GTPBP8 modulates mitochondrial fission through a Drp1-dependent process.

Mitochondrial fission is a tightly regulated process involving multiple proteins and cell signaling. Despite extensive studies on mitochondrial fission factors, our understanding of the regulatory mechanisms remains limited. This study shows the critical role of a mitochondrial GTPase, GTPBP8, in orchestrating mitochondrial fission in mammalian cells. Depletion of GTPBP8 resulted in drastic elongation and interconnectedness of mitochondria. Conversely, overexpression of GTPBP8 shifted mitochondrial morphology from tubular to fragmented. Notably, the induced mitochondrial fragmentation from GTPBP8 overexpression was inhibited in cells either depleted of the mitochondrial fission protein Drp1 (also known as DNM1L) or carrying mutated forms of Drp1. Importantly, downregulation of GTPBP8 caused an increase in oxidative stress, modulating cell signaling involved in the increased phosphorylation of Drp1 at Ser637. This phosphorylation hindered the recruitment of Drp1 to mitochondria, leading to mitochondrial fission defects. By contrast, GTPBP8 overexpression triggered enhanced recruitment and assembly of Drp1 at mitochondria. In summary, our study illuminates the cellular function of GTPBP8 as a pivotal modulator of the mitochondrial division apparatus, inherently reliant on its influence on Drp1.

Comparison of the performance of the GLIM criteria, PG-SGA and mPG-SGA in diagnosing malnutrition and predicting survival among lung cancer patients: A multicenter study.

BACKGROUND & AIMS: The present study aimed to compare the ability of the GLIM criteria, PG-SGA and mPG-SGA to diagnose malnutrition and predict survival among Chinese lung cancer (LC) patients. METHODS: This was a secondary analysis of a multicenter, prospective, nationwide cohort study, 6697 LC inpatients were enrolled between July 2013 and June 2020. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC), and quadratic weighted Kappa coefficients were calculated to compare the ability to diagnose malnutrition. There were 754 patients who underwent follow-up for a median duration of 4.5 years. The associations between the nutritional status and survival were analyzed by the Kaplan-Meier method and multivariable Cox proportional hazard regression models. RESULTS: The median age of LC patients was 60 (53, 66), and 4456 (66.5%) were male. There were 617 (9.2%), 752 (11.2%), 1866 (27.9%), and 3462 (51.7%) patients with clinical stage Ⅰ, Ⅱ, Ⅲ, and Ⅳ LC, respectively. Malnutrition was present in 36.1%-54.2% (as evaluated using different tools). Compared with the PG-SGA (used as the diagnostic reference), the sensitivity of the mPG-SGA and GLIM was 93.7% and 48.3%; the specificity was 99.8% and 78.4%; and the AUC was 0.989 and 0.633 (P < 0.001). The weighted Kappa coefficients were 0.41 for the PG-SGA vs. GLIM, 0.44 for the mPG-SGA vs. GLIM, and 0.94 for the mPG-SGA vs PG-SGA in patients with stage Ⅰ-Ⅱ LC. These values were respectively 0.38, 0.39, and 0.93 in patients with stage Ⅲ-Ⅳ of LC. In a multivariable Cox analysis, the mPG-SGA (HR = 1.661, 95%CI = 1.348-2.046, P < 0.001), PG-SGA (HR = 1.701, 95%CI = 1.379-2.097, P < 0.001) and GLIM (HR = 1.657, 95%CI = 1.347-2.038, P < 0.001) showed similar death hazard ratios. CONCLUSIONS: The mPG-SGA provides nearly equivalent power to predict the survival of LC patients as the PG-SGA and the GLIM, indicating that all three tools are applicable for LC patients. The mPG-SGA has the potential to be an alternative replacement for quick nutritional assessment among LC patients.

Development and validation of an online dynamic nomogram system for predicting cancer cachexia among inpatients: a real-world cohort study in China.

BACKGROUND: Early recognition of cachexia is essential for ensuring the prompt intervention and treatment of cancer patients. However, the diagnosis of cancer cachexia (CC) usually is delayed. This study aimed to establish an accurate and high-efficiency diagnostic system for CC. METHODS: A total of 4834 cancer inpatients were enrolled in the INSCOC project from July 2013 to June 2020. All cancer patients in the study were randomly assigned to a development cohort (n=3384, 70%) and a validation cohort (n=1450, 30%). The least absolute shrinkage and selection operator (LASSO) method and multivariable logistic regression were used to identify the independent predictors for developing the dynamic nomogram. Discrimination and calibration were adopted to evaluate the ability of nomogram. A decision curve analysis (DCA) was used to evaluate clinical use. RESULTS: We combined 5 independent predictive factors (age, NRS2002, PG-SGA, QOL by the QLQ-C30, and cancer categories) to establish the online dynamic nomogram system. The C-index, sensitivity, and specificity of the nomo-system to predict CC was 0.925 (95%CI, 0.916-0.934, P < 0.001), 0.826, and 0.862 in the development set, while the values were 0.923 (95%CI, 0.909-0.937, P < 0.001), 0.854, and 0.829 in the validation set. In addition, the calibration curves of the diagnostic nomogram also presented good agreement with the actual situation. DCA showed that the model is clinically useful and can increase the clinical benefit in cancer patients. CONCLUSIONS: This study developed an online dynamic nomogram system with outstanding accuracy to help clinicians and dieticians estimate the probability of cachexia. This simple-to-use online nomogram can increase the clinical benefit in cancer patients and is expected to be widely adopted.

Case Report: Aarskog-scott syndrome caused by FGD1 gene variation: A family study.

Aarskog-Scott syndrome is a rare genetic disorder characterized by short stature, abnormal facial features, and digital and genital deformities. FGD1 gene variation is the known cause of this disorder. This paper described a Chinese family study of Aarskog-Scott syndrome in which the main patients were two brothers. Then, the relationship between genotype and phenotype in Aarskog-Scott syndrome was investigated preliminarily. A new FGD1 gene variant was revealed in this study, providing insights into the link between phenotype and genotype variations in Aarskog-Scott syndrome as well as a foundation for its diagnosis and treatment.

Mitochondrial protein dysfunction in pathogenesis of neurological diseases.

Mitochondria are essential organelles for neuronal function and cell survival. Besides the well-known bioenergetics, additional mitochondrial roles in calcium signaling, lipid biogenesis, regulation of reactive oxygen species, and apoptosis are pivotal in diverse cellular processes. The mitochondrial proteome encompasses about 1,500 proteins encoded by both the nuclear DNA and the maternally inherited mitochondrial DNA. Mutations in the nuclear or mitochondrial genome, or combinations of both, can result in mitochondrial protein deficiencies and mitochondrial malfunction. Therefore, mitochondrial quality control by proteins involved in various surveillance mechanisms is critical for neuronal integrity and viability. Abnormal proteins involved in mitochondrial bioenergetics, dynamics, mitophagy, import machinery, ion channels, and mitochondrial DNA maintenance have been linked to the pathogenesis of a number of neurological diseases. The goal of this review is to give an overview of these pathways and to summarize the interconnections between mitochondrial protein dysfunction and neurological diseases.

Demographic characteristics, family environment and psychosocial factors affecting internet addiction in Chinese adolescents.

BACKGROUND: Internet addiction of adolescents has aroused social concern recently. The present study aims to identify predicting factors of internet addiction on adolescents. METHODS: The demographic characteristics and psychological characteristics of 50, 855 middle school students were investigated through Internet Gaming Disorder Scale- Short Form(IGDS9-SF), Smartphone Application-Based Addiction Scale (SABAS), Bergen Social Media Addiction Scale (BSMAS), Strengths and Difficulties Questionnaire-students (SDQS), 16-Item Version of the Prodromal Questionnaire (PQ-16), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), Multidimensional Peer Victimization Scale (MPVS), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and Connor-Davidson Resilience Scale (CD-RISC10) were used to analyze factors associated with internet addiction by Pearson correlation coefficient and multiple hierarchical regression. RESULTS: IGDS9-SF, SABAS and BSMAS are positively correlated with SDQS, PQ-16, PHQ-9, GAD-7 and MPVS (r-values ranging from 0.180 to 0.488, p < 0.01). IGDS9-SF, SABAS and BSMAS are negatively correlated with WEMWB and CD-RISC (r-values ranging from -0.242 ~ -0.338, p < 0.01). Multiple hierarchical regression shown gender, one-child, twins, left-behind, rural, education (father), drink (father), smoke (father), CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 32.7 % of the variance in internet gaming disorder (IGD) (F = 1174.949, p < 0.001). Group (junior and senior), Gender, Age, One-Child, Twins, Village, Education (father), Drink (father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 28.9 % of the total variance in social media addiction (SMA) (F = 982.932, p < 0.001). Fifteen variables [Gender, Age, Twins, Left-behind, Residence, Residence, Education (mother), Drink(father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, PHQ-9, GAD-7 and MPVS] predicted 30.7 % of the variance in smartphone addiction (SA) (F = 1076.02, p < 0.001). CONCLUSION: The present study found that demographic characteristics, family environment and psychosocial factors were associated with internet gaming addiction, social media addiction and smartphone addiction. Negative psychological factors (such as anxiety and depression) play an important role in different behavioral addictions.

MicroRNA hsa-miR-657 promotes retinoblastoma malignancy by inhibiting peroxisome proliferator-activated receptor alpha expression.

Retinoblastoma is a familial inherited embryonic neuroretinal malignancy with a low survival rate and poor prognosis. Our study aimed to evaluate the potential interaction between microRNA miR-657 and the peroxisome proliferator-activated receptor alpha (PPARA) in retinoblastoma. Expression of miR-657 and PPARA was analyzed in retinoblastoma tissues and cells using RT-qPCR. Cell proliferation, apoptosis, and migration were measured in retinoblastoma cell lines, and xenografting experiments were performed using nude mice. Our study showed that miR-657 expression was markedly increased, whereas that of PPARA was markedly decreased in retinoblastoma. Additionally, PPARA knockdown enhanced the development of retinoblastoma. miR-657 enhanced the retinoblastoma tumorigenesis by directly inhibiting PPARA expression, suggesting that PPARA targeting by miR-657 facilitates retinoblastoma development by enhancing cell growth. This study provides novel insights into the miR-657- and PPARA-mediated mechanisms underlying retinoblastoma progression and suggests that the interaction between miR-657 and PPARA may serve as an effective target for therapeutic intervention.

Fat mass assessment using the triceps skinfold thickness enhances the prognostic value of the Global Leadership Initiative on Malnutrition criteria in patients with lung cancer.

The present study evaluated whether fat mass assessment using the triceps skinfold (TSF) thickness provides additional prognostic value to the Global Leadership Initiative on Malnutrition (GLIM) framework in patients with lung cancer (LC). We performed an observational cohort study including 2672 LC patients in China. Comprehensive demographic, disease and nutritional characteristics were collected. Malnutrition was retrospectively defined using the GLIM criteria, and optimal stratification was used to determine the best thresholds for the TSF. The associations of malnutrition and TSF categories with survival were estimated independently and jointly by calculating multivariable-adjusted hazard ratios (HR). Malnutrition was identified in 808 (30·2 %) patients, and the best TSF thresholds were 9·5 mm in men and 12 mm in women. Accordingly, 496 (18·6 %) patients were identified as having a low TSF. Patients with concurrent malnutrition and a low TSF had a 54 % (HR = 1·54, 95 % CI = 1·25, 1·88) greater death hazard compared with well-nourished individuals, which was also greater compared with malnourished patients with a normal TSF (HR = 1·23, 95 % CI = 1·06, 1·43) or malnourished patients without TSF assessment (HR = 1·31, 95 % CI = 1·14, 1·50). These associations were concentrated among those patients with adequate muscle mass (as indicated by the calf circumference). Additional fat mass assessment using the TSF enhances the prognostic value of the GLIM criteria. Using the population-derived thresholds for the TSF may provide significant prognostic value when used in combination with the GLIM criteria to guide strategies to optimise the long-term outcomes in patients with LC.

Association of Malnutrition, as Defined by the PG-SGA, ESPEN 2015, and GLIM Criteria, With Complications in Esophageal Cancer Patients After Esophagectomy.

Background: There are several approaches that can be used for the pre-treatment identification of malnutrition in oncology populations including the Patient-Generated Subjective Global Assessment (PG-SGA), the 2015 consensus statement by the European Society for Clinical Nutrition and Metabolism (ESPEN 2015) and the Global Leadership Initiative on Malnutrition (GLIM). Aims: This study aimed to evaluate whether malnutrition, as defined by these three methods, can be used to predict complications in esophageal cancer (EC) patients after esophagectomy. Methods: We performed a single center, observational cohort study that included 360 EC patients undergoing esophagectomy from December 2014 to November 2019 at Daping Hospital in China. The prevalence of malnutrition in the study population was prospectively defined using the PG-SGA (≥9 defined malnutrition), and retrospectively defined using the ESPEN 2015 and the GLIM. The prevalence of malnutrition and association with postoperative complications were compared in parallel for the three methods. Results: The prevalence of malnutrition before surgery was 23.1% (83/360), 12.2% (44/360), and 33.3% (120/360) in the study population, as determined by the PG-SGA, the ESPEN 2015 and the GLIM, respectively. The PG-SGA and GLIM had higher diagnostic concordance (Kappa = 0.519, P < 0.001) compared to the ESPEN 2015 vs. GLIM (Kappa = 0.361, P < 0.001) and PG-SGA vs. ESPEN 2015 (Kappa = 0.297, P < 0.001). The overall incidence of postoperative complications for the study population was 58.1% (209/360). GLIM- and ESPEN 2015-defined malnutrition were both associated with the total number of postoperative complications in multivariable analyses. Moreover, GLIM-defined malnutrition exhibited the highest power to identify the incidence of complications among all independent predictors in a pooled analysis. Conclusion: Among the PG-SGA, the ESPEN 2015 and the GLIM, the GLIM framework defines the highest prevalence rate of malnutrition and appears to be the optimal method for predicting postoperative complications in EC patients undergoing esophagectomy. These results support the importance of preoperatively identifying malnutrition using appropriate assessment tools, because it can facilitate the selection of management strategies that will optimize the clinical outcomes of EC patients.

Classification Tree-Based Machine Learning to Visualize and Validate a Decision Tool for Identifying Malnutrition in Cancer Patients.

BACKGROUND: The newly proposed Global Leadership Initiative on Malnutrition (GLIM) framework is promising to gain global acceptance for diagnosing malnutrition. However, the role of machine learning in facilitating its application in clinical practice remains largely unknown. METHODS: We performed a multicenter, observational cohort study including 3998 patients with cancer. Baseline malnutrition was defined using the GLIM criteria, and the study population was randomly divided into a derivation group (n = 2998) and a validation group (n = 1000). A classification and regression trees (CART) algorithm was used to develop a decision tree for classifying the severity of malnutrition in the derivation group. Model performance was evaluated in the validation group. RESULTS: GLIM criteria diagnosed 588 patients (14.7%) with moderate malnutrition and 532 patients (13.3%) with severe malnutrition among the study population. The CART cross-validation identified 5 key predictors for the decision tree construction, including age, weight loss within 6 months, body mass index, calf circumference, and the Nutritional Risk Screening 2002 score. The decision tree showed high performance, with an area under the curve of 0.964 (κ = 0.898, P < .001, accuracy = 0.955) in the validation group. Subgroup analysis showed that the model had apparently good performance in different cancers. Among the 5 predictors constituting the tree, age contributed the least to the classification power. CONCLUSION: Using the machine learning, we visualized and validated a decision tool based on the GLIM criteria that can be conveniently used to accelerate the pretreatment identification of malnutrition in patients with cancer.

Is hand grip strength a necessary supportive index in the phenotypic criteria of the GLIM-based diagnosis of malnutrition in patients with cancer?

BACKGROUND: The Global Leadership Initiative on Malnutrition (GLIM) has the potential to gain global acceptance for diagnosing malnutrition. Of which, calf circumference (CC) was proposed as an alternative to evaluate the reduced muscle mass (RMM). The present study aimed to evaluate whether including the hand grip strength (HGS) was helpful for diagnosing malnutrition under the GLIM framework. METHODS: We performed a multicenter, observational cohort study including 3998 patients with cancer at two teaching hospitals. The RMM criterion was separately assessed using the calf circumference (CC), or the CC and HGS combined. Accordingly, two methods of GLIM diagnosis were independently developed to determine the nutritional status of the patients. The diagnostic concordance, baseline characteristics, and outcomes of patients were compared across the malnourished-CC-HGS, malnourished-CC+HGS, and well-nourished groups. The Patient-Generated Subjective Global Assessment (PG-SGA) was used as a comparator to identify the optimal method. RESULTS: Malnutrition was identified in 1120 (28%) patients by the CC method and 1060 (26.5%) patients by the CC+HGS method. Compared to the well-nourished group, the malnourished-CC+HGS group (60 patients, 1.5%) had poorer nutritional characteristics, poorer Karnofsky Performance Status scores, poorer global quality of life scores, and higher Nutritional Risk Screening 2002 scores. The severity of malnutrition diagnosed using the CC method (Kappa = 0.136) showed higher agreement with the PG-SGA than the CC+HGS method (Kappa = 0.127). CONCLUSION: Compared to CC+HGS, the CC alone appears to be adequate to evaluate RMM under the GLIM framework. A simpler method might facilitate the application of these criteria in clinical settings by increasing efficacy and minimizing missed diagnoses.

Evaluation of the Global Leadership Initiative on Malnutrition Criteria Using Different Muscle Mass Indices for Diagnosing Malnutrition and Predicting Survival in Lung Cancer Patients.

BACKGROUND: Malnutrition is prevalent in lung cancer (LC) patients, yet there are no globally accepted criteria for diagnosing malnutrition. Recently, the Global Leadership Initiative on Malnutrition (GLIM) criteria were proposed. However, the role of these criteria in prospective LC cohorts remains unclear. METHODS: We performed a multicenter, observational cohort study including 1219 LC patients. Different anthropometric measures were compared for assessment of reduced muscle mass (RMM) in the GLIM criteria. Least absolute shrinkage and selection operator and multivariate Cox regressions were performed to analyze the association between the GLIM criteria and survival. Independent prognostic predictors were incorporated to develop a nomogram for individualized survival prediction, and decision curve was applied to assess the clinical significance of the nomogram. RESULTS: Patients in the stage II (severe) malnutrition group, diagnosed using combined calf circumference (CC) plus body weight-standardized handgrip strength (HGS/W) criteria, had the highest hazard ratio (HR, 2.07; 95%CI, 1.50-2.86) compared with other methods used to evaluate RMM. The GLIM criteria diagnosed malnutrition in 24% of cases (292 patients, using the CC and HGS/W criteria) and were effective for determining the nutrition status of LC patients. GLIM-diagnosed malnutrition was an independent risk factor for survival, and malnutrition severity was monotonically associated with death hazards (P = .002). The GLIM nomogram showed good performance in predicting the survival of LC patients, and the decision-curve analysis demonstrated that the nomogram was clinically useful. CONCLUSION: These findings support the effectiveness of GLIM in diagnosing malnutrition and predicting survival among LC patients.

Evaluating mitochondrial DNA in patients with breast cancer and benign breast disease.

PURPOSE: To evaluate the role of mtDNA in breast cancer. METHODS: We carried out an investigation into the mtDNA major control region or D-loop region and an essential and the largest mtDNA protein-coding gene, NADH dehydrogenase subunit 5 (ND5), together with a mitochondrial haplogroup analysis in 64 patients with breast cancer (BC) and 54 patients with benign breast disease (BBD) as controls. RESULTS: Mutations in D-loop region were found in 10/64 or 15.6% of patients with BC and 14/54 or 25.9% of patients with BBD, while mutations in ND5 were detected in 6/64 or 9.4% of patients with BC and 5/54 or 9.3% of patients with BBD. In addition, in patients with BBD, mtDNA mutations were more likely to rise in D-loop region and the mutations were more likely to be heteroplasmic. However, in patients with BC, those with metastatic feature were less likely to carry mutations in D-loop region. Finally, we found haplogroup M has an increased risk of breast cancer compared with haplogroup N. CONCLUSION: mtDNA mutation may play a role in early stage of tumorigenesis, and mitochondrial haplogroup can also modulate breast cancer occurrence.

Maternally inherited hearing loss is associated with the novel mitochondrial tRNA Ser(UCN) 7505T>C mutation in a Han Chinese family.

Mutations in mitochondrial DNA (mtDNA) have been found to be one of the most important causes of sensorineural hearing loss. We report here a clinical, genetic, molecular and biochemical characterization of a Han Chinese pedigree with maternally transmitted nonsyndromic hearing impairment. Seven of nine matrilineal relatives exhibited a variable severity and age-at-onset (8 years old) of hearing loss. Mutational analysis of mtDNA identified the novel homoplasmic tRNA(Ser(UCN)) 7505T>C mutation and other 37 variants belonging to haplogroup F1. The 7505T>C mutation, which is absent in 449 Chinese controls, is located at a highly conserved base-pairing (10A-20U) of tRNA(Ser(UCN)). The abolishment of 10A-20U base-pairing likely alters the tRNA(Ser(UCN)) metabolism. Functional significant of this mutation was supported by approximately 65% reductions in the level of tRNA(Ser(UCN)) observed in the lymphoblastoid cell lines carrying the 7505T>C mutation, compared with the wild-type cell lines. This reduced tRNA level is below the proposed threshold to support a normal respiration in lymphoblastoid cells. Furthermore, the highly conserved tRNA(Ala) 5587T>C and Cytb C93Y variants may have a modifying role of deafness expression associated with the 7505T>C mutation. However, genotyping analysis of nuclear modifier gene TRMU and the prominent deafness-cause gene GJB2 failed to detect any mutations in the member of this family. These data strongly indicate that the novel tRNA(Ser(UCN)) 7505T>C mutation is involved in maternally transmitted hearing loss. However, other genetic, epigenetic or environmental factors may contribute to the phenotypic variability of this family. Our findings will be helpful for counseling families of maternally inherited hearing loss.

Determination of traces of bismuth by quenching of solid-substrate room-temperature phosphorescence from morin-labeled silicon dioxide nano-particles.

Silicon dioxide nano-particles, diameter 50 nm, containing morin (morin-SiO2) have been synthesized by the sol-gel method. They emit strong and stable room-temperature phosphorescence (SS-RTP) on filter paper as substrate, and bismuth can quench the intensity of the SS-RTP. On this basis a new morin-SiO2 solid-substrate room-temperature phosphorescence-quenching method has been established for determination of traces of bismuth. Reduction of phosphorescence intensity (DeltaI(p)) is directly proportional to the concentration of bismuth in the working range 0.16-14.4 ag spot(-1) (sample volume 0.40 muL spot(-1), corresponding to the concentration range 0.40-36.0 fg mL(-1)). The regression equation of the working curve is DeltaI(p)=14.86+5.279x[Bi3+] (ag spot(-1)) (n=6, r=0.9982). The detection limit of this method is 0.026 ag spot(-1) (corresponding to a concentration of 6.5 x 10(-17) g mL(-1)).This sensitive, reproducible and accurate method has been used for successful analysis of real samples.