC rat models by trinitrobenzene sulfonic acid(TNBS)/ethanol enema were then randomly divided into the model group,the sulfasalazine group(0.3 g/kg)and the low,medium and high dose R.roxburghii Radix groups(2,4,8 g/kg),followed by dosing of corresponding drugs by gavage.21 days later,the rats had their disease activity index(DAI)score calculated;their pathological changes of colon tissue observed by HE staining;their levels of serum interleukin(IL)-18,IL-1β and myeloperoxidase(MPO)detected by ELISA;and their protein expressions of NE,MPO,NLRP3,caspase-1 and GSDMD in colon tissue detected by Western blot and immunohistochemistry.RESULTS Compared with the normal group,the model group displayed increased DAI score(P＜0.01),increased serum levels of IL-1β,IL-18 and MPO(P＜0.01),and increased protein expressions of NE,MPO,caspase-1,NLRP3 and GSDMD in colon tissue(P＜0.01).Compared with the model group,the groups intervened with sulfasalazine,or medium,or high dose R.roxburghii Radix demonstrated with decreased DAI scores(P＜0.05,P＜0.01),decreased serum levels of IL-1β,IL-18 and MPO(P＜0.01),and decreased protein expressions of NE,MPO,caspase-1,NLRP3 and GSDMD in colon tissue(P＜0.05,P＜0.01).CONCLUSION R.roxburghii Radix may alleviate the inflammatory reaction in a rat model of UC and improve its pathological injury of colon via regulating pyroptosis and NETs.

The 2-(2-phenylethyl)chromones were separated from agarwood of Aquilaria agallocha Roxb. and their anti-KRAS mutant non-small cell lung cancer (NSCLC) activities were evaluated. 2-(2-Phenyethyl)chromones in agarwood were separated and purified by silica gel, RP-18 reverse phase silica gel, MCI gel CH20P, Diol, and semi preparative HPLC chromatography techniques, while the structures of the compounds were identified by extensive spectroscopic analysis, such as 1D and 2D NMR and ESI-MS. The cell counting kit 8 (CCK-8) assay was used to screen the anti-tumor activity of the isolated monomeric compounds on three KRAS-mutant NSCLC cells. The cell proliferation, cloning formation, adhesion ability, and cell cycle arrest activity of compound 8 were analyzed. Molecular docking and Western blot experiments were used to study the mechanism of compound 8. The in vivo anti-tumor activity of the compound 8 was evaluated by zebrafish cell derived xenograft (CDX) model. Nineteen known 2-(2-phenylethyl)chromones were isolated from the ethyl acetate extract of agarwood. On A549 (KRAS G12S) cells, compounds 8, 10, and 19 showed good inhibitory activity, on H23 (KRAS G12C) cells, compounds 7, 8, and 19 showed good inhibitory activity, and on H358 (KRAS G12C) cells, compounds 8, 10, and 16 showed good inhibitory activity. Compound 8 had the best inhibitory activity in all three cell lines. It effectively inhibited cell proliferation, clone formation, adhesion ability, and arrested the H23 cell cycle at G2/M phase. Compound 8 could also inhibit the expression of c-Met and its downstream signaling pathways, effectively inhibiting tumor growth in zebrafish CDX model. In conclusion, among the nineteen known 2-(2-phenylethyl)chromones, compound 8 had the best activity and significantly inhibited the proliferation of KRAS-mutant NSCLC cells by arresting the cells in the G2/M phase.

ObjectiveGastric cancer (GC) seriously affects human health and life, and research has shown that it is closely related to the serine/glycine metabolism. The proliferation ability of tumor cells is greatly influenced by the metabolism of serine and glycine. The aim of this study was to investigate the molecular mechanism of serine/glycine metabolism can affect the proliferation of gastric cancer cells. MethodsIn this work, a stable metabolic dynamic model of gastric cancer cells was established via a large-scale metabolic network dynamic modeling method in terms of a potential landscape description of stochastic and non-gradient systems. Based on the regulation of the model, a quantitative analysis was conducted to investigate the dynamic mechanism of serine/glycine metabolism affecting the proliferation of gastric cancer cells. We introduced random noise to the kinetic equations of the general metabolic network, and applied stochastic kinetic decomposition to obtain the Lyapunov function of the metabolic network parameter space. A stable metabolic network was achieved by further reducing the change in the Lyapunov function tied to the stochastic fluctuations. ResultsDespite the unavailability of a large number of dynamic parameters, we were able to successfully construct a dynamic model for the metabolic network in gastric cancer cells. When extracellular serine is available, the model preferentially consumes serine. In addition, when the conversion rate of glycine to serine increases, the model significantly upregulates the steady-state fluxes of S-adenosylmethionine (SAM) and S-adenosyl homocysteine (SAH). ConclusionIn this paper, we provide evidence supporting the preferential uptake of serine by gastric cancer cells and the important role of serine/glycine conversion rate in SAM generation, which may affect the proliferation ability of gastric cancer cells by regulating the cellular methylation process. This provides a new idea and direction for targeted cancer therapy based on serine/glycine metabolism.

Non-syndromic oral cleft (NSOC), a common birth defect, remains to be a critical public health problem in China. In the context of adjustment of childbearing policy for two times in China and the increase of pregnancy at older childbearing age, NSOC risk prediction will provide evidence for high-risk population identification and prenatal counseling. Genome-wide association study and second generation sequencing have identified multiple loci associated with NSOC, facilitating the development of genetic risk prediction of NSOC. Despite the marked progress, risk prediction models of NSOC still faces multiple challenges. This paper summarizes the recent progress in research of NSOC risk prediction models based on the results of extensive literature retrieval to provide some insights for the model development regarding research design, variable selection, model-build strategy and evaluation methods.
Humans ; Cleft Palate/genetics* ; Cleft Lip/genetics* ; Genome-Wide Association Study ; Genetic Predisposition to Disease ; Risk Factors ; Polymorphism, Single Nucleotide