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Mitochondrial fusion requires the sequential merger of four bilayers to two. The outer-membrane solute carrier protein SLC25A46 interacts with both the outer and inner-membrane dynamin family GTPases Mfn1/2 and Opa1. While SLC25A46 levels are known to affect mitochondrial morphology, how SLC25A46 interacts with Mfn1/2 and Opa1 to regulate membrane fusion is not understood. In this study, we use crosslinking mass-spectrometry and AlphaFold 2 modeling to identify interfaces mediating a SLC25A46 interactions with Opa1 and Mfn2. We reveal that the bundle signaling element of Opa1 interacts with SLC25A46, and present evidence of a Mfn2 interaction involving the SLC25A46 cytosolic face. We validate these newly identified interaction interfaces and show that they play a role in mitochondrial network maintenance.

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Cdc14 phosphatases are related structurally and mechanistically to protein tyrosine phosphatases (PTPs) but evolved a unique specificity for phosphoSer-Pro-X-Lys/Arg sites primarily deposited by cyclin-dependent kinases. This specialization is widely conserved in eukaryotes. The evolutionary reconfiguration of the Cdc14 active site to selectively accommodate phosphoSer-Pro likely required modification to the canonical PTP catalytic cycle. While studying Saccharomyces cerevisiae Cdc14, we discovered a short sequence in the disordered C terminus, distal to the catalytic domain, which mimics an optimal substrate. Kinetic analyses demonstrated this pseudosubstrate binds the active site and strongly stimulates rate-limiting phosphoenzyme hydrolysis, and we named it "substrate-like catalytic enhancer" (SLiCE). The SLiCE motif is found in all Dikarya fungal Cdc14 orthologs and contains an invariant glutamine, which we propose is positioned via substrate-like contacts to assist orientation of the hydrolytic water, similar to a conserved active site glutamine in other PTPs that Cdc14 lacks. AlphaFold2 predictions revealed vertebrate Cdc14 orthologs contain a conserved C-terminal alpha helix bound to the active site. Although apparently unrelated to the fungal sequence, this motif also makes substrate-like contacts and has an invariant glutamine in the catalytic pocket. Altering these residues in human Cdc14A and Cdc14B demonstrated that it functions by the same mechanism as the fungal motif. However, the fungal and vertebrate SLiCE motifs were not functionally interchangeable, illuminating potential active site differences during catalysis. Finally, we show that the fungal SLiCE motif is a target for phosphoregulation of Cdc14 activity. Our study uncovered evolution of an unusual stimulatory pseudosubstrate motif in Cdc14 phosphatases.

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AlphaFold2 (AF2) has emerged in recent years as a groundbreaking innovation that has revolutionized several scientific fields, in particular structural biology, drug design, and the elucidation of disease mechanisms. Many scientists now use AF2 on a daily basis, including non-specialist users. This chapter is aimed at the latter. Tips and tricks for getting the most out of AF2 to produce a high-quality biological model are discussed here. We suggest to non-specialist users how to maintain a critical perspective when working with AF2 models and provide guidelines on how to properly evaluate them. After showing how to perform our own structure prediction using ColabFold, we list several ways to improve AF2 models by adding information that is missing from the original AF2 model. By using software such as AlphaFill to add cofactors and ligands to the models, or MODELLER to add disulfide bridges between cysteines, we guide users to build a high-quality biological model suitable for applications such as drug design, protein interaction, or molecular dynamics studies.

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Introduction: Decades of research in population health have established depression as a likely precursor to Alzheimer's disease. A combination of causal estimates and machine learning methods in artificial intelligence could identify internal and external mediating mechanisms that contribute to the likelihood of progression from depression to Alzheimer's disease. Methods: We developed an integrated predictive model, combining the marginal structural model and an artificial intelligence predictive model, distinguishing between patients likely to progress from depressive states to Alzheimer's disease better than each model alone. Results: The integrated predictive model achieved substantial clinical relevance when using the area under the curve measure. It performed better than the traditional statistical method or a single artificial intelligence method alone. Discussion: The integrated predictive model could form a part of a clinical screening tool that identifies patients who are likely to progress from depression to Alzheimer's disease for early behavioral health interventions. Given the high costs of treating Alzheimer's disease, our model could serve as a cost-effective intervention for the early detection of depression before it progresses to Alzheimer's disease.

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PURPOSE: This study aimed to reveal the association of fatigue with weekly changes in the body composition in patients with nasopharyngeal carcinoma (NPC) and identified the independent strength. METHODS: Four body composition indexes and fatigue were assessed before treatment (T0, baseline) and once a week throughout radiotherapy (T1-T7). Generalized additive mixed models (GAMMs) were used to explore the trajectories and longitudinal relationships of fatigue and weekly changes in body composition. The marginal structural model (MSM) was used to control the effect of depression and anxiety. RESULTS: The trajectories of fatigue in 105 participants reached a peak in the fifth week, and changes in body composition started appearing from the second week. Four body composition indexes, weight, body mass index (BMI), body fat rate, and lean body weight loss weekly were positively associated with fatigue. High magnitude of effects was revealed when anxiety and depression were controlled as time-dependent confounders. The positive associations with fatigue were manifested in patients aged >53 years, those with senior high and above education, no drinking, >5000 Y/month of family inflow, ≥ stage III, or those receiving a dose of ≥70 Gy, ≥3 cycles of induced chemotherapy, and ≤1 cycle of concurrent chemotherapy. CONCLUSIONS: Loss of weight, BMI, body fat rate, and lean body weight could be used to independently evaluate the development of fatigue in patients with NPC during radiotherapy. Positive associations between fatigue and weekly body composition loss were found in patients with certain characteristics.

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Sensor faults are one of the most common faults that cause performance degradation or functional loss in permanent magnet traction drive systems (PMTDSs). To quickly diagnose faulty sensors, this paper proposes a real-time joint diagnosis method for multi-sensor faults based on structural analysis. Firstly, based on limited monitoring signals on board, a structured model of the system was established using the structural analysis method. The isolation and detectability of faulty sensors were analyzed using the Dulmage-Mendelsohn decomposition method. Secondly, the minimum collision set method was used to calculate the minimum overdetermined equation set, transforming the higher-order system model into multiple related subsystem models, thereby reducing modeling complexity and facilitating system implementation. Next, residual vectors were constructed based on multiple subsystem models, and fault detection and isolation strategies were designed using the correlation between each subsystem model and the relevant sensors. The validation results of the physical testing platform based on online fault data recordings showed that the proposed method could achieve rapid fault detection and the localization of multi-sensor faults in PMTDS and had a good application value.

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In this study, we developed a scale to evaluate emotion management and its benefits for young athletes in China, and to analyze the impact of emotion management on their training efficiency. Following an extensive literature review, we used AMOS structural equation model software to develop a scale for evaluating the effects and benefits of emotion management on young athletes' training efficiency. Results showed that young athletes' emotion management training and its benefits can be divided into five dimensions: benefit evaluation, emotional cognition, emotion influence, emotion control, and emotion regulation. The internal consistency reliability of the formal scale was 0.895, and the internal consistency reliability of each subscale was between 0.734 and 0.901. The split-half reliability was 0.769, and the split-half reliability of each subscale was between 0.623 and 0.864. The KMO value was 0.904, P = 0.00 (p < 0.05), and the cumulative interpretation rate was 61.782 % of the total variance. The lowest factor load of a scale item was 0.436, and the highest factor load was 0.846. The common degree of all items was between 0.402 and 0.762, indicating that the scale has good validity. A SEM model verified that the scale has good construct validity. Significant correlational differences were observed among the levels. The results of the SEM structural equation model analysis showed that the model's NC = 2.660 (1 < NC < 3 indicates that the model has a simple fit), PGFI = 0.722, PNFI = 0.699, IFI = 0.851, PRA = 0.927, RMR = 0.006, and RMSEA = 0.07, thus, these indexes reached the standard of excellent model fitting. The strongest correlation was found between emotional cognition and benefit evaluation (R = 0.690), and the weakest correlation was found between emotion influence and benefit evaluation (R = 0.079). These findings provide a basis for measuring the effect of emotion management on training efficiency in the training process of young athletes and offer a theoretical reference for their emotional development while in training.

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The subjective well-being of Chinese college students has always been a topic of concern. Subjective well-being is an overall evaluation of the quality of life according to the standards set by individuals, which is of great significance to the development of college students. Based on the data published in the past 5 years of China's comprehensive social survey, this study uses panel model and adversarial explanatory structure model to analyze the influencing factors of subjective well-being of Chinese college students from five dimensions: social equity attitude, parental education, use of network, social interaction and physical health. The results show that social justice attitude, parents' education, network use, social interaction and physical health have a positive impact on the subjective well-being of Chinese college students. Among them, the use of the network and the education of parents mainly affect the social justice attitude, social interaction attitude, physical health status, and ultimately affect the subjective well-being of college students. Based on the above conclusions, this study proposes strategies to improve the subjective well-being of college students, which has certain reference and guiding significance for educators and decision makers, and has reference significance for developing countries.

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We estimate a dynamic structural model of labor supply, retirement, and informal caregiving to study short and long-term costs of informal caregiving in Germany. Incorporating labor market frictions and the German tax and benefit system, we find that in the absence of Germany's public long-term insurance scheme, informal elderly care has adverse and persistent effects on labor market outcomes and, thus, negatively affects lifetime earnings and future pension benefits. These consequences of caregiving are heterogeneous and depend on age, previous earnings, and institutional regulations. Policy simulations suggest that while public long-term care insurance policies are fiscally costly and induce negative labor market effects, they can largely offset the personal costs of caregiving and increase welfare, especially for low-income individuals.

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Developing a viscoelastic model for the cyclic thermomechanical loading of thermosetting polymers is the main goal of this study. The model includes memory for residual thermal stresses and can consider stress accumulation across many loading cycles. By considering stress accumulation, we can improve predictions and understand how thermosetting polymers' stress-strain state changes under cyclic thermomechanical loading. This approach was validated through experimental verification to ensure its applicability in practical engineering scenarios. The experiment showed that the thermosetting polymer can accumulate stress during cycles of heating and mechanical loading during use. The results of the modeling and experiment are compared. The results have led to corrections in the way this model is applied to thermosetting polymers like the epoxy resin in this study. The corrected results matched well with the experimental measurements of stress under cyclic thermomechanical load, with a difference of only 1 to 6%.

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The current study explores the dynamics of business practices in Pakistan's Small and Medium Enterprises (SMEs). This research focusing on how "green supply chain management" (GSCM), Industry 4.0 technologies (IND), total quality management (TQM) and sustainable performance (SP) are interconnected. The study collected data from 382 SMEs owners and managers and data analysis was conducted utilizing by SPSS and SmartPLS. The results indicate that employ GSCM pattern has constructive impact on SMEs overall performance in terms of their social and financial aspects. Interestingly IND act as intermediaries among GSCM and sustainable performance underscoring their potential to translate sustainability efforts into outcomes. Moreover, our survey reveals that TQM have a crucial function in enriching the relationship between Industry 4.0 technologies and sustainable performance by executing as a moderator. It further highlighting the value of adopting a quality focused approach to maximize the causal factor of advancements on sustainability output. The findings of this survey research offering insights for practitioners, SMEs, and policy makers alike by highlighting the significance of integrating practices such as GSCM, IND and effective quality management to enhance SME efficiency. These outcomes further contribute to an understanding of the mechanics at play, within SMEs while offering guidance for organizations maneuvering the changing landscape of sustainable business practices and IND.

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Serum amyloid A (SAA) is a highly conserved acute-phase protein that plays roles in activating multiple pro-inflammatory pathways during the acute inflammatory response and is commonly used as a biomarker of inflammation. It has been linked to beneficial roles in tissue repair through improved clearance of lipids and cholesterol from sites of damage. In patients with chronic inflammatory diseases, elevated levels of SAA may contribute to increased severity of the underlying condition. The majority of circulating SAA is bound to lipoproteins, primarily high-density lipoprotein (HDL). Interaction with HDL not only stabilizes SAA but also alters its functional properties, likely through altered accessibility of protein-protein interaction sites on SAA. While high-resolution structures for lipid-free, or apo-, forms of SAA have been reported, their relationship with the HDL-bound form of the protein, and with other possible mechanisms of SAA binding to lipids, has not been established. Here, we have used multiple biophysical techniques, including SAXS, TEM, SEC-MALS, native gel electrophoresis, glutaraldehyde crosslinking, and trypsin digestion to characterize the lipid-free and lipid-bound forms of SAA. The SAXS and TEM data show the presence of soluble octamers of SAA with structural similarity to the ring-like structures reported for lipid-free ApoA-I. These SAA octamers represent a previously uncharacterized structure for lipid-free SAA and are capable of scaffolding lipid nanodiscs with similar morphology to those formed by ApoA-I. The SAA-lipid nanodiscs contain four SAA molecules and have similar exterior dimensions as the lipid-free SAA octamer, suggesting that relatively few conformational rearrangements may be required to allow SAA interactions with lipid-containing particles such as HDL. This study suggests a new model for SAA-lipid interactions and provides new insight into how SAA might stabilize protein-lipid nanodiscs or even replace ApoA-I as a scaffold for HDL particles during inflammation.

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The frog-inspired jumping robot is an interesting topic in the field of biomechanics and bionics. However, due to the frog's explosive movement and large range of joint motion, it is very difficult to make their structure completely bionic. To obtain the optimal jumping motion model, the musculoskeletal structure, jumping movement mechanism, and characteristics of frogs are first systematically analyzed, and the corresponding structural and kinematic parameters are obtained. Based on biological characteristics, a model of the articular bone structure is created, which can fully describe the features of frog movement. According to the various factors affecting the frog's jumping movement, mass and constraints are added, and the complex biological joint structure is simplified into four different jumping structure models. The jumping ground reaction force, velocity, and displacement of the center of mass, joint torque, and other motion information of these four models are obtained through ADAMS simulation to reveal the jumping movement mechanism and the influencing factors of frogs. Finally, various motion features are analyzed and compared to determine the optimal structural model of the comprehensive index, which provides a theoretical basis for the design of the frog-inspired jumping robot.

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Objective: To further study the causes of acute occupational poisoning accidents, and to provide scientific basis and decision support for the prevention of accidents in advance. Methods: From September 2022 to May 2023, the literature was searched and 232 cases of acute occupational poisoning cases occurred from 2013 to 2022 were collected. The causal nodes of the accident were determined according to the expert score, and the interpretative structural model (ISM) was used to construct the correlation model between the causal nodes to obtain the hierarchical relationship between the factors. The influence of each causal node on the occurrence of acute occupational poisoning accidents was studied by using Bayesian network (BN), and the relationship and influence among the causal nodes were analyzed by Netica 5.18 software to establish the pre-prevention model of acute occupational poisoning accidents and identify the key causal factors. Results: A total of 23, 203, and 6 cases of significant, large, and medium acute occupational poisoning accidents were included, of which 179, 29, and 24 cases were asphyxiating gas, irritating gas, and mixed gas, respectively. ISM of acute occupational poisoning accidents divided the causal factors into a 7-layer and 3-level hierarchical structure model. Among them, operation conditions, protective measures, ventilation equipment, hidden trouble investigation, emergency management, illegal operation, equipment and facilities, and blind rescue were the direct causes of the occurrence and expansion of accidents. Warning devices, inspection situation, safety education situation, safety operation procedures, and technology in the production process were indirect influences that lead to the occurrence and expansion of accidents. Safety production responsibility system, enterprise supervision and management and government supervision were the deep-rooted influences. BN reasoning showed that the maximum probability causal chain of acute occupational poisoning accidents was as follows: safety production responsibility system→enterprise supervision and management→safety education and training→protective measures→accident occurrence. The key factors leading to the occurrence of acute occupational poisoning accidents were inadequate protective measures, equipment and facility failures, operational errors, ventilation equipment not being used properly and improper emergency management. Conclusion: In the prevention of acute occupational poisoning accidents, it is necessary to correctly use protective measures, test equipment and facilities before operation, operate according to regulations, ensure the normal use of ventilation equipment, and strengthen emergency management, so as to reduce the incidence of acute occupational poisoning accidents.

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Insects utilize seven transmembrane (7TM) odorant receptor (iOR) proteins, with an inverted topology compared to G-protein coupled receptors (GPCRs), to detect chemical cues in the environment. For pest biocontrol, chemical attractants are used to trap insect pests. However, with the influx of invasive insect pests, novel odorants are urgently needed, specifically designed to match 3D iOR structures. Experimental structural determination of these membrane receptors remains challenging and only four experimental iOR structures from two evolutionarily distant organisms have been solved. Template-based modelling (TBM) is a complementary approach, to generate model structures, selecting templates based on sequence identity. As the iOR family is highly divergent, a different template selection approach than sequence identity is needed. Bio-GATS template selection for GPCRs, based on hydrophobicity correspondence, has been morphed into iBio-GATS, for template selection from available experimental iOR structures. This easy-to-use semi-automated workflow has been extended to generate high-quality models from any iOR sequence from the selected template, using Python and shell scripting. This workflow was successfully validated on Apocrypta bakeri Orco and Machilis hrabei OR5 structures. iBio-GATS models generated for the fruit fly iOR, OR59b and Orco, yielded functional ligand binding results concordant with experimental mutagenesis findings, compared to AlphaFold2 models.

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The importance of flexible employment has been highlighted at the policy level in China. In the process of implementing the employment priority strategy, the number of flexible workers in China has exceeded 200 million. Platform-based flexible employment has shown great potentiality in stabilising employment, but as a new form of employment, its employment quality still needs to be improved. Based on the research data, this study identified 14 effective factors influencing the employment quality of platform-based flexible workers and constructed a five-level interpretative structural model (ISM) for the employment quality of platform-based flexible workers. According to the characteristics of different platform types, platform-based flexible employment was divided into business-type and labour-type flexible employment. Then hierarchical logistic regression analysis was conducted on the quality of the two types of flexible workers respectively. The results showed that working hours only had a significant positive effect on the employment quality of business-type flexible workers, while salary and employment injury insurance only had a significant positive effect on the employment quality of labour-type flexible workers. This paper proposed policy recommendations to achieve high-quality employment for flexible workers on different platforms.

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The Hepatitis B Virus (HBV) ribonuclease H (RNase H) although promising remains an unexploited therapeutic target. HBV RNase H inhibition causes premature termination of viral minus-polarity DNA strands, prevents the synthesis of the viral positive-polarity DNA strand, and causes accumulation of RNA:DNA heteroduplexes within viral capsids. As part of our ongoing research to develop more potent anti-HBV RNase H inhibitors, we designed, synthesized and analyzed a library of 18 novel compounds (17 N-hydroyxpyridinedione (HPD) imine derivatives and 1 barbituric acid analogue) as potential leads for HBV treatment development. In cell assays, fourteen HPDs showed significant anti-HBV activity with EC50s from 1.1 to 2.5 µM and selectivity indices (SI) of up to 58. Three of them exhibited more than 3-fold improvement in the SI over the best previous HPD imine (SI = 13). To gain insight to the interaction between the tested compounds and the active site of HBV RNase H, docking experiments were undertaken. In almost all binding poses, the novel HPDs coordinated both active site Mg2+ ions via their oxygen trident. Furthermore, the novel HPDs displayed high cell permeability and solubility as well as good drug-like properties. These results reveal that HPD imines can be significantly active and selective HBV inhibitors, and that the HPD scaffold merits further development towards anti-HBV agents.

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Background: We identified a novel SCN5A variant, E171Q, in a neonate with very frequent ectopy and reduced ejection fraction which normalized after arrhythmia suppression by flecainide. This clinical picture is consistent with multifocal ectopic Purkinje-related premature contractions (MEPPC). Most previous reports of MEPPC have implicated SCN5A variants such as R222Q that neutralize positive charges in the S4 voltage sensor helix of the channel protein NaV1.5 and generate a gating pore current. Methods and Results: E171 is a highly conserved negatively-charged residue located in the S2 transmembrane helix of NaV1.5 domain I. E171 is a key component of the Gating Charge Transfer Center, a region thought to be critical for normal movement of the S4 voltage sensor helix. We used heterologous expression, CRISPR-edited induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), and molecular dynamics simulations to demonstrate that E171Q generates a gating pore current, which was suppressed by a low concentration of flecainide (IC50 = 0.71±0.07 µM). R222Q shifts voltage dependence of activation and inactivation in a negative direction but we observed positive shifts with E171Q. E171Q iPSC-CMs demonstrated abnormal spontaneous activity and prolonged action potentials. Molecular dynamics simulations revealed that both R222Q and E171Q proteins generate a water-filled permeation pathway that underlies generation of the gating pore current. Conclusion: Previously identified MEPPC-associated variants that create gating pore currents are located in positively-charged residues in the S4 voltage sensor and generate negative shifts in the voltage dependence of activation and inactivation. We demonstrate that neutralizing a negatively charged S2 helix residue in the Gating Charge Transfer Center generates positive shifts but also create a gating pore pathway. These findings implicate the gating pore pathway as the primary functional and structural determinant of MEPPC and widen the spectrum of variants that are associated with gating pore-related disease in voltage-gated ion channels.

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The sequence-specific endoribonuclease MazF is widely conserved among prokaryotes. Approximately 20 different MazF cleavage sequences have been discovered, varying from three to seven nucleotides in length. Although MazFs from various prokaryotes were found, the cleavage sequences of most MazFs are unknown. Here, we characterized the conserved MazF of Salmonella enterica subsp. arizonae (MazF-SEA). Using massive parallel sequencing and fluorometric assays, we revealed that MazF-SEA preferentially cleaves the sequences U∧ACG and U∧ACU (∧ represents cleavage sites). In addition, we predicted the 3D structure of MazF-SEA using AlphaFold2 and aligned it with the crystal structure of RNA-bound Bacillus subtilis MazF to evaluate RNA interactions. We found Arg-73 of MazF-SEA interacts with RNAs containing G and U at the third position from the cleavage sites (U∧ACG and U∧ACU). We then obtained the mutated MazF-SEA R73L protein to evaluate the significance of Arg-73 interaction with RNAs containing G and U at this position. We also used fluorometric and kinetic assays and showed the enzymatic activity of MazF-SEA R73L for the sequence UACG and UACU was significantly decreased. These results suggest Arg-73 is essential for recognizing G and U at the third position from the cleavage sites. This is the first study to our knowledge to identify a single residue responsible for RNA recognition by MazF. Owing to its high specificity and ribosome-independence, MazF is useful for RNA cleavage in vitro. These results will likely contribute to increasing the diversity of MazF specificity and to furthering the application of MazF in RNA engineering.

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