Search Results (7,966)

Background: Two natural steroids derived from cholesterol pathways are testosterone and progesterone, androgen and antiandrogen receptor binding. Steroid androgen antagonists can be prescribed to treat an array of diseases and disorders such as gender dysphoria. In men, androgen antagonists are frequently used to treat prostate cancer and hyperplasia. Sex hormones regulate the expression of the viral receptors in COVID-19 progression, and these hormones may act as a metabolic signal-mediating response to changes in glucose and Reactive Oxygen Species (ROS). The objective of the present study is to use artificial intelligence (AI) applications in healthcare to predict the targets and to assess biological assays of novel steroid derivatives prepared in house from the commercially available 16-dehydropregnenolone acetate (DPA^®) aimed at achieving the metabolic stability of glucose and steroid brain homeostasis. This suggests the introduction of aromatic or aliphatic structures in the steroid B-ring and D-ring. This is important since the roles of 5α-reductase and ROS in brain control of glucose and novel steroids homeostasis remain unclear. Methods: A tool prediction was used as a tuned algorithm, with the novel steroid derivatives data in web interface to carry out their pharmacological evaluation. The new steroidal derivatives were determined with neuroprotection effect using the select biomarkers of oxidative stress on induced hypoglycemic male rat brain and liver. The enzyme kinetics was established by the inhibition of the 5α-reductase enzyme on the brain myelin. Results: We used novel chemical structures to order the information of a Swiss data bank that allow target predictions. Biological assays suggest that steroid derivatives with an electrophilic center can interact more efficiently with the 5α-reductase enzyme, and by this way, induce neuroprotection in hypoglycemia model. All compounds were synthesized with a yield of 30–80% and evaluated with tool target prediction to understand the molecular mechanisms underlying a given phenotype or bioactivity and to rationalize possible favorable or unfavorable side effects, as well as to predict off-targets of known molecules and to clear the way for drug repurposing. Apart, they turned out to be good inhibitors for the 5α-reductase enzyme. Conclusions: The probed efficacy of these novel steroids with respect to spironolactone control appears to be a promising compound for future hormonal therapy with neuroprotection activity in glucose disorder status. However, further research with clinically meaningful endpoints is needed to optimize the use of androgen antagonists in these hormonal therapies in COVID-19 progression. Full article

Background/Objectives: Myotonic dystrophy type 1 (DM1) is a rare, multisystemic disorder caused by an expanded (CTG)n repeat in the DMPK gene. Although DM1 has been studied in several populations, access to molecular diagnosis and comprehensive care remains limited in many low- and middle-income countries. This study provides an updated overview of DM1 in Mexico, from diagnostic implementation to patient management, describing key clinical and genetic findings. Methods: We conducted a nationwide, 15-year prospective study at Mexico’s National Reference Center for neuromuscular diseases. A total of 853 individuals at risk were subjected to clinical and molecular evaluation using PCR, TP-PCR, and SP-PCR, encompassing symptomatic, pre-symptomatic, prenatal, and preimplantation genetic diagnosis. Socioeconomic, clinical, and molecular variables were analyzed. Results: A total of 488 individuals were confirmed as DM1 carriers, with the most prevalent phenotypes being classic (36.5%) and juvenile (28.5%). Genomic analysis revealed a correlation between CTG tract sizes and phenotypes. Intriguingly, interrupted CTG repeat tracts were identified in 2.8% of DM1 carriers, who exhibited milder clinical phenotypes and a reduced degree of somatic and intergenerational instability. Survival analysis revealed a reduction in symptom-free survival in patients with larger expansions, while interrupted CTG tracts were associated with delayed onset. Conclusions: The centralization of diagnostic services in Mexico resulted in regional disparities, impacting early diagnosis and family planning. This study highlights the clinical and molecular diversity of DM1 in a Latin American population and underscores the urgent need for decentralized diagnostic services, integrated care models, and tailored prognostic tools in underserved settings. Full article

Celiac disease (CeD) is an immune-mediated enteropathy triggered by gluten in genetically susceptible individuals, with a heterogeneous clinical spectrum spanning classical gastrointestinal symptoms, extraintestinal manifestations, and subclinical forms. We synthesize contemporary epidemiology, immunopathogenesis, and the updated 2025 European Society for the Study of Coeliac Disease diagnostic framework. Adaptive responses to deamidated gliadin peptides presented by human leukocyte antigen (HLA)-DQ2/DQ8, together with interleukin-15-driven activation of intraepithelial lymphocytes (IELs), culminate in villous atrophy, crypt hyperplasia, and increased IELs. Serology centered on tissue transglutaminase immunoglobulin A (tTG-IgA) with total immunoglobulin A assessment remains first-line, complemented by standardized duodenal sampling (≥4 distal + 2 bulb biopsies) and selective HLA typing. The guidelines conditionally endorse a no-biopsy pathway for adults <45 years with tTG-IgA ≥10× upper limit of normal confirmed on a second sample, emphasizing shared decision-making and exclusion of red flags. We delineate differential diagnoses (tropical sprue, Crohn’s disease, common variable immunodeficiency, small intestinal bacterial overgrowth) and contrast CeD with non-celiac gluten sensitivity, which lacks villous atrophy, disease-specific serology, and HLA association. Emerging tools (immunohistochemistry, CD3/CD8/γδ IELs, video capsule endoscopy, confocal laser endomicroscopy) and the limitations of salivary/fecal assays are reviewed. Early detection improves quality of life and reduces healthcare utilization. Future directions include artificial intelligence-assisted imaging, molecular immunophenotyping, and non-dietary therapeutics. Full article

Background and Objectives: Grade 4 adult-type diffuse gliomas remain the most aggressive primary central nervous system malignancies, with limited prognostic tools beyond molecular classification. This study introduces the HALLMOUNT score, a multidimensional prognostic index integrating hematologic, biochemical, and clinical parameters to capture the interplay between tumor biology and systemic host response. Materials and Methods: A total of 227 patients with histologically confirmed grade 4 adult-type diffuse glioma were retrospectively analyzed. The HALLMOUNT score incorporated nine pretreatment variables: hemoglobin, albumin, lactate dehydrogenase (LDH), lymphocyte, monocyte, Eastern Cooperative Oncology Group (ECOG) performance status, uric acid, neutrophil, and thrombocyte counts. Receiver operating characteristic (ROC) analyses determined optimal cut-offs, and Cox regression models evaluated prognostic performance for overall (OS) and progression-free survival (PFS). Results: High HALLMOUNT scores (≥2.5) were significantly associated with older age, comorbidities, poor ECOG status, isocitrate dehydrogenase (IDH)-wild phenotype, lower resection rates, and reduced treatment responses. ROC analysis showed predictive accuracy comparable to CAR and PIV (AUC = 0.650). High scores independently predicted inferior OS (HR = 2.78, p < 0.001) and PFS (HR = 2.76, p < 0.001). Conclusions: The HALLMOUNT score provides a simple, cost-effective, and biologically grounded biomarker reflecting both tumor aggressiveness and host vulnerability. It enables refined risk stratification, supports individualized therapeutic planning, and warrants prospective validation in molecularly defined and multicenter cohorts. Full article

Sansevieria, a perennial herb known for its ornamental and medicinal value, has many varieties due to its leaf size and stripe color. However, it is very difficult to distinguish them during the seedling stage. In this study, we conducted chloroplast genome sequencing analysis on 10 cultivars of Sansevieria trifasciata. The chloroplast genomes exhibited a typical quadripartite circular structure (154.2–158.7 kb), encoding 113 functional genes with highly conserved gene order. Phylogenetic analysis supported the evolutionary linkage between Sansevieria and Dracaena. Dynamic inverted repeats (IR) boundary expansions/contractions, particularly species-specific patterns in ndhF and rps19 gene distributions across IR junctions, indicating its adaptive divergence. We also discovered the trnT-psbD marker, which is a deletion marker developed from hypervariable regions and can effectively distinguish closely related species. This work provides critical molecular tools and theoretical foundations for germplasm identification, phylogenetic reconstruction, and chloroplast genome evolution in Sansevieria, and also promotes taxonomic revisions in Asparagaceae. Full article

Beetles (Coleoptera) represent one of the most diverse insect groups and play vital ecological roles, yet their accurate identification is often challenging due to morphological similarities among taxa. DNA barcoding has emerged as a powerful and reliable tool for species-level identification and biodiversity monitoring. In this study, we established a local DNA barcode reference database for beetles in the Liancheng Nature Reserve, Gansu Province, China. From May to August 2024, beetle specimens were collected and identified using both morphological traits and DNA barcoding. Three species delimitation methods—Automatic Barcode Gap Discovery (ABGD), Assemble Species by Automatic Partitioning (ASAP), and Bayesian Poisson Tree Processes (bPTP)—were employed as complementary analytical tools, and phylogenetic relationships were inferred from cytochrome c oxidase subunit I (COI) sequences. A total of 164 COI sequences (650 bp) were obtained, representing 126 beetle species from 95 genera and 20 families. DNA barcoding successfully resolved morphologically ambiguous taxa, with many sequences reported here for the first time. Phylogenetic analysis revealed that species within the same genus formed cohesive clades before clustering at the family level, confirming the species-level discriminative power of the COI gene. Collectively, these findings demonstrate that COI-based DNA barcoding is a powerful complement to traditional taxonomy. The establishment of this preliminary reference database provides a valuable molecular resource for beetle identification and a practical tool to support biodiversity conservation, resource management, and long-term monitoring in the Liancheng Nature Reserve. Full article

Background and Clinical Significance: DNA methylation profiling has revolutionized the classification of central nervous system (CNS) tumors, providing insights into tumor prognosis, recurrence, and personalized treatments. However, a significant challenge remains in classifying rare or molecularly undefined high-grade gliomas (HGGs) that fail to match existing methylation reference classes. This study evaluates the clinical, histopathological, and molecular characteristics of three unclassifiable cases through a retrospective analysis. Methylation profiling was performed by the National Institute of Health based on the 11b6 and 12b6 of the Heidelberg classifier, as well as the National Cancer Institute/Bethesda classifier. The cases were evaluated for histopathological features, molecular markers, and clinical outcomes. Case Presentation: We present three adult patients with histologically confirmed HGGs that were unclassifiable by standard DNA methylation profiling. All patients presented with diverse clinical and radiographic findings. Histopathological examination confirmed high-grade glial neoplasms in each case. However, methylation profiling failed to yield clear matches for any known class. Instead, profiling suggested indeterminate IDH-wildtype neoplasms with aggressive clinical courses. Following treatment, one patient experienced disease progression and died, while the other two remained without evidence of recurrence at follow-up. Conclusions: These cases underscore the persistent diagnostic challenges posed by CNS tumors that are unclassifiable by current DNA methylation, highlighting the urgent need for expanded reference datasets. While methylation profiling has transformed the field of tumor diagnostics, its limitations still exist. Enhanced collaboration to broaden diagnostic categories is essential to broaden diagnostic classifiers. Until these tools are refined, integration of clinical, histological, and molecular findings is imperative to optimize patient management, improve classification accuracy, and optimize therapeutic outcomes. Unclassifiable HGGs represent a critical gap in CNS tumor diagnostics. Addressing this requires global collaboration to enrich methylation databases. In the interim, a multimodal diagnostic strategy remains essential for the management of these challenging tumors. Full article

Ester-based lubricants have been widely used owing to their excellent overall performance. In this study, the quantitative structure–property relationship (QSPR) approach was combined with molecular descriptors, a genetic algorithm (GA), and an artificial neural network (ANN) to systematically predict the key properties—kinematic viscosity at 40 °C and 100 °C, viscosity index, pour point, and flash point—of 64 diester-based lubricants. Quantum chemical calculations were first performed to obtain the equilibrium geometries and electronic information of the molecules. Geometry optimizations and frequency analyses were carried out using the Gaussian 16 software at the B3LYP/6-31G (d, p) level, providing a reliable foundation for molecular descriptor computation. Subsequently, topological, geometrical, and electronic descriptors were calculated using the RDKit toolkit, and the optimal feature subsets were selected by GA and used as ANN inputs for property prediction. The results showed that the ANN models exhibited good performance in predicting viscosity and flash point, with R² values of 0.9455 and 0.8835, respectively, indicating that the ANN effectively captured the nonlinear relationships between molecular structure and physicochemical properties. In contrast, the prediction accuracy for pour point was relatively lower (R² = 0.6155), suggesting that it is influenced by complex molecular packing and crystallization behaviors at low temperatures. Overall, the study demonstrates the feasibility of integrating quantum chemical calculations with the QSPR–ANN framework for lubricant property prediction, providing a theoretical basis and data-driven tool for molecular design and performance optimization of ester-based lubricants. Full article

Non-invasive brain stimulation (NIBS) techniques—including repetitive transcranial magnetic stimulation (rTMS), theta-burst stimulation (TBS), paired associative stimulation (PAS), transcranial direct current stimulation (tDCS), and transcranial alternating current stimulation (tACS)—have emerged as valuable tools for modulating neural activity and promoting plasticity. Traditionally, their effects have been interpreted within a binary framework of long-term potentiation (LTP)-like and long-term depression (LTD)-like plasticity, largely inferred from changes in motor evoked potentials (MEPs). However, existing models do not fully capture the complexity of the biological processes engaged by these techniques and despite extensive clinical application, the cellular and molecular mechanisms underlying NIBS remain only partially understood. This systematic review, conducted in accordance with the PRISMA 2020 guidelines, synthesizes evidence from in vivo, in vitro, and ex vivo studies to delineate how NIBS influences neurotransmission through intracellular signaling, gene expression, and protein synthesis at the cellular level. Emphasis is placed on the roles of classical synaptic models, grounded in Ca²⁺-dependent glutamatergic signaling and receptor phosphorylation dynamics, as well as broader forms of plasticity involving BDNF–TrkB signaling, epigenetic modifications, neuroimmune and glial interactions, anti-inflammatory pathways, and apoptosis- and survival-related cascades. By integrating findings in humans with those in animal and cellular models, we identify both shared and technique-specific molecular mechanisms underlying NIBS-induced effects, highlighting emerging evidence for multi-pathway, non-binary plasticity mechanisms. Understanding these convergent pathways provides a mechanistic foundation for refining stimulation paradigms and improving their translational relevance for treatment of neurological and psychiatric disorders. Full article

It is difficult to achieve ultra-precision machining (UPM) on semiconductor materials like single-crystal silicon because of their hardness and brittleness. To solve this issue, numerous field-assisted machining systems and their combinations have been suggested and developed. However, the difficulty in directly observing the physical variables limits our comprehension of the in-depth machining mechanisms of field-assisted machining. In this work, we investigated the machining mechanism of single-crystal silicon under the combination of laser heating and tool vibration using molecular dynamics (MD) simulations. The effect of tool vibration trajectory determined by different tool edge radii is discussed under the condition of raising temperature. The simulation results indicate that the surface morphology is closely related to vibration and heating parameters. Raising the cutting temperature causes a reversed relation between tool edge radius and surface roughness. While the subsurface damage and internal stress are also determined by the tool edge radius and cutting temperature. The findings in this simulation could help to improve the understanding of machining mechanics in multi-field-assisted machining. Full article

Low temperatures have a significant impact on the growth, development, and productivity of cucumber plants. The potential of near-infrared spectroscopy and the aquaphotomics approach for investigating chilling stress was studied in Voreas F1 and Gergana cultivars. Changes in the spectral patterns of cucumber plants were compared with physiological and metabolic data. Voreas plants were unable to survive seven days of low-temperature stress due to a drastic increase in electrolyte leakage and a decrease in the net photosynthesis rate, stomatal conductance, and transpiration rate. Gergana plants survived chilling by preserving cell membrane integrity and photosynthesis efficiency. During chilling treatment, the content of most metabolites in both cultivars was reduced compared to the controls, yet it was much more pronounced in Voreas. We observed an increased accumulation of cinnamic acid on the seventh day only in the Gergana cultivar. A MicroNIR spectrometer was used for in vivo spectral measurements of cotyledons and the first two leaves. Differences in absorption spectra were observed among control, stressed, and recovered plants, across different days of stress, and between the studied cultivars. The most significant differences were in the 1300–1600 nm range, much smaller for Gergana than Voreas. Aquagrams of the two cultivars also reveal differences in their responses to low temperatures and changes in water molecular structure in the leaves. The errors of prediction for the days of chilling by using PLS models were from 0.96 to 1.14 days for independent validation, depending on the spectral data of different leaves used. Near-infrared spectroscopy and aquaphotomics can be used as additional tools for early detection of stress and investigation of low-temperature tolerance in cucumber cultivars. Full article

Breast cancer is a substantial and growing public health issue in India, with epidemiological data demonstrating distinct and often severe disease characteristics in contrast to Western countries. Contrary to the global trend, Indian women frequently develop the disease at an earlier age and tend to present with more advanced stages, emphasizing important variations in disease pathophysiology. This review compiles and critically evaluates the current literature to describe the specific pathophysiology of breast cancer in the Indian population. We investigate the unique cellular and molecular landscapes, evaluate the impact of specific Indian demographic and genetic features, and highlight crucial gaps in knowledge, diagnostic tools, and therapeutic approaches. The assessment reveals a molecular landscape determined by the incidence of specific tumor subtypes; triple-negative breast cancer, for instance, is frequently diagnosed in younger women, and genetic profiling research suggests variations in its susceptibility genes and mutation patterns when compared to global populations. While this paper brings together recent advancements, it highlights the challenges of adopting global diagnostic and treatment guidelines in the Indian healthcare system. These challenges are largely due to variances and specific demographic and socioeconomic discrepancies that create substantial hurdles for timely diagnosis and patient care. We highlight significant gaps, such as the need for more complete multi-omics profiling of Indian patient cohorts, an absence of uniform and readily available screening programs, and shortcomings in healthcare infrastructure and qualified oncology experts. Furthermore, the review highlights the crucial need for therapeutic strategies tailored to the distinct genetic and demographic profiles of Indian breast cancer patients. We present significant strategies for addressing these challenges, with a focus on integrating multi-omics data and clinical characteristics to gain deeper insight into the underlying causes of the disease. Promising avenues include using artificial intelligence and advancements in technology to improve diagnostics, developing indigenous and affordable treatment options, and establishing context-specific research frameworks for the Indian population. This review also underlines the necessity for personalized strategies to improve breast cancer outcomes in India. Full article

MLASA2 is a rare mitochondrial disorder with limited geographic representation in published medical literature. Here, we report the first confirmed case of MLASA2 in a Latin American 16-year-old male harboring a homozygous pathogenic variant p.(Asp311Glu) in the YARS2 gene. The patient presented with sideroblastic anemia and short stature, accompanied by other skeletal dysplasia features not previously associated with MLASA2, including epiphyseal dysplasia, rib edge widening, and poorly defined vertebral structures, but without lactic acidosis. Notably, the patient did not present exercise intolerance but recently exhibited reduced muscle strength. The p.(Asp311Glu) variant, located in the anticodon-binding domain of the mitochondrial tyrosyl-tRNA synthetase (Mt-TyrRS), was consistently predicted to be pathogenic by multiple in silico tools. Molecular modeling revealed that this variant destabilizes the ‘KMSKS’ motif, potentially compromising tRNA recognition fidelity and aminoacylation efficiency. Analysis of runs of homozygosity (ROH) revealed significantly elevated consanguinity (ROH: 31.93%), consistent with a consanguineous mating between biological parents. This case expands the geographic distribution of MLASA2, documents previously unreported phenotypes, suggests a novel pathogenic mechanism, and demonstrates the utility of genomic approaches for diagnosing rare mitochondrial disorders in the absence of complete clinical information and family history. Full article

Background/Objectives: Differentiating atypical lipomatous tumours (ALT) from lipomas remains challenging, as both share similar clinical and radiological features but require different forms of management. We previously proposed a clinical–radiological score integrating routine parameters to improve preoperative discrimination. This study aimed to externally validate the score in an independent cohort and refine it for enhanced robustness. Methods: We retrospectively analysed 119 patients with lipomatous tumours treated between 2022 and 2024 at an external university hospital. Diagnostic performance of the original models was assessed using receiver operating characteristic analysis. Data were then combined with the initial development cohort (n = 106) to recalibrate the models and define new cut-offs. Results: In the external validation cohort, predictive accuracy decreased compared to the derivation cohort, especially in extremity tumours assessed without contrast (AUC 0.830 vs. 0.942). Across four recalibrated models in the combined dataset (n = 225), diagnostic accuracy remained high (AUCs 0.918–0.954). Models combining clinical and imaging parameters consistently outperformed single-parameter approaches, with contrast enhancement providing the greatest incremental value. Accuracy was lower in trunk-localised tumours, highlighting the need for molecular confirmation in selected subgroups. Conclusions: The re-modelled score demonstrated robust diagnostic accuracy and practicality for routine use, offering a resource-efficient tool to support preoperative risk stratification. While molecular testing remains essential in high-risk cases, the refined score may reduce unnecessary testing and facilitate tailored diagnostic strategies. To support clinical adoption, the score is available as a web application that automatically selects the appropriate model and presents results in a colour-coded format. Full article