Search Results (356)

Objectives: This study aimed to describe the epidemiological and clinical characteristics and the potential risk factors associated with Clostridioides difficile infection (CDI) in a high-complexity healthcare center. Methods: This was a retrospective case–control study conducted from 2020 to 2022 with a cohort of participants aged ≥18 years with diarrhea (more than three liquid stools per day), which included a molecular testing request (the FilmArray Gastrointestinal [GI] PCR Panel) in a high-complexity clinic in Santiago de Cali, Colombia. Controls were randomly selected from the same institutional laboratory database at a 2:1 ratio, matched by age and sex, and required to test negative for C. difficile. Patients from other institutions were excluded to avoid exposure misclassification. Results: Our study included 147 participants (49 cases and 98 controls) and found a 22% infection prevalence among those who underwent molecular testing. When comparing CDI cases with controls, significant differences were observed in the univariate analysis: cases showed longer time to symptom resolution, longer post-diagnosis hospital stay, and greater exposure to in-hospital antibiotics for more than 7 days prior to symptom onset (p < 0.05). Among CDI cases, 55% were healthcare-associated and 18% were classified as severe, with an overall 30-day mortality of 15%. In the multivariate logistic regression model, three variables remained significantly associated with CDI: hospital stay longer than 10 days before symptom onset, antibiotic exposure in the previous 90 days, and in-hospital proton pump inhibitor use. Conclusions: CDI can present a wide range of clinical manifestations, so underdiagnosis should be avoided. Identifying risk factors, particularly in patients with hospital-acquired diarrhea, is crucial. Factors such as a hospital stay longer than 10 days before symptom onset and in-hospital exposure to PPIs or antibiotics in the last 90 days were significant in our study. Early recognition of these risk factors may reduce hospital stay, lower the risk of complications, and optimize healthcare resources. Full article

In the current context of environmental sustainability and reduced agricultural inputs, biostimulants represent one of the most efficient, eco-friendly and innovative strategies to preserve plants from biotic and abiotic stresses and to ensure sustainable agriculture. Ranging from benefic microorganisms, seaweed extracts, and humic acids to complex carbohydrates such as polysaccharides and oligosaccharides, these biostimulants are able to increase plant growth, photosynthetic efficiency, root development and nutrient uptake when they are applied during seed priming as foliar sprays or as liquid and solid soil amendments. The mechanisms underlying their effective action on plants are mainly related to the enhancement of antioxidant defenses and the regulation of hormonal pathways, particularly auxin homeostasis and transport. Several studies reported the relevance of biostimulant application in promoting root growth. In plants, roots play crucial roles, performing a variety of functions such as nutrients and water uptake, mediating stress perception and adaptation, influencing the rhizosphere microbiome, and providing structural support. The effectiveness and perception of polysaccharide-based biostimulants (PBs) are highly dependent on crucial factors, including the degree of depolymerization and the chemical modifications such as acetylation, methylation, sulfation, and oxidation. Furthermore, not all receptors and co-receptors involved in the recognition of PBs have yet been identified. However, there remain many gaps in our understanding regarding the interaction between biostimulants and roots, which is still far from fully elucidated. For these reasons, the present review provides a comprehensive overview of current research on biostimulants–root interactions, with a particular focus on polysaccharide-based biostimulants. It highlights the mechanisms involved in their recognition by plants roots, from perception to response, and the subsequent signaling cascades and the molecular pathways activated, with special emphasis on existing knowledge gaps and future research perspectives. Full article

The issue of microplastics in the aquatic environment has become one of the key topics in contemporary environmental engineering, chemical engineering and materials technology. Plastic microparticles are found not only in natural waters, but also in industrial and municipal piping systems, process installations and even in drinking water, posing a growing threat to public health, ecosystem stability and the reliability of technical equipment. Due to its chemical resistance, hydrophobicity and variety of sizes and shapes, microplastics are difficult to remove using traditional separation methods, and their harmful impact is part of a broader analysis of the life cycle of plastics, from their production and use to the waste phase and their impact on the environment. In response to the scale of the phenomenon, a number of liquid–solid separation methods have been developed, including approaches based on physical, chemical and biological principles. These methods vary in their scope of application, operational requirements and the way they interact with the particles present in the flow. The scientific literature describes mechanical techniques, chemical reactions and the interaction of biological organisms in a controlled environment as the main groups of separation. Each group has specific limitations resulting from the properties of microplastics, flow conditions and medium characteristics, which means that the choice of separation technology must take into account the specific nature of the system in question. The development of advanced measurement methods, monitoring systems and control techniques enables more accurate observation and analysis of particle movement, as well as the study of the relationship between device operating parameters and the behaviour of contaminants in the flow. The increasingly widespread use of measurement data, predictive algorithms and pattern recognition techniques makes it possible to describe the phenomena accompanying microplastic separation in greater detail and to formulate new concepts for devices and flow systems based on analytical methods, computational tools and adaptive control systems is in line with current trends in process engineering and automation, as well as with the concept of Industry 4.0. Taking the above information into account, the aim of this work is to analyse selected liquid–solid separation methods in order to identify the most optimal in terms of the effectiveness of removing plastic microparticles, with the assumption of the greatest possible number of features indicating the possible future automation of a given process. Full article

Gastrointestinal (GI) cancers constitute an umbrella term for a wide variety of malignancies that are located in the digestive tract (esophageal, gastric, small and large intestine, anus, liver, gallbladder, and pancreas), with 25% of total cancers and 35% of cancer-related deaths being attributed to them. An alarming trend of rising GI malignancy diagnoses, especially in younger age groups, underscores the need for discoveries in liquid-based biomarkers that facilitate both early detection and optimal disease management. Extracellular vesicles (EVs) not only constitute promising nano-sized biomarkers, but also, via bioengineering, have shown a great therapeutic potential, with artificial intelligence (AI) revolutionizing their research via the selection of the best biomarkers from omics, the recognition of pathophysiological patterns, and facilitating a faster drug-development via AI-driven EV engineering, drug delivery modeling, and target identification. In this review, we will provide a clear insight into the implementation of AI methodologies in EV-based biomarker discovery and therapeutics for pancreatic and hepatobiliary cancer. Full article

Bongkrekic acid (BKA), a highly lethal toxin, has been implicated in frequent poisoning incidents in recent years, posing a serious threat to global food safety and creating an urgent need for rapid and sensitive detection methods. This review provides a systematic analysis of the entire BKA detection technologies, covering sample pretreatment techniques, instrumental analysis, immunoassays, and biosensing methods. It assesses the merits of key methods and also explores the strategic cross-application of detection paradigms developed for analogous toxins. This review delivers a comprehensive and critical evaluation of BKA detection technologies. First, it discusses sample pretreatment strategies, notably solid-phase extraction (SPE) and QuEChERS. Subsequently, it analyzes the principles, performance, and applications of core detection methods, including high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS), high-resolution mass spectrometry (HRMS), time-resolved fluorescence immunoassay (TRFIA), dual-mode immunosensors and nanomaterial-based sensors. Instrumental methods (e.g., HRMS) offer unmatched sensitivity [with a limit of detection (LOD) as low as 0.01 μg/kg], yet remain costly and laboratory-dependent. Immunoassay and biosensor approaches (TRFIA and dual-mode sensors) enable rapid on-site detection with high sensitivity (ng/mL to pg/mL), though challenges in stability and specificity remain. Looking forward, the development of next-generation BKA detection could be accelerated by cross-applying cutting-edge strategies proven for toxins—such as Fumonisin B1 (FB1), Ochratoxin A (OTA), and Aflatoxin B1 (AFB1)—including nanobody technology, CRISPR-Cas-mediated signal amplification, and multimodal integrated platforms. To translate this potential into practical tools, future research should prioritize the synthesis of high-specificity recognition elements, innovative signal amplification strategies, and integrated portable devices, aiming to establish end-to-end biosensing systems capable of on-site rapid detection through multitechnology integration. Full article

The quality of cow’s milk is critical for human nutrition; thus, it is important to develop rapid, sensitive, and cost-effective methods to monitor milk quality. Volatile Organic Compounds (VOCs) from milk are odorant molecules that can be used as key indicators of milk quality, since their presence is influenced by important factors such as animal metabolism, animal diet, and farming practices. In this work, we used the porcine odorant-binding protein (pOBP) and the bovine odorant-binding protein (bOBP) as molecular recognition elements (MREs) of an innovative fluorescence biosensor to detect the presence of odorant molecules in (a) milk produced by intensive livestock farming and (b) milk produced by extensive livestock farming. For biosensors, it is important to use proteins that are stable under operative conditions; therefore, we used fluorescence spectroscopy for a biophysical characterization of the pOBP and of the bOBP at different temperatures. The proposed biosensor employs a system to capture the odorant molecules from milk, which are then transferred to a liquid phase for quantitative and qualitative analyses. The binding of the odorant molecules to the OBPs triggers a Förster Resonance Energy Transfer (FRET) signal, allowing for real-time VOC quantification. The performance of the assays was evaluated by Headspace Solid-Phase Microextraction coupled with Gas Chromatography–Mass Spectrometry (HS-SPME/GC-MS) experiments. The experimental approach used for the development of the biosensor demonstrated high sensitivity and specificity, enabling the differentiation of milk from intensive and extensive farming systems. The results indicate the potential of this method for the real-time monitoring of VOCs in milk samples for food traceability and quality control. Full article

The recognition of liquid–liquid phase separation (LLPS) as a widespread organizing principle has revolutionized our view of cellular biochemistry. By forming biomolecular condensates, cells spatially orchestrate reactions without membranes. However, the dysregulation of this precise physical organization is emerging as a driver of diverse pathologies, collectively termed “Condensatopathies.” Unlike traditional proteinopathies defined by static aggregates, these disorders span a dynamic spectrum of material state dysfunctions, from the failure to assemble essential compartments to the formation of aberrant, toxic phases. While research has largely focused on neurodegeneration and cancer, the impact of condensate dysfunction likely extends across broad physiological landscapes. A central unresolved challenge lies in deciphering the “molecular grammar” that governs the transition from functional fluids to pathological solids and, critically, visualizing these transitions in situ. This “material science” perspective presents a profound conundrum for drug discovery: how to target the collective physical state of a protein ensemble rather than a fixed active site. This review navigates the evolving therapeutic horizon, examining the limitations of current pharmacological approaches in addressing the complex “condensatome.” Moving beyond inhibition, we propose that the future of intervention lies in “reverse-engineering” the biophysical codes of phase separation. We discuss how deciphering these principles enables the creation of programmable molecular tools—such as synthetic peptides and state-specific degraders—designed to precisely modulate or dismantle pathological condensates, paving the way for a new era of precision medicine governed by soft matter physics. Full article

Metamaterials (MMs)-based terahertz (THz) biosensors hold promise for clinical diagnosis, featuring label-free operation, simple, rapid detection, low cost, and multi-cell-type discrimination. However, liquid around cells causes severe interference to sensitive detection. Most existing MMs-based cell biosensors detect dead cells without culture medium (losing original morphology), hindering stable, sensitive multi-cell discrimination. Here, a terahertz biosensor composed of a microcavity and MMs can be used to detect and discriminate multiple cell types within suspension. Its detection mechanism relies on cellular size (radius)/density in suspension, which induces effective permittivity (ε_eff) differences. By designing MMs’ split rings with luxuriant gaps, the biosensor achieves a theoretical sensitivity of ~328 GHz/RIU, enabling sensitive responses to suspended cells. It shows a robust, increasing frequency shift (610–660 GHz) over 72 h of cell apoptosis. Moreover, it discriminates nerve cells, glioblastoma (GBM) cells, and their 1:1 mixture with obviously distinct frequency responses (~650, ~630, ~620 GHz), which suggests effective and reliable multi-cell-type recognition. Overall, this study and its measurement method should pave the way for metamaterial-based terahertz biosensors for living cell detection and discrimination, and this technology may inspire further innovations in tumor investigation and treatment. Full article

Unmanned Aerial Spraying Systems (UASS) has rapidly advanced precision crop protection. However, the spray performance of UASSs is influenced by nozzle atomization, rotor-induced airflow, and external environmental conditions. These factors cause strong spatiotemporal coupling and high uncertainty. As a result, visualization-based monitoring techniques are now essential for understanding these dynamics and supporting spray modeling and drift-mitigation design. This review highlights developments in spray visualization technologies along the “droplet–airflow–target” chain mechanism in UASS spraying. We first outline the physical fundamentals of droplet formation, liquid-sheet breakup, droplet size distribution, and transport mechanisms in rotor-induced flow. Dominant processes are identified across near-field, mid-field, and far-field scales. Next, we summarize major visualization methods. These include optical imaging (PDPA/PDIA, HSI, DIH), laser-based scattering and ranging (LD, LiDAR), and flow-field visualization (PIV). We compare their spatial resolution, measurement range, 3D reconstruction capabilities, and possible sources of error. We then review wind-tunnel trials, field experiments, and point-cloud reconstruction studies. These studies show how downwash flow and tip vortices affect plume structure, canopy disturbance, and deposition patterns. Finally, we discuss emerging intelligent analysis for large-scale monitoring—such as image-based droplet recognition, multimodal data fusion, and data-driven modeling. We outline future directions, including unified feature systems, vortex-coupled models, and embedded closed-loop spray control. This review is a comprehensive reference for advancing UASS analysis, drift assessment, spray optimization, and smart support systems. Full article

Catalytic coacervates, or droplet reactors, represent a forefront research area in chemistry and materials science. Despite advancements in this field, challenges persist in achieving liquid–liquid phase separation (LLPS) droplet compartmentalization and site-specific reactant recruitment/localization for reaction catalysis, similar to those within biological systems. Herein, we describe the catalytic coacervates for aqueous photo-RAFT in dilution, focusing on the site-specific recruitment/localization of ionized monomer with the aid of macromolecular crowding and confinement. Cooperative hydrogen-bonded interpolymer complexation (IPC) of imidazolium-copolymers initiates the ion-cluster formation. Further hierarchical inter-cluster complexation (ICC) leads to the LLPS droplet compartmentalization into charged dense-phase and neutral dilute-phase compartments. Site-specific recruitment and localization of the oppositely charged monomer into dense-phase compartments are achieved by salt-bridging molecular recognition. “Substantial DMA-dilution” (that is, macromolecular crowding) results in sustainable dense-phase catalytic sites within dilute-phase crowding surroundings, enabling reaction catalysis in dilution (<2% w/w monomer) to 97% conversion in 12 min. These findings underscore the key roles of macromolecular crowding and confinement in the tailorable LLPS droplet compartmentalization and also the site-specific reactant recruitment/localization essential for enzyme reaction catalysis, and provide practical guidelines for creating catalytic coacervates towards lifelike reaction functions. Full article

Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality worldwide, with heart failure (HF) representing a major contributor to hospitalizations, healthcare costs, and death. Effective management of HF is hindered by the limitations of current biomarkers and diagnostic tools. Conventional biomarkers, such as natriuretic peptides, primarily reflect downstream hemodynamic stress and often lack specificity, particularly in HF with preserved ejection fraction or multiple comorbidities. While imaging provides valuable structural and functional information, it is resource-intensive, costly, and unsuitable for frequent longitudinal monitoring. As a result, these conventional approaches are inadequate to capture the dynamic and heterogeneous nature of HF pathophysiology. Circulating cell-free nucleic acids (cfNAs), including cell-free DNA (cfDNA) and RNA (cfRNA), have emerged as promising noninvasive liquid biopsy biomarkers capable of providing real-time insight into upstream pathological events, such as cardiomyocyte injury, immune activation, inflammation, and maladaptive remodeling. Importantly, cfNAs also act as active mediators of CVD pathology. When released under stress or injury, cfNAs interact with pattern recognition receptors (PRRs) that trigger sterile inflammation, cardiovascular cell dysfunction, and adverse cardiac remodeling. This review summarizes the origins, mechanistic roles, and clinical significance of cfNAs in HF and related CVD, highlighting their dual roles as diagnostic biomarkers and mechanistic effectors of disease. Finally, we discuss emerging cfNA-targeted therapeutic strategies, challenges, and future opportunities for precision medicine in HF and HF-associated CVD. Full article

Colorectal cancer (CRC) remains a major cause of morbidity and mortality worldwide, with its incidence and biological behavior influenced by both genetic and environmental factors. Emerging evidence highlights notable sex differences in CRC, with men generally exhibiting higher incidence rates and poorer prognoses, while women often display stronger immune responses and distinct molecular profiles. Traditional screening tools, such as colonoscopy and fecal-based tests, have improved survival through early detection but are limited by invasiveness, cost, and adherence issues. In this context, biosensors have emerged as innovative diagnostic platforms capable of rapid, sensitive, and non-invasive detection of CRC-associated biomarkers, including genetic, epigenetic, and metabolic alterations. These technologies integrate biological recognition elements with nanomaterials, microfluidics, and digital systems, enabling the analysis of biomarkers such as proteins, nucleic acids, autoantibodies, epigenetic marks, and metabolic or VOC signatures from blood, stool, or breath and supporting point-of-care applications. Electrochemical, optical, piezoelectric, and FET platforms enable label-free or ultrasensitive multiplexed readouts and align with liquid biopsy workflows. Despite challenges related to standardization, robustness in complex matrices, and clinical validation, advances in nanotechnology, multi-analyte biosensing with artificial intelligence are enhancing biosensor performance. Integrating biosensor-based diagnostics with knowledge of sex-specific molecular and hormonal pathways may lead to more precise and equitable approaches in CRC detection, selection of therapeutic regimes and management. Full article

Cervical cancer (CC) can be prevented through continuous screening and the timely detection of cervical intraepithelial neoplasia (CIN) using immunohistochemistry techniques to identify biomarker expressions. In a previous study, we proposed nuclear REST loss as a biomarker in precancerous lesions and CC; however, no validated antibodies are available for detecting REST in cytology or cervical tissues. Although we have developed an IgM-type anti-REST monoclonal antibody capable of detecting REST in liquid-based cytology cells, it was not useful for the detection of REST in cervical tissues by immunohistochemistry. The main objective of this study is to generate single-chain variable fragments (scFvs) for the clinical evaluation of REST in cervical tissues from women with CIN and CC. Using RNA from an IgM-producing hybridoma anti-REST, we conducted RT-PCR and PCR to obtain the coding sequences for the variable regions of the heavy and light chains. These sequences were joined with a linker to create a single-chain antibody. The scFv was then cloned into the pSyn1 vector, expressed in E. coli TG1, and purified through chromatography. Subsequently, it was characterized using immunological methods to assess its biological activity and employed to evaluate REST expression in cytological samples and cervical tissues. The anti-REST scFv represents an innovative detection tool that retains the antigen recognition of the parental IgM while overcoming its size limitation, enabling tissue penetration and detection of REST in cervical samples. Its application facilitates the identification of REST in cervical samples, reinforcing REST’s potential as a diagnostic biomarker for CC and CIN. Full article

Background/Objectives: Alzheimer’s disease (AD) is a neurodegenerative disorder with a high incidence but limited agents. Herein, PZ-2891 was discovered as a novel anti-AD candidate. Both in vivo and in vitro pharmacodynamic (PD) studies and pharmacokinetic (PK) properties were investigated and illustrated in this research. Methods: A computer-generated random number table was used to divide mice into various groups randomly. Injecting Aβ into the mice hippocampus to mimic AD-like pathologies, neurobehavioral tests, including the Morris maze, Y maze, open field test (OFT) and novel object recognition (NOR), were operated to evaluate the cognitive improvement in PZ-2891. D-galactose (D-gal), okadaic acid (OA) and lipopolysaccharide (LPS) were employed to trigger neural injuries in vitro. A reliable analytic method was developed to profile PZ-2891’s PK properties in SD rats through a triple quadrupole liquid chromatography–mass spectrometry (LC–MS/MS) instrument. Results: PZ-2891 markedly alleviated cognitive impairment in the Aβ-induced model mice. It also protected nerve cells from oxidative stress and inflammatory injuries and significantly reduced AD-typical pathological biomarkers. The PK results showed that PZ-2891 was exposed rapidly in both plasma and brain, with a brain-to-blood ratio of around 0.59, C_max of around 454.50 ± 151.35 ng/mL, T_max of around 0.49 ± 0.15 h and oral bioavailability of around 19.74 ± 6.78%. Conclusions: These findings suggest that PZ-2891, an agonist of PANK2, is a novel and potential candidate agent for AD with excellent efficacy and PK properties. Full article

Background/Objectives: Malignant pleural mesothelioma (MPM) is a rare, aggressive tumor with a poor prognosis and complex diagnostic pathways. Pulmonologists often play a central role in its initial recognition and investigation. This narrative review synthesizes the current evidence on the diagnostic approach to MPM, with emphasis on imaging, tissue sampling, histopathology, and emerging diagnostic innovations relevant to clinical pulmonology. Methods: English-language studies published between January 2005 and June 2025 were identified from PubMed and Scopus. International guidelines and consensus documents were also reviewed to provide an updated overview of diagnostic strategies. Results: Diagnosis of MPM relies on a stepwise integration of clinical, radiological, and pathological information. Thoracic ultrasound, computed tomography, positron emission computed tomography and magnetic resonance imaging complement each other across different stages of the diagnostic pathway. Image-guided pleural biopsy and medical thoracoscopy remain the gold standard for tissue confirmation, supported by immunohistochemistry and molecular testing. The 2021 World Health Organization classification of pleural tumors and the International Association Study of Lung Cancer 9th Edition Tumour-Node-Mestastatis system have refined histologic and staging criteria, thereby improving reproducibility and prognostic accuracy. Emerging tools, including liquid biopsy, novel serum and molecular biomarkers, artificial-intelligence-based radiomics, and breathomics, offer promise for earlier and less invasive diagnosis but require prospective validation. Conclusions: Current advances are redefining MPM diagnosis toward integrated, multidisciplinary, and precision-based models. Future priorities include standardizing diagnostic algorithms, validating minimally invasive biomarkers, and integrating AI and molecular profiling into clinical workflows to enhance patient stratification. Full article