Age- and sex-specific reference intervals for thyroid hormones in a Chinese pediatrics: a prospective observational study of 1,279 healthy children Cong Yao, Mo Wu, Mei Liu, Xiaoqian Chen, Hongmin Zhu, Chen Xiong, Dan Wang, Yun Xiang, Guori Suo, Jun Wang, Hong Sun, Chunhui Yuan, Yong Xia

Background: The transfer RNA (tRNA)-derived fragments, generated by the cleavage of mature and pre-tRNAs, play a vital role in the tumorigenesis and progression of hepatocellular carcinoma (HCC). However, the relationship between tRNA-derived fragments and the prognosis of patients with HCC has not been thoroughly studied. This study aims to discuss the relationship between tiRNA-Gly-GCC-002 and the prognosis of HCC patients and its role in guiding HCC treatment. Methods: In this study, the differently expressed tRNA-derived fragments were screened out from the tumor tissues and paracancerous tissues. These tRNA-derived fragments were validated in the tissues and serum samples of patients with HCC by quantitative real-time polymerase chain reaction (qRT-PCR). The target genes of the tRNA-derived fragments were predicted with the microRNA target prediction database (miRDB), which was proceeded with gene set enrichment analysis (GSEA). After that, we analyzed the prognostic effect of the tRNA-derived fragment in relapse-free survival (RFS). Based on univariate and multivariate Cox regression analysis, independent prognostic factors for RFS were obtained. In addition, a column chart was constructed based on clinical pathological features and tiRNAGly-GCC-002. Results: The tiRNA-Gly-GCC-002 was ultimately served as the candidate gene. Function analysis indicated that tiRNA-Gly-GCC-002 was primarily involved in adenyl nucleotide binding, cell cycle, cell cycle process and chromosome organization. We found that patients with high expression level of tiRNA-Gly-GCC-002 had worse prognosis than low expression level. The univariable and multivariable Cox regression analyses showed that tiRNAGly-GCC-002 was an important prognostic factor. Furthermore, the nomogram by combining tiRNA-Gly-GCC-002 expression level (P=0.03) and serum gamma-glutamyl transferase (GGT) level (P=0.001) was established to predict the prognosis of patients with HCC [concordance index (C-index): 0.789]. Conclusions: In summary, the tiRNA-Gly-GCC-002 can predict the outcome of patients with HCC, which may play a vital role in directing the treatment of HCC.

Background: Identifying alpha-fetal protein (AFP)-negative focal hepatic lesions presents a significant challenge, particularly in China. We sought to develop an economically portable tool for the diagnosis of benign and malignant liver lesions with AFP-negative status, and explore its clinical diagnostic efficiency. Methods: A retrospective study was conducted at Peking University Shenzhen Hospital from January 2017 to February 2023, including a total of 348 inpatients with AFP-negative liver space-occupying lesions. The study used a training set of 252 inpatients from January 2017 to September 2021 to establish a diagnostic model for differentiating benign and malignant AFP-negative liver space-occupying lesions. Additionally, a validation cohort of 96 inpatients from October 2021 to February 2023 was used to confirm the diagnostic performance of the model. From January 2017 to February 2023, patients at JingNing People’s Hospital, Gansu Province were assigned to the external cohort (n = 78). Results: A predictive tool was established by screening age, gender, hepatitis B virus (HBV)/hepatitis C virus (HCV) infected, single lesion, alanine amino transferase (ALT), and lymphocyte-to-monocyte ratio (LMR) using multivariate logistic regression analysis and clinical practice. The area under the curve (AUC) of the model was 0.911 (95% CI [0.873–0.949]) in the training set and 0.882 (95% CI [0.815–0.949]) in the validation cohort. In addition, the model achieved an area under the curve of 0.811 (95% CI [0.687–0.935]) in the external validation cohort. Conclusion: Our results demonstrated that the predictive tool has the characteristics of good diagnostic efficiency, economy and convenience, which is helpful for the clinical triage and decision-making of AFP-negative liver space-occupying lesions.

Background: To make early prediction of immunoglobulin A nephropathy (IgAN) before renal biopsy, we developed and validated a new non-invasive nomogram for the early prediction of IgAN in primary glomerulonephritis (GN) in south China. Methods: A total of 431 patients were included in this study and additional 113 patients were included as the independent test cohorts to validate our results. A stepwise regression model was used for features selection. Multivariate logistic regression analysis with 5-fold cross validation was used to validate the result of the stepwise selection. Performance of the logistic regression model was assessed with respect to its calibration, discrimination, and clinical usefulness. Independent test was assessed. Results: We developed a model incorporating age of patients and four clinical chemistry signatures, including serum IgA, serum albumin (ALB), serum phosphorus (P) and 24-hour urinary protein (24hUpro) and presented with a nomogram. The area under the receiver operating characteristic (ROC) curve (AUC) reached 0.89 (95% CI: 0.86–0.92) and 0.88 (95%: 0.85-0.92) in the training set and validation set, respectively. The model also had good performance in independent test cohorts (AUC of 0.82, 95% CI: 0.75–0.90). The DCA and calibration plot of the model also shows good performance. Conclusions: The logistic regression model presented in this study incorporates age of patients, IgA, ALB, P and 24hUpro and can be conveniently used to facilitate the individualized prediction of IgAN.

Background Uroepithelial carcinoma is a serious threat to human health and causes heavy economic burden. Enhanced CT is widely used in screening or preliminary diagnosis of uroepithelial tumors. However, false-positive results of enhanced CT will bring unnecessary mental pain, expensive examination costs, physical injuries, and other adverse consequences; while false-negative results of enhanced CT bring delayed treatment, and patients will thus have to bear the adverse consequences of poor prognosis, high treatment costs, poor quality of life, and short survival period. There is an urgent need to find convenient, cost-effective and non-invasive diagnostic methods to reduce the false-negative and false-positive rates of enhanced CT in uroepithelial tumors. The aim of this study was to evaluate the diagnostic value of YiDiXie™-SS and YiDiXie™-HS in uroepithelial carcinoma. Patients and methods 319 subjects (malignant group, n=240; benign group, n=79) were finally included in this study. Remaining serum samples from the subjects were collected and tested by applying the YiDiXie™ all-cancer detection kit to evaluate the sensitivity and specificity of YiDiXie™-SS and YiDiXie™-HS. Results The sensitivity of YiDiXie™-SS in enhanced CT-positive patients was 96.3% (95% CI: 96.3% - 98.3%; 158/164)and its specificity was 64.3% (95% CI: 38.8% - 83.7%; 9/14). This means that the application of YiDiXie ™ -SS reduces the false-positive rate of urological enhanced CT by 64.3% (95% CI: 38.8% - 83.7%; 9/14) with essentially no increase in malignancy leakage. The sensitivity of YiDiXie™-HS in enhanced CT-negative patients was 85.5% (95% CI: 75.9% - 91.7%; 65/76)and its specificity was 84.6% (95% CI: 73.9% - 91.4%; 55/65). This means that the application of YiDiXie™-HS reduces the false-negative rate of urological enhanced CT by 85.5% (95% CI: 75.9% - 91.7%; 65/76). Conclusion YiDiXie ™ -SS substantially reduces the rate of urological enhanced CT false positives with essentially no increase in delayed treatment of malignancies. YiDiXie™-HS substantially reduces the false negative rate of urological enhanced CT. YiDiXie™ -SS and YiDiXie™ -HS have an important diagnostic value in uroepithelial carcinoma, and are expected to solve the problems of “high false-positive rate of urological enhanced CT” and “high false-negative rate of urological enhanced CT” in uroepithelial carcinoma. Clinical trial number ChiCTR2200066840.