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.

BACKGROUND: Effective interventions during the coronavirus disease 2019 (COVID-19) pandemic require an understanding of patients' knowledge and perceptions that influence their behaviour. Our study assessed knowledge of COVID-19 among kidney transplant recipients and donors, hitherto unevaluated. METHODS: We conducted a cross-sectional survey among 325 kidney transplant recipients and 172 donors between 1 May 2020 and 30 June 2020. The survey questionnaire assessed knowledge levels of COVID-19, sociodemographic data, health status, psychosocial impact of COVID-19 and precautionary behaviours during the pandemic. RESULTS: The mean COVID-19 knowledge score of the study population was 7.5 (standard deviation: 2.2) out of 10. The mean score was significantly higher among kidney recipients compared to kidney donors (7.9 [1.9] vs. 6.7 [2.6]; P <0.001). Younger age (21-49 vs. ≥50 years) and higher education (diploma and higher vs. secondary and lower) were associated with significantly higher knowledge scores in donors, but not among recipients ( P -interactions ≤0.01). In both kidney recipients and donors, financial concerns and/or social isolation were associated with lower knowledge levels. CONCLUSIONS Concerted efforts are needed to improve COVID-19 knowledge in kidney transplant recipients and donors, particularly older donors, donors with lower education and patients with financial concerns or feelings of social isolation. Intensive patient education may mitigate the impact of education levels on COVID-19 knowledge levels.
Humans ; COVID-19/epidemiology* ; Kidney Transplantation ; Middle Aged ; Singapore/epidemiology* ; Male ; Female ; Adult ; Cross-Sectional Studies ; Health Knowledge, Attitudes, Practice ; Transplant Recipients/psychology* ; Surveys and Questionnaires ; Tissue Donors/psychology* ; SARS-CoV-2 ; Young Adult ; Aged ; Pandemics

Objective:To construct a nomogram prediction model for the malignant risk of breast lesions based on quantitative multimodal ultrasound features and clinical indicators，and to explore its clinical application value.Methods:A total of 430 patients with breast diseases（473 lesions）confirmed by pathological examination at Kunshan Traditional Chinese Medicine Hospital from August 2018 to December 2023 were retrospectively analyzed in the study. All the patients underwent routine handheld ultrasound（HHUS），automated breast volume scanning（ABVS）and ultrasound elastography（UE）examinations before biopsy or surgery. Four hundred and seventy-three breast lesions were randomly divided into training set（ n=331）and validation set（ n=142）at a ratio of 7∶3. The ABVS ultrasound features of 331 lesions in the training set were analyzed to identify the risk features of malignant breast lesions. Based on the weight of the regression coefficients β，the ABVS risk features were assigned quantitative scores for each lesion. Using pathology results as the gold standard，ROC curves were plotted to compare the diagnostic efficacy of ABVS quantitative scoring and HHUS in the training set. The variable with higher efficacy was selected for inclusion in the multivariable logistic regression analysis. Based on the identified independent predictive factors，a nomogram was constructed to quantify the malignancy risk of breast lesions. The nomogram was evaluated and validated using the area under the ROC curve（AUC），calibration curve and clinical decision curve analysis（DCA）. Results:The AUC for ABVS quantitative scoring and HHUS in distinguishing benign and malignant breast lesions were 0.941 and 0.903，respectively，with a statistically significant difference（ Z=2.081， P=0.037）. Multivariate Logistic regression analysis showed that age，ABVS quantitative score and elasticity score were independent predictors for the identification of benign and malignant breast lesions（all P<0.05）. A nomogram was constructed based on the aforementioned independent predictive factors. The AUC for the nomogram were 0.968 in the training set and 0.943 in the validation set，indicating good discrimination. The calibration curve indicated that the predicted probabilities from the nomogram were in good agreement with the actual outcomes. DCA indicated strong clinical applicability of the nomogram. Conclusions:The nomogram based on ABVS quantitative scores，elasticity scores，and age demonstrates high diagnostic value，providing a novel method for preoperative assessment of the malignancy risk of breast lesions.

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 transcriptome sequencing based on Illumina Novaseq 6000 Platform was performed with the untreated seed embryo(DS), stratified seed embryo(SS), and germinated seed embryo(GS) of Zanthoxylum nitidum, aiming to explore the molecular mechanism regulating the seed dormancy and germination of Z. nitidum and uncover key differentially expressed genes(DEGs). A total of 61.41 Gb clean data was obtained, and 86 386 unigenes with an average length of 773.49 bp were assembled. A total of 29 290 DEGs were screened from three comparison groups(SS vs DS, GS vs SS, and GS vs DS), and these genes were annotated on 134 Kyoto Encyclopedia of Genes and Genomes(KEGG) pathways. KEGG enrichment analysis revealed that the plant hormone signal transduction pathway is the richest pathway, containing 226 DEGs. Among all DEGs, 894 transcription factors were identified, which were distributed across 34 transcription factor families. These transcription factors were also mainly concentrated in plant hormone signal transduction and mitogen-activated protein kinase(MAPK) signaling pathways. Further real-time quantitative polymerase chain reaction(RT-qPCR) validation of 12 DEGs showed that the transcriptome data is reliable. During the process of seed dormancy release and germination, a large number of DEGs involved in polysaccharide degradation, protein synthesis, lipid metabolism, and hormone signal transduction were expressed. These genes were involved in multiple metabolic pathways, forming a complex regulatory network for dormancy and germination. This study lays a solid foundation for analyzing the molecular mechanisms of seed dormancy and germination of Z. nitidum.
Zanthoxylum/metabolism* ; Plant Dormancy/genetics* ; Seeds/metabolism* ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism* ; Transcriptome ; Gene Expression Profiling ; Germination ; Transcription Factors/metabolism* ; Plant Growth Regulators/genetics* ; Signal Transduction

OBJECTIVES: To investigate the clinical characteristics and prognosis of chronic disseminated candidiasis (CDC) in children with acute leukemia (AL) following chemotherapy. METHODS: A retrospective analysis was conducted on children diagnosed with CDC (including confirmed, clinically diagnosed, and suspected cases) after AL chemotherapy from January 2015 to December 2023 at Fujian Medical University Union Hospital, Zhangzhou Municipal Hospital, and Quanzhou First Hospital Affiliated to Fujian Medical University. Clinical characteristics and prognosis were analyzed. RESULTS: The incidence of CDC in children with AL following chemotherapy was 1.92% (32/1 668). Among the children with acute lymphoblastic leukemia, the incidence of CDC in the high-risk group was significantly higher than in the low-risk group (P=0.002). All patients presented with fever unresponsive to antibiotics during the neutropenic period, with 81% (26/32) involving the liver. C-reactive protein (CRP) levels were significantly elevated (≥50 mg/L) in 97% (31/32) of the patients. The efficacy of combined therapy with liposomal amphotericin B and caspofungin or posaconazole for CDC was 66% (19/29), higher than with caspofungin (9%, 2/22) or liposomal amphotericin B (18%, 2/11) monotherapy. The overall cure rate was 72% (23/32). The proportion of patients with CRP ≥50 mg/L and/or a positive β-D-glucan test for more than 2 weeks and breakthrough infections during caspofungin treatment was significantly higher in the treatment failure group compared to the successful treatment group (P<0.05). CONCLUSIONS CDC in children with AL after chemotherapy may be associated with prolonged neutropenia due to intensive chemotherapy. Combination antifungal regimens based on liposomal amphotericin B have a higher cure rate, while persistently high CRP levels and positive β-D-glucan tests may indicate poor prognosis.
Adolescent ; Child ; Child, Preschool ; Female ; Humans ; Infant ; Male ; Antifungal Agents/therapeutic use* ; Candidiasis/diagnosis* ; Chronic Disease ; Leukemia/complications* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma/complications* ; Prognosis ; Retrospective Studies

OBJECTIVE: To investigate the characteristics of gut microbiota changes in patients with acute myeloid leukemia (AML) undergoing induction chemotherapy and to explore the relationship between infectious complications and gut microbiota. METHODS: Fecal samples were collected from 37 newly diagnosed AML patients at four time points: before induction chemotherapy, during chemotherapy, during the neutropenic phase, and during the recovery phase. Metagenomic sequencing was used to analyze the dynamic changes in gut microbiota. Correlation analyses were conducted to assess the relationship between changes in gut microbiota and the occurrence of infectious complications. RESULTS: During chemotherapy, the gut microbiota α-diversity (Shannon index) of AML patients exhibited significant fluctuations. Specifically, the diversity decreased significantly during induction chemotherapy, further declined during the neutropenic phase (P < 0.05, compared to baseline), and gradually recovered during the recovery phase, though not fully returning to baseline levels.The abundances of beneficial bacteria, such as Firmicutes and Bacteroidetes, gradually decreased during chemotherapy, whereas the abundances of opportunistic pathogens, including Enterococcus, Klebsiella, and Escherichia coli, progressively increased.Analysis of the dynamic changes in gut microbiota of seven patients with bloodstream infections revealed that the bloodstream infection pathogens could be detected in the gut microbiota of the corresponding patients, with their abundance gradually increasing during the course of infection. This finding suggests that bloodstream infections may be associated with opportunistic pathogens originating from the gut microbiota.Compared to non-infected patients, the baseline samples of infected patients showed a significantly lower relative abundance of Bacteroidetes (P < 0.05). Regression analysis indicated that Bacteroidetes abundance is an independent predictive factor for infectious complications (P < 0.05, OR =13.143). CONCLUSION During induction chemotherapy in AML patients, gut microbiota α-diversity fluctuates significantly, and the abundance of opportunistic pathogens increase, which may be associated with bloodstream infections. Patients with lower baseline Bacteroidetes abundance are more prone to infections, and its abundance can serve as an independent predictor of infectious complications.
Humans ; Gastrointestinal Microbiome ; Leukemia, Myeloid, Acute/microbiology* ; Induction Chemotherapy ; Feces/microbiology* ; Male ; Female ; Middle Aged

OBJECTIVE: To explore the potential effects and mechanisms of Liang-Ge-San (LGS) for the treatment of acute respiratory distress syndrome (ARDS) through network pharmacology analysis and to verify LGS activity through biological experiments. METHODS: The key ingredients of LGS and related targets were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. ARDS-related targets were selected from GeneCards and DisGeNET databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed using the Metascape Database. Molecular docking analysis was used to confirm the binding affinity of the core compounds with key therapeutic targets. Finally, the effects of LGS on key signaling pathways and biological processes were determined by in vitro and in vivo experiments. RESULTS: A total of LGS-related targets and 496 ARDS-related targets were obtained from the databases. Network pharmacological analysis suggested that LGS could treat ARDS based on the following information: LGS ingredients luteolin, wogonin, and baicalein may be potential candidate agents. Mitogen-activated protein kinase 14 (MAPK14), recombinant V-Rel reticuloendotheliosis viral oncogene homolog A (RELA), and tumor necrosis factor alpha (TNF-α) may be potential therapeutic targets. Reactive oxygen species metabolic process and the apoptotic signaling pathway were the main biological processes. The p38MAPK/NF-κ B signaling pathway might be the key signaling pathway activated by LGS against ARDS. Moreover, molecular docking demonstrated that luteolin, wogonin, and baicalein had a good binding affinity with MAPK14, RELA, and TNF α. In vitro experiments, LGS inhibited the expression and entry of p38 and p65 into the nucleation in human bronchial epithelial cells (HBE) cells induced by LPS, inhibited the inflammatory response and oxidative stress response, and inhibited HBE cell apoptosis (P<0.05 or P<0.01). In vivo experiments, LGS improved lung injury caused by ligation and puncture, reduced inflammatory responses, and inhibited the activation of p38MAPK and p65 (P<0.05 or P<0.01). CONCLUSION LGS could reduce reactive oxygen species and inflammatory cytokine production by inhibiting p38MAPK/NF-κ B signaling pathway, thus reducing apoptosis and attenuating ARDS.
Drugs, Chinese Herbal/pharmacology* ; Respiratory Distress Syndrome/enzymology* ; p38 Mitogen-Activated Protein Kinases/metabolism* ; NF-kappa B/metabolism* ; Animals ; Signal Transduction/drug effects* ; Molecular Docking Simulation ; Humans ; Male ; Network Pharmacology ; Apoptosis/drug effects* ; Mice