TUFM in health and disease: exploring its multifaceted roles

The nuclear-encoded mitochondrial protein Tu translation elongation factor, mitochondrial (TUFM) is well-known for its role in mitochondrial protein translation. Originally discovered in yeast, TUFM demonstrates significant evolutionary conservation from prokaryotes to eukaryotes. Dysregulation of TUFM has been associated with mitochondrial disorders. Although early hypothesis suggests that TUFM is localized within mitochondria, recent studies identify its presence in the cytoplasm, with this subcellular distribution being linked to distinct functions of TUFM. Significantly, in addition to its established function in mitochondrial protein quality control, recent research indicates a broader involvement of TUFM in the regulation of programmed cell death processes (e.g., autophagy, apoptosis, necroptosis, and pyroptosis) and its diverse roles in viral infection, cancer, and other disease conditions. This review seeks to offer a current summary of TUFM’s biological functions and its complex regulatory mechanisms in human health and disease. Insight into these intricate pathways controlled by TUFM may lead to the potential development of targeted therapies for a range of human diseases

Optimisation of the Logistics System in an Electric Motor Assembly Flowshop by Integrating the Taguchi Approach and Discrete Event Simulation

An electric motor assembly flowshop (EMAF) is a type of classical mixed-product assembly line that uses automatic guided vehicle (AGV) systems for material handling. To optimise the logistics system configuration and alleviate the impact of the AGV parameters on the efficiency of the EMAF, a modelling and optimisation method based on discrete event simulation (DES) combined with Taguchi orthogonal experimental design was proposed. A DES model of the entire production process for the EMAF was constructed using the Tecnomatix Plant Simulation software package. After optimisation of the principal layout in the DES model, the number of assembly stations was decreased from 13 to 9, and the balance ratio was increased from 65.08% to 84.65%. In addition, the combination of the Taguchi method with the DES model was further developed to achieve the optimal parameter combination of the AGVs in order to allow the AGVs to operate more efficiently under various states. The final overall theoretical throughput was increased from 134 to 295 units within the seven-hour observation period

Optimisation of the Logistics System in an Electric Motor Assembly Flowshop by Integrating the Taguchi Approach and Discrete Event Simulation

An electric motor assembly flowshop (EMAF) is a type of classical mixed-product assembly line that uses automatic guided vehicle (AGV) systems for material handling. To optimise the logistics system configuration and alleviate the impact of the AGV parameters on the efficiency of the EMAF, a modelling and optimisation method based on discrete event simulation (DES) combined with Taguchi orthogonal experimental design was proposed. A DES model of the entire production process for the EMAF was constructed using the Tecnomatix Plant Simulation software package. After optimisation of the principal layout in the DES model, the number of assembly stations was decreased from 13 to 9, and the balance ratio was increased from 65.08% to 84.65%. In addition, the combination of the Taguchi method with the DES model was further developed to achieve the optimal parameter combination of the AGVs in order to allow the AGVs to operate more efficiently under various states. The final overall theoretical throughput was increased from 134 to 295 units within the seven-hour observation period

Assessment of important soil properties related to Chinese Soil Taxonomy based on vis–NIR reflectance spectroscopy

Assessment of important soil properties related to Chinese Soil Taxonomy based on vis–NIR reflectance spectroscop

High Sensitivity Determination of TNF-α for Early Diagnosis of Neonatal Infections with a Novel and Reusable Electrochemical Sensor

Early diagnosis is vital for the reduction of mortality caused by neonatal infections. Since TNF-α can be used as a marker for the early diagnosis, the detection of TNF-α with high sensitivity and specificity has great clinical significance. Herein, a highly sensitive and reusable electrochemical sensor was fabricated. Due to the high specificity of aptamers, TNF-α could be accurately detected from five similar cytokines, even from serum samples. In addition, Au nanoparticles (AuNPs) with a high surface area were able to combine a large number of doxorubicin hydrochloride (DOXh), which made the sensor have a high sensitivity. The sensor had a good linear relationship with TNF-α concentration in the range from 1 to 1 × 104 pg/mL and the lowest detection limit is 0.7 pg/mL. More important was that the sensor could be reused 6 times by a crafty use of chain replacement reaction. Meanwhile, the detection time and cost were greatly reduced. Thus, we believe that these advantages of higher specificity and sensitivity, lower cost, and shorter detection time will provide a stronger potential for early diagnosis of neonatal infections in clinical applications

Quantitative Estimation of Soil Salinity Using UAV-Borne Hyperspectral and Satellite Multispectral Images

Soil salinization is a global issue resulting in soil degradation, arable land loss and ecological environmental deterioration. Over the decades, multispectral and hyperspectral remote sensing have enabled efficient and cost-effective monitoring of salt-affected soils. However, the potential of hyperspectral sensors installed on an unmanned aerial vehicle (UAV) to estimate and map soil salinity has not been thoroughly explored. This study quantitatively characterized and estimated field-scale soil salinity using an electromagnetic induction (EMI) equipment and a hyperspectral camera installed on a UAV platform. In addition, 30 soil samples (0~20 cm) were collected in each field for the lab measurements of electrical conductivity. First, the apparent electrical conductivity (ECa) values measured by EMI were calibrated using the lab measured electrical conductivity derived from soil samples based on empirical line method. Second, the soil salinity was quantitatively estimated using the random forest (RF) regression method based on the reflectance factors of UAV hyperspectral images and satellite multispectral data. The performance of models was assessed by Lin’s concordance coefficient (CC), ratio of performance to deviation (RPD), and root mean square error (RMSE). Finally, the soil salinity of three study fields with different land cover were mapped. The results showed that bare land (field A) exhibited the most severe salinity, followed by dense vegetation area (field C) and sparse vegetation area (field B). The predictive models using UAV data outperformed those derived from GF-2 data with lower RMSE, higher CC and RPD values, and the most accurate UAV-derived model was developed using 62 hyperspectral bands of the image of the field A with the RMSE, CC, and RPD values of 1.40 dS m−1, 0.94, and 2.98, respectively. Our results indicated that UAV-borne hyperspectral imager is a useful tool for field-scale soil salinity monitoring and mapping. With the help of the EMI technique, quantitative estimation of surface soil salinity is critical to decision-making in arid land management and saline soil reclamation

Clinical impact and in vitro characterization of ADNP variants in pediatric patients

Abstract Background Helsmoortel–Van der Aa syndrome (HVDAS) is a rare genetic disorder caused by variants in the activity-dependent neuroprotector homeobox (ADNP) gene; hence, it is also called ADNP syndrome. ADNP is a multitasking protein with the function as a transcription factor, playing a critical role in brain development. Furthermore, ADNP variants have been identified as one of the most common single-gene causes of autism spectrum disorder (ASD) and intellectual disability. Methods We assembled a cohort of 15 Chinese pediatric patients, identified 13 variants in the coding region of ADNP gene, and evaluated their clinical phenotypes. Additionally, we constructed the corresponding ADNP variants and performed western blotting and immunofluorescence analysis to examine their protein expression and subcellular localization in human HEK293T and SH-SY5Y cells. Results Our study conducted a thorough characterization of the clinical manifestations in 15 children with ADNP variants, and revealed a broad spectrum of symptoms including global developmental delay, intellectual disability, ASD, facial abnormalities, and other features. In vitro studies were carried out to check the expression of ADNP with identified variants. Two cases presented missense variants, while the remainder exhibited nonsense or frameshift variants, leading to truncated mutants in in vitro overexpression systems. Both overexpressed wildtype ADNP and all the different mutants were found to be confined to the nuclei in HEK293T cells; however, the distinctive pattern of nuclear bodies formed by the wildtype ADNP was either partially or entirely disrupted by the mutant proteins. Moreover, two variants of p.Y719* on the nuclear localization signal (NLS) of ADNP disrupted the nuclear expression pattern, predominantly manifesting in the cytoplasm in SH-SY5Y cells. Limitations Our study was limited by a relatively small sample size and the absence of a longitudinal framework to monitor the progression of patient conditions over time. Additionally, we lacked in vivo evidence to further indicate the causal implications of the identified ADNP variants. Conclusions Our study reported the first cohort of HVDAS patients in the Chinese population and provided systematic clinical presentations and laboratory examinations. Furthermore, we identified multiple genetic variants and validated them in vitro. Our findings offered valuable insights into the diverse genetic variants associated with HVDAS