Objective To explore the risk factors for postoperative respiratory failure (RF) in patients with esophageal cancer, construct a predictive model based on the least absolute shrinkage and selection operator (LASSO)-logistic regression, and visualize the constructed model. Methods A retrospective analysis was conducted on patients with esophageal cancer who underwent surgical treatment in the Department of Thoracic Surgery, Sun Yat-sen University Cancer Center Gansu Hospital from 2020 to 2023. Patients were divided into a RF group and a non-RF (NRF) group according to whether RF occurred after surgery. Clinical data of the two groups were collected, and LASSO-logistic regression was used to optimize feature selection and construct the predictive model. The model was internally validated by repeated sampling 1000 times based on the Bootstrap method. Results A total of 217 patients were included, among which 24 were in the RF group, including 22 males and 2 females, with an average age of (63.33±9.10) years; 193 were in the NRF group, including 161 males and 32 females, with an average age of (62.14±8.44) years. LASSO-logistic regression analysis showed that the percentage of forced expiratory volume in one second/forced vital capacity (FEV1/FVC) to predicted value (FEV1/FVC%pred) [OR=0.944, 95%CI (0.897, 0.993), P=0.026], postoperative anastomotic fistula [OR=4.106, 95%CI (1.457, 11.575), P=0.008], and postoperative lung infection [OR=3.776, 95%CI (1.373, 10.388), P=0.010] were risk factors for postoperative RF in patients with esophageal cancer. Based on the above risk factors, a predictive model was constructed, with an area under the receiver operating characteristic curve of 0.819 [95%CI (0.737, 0.901)]. The Hosmer-Lemeshow test for the calibration curve showed that the model had good goodness of fit (P=0.527). The decision curve showed that the model had good clinical net benefit when the threshold probability was between 5% and 50%. Conclusion FEV1/FVC%pred, postoperative anastomotic fistula, and postoperative lung infection are risk factors for postoperative RF in patients with esophageal cancer. The predictive model constructed based on LASSO-logistic regression analysis is expected to help medical staff screen high-risk patients for early individualized intervention.

[Objective] To establish a method for detecting the potency of recombinant human coagulation factor Ⅶa for injection. [Methods] By adding the sample and factor Ⅶ deficient plasma to the sample cup and activating the reaction with prothrombin time assay reagent (PT reagent), the coagulation time of the sample was determined by the change in magnetic bead swing amplitude in the sample cup. The logarithm of coagulation time was inversely proportional to the logarithm of human factor Ⅶa potency. [Results] Under the experimental conditions, the specificity of the methodology was evaluated through spiked recovery, and the recovery rates ranged from 90.0% to 110.0%. Within the range from 0.125 to 1.000 IU/mL, there was a good linear response between the potency and coagulation time of the standard and sample, with correlation coefficients r>0.99. As for the accuracy and repeatability, the recovery rates of various concentrations detected in the stock solution were 101.0%, 100.0% and 112.0%, respectively, with RSD values of 2.6%, 4.0% and 0.0%, respectively. The recovery rates of various concentrations in finished product testing were 104.0%, 94.7% and 112.0%, respectively, with RSD values of 1.9%, 2.4% and 0.0%, respectively. As for the intermediate precision, the RSD were 4.5% and 3.7%, respectively. After treated with sample diluent, the sample was tested at room temperature for 6 hours and still exhibited relatively stable biological activity. [Conclusion] This detection method is accurate, stable, easy to operate and highly automated, and is suitable for detecting the potency of recombinant human coagulation factor Ⅶa for Injection.

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.

OBJECTIVES: To summarize the clinical and genetic characteristics of end-stage renal disease caused by PLCE1 gene mutations. METHODS: A retrospective analysis of the clinical and genetic features of three children from a family with PLCE1 gene mutations was conducted, along with a literature review of hereditary kidney disease cases caused by PLCE1 gene mutations. RESULTS: The proband was an 8-year-old male presenting with nephrotic syndrome stage 4 chronic kidney disease. Renal biopsy showed focal segmental glomerulosclerosis. Two years and five months after kidney transplantation, the patient had persistent negative proteinuria and normal renal function. Whole-exome sequencing identified two pathogenic heterozygous variants: c.961C>T and c.3255_3256delinsT, with c.3255_3256delinsT being a novel mutation. Family screening revealed no renal involvement in the parents, but among five siblings, one brother died at age of 4 years from end-stage renal disease. A 7-year-old sister presented with proteinuria and bilateral medullary sponge kidney, with proteinuria resolving after one year of follow-up. A 3-year-old brother died after kidney transplantation due to severe pneumonia. The literature review included 45 patients with hereditary kidney disease caused by PLCE1 gene mutations. The main clinical phenotype was nephrotic syndrome (87%, 39/45), and renal pathology predominantly showed focal segmental glomerulosclerosis (57%, 16/28). No mutation hotspots were identified. CONCLUSIONS Compound heterozygous mutations in the PLCE1 gene can lead to rapid progression of the disease to end-stage renal disease, with favorable outcomes following kidney transplantation. Family screening is crucial for early diagnosis, and medullary sponge kidney may be a novel phenotype associated with these gene mutations.
Humans ; Male ; Proteinuria/genetics* ; Kidney Failure, Chronic/etiology* ; Child ; Mutation ; Female ; Child, Preschool ; Retrospective Studies ; Phosphoinositide Phospholipase C

OBJECTIVE: To analyze the distribution characteristics of glucose-6-phosphate-dehydrogenase (G6PD) mutations and their enzyme activity in newborns patients with G6PD deficiency in Guilin region. METHODS: From July 2022 to July 2024, umbilical cord blood samples from 4 554 newborns in Guilin were analyzed for G6PD mutations using fluorescence PCR melting curve analysis. Enzyme activity was detected in 4 467 cases using the rate assay. RESULTS: Among 4 467 newborns who underwent G6PD activity testing, 162 newborns (3.63%) were identified as G6PD-deficient, including 142 males (6.04%) and 20 females (0.94%), the prevalence of G6PD deficiency was significantly higher in males than in females (P < 0.001). Genetic analysis of 4 554 newborns detected G6PD mutations in 410 cases (9%), including 171 males (7.13%) and 239 females (11.09%), with a significantly higher mutation detection rate in females than in males (P < 0.001). A total of nine single mutations and four compound heterozygous mutations were identified. The most common mutations were c.1388G>A (33.66%), c.1376G>T (23.66%) and c.95A>G (16.34%). Among newborns who underwent both enzyme activity and genetic mutation testing, males with G6PD mutations had significantly lower enzyme activity than that of females with G6PD mutations(P < 0.001). Specifically, among newborns carrying the mutations c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T or c.871G>A, males consistently exhibited lower enzymatic activity than females with the same mutations (P < 0.001). Furthermore, in male G6PD-deficient newborns, the enzyme activity levels in those carrying c.1388G>A, c.1376G>T, c.95A>G, c.1024C>T, or c.871G>A were lower than those in both the control group and the c.519C>T group (P < 0.05). CONCLUSION This study provides a comprehensive profile of G6PD deficiency incidence and mutation spectrum in the Guilin region. By analyzing enzyme activity and genetic mutation results, this study provides insights into potential intervention strategies and personalized management approaches for the prevention and treatment of neonatal G6PD deficiency in the region.
Humans ; Infant, Newborn ; Glucosephosphate Dehydrogenase Deficiency/epidemiology* ; Glucosephosphate Dehydrogenase/genetics* ; Female ; Male ; Mutation ; China/epidemiology*

Objective To establish a rapid detection method for zika virus based on direct amplification re-al-time fluorescent quantitative reverse transcription polymerase chain reaction(RT-PCR)technique.Methods A direct amplification RT-PCR technique for the rapid detection of zika virus in 5 samples(whole blood,serum,saliva,throat swab and urine)was established by using a special function DNA polymerase and a preferred PCR enhancer.Results The detection limits of the 5 samples were 103 PFU/mL in serum,102 PFU/mL in urine,throat swab,and saliva,and 104 PFU/mL in whole blood.The coefficient of goodness-fit of stand-ard curves was above 0.98,and the amplification efficiency was 90％-110％.Zika virus nucleic acid was suc-cessfully amplified,but non-zika virus nucleic acid was not amplified.Based on the repeatable detection of sam-ples from urine,whole blood,and saliva,the variation coefficient of 6 repeated Ct values at 106 PFU/mL and 102 PFU/mL concentrations were all＜5％.The zika virus detection method established by the direct amplifi-cation RT-PCR technique was consistent with the detection results of conventional RT-PCR technique.Only two serum samples were detected in eight zika virus samples,and the remaining 62 non-zika virus samples and 12 negative samples were not amplified.Conclusion A rapid detection method for zika virus based on direct ampli-fication RT-PCR technique is successfully established.The method is simple,rapid,sensitive and specific.