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Human pathogenic variants of TBC1D24 are associated with clinically heterogeneous phenotypes, including recessive nonsyndromic deafness DFNB86, dominant nonsyndromic deafness DFNA65, seizure accompanied by deafness, a variety of isolated seizure phenotypes and DOORS syndrome, characterized by deafness, onychodystrophy, osteodystrophy, intellectual disability and seizures. Thirty-five pathogenic variants of human TBC1D24 associated with deafness have been reported. However, functions of TBC1D24 in the inner ear and the pathophysiology of TBC1D24-related deafness are unknown. In this study, a novel splice-site variant of TBC1D24 c.965 + 1G > A in compound heterozygosity with c.641G > A p.(Arg214His) was found to be segregating in a Pakistani family. Affected individuals exhibited, either a deafness-seizure syndrome or nonsyndromic deafness. In human temporal bones, TBC1D24 immunolocalized in hair cells and spiral ganglion neurons, whereas in mouse cochlea, Tbc1d24 expression was detected only in spiral ganglion neurons. We engineered mouse models of DFNB86 p.(Asp70Tyr) and DFNA65 p.(Ser178Leu) nonsyndromic deafness and syndromic forms of deafness p.(His336Glnfs*12) that have the same pathogenic variants that were reported for human TBC1D24. Unexpectedly, no auditory dysfunction was detected in Tbc1d24 mutant mice, although homozygosity for some of the variants caused seizures or lethality. We provide some insightful supporting data to explain the phenotypic differences resulting from equivalent pathogenic variants of mouse Tbc1d24 and human TBC1D24.

Recent research provides limited knowledge about how and whether digital transformation related to environmental, social, and governance (ESG) affects the total factor productivity (TFP). To fill the gap, this study explores the impact of digital transformation on TFP based on a fixed‐effect model and the staggered difference‐in‐differences method and reveals that digital transformation can boost corporate TFP. Mechanism analysis reveals that digital transformation promotes ESG performance in companies, thereby affecting TFP. Social performance in ESG plays a mediating effect, while environmental performance plays a suppressing effect. Besides, the primary driver of TFP improvement through digital transformation lies in its direct effect, whereas the indirect effect of ESG factors is relatively limited. Our findings provide new insight into how digital transformation promotes corporate ESG and productivity. [ABSTRACT FROM AUTHOR]

Organizations are advised to consistently seek and assimilate novel information from external sources to enhance their adsorptive capacity and better understand and address environmental challenges. Despite the evident influence of external knowledge on absorptive capacity and green innovation performance (GIP), there is a notable dearth of discussion on the internal mechanisms facilitating this transformation, potentially leading to adverse consequences for GIP. In response to this gap, our research intends to explore the direct impact of organizational forgetting (OF) on GIP, both independently and through potential absorptive capacity (PAC) and realized absorptive capacity (RAC). Further, this investigation incorporates the moderating role of organizational improvisation (OI) to provide a comprehensive understanding of an encompassing model. Utilizing structural equation modeling (SEM) on data from 321 respondents from Chinese manufacturing firms, our findings reveal that OF significantly contributes to GIP, PAC, and RAC. Moreover, this association is partially mediated by both PAC and RAC. Further, OI expressively moderated the targeted relationships in confounding ways. Importance–performance map analysis also highlights the pivotal role of PAC with a notable performance value (68.812), while OF takes precedence in importance with a substantial value (0.572) compared to all exogenous variables. These insights contribute to an enriched understanding of the vital role OF plays in enhancing PAC, RAC, OI, and GIP—an aspect that has yielded inconsistent results in prior studies. Consequently, our findings advocate for increased investment by managers and policymakers in cultivating the capacity to absorb new knowledge as a strategic imperative for fostering innovation and GIP within industries. [ABSTRACT FROM AUTHOR]

Intellectual disability (ID), which affects around 2% to 3% of the population, accounts for 0.63% of the overall prevalence of neurodevelopmental disorders (NDD). ID is characterized by limitations in a person's intellectual and adaptive functioning, and is caused by pathogenic variants in more than 1000 genes. Here, we report a rare missense variant (c.350T>C; p.(Leu117Ser)) in HACE1 segregating with NDD syndrome with clinical features including ID, epilepsy, spasticity, global developmental delay, and psychomotor impairment in two siblings of a consanguineous Pakistani kindred. HACE1 encodes a HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1), which is involved in protein ubiquitination, localization, and cell division. HACE1 is also predicted to interact with several proteins that have been previously implicated in the ID phenotype in humans. The p.(Leu117Ser) variant replaces an evolutionarily conserved residue of HACE1 and is predicted to be deleterious by various in silico algorithms. Previously, eleven protein truncating variants of HACE1 have been reported in individuals with NDD. However, to our knowledge, p.(Leu117Ser) is the second missense variant in HACE1 found in an individual with NDD. [ABSTRACT FROM AUTHOR]

Here we demonstrate association of variants in the mitochondrial asparaginyl-tRNA synthetase NARS2 with human hearing loss and Leigh syndrome. A homozygous missense mutation ([c.637G>T; p.Val213Phe]) is the underlying cause of nonsyndromic hearing loss (DFNB94) and compound heterozygous mutations ([c.969T>A; p.Tyr323*] + [c.1142A>G; p.Asn381Ser]) result in mitochondrial respiratory chain deficiency and Leigh syndrome, which is a neurodegenerative disease characterized by symmetric, bilateral lesions in the basal ganglia, thalamus, and brain stem. The severity of the genetic lesions and their effects on NARS2 protein structure cosegregate with the phenotype. A hypothetical truncated NARS2 protein, secondary to the Leigh syndrome mutation p.Tyr323* is not detectable and p.Asn381Ser further decreases NARS2 protein levels in patient fibroblasts. p.Asn381Ser also disrupts dimerization of NARS2, while the hearing loss p.Val213Phe variant has no effect on NARS2 oligomerization. Additionally we demonstrate decreased steady-state levels of mt-tRNAAsn in fibroblasts from the Leigh syndrome patients. In these cells we show that a decrease in oxygen consumption rates (OCR) and electron transport chain (ETC) activity can be rescued by overexpression of wild type NARS2. However, overexpression of the hearing loss associated p.Val213Phe mutant protein in these fibroblasts cannot complement the OCR and ETC defects. Our findings establish lesions in NARS2 as a new cause for nonsyndromic hearing loss and Leigh syndrome.

Fuzzy set theory is the most powerful tool to describe the process of uncertainty which exist in real world and fuzzy regression is an important research topic which can be used for prediction by establishing the functional relationship between fuzzy variables. Quantile regression is also a significant statistical method for estimating and drawing inferences about conditional quantile functions. This study introduced the idea of quantile regression with respect to fuzzy. The ordinary fuzzy regression is based on least square method but here we have introduced the idea of weighted least absolute deviation method in fuzzy regression. We have considered two different cases for the illustration of our proposed technique, firstly when the input and output are taken as fuzzy and secondly, the input and output are taken as fuzzy but the parameters are crisp. The algorithm for each case is based on linear programming problem (LPP). The LPP is constructed for individual case and solved it by the method of Simplex procedure. The proposed work is then compared with the conventional fuzzy regression by using AIC criterion. Empirical study shows that the proposed technique works best in every situation where the fuzzy regression fails and also provide the results in depth. [ABSTRACT FROM AUTHOR]