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Abstract Objective To further comprehend the phenotype of multiple mitochondrial dysfunction syndrome type 3 (MMDS3:OMIM#615330) caused by IBA57 mutation. We present a case involving a patient who experienced acute neurological regression, and the literature was reviewed. Methods Clinical data and laboratory test results were collected; early language and development progress were tested; and genetic testing was performed. Bioinformatics analysis was performed using Mutation Taster and PolyPhen‐2, and the literature in databases such as PubMed and CNKI was searched using MMDS3 and IBA57 as keywords. Results The child, aged 1 year and 2 months, had motor decline, unable to sit alone, limited right arm movement, hypotonia, hyperreflexia of both knees, and Babinski sign positivity on the right side, accompanied by nystagmus. Blood lactate levels were elevated at 2.50 mmol/L. Brain MR indicated slight swelling in the bilateral frontoparietal and occipital white matter areas and the corpus callosum, with extensive abnormal signals on T1 and T2 images, along with the semioval center and occipital lobes bilaterally. The multiple abnormal signals in the brain suggested metabolic leukoencephalopathy. Whole‐exome sequencing analysis revealed that the child had two heterozygous mutations in the IBA57 gene, c.286T>C (p.Y96H) (likely pathogenic, LP) and c.992T>A (p.L331Q) (variant of uncertain significance, VUS). As of March 2023, a literature search showed that 56 cases of MMDS3 caused by IBA57 mutation had been reported worldwide, with 35 cases reported in China. Among the 35 IBA57 mutations listed in the HGMD database, there were 28 missense or nonsense mutations, 2 splicing mutations, 2 small deletions, and 3 small insertions. Conclusion MMDS3 predominantly manifests in infancy, with primary symptoms including feeding difficulties, neurological functional regression, muscle weakness, with severe cases potentially leading to mortality. Diagnosis is supported by elevated lactate levels, multisystem impairment (including auditory and visual systems), and distinctive MRI findings. Whole‐exome sequencing is crucial for diagnosis. Currently, cocktail therapy offers symptomatic relief.

BackgroundThe inflammatory response plays an essential role in the tumor microenvironment (TME) of colorectal cancer (CRC) by modulating tumor growth, progression, and response to therapy through the recruitment of immune cells, production of cytokines, and activation of signaling pathways. However, the molecular subtypes and risk score prognostic model based on inflammatory response remain to be further explored.MethodsInflammation-related genes were collected from the molecular signature database and molecular subtypes were identified using nonnegative matrix factorization based on the TCGA cohort. We compared the clinicopathological features, immune infiltration, somatic mutation profile, survival prognosis, and drug sensitivity between the subtypes. The risk score model was developed using LASSO and multivariate Cox regression in the TCGA cohort. The above results were independently validated in the GEO cohort. Moreover, we explored the biological functions of the hub gene, receptor interacting protein kinase 2 (RIPK2), leveraging proteomics data, in vivo, and in vitro experiments.ResultsWe identified two inflammation-related subtypes (inflammation-low and inflammation-high) and have excellent internal consistency and stability. Inflammation-high subtype showed higher immune cell infiltration and increased sensitivity to common chemotherapeutic drugs, while inflammation-low subtype may be more suitable for immunotherapy. Besides, the two subtypes differ significantly in pathway enrichment and biological functions. In addition, the 11-gene signature prognostic model constructed from inflammation-related genes showed strong prognostic assessment power and could serve as a novel prognostic marker to predict the survival of CRC patients. Finally, RIPK2 plays a crucial role in promoting malignant proliferation of CRC cell validated by experiment.ConclusionsThis study provides new insights into the heterogeneity of CRC and provides novel opportunities for treatment development and clinical decision making.

Abstract Objective This study aimed to establish novel nomograms that could be used to predict the prognosis of gastric carcinoma patients who underwent D2 + total gastrectomy on overall survival (OS) and progression-free survival (PFS). Methods Lasso regression was employed to construct the nomograms. The internal validation process included bootstrapping, which was used to test the accuracy of the predictions. The calibration curve was then used to demonstrate the accuracy and consistency of the predictions. In addition, the Harrell’s Concordance index (C-index) and time-dependent receiver operating characteristic (t-ROC) curves were used to evaluate the discriminative abilities of the new nomograms and to compare its performance with the 8th edition of AJCC-TNM staging. Furthermore, decision curve analysis (DCA) was performed to assess the clinical application of our model. Finally, the prognostic risk stratification of gastric cancer was conducted with X-tile software, and the nomograms were converted into a risk-stratifying prognosis model. Results LASSO regression analysis identified pT stage, the number of positive lymph nodes, vascular invasion, neural invasion, the maximum diameter of tumor, the Clavien–Dindo classification for complication, and Ki67 as independent risk factors for OS and pT stage, the number of positive lymph nodes, neural invasion, and the maximum diameter of tumor for PFS. The C-index of OS nomogram was 0.719 (95% CI: 0.690–0.748), which was superior to the 8th edition of AJCC-TNM staging (0.704, 95%CI: 0.623–0.783). The C-index of PFS nomogram was 0.694 (95% CI: 0.654–0.713), which was also better than that of the 8th edition of AJCC-TNM staging (0.685, 95% CI: 0.635–0.751). The calibration curves, t-ROC curves, and DCA of the two nomogram models showed that the prediction ability of the two nomogram models was outstanding. The statistical difference in the prognosis between the low- and high-risk groups further suggested that our model had an excellent risk stratification performance. Conclusion We reported the first risk stratification and nomogram for gastric carcinoma patients with total gastrectomy in Chinese population. Our model could potentially be used to guide treatment selections for the low- and high-risk patients to avoid delayed treatment or unnecessary overtreatment.

BackgroundDiabetic nephropathy (DN), which is the main cause of renal failure in end-stage renal disease, is becoming a common chronic renal disease worldwide. Mendelian randomization (MR) is a genetic tool that is widely used to minimize confounding and reverse causation when identifying the causal effects of complex traits. In this study, we conducted an integrated multiple microarray analysis and large-scale plasma proteome MR analysis to identify candidate biomarkers and evaluate the causal effects of prospective therapeutic targets in DN.MethodsFive DN gene expression datasets were selected from the Gene Expression Omnibus. The robust rank aggregation (RRA) method was used to integrate differentially expressed genes (DEGs) of glomerular samples between patients with DN and controls, followed by functional enrichment analysis. Protein quantitative trait loci were incorporated from seven different proteomic genome-wide association studies, and genetic association data on DN were obtained from FinnGen (3676 cases and 283,456 controls) for two-sample MR analysis. External validation and clinical correlation were also conducted.ResultsA total of 82 DEGs (53 upregulated and 29 downregulated) were identified through RRA integrated analysis. The enriched Gene Ontology annotations and Kyoto Encyclopedia of Genes and Genomes pathways of the DEGs were significantly enriched in neutrophil degranulation, neutrophil activation, proteoglycan binding, collagen binding, secretory granule lumen, gluconeogenesis, tricarboxylic acid cycle, and pentose phosphate pathways. MR analysis revealed that the genetically predicted levels of MHC class I polypeptide-related sequence B (MICB), granzyme A (GZMA), cathepsin S (CTSS), chloride intracellular channel protein 5, and ficolin-1 (FCN1) were causally associated with DN risk. Expression validation and clinical correlation analysis showed that MICB, GZMA, FCN1, and insulin-like growth factor 1 may participate in the development of DN, and carbonic anhydrase 2 and lipoprotein lipase may play protective roles in patients with DN.ConclusionOur integrated analysis identified novel biomarkers, including MICB and GZMA, which may help further understand the complicated mechanisms of DN and identify new target pathways for intervention.

Objective. A 3-month depot of leuprorelin acetate (LA) was introduced in China in July 2020. However, the clinical experience is limited. The purpose of this study was to compare the efficacy of a LA 11.25 mg 3-month depot with that of a 3.75 mg 1-month depot in suppressing pubertal development for the treatment of central precocious puberty (CPP). Subjects and Methods. A prospective study, including 78 girls with CPP treated with LA, was conducted. 31 patients were treated with a LA 3-month depot, and 47 were treated with a LA 1-month depot. Participants were interviewed at baseline and 6 months. Anthropometric, metabolic, and reproductive data were assessed at each interview. Bone age, serum endocrine hormones, maximum diameter of uterus and volume of ovary of each patient were evaluated. A pharmacoeconomic evaluation was also conducted. Results. Treatment with a 3-month depot was similar to treatment with a 1-month depot in terms of baseline characteristics. After 6 months of treatment, a suppressed level of luteinizing hormone (LH) (LH

According to French Paradox, red wine was famous for the potential effects on coronary heart disease (CHD), but the specific compounds against CHD were unclear. Therefore, screening and characterization of bioactive compounds from red wine was extremely necessary. In this paper, the multi-activity integrated strategy was developed and validated to screen, identify and quantify active compounds from red wine by using ultra high performance liquid chromatography-fraction collector (UHPLC-FC), ultra fast liquid chromatography-quadrupole-time-of-flight/mass spectrometry (UFLC-Q-TOF/MS) and bioactive analysis. UHPLC-FC was employed to separate and collect the components from red wine, which was further identified by UFLC-Q-TOF/MS to acquire their structural information. Furthermore, the active fractions were tested for antioxidant activity, inhibitory activity against thrombin and lipase activities in vitro by the activity screening kit. As the results, there were 37 fractions had antioxidant activity, 22 fractions had thrombin inhibitory activity and 28 fractions had lipase inhibitory activity. Finally, 77 active components from red wine were screened and 12 ingredients out of them were selected for quantification based on the integration of multi-activity. Collectively, the multi-activity integrated strategy was helpful for the rapid and effective discovery of bioactive components, which provided reference for exploring the health care function of food.