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Abstract Our recent studies have identified p21-activated kinase 4 (PAK4) as a key regulator of lipid catabolism in the liver and adipose tissue, but its role in glucose homeostasis in skeletal muscle remains to be explored. In this study, we find that PAK4 levels are highly upregulated in the skeletal muscles of diabetic humans and mice. Skeletal muscle-specific Pak4 ablation or administering the PAK4 inhibitor in diet-induced obese mice retains insulin sensitivity, accompanied by AMPK activation and GLUT4 upregulation. We demonstrate that PAK4 promotes insulin resistance by phosphorylating AMPKα2 at Ser491, thereby inhibiting AMPK activity. We additionally show that skeletal muscle-specific expression of a phospho-mimetic mutant AMPKα2S491D impairs glucose tolerance, while the phospho-inactive mutant AMPKα2S491A improves it. In summary, our findings suggest that targeting skeletal muscle PAK4 may offer a therapeutic avenue for type 2 diabetes.

This study aimed to analyze whether the coronavirus disease 2019 (COVID-19) pandemic affected the characteristics of first-visit patients with peripheral facial palsy (PFP) and observe changes in their characteristics. This study analyzed the electronic medical records of 2,310 first-visit patients with PFP who visited the Facial Palsy Center, Kyung Hee University Korean Medicine Hospital from January 1, 2019, to December 31, 2021, in terms of demographic characteristics, disease phase, residence locations, hospital visit route, and patient care. During COVID-19, the proportion of acute patients increased by 5.3%, the proportion of visits by residents in Seoul increased by 3.8%, and the proportion of patients receiving only outpatient treatments increased by 12.8%. Significant relationships were present between the presence of the COVID-19 pandemic and the number of patients by disease phase (p = 0.043), residence locations (p = 0.003), and patient care (p = 0.003). Thus, several differences in the characteristics of first-visit patients with PFP visiting a Korean medicine hospital during the COVID-19 pandemic in terms of demographic characteristics, disease phase, residence locations, and patient care.

Abstract Background Transmembrane 4 L six family member 5 (TM4SF5) translocates subcellularly and functions metabolically, although it is unclear how intracellular TM4SF5 translocation is linked to metabolic contexts. It is thus of interests to understand how the traffic dynamics of TM4SF5 to subcellular endosomal membranes are correlated to regulatory roles of metabolisms. Methods Here, we explored the metabolic significance of TM4SF5 localization at mitochondria‐lysosome contact sites (MLCSs), using in vitro cells and in vivo animal systems, via approaches by immunofluorescence, proximity labelling based proteomics analysis, organelle reconstitution etc. Results Upon extracellular glucose repletion following depletion, TM4SF5 became enriched at MLCSs via an interaction between mitochondrial FK506‐binding protein 8 (FKBP8) and lysosomal TM4SF5. Proximity labeling showed molecular clustering of phospho‐dynamic‐related protein I (DRP1) and certain mitophagy receptors at TM4SF5‐enriched MLCSs, leading to mitochondrial fission and autophagy. TM4SF5 bound NPC intracellular cholesterol transporter 1 (NPC1) and free cholesterol, and mediated export of lysosomal cholesterol to mitochondria, leading to impaired oxidative phosphorylation but intact tricarboxylic acid (TCA) cycle and β‐oxidation. In mouse models, hepatocyte Tm4sf5 promoted mitophagy and cholesterol transport to mitochondria, both with positive relations to liver malignancy. Conclusions Our findings suggested that TM4SF5‐enriched MLCSs regulate glucose catabolism by facilitating cholesterol export for mitochondrial reprogramming, presumably while hepatocellular carcinogenesis, recapitulating aspects for hepatocellular carcinoma metabolism with mitochondrial reprogramming to support biomolecule synthesis in addition to glycolytic energetics.

Background: Researchers have noted that the advent of artificial intelligence (AI) heralds a promising era, with potential to significantly enhance diagnostic and predictive abilities in clinical settings. The aim of this meta-analysis is to evaluate the discrepancies in identifying anatomical landmarks between AI and manual approaches. Methods: A comprehensive search strategy was employed, incorporating controlled vocabulary (MeSH) and free-text terms. This search was conducted by two reviewers to identify published systematic reviews. Three major electronic databases, namely, Medline via PubMed, the Cochrane database, and Embase, were searched up to May 2024. Results: Initially, 369 articles were identified. After conducting a comprehensive search and applying strict inclusion criteria, a total of ten studies were deemed eligible for inclusion in the meta-analysis. The results showed that the average difference in detecting anatomical landmarks between artificial intelligence and manual approaches was 0.35, with a 95% confidence interval (CI) ranging from −0.09 to 0.78. Additionally, the overall effect between the two groups was found to be insignificant. Upon further analysis of the subgroup of cephalometric radiographs, it was determined that there were no significant differences between the two groups in terms of detecting anatomical landmarks. Similarly, the subgroup of cone-beam computed tomography (CBCT) revealed no significant differences between the groups. Conclusions: In summary, the study concluded that the use of artificial intelligence is just as effective as the manual approach when it comes to detecting anatomical landmarks, both in general and in specific contexts such as cephalometric radiographs and CBCT evaluations.

Abstract Background Malignant glioma is among the most lethal and frequently occurring brain tumors, and the average survival period is 15 months. Existing chemotherapy has low tolerance and low blood-brain barrier (BBB) permeability; therefore, the required drug dose cannot be accurately delivered to the tumor site, resulting in an insufficient drug effect. Methods Herein, we demonstrate a precision photodynamic tumor therapy using a photosensitizer (ZnPcS) capable of binding to albumin in situ, which can increase the permeability of the BBB and accurately target glioma. Albumin-binding ZnPcS was designed to pass through the BBB and bind to secreted protein acidic and rich in cysteine (SPARC), which is abundant in the glioma plasma membrane. Results When the upper part of a mouse brain was irradiated using a laser (0.2 W cm− 2) after transplantation of glioma and injection of ZnPcS, tumor growth was inhibited by approximately 83.6%, and the 50% survival rate of the treatment group increased by 14 days compared to the control group. In glioma with knockout SPARC, the amount of ZnPcS entering the glioma was reduced by 63.1%, indicating that it can target glioma through the SPARC pathway. Conclusion This study showed that the use of albumin-binding photosensitizers is promising for the treatment of malignant gliomas. Graphical Abstract

The preparation of raw images for subsequent analysis, known as image preprocessing, is a crucial step that can boost the performance of an image classification model. Although deep learning has succeeded in image classification without handcrafted features, certain studies underscore the continued significance of image preprocessing for enhanced performance during the training process. Nonetheless, this task is often demanding and requires high-quality images to effectively train a classification model. The quality of training images, along with other factors, impacts the classification model’s performance and insufficient image quality can lead to suboptimal classification performance. On the other hand, achieving high-quality training images requires effective image preprocessing techniques. In this study, we perform exploratory experiments aimed at improving a classification model of unexposed potsherd cavities images via image preprocessing pipelines. These pipelines are evaluated on two distinct image sets: a laboratory-made, experimental image set that contains archaeological images with controlled lighting and background conditions, and a Jōmon–Yayoi image set that contains images of real-world potteries from the Jōmon period through the Yayoi period with varying conditions. The best accuracy performances obtained on the experimental images and the more challenging Jōmon–Yayoi images are 90.48% and 78.13%, respectively. The comprehensive analysis and experimentation conducted in this study demonstrate a noteworthy enhancement in performance metrics compared to the established baseline benchmark.

ABSTRACT In plant-pathogen interactions, oxidative bursts are crucial for plants to defend themselves against pathogen infections. Rapid production and accumulation of reactive oxygen species kill pathogens directly and cause local cell death, preventing pathogens from spreading to adjacent cells. Meanwhile, the pathogens have developed several mechanisms to tolerate oxidative stress and successfully colonize plant tissues. In this study, we investigated the mechanisms responsible for resistance to oxidative stress by analyzing the transcriptomes of six oxidative stress-sensitive strains of the plant pathogenic fungus Fusarium graminearum. Weighted gene co-expression network analysis identified several pathways related to oxidative stress responses, including the DNA repair system, autophagy, and ubiquitin-mediated proteolysis. We also identified hub genes with high intramodular connectivity in key modules and generated deletion or conditional suppression mutants. Phenotypic characterization of those mutants showed that the deletion of FgHGG4, FgHGG10, and FgHGG13 caused sensitivity to oxidative stress, and further investigation on those genes revealed that transcriptional elongation and DNA damage responses play roles in oxidative stress response and pathogenicity. The suppression of FgHGL7 also led to hypersensitivity to oxidative stress, and we demonstrated that FgHGL7 plays a crucial role in heme biosynthesis and is essential for peroxidase activity. This study increases the understanding of the adaptive mechanisms to cope with oxidative stress in plant pathogenic fungi. IMPORTANCE Fungal pathogens have evolved various mechanisms to overcome host-derived stresses for successful infection. Oxidative stress is a representative defense system induced by the host plant, and fungi have complex response systems to cope with it. Fusarium graminearum is one of the devastating plant pathogenic fungi, and understanding its pathosystem is crucial for disease control. In this study, we investigated adaptive mechanisms for coping with oxidative stress at the transcriptome level using oxidative stress-sensitive strains. In addition, by introducing genetic modification technique such as CRISPR-Cas9 and the conditional gene expression system, we identified pathways/genes required for resistance to oxidative stress and also for virulence. Overall, this study advances the understanding of the oxidative stress response and related mechanisms in plant pathogenic fungi.

Humans are exposed to the common carcinogen benzo[a]pyrene (BaP) by ingesting contaminated foods and water or inhaling polluted air. Given the enriched lipids and reduced antioxidative properties in the brain and the accumulation of BaP in the brain due to its high lipophilicity, the brain is susceptible to BaP-induced toxicity. Exposure to BaP leads to impairments in learning and memory, increased anxiety behavior, and neuronal death. It induces protein dysfunctions in neuronal compartments that play essential roles in neuronal activity or physiology. However, the neurotoxicity of BaP on presynaptic terminals, which is crucial to neurotransmission by releasing synaptic vesicles that contain neurotransmitters, has not yet been investigated. In the present study, we investigated the toxicity of BaP at presynaptic terminals in living hippocampal neurons. These neurons were sourced from transgenic mice pups (postnatal 1-day, a total of 12 pups, equal numbers for each sex) that endogenously express synaptic vesicle-fused pHluorin, which is a green fluorescent protein that enables monitoring of synaptic vesicle dynamics. We observed that BaP suppressed synaptic vesicle exocytosis by inhibiting presynaptic Ca2+ entry via P/Q-type Ca2+ channels. Together with molecular docking simulation, we speculate that BaP and metabolites may bind to the P/Q Ca2+ channels. These results suggest the toxic mechanism of BaP exposure-induced abnormal behavior that provides a basis to evaluate the risk assessment of BaP-induced neurotoxicity.

Purinergic receptors are membrane proteins that regulate numerous cellular functions by catalyzing reactions involving purine nucleotides or nucleosides. Among the three receptor families, i.e., P1, P2X, and P2Y, the P1 and P2Y receptors share common structural features of class A GPCR. Comprehensive sequence and structural analysis revealed that the P1 and P2Y receptors belong to two distinct groups. They exhibit different ligand-binding site features that can distinguish between specific activators. These specific amino acid residues in the binding cavity may be involved in the selectivity and unique pharmacological behavior of each subtype. In this study, we conducted a structure-based analysis of purinergic P1 and P2Y receptors to identify their evolutionary signature and obtain structural insights into ligand recognition and selectivity. The structural features of the P1 and P2Y receptor classes were compared based on sequence conservation and ligand interaction patterns. Orthologous protein sequences were collected for the P1 and P2Y receptors, and sequence conservation was calculated based on Shannon entropy to identify highly conserved residues. To analyze the ligand interaction patterns, we performed docking studies on the P1 and P2Y receptors using known ligand information extracted from the ChEMBL database. We analyzed how the conserved residues are related to ligand-binding sites and how the key interacting residues differ between P1 and P2Y receptors, or between agonists and antagonists. We extracted new similarities and differences between the receptor subtypes, and the results can be used for designing new ligands by predicting hotspot residues that are important for functional selectivity.

Fusion devices like tokamaks require plasma current to generate magnetic field for plasma confinement. Here the authors report an observation of a self-generated anomalous current that contributes up to 30% of the total current in the fusion plasma at KSTAR.

Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical industry and research, where it has been utilized to efficiently identify new chemical entities with desirable properties. The application of AI algorithms to drug discovery presents both remarkable opportunities and challenges. This review article focuses on the transformative role of AI in medicinal chemistry. We delve into the applications of machine learning and deep learning techniques in drug screening and design, discussing their potential to expedite the early drug discovery process. In particular, we provide a comprehensive overview of the use of AI algorithms in predicting protein structures, drug–target interactions, and molecular properties such as drug toxicity. While AI has accelerated the drug discovery process, data quality issues and technological constraints remain challenges. Nonetheless, new relationships and methods have been unveiled, demonstrating AI’s expanding potential in predicting and understanding drug interactions and properties. For its full potential to be realized, interdisciplinary collaboration is essential. This review underscores AI’s growing influence on the future trajectory of medicinal chemistry and stresses the importance of ongoing synergies between computational and domain experts.

The dissemination of edge devices drives new requirements for security primitives for privacy protection and chip authentication. Memristors are promising entropy sources for realizing hardware‐based security primitives due to their intrinsic randomness and stochastic properties. With the adoption of memristors among several technologies that meet essential requirements, the neural network physically unclonable function (NNPUF) is proposed, a novel PUF design that takes advantage of deep learning algorithms. The proposed design integrated with the memristor array can be constructed easily because the system does not depend on write operation accuracy. To contemplate a nondifferentiable module during training, an original concept of loss called PUF loss is devised. Iterations of weight update with the loss function bring about optimal NNPUF performance. It is shown that the design achieves a near‐ideal 50% average value for security metrics, including uniformity, diffuseness, and uniqueness. This means that the NNPUF satisfies practical quality standards for security primitives by training with PUF loss. It is also demonstrated that the NNPUF response has an unassailable resistance against deep learning‐based modeling attacks, which is verified by the near‐50% prediction model accuracy.

Adenosine mediates various physiological activities in the body. Adenosine receptors (ARs) are widely expressed in tumors and the tumor microenvironment (TME), and they induce tumor proliferation and suppress immune cell function. There are four types of human adenosine receptor (hARs): hA1, hA2A, hA2B, and hA3. Both hA1 and hA3 AR play an important role in tumor proliferation. We designed and synthesized novel 1,3,5-triazine derivatives through amination and Suzuki coupling, and evaluated them for binding affinities to each hAR subtype. Compounds 9a and 11b showed good binding affinity to both hA1 and hA3 AR, while 9c showed the highest binding affinity to hA1 AR. In this study, we discovered that 9c inhibits cell viability, leading to cell death in lung cancer cell lines. Flow cytometry analysis revealed that 9c caused an increase in intracellular reactive oxygen species (ROS) and a depolarization of the mitochondrial membrane potential. The binding mode of 1,3,5-triazine derivatives to hA1 and hA3 AR were predicted by a molecular docking study.

Background. Little information is available on the association between parents’ metabolic syndrome (MetS) and adolescent offspring’s obesity in Korea. The aim of our study is to determine the association between parent’s metabolic syndrome and offspring’s obesity. Methods. The study data were obtained from the Korean National Health and Nutrition Examination Survey conducted during 2009–2016. In the present study, 3140 adolescents aged 12 to 18 years, their paternal pairs (PP, fathers = 2244), and maternal pairs (MP, mothers = 3022) were analyzed. Of these 3140 adolescents, 2637 had normal weight {age- and sex-specific body mass index (BMI) under the 85th percentile}, whereas 467 were overweight (age- and sex-specific BMI over the 85th percentile). Results. Offspring’s overweight and central obesity were associated with all components of the PP’s metabolic risk factors, including central obesity (p

The new advances in deep learning methods have influenced many aspects of scientific research, including the study of the protein system. The prediction of proteins’ 3D structural components is now heavily dependent on machine learning techniques that interpret how protein sequences and their homology govern the inter-residue contacts and structural organization. Especially, methods employing deep neural networks have had a significant impact on recent CASP13 and CASP14 competition. Here, we explore the recent applications of deep learning methods in the protein structure prediction area. We also look at the potential opportunities for deep learning methods to identify unknown protein structures and functions to be discovered and help guide drug–target interactions. Although significant problems still need to be addressed, we expect these techniques in the near future to play crucial roles in protein structural bioinformatics as well as in drug discovery.

Fusarium graminearum is an important fungal plant pathogen that causes serious losses in cereal crop yields and mycotoxicoses in humans and livestock. In this study, we characterized an insertion mutant, Z39R9282, with pleiotropic defects in sexual development and virulence. We determined that the insertion occurred in a gene encoding an ortholog of yeast elongator complex protein 3 (ELP3). Deletion of elp3 led to significant defects in sexual and asexual development in F. graminearum. In the elp3 deletion mutant, the number of perithecia formed was reduced and maturation of perithecia was delayed. This mutant also produced morphologically abnormal ascospores and conidia. Histone acetylation in the elp3 deletion mutant was reduced compared with the wild type, which likely caused the developmental defects. Trichothecenes were not produced at detectable levels, and expression of trichothecene biosynthesis genes were significantly reduced in the elp3 deletion mutant. Infection of wheat heads revealed that the elp3 deletion mutant was unable to spread from inoculated florets to neighboring spikelets. Furthermore, the elp3 deletion mutant was more sensitive to oxidative stress than the wild type, and the expression of putative catalase genes was reduced. We demonstrate that elp3 functions in sexual and asexual development, virulence, and the oxidative stress response of F. graminearum by regulating the expression of genes involved in these various developmental processes.

Fusarium head blight (FHB) caused by infection with Fusarium graminearum leads to enormous losses to crop growers, and may contaminate grains with a number of Fusarium mycotoxins that pose serious risks to human and animal health. Antagonistic bacteria that are used to prevent FHB offer attractive alternatives or supplements to synthetic fungicides for controlling FHB without the negative effects of chemical management. Out of 500 bacterial strains isolated from soil, Bacillus amyloliquefaciens JCK-12 showed strong antifungal activity and was considered a potential source for control strategies to reduce FHB. B. amyloliquefaciens JCK-12 produces several cyclic lipopeptides (CLPs) including iturin A, fengycin, and surfactin. Iturin A inhibits spore germination of F. graminearum. Fengycin or surfactin alone did not display any inhibitory activity against spore germination at concentrations less than 30 μg/ml, but a mixture of iturin A, fengycin, and surfactin showed a remarkable synergistic inhibitory effect on F. graminearum spore germination. The fermentation broth and formulation of B. amyloliquefaciens JCK-12 strain reduced the disease incidence of FHB in wheat. Furthermore, co-application of B. amyloliquefaciens JCK-12 and chemical fungicides resulted in synergistic in vitro antifungal effects and significant disease control efficacy against FHB under greenhouse and field conditions, suggesting that B. amyloliquefaciens JCK-12 has a strong chemosensitizing effect. The synergistic antifungal effect of B. amyloliquefaciens JCK-12 and chemical fungicides in combination may result from the cell wall damage and altered cell membrane permeability in the phytopathogenic fungi caused by the CLP mixtures and subsequent increased sensitivity of F. graminearum to fungicides. In addition, B. amyloliquefaciens JCK-12 showed the potential to reduce trichothecenes mycotoxin production. The results of this study indicate that B. amyloliquefaciens JCK-12 could be used as an available biocontrol agent or as a chemosensitizer to chemical fungicides for controlling FHB disease and as a strategy for preventing the contamination of harvested crops with mycotoxins.

Transcriptome analysis is a widely used approach to study the molecular mechanisms underlying development and the responses of fungi to environmental cues. However, it is difficult to obtain cells with a homogeneous status from the sexually-induced culture of the plant pathogenic fungus Fusarium graminearum. In this study, we provided phenotypic and genetic evidence to show that the current conditions applied for perithecia induction inevitably highly induced asexual sporulation in this fungus. We also found that hundreds of genes under the control of the conidiation-specific gene ABAA were unnecessarily upregulated after perithecia induction. Deletion of ABAA specifically blocked conidia production in both the wild-type strain and sexually-defective mutants during sexual development. Taken together, our results suggest that the abaA strain could be used as a background strain for studies of the initial stages of perithecia production in F. graminearum. Further comparative transcriptome analysis between the abaA mutant and the sexually-defective transcription factor mutant carrying the ABAA deletion would contribute to the construction of the genetic networks involved in perithecia development in F. graminearum.

Dynamics and functions of G-protein coupled receptors (GPCRs) are accurately regulated by the type of ligands that bind to the orthosteric or allosteric binding sites. To glean the structural and dynamical origin of ligand-dependent modulation of GPCR activity, we performed total ~ 5 μsec molecular dynamics simulations of A2A adenosine receptor (A2AAR) in its apo, antagonist-bound, and agonist-bound forms in an explicit water and membrane environment, and examined the corresponding dynamics and correlation between the 10 key structural motifs that serve as the allosteric hotspots in intramolecular signaling network. We dubbed these 10 structural motifs "binary switches" as they display molecular interactions that switch between two distinct states. By projecting the receptor dynamics on these binary switches that yield 2(10) microstates, we show that (i) the receptors in apo, antagonist-bound, and agonist-bound states explore vastly different conformational space; (ii) among the three receptor states the apo state explores the broadest range of microstates; (iii) in the presence of the agonist, the active conformation is maintained through coherent couplings among the binary switches; and (iv) to be most specific, our analysis shows that W246, located deep inside the binding cleft, can serve as both an agonist sensor and actuator of ensuing intramolecular signaling for the receptor activation. Finally, our analysis of multiple trajectories generated by inserting an agonist to the apo state underscores that the transition of the receptor from inactive to active form requires the disruption of ionic-lock in the DRY motif.