Search Results (184)

Central nervous system (CNS) disorders such as neurodegenerative diseases, multiple sclerosis, or even brain ischemia represent major therapeutic challenges with limited effective treatments. The sigma-1 receptor (S1R), a unique ligand-operated molecular chaperone enriched at mitochondria-associated membranes, has emerged as a promising drug target due to its role in neuroprotection and neuroinflammation. Building upon our previously identified S1R ligand (compound 1), we designed and synthesized six novel benzamide derivatives through pharmacomodulation to optimize affinity, selectivity, and safety profiles. Among these, compound 2 demonstrated superior S1R affinity, improved selectivity over the sigma-2 receptor (S2R), and favorable ADME properties, including enhanced permeability and markedly reduced in vitro cardiac toxicity compared to the lead compound. Functional assays confirmed the agonist activity of key derivatives, while safety evaluations revealed low cytotoxicity and minimal off-target receptor interactions. Collectively, these findings support compound 2 as a promising candidate for further preclinical development in S1R-related CNS disorders. Full article

Age-related macular degeneration (AMD) is a common eye disease that significantly affects daily activities and impedes the quality of life in aging adults, yet effective treatments to halt or reverse disease progression are currently lacking. Ongoing research aims at understanding the complex mechanisms underlying AMD pathophysiology involving retinal pigment epithelium (RPE) dysfunction, drusen formation, inflammation, neovascularization, and RPE/photoreceptor degeneration. Sigma 2 receptor/transmembrane protein 97 (σ₂R/TMEM97) is a multifunctional protein implicated in cellular processes including cholesterol homeostasis, lysosome-dependent autophagy, calcium homeostasis, and integrated stress response (ISR). Recent genome-wide association studies (GWASs) have identified σ₂R/TMEM97 as a novel genetic risk factor strongly associated with AMD development. In this review, we summarize recent research progress on σ₂R/TMEM97 in age-related neurodegenerative diseases, highlighting its implication as a molecular target in AMD via regulating oxidative stress, inflammation, lipid uptake, drusen formation, and epithelial–mesenchymal transition (EMT). We also discuss the potential of modulating σ₂R/TMEM97 function with novel small-molecule drugs as a promising treatment for dry AMD and the unresolved questions in understanding the mechanistic basis of their actions. Full article

High-precision Sea Surface Temperature (SST) prediction is critical for understanding ocean–atmosphere interactions and climate anomaly monitoring. We propose GRU_EKAN, a novel hybrid model where Gated Recurrent Units (GRUs) capture temporal dependencies and the Enhanced Kolmogorov–Arnold Network (EKAN) models complex feature interactions between SST and multivariate ocean predictors. This study integrates GRU with EKAN, using B-spline-parameterized activation functions to model high-dimensional nonlinear relationships between multiple ocean variables (including sea water potential temperature at the sea floor, ocean mixed layer thickness defined by sigma theta, sea water salinity, current velocities, and sea surface height) and SST. L2 regularization addresses multicollinearity among predictors. Experiments were conducted at 25 South China Sea sites using 2011–2021 CMEMS data. The results show that GRU_EKAN achieves a superior mean R² of 0.85, outperforming LSTM_EKAN, GRU, and LSTM by 5%, 25%, and 23%, respectively. Its average RMSE (0.90 °C), MAE (0.76 °C), and MSE (0.80 °C²) represent reductions of 31.3%, 27.0%, and 53.2% compared to GRU. The model also exhibits exceptional stability and minimal Weighted Quality Evaluation Index (WQE) fluctuation. During the 2019–2020 temperature anomaly events, GRU_EKAN predictions aligned closest with observations and captured abrupt trend shifts earliest. This model provides a robust tool for high-precision SST forecasting in the South China Sea, supporting marine heatwave warnings. Full article

Choline has been recognized as an essential nutrient involved in various physiological functions critical to human health. Adequate daily intake of choline has been established by the US National Academy of Medicine in 1998, considering choline requirements for different ages, sex differences and physiological states (e.g., pregnancy). By serving as a precursor for acetylcholine and phospholipids, choline is important for cholinergic transmission and the structural integrity of cell membranes. In addition, choline is involved in lipid and cholesterol transport and serves as a methyl donor after oxidation to betaine. Extracellular choline is transported across the cell membrane via various transport systems (high-affinity and low-affinity choline transporters) with distinct features and roles. An adequate dietary intake of choline during pregnancy supports proper fetal development, and throughout life supports brain, liver, and muscle functions, while choline deficiency is linked to disease states like fatty liver. Choline has important roles in neurodevelopment, cognition, liver function, lipid metabolism, and cardiovascular health. While its signaling role has been considered mostly indirect via acetylcholine and phosphatidylcholine which are synthesized from choline, emerging evidence supports a role for choline as an intracellular messenger acting on Sigma-1R, a non-opioid intracellular receptor. These new findings expand the cell signaling repertoire and increase the current understanding of the role of choline while warranting more research to uncover the molecular mechanisms and significance in the context of GPCR signaling, the relevance for physiology and disease states. Full article

Sigma1 receptor (S1R) and some aquaporins (AQPs) are involved in controlling oxidative stress, but only recently has their possible interaction emerged. S1R acts by interacting with proteins in the plasma membrane and organelles and AQPs by favoring the hydrogen peroxide (H₂O₂) cell removal. To date, the possible regulation of peroxiporins by S1R has not been explored. Using H₂O₂ HyPer7 biosensors and knockdown techniques, we investigated (1) the AQPs and S1R functional involvement in H₂O₂ diffusion through the plasma membrane and in the outer and inner mitochondrial membranes, and (2) the possible interaction between S1R and AQPs. Our data showed the functional involvement of different AQPs in the diffusion of H₂O₂: AQP3, AQP6, and AQP8 in the plasma membrane; AQP6 in the outer mitochondrial membrane; and AQP6 and AQP8 in the inner mitochondrial membrane. The knockdown of S1R demonstrated its involvement in the overall diffusion of H₂O₂ across the three compartments. The double knockdown of S1R and a single AQP indicated that AQP8 and AQP6 could be regulated by S1R. These findings demonstrate the coordinated role of AQPs in the mitochondria and the plasma membranes and that S1R modulates the AQP-facilitated H₂O₂ cell removal, thus controlling the oxidative status and, most likely, the oxidative stress. Full article

The envelope stress response in Escherichia coli is primarily governed by the sigma factor RpoE (σ^E), which activates protective genes upon membrane perturbation. Under non-stress conditions, σ^E is sequestered by its anti-sigma factor RseA. In this study, we identify an unexpected role for the nitric-oxide-sensing repressor NsrR in dampening σ^E activity and repressing σ^E-dependent small RNAs, including rybB, micA, and micL. Overexpression of nsrR represses transcription from σ^E-dependent promoters and phenocopies σ^E inactivation, resulting in filamentous morphology and growth defects. Conversely, ΔnsrR de-represses σ^E targets, with additive effects in rseA mutants—supporting an RseA-independent regulatory role. Time-course analysis shows NsrR represses σ^E activity, with kinetics comparable to those of RseA. While in vitro assays failed to detect robust NsrR binding to σ^E target promoters, NsrR directly interacts with σ^E in bacterial two-hybrid assays. Structural modeling using AlphaFold3 supports a plausible NsrR–RpoE interaction interface. These findings suggest that NsrR functions as a noncanonical anti-sigma-like modulator of σ^E, integrating redox and envelope stress signals to maintain membrane homeostasis. Full article

Neurosteroids pregnenolone, progesterone, allopregnanolone, and dehydroepiandrosterone have been actively studied in the last years as candidates for the treatment of neurodegenerative diseases and postinjury rehabilitation. The neuroprotective mechanisms of these neurosteroids have been shown in clinical studies of depression, epilepsy, status epilepticus, traumatic brain injury, fragile X syndrome, and chemical neurotoxicity. However, only the allopregnanolone analogs brexanolone and zuranolone have been recently approved by the FDA for the treatment of depression. The aim of this review was to evaluate whether the endogenous neurosteroids can be used in clinical practice as neuroprotectors. Neurosteroids are multitarget compounds with strong anti-inflammatory, immunomodulatory, and cytoprotective action; they stimulate the synthesis and release of BDNF and increase remyelination and regeneration. In addition to nuclear and membrane steroid hormone receptors, such as PR, mPR, PGRMC1,2, ER, AR, CAR, and PXR, they can bind to GABAA receptors, NMDA receptors, Sigma-1 and -2 receptors (σ1-R/σ2-R). Among these, mPRs, PGRMC1,2, sigma receptors, and mitochondrial proteins attract comprehensive attention because of strong binding with the P4 and DHEA, but subsequent signaling is poorly studied. Other plasma membrane and mitochondrial proteins are involved in the rapid nongenomic neuroprotective action of neurosteroids. P-glycoprotein, BCL-2 proteins, and the components of the mitochondrial permeability transition pore (mPTP) play a significant role in the defense against the injuries of the brain and the peripheral nervous system. The role of these proteins in the molecular mechanisms of action in neuroprotection and neuroinflammation has not yet been clearly established. The aspects of their participation in these pathological processes are discussed. New formulations, such as lipophilic emulsions, nanogels, and microneedle array patches, are attractive strategies to overcome the low bioavailability of these neurosteroids for the amelioration and treatment of various nervous disorders. Full article

The path-integral re-formulation due to E. Gozzi, M. Regini, M. Reuter, and W. D. Thacker of Koopman and von Neumann’s original operator formulation of a classical Hamiltonian system on a symplectic manifold M is identified as a gauge slice of a one-dimensional Alexandrov–Kontsevich–Schwarz–Zaboronsky sigma model with target $T^{*}(T\left[1\right]M\times \mathbb{R}\left[1\right])$. Full article

High-quality precipitation data are vital for hydrological research. In regions with sparse observation stations, reliable gridded data cannot be obtained through interpolation, while the coarse resolution of satellite products fails to meet the demands of small watershed studies. Downscaling satellite-based precipitation products offers an effective solution for generating high-resolution data in such areas. Among these techniques, machine learning plays a pivotal role, with performance varying according to surface conditions and algorithmic mechanisms. Using the Qinghai Lake Basin as a case study and rain gauge observations as reference data, this research conducted a systematic comparative evaluation of nine machine learning algorithms (ANN, CLSTM, GAN, KNN, MSRLapN, RF, SVM, Transformer, and XGBoost) for downscaling IMERG precipitation products from 0.1° to 0.01° resolution. The primary objective was to identify the optimal downscaling method for the Qinghai Lake Basin by assessing spatial accuracy, seasonal performance, and residual sensitivity. Seven metrics were employed for assessment: correlation coefficient (CC), root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), standard deviation ratio (Sigma Ratio), Kling-Gupta Efficiency (KGE), and bias. On the annual scale, KNN delivered the best overall results (KGE = 0.70, RMSE = 17.09 mm, Bias = −3.31 mm), followed by Transformer (KGE = 0.69, RMSE = 17.20 mm, Bias = −3.24 mm). During the cold season, KNN and ANN both performed well (KGE = 0.63; RMSE = 5.97 mm and 6.09 mm; Bias = −1.76 mm and −1.75 mm), with SVM ranking next (KGE = 0.63, RMSE = 6.11 mm, Bias = −1.63 mm). In the warm season, Transformer yielded the best results (KGE = 0.74, RMSE = 23.35 mm, Bias = −1.03 mm), followed closely by ANN and KNN (KGE = 0.74; RMSE = 23.38 mm and 23.57 mm; Bias = −1.08 mm and −1.03 mm, respectively). GAN consistently underperformed across all temporal scales, with annual, cold-season, and warm-season KGE values of 0.61, 0.43, and 0.68, respectively—worse than the original 0.1° IMERG product. Considering the ability to represent spatial precipitation gradients, KNN emerged as the most suitable method for IMERG downscaling in the Qinghai Lake Basin. Residual analysis revealed error concentrations along the lakeshore, and model performance declined when residuals exceeded specific thresholds—highlighting the need to account for model-specific sensitivity during correction. SHAP analysis based on ANN, KNN, SVM, and Transformer identified NDVI (0.218), longitude (0.214), and latitude (0.208) as the three most influential predictors. While longitude and latitude affect vapor transport by representing land–sea positioning, NDVI is heavily influenced by anthropogenic activities and sandy surfaces in lakeshore regions, thus limiting prediction accuracy in these areas. This work delivers a high-resolution (0.01°) precipitation dataset for the Qinghai Lake Basin and provides a practical basis for selecting suitable downscaling methods in similar environments. Full article

Extreme acidophiles from the Acidithiobacillia class thrive in highly acidic environments where they rely on diverse regulatory mechanisms for adaptation. These mechanisms include sigma factors, transcription factors (TFs), and transcription factor binding sites (TFBS), which control essential pathways. Comparative genomics and bioinformatics analyses identified sigma factors and TFs in Acidithiobacillia, showing similarities but key differences from reference neutrophiles. This study highlights sigma54-dependent one- and two-component systems that are crucial for survival in energy acquisition from sulfur compounds and hydrogen as well as nutrient assimilation. Furthermore, the data suggested evolutionary divergence in regulatory elements distinguishes S-oxidizing from Fe-S-oxidizing members of Acidithiobacillia. Conservation of gene clusters, synteny, and phylogenetic analyses supported the expected phenotypes in each species. Notable examples include HupR’s role in hydrogenase-2 oxidation in Fe-S-oxidizers, TspR/TspS regulation of the sulfur oxidation complex, and FleR/FleS control of flagellar motility in S-oxidizers. These regulatory mechanisms act as master controllers of bacterial activity, reflecting adaptation to distinct metabolic needs within Acidithiobacillia. Full article

Neurodegenerative disorders, such as Alzheimer’s, Parkinson’s, and Huntington’s disease, due to their multifaced and complicated nature, remain uncurable and impose substantial financial and human burdens on society. Therefore, developing new innovative therapeutic strategies is vital. In this context, drug repurposing has emerged as a promising avenue to expedite the development of treatments for these challenging conditions. One particularly compelling target in this regard is the chaperone protein sigma-1 receptor (S1R), which has garnered significant attention for its neuroprotective properties. Interestingly, several medications, including fluvoxamine (an antidepressant), dextromethorphan (a cough suppressant), and amantadine (an antiviral), which were initially developed for unrelated indications, have shown encouraging results in neurodegenerative therapy through S1R activation. These findings suggest that existing drugs in pharmacopeias can play an essential role in alleviating neurodegenerative symptoms by modulating S1R, thereby offering a faster route and cost-effective path to clinical applications compared to the de novo development of entirely new compounds. Furthermore, as a synergistic benefit, combining S1R-targeting drugs with other therapeutic agents may also improve treatment efficacy. In this review, we highlight key repurposed drugs targeting S1R and explore their mechanisms of action, shedding light on their emerging therapeutic potential in the fight against neurodegeneration. Full article

Winding deformities in distribution transformers pose significant risks to operational reliability and system safety. Frequency response analysis (FRA) is a well-established technique for identifying mechanical faults; however, its diagnostic reliability is hindered by subjectivity in interpreting response signatures. This study proposes a novel diagnostic technique, termed FRA6σ, which integrates Six Sigma (6σ) statistical tools with FRA to enable objective fault detection. The methodology employs control charts ($\overline{X}$ chart, $\overline{R}$-chart) to monitor deviations from baseline signatures and utilizes process capability indices ($C_p$ and $C_{pk}$) to quantify the severity of deviations. Three transformer cases were evaluated across five defined frequency regions (10 Hz to 2 MHz), each associated with distinct physical fault types. The FRA6σ approach successfully identified early-stage faults across all cases. In one instance, axial and radial winding deformation was detected with a $C_p$ of 1.0 and corresponding range chart violations, preceding any visible damage. Another case revealed inter-turn insulation degradation in the 100 kHz–1 MHz band with $C_{pk}$ values below 0.9, prompting immediate intervention. Compared to traditional FRA interpretation, the proposed method improved diagnostic sensitivity by 31.25% and enabled fault detection earlier based on retrospective physical inspection benchmarks. The integration of Six Sigma with FRA provides a structured, quantifiable, and repeatable approach to transformer fault diagnostics. FRA6σ enhances early detection of winding deformities and dielectric issues, offering a robust alternative to subjective analysis and supporting predictive maintenance strategies in power systems. Full article

A greenhouse trial was conducted in Southern Italy to examine the effects of foliar applications of two substances, methyl-jasmonate (MeJA) and a zeolite, on the harvest and post-harvest performance of two hydroponically grown baby leaf genotypes (leafy chicory ‘Cicoria costa rossa’; kale ‘Cavolo nero’). MeJA is a phyto-hormone primarily studied for fruit and post-harvest applications, while zeolite is typically used for pest and disease biological control. MeJA (Sigma-Aldrich Merck KGaA, Darmstadt, Germany), and a commercial zeolite (Big-Zeo, Agricola Internazionale s.r.l., Pisa, Italy) (BigZeo) were sprayed twice at the second and fourth true leaf stages (BigZeo, 5 kg ha⁻¹; MeJA, 250 µM). Bio-physiological (yield, dry matter DM, chlorophyll CHL, weight loss WL) and qualitative (nitrate, carotenoids, phenols, flavonoids, anthocyanins, antioxidant activity) traits were evaluated in both raw and fresh-cut (7 day-cold-stored) products. Treatments did not significantly affect yield (1.0 kg m⁻²), while plant responses to the substances concerning other traits were genotype-dependent. MeJA enhanced greenness (CHL), texture (DM), and antioxidant activity (by increasing carotenoids and flavonoids) in chicory. In contrast, zeolite improved greenness, texture, and antioxidant activity (by increasing carotenoids, anthocyanins, and phenols), and reduced nitrate in kale. Treatments did not affect weight loss (2.2 g 100 g⁻¹ f.w., on average). After 7 days of storage, MeJA-treated chicory and zeolite-treated kale exhibited improved textural and nutritional quality. Full article

In this paper, based on the Weibull Inverse Power Law, we present a methodology to determine the following: (1) the failure percentiles, referred to as the P–S–N field, of an S–N curve for a 42CrMo4 steel material exhibiting bilinear ($s_1 \mathrm{and} s_2)$ behavior (e.g., a competence failure mode); (2) the Weibull family that characterizes the entire bilinear behavior; and (3) the zero-vibration test plan that meets the required vibration reliability index of $R\left(t\right)=0.97$ with a reliability confidence level of $CL=0.75$. From the application, based on the formulated normal–Weibull relationship, we determine the failure percentiles for the normal (one, two, and three) sigma levels, as well as those failure percentiles corresponding to the capability ($Cp$) and ability ($Cpk$) indices. Finally, we present the formulation to determine the $R\left(t\right)$ index and the $CL$ level associated with each normal percentile, along with their numerical values. Full article

Sigma receptors (σRs) represent very attractive biological targets for the development of potential agents for the treatment of several neurological disorders. In the search for new small molecule drugs against neuropathic pain, we identified 2-{[2-(1-benzylpiperidin-4-yl)ethyl]amino}-6-[methyl(prop-2-yn-1-yl)amino]pyridine-3,5-dicarbonitrile (5) as a polyfunctionalized small pyridine with potent dual-target activities against acetylcholinesterase (AChE) (IC₅₀ = 13 nM) and butyrylcholinesterase (BuChE) (IC₅₀ = 3.1 µM), exhibiting high σ₁R affinity (K_i(hσ₁R) = 1.45 nM) and 290-fold selectivity over the σ₂R subtype. These results are in good agreement with those found in the molecular modeling of compound 5. This is possibly due to the preferred combination in this molecule of a linker n = 2 connecting the N-Bn-piperidine motif to the C2 pyridine, without a phenyl group at C4, and a N-Me-substituted propargyl amine in the chain located at C6. Full article