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Cryogenic electron tomography (cryoET) is capable of determining in situ biological structures of molecular complexes at near-atomic resolution by averaging half a million subtomograms. While abundant complexes/particles are often clustered in arrays, precisely locating and seamlessly averaging such particles across many tomograms present major challenges. Here, we developed TomoNet, a software package with a modern graphical user interface to carry out the entire pipeline of cryoET and subtomogram averaging to achieve high resolution. TomoNet features built-in automatic particle picking and three-dimensional (3D) classification functions and integrates commonly used packages to streamline high-resolution subtomogram averaging for structures in 1D, 2D, or 3D arrays. Automatic particle picking is accomplished in two complementary ways: one based on template matching and the other using deep learning. TomoNet's hierarchical file organization and visual display facilitate efficient data management as required for large cryoET datasets. Applications of TomoNet to three types of datasets demonstrate its capability of efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures: virus-like particles, bacterial surface layers within cellular lamellae, and membranes decorated with nuclear egress protein complexes. These results demonstrate TomoNet's potential for broad applications to various cryoET projects targeting high-resolution in situ structures.

Obesity-induced lipid overload in cardiomyocytes contributes to profound oxidative stress and cardiomyopathy, culminating in heart failure. In this study, we investigate a novel mechanism whereby lipids accumulate in cardiomyocytes, and seek the relevant treatment strategies. P21-activated kinase 3 (PAK3) was elevated in obese human myocardium, and the murine hearts and cardiomyocytes upon diet- or fatty acid–induced stress, respectively. Mice with cardiac-specific overexpression of PAK3 were more susceptible to the development of cardiac dysfunction upon diet stress, at least partially, because of increased deposition of toxic lipids within the myocardium. Mechanistically, PAK3 promoted the nuclear expression of sterol regulatory element binding protein 1c (SREBP1c) through activation of mammalian target of rapamycin (mTOR) and ribosomal protein S6 kinase β-1 (S6K1) pathway in cardiomyocytes, resulting in abnormal lipid genes profile, accumulation of excessive lipids, and oxidative stress. More importantly, PAK3 knockdown attenuated fatty acid–induced lipotoxicity and cell death in rat and human cardiomyocytes. More importantly, the S6K1 or SREBP1c inhibitor alleviated PAK3-triggered intracellular lipid overload and cardiac dysfunction under obese stress. Collectively, we have demonstrated that PAK3 impairs myocardial lipid homeostasis, while inhibition of cardiac lipotoxicity mitigates cardiac dysfunction. Our study provides a promising therapeutic strategy for ameliorating obesity cardiomyopathy. Article Highlights: Obesity increases the risk of cardiac dysfunction; however, effective treatments remain absent. Here, we investigate an underlying mechanism of obesity cardiomyopathy. We found that PAK3 expression is increased in the myocardium of obese human and mouse models. PAK3 upregulation mediates the nuclear SREBP1c via activation of mTOR and S6K1, resulting in myocardial lipid overload. Inhibition of either PAK3 and S6K1 pathway or SREBP1c prevents lipotoxicity and exerts beneficial effects on cardiomyocyte survival. Pharmacological inhibition of S6K1 and SREBP1c in vivo proved effective in modulating cardiac lipid homeostasis and delaying the progression of obesity cardiomyopathy. [ABSTRACT FROM AUTHOR]

Lactic acid bacteria fermentation is a beneficial bioprocessing method that can improve the flavor, transform nutrients, and maintain the biological activity of foods. The aim of this study is to investigate the effects of Lactiplantibacillus plantarum dy-1 fermentation on the nutritional components, flavor and taste properties, and composition of saponin compounds and their hypolipidemic and antioxidant activities. The results suggested that the total polyphenol content increased, and the soluble polysaccharides and total saponin contents decreased in fermented bitter melon juice (FJ) compared with those in non-fermented bitter melon juice (NFJ). The determination of volatile flavor substances by GC-MS revealed that the response values of acetic acid, n-octanol, sedumol, etc., augmented significantly, and taste analysis with an electronic tongue demonstrated lower bitterness and higher acidity in FJ. Furthermore, UPLC-Q-TOF-MS/MS testing showed a significant decrease in bitter compounds, including momordicines I and II, and a significant increase in the active saponin momordicine U in the fermented bitter melon saponin group (FJBMS). The in vitro assays indicated that FJBMS exhibited similar antioxidant activities as the non-fermented bitter melon saponin group (NFBMS). The in vitro results show that both NFBMS and FJBMS, when used at 50 μg/mL, could significantly reduce fat accumulation and the malondialdehyde (MDA) content and increased the catalase (CAT) activity, while there was no significant difference in the bioactivities of NFBMS and FJBMS. In conclusion, Lactiplantibacillus plantarum dy-1 fermentation is an effective means to lower the bitterness value of bitter melon and preserve the well-known bioactivities of its raw materials, which can improve the edibility of bitter melon. [ABSTRACT FROM AUTHOR]

Backgroundsand Aims. Colorectal cancer (CRC) represents a major global health challenge, necessitating comprehensive investigations into its underlying molecular mechanisms to enhance diagnostic and therapeutic strategies. This study focuses on elucidating the oncogenic role of Membrane‐Associated Ring‐CH‐Type Finger 9 (MARCHF9), a RING‐Type E3 ubiquitin transferase, in CRC. We aim to assess MARCHF9's clinical significance, functional impact on CRC progression, and its potential as a prognostic biomarker. Methods. We leveraged data from the Cancer Genome Atlas (TCGA) cohort to evaluate MARCHF9 expression profiles in CRC. In vitro experiments involved siRNA‐mediated MARCHF9 knockdown in COAD cell lines (SW480 and LoVo). Cell proliferation and invasion assays were conducted to investigate MARCHF9's functional relevance. Survival analyses were performed to assess its prognostic role. Results. Our analysis revealed significantly elevated MARCHF9 expression in CRC tissues compared to normal colorectal tissues (P < 0.05). High MARCHF9 expression correlated with advanced clinical stages, distant metastases, and the presence of residual tumors in CRC patients. Survival analyses demonstrated that high MARCHF9 expression predicted unfavorable overall and disease‐free survival outcomes (P < 0.05). In vitro experiments further supported its oncogenic potential, with MARCHF9 knockdown inhibiting COAD cell proliferation and invasion. Conclusions. This study unveils the oncogenic role of MARCHF9 in CRC, highlighting its clinical relevance as a potential biomarker and therapeutic target. MARCHF9's association with adverse clinicopathological features and its functional impact on cancer cell behavior underscore its significance in CRC progression. Further research is essential to elucidate precise mechanisms by which MARCHF9 enhances tumorigenesis and to explore its therapeutic potential in CRC management. [ABSTRACT FROM AUTHOR]

Arabinoxylans (AXs) are non-starch polysaccharides with complex structures naturally occurring in grains (i.e., barley, corn, and others), providing many health benefits, especially as prebiotics. AXs can be classified as water-extractable (WEAX) and water-unextractable (WUAX) based on their solubility, with properties influenced by grain sources and extraction methods. Numerous studies show that AXs exert an important health impact, including glucose and lipid metabolism regulation and immune system enhancement, which is induced by the interactions between AXs and the gut microbiota. Recent research underscores the dependence of AX physiological effects on structure, advocating for a deeper understanding of structure-activity relationships. While systematic studies on WEAX are prevalent, knowledge gaps persist regarding WUAX, despite its higher grain abundance. Thus, this review reports recent data on WUAX structural properties (chemical structure, branching, and MW) in cereals under different treatments. It discusses WUAX applications in baking and the benefits deriving from gut fermentation. [ABSTRACT FROM AUTHOR]

Noodles are popular staple foods globally, and dried noodle products (DNPs) have gained increasing attention due to recent changes in consumer diet behavior. Rapid rehydration and excellent texture quality are the two major demands consumers make of dried noodle products. Unfortunately, these two qualities conflict with each other: the rapid rehydration of DNPs generally requires a loose structure, which is disadvantageous for good texture qualities. This contradiction limits further development of the noodle industry, and overcoming this limitation remains challenging. Starch is the major component of noodles, and it has two main roles in DNPs. It serves as a skeleton for the noodle in gel networks form or acts as a noodle network filler in granule form. In this review, we comprehensively investigate the different roles of starch in DNPs, and propose strategies for balancing the conflicts between texture and rehydration qualities of DNPs by regulating the gel network and granule structure of starch. Current strategies in regulating the gel network mainly focused on the hydrogen bond strength, the orientation degree, and the porosity; while regulating granule structure was generally performed by adjusting the integrity and the gelatinization degree of starch. This review assists in the production of instant dried noodle products with desired qualities, and provides insights into promising enhancements in the quality of starch-based products by manipulating starch structure. [ABSTRACT FROM AUTHOR]

The 21st century is an era of rapid development of high-tech industry. Through continuous collection and sharing of data, IoT technology connected by things has penetrated into every aspect of human life. Modern organizations find that they increasingly rely on knowledge and information sharing and interconnection to enhance their innovation and development capabilities. Therefore, this paper studies the strategic decision-making of knowledge sharing among employees on the IoT platform drawing on evolutionary game theory, this paper constructs a three-party game model composed of "organization-knowledge sharers-knowledge seekers" from the perspective of stakeholders, and discusses the strategic choice of organization and employee behavior under the dynamic decision mechanism and when the game reaches equilibrium and stability. Moreover, this paper uses MATLAB 2016a to simulate the model. The results show that under the premise of higher organizational rewards, synergistic benefits, high-shared extra income, knowledge-sharing preferences, incentive preferences of the organization, the system is easier to reach the ideal state. With the smaller cost of sharing and incentive, organization and employees are more willing to be motivators and sharers, while the incentive degree of organization should be controlled within a reasonable range. This paper can provide specific theoretical and practical guidance for the practice of organizational knowledge management. [ABSTRACT FROM AUTHOR]

In this paper, we explore the trade-offs between public and private investment in autonomous driving technologies. Utilizing an evolutionary game model, we delve into the complex interaction mechanisms between governments and auto manufacturers, focusing on how strategic decisions impact overall outcomes. Specifically, we predict that governments may opt for strategies such as constructing and maintaining infrastructure for Roadside Infrastructure-based Vehicles (RIVs) or subsidizing high-level Autonomous Driving Vehicles (ADVs) without additional road infrastructure. Manufacturers' choices involve deciding whether to invest in RIVs or ADVs, depending on governmental policies and market conditions. Our simulation results, based on scenarios derived from existing economic data and forecasts on technology development costs, suggest that government subsidy policies need to dynamically adjust in response to manufacturers' shifting strategies and market behavior. This dynamic adjustment is crucial as it addresses the evolving economic environment and technological advancements, ensuring that subsidies effectively incentivize the desired outcomes in autonomous vehicle development. The findings of this paper could serve as valuable decision-making tools for governments and auto manufacturers, guiding investment strategies that align with the dynamic landscape of autonomous driving technology. [ABSTRACT FROM AUTHOR]

2-(3-Bromophenyl)-1-(4-morpholinyl)ethanone belongs to one of morpholine derivatives. In this paper, 2-(3-bromophenyl)-1-(4-morpholinyl)ethanone was synthesized by a two-step synthesis method. In order to determine the structure of the target compound, FT-IR,1H NMR,13C NMR and MS were used for detection. Meanwhile, X-ray diffraction was used to detect the single crystal and obtain the crystal structure data of the target compound. The molecular crystal structure was compared with that determined by density functional theory. The frontier molecular orbitals and molecular electrostatic potential energy were used to further study the physical properties of the compounds. [ABSTRACT FROM AUTHOR]

Background: There is no unified scope for regional lymph node (LN) dissection in patients with pancreatic ductal adenocarcinoma (PDAC). Incomplete regional LN dissection can lead to postoperative recurrence, while blind expansion of the scope of regional LN dissection significantly increases the perioperative risk without significantly prolonging overall survival. We aimed to establish a noninvasive visualization tool based on dual-layer detector spectral computed tomography (DLCT) to predict the probability of regional LN metastasis in patients with PDAC., Methods: A total of 163 regional LNs were reviewed and divided into a metastatic cohort (n=58 LNs) and nonmetastatic cohort (n=105 LNs). The DLCT quantitative parameters and the nodal ratio of the longest axis to the shortest axis (L/S) of the regional LNs were compared between the two cohorts. The DLCT quantitative parameters included the iodine concentration in the arterial phase (APIC), normalized iodine concentration in the arterial phase (APNIC), effective atomic number in the arterial phase (APZeff), normalized effective atomic number in the arterial phase (APNZeff), slope of the spectral attenuation curves in the arterial phase (APλHU), iodine concentration in the portal venous phase (PVPIC), normalized iodine concentration in the portal venous phase (PVPNIC), effective atomic number in the portal venous phase (PVPZeff), normalized effective atomic number in the portal venous phase (PVPNZeff), and slope of the spectral attenuation curves in the portal venous phase (PVPλHU). Logistic regression analysis based on area under the curve (AUC) was used to analyze the diagnostic performance of significant DLCT quantitative parameters, L/S, and the models combining significant DLCT quantitative parameters and L/S. A nomogram based on the models with highest diagnostic performance was developed as a predictor. The goodness of fit and clinical applicability of the nomogram were assessed through calibration curve and decision curve analysis (DCA)., Results: The combined model of APNIC + L/S (APNIC + L/S) had the highest diagnostic performance among all models, yielding an AUC, sensitivity, and specificity of 0.878 [95% confidence interval (CI): 0.825-0.931], 0.707, and 0.886, respectively. The calibration curve indicated that the APNIC-L/S nomogram had good agreement between the predicted probability and the actual probability. Meanwhile, the decision curve indicated that the APNIC-L/S nomogram could produce a greater net benefit than could the all- or-no-intervention strategy, with threshold probabilities ranging from 0.0 to 0.75., Conclusions: As a valid and visual noninvasive prediction tool, the APNIC-L/S nomogram demonstrated favorable predictive efficacy for identifying metastatic LNs in patients with PDAC., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-1624/coif). The authors have no conflicts of interest to declare., (2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Background: Thyroid nodules (TNs) cytologically defined as category Bethesda III and IV pose a major diagnostic challenge before surgery, demanding new methods to reduce unnecessary diagnostic thyroid lobectomies for patients with benign TNs. This study aimed to assess whether a model combining dual-energy computed tomography (DECT) quantitative parameters with morphologic features could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs., Methods: Data from 77 patients scheduled for thyroid surgery for Bethesda III and IV TNs (malignant =48; benign =29) who underwent DECT scans were reviewed. DECT quantitative parameters including normalized iodine concentration (NIC), attenuation on the slope of spectral Hounsfield unit (HU) curve, and normalized effective atomic number (Zeff) were measured in the arterial phase (AP) and venous phase (VP). DECT quantitative parameters and morphologic features were compared between the malignant and benign cohorts. The receiver operating characteristic curve was performed to compare the performances of significant DECT quantitative parameters, morphologic features, or the models combining the DECT parameters, respectively, with morphologic features. A nomogram was constructed from the optimal performance model, and the performance was evaluated via the calibration curve and decision curve analysis., Results: The areas under the receiver operating characteristic curve with 95% confidence interval (CI) of the NIC in the AP (AP-NIC), slope of spectral HU curve in the AP, and NZeff in the AP were 0.749 (95% CI: 0.641-0.857), 0.654 (95% CI: 0.530-0.778), and 0.722 (95% CI: 0.602-0.842), respectively. The model combining AP-NIC with enhanced blurring showed the highest diagnostic performance, with an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of 0.808, 0.854, and 0.655, respectively; it was then used to construct a nomogram. The calibration curve showed that the discrepancy between the prediction of the nomogram and actual observations was less than 5%. The decision curve analysis indicated the nomogram had a positive net benefit in threshold risk ranges of 14% to 58% or 60% to 91% for malignant Bethesda III and IV TNs., Conclusions: The model combining AP-NIC with enhanced blurring could reliably differentiate between benign and malignant lesions in Bethesda III and IV TNs., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-1511/coif). The authors have no conflicts of interest to declare., (2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Cryogenic electron tomography (cryoET) is capable of determining in situ biological structures of molecular complexes at near-atomic resolution by averaging half a million subtomograms. While abundant complexes/particles are often clustered in arrays, precisely locating and seamlessly averaging such particles across many tomograms present major challenges. Here, we developed TomoNet, a software package with a modern graphical user interface to carry out the entire pipeline of cryoET and subtomogram averaging to achieve high resolution. TomoNet features built-in automatic particle picking and three-dimensional (3D) classification functions and integrates commonly used packages to streamline high-resolution subtomogram averaging for structures in 1D, 2D, or 3D arrays. Automatic particle picking is accomplished in two complementary ways: one based on template matching and the other using deep learning. TomoNet's hierarchical file organization and visual display facilitate efficient data management as required for large cryoET datasets. Applications of TomoNet to three types of datasets demonstrate its capability of efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures: virus-like particles, bacterial surface layers within cellular lamellae, and membranes decorated with nuclear egress protein complexes. These results demonstrate TomoNet's potential for broad applications to various cryoET projects targeting high-resolution in situ structures., Competing Interests: The authors declare none., (© The Author(s) 2024.)