Search Results (790)

Snakebite envenomation by Bothrops species is a neglected tropical disease and a major cause of local tissue damage and disability in Latin America. Antivenom therapy is effective against systemic effects but fails to prevent local myonecrosis, inflammation, and pain. This study evaluated photobiomodulation therapy (PBMT) using infrared (808 nm) alone or in combination with red (660 nm) laser in a murine model of Bothrops leucurus envenomation. A single PBMT session was applied, and animals were evaluated at 24 and 72 h. Combined treatment significantly reduced edema, hyperthermia, plasma CK and LDH, restored nociceptive thresholds, and improved motor recovery compared with infrared alone. Principal component analysis demonstrated clustering of combined-treatment animals with negative controls, supporting a synergistic therapeutic effect. These findings highlight dual-wavelength PBMT as a promising adjunctive approach to antivenom, directly targeting local venom-induced pathology. Full article

Background/Objectives: Alzheimer’s disease (AD) exhibits clinical and biological variability. This study aimed to identify MRI-defined subtypes reflecting distinct biological pathways of neurodegeneration and cognitive decline. Methods: We applied principal component analysis followed by k-means clustering (k = 3) on volumetric MRI data from 924 participants and validated clusters using cerebrospinal fluid (CSF) biomarkers (Aβ₄₂, total tau, p-tau, CTRED, MAPres, glucose, CTWHITE). Results: Three major phenotypes emerged: (1) a tau/vascular limbic subtype with pronounced hippocampal and amygdala atrophy and elevated tau and CTRED levels; (2) a volume-preserved, low-amyloid subtype consistent with early-stage or cognitively resilient AD; and (3) a diffuse-atrophy subtype with high amyloid and tau burden and ventriculomegaly. Comparative analysis revealed progressive biological shifts from amyloid accumulation to tau aggregation and vascular compromise across these clusters. Conclusions: MRI-based clustering validated by CSF biomarkers delineates biologically meaningful AD endophenotypes. The results suggest a gradual cognitive decline driven by amyloid–tau–vascular interactions, supporting multimodal phenotyping as a practical approach for precision staging and intervention. Full article

Background and Objectives: Alzheimer’s disease (AD) and frontotemporal dementia (FTD) present overlapping clinical and neuroanatomical features, complicating early diagnosis. Therefore, this study evaluated whether EEG microstate analysis can provide reliable markers to distinguish patients with dementia from healthy controls. Materials and Methods: Resting-state EEG was recorded from 36 AD patients, 23 FTD patients, and 29 healthy controls. Preprocessing and microstate analysis were conducted using the MICROSTATELAB pipeline in EEGLAB. Clustering solutions ranging from four to seven classes were tested, with grand mean fitting and variance thresholds. Temporal parameters (duration, occurrence, and coverage) and their ratio-normalized forms were compared across groups using ANCOVA and nonparametric tests. Associations with Mini-Mental State Examination (MMSE) scores were assessed by regression analyses. Results: The four- and seven-class clustering solutions achieved high variance overlap with published microstate templates. In the four-class solution, temporal parameters of microstates B and D significantly differentiated controls from dementia groups, while in the seven-class solution, microstates C and G were the most informative. Ratio-normalized parameters improved group discrimination and were associated with MMSE scores. Conclusions: EEG microstates capture disease-related alterations in large-scale brain dynamics that differentiate patients with dementia from healthy individuals. Full article

Aim: With the intensification of population aging, the public health challenges posed by multimorbidity have become increasingly severe. This study employs bibliometric analysis to elucidate research hotspots and trends in the field of multimorbidity against the backdrop of global aging. The immediate aim is to systematically map the intellectual landscape and evolving patterns in multimorbidity research. The ultimate long-term aim is to provide a scientific basis for optimizing chronic disease prevention systems and guiding future research directions. Methods: The study adopted the descriptive research method and employed a bibliometric approach, analyzing 8129 publications related to multimorbidity from the Web of Science Core Collection. Using CiteSpace, we constructed and visualized several knowledge structures, including collaboration networks, keyword co-occurrence networks, burst detection maps, and co-citation networks within the multimorbidity research domain. Results: The analysis included 8129 articles from 2004 to 2024, published across 1042 journals, with contributions from 740 countries/regions, 33,931 institutions, and 40,788 authors. The five most frequently occurring keywords were prevalence, health, older adult, mortality, and risk. The top five contributing countries globally were the United States, the United Kingdom, Germany, China, and Spain. Five pivotal research trajectories delineate the intellectual architecture of this field: ① Evolution of Disease Cluster Management: Initial investigations (2013–2014) prioritized disease cluster coordination within general practice settings, particularly cardiovascular comorbidity management through primary care protocols and self-management strategies. ② Paradigm Shifts in Health Impact Assessment: Multimorbidity outcome research demonstrated sequential transitions—from physical disability evaluation (2013) to mental health consequences like depression (2016), culminating in current emphasis on holistic health indicators including frailty syndromes (2015–2019). ③ Expansion of Risk Factor Exploration: Analytical frameworks evolved from singular physical activity metrics (2014) toward comprehensive lifestyle-related determinants encompassing behavioral and environmental dimensions (2021). ④ Emergence of Polypharmacy Scholarship: Medication optimization studies emerged as a distinct research stream since 2016, addressing therapeutic complexities in multimorbidity management. ⑤ Frontier Investigations: Cutting-edge directions (2019–2021) feature cardiometabolic multimorbidity patterns and their dementia correlations, signaling novel interdisciplinary interfaces. Conclusions: The prevalence of multimorbidity is on the rise globally, particularly in older populations. Therefore, it is essential to prioritize the prevention of cardiometabolic conditions in older adults and to provide them with appropriate and effective health services, including disease risk monitoring and community-based chronic disease care. Full article

Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a multifactorial condition requiring multi-target therapeutic strategies beyond traditional single-marker approaches. In this work, we present a fully in silico nutraceutical screening pipeline that integrates molecular prediction, systemic aggregation, and technological design. A curated panel of ten MASLD-relevant targets, spanning nuclear receptors (FXR, PPAR-α/γ, THR-β), lipogenic and cholesterogenic enzymes (ACC1, FASN, DGAT2, HMGCR), and transport/regulatory proteins (LIPG, FABP4), was assembled from proteomic evidence. Bioactivity records were extracted from ChEMBL, structurally standardized, and converted into RDKit descriptors. Predictive modeling employed a stacked ensemble of Random Forest, XGBoost, and CatBoost with isotonic calibration, yielding robust performance (mean cross-validated ROC-AUC 0.834; independent test ROC-AUC 0.840). Calibrated probabilities were aggregated into total activity (TA) and weighted TA metrics, combined with structural clustering (six structural clusters, twelve MOA clusters) to ensure chemical diversity. We used physiologically based pharmacokinetic (PBPK) modeling to translate probabilistic profiles into minimum simulated doses (MSDs) and chrono-specific exposure (%T>IC50) for three prototype concepts: HepatoBlend (morning powder), LiverGuard Tea (evening aqueous form), and HDL-Chews (postprandial chew). Integration of physicochemical descriptors (MW, logP, TPSA) guided carrier and encapsulation choices, addressing stability and sensory constraints. The results demonstrate that a computationally integrated pipeline can rationally generate multi-target nutraceutical formulations, linking molecular predictions with systemic coverage and practical formulation specifications, and thus provides a transferable framework for MASLD and related metabolic conditions. Full article

Acute respiratory infections and other infectious diseases causing acute febrile syndrome are major public health concerns in Colombia, particularly among vulnerable populations such as the Wayuu Indigenous community in Manaure, La Guajira. To investigate their viral etiology, 55 nasopharyngeal swabs and 58 serum samples were collected from febrile Wayuu individuals in Manaure. RT-qPCR screening identified Coronavirus, Enteroviruses, Adenovirus, and Influenza A/B in respiratory samples, while no arboviruses were detected in serum. Sixteen representative samples underwent metatranscriptomic next-generation sequencing (mtNGS) using the Chan-Zuckerberg ID (CZ-ID) platform. This analysis confirmed RT-qPCR findings and additionally revealed six viral contigs related to Orthopicobirnavirus hominis. Sequencing coverage enabled the reconstruction of a consensus RdRp segment, which was phylogenetically compared with sequences from diverse hosts. The virus clustered within genogroup 1, alongside Colombian isolates linked to severe acute respiratory infection. The absence of strict host-specific clustering suggests possible interspecies transmission. These findings underscore the complementary roles of targeted and unbiased approaches: RT-qPCR detected common respiratory viruses, whereas mtNGS uncovered a virus previously unreported in this community. Overall, mtNGS emerges as a powerful tool to support viral surveillance and provide baseline evidence in indigenous populations, emphasizing the need to decentralize advanced molecular diagnostics and strengthen public health capacity in Colombia. Full article

MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology and cardiovascular disease. miR-106b-5p, a member of the miR-106b-25 cluster, has been widely studied for its oncogenic activity in various malignancies. However, its role as a direct molecular driver of anthracycline-induced cardiotoxicity has only recently been uncovered. This finding highlights new therapeutic possibilities at the intersection of oncology and cardiovascular medicine. This review outlines the dual role of miR-106b-5p as a key modulator in both tumor progression and chemotherapy-induced cardiac dysfunction. miR-106b-5p is upregulated in numerous cancers—including breast, prostate, lung, gastric, colorectal, hepatocellular, and esophageal—and promotes tumorigenesis via suppression of tumor suppressors such as PTEN, BTG3, p21, and SMAD7, leading to activation of oncogenic pathways like PI3K/AKT and TGF-β. Importantly, we present the first evidence that miR-106b-5p is significantly upregulated in the myocardium in response to doxorubicin treatment, where it drives left ventricular dysfunction by targeting PR55α, a key regulator of PP2A activity. This pathway results in cytoplasmic HDAC4 accumulation, aberrant activation of the YY1 transcription factor, and upregulation of sST2, a biomarker linked to adverse cardiac remodeling and poor prognosis. In response, we developed AM106, a novel locked nucleic acid antagomir that silences miR-106 b-5p. Preclinical studies demonstrate that AM106 restores PR55α/PP2A activity, reduces sST2 expression, and prevents structural and functional cardiac damage without compromising anti-tumor efficacy. In parallel, artificial intelligence (AI) tools could be leveraged in the future—based on established AI applications in miRNA cancer research—to accelerate the identification of miR-106b-5p-related biomarkers and guide personalized therapy selection. Our findings position miR-106b-5p as a previously unrecognized molecular bridge between cancer and doxorubicin-induced cardiotoxicity. The development of the AM106 antagomir represents a promising approach with potential clinical applicability in cardio-oncology, offering dual benefits: tumor control and cardioprotection. Coupling this innovation with AI-driven analysis of patient data may enable precision risk stratification, early intervention, and improved outcomes. miR-106b-5p thus emerges as a central therapeutic target and biomarker candidate for transforming the clinical management of cancer patients at risk for heart failure. Full article

Slaughterhouses serve as critical surveillance hubs for identifying subclinical and economically important diseases in food-producing animals. Trueperella (Arcanobacterium) pyogenes, an opportunistic pathogen commonly found on the mucous membranes of livestock, is associated with mastitis, abortion, and suppurative infections such as abscesses. In this study, we investigated 30 pig carcasses fully condemned due to vertebral osteomyelitis (VO) at two slaughterhouses in Gwangju, Republic of Korea, between November 2023 and May 2024. From abscess lesions, 11 T. pyogenes strains were isolated and characterized morphologically, biochemically, and genetically. The hemolytic exotoxin pyolysin (plo gene), a major virulence factor, was detected in five isolates (45.46%). Phylogenetic analysis of partial 16S rDNA sequences confirmed close clustering with known T. pyogenes reference strains. All 11 isolates exhibited multidrug resistance, showing resistance to 8–14 antimicrobial agents per strain. Complete resistance (11/11, 100%) was observed against amikacin (AMI), nalidixic acid (NAL), chloramphenicol (CHL), florfenicol (FFN), and trimethoprim/sulfamethoxazole (SXT). High resistance rates were also detected for erythromycin (ERY) and clindamycin (CLI) (10/11, 90.9%), ceftazidime (TAZ), ceftriaxone (AXO), ciprofloxacin (CIP) (7/11, 63.6%), and tetracycline (TET) and streptomycin (STR) (5/11, 45.5%), while gentamicin (GEN) resistance was found in three isolates (27.3%). In contrast, none of the isolates showed resistance to ampicillin, cefoxitin, or cefotaxime. These findings underscore the epidemiological value of abattoir-based monitoring in detecting emerging pathogens and tracking antimicrobial resistance. The results provide important baseline data to inform disease control strategies, guide antimicrobial stewardship, and support One Health approaches, including the development of preventive measures such as vaccines. Full article

Background and Clinical Significance: In gastric cancer, splenic metastases are found in less than 7% of cases and are usually associated with other systemic secondary determinations; much more rarely, they represent the sole secondary determination of the malignant disease. Case presentation: In this paper, we present the case of a 64-year-old patient who underwent curative surgery for gastric adenocarcinoma 10 months ago and, during oncological monitoring, was diagnosed with a splenic tumor formation with intense metabolic activity on PET-CT examination, raising suspicion of splenic metastases. The medical team observed an increase in carcinoembryonic antigen (CEA), carbohydrate antigen (CA) 19-9, and Cluster of Differentiation (CD) 276 values, along with a slight decrease in Dickkopf Related Protein 3 (DKK 3). Considering that the spleen was the only site of secondary localization of the malignant disease, the patient underwent laparoscopic splenectomy with histopathological confirmation of the presence of gastric adenocarcinoma. There are no signs of loco-regional or distant recurrence 15 months postoperatively. In patients with radical excision of gastric cancer who present only with splenic metastases, splenectomy is indicated and is associated with good disease-free survival. If other secondary manifestations of malignant gastric disease are identified or suspected, chemotherapy treatment and the wait-and-see approach are recommended, as the patient does not have a real benefit from splenectomy. Until now, there is no standard protocol for the diagnostic and therapeutic management of patients with gastric cancer and metachronous splenic metastases; thus, the development of a decision-making scheme for these situations is necessary. Conclusions: The multidisciplinary approach, including the tumor board and an infectious disease specialist, are important steps in the effective management of these cases. The role of new biological markers such as CD 276 and DKK 3 for assessing the progression of malignant disease could constitute a new direction for research. Full article

In Ecuador, the transmission of dengue has steadily increased in recent decades, particularly in coastal cities like Manta, where the conditions are favorable for the proliferation of the Aedes aegypti mosquito. The objective of this study was to model the spatial distribution of dengue transmission risk in Manta, a coastal city in Ecuador with consistently high incidence rates. A total of 148 georeferenced dengue cases from 2018 to 2021 were collected, and environmental and socioeconomic variables were incorporated into a maximum entropy model (MaxEnt). Additionally, climate and social zoning were performed using a multi-criteria model in TerrSet. The MaxEnt model demonstrated excellent predictive ability (training AUC = 0.916; test AUC = 0.876) and identified population density, sewer system access, and distance to rivers as the primary predictors. Three high-risk clusters were identified in the southern, northwestern, and northeastern parts of the city, while the coastal strip showed lower suitability due to low rainfall and vegetation. These findings reveal the strong spatial heterogeneity of dengue risk at the neighborhood level and provide operational information for targeted interventions. This approach can support more efficient surveillance, resource allocation, and community action in coastal urban areas affected by vector-borne diseases. Full article

Repairing the central nervous system (CNS) remains one of the most difficult obstacles to overcome in translational neurosciences. This is due to intrinsic growth inhibitors, extracellular matrix issues, the glial scar–form barrier, chronic neuroinflammation, and epigenetic silencing. The purpose of this review is to bring together findings from recent developments in genome editing and computational approaches, which center around the possible convergence of clustered regularly interspaced short palindromic repeats (CRISPR) platforms and artificial intelligence (AI), towards precision neuroregeneration. We wished to outline possible ways in which CRISPR-based systems, including but not limited to Cas9 and Cas12 nucleases, RNA-targeting Cas13, base and prime editors, and transcriptional regulators such as CRISPRa/i, can be applied to potentially reactivate axon-growth programs, alter inhibitory extracellular signaling, reprogram or lineage transform glia to functional neurons, and block oncogenic pathways in glioblastoma. In addition, we wanted to highlight how AI approaches, such as single-cell multi-omics, radiogenomic prediction, development of digital twins, and design of adaptive clinical trials, will increasingly be positioned to act as system-level architects that allow translation of complex datasets into predictive and actionable therapeutic approaches. We examine convergence consumers in spinal cord injury and adaptive neuro-oncology and discuss expanse consumers in ischemic stroke, Alzheimer’s disease, Parkinson’s disease, and rare neurogenetic syndromes. Finally, we discuss the ethical and regulatory landscape around beyond off-target editing and genomic stability of CRISPR, algorithmic bias, explainability, and equitable access to advanced neurotherapies. Our intent was not to provide a comprehensive inventory of possibilities but rather to provide a conceptual tool where CRISPR acts as a molecular manipulator and AI as a computational integrator, converging to create pathways towards precision neuroregeneration, personalized medicine, and adaptive neurotherapeutics that are ethically sound. Full article

Neuromuscular diseases (NMDs) like Duchenne muscular dystrophy (DMD), limb–girdle muscular dystrophy (LGMD), and amyotrophic lateral sclerosis (ALS) are rare, progressive disorders with complex molecular mechanisms. Traditional transcriptomic analyses often struggle to capture systems-level dysregulation, especially given the small sample sizes typical of rare disease studies. Our differential expression analysis of eight public RNA-seq datasets from various cell types in DMD, LGMD, and ALS revealed not only disease-relevant pathways but also unexpected enrichments, such as renal development, suggesting systemic impacts beyond muscle tissue. To address limitations in capturing broader molecular mechanisms, we applied an integrative systems biology approach combining differential expression data, protein–protein interaction (PPI) networks, and network embedding techniques. Comparative functional enrichment revealed shared pathways, including glycosaminoglycan binding in both DMD and FUS-related ALS, implicating extracellular matrix–protein interactions in FUS mutation effects. Mapping DEGs onto the human PPI network and assessing their proximity to causal genes uncovered dysregulated non-coding RNAs, such as PAX8-AS1, SBF2-AS1, and NEAT1, potentially indicating common regulatory roles. We also found candidate genes within disease-proximal clusters, like HS3ST3A1, which may contribute to pathogenesis. Overall, this integrative approach reveals shared transcriptional programs and novel targets, advancing our understanding and potential treatment strategies for NMDs. Full article

Background/Objectives: Type 2 diabetes (T2D) is a clinically and genetically heterogeneous disease. In this study, we aimed to stratify patients with T2D from the Volga-Ural region of Eurasia into distinct subgroups based on clinical characteristics and to investigate the genetic underpinnings of these clusters. Methods: A total of 254 Tatar individuals with T2D and 361 ethnically matched controls were recruited. Clinical clustering was performed using k-means and hierarchical algorithms on five variables: age at diagnosis, body mass index (BMI), glycated hemoglobin (HbA1c), insulin resistance (HOMA-IR), and β-cell function (HOMA-B). Genetic association analysis was conducted using logistic regression under an additive model, adjusted for age and sex, and corrected for multiple comparisons using the Benjamini–Hochberg method. Results: Four distinct T2D subtypes were identified—mild age-related diabetes (MARD, n = 25), mild obesity-related diabetes (MOD, n = 72), severe insulin-resistant diabetes (SIRD, n = 66), and severe insulin-deficient diabetes (SIDD, n = 52)—each with unique clinical and comorbidity profiles. SIDD patients exhibited the highest burden of microvascular complications and lowest estimated glomerular filtration rate. Nine genetic variants showed significant associations with T2D and/or specific subtypes, including loci in genes related to neurotransmission (e.g., HTR1B, CHRM5), appetite regulation (NPY2R), insulin signaling (TCF7L2, PTEN), and other metabolic pathways. Some variants demonstrated subtype-specific associations, underscoring the genetic heterogeneity of T2D. Conclusions: Our findings support the utility of clinical clustering in uncovering biologically and clinically meaningful T2D subtypes and reveal genetic variants that may contribute to this heterogeneity. These insights may inform future precision medicine approaches for T2D diagnosis and management. Full article

Chimeric Antigen Receptor (CAR)-T cell therapy has transformed the treatment landscape of cancer, yet major challenges remain in enhancing efficacy, reducing adverse effects, and expanding accessibility. Autologous CAR-T cells, derived from individual patients, have achieved remarkable clinical success in hematologic malignancies; however, their highly personalized nature limits scalability, increases costs, and delays timely treatment. Allogeneic CAR-T cells generated from healthy donors provide an “off-the-shelf” alternative but face two critical immune barriers: graft-versus-host disease (GvHD), caused by donor T-cell receptor (TCR) recognition of host tissues, and host-versus-graft rejection, mediated by recipient immune responses against donor HLA molecules. Recent advances in genome engineering, particularly Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9, allow precise modification of donor T cells to overcome these limitations. For example, TRAC gene knockout eliminates TCR expression, preventing GvHD, while disruption of HLA molecules reduces immunogenicity without impairing cytotoxicity. Beyond hematologic cancers, CRISPR-edited allogeneic CAR-T cells targeting the NKG2D receptor have shown promise in preclinical studies and early-phase trials. NKG2D CAR-T cells recognize stress ligands (MICA/B, ULBP1–6) expressed on over 80% of diverse solid tumors, including pancreatic and ovarian cancers, thereby broadening therapeutic applicability. Nevertheless, the genomic editing process carries risks of off-target effects, including potential disruption of tumor suppressor genes and oncogenes, underscoring the need for stringent safety and quality control. This review examines the distinguishing features of allogeneic versus autologous CAR-T therapy, with a particular focus on NKG2D-based allogeneic CAR-T approaches for solid tumors. We summarize current strategies to mitigate immune barriers, discuss practical manufacturing challenges, and analyze available clinical data on NKG2D CAR-T trials. Collectively, these insights underscore both the promise and the hurdles of developing safe, universal, and scalable allogeneic CAR-T therapies for solid malignancies. Full article

Background/Objectives: Large-scale bibliometric assessments of psoriasis pharmacotherapy research remain limited despite significant research output in this rapidly evolving field. This study aimed to map the evolution of systemic psoriasis therapy research over five decades and demonstrate how systematic analysis of research trajectories can illuminate the transformation of specialized medical fields into central components of precision medicine. Methods: A comprehensive bibliometric analysis was conducted using Web of Science Core Collection as the single data source, examining 19,284 publications spanning 1975–2025. The methodology employed AI-enhanced terminology normalization for standardizing pharmaceutical nomenclature, VOSviewer version 1.6.20 for network visualization, and Bibliometrix package for temporal trend analysis and thematic evolution mapping. International collaboration networks, thematic evolution across three distinct periods (1975–2000, 2001–2010, 2011–2025), and citation impact patterns were systematically analyzed. Results: Four distinct developmental phases were identified, with publications growing from 9 articles in 1975 to 1638 in 2024. The United States dominated research output with 5959 documents, while Canada achieved the highest citation efficiency at 62.65 citations per document. Global collaboration encompassed 70 countries organized into four regional clusters, with a 28-nation Asia–Pacific–Africa–Middle East alliance representing the largest collaborative group. Citation impact peaked during 2001–2008, coinciding with revolutionary biological therapy introduction. Thematic evolution demonstrated systematic transformation from two foundational themes to nine specialized domains, ultimately consolidating into four core areas focused on targeted therapeutics and evidence-based methodologies. Keyword analysis demonstrated progression from basic immunological studies to sophisticated targeted interventions, evolving from tumor necrosis factor alpha inhibitors to contemporary interleukin-17/interleukin-23 pathway targeting and Janus kinase inhibitors. Conclusions: Over five decades, psoriasis therapeutics research has shifted from a niche dermatological discipline to a central model for innovation in immune-mediated diseases. This evolution illustrates how bibliometric approaches can capture the dynamics of scientific transformation, offering strategic insights for guiding pharmaceutical innovation, shaping research priorities, and informing precision medicine strategies across inflammatory conditions. Full article