AIBP controls TLR4 inflammarafts and mitochondrial dysfunction in a mouse model of Alzheimer's disease.

Microglia-driven neuroinflammation plays an important role in the development of Alzheimer's disease. Microglia activation is accompanied by the formation and chronic expression of TLR4 inflammarafts, defined as enlarged and cholesterol-rich lipid rafts serving as an assembly platform for TLR4 dimers and complexes of other inflammatory receptors. The secreted apoA-I binding protein (APOA1BP or AIBP) binds TLR4 and selectively targets cholesterol depletion machinery to TLR4 inflammaraft-expressing inflammatory, but not homeostatic microglia. Here we demonstrated that amyloid-beta (Aß) induced formation of TLR4 inflammarafts in microglia in vitro and in the brain of APP/PS1 mice. Mitochondria in Apoa1bp-/- APP/PS1 microglia were hyperbranched and cupped, which was accompanied by increased reactive oxygen species and the dilated endoplasmic reticulum. The size and number of Aß plaques and neuronal cell death were significantly increased, and the animal survival was decreased in Apoa1bp-/-APP/PS1 compared to APP/PS1 female mice. These results suggest that AIBP exerts control of TLR4 inflammarafts and mitochondrial dynamics in microglia and plays a protective role in Alzheimer's disease associated oxidative stress and neurodegeneration.

Microbiome-Mucosal Immunity Nexus: Driving Forces in Respiratory Disease Progression.

The importance of the complex interplay between the microbiome and mucosal immunity, particularly within the respiratory tract, has gained significant attention due to its potential implications for the severity and progression of lung diseases. Therefore, this review summarizes the specific interactions through which the respiratory tract-specific microbiome influences mucosal immunity and ultimately impacts respiratory health. Furthermore, we discuss how the microbiome affects mucosal immunity, considering tissue-specific variations, and its capacity in respiratory diseases containing asthma, chronic obstructive pulmonary disease, and lung cancer. Additionally, we investigate the external factors which affect the relationship between respiratory microbiome and mucosal immune responses. By exploring these intricate interactions, this review provides valuable insights into the potential for microbiome-based interventions to modulate mucosal immunity and alleviate the severity of respiratory diseases.

Therapeutic role of histone deacetylase inhibition in an in vitro model of Graves' orbitopathy.

Graves' orbitopathy (GO), a manifestation of Graves' disease, is characterized by orbital fibroblast­induced inflammation, leading to fibrosis or adipogenesis. Histone deacetylase (HDAC) serves a central role in autoimmune diseases and fibrosis. The present study investigated HDAC inhibition in orbital fibroblasts from patients with GO to evaluate its potential as a therapeutic agent. Primary cultured orbital fibroblasts were treated with an HDAC inhibitor, panobinostat, under the stimulation of IL­1ß, TGF­ß or adipogenic medium. Inflammatory cytokines, and fibrosis­ and adipogenesis­related proteins were analyzed using western blotting. The effects of panobinostat on HDAC mRNA expression were measured in GO orbital fibroblasts, and specific HDACs were inhibited using small interfering RNA transfection. Panobinostat significantly reduced the IL­1ß­induced production of inflammatory cytokines and TGF­ß­induced production of fibrosis­related proteins. It also suppressed adipocyte differentiation and adipogenic transcription factor production. Furthermore, it significantly attenuated HDAC7 mRNA expression in GO orbital fibroblasts. In addition, the silencing of HDAC7 led to anti­inflammatory and anti­fibrotic effects. In conclusion, by inhibiting HDAC7 gene expression, panobinostat may suppress the production of inflammatory cytokines, profibrotic proteins and adipogenesis in GO orbital fibroblasts. The present in vitro study suggested that HDAC7 could be a potential therapeutic target for inhibiting the inflammatory, adipogenic and fibrotic mechanisms of GO.

Overgeneralization of conditioned fear in patients with social anxiety disorder.

Introduction: While abnormal responses to threat, including overgeneralization to conditioned fear, have been postulated to play a critical role in pathological anxiety, the relevance of previous findings to social anxiety disorder (SAD) is unclear. We investigated conditioned and generalized fear responses in patients with SAD using socially relevant stimuli. Methods: A total of 26 patients with SAD and 25 healthy controls participated in a fear conditioning and generalization paradigm consisting of two neutral faces as conditioned stimuli (CS+ or CS-) and an angry face with contemptuous comments as unconditioned stimuli. Eight morphed faces of two conditioned stimuli in each continuum were given to test generalization. Behavioral data and physiological responses were acquired. Results: Successful conditioning was observed in the risk ratings for both groups, while only a marginal indication of conditioning was noted in physiological measures. During the generalization phase, patients rated the risk higher than CS- when the stimuli close to CS- contained a portion of CS+ features. Larger skin conductance responses to this stimulus were linked to higher fear of negative evaluation. In addition, patients spent a longer time evaluating safe and ambiguous stimuli than healthy controls and exhibited consistently high levels of subjective arousal. Discussion: Taken together, our findings suggest that SAD patients may exhibit a tendency towards overgeneralization of fear responses and show distinct patterns in processing generalized threat stimuli compared to healthy controls. Even though overgeneralization was not evident in physiological measures, it is necessary to consider this behavioral characteristic in the clinical management of patients with SAD.

Assessment of noise pollution-prone areas using an explainable geospatial artificial intelligence approach.

This research aims to use the power of geospatial artificial intelligence (GeoAI), employing the categorical boosting (CatBoost) machine learning model in conjunction with two metaheuristic algorithms, the firefly algorithm (CatBoost-FA) and the fruit fly optimization algorithm (CatBoost-FOA), to spatially assess and map noise pollution prone areas in Tehran city, Iran. To spatially model areas susceptible to noise pollution, we established a comprehensive spatial database encompassing data for the annual average Leq (equivalent continuous sound level) from 2019 to 2022. This database was enriched with critical spatial criteria influencing noise pollution, including urban land use, traffic volume, population density, and normalized difference vegetation index (NDVI). Our study evaluated the predictive accuracy of these models using key performance metrics, including root mean square error (RMSE), mean absolute error (MAE), and receiver operating characteristic (ROC) indices. The results demonstrated the superior performance of the CatBoost-FA algorithm, with RMSE and MAE values of 0.159 and 0.114 for the training data and 0.437 and 0.371 for the test data, outperforming both the CatBoost-FOA and CatBoost models. ROC analysis further confirmed the efficacy of the models, achieving an accuracy of 0.897, CatBoost-FOA with an accuracy of 0.871, and CatBoost with an accuracy of 0.846, highlighting their robust modeling capabilities. Additionally, we employed an explainable artificial intelligence (XAI) approach, utilizing the SHAP (Shapley Additive Explanations) method to interpret the underlying mechanisms of our models. The SHAP results revealed the significant influence of various factors on noise-pollution-prone areas, with airport, commercial, and administrative zones emerging as pivotal contributors.

Limitations of NHIC claim code-based surveillance and the necessity of UDI implementation in Korea.

The E-Health Big Data Evidence Innovation Network (FeederNet) in Korea, based on the observational medical outcomes partnership (OMOP) common data model (CDM), had 72.3% participation from tertiary hospitals handling severe diseases as of October 2022. While this contributes to the activation of multi-institutional research, concerns about the comprehensiveness of device data persist due to the adoption of national health insurance corporation (NHIC) claim codes as device identifiers in the medical device field. This study critically evaluated the effectiveness and compatibility of NHIC claim codes and unique device identifier (UDI) within FeederNet to identify the optimal identifier for efficient Post-market surveillance (PMS). Specifically, this study addressed three main questions: (1) the number of UDIs classified as NHIC-covered items, (2) the number of UDIs included in each NHIC claim code, and (3) the number of NHIC claim codes each UDI covers. Among the 1,979,655 UDIs registered domestically, only 36.02% (712,983) were classified as covered by National Health Insurance. NHIC-covered medical devices were limited to categories (A) medical devices, (B) medical supplies, and (C) dental materials, excluding most software and in vitro diagnostics (IVD). Multiple UDIs could be registered under a single NHIC claim code, and a single UDI could be registered under multiple NHIC claim codes. Only 32.62% (13,756/42,171) of NHIC claim codes had registered UDIs, with an average of 53 UDIs per claim code. Of the UDIs listed as NHIC covered, 92.39% (659,046/713,341) had one claim code, while 7.25% (51,652) had multiple claim codes. Additionally, 2643 UDIs were listed as NHIC covered but had no registered claim codes. Due to this complex relationship, NHIC claim code-based PMS may pool safe and unsafe models or disperse problematic models across multiple claim codes, leading to a lower problem rate or insignificant differences between claim codes, thus reducing signal detection sensitivity compared to UDI-based PMS. In conclusion, NHIC claim code-based PMS has limitations in granularity and signal detection sensitivity, necessitating the adoption of UDI-based PMS to address these issues. The UDI system can enhance the accuracy of medical device identification and tracking, playing a crucial role in generating real-world evidence (RWE) by integrating data from various sources. Future research should explore specific strategies for integrating and utilizing UDI with NHIC claim codes, contributing to the implementation of a more reliable and comprehensive PMS in Korea's healthcare system.

Preventive and Therapeutic Effects of Lactiplantibacillus plantarum HD02 and MD159 through Mast Cell Degranulation Inhibition in Mouse Models of Atopic Dermatitis.

As the relationship between the gut microbiome and allergies becomes better understood, targeted strategies to prevent and treat allergies through gut microbiome modulation are being increasingly developed. In the study presented herein, we screened various probiotics for their ability to inhibit mast cell degranulation and identified Lactiplatibacillus plantarum HD02 and MD159 as effective candidates. The two strains significantly attenuated vascular permeability induced by mast cell degranulation in a passive cutaneous anaphylaxis (PCA) model and, in the MC903-induced murine atopic dermatitis (AD) model, demonstrated comparable preventive effects against allergies, reducing blood levels of MCPT-1 (mast cell protease-1) and total IgE. In the house dust mite (HDM)-induced murine AD model, both L. plantarum HD02 and MD159 showed therapeutic effects, with L. plantarum HD02 demonstrating superior efficacy. Nevertheless, L. plantarum MD159 better suppressed transepidermal water loss (TEWL). Furthermore, L. plantarum HD02 and MD159 significantly increased the number of splenic Foxp3+ regulatory T cells, with L. plantarum MD159 having a more pronounced effect. However, only L. plantarum HD02 achieved a reduction in immune cells in the draining lymph nodes. Our findings highlight L. plantarum HD02 and MD159 as promising candidates for the prevention and treatment of allergies, demonstrating significant efficacy in suppressing mast cell degranulation, reducing the number of allergy biomarkers, and modulating immune responses in experimental models of AD. Their distinct mechanisms of action suggest potential complementary roles in addressing allergic diseases, underscoring their therapeutic promise in clinical applications.

Pentraxin3 mediates inflammation and adipogenesis in Graves' orbitopathy pathogenesis.

Pentraxin 3 (PTX3) is a prototypic humoral soluble pattern-recognition molecule known to function in immunity-related inflammation. Given the lack of information on the precise functions of PTX3 in the pathogenesis of Graves' orbitopathy (GO), this study investigated the role of PTX3 in the inflammation and adipogenesis mechanism of GO. We first compared the PTX3 expression between orbital tissues from patients with GO and normal controls, using real-time polymerase chain reaction, which estimated significantly higher PTX3 transcript levels in the GO tissues than in the normal tissues. In addition, PTX3 production was markedly increased upon interleukin (IL)-1ß and adipogenic stimulation. We then evaluated the effects of silencing PTX3 in primary orbital fibroblast cultures by analyzing the expression levels of pro-inflammatory cytokines, adipogenesis-related proteins, and downstream transcription factors in cells transfected with or without a small interfering RNA against PTX3, using western blot. Silencing PTX3 attenuated the IL-1ß-induced secretion of pro-inflammatory cytokines, including IL-6, IL-8, monocyte chemotactic protein-1, intercellular adhesion molecule-1, and cyclooxygenase-2, and suppressed the IL-1ß-mediated activation of p38 kinase, nuclear factor-κB, and extracellular signal-regulated kinase. Moreover, PTX3 knockdown suppressed adipogenic differentiation, as assessed using Oil Red O staining, as well as the expression of adipogenesis-associated transcription factors including peroxisome proliferator activator-γ, CCAAT/enhancer-binding proteins α and ß, adipocyte protein 2, adiponectin, and leptin. Thus, this study suggests that PTX3 plays a significant role in the pathogenesis of GO and may serve as a novel therapeutic target for the condition.

Impacts of Tocolytics on Maternal and Neonatal Glucose Levels in Women With Gestational Diabetes Mellitus.

BACKGROUND: We investigated the impacts of tocolytic agents on maternal and neonatal blood glucose levels in women with gestational diabetes mellitus (GDM) who used tocolytics for preterm labor. METHODS: This multi-center, retrospective cohort study included women with GDM who were admitted for preterm labor from twelve hospitals in South Korea. We excluded women with multiple pregnancies, anomalies, overt DM diagnosed before pregnancy or 23 weeks of gestation, and women who received multiple tocolytics. The patients were divided according to the types of tocolytics; atosiban, ritodrine, and nifedipine group. We collected baseline maternal characteristics, pregnancy outcomes, maternal glucose levels during hospitalization, and neonatal glucose levels. We compared the frequency of maternal hyperglycemia and neonatal hypoglycemia among three groups. A multivariate logistic regression analysis was performed to evaluate the contributing factors to the occurrence of maternal hyperglycemia and neonatal hypoglycemia. RESULTS: A total of 128 women were included: 44 (34.4%), 51 (39.8%), and 33 (25.8%) women received atosiban, ritodrine, and nifedipine, respectively. Mean fasting blood glucose (FBG) (112.3, 109.6, and 89.5 mg/dL, P < 0.001) and 2-hour postprandial glucose (PPG2) levels (145.4, 148.3, and 116.5 mg/dL, P = 0.004) were significantly higher in atosiban and ritodrine group than those in nifedipine group. Even after adjusting for covariates including antenatal steroid use, gestational age at admission, and pre-pregnancy body mass index, there was an increased risk of high maternal mean FBG (≥ 95 mg/dL) and PPG2 (≥ 120 mg/dL) levels in the atosiban and ritodrine group than in nifedipine group. The atosiban and ritodrine groups are also at increased risk of neonatal hypoglycemia (< 47 mg/dL) compared to the nifedipine group with the odds ratio of 4.58 and 4.67, respectively (P < 0.05). CONCLUSION: There is an increased risk of maternal hyperglycemia and neonatal hypoglycemia in women with GDM using atosiban and ritodrine tocolytics for preterm labor compared to those using nifedipine.

Anti-muscle atrophy effect of fermented Tenebrio molitor larvae extract by modulating the PI3K-Akt-mTOR/FoxO3α pathway in mice treated with dexamethasone.

This study investigated the anti-sarcopenic effect of fermented Tenebrio molitor larvae (mealworms) extract (FME) in both dexamethasone (DEX)-treated C2C12 cells and mice. FME (100 µg/mL) increased the diameter of myotubes and inhibited the gene and protein expression of atrogin-1 compared to DEX- or non-fermented mealworms extract (ME)-treated C2C12 cells. Male C57BL/6N mice were divided into five groups: Normal Control (NC), DEX (10 mg/kg, intraperitoneal), and three groups of DEX+FME (100, 200, or 500 mg FME/kg/day, oral) for two weeks. FME at doses of 200 and 500 mg/kg effectively improved grip strength when compared to the DEX group. Histological analysis of the quadriceps muscle showed a larger muscle fiber size in the DEX+FME groups compared to DEX group. FME (200 and 500 mg/kg) significantly increased cross-sectional area of the muscle fiber compared to DEX group. FME (500 mg/kg) significantly decreased the ubiquitin, atrogin-1 and MuRF-1 protein levels, and increased levels of MHC and MyoG in DEX-treated mice. The puromycin labeling assay revealed that FME increased protein synthesis in DEX-induced muscle atrophy. The FME treatment demonstrated significant upregulation in phosphorylation levels, including mTOR, FoxO3α, Akt, and PI3K compared to DEX group. In conclusion, FME inhibited the increase in proteins associated with muscle atrophy, including, atrogin-1 and MuRF-1, by regulating the PI3K-Akt-FoxO3α pathway. FME improved the PI3K-Akt-mTOR signaling pathway, which was reduced by DEX. This study suggests that FME has the potential for use in sarcopenia therapy, possibly serving as a natural agent that counteracts the negative effects of DEX on muscle tissue.

Comparisons of clinical outcomes between hypertensive and normotensive living kidney donors: a prospective, multicenter nationwide cohort study.

Background: Living kidney donors with hypertension are potential candidates for solving the donor shortages in renal transplantation. However, the safety of donors with hypertension after nephrectomy has not been sufficiently confirmed. Methods: A total of 642 hypertensive and 4,848 normotensive living kidney donors who were enrolled in the Korean Organ Transplantation Registry between May 2014 and December 2020 were included in this study. The study endpoints were a decreased estimated glomerular filtration rate (eGFR) and proteinuria. Results: In the entire cohort, donors with hypertension had a lower eGFR before nephrectomy in comparison to normotensive donors which remained lower after kidney transplantation. The incidence of proteinuria in hypertensive donors increased during follow-up. In propensity score-matched analysis, the risk of eGFR being <60 mL/min/1.73 m2 (hazard ratio [HR], 0.77; 95% confidence interval [CI], 0.50-1.19) or <45 mL/min/1.73 m2 (HR, 0.50; 95% CI, 0.06-4.03) was not significantly increased in donors with hypertension. However, hypertensive donors were found to have a significantly higher risk of proteinuria than normotensive donors (HR, 2.28; 95% CI, 1.05-4.94). Similar findings were also observed in the analysis of the entire cohort, indicating that hypertensive donors had a significantly higher risk of proteinuria (adjusted HR, 1.77; 95% CI, 1.10-2.85), without a substantial increase in the risk of decreased renal function. Conclusion: The risk of proteinuria after donation was substantially increased in donors with hypertension. These findings underscore the need for careful monitoring of proteinuria in hypertensive donors following donation.

Bridge-rich and loop-less hydrogel networks through suppressed micellization of multiblock polyelectrolytes.

Most triblock copolymer-based physical hydrogels form three-dimensional networks through micellar packing, and formation of polymer loops represents a topological defect that diminishes hydrogel elasticity. This effect can be mitigated by maximizing the fraction of elastically effective bridges in the hydrogel network. Herein, we report hydrogels constructed by complexing oppositely charged multiblock copolymers designed with a sequence pattern that maximizes the entropic and enthalpic penalty of micellization. These copolymers self-assemble into branched and bridge-rich network units (netmers), instead of forming sparsely interlinked micelles. We find that the storage modulus of the netmer-based hydrogel is 11.5 times higher than that of the micelle-based hydrogel. Complementary coarse grained molecular dynamics simulations reveal that in the netmer-based hydrogels, the numbers of charge-complexed nodes and mechanically reinforcing bridges increase substantially relative to micelle-based hydrogels.

Analysis of Rice Blast Fungus Genetic Diversity and Identification of a Novel Blast Resistance OsDRq12 Gene.

The rice blast fungus Magnaporthe oryzae poses a significant challenge to maintaining rice production. Developing rice varieties with resistance to this disease is crucial for its effective control. To understand the genetic variability of blast isolates collected between 2015 and 2017, the 27 monogenic rice lines that carry specific resistance genes were used to evaluate blast disease reactions. Based on criteria such as viability, virulence, and reactions to resistance genes, 20 blast isolates were selected as representative strains. To identify novel resistance genes, a quantitative trait locus analysis was carried out utilizing a mixture of the 20 representative rice blast isolates and a rice population derived from crossing the blast-resistant cultivar 'Cheongcheong' with the blast-susceptible cultivar 'Nagdong'. This analysis revealed a significant locus, RM1227-RM1261 on chromosome 12, that is associated with rice blast resistance. Within this locus, 12 disease resistance-associated protein genes were identified. Among them, OsDRq12, a member of the nucleotide-binding, leucine-rich repeat disease resistance family, was chosen as the target gene for additional computational investigation. The findings of this study have significant implications for enhancing rice production and ensuring food security by controlling rice blast and developing resistant rice cultivars.

First Report of Nigrospora oryzae Causing Leaf Spot on Peanut (Arachis hypogaea L.) in the Republic of Korea.

Peanut (Arachis hypogaea L.) is one of the most profitable upland crops, yielding 10,711 tonnes in an area of 4,062 ha in the Republic of Korea (Ministry of Agriculture, Food and Rural Affairs 2023). In September 2023, dark gray spots surrounded by yellow halos were observed on the peanut leaves over an area of 880 m2 at the National Institute of Crop Science (35°50'31.4"N 127°02'41.0"E), with a disease incidence up to 80%. Early symptoms appeared as small, brown, circular or irregular spots that enlarged and were surrounded by chlorotic halos. Leaf cuttings (5 mm x 5 mm) from five symptomatic plants were surface-sterilized with 70% EtOH for 1 min, followed by 1% NaClO for 1 min, and rinsed 3 times with sterile water. The pieces were placed on Potato Dextrose Agar (PDA) and incubated at 25 °C in the dark for 3 days. Three isolates obtained by single-spore isolation were designated as F23025, F23026, and F23027. Two isolates, F23025 and F23026 were deposited in the Korean Agricultural Culture Collection (https://genebank.rda.go.kr) under the accession numbers 410722 and 410723. Fungal colonies were initially white and turned sooty gray after 5 days. Conidia were unicellular, brown to black, and spherical or sub-spherical with 6.8 µm to 14.3 µm (mean = 11.1 µm ± 1.8, n = 50). The morphology of the three isolates was identical and showed the same characteristics as Nigrospora oryzae (Ellis 1971; Hudson 1963). For molecular identification, the Internal Transcribed Spacer (ITS) region (GenBank accession PP388306 and PP574448), beta tubulin (PP397027 and PP580108), and translation elongation factor 1- ɑ (PP397028 and PP580109) of isolates F23025 and F23026 were amplified and sequenced with primers of ITS5/ITS4, Bt2a/Bt2b, EF1-727F/EF2, respectively and showed high identity of 99.62% (530 bp/532 bp), 100% (384/384), and 99.79% (475/476) with N. oryzae strain LC2693 (GenBank accessions KX985994, KY019471, and KY019299, respectively). Multilocus sequence analysis showed isolates F23025 and F23026 were on the same clade with N. oryzae strain LC2693. To determine the pathogenicity to peanut, a conidial suspension (1 x 106 conidia/mL) was sprayed onto leaves of five 3-week-old plants 'Sewon' grown in pots, while sterile distilled water was sprayed onto two plants used as negative control. Sprayed plants were placed in a dew chamber at 25℃ for two days and grown in a growth chamber at 25℃ and 80% of relative humidity with a 16L:8D cycle. Two weeks later, dark spots with chlorotic halos appeared only on leaves sprayed with conidia, and no symptoms on leaves sprayed with sterile distilled water. The pathogenicity test was repeated three times, and each time the pathogen was re-isolated and identified by ITS sequence, thus fulfilling Koch's postulates. Nigrospora species are cosmopolitan, and some species have a wide host range as plant pathogens. Recently, two species of the genus Nigrospora, N. sphaerica and N. aurantiaca, were reported to cause peanut leaf blight in China (Liu et al. 2020; He et al. 2023). To the best of our knowledge, this is the first report of N. oryzae causing leaf spot to A. hypogaea L. in the Republic of Korea. As identifying new pathogens and registering fungicides to control them are important for the continued cultivation of peanut, this report will help in that endeavor.

Neural correlates of anhedonia in young adults with subthreshold depression: A graph theory approach for cortical-subcortical structural covariance.

BACKGROUND: Anhedonia is an enduring symptom of subthreshold depression (StD) and predict later onset of major depressive disorder (MDD). Brain structural covariance describes the inter-regional distribution of morphological changes compared to healthy controls (HC) and reflects brain maturation and disease progression. We investigated neural correlates of anhedonia from the structural covariance. METHODS: T1-weighted brain magnetic resonance images were acquired from 79 young adults (26 StD, 30 MDD, and 23 HC). Intra-individual structural covariance networks of 68 cortical surface area (CSAs), 68 cortical thicknesses (CTs), and 14 subcortical volumes were constructed. Group-level hubs and principal edges were defined using the global and regional graph metrics, compared between groups, and examined for the association with anhedonia severity. RESULTS: Global network metrics were comparable among the StD, MDD, and HC. StD exhibited lower centralities of left pallidal volume than HC. StD showed higher centralities than HC in the CSAs of right rostral anterior cingulate cortex (ACC) and pars triangularis, and in the CT of left pars orbitalis. Less anhedonia was associated with higher centralities of left pallidum and right amygdala, higher edge betweenness centralities in the structural covariance (EBSC) of left postcentral gyrus-parahippocampal gyrus and LIPL-right amygdala. More anhedonia was associated with higher centralities of left inferior parietal lobule (LIPL), left postcentral gyrus, left caudal ACC, and higher EBSC of LIPL-left postcentral gyrus, LIPL-right lateral occipital gyrus, and left caudal ACC-parahippocampal gyrus. LIMITATIONS: This study has a cross-sectional design. CONCLUSIONS: Structural covariance of brain morphologies within the salience and limbic networks, and among the salience-limbic-default mode-somatomotor-visual networks, are possible neural correlates of anhedonia in depression.

Protective Effect of Memantine on Cisplatin-Induced Ototoxicity: An In Vitro Study.

HYPOTHESIS: Memantine, an N -methyl- d -aspartate receptor antagonist, is widely used to treat Alzheimer's disease and has been found to have potential neuroprotective effects. In this study, we evaluated the protective effects of memantine against cisplatin-induced ototoxicity. BACKGROUND: Cisplatin is a widely used anticancer drug for various cancers; however, its use is limited by its side effects, including ototoxicity. Several drugs have been developed to reduce cisplatin toxicity. In this study, we treated cisplatin-damaged cochlear hair cells with memantine and evaluated its protective effects. METHOD: House Ear Institute Organ of Corti 1 (HEI-OC1) cells and cochlear explants were treated with cisplatin or memantine. Cell viability, apoptotic patterns, reactive oxygen species (ROS) production, Bcl-2/caspase-3 activity, and cell numbers were measured to evaluate the anti-apoptotic and antioxidative effects of memantine. RESULT: Memantine treatment significantly improved cell viability and reduced cisplatin-induced apoptosis in auditory cells. Bcl-2/caspase-3 activity was also significantly increased, suggesting anti-apoptotic effects against cisplatin-induced ototoxicity. CONCLUSION: Our results suggest that memantine protects against cisplatin-induced ototoxicity in vitro, providing a potential new strategy for preventing hearing loss in patients undergoing cisplatin chemotherapy.

Alteration of Piezo1 signaling in type 2 diabetic mice: focus on endothelium and BKCa channel.

Piezo1 mechanosensitive ion channel plays a important role in vascular physiology and disease. This study aimed to elucidate the altered signaling elicited by Piezo1 activation in the arteries of type 2 diabetes. Ten- to 12-week-old male C57BL/6 (control) and type 2 diabetic mice (db-/db-) were used. The second-order mesenteric arteries (~ 150 µm) were used for isometric tension experiments. Western blot analysis and immunofluorescence staining were performed to observe protein expression. Piezo1 was significantly decreased in mesenteric arteries of type 2 diabetic mice compared to control mice, as analyzed by western blot and immunofluorescence staining. Piezo1 agonist, Yoda1, concentration-dependently induced relaxation of mesenteric arteries in both groups. Interestingly, the relaxation response was significantly greater in control mice than in db-/db- mice. The removal of endothelium reduced relaxation responses induced by Yoda1, which was greater in control mice than db-/db- mice. Furthermore, the relaxation response was reduced by pre-treatment with various types of K+ channel blockers in endothelium-intact arteries in control mice. In endothelium-denuded arteries, pre-incubation with charybdotoxin, an Ca2+-activated K+ channel (BKCa channel) blocker, significantly attenuated Yoda1-induced relaxation in db-/db- mice, while there was no effect in control mice. Co-immunofluorescence staining showed co-localization of Piezo1 and BKCa channel was more pronounced in db-/db- mice than in control mice. These results indicate that the vascular responses induced by Piezo1 activation are different in the mesenteric resistance arteries in type 2 diabetic mice.

Alzheimer's disease diagnosis in the metaverse.

BACKGROUND AND OBJECTIVE: The importance of early diagnosis of Alzheimer's Disease (AD) is by no means negligible because no cure has been recognized for it rather than some therapies only lowering the pace of progression. The research gap reveals information on the lack of an automatic non-invasive approach toward the diagnosis of AD, in particular with the help of Virtual Reality (VR) and Artificial Intelligence. Another perspective highlights that current VR studies fail to incorporate a comprehensive range of cognitive tests and consider design notes for elderlies, leading to unreliable results. METHODS: This paper tried to design a VR environment suitable for older adults in which three cognitive assessments namely: ADAS-Cog, Montreal Cognitive Assessment (MoCA), and Mini Mental State Exam (MMSE), are implemented. Moreover, a 3DCNN-ML model was trained based on the corresponding cognitive tests and Magnetic Resonance Imaging (MRI) with different modalities using the Alzheimer's Disease Neuroimaging Initiative 2 (ADNI2) dataset and incorporated into the application to predict if the patient suffers from AD. RESULTS: The model has undergone three experiments with different modalities (Cognitive Scores (CS), MRI images, and CS-MRI). As for the CS-MRI experiment, the trained model achieved 97%, 95%, 95%, 96%, and 94% in terms of precision, recall, F1-score, AUC, and accuracy respectively. The considered design notes were also assessed using a new proposed questionnaire based on existing ones in terms of user experience, user interface, mechanics, in-env assistance, and VR induced symptoms and effects. The designed VR system provided an acceptable level of user experience, with participants reporting an enjoyable and immersive experience. While there were areas for improvement, including graphics and sound quality, as well as comfort issues with prolonged HMD use, the user interface and mechanics of the system were generally well-received. CONCLUSIONS: The reported results state that our method's comprehensive analysis of 3D brain volumes and incorporation of cognitive scores enabled earlier detection of AD progression, potentially allowing for timely interventions and improved patient outcomes. The proposed integrated system provided us with promising insights for improvements in the diagnosis of AD using technologies.

Solving water scarcity challenges in arid regions: A novel approach employing human-based meta-heuristics and machine learning algorithm for groundwater potential mapping.

Addressing water scarcity challenges in arid regions is a pressing concern and demands innovative solutions for accurate groundwater potential mapping (GPM). This study presents a comprehensive evaluation of advanced modeling techniques to enhance the precision of GPM. This study, conducted in the Zayandeh Rood watershed, Iran, employed a spatial database comprising 16 influential factors on groundwater potential and data from 175 wells. This study introduced an innovative approach to GPM by enhancing the Random Forest (RF) algorithm. This enhancement involved integrating three metaheuristic algorithms inspired by human behavior: ICA (Imperialist Competitive Algorithm), TLBO (Teaching-Learning-Based Optimization), and SBO (Student Psychology Based Optimization). The modeling process used 70% training data and 30% evaluation data. Data preprocessing was performed using the multicollinearity test method and frequency ratio (FR) technique to refine the dataset. Subsequently, the GPM was generated using four distinct models, demonstrating the combined power of machine learning and human-inspired metaheuristic algorithms. The performance of the models was systematically assessed through extensive statistical analyses, including root mean squared error (RMSE), mean absolute error (MAE), area under the curve (AUC) for the receiver operating characteristic curve (ROC), Friedman tests, chi-squared tests, and Wilcoxon signed-rank tests. RF-ICA and RF-SPBO emerged as frontrunners, displaying statistically comparable accuracy and significantly outperforming RF-TLBO and the non-optimized RF model. The results of the GPM revealed the exceptional accuracy of RF-ICA, which exhibited a commanding AUC score of 0.865, underscoring its superiority in discriminating between different groundwater potential classes. RF-SPBO also displayed strong performance with an AUC of 0.842, highlighting its effectiveness in inaccurate classification. RF-TLBO and the non-optimized RF model achieved AUC values of 0.813 and 0.810, respectively, indicating comparable performance. The outcomes of this study provide valuable insights for policymakers, offering a robust framework for tackling water scarcity challenges in arid regions through precise and reliable groundwater potential assessments.