Search Results (7,189)

The treatment of chronic wounds is one of the most complex therapeutic problems of modern medicine. It leads to patients’ protracted recovery, generating high treatment costs. Herbal products may be useful in the treatment of chronic wounds via a wide range of pharmacological properties and multidirectional effects on the wound healing phases. The study aims to determine the ability of selected plant extracts to modulate the processes involved in wound healing. The antimicrobial (MIC, MBC, MFC) and antioxidant (ABTS, DPPH) activities, cytotoxicity (MTT test), scratch wound test, and collagen assay were tested. R. canina (MBC 0.39 mg/mL) and V. venifera (MBC 3.13 mg/mL) extracts had bactericidal activities against P. aeruginosa and S. aureus, respectively. The V. vinifera extract showed the highest antioxidant activity in both ABTS (EC50 0.078 mg/mL) and DPPH (EC50 0.005 mg/mL) methods. The percentage of wound closure observed for C. cardunculus, R. rosea, and R. canina extracts with HaCaT, and V. vinifera extract with Hs27 cells was set as 100%. V. vinifera extract (50 μg/mL) stimulated collagen synthesis 5.16 times more strongly than ascorbic acid. Our preliminary study showed that some plant extracts may be promising modulators of the wound healing process, although further in-depth studies are necessary to determine their effectiveness in the in vivo model. Full article

(1) Background: Polyploid fish are highly important in increasing fish production, improving fish quality, and breeding new varieties. The loach (Misgurnus anguillicaudatus), as a naturally polyploid fish, serves as an ideal biological model for investigating the mechanisms of chromosome doubling; (2) Methods: In this study, tetraploidization in diploid loach was induced by heat shock treatment, and, for the first time, the role of the key cell cycle gene cdk1 (cyclin-dependent kinase 1) in chromosome doubling was investigated; (3) Results: The experimental results show that when eggs are fertilized for 20 min and then subjected to a 4 min heat shock treatment at 39–40 °C, this represents the optimal induction condition, resulting in a tetraploid rate of 44%. Meanwhile, the results of the cdk1 knockout model (2n cdk1^−/−) constructed using CRISPR/Cas9 showed that the absence of cdk1 significantly increased the chromosome doubling efficiency of the loach. The qPCR analysis revealed that knockout of cdk1 significantly upregulated cyclin genes (ccnb3,ccnc, and ccne1), while inhibiting expression of the separase gene espl1 (p < 0.05); (4) Conclusions: During chromosome doubling in diploid loaches induced by heat shock, knocking out the cdk1 gene can increase the tetraploid induction rate. This effect may occur through downregulation of the espl1 gene. This study offers novel insights into optimizing the induced breeding technology of polyploid fish and deciphering its molecular mechanism, while highlighting the potential application of integrating gene editing with physical induction. Full article

Lactic acid bacteria (LAB) are central to food, feed, and health biotechnology, yet their genomes have long resisted rapid, precise manipulation. This review charts the evolution of LAB genome-editing strategies from labor-intensive RecA-dependent double-crossovers to state-of-the-art CRISPR and CRISPR-associated transposase systems. Native homologous recombination, transposon mutagenesis, and phage-derived recombineering opened the door to targeted gene disruption, but low efficiencies and marker footprints limited throughput. Recent phage RecT/RecE-mediated recombineering and CRISPR/Cas counter-selection now enable scar-less point edits, seamless deletions, and multi-kilobase insertions at efficiencies approaching model organisms. Endogenous Cas9 systems, dCas-based CRISPR interference, and CRISPR-guided transposases further extend the toolbox, allowing multiplex knockouts, precise single-base mutations, conditional knockdowns, and payloads up to 10 kb. The remaining hurdles include strain-specific barriers, reliance on selection markers for large edits, and the limited host-range of recombinases. Nevertheless, convergence of phage enzymes, CRISPR counter-selection and high-throughput oligo recombineering is rapidly transforming LAB into versatile chassis for cell-factory and therapeutic applications. Full article

The transgenic animals have been yielding invaluable insights into amyloid pathology by replicating the key features of Alzheimer’s disease (AD). However, there is no clear relationship between senile plaques and memory deficits. Instead, cognitive impairment and synaptic dysfunction are particularly linked to a rise in Aβ_1-42 oligomer level. Thus, injection of Aβ_1-42 oligomers into a specific brain region is considered an alternative approach to investigate the effects of increased soluble Aβ species without any plaques, offering higher controllability, credibility and validity compared to the transgenic model. The hippocampal CA1 (cornu ammonis 1) region is selectively affected in the early stage of AD and specific targeting of CA1 region directly links Aβ oligomer-related pathology with memory impairment in early AD. Next, the inhibitory avoidance (IA) task, a learning paradigm to assess the synaptic basis of CA1-dependent contextual learning, triggers training-dependent synaptic plasticity similar to in vitro HFS (high-frequency stimulation). Given its reliability in assessing contextual memory and synaptic plasticity, this task provides an effective framework for studying early stage AD-related memory deficit. Therefore, in this review, we will focus on why Aβ_1-42 oligomer injection is a valid in vivo model to investigate the early stage of AD and why dorsal CA1 region serves as a target area to understand the adverse effects of Aβ_1-42 oligomers on contextual learning through the IA task. Full article

Inflammatory arthritis (IA) is a chronic condition marked by joint dysfunction and pain, posing significant challenges for effective drug delivery. This study separated Perilla frutescens leaf-derived exosome-like nanovesicles (PFE) to effectively penetrate the stratum corneum barrier. These nanovesicles and indomethacin (IND) were subsequently developed into a nanogel designed for topical drug delivery systems (PFE-IND-GEL). PFE exhibited a typical vesicular structure with a mean diameter of 98.4 ± 1.3 nm. The hydrodynamic size and zeta potential of PFE-IND-GEL were 129.6 ± 5.9 nm and −17.4 ± 1.9 mV, respectively. Mechanistic investigations in HaCaT keratinocytes showed that PFE significantly downregulated tight junction proteins (ZO-1 and Occludin, p < 0.01) via modulation of the IL-17 signaling pathway, as evidenced by transcriptomic analysis. In a sodium urea crystal-induced rat IA model, the topical application of PFE-IND-GEL significantly reduced joint swelling (p < 0.05) and serum levels of inflammatory cytokines (IL-6, IL-1α, TNF-α) compared to control groups. Histopathological analysis confirmed the marked attenuation of synovial inflammation and cartilage preservation in treated animals. These findings underscore the dual role of PFE as both a topical permeation enhancer and an anti-inflammatory agent, presenting a promising strategy for managing IA. Full article

Water infiltration into soil is a key process in regulating the hydrological cycle and sustaining ecosystem services in high-Andean environments. However, limited information is available regarding its dynamics in these ecosystems. This study evaluated the influence of three types of vegetation cover and soil properties on water infiltration in a high-Andean environment. A double-ring infiltrometer, the Water Drop Penetration Time (WDPT, s) method, and laboratory physicochemical characterization were employed. Soils under forest cover exhibited significantly higher quasi-steady infiltration rates (i_s, 0.248 ± 0.028 cm·min⁻¹) compared to grazing areas (0.051 ± 0.016 cm·min⁻¹) and agricultural lands (0.032 ± 0.013 cm·min⁻¹). Soil organic matter content was positively correlated with i_s. The modified Kostiakov infiltration model provided the best overall fit, while the Horton model better described infiltration rates approaching i_s. Sand and clay fractions, along with K⁺, Ca²⁺, and Mg²⁺, were particularly significant during the soil’s wet stages. In drier stages, increased Na⁺ concentrations and decreased silt content were associated with higher water repellency. Based on WDPT, agricultural soils exhibited persistent hydrophilic behavior even after drying (median [IQR] from 0.61 [0.38] s to 1.24 [0.46] s), whereas forest (from 2.84 [3.73] s to 3.53 [24.17] s) and grazing soils (from 4.37 [1.95] s to 19.83 [109.33] s) transitioned to weakly or moderately hydrophobic patterns. These findings demonstrate that native Andean forest soils exhibit a higher infiltration capacity than soils under anthropogenic management (agriculture and grazing), highlighting the need to conserve and restore native vegetation cover to strengthen water resilience and mitigate the impacts of land-use change. Full article

To advance the development of protein-rich plant-based foods, a novel binder system for vegan sausage alternatives without the requirement of heat application was investigated. This enables long-term ripening of plant-based analogs similar to traditional fermented meat or dairy products, allowing for refined flavor and texture development. This was achieved by using a poorly water-soluble calcium source (calcium carbonate) to introduce calcium ions into a low-ester pectin—gluten matrix susceptible to crosslinking via divalent ions. The gelling reaction of pectin–gluten dispersions with Ca²⁺ ions was time-delayed due to the gradual production of lactic acid during fermentation. Firm, sliceable matrices were formed, in which particulate substances such as texturized proteins and solid vegetable fat could be integrated, hence forming an unheated raw-fermented plant-based salami-type sausage model matrix which remained safe for consumption over 21 days of ripening. Gluten as well as pectin had a significant influence on the functional properties of the matrices, especially water holding capacity (increasing with higher pectin or gluten content), hardness (increasing with higher pectin or gluten content), tensile strength (increasing with higher pectin or gluten content) and cohesiveness (decreasing with higher pectin or gluten content). A combination of three simultaneously occurring effects was observed, modulating the properties of the matrices, namely, (a) an increase in gel strength due to increased pectin concentration forming more brittle gels, (b) an increase in gel strength with increasing gluten content forming more elastic gels and (c) interactions of low-ester pectin with the gluten network, with pectin addition causing increased aggregation of gluten, leading to strengthened networks. Full article

High-quality, openly accessible clinical datasets remain a significant bottleneck in advancing both research and clinical applications within medical artificial intelligence. Case reports, often rich in multimodal clinical data, represent an underutilized resource for developing medical AI applications. We present an enhanced version of MultiCaRe, a dataset derived from open-access case reports on PubMed Central. This new version addresses the limitations identified in the previous release and incorporates newly added clinical cases and images (totaling 93,816 and 130,791, respectively), along with a refined hierarchical taxonomy featuring over 140 categories. Image labels have been meticulously curated using a combination of manual and machine learning-based label generation and validation, ensuring a higher quality for image classification tasks and the fine-tuning of multimodal models. To facilitate its use, we also provide a Python package for dataset manipulation, pretrained models for medical image classification, and two dedicated websites. The updated MultiCaRe dataset expands the resources available for multimodal AI research in medicine. Its scale, quality, and accessibility make it a valuable tool for developing medical AI systems, as well as for educational purposes in clinical and computational fields. Full article

Purpose: Predicting colorectal cancer liver metastasis (CRLM) is essential for prognostic assessment. This study aims to develop and validate an interpretable multimodal machine learning framework based on multiparametric MRI for predicting CRLM, and to enhance the clinical interpretability of the model through SHapley Additive exPlanations (SHAP) analysis and deep learning visualization. Methods: This multicenter retrospective study included 463 patients with pathologically confirmed colorectal cancer from two institutions, divided into training (n = 256), internal testing (n = 111), and external validation (n = 96) sets. Radiomics features were extracted from manually segmented regions on axial T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI). Deep learning features were obtained from a pretrained ResNet101 network using the same MRI inputs. A least absolute shrinkage and selection operator (LASSO) logistic regression classifier was developed for clinical, radiomics, deep learning, and combined models. Model performance was evaluated by AUC, sensitivity, specificity, and F1-score. SHAP was used to assess feature contributions, and Grad-CAM was applied to visualize deep feature attention. Results: The combined model integrating features across the three modalities achieved the highest performance across all datasets, with AUCs of 0.889 (training), 0.838 (internal test), and 0.822 (external validation), outperforming single-modality models. Decision curve analysis (DCA) revealed enhanced clinical net benefit from the integrated model, while calibration curves confirmed its good predictive consistency. SHAP analysis revealed that radiomic features related to T2WI texture (e.g., LargeDependenceLowGrayLevelEmphasis) and clinical biomarkers (e.g., CA19-9) were among the most predictive for CRLM. Grad-CAM visualizations confirmed that the deep learning model focused on tumor regions consistent with radiological interpretation. Conclusions: This study presents a robust and interpretable multiparametric MRI-based model for noninvasively predicting liver metastasis in colorectal cancer patients. By integrating handcrafted radiomics and deep learning features, and enhancing transparency through SHAP and Grad-CAM, the model provides both high predictive performance and clinically meaningful explanations. These findings highlight its potential value as a decision-support tool for individualized risk assessment and treatment planning in the management of colorectal cancer. Full article

In the absence of appropriate tools and a knowledge base for exploring high-grade metamorphic terrains, felsic gneiss complexes at granulite facies have long been considered barren and have remained undermapped and understudied. This was the case of the Bondy gneiss complex in the southwestern Grenville Province of Canada which consists of 1.39–1.35 Ga volcanic and plutonic rocks metamorphosed under granulite facies conditions at 1.19 Ga. Iron oxide–apatite and Cu-Ag-Au mineral occurrences occur among gneisses rich in biotite, cordierite, garnet, K-feldspar, orthopyroxene and/or sillimanite-rich gneisses, plagioclase-cordierite-orthopyroxene white gneisses, magnetite-garnet-rich gneisses, garnetites, hyperaluminous sillimanite-pyrite-quartz gneisses, phlogopite-sillimanite gneisses, and tourmalinites. Petrological and geochemical studies indicate that the precursors of these gneisses are altered volcanic and volcaniclastic rocks with attributes of pre-metamorphic Na, Ca-Fe, K-Fe, K, chloritic, argillic, phyllic, advanced argillic and skarn alteration. The nature of these hydrothermal rocks and the ore deposit model that best represents them are further investigated herein through lithogeochemistry. The lithofacies mineralized in Cu (±Au, Ag, Zn) are distinguished by the presence of garnet, magnetite and zircon, and exhibit pronounced enrichment in Fe, Mg, HREE and Zr relative to the least-altered rocks. In discrimination diagrams, the metamorphosed mineral system is demonstrated to exhibit the diagnostic attributes of, and is interpreted as, a metasomatic iron and alkali-calcic (MIAC) mineral system with iron oxide–apatite (IOA) and iron oxide copper–gold (IOCG) mineralization that evolves toward an epithermal cap. This contribution demonstrates that alteration facies diagnostic of MIAC systems and their IOCG and IOA mineralization remain diagnostic even after high-grade metamorphism. Exploration strategies can thus use the lithogeochemical footprint and the distribution and types of alteration facies observed as pathfinders for the facies-specific deposit types of MIAC systems. Full article

Central Asia (CA) faces growing Water–Energy–Food (WEF) Nexus challenges, due to its complex transboundary water management, legacy Soviet-era water infrastructure, and increasing climate and socio-economic pressures. This study presents the development of a System Dynamics Model (SDM) to evaluate WEF interdependencies across the Aral Sea Basin (ASB), including the Amu Darya and Syr Darya river basins and their sub-basins. Different downscaling strategies based on the area, population, or land use have been applied to process open-access databases at the national level in order to match the scope of the study. Climate and socio-economic assumptions were introduced through the integration of already defined Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs). The resulting SDM incorporates more than 500 variables interacting through mathematical relationships to generate comprehensive outputs to understand the WEF Nexus concerns. The SDM was successfully calibrated and validated across three key dimensions of the WEF Nexus: final water discharge to the Aral Sea (Mean Absolute Error, MAE, <5%), energy balance (MAE = 4.6%), and agricultural water demand (basin-wide MAE = 1.2%). The results underscore the human-driven variability of inflows to the Aral Sea and highlight the critical importance of transboundary coordination to enhance future resilience. Full article

Xylosyltransferase-I (XT-I) plays a crucial role in skeletal development and cartilage integrity. An XT-I deficiency is linked to severe bone disorders, such as Desbuquois dysplasia type 2. While animal models have provided insights into XT-I’s role during skeletal development, its specific effects on adult bone homeostasis, particularly in human mesenchymal stem cell (hMSC) differentiation, remain unclear. This study investigates how XT-I deficiency impacts the differentiation of hMSCs into chondrocytes, osteoblasts, and adipocytes—key processes in bone formation and repair. The aim of this study was to elucidate for the first time the molecular mechanisms by which XT-I deficiency leads to impaired bone homeostasis. Using CRISPR-Cas9-mediated gene editing, we generated XYLT1 knockdown (KD) hMSCs to assess their differentiation potential. Our findings revealed significant disruption in the chondrogenic differentiation in KD hMSCs, characterized by the altered expression of regulatory factors and extracellular matrix components, suggesting premature chondrocyte hypertrophy. Despite the presence of perilipin-coated lipid droplets in the adipogenic pathway, the overall leptin mRNA and protein expression was reduced in KD hMSCs, indicating a compromised lipid metabolism. Conversely, osteogenic differentiation was largely unaffected, with KD and wild-type hMSCs exhibiting comparable mineralization processes, indicating that critical aspects of osteogenesis were preserved despite the XYLT1 deficiency. In summary, these results underscore XT-I’s pivotal role in regulating differentiation pathways within the bone marrow niche, influencing cellular functions critical for skeletal health. A deeper insight into bone biology may pave the way for the development of innovative therapeutic approaches to improve bone health and treat skeletal disorders. Full article

Precision neurosurgery is rapidly evolving as a medical specialty by merging genomic medicine, multi-omics technologies, and artificial intelligence (AI) technology, while at the same time, society is shifting away from the traditional, anatomic model of care to consider a more precise, molecular model of care. The general purpose of this review is to contemporaneously reflect on how these advances will impact neurosurgical care by providing us with more precise diagnostic and treatment pathways. We hope to provide a relevant review of the recent advances in genomics and multi-omics in the context of clinical practice and highlight their transformational opportunities in the existing models of care, where improved molecular insights can support improvements in clinical care. More specifically, we will highlight how genomic profiling, CRISPR-Cas9, and multi-omics platforms (genomics, transcriptomics, proteomics, and metabolomics) are increasing our understanding of central nervous system (CNS) disorders. Achievements obtained with transformational technologies such as single-cell RNA sequencing and intraoperative mass spectrometry are exemplary of the molecular diagnostic possibilities in real-time molecular diagnostics to enable a more directed approach in surgical options. We will also explore how identifying specific biomarkers (e.g., IDH mutations and MGMT promoter methylation) became a tipping point in the care of glioblastoma and allowed for the establishment of a new taxonomy of tumors that became applicable for surgeons, where a change in practice enjoined a different surgical resection approach and subsequently stratified the adjuvant therapies undertaken after surgery. Furthermore, we reflect on how the novel genomic characterization of mutations like DEPDC5 and SCN1A transformed the pre-surgery selection of surgical candidates for refractory epilepsy when conventional imaging did not define an epileptogenic zone, thus reducing resective surgery occurring in clinical practice. While we are atop the crest of an exciting wave of advances, we recognize that we also must be diligent about the challenges we must navigate to implement genomic medicine in neurosurgery—including ethical and technical challenges that could arise when genomic mutation-based therapies require the concurrent application of multi-omics data collection to be realized in practice for the benefit of patients, as well as the constraints from the blood–brain barrier. The primary challenges also relate to the possible gene privacy implications around genomic medicine and equitable access to technology-based alternative practice disrupting interventions. We hope the contribution from this review will not just be situational consolidation and integration of knowledge but also a stimulus for new lines of research and clinical practice. We also hope to stimulate mindful discussions about future possibilities for conscientious and sustainable progress in our evolution toward a genomic model of precision neurosurgery. In the spirit of providing a critical perspective, we hope that we are also adding to the larger opportunity to embed molecular precision into neuroscience care, striving to promote better practice and better outcomes for patients in a global sense. Full article

Accurate peak detection in the frequency domain is fundamental to reliable range estimation in Frequency-Modulated Continuous-Wave (FMCW) radar systems, particularly in challenging conditions characterized by a low signal-to-noise ratio (SNR) and phase noise impairments. This paper presents a comprehensive comparative analysis of five peak detection algorithms: FFT thresholding, Cell-Averaging Constant False Alarm Rate (CA-CFAR), a simplified Matrix Pencil Method (MPM), SVD-based detection, and a novel Learned Thresholded Subspace Projection (LTSP) approach. The proposed LTSP method leverages singular value decomposition (SVD) to extract the dominant signal subspace, followed by signal reconstruction and spectral peak analysis, enabling robust detection in noisy and spectrally distorted environments. Each technique was analytically modeled and extensively evaluated through Monte Carlo simulations across a wide range of SNRs and oscillator phase noise levels, from $-100$ dBc/Hz to $-70$ dBc/Hz. Additionally, real-world validation was performed using a custom-built harmonic FMCW radar prototype operating in the 2.4–2.5 GHz transmission band and 4.8–5.0 GHz harmonic reception band. Results show that CA-CFAR offers the highest resilience to phase noise, while the proposed LTSP method delivers competitive detection performance with improved robustness over conventional FFT and MPM techniques. Furthermore, the hardware feasibility of each algorithm is assessed for implementation on a Xilinx FPGA platform, highlighting practical trade-offs between detection performance, computational complexity, and resource utilization. These findings provide valuable guidance for the design of real-time, embedded FMCW radar systems operating under adverse conditions. Full article

Previous studies have mostly focused on the adsorption behavior of microplastics for antibiotics in soil or aqueous environments. This study explores the adsorption characteristics of microplastics for antibiotics under groundwater environmental conditions and the influence of typical influencing factors of the groundwater environment (pH, pollutant concentration, aquifer media, dissolved organic matter, and ionic strength) on the adsorption process. Polyethylene (PE) and tetracycline (TC) were selected as typical microplastics and antibiotics in the experiment. The study results showed that the adsorption of TC by PE reached equilibrium at 48 h, and the adsorption kinetics fitted pseudo-second-order kinetics models well. The adsorption isotherm was consistent with the Langmuir model. The adsorption capacity of PE for TC was highest under neutral conditions and positively correlated with the initial concentration of TC. The aquifer media exhibited limited effects on the adsorption process. Fulvic acid (FA) significantly suppressed TC adsorption onto PE, attributable to competitive adsorption mechanisms. TC adsorption on PE initially increased then declined with Ca²⁺ concentration due to Ca²⁺ bridging and competition. This research elucidates the adsorption mechanisms of PE towards TC, providing theoretical basis and reference for assessing the environmental risk of microplastics and antibiotics in groundwater. Full article