MicroRNA­mediated regulation of muscular atrophy: Exploring molecular pathways and therapeutics (Review).

Muscular atrophy, which results in loss of muscle mass and strength, is a significant concern for patients with various diseases. It is crucial to comprehend the molecular mechanisms underlying this condition to devise targeted treatments. MicroRNAs (miRNAs) have emerged as key regulators of gene expression, serving vital roles in numerous cellular processes, including the maintenance of muscle stability. An intricate network of miRNAs finely regulates gene expression, influencing pathways related to muscle protein production, and muscle breakdown and regeneration. Dysregulation of specific miRNAs has been linked to the development of muscular atrophy, affecting important signaling pathways including the protein kinase B/mTOR and ubiquitin­proteasome systems. The present review summarizes recent work on miRNA patterns associated with muscular atrophy under various physiological and pathological conditions, elucidating its intricate regulatory networks. In conclusion, the present review lays a foundation for the development of novel treatment options for individuals affected by muscular atrophy, and explores other regulatory pathways, such as autophagy and inflammatory signaling, to ensure a comprehensive overview of the multifarious nature of muscular atrophy. The objective of the present review was to elucidate the complex molecular pathways involved in muscular atrophy, and to facilitate the development of innovative and specific therapeutic strategies for the prevention or reversal of muscular atrophy in diverse clinical scenarios.

Neuron pruning in temporal domain for energy efficient SNN processor design.

Recently, the accuracy of spike neural network (SNN) has been significantly improved by deploying convolutional neural networks (CNN) and their parameters to SNN. The deep convolutional SNNs, however, suffer from large amounts of computations, which is the major bottleneck for energy efficient SNN processor design. In this paper, we present an input-dependent computation reduction approach, where relatively unimportant neurons are identified and pruned without seriously sacrificing the accuracies. Specifically, a neuron pruning in temporal domain is proposed that prunes less important neurons and skips its future operations based on the layer-wise pruning thresholds of membrane voltages. To find the pruning thresholds, two pruning threshold search algorithms are presented that can efficiently trade-off accuracy and computational complexity with a given computation reduction ratio. The proposed neuron pruning scheme has been implemented using 65 nm CMOS process. The SNN processor achieves a 57% energy reduction and a 2.68× speed up, with up to 0.82% accuracy loss and 7.3% area overhead for CIFAR-10 dataset.

AXL is required for hypoxia-mediated hypoxia-inducible factor-1 alpha function in glioblastoma.

Glioblastoma (GBM) is the most aggressive type of central nervous system tumor. Molecular targeting may be important when developing efficient GBM treatment strategies. Sequencing of GBMs revealed that the receptor tyrosine kinase (RTK)/RAS/phosphatidylinositol-3-kinase pathway was altered in 88% of samples. Interestingly, AXL, a member of RTK, was proposed as a promising target in glioma therapy. However, the molecular mechanism of AXL modulation of GBM genesis and proliferation is still unclear. In this study, we investigated the expression and localization of hypoxia-inducible factor-1 alpha (HIF-1α) by AXL in GBM. Both AXL mRNA and protein are overexpressed in GBM. Short-interfering RNA knockdown of AXL in U251-MG cells reduced viability and migration. However, serum withdrawal reduced AXL expression, abolishing the effect on viability. AXL is also involved in hypoxia regulation. In hypoxic conditions, the reduction of AXL decreased the level and nuclear localization of HIF-1α. The co-expression of HIF-1α and AXL was found in human GBM samples but not normal tissue. This finding suggests a mechanism for GBM proliferation and indicates that targeting AXL may be a potential GBM therapeutic. Supplementary Information: The online version contains supplementary material available at 10.1007/s43188-023-00195-z.

Exploring scavenger receptor class F member 2 and the importance of scavenger receptor family in prediagnostic diseases.

Scavenger Receptor Class F Member 2 (SCARF2), also known as the Type F Scavenger Receptor Family gene, encodes for Scavenger Receptor Expressed by Endothelial Cells 2 (SREC-II). This protein is a crucial component of the scavenger receptor family and is vital in protecting mammals from infectious diseases. Although research on SCARF2 is limited, mutations in this protein have been shown to cause skeletal abnormalities in both SCARF2-deficient mice and individuals with Van den Ende-Gupta syndrome (VDEGS), which is also associated with SCARF2 mutations. In contrast, other scavenger receptors have demonstrated versatile responses and have been found to aid in pathogen elimination, lipid transportation, intracellular cargo transportation, and work in tandem with various coreceptors. This review will concentrate on recent progress in comprehending SCARF2 and the functions played by members of the Scavenger Receptor Family in pre-diagnostic diseases.

What Makes NPOs Sustainable in an Emergency? Examining the Effect of Person-Organization Fit and Generation on Volunteer Activities During the COVID-19 Pandemic.

Purpose: Despite the unprecedented challenges caused by the COVID-19 pandemic, nonprofit organizations (NPOs) continued providing services, thereby contributing to overcoming the pandemic. What enabled NPOs to sustain their service provision during this global emergency? This study attempts to answer this question by focusing on one of the essential pillars supporting the operation of NPOs: volunteers. More specifically, we aim to investigate how person-organization (P-O) fit and generation, particularly the Millennial generation, are related to engagement in voluntary activities during the COVID-19 pandemic. Methods: We collected data through an online survey conducted in March 2021. This US national survey was completed by 2307 respondents, yielding the US Census balanced data regarding gender, age, race, education, and income. To analyze the data, we employed the two-stage Heckman selection model. Results: Relying on P-O fit theory and generational theory, the study identifies what led existing volunteers to continue engaging in volunteer activities at their NPO during the COVID-19 pandemic despite the risks. We found that P-O fit mattered in volunteers' decision to continue engaging. In addition, our study uncovered that when existing volunteers were Millennials, the relationship between P-O fit and engagement in voluntary activities strengthened during the pandemic. Conclusion: This study contributes to expanding the explanatory power of the P-O fit theory by testing it in an emergency and extends the generational theory by clarifying under what conditions Millennials (aka Generation Me) transform themselves into Generation We. In addition, linking NPO management and emergency management, this study provides NPO managers with practical implications for securing reliable volunteers who will sustain the capacity of the NPO in a crisis.

Complete chloroplast genome of Daphne pseudomezereum var. koreana (Thymelaeaceae).

Daphne pseudomezereum A. Gray var. koreana (Nakai) Hamaya is a shrub distributed in high mountains in Japan and Korea and is used as a medicinal plant. The complete chloroplast genome of D. pseudomezereum var. koreana is 171,152 bp long with four subregions consisting of a large single-copy region (84,963 bp), a small single-copy region (41,725 bp), and a pair of inverted repeats (2739 bp). The genome includes 139 genes (93 protein-coding genes, eight rRNAs, and 38 tRNAs). Phylogenetic analyses show that D. pseudomezereum var. koreana is nested within the Daphne clade in the narrow sense and that it forms a distinct lineage.

MARS2 drives metabolic switch of non-small-cell lung cancer cells via interaction with MCU.

Mitochondrial methionyl-tRNA synthetase (MARS2) canonically mediates the formation of fMet-tRNAifMet for mitochondrial translation initiation. Mitochondrial calcium uniporter (MCU) is a major gate of Ca2+ flux from cytosol into the mitochondrial matrix. We found that MARS2 interacts with MCU and stimulates mitochondrial Ca2+ influx. Methionine binding to MARS2 would act as a molecular switch that regulates MARS2-MCU interaction. Endogenous knockdown of MARS2 attenuates mitochondrial Ca2+ influx and induces p53 upregulation through the Ca2+-dependent CaMKII/CREB signaling. Subsequently, metabolic rewiring from glycolysis into pentose phosphate pathway is triggered and cellular reactive oxygen species level decreases. This metabolic switch induces inhibition of epithelial-mesenchymal transition (EMT) via cellular redox regulation. Expression of MARS2 is regulated by ZEB1 transcription factor in response to Wnt signaling. Our results suggest the mechanisms of mitochondrial Ca2+ uptake and metabolic control of cancer that are exerted by the key factors of the mitochondrial translational machinery and Ca2+ homeostasis.

Low Complexity Gradient Computation Techniques to Accelerate Deep Neural Network Training.

Deep neural network (DNN) training is an iterative process of updating network weights, called gradient computation, where (mini-batch) stochastic gradient descent (SGD) algorithm is generally used. Since SGD inherently allows gradient computations with noise, the proper approximation of computing weight gradients within SGD noise can be a promising technique to save energy/time consumptions during DNN training. This article proposes two novel techniques to reduce the computational complexity of the gradient computations for the acceleration of SGD-based DNN training. First, considering that the output predictions of a network (confidence) change with training inputs, the relation between the confidence and the magnitude of the weight gradient can be exploited to skip the gradient computations without seriously sacrificing the accuracy, especially for high confidence inputs. Second, the angle diversity-based approximations of intermediate activations for weight gradient calculation are also presented. Based on the fact that the angle diversity of gradients is small (highly uncorrelated) in the early training epoch, the bit precision of activations can be reduced to 2-/4-/8-bit depending on the resulting angle error between the original gradient and quantized gradient. The simulations show that the proposed approach can skip up to 75.83% of gradient computations with negligible accuracy degradation for CIFAR-10 dataset using ResNet-20. Hardware implementation results using 65-nm CMOS technology also show that the proposed training accelerator achieves up to 1.69× energy efficiency compared with other training accelerators.

H2Opred: a robust and efficient hybrid deep learning model for predicting 2'-O-methylation sites in human RNA.

2'-O-methylation (2OM) is the most common post-transcriptional modification of RNA. It plays a crucial role in RNA splicing, RNA stability and innate immunity. Despite advances in high-throughput detection, the chemical stability of 2OM makes it difficult to detect and map in messenger RNA. Therefore, bioinformatics tools have been developed using machine learning (ML) algorithms to identify 2OM sites. These tools have made significant progress, but their performances remain unsatisfactory and need further improvement. In this study, we introduced H2Opred, a novel hybrid deep learning (HDL) model for accurately identifying 2OM sites in human RNA. Notably, this is the first application of HDL in developing four nucleotide-specific models [adenine (A2OM), cytosine (C2OM), guanine (G2OM) and uracil (U2OM)] as well as a generic model (N2OM). H2Opred incorporated both stacked 1D convolutional neural network (1D-CNN) blocks and stacked attention-based bidirectional gated recurrent unit (Bi-GRU-Att) blocks. 1D-CNN blocks learned effective feature representations from 14 conventional descriptors, while Bi-GRU-Att blocks learned feature representations from five natural language processing-based embeddings extracted from RNA sequences. H2Opred integrated these feature representations to make the final prediction. Rigorous cross-validation analysis demonstrated that H2Opred consistently outperforms conventional ML-based single-feature models on five different datasets. Moreover, the generic model of H2Opred demonstrated a remarkable performance on both training and testing datasets, significantly outperforming the existing predictor and other four nucleotide-specific H2Opred models. To enhance accessibility and usability, we have deployed a user-friendly web server for H2Opred, accessible at https://balalab-skku.org/H2Opred/. This platform will serve as an invaluable tool for accurately predicting 2OM sites within human RNA, thereby facilitating broader applications in relevant research endeavors.

The impact of price transparency and competition on hospital costs: a research on all-payer claims databases.

BACKGROUND: Public reporting has been considered effective in reducing health care costs by mitigating information asymmetry in the market as payers have incorporated publicly available information mandates into pay-for-performance programs and value-based purchasing. Therefore, hospitals have faced increasing pressures to provide price transparency. Despite the widespread promotion of healthcare transparency, the effectiveness of public reporting has not yet been sufficiently understood. This study analyzed the impact of transparency policy and competition on hospital costs by taking the state operations of all-payer claims databases (APCDs) as a case of interest. METHODS: We employed a fixed-effects regression, which allows the generation of hospital-specific effects, in accordance with the suggestion by the Hausman test. The study samples comprise nonprofit and for-profit general acute care hospitals in the United States for 2011-2017. The finalized dataset ranges from 3547 observations in 2011 to 3405 observations in 2015 after removing missing values. RESULTS: We found that hospitals in the states with APCDs tend to bear higher average operating expenses than those without APCDs, which may indicate that states maintaining higher healthcare expenditures are more attentive to a price transparency initiative and tend to adopt APCDs. With regard to competition, the results showed that weak market competition is significantly associated with higher operating costs, supporting the traditional competition theory. However, the combined effect of APCDs and competition did not indicate a significant association with operating expenses. Further investigation showed a continued tendency for a weak intensity of competition to be linked to lower hospital operating costs in states without APCDs. For those located in non-APCD adopted states, market consolidation helped hospitals coordinate care more effectively, economize operating costs, and enjoy economies of scale due to their large size. Similar trends did not appear in APCD-adopted states except for in 2015. CONCLUSIONS: This study observed limited evidence of the impact of APCDs and market competition. Our findings suggest that states need to make multifaceted efforts to contain hospital costs, not solely depending on the rollout of cost information or market competition. Market concentration may lead to coordinated care or cost economization in some cases. Still, the existing literature also demonstrates some potentially harmful impacts of increased concentration in the healthcare market, such as inefficient use of resources, unilateral market power, and deterrence of innovation. The introduction of a price transparency tool may require additional policy actions that take market competition into consideration.

The potential inhibitory effect of ginsenoside Rh2 on mitophagy in UV-irradiated human dermal fibroblasts.

Background: In addition to its use as a health food, ginseng is used in cosmetics and shampoo because of its extensive health benefits. The ginsenoside, Rh2, is a component of ginseng that inhibits tumor cell proliferation and differentiation, promotes insulin secretion, improves insulin sensitivity, and shows antioxidant effects. Methods: The effects of Rh2 on cell survival, extracellular matrix (ECM) protein expression, and cell differentiation were examined. The antioxidant effects of Rh2 in UV-irradiated normal human dermal fibroblast (NHDF) cells were also examined. The effects of Rh2 on mitochondrial function, morphology, and mitophagy were investigated in UV-irradiated NHDF cells. Results: Rh2 treatment promoted the proliferation of NHDF cells. Additionally, Rh2 increased the expression levels of ECM proteins and growth-associated immediate-early genes in ultraviolet (UV)-irradiated NHDF cells. Rh2 also affected antioxidant protein expression and increased total antioxidant capacity. Furthermore, treatment with Rh2 ameliorated the changes in mitochondrial morphology, induced the recovery of mitochondrial function, and inhibited the initiation of mitophagy in UV-irradiated NHDF cells. Conclusion: Rh2 inhibits mitophagy and reinstates mitochondrial ATP production and membrane potential in NHDF cells damaged by UV exposure, leading to the recovery of ECM, cell proliferation, and antioxidant capacity.

The complete mitochondrial genome of Aclees taiwanensis Kôno, 1933 (Coleoptera: Curculionidae).

We sequenced the complete mitochondrial genome of Aclees taiwanensis collected in Korea. The circular mitogenome of A. taiwanensis is 17,435 bp, longer than that of Aclees cribratus, and includes 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNAs, and a control region/D-loop. The AT ratio is 75.4%. Maximum-likelihood and Bayesian inference phylogenetic trees showed that A. taiwanensis was clustered with A. cribratus with full-support values for both trees.

Functional characteristics and research trends of PDE11A in human diseases (Review).

cAMP and cGMP are important secondary messengers involved in cell regulation and metabolism driven by the G protein­coupled receptor. cAMP is converted via adenylyl cyclase (AC) and activates protein kinase A to phosphorylate intracellular proteins that mediate specific responses. cAMP signaling serves a role at multiple steps in tumorigenesis. The level of cAMP is increased in association with cancer cell formation through activation of AC­stimulatory G protein by mutation. Phosphodiesterases (PDEs) hydrolyze cAMP and cGMP to AMP and GMP. PDEs are composed of 11 families, and each can hydrolyze cAMP and cGMP or both cAMP and cGMP. PDEs perform various roles depending on their location and expression site, and are involved in several diseases, including male erectile dysfunction, pulmonary hypertension, Alzheimer's disease and schizophrenia. PDE11A is the 11th member of the PDE family and is characterized by four splice variants with varying tissue expression and N­terminal regulatory regions. Among tissues, the expression of PDE11A was highest in the prostate, and it was also expressed in hepatic skeletal muscle, pituitary, pancreas and kidney. PDE11A is the first PDE associated with an adrenocortical tumor associated genetic condition. In several studies, three PDE11A mutations have been reported in patients with Cushing syndrome with primary pigmented nodular adrenocortical disease or isolated micronodular adrenocortical disease without other genetic defects. It has been reported that an increase in PDE11A expression affects the proliferation of glioblastoma and worsens patient prognosis. The present mini­review summarizes the location of PDE11A expression, the impact of structural differences and disease relevance.

HDAC8-Selective Inhibition by PCI-34051 Enhances the Anticancer Effects of ACY-241 in Ovarian Cancer Cells.

HDAC6 is overexpressed in ovarian cancer and is known to be correlated with tumorigenesis. Accordingly, ACY-241, a selective HDAC6 inhibitor, is currently under clinical trial and has been tested in combination with various drugs. HDAC8, another member of the HDAC family, has recently gained attention as a novel target for cancer therapy. Here, we evaluated the synergistic anticancer effects of PCI-34051 and ACY-241 in ovarian cancer. Among various ovarian cancer cells, PCI-34051 effectively suppresses cell proliferation in wild-type p53 ovarian cancer cells compared with mutant p53 ovarian cancer cells. In ovarian cancer cells harboring wild-type p53, PCI-34051 in combination with ACY-241 synergistically represses cell proliferation, enhances apoptosis, and suppresses cell migration. The expression of pro-apoptotic proteins is synergistically upregulated, whereas the expressions of anti-apoptotic proteins and metastasis-associated proteins are significantly downregulated in combination treatment. Furthermore, the level of acetyl-p53 at K381 is synergistically upregulated upon combination treatment. Overall, co-inhibition of HDAC6 and HDAC8 through selective inhibitors synergistically suppresses cancer cell proliferation and metastasis in p53 wild-type ovarian cancer cells. These results suggest a novel approach to treating ovarian cancer patients and the therapeutic potential in developing HDAC6/8 dual inhibitors.

Phosphodiesterase 11 A (PDE11A), a potential biomarker for glioblastoma.

Phosphodiesterase 11A (PDE11A), a 3',5'-cyclic nucleotide phosphodiesterase, is a key regulator of intracellular signaling that functions by degrading cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP). However, the function of PDE11A in brain tumors is currently unclear. In this study, we found that PDE11A may be involved in glioblastoma development. The protein and mRNA levels of PDE11A were significantly higher in U87-MG, U251-MG and U343-MG glioblastoma cell lines. Gene expression analyses by deep-sequencing revealed that PDE11A mRNA levels were higher in U87-MG and U251-MG cells compared to other cells in the cerebral cortex. A comprehensive analysis of The Cancer Genome Atlas (TCGA) data revealed that PDE11A expression was also elevated in glioblastoma patients. Taken together, these data indicate that PDE11A expression was increased in glioblastoma cell lines and glioma patients, suggesting that PDE11A could be a putative diagnostic marker and therapeutic target for glioma.

The Veterans Choice Act and Technical Efficiency of Veterans Affairs (VA) Hospitals.

The Veterans Health Administration (VHA), responsible for providing 9 million veterans with quality healthcare, is not insulated from concerns about efficiency. In the aftermath of the Veterans Affairs (VA) hospital scandal in 2014, Congress passed the Veterans Choice Act of 2014, which allows eligible veterans to use non-VA hospitals instead of VA hospitals. After analyzing 118 or 119 VA hospitals each year from 2012 through 2017 in the U.S, this paper evaluates the efficiency scores of VA hospitals and examines how the 2014 Act has influenced their technical efficiency over time. Slack analysis shows that inefficient VA hospitals can improve efficiency by reallocating input resources, and regression analysis demonstrates that the overall technical efficiency of VA hospitals decreased by 0.164 after the implementation of the Act. This means that as more veterans used non-VA hospitals under the 2014 Act, the technical efficiency of VA hospitals decreased considerably. Given that a substantial portion of veterans' demands for healthcare transferred out to non-VA hospitals, the VHA should evaluate whether the current capacity of VA hospitals is appropriate and try to reduce wasted input resources to improve efficiency.

Early Termination Based Training Acceleration for an Energy-Efficient SNN Processor Design.

In this paper, we present a novel early termination based training acceleration technique for temporal coding based spiking neural network (SNN) processor design. The proposed early termination scheme can efficiently identify the non-contributing training images during the training's feedforward process, and it skips the rest of the processes to save training energy and time. A metric to evaluate each input image's contribution to training has been developed, and it is compared with pre-determined threshold to decide whether to skip the rest of the training process. For the threshold selection, an adaptive threshold calculation method is presented to increase the computation skip ratio without sacrificing accuracy. Timestep splitting approach is also employed to allow more frequent early termination in split timesteps, thus leading to more computation savings. The proposed early termination and timestep splitting techniques achieve 51.21/42.31/93.53/30.36% reduction of synaptic operations and 86.06/64.63/90.82/49.14% reduction of feedforward timestep for the training process on MNIST/Fashion-MNIST/ETH-80/EMNIST-Letters dataset, respectively. The hardware implementation of the proposed SNN processor using 28 nm CMOS process shows that the SNN processor achieves the training energy saving of 61.76/31.88% and computation cycle reduction of 69.10/36.26% on MNIST/Fashion-MNIST dataset, respectively.

The complete chloroplast genome of Utricularia tenuicaulis Miki (Lentibulariaceae) isolated in Korea.

Utricularia tenuicaulis Miki 1935 is an aquatic carnivorous plant species found in East Asia including Korea and Japan. In this study, the chloroplast genome of U. tenuicaulis was successfully sequenced. The assembled genome (153,976 bp; GC ratio, 37.0%) contains four subregions, with the large single copy (LSC; 84,596 bp; 34.9%) and small single copy (SSC; 17,946 bp; 30.5%) regions separated by 25,718 bp of inverted repeat regions (42.7%), and includes 126 genes (81 protein-coding genes, 8 rRNAs, and 37 tRNAs). Phylogenetic analyses based on the whole-chloroplast genomes of 18 species, including 17 Lentibulariaceae species and one outgroup species, suggest a close relationship between U. tenuicaulis and Utricularia macrorhiza Leconte 1824. A comparison of genomic variation between U. tenuicaulis and U. macrorhiza confirmed the validity of the specific discrimination of U. tenuicaulis.

Emerging role of LETM1/GRP78 axis in lung cancer.

The selective autophagy of damaged mitochondria is called mitophagy. Mitochondrial dysfunction, mitophagy, and apoptosis have been suggested to be interrelated in various human lung carcinomas. Leucine zipper EF-hand-containing transmembrane protein-1 (LETM1) was cloned in an attempt to identify candidate genes for Wolf-Hirschhorn syndrome. LETM1 plays a role in mitochondrial morphology, ion homeostasis, and cell viability. LETM1 has also been shown to be overexpressed in different human cancer tissues, including lung cancer. In the current study, we have provided clear evidence that LETM1 acts as an anchoring protein for the mitochondria-associated ER membrane (MAM). Fragmented mitochondria have been found in lung cancer cells with LETM1 overexpression. In addition, a reduction of mitochondrial membrane potential and significant accumulation of microtubule-associated protein 1 A/1B-light chain 3 punctate, which localizes with Red-Mito, was found in LETM1-overexpressed cells, suggesting that mitophagy is upregulated in these cells. Interestingly, glucose-regulated protein 78 kDa (GRP78; an ER chaperon protein) and glucose-regulated protein 75 kDa (GRP75) were posited to interact with LETM1 in the immunoprecipitated LETM1 of H460 cells. This interaction was enhanced in cells treated with carbonyl cyanide m-chlorophenylhydrazone, a chemical mitophagy inducer. Treatment of cells with honokiol (a GRP78 inhibitor) blocked LETM1-mediated mitophagy, and CRISPR/Cas9-mediated GRP75 knockout inhibited LETM1-induced autophagy. Thus, GRP78 interacts with LETM1. Taken together, these observations support the notion that the complex formation of LETM1/GRP75/GRP78 might be an important step in MAM formation and mitophagy, thus regulating mitochondrial quality control in lung cancer.