Search Results (3,258)

Advanced therapy medicinal products (ATMPs), especially effective against cancer, remain costly due to their reliance on genetically modified T cells. Contamination during production is a major concern, as traditional quality control methods involve samplings, which can themselves introduce contaminants. It is therefore necessary to develop methods for detecting contamination without sampling and, if possible, in real time. In this article, we present a white light spectroscopy method that makes this possible. It is based on shape analysis of the absorption spectrum, which evolves from an approximately Gaussian shape to a shape modified by the 1/λ component of bacterial absorption spectra when contamination develops. A warning value based on this shape descriptor is proposed. It is demonstrated that a few hours are sufficient to detect contamination and trigger an alarm to quickly stop the production. This time-saving should reduce the cost of these new drugs, making them accessible to as many people as possible. This method can be used regardless of the type of contaminants, provided that the shape of their absorption spectrum is sufficiently different from that of pure T cells so that the shape descriptor is efficient. Full article

Immunoglobulin light chains are essential components of intact immunoglobulins, traditionally believed to be produced exclusively by B cells. Physiologically, excess light chains not assembled into intact antibodies exist as free light chains (FLCs). Increasingly recognized as important biomarkers for diseases such as multiple myeloma, systemic amyloidosis, and light chain-related renal injuries, FLCs have also been shown in recent decades to originate from non-B cell sources, including epithelial and carcinoma cells. This review primarily focuses on novel non-B cell-derived FLCs, which challenge the conventional paradigms. It systematically compares B cell-derived and non-B cell-derived FLCs, analyzing differences in genetic features, physicochemical properties, and functional roles in both health and disease. By elucidating the distinctions and similarities in their nature as immune regulators and disease mediators, we highlight the significant clinical potential of FLCs, particularly non-B cell-derived FLCs, for novel diagnostic and therapeutic strategies. Full article

Landscape metrics are one of the main tools for studying changes in the landscape and the ecological structure of the territory. However, the calculation of some metrics yields significantly different values depending on the configuration of the “Cell neighborhood” (CN) used. This makes the comparison of different analysis results often impossible. In fact, although the metrics are defined in the same way for all software, the choice of a CN with four cells, which includes only the elements on the same row or column, or eight cells, which also includes the cells on the diagonal, changes their value. QGIS’ LecoS plugin uses the value eight while GRASS’ r.li module uses the value four and these values are not modifiable by users. A previous study has shown how the value of the CN used for the calculation of landscape metrics is rarely explicit in scientific publications and its value cannot always be deduced from the indication of the software used. The difference in value for the same metric depends on the CN configuration and on the compactness of the patches, which can be expressed through the Aggregation Index (AI), of the investigated landscape. The scope of this paper is to explore the possibility of deriving an analytical relationship between the Aggregation Index and the variation in the values of some landscape metrics as the CN varies. The numerical experiments carried out in this research demonstrate that it is possible to estimate the differences in landscape metrics evaluated with a four and eight CN configuration using polynomials only for few metrics and only for some intervals of AI values. This analysis combines different Free and Open Source Software (FOSS) systems: GRASS GIS for the creation of test maps and R landscapemetrics package for the calculation of landscape metrics and the successive statistical analysis. Full article

Free-space optical (FSO) communications have emerged as a promising complement to conventional radio-frequency (RF) systems due to their high bandwidth, low interference, and license-free spectrum. Visible-light FSO communication, using laser diodes or LEDs, offers potential for short-range data links, but performance is highly wavelength-dependent under varying atmospheric conditions. This study presents an experimental evaluation of three visible laser diodes at 650 nm (red), 532 nm (green), and 405 nm (violet), focusing on their optical output power, quantum efficiency, and modulation behavior across a range of driving currents and frequencies. A custom laboratory testbed was developed using an Atmega328p microcontroller and a Visual Basic control interface, allowing precise control of current and modulation frequency. A silicon photovoltaic cell was employed as the optical receiver and energy harvester. The results demonstrate that the 650 nm red laser consistently delivers the highest quantum efficiency and optical output, with stable performance across electrical and modulation parameters. These findings support the selection of 650 nm as the most energy-efficient and versatile wavelength for short-range, cost-effective visible-light FSO communication. This work provides experimentally grounded insights to guide wavelength selection in the development of energy-efficient optical wireless systems. Full article

Background: Pleural mesothelioma (PM) is a type of cancer that is difficult to diagnose and treat. Patients may have vastly varying prognoses, and prognostic factors may help guide the clinical approach. As a recently identified biomarker, the pan-Immune-Inflammation-Value (PIV) is a simple, comprehensive, and peripheral blood cell-based biomarker. Methods: The present study represents a retrospective observational analysis carried out within a single-center setting. Ninety-five patients with PM stages I–IV were enrolled in the study. We analyzed the correlation between patients’ demographic characteristics, clinicopathological factors such as histological subtypes, surgery status, tumor thickness, blood-based parameters, and treatment options with their prognoses. PIV was calculated by the following formula: (neutrophil count × monocyte count × platelet count)/lymphocyte count. Additionally, blood-based parameters were used to calculate the platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII). Results: We categorized the patients into two groups, low PIV group (PIV ≤ 732.3) and high PIV group (PIV > 732.3) according to the determined cut-off value, which was defined as the median. It was revealed that high PIV was associated with poor survival outcomes. The median follow-up period was 15.8 months (interquartile range, IQR, 7.1 to 29.8 months). The median overall survival (OS) was significantly longer in patients in the low PIV group (median 29.8 months, 95% confidence interval (CI), 15.6 to 44) than the high PIV group (median 14.7 months, 95% CI, 10.8 to 18.6 p < 0.001). Furthermore, the study revealed that patients with low PIV, NLR, and SII values were more likely to be eligible for surgery and were diagnosed at earlier stages. Additionally, these markers were identified as potential predictors of disease-free survival (DFS) in the surgical cohort and of treatment response across the entire patient population. Conclusions: In addition to well-established clinical factors such as stage, histologic subtype, resectability, and Eastern Cooperative Oncology Group (ECOG) performance status (PS), PIV emerged as an independent and significant prognostic factor of overall survival (OS) in patients with PM. Moreover, PIV also demonstrated a remarkable independent prognostic value for disease-free survival (DFS) in this patient population. Additionally, some clues are provided for conditions such as treatment responses, staging, and suitability for surgery. As such, in this cohort, it has outperformed the other blood-based markers based on our findings. Given its ease of calculation and cost-effectiveness, PIV represents a promising and practical prognostic tool in the clinical management of pleural mesothelioma. It can be easily calculated using routinely available laboratory parameters for every cancer patient, requiring no additional cost or complex procedures, thus facilitating its integration into everyday clinical practice. Full article

Cell-free biosensors harness the selectivity of cellular machinery without living cells’ constraints, offering advantages in environmental monitoring, medical diagnostics, and biotechnological applications. This review examines recent advances in cell-free biosensor development, highlighting their ability to detect diverse analytes including heavy metals, organic pollutants, pathogens, and clinical biomarkers with high sensitivity and specificity. We analyze technological innovations in cell-free protein synthesis optimization, preservation strategies, and field deployment methods that have enhanced sensitivity, and practical applicability. The integration of synthetic biology approaches has enabled complex signal processing, multiplexed detection, and novel sensor designs including riboswitches, split reporter systems, and metabolic sensing modules. Emerging materials such as supported lipid bilayers, hydrogels, and artificial cells are expanding biosensor capabilities through microcompartmentalization and electronic integration. Despite significant progress, challenges remain in standardization, sample interference mitigation, and cost reduction. Future opportunities include smartphone integration, enhanced preservation methods, and hybrid sensing platforms. Cell-free biosensors hold particular promise for point-of-care diagnostics in resource-limited settings, environmental monitoring applications, and food safety testing, representing essential tools for addressing global challenges in healthcare, environmental protection, and biosecurity. Full article

Microalgae, with their unparalleled capabilities for sunlight-driven growth, CO₂ fixation, and synthesis of diverse high-value compounds, represent sustainable cell factories for a circular bioeconomy. However, industrial deployment has been hindered by biological constraints and the inadequacy of conventional genetic tools. The advent of CRISPR-Cas systems initially provided precise gene editing via targeted DNA cleavage. This review argues that the true transformative potential lies in moving decisively beyond cutting to harness CRISPR as a versatile synthetic biology “Swiss Army Knife”. We synthesize the rapid evolution of CRISPR-derived tools—including transcriptional modulators (CRISPRa/i), epigenome editors, base/prime editors, multiplexed systems, and biosensor-integrated logic gates—and their revolutionary applications in microalgal engineering. These tools enable tunable gene expression, stable epigenetic reprogramming, DSB-free nucleotide-level precision editing, coordinated rewiring of complex metabolic networks, and dynamic, autonomous control in response to environmental cues. We critically evaluate their deployment to enhance photosynthesis, boost lipid/biofuel production, engineer high-value compound pathways (carotenoids, PUFAs, proteins), improve stress resilience, and optimize carbon utilization. Persistent challenges—species-specific tool optimization, delivery efficiency, genetic stability, scalability, and biosafety—are analyzed, alongside emerging solutions and future directions integrating AI, automation, and multi-omics. The strategic integration of this CRISPR toolkit unlocks the potential to engineer robust, high-productivity microalgal cell factories, finally realizing their promise as sustainable platforms for next-generation biomanufacturing. Full article

Cell culture models are of central importance for the investigation of cellular metabolism, proliferation and stress responses. In this study, the effects of different concentrations of glucose (1 g/L vs. 4.5 g/L) and fetal bovine serum (FBS; 5%, 10%, 15%) on viability, mitochondrial function and autophagy are investigated in four human cell lines: MRC-5, HeLa, Caco-2 and SW-620. Cells were cultured in defined media for 72 h, and viability was assessed by LDH release, mitochondrial membrane potential using Rhodamine 123, ATP content by luminescence and autophagy activity by dual fluorescence staining. The results showed that HeLa and SW-620 cancer cells exhibited increased proliferation and mitochondrial activity under high glucose conditions, while low glucose media resulted in decreased ATP content and increased membrane permeability in HeLa cells. MRC-5 fibroblasts and Caco-2 cells showed greater resilience to nutrient stress, with minimal changes in LDH release and consistent proliferation. Autophagy was activated under all conditions, with a significant increase only in selected cell-medium combinations. These results highlight the importance of medium composition in influencing cellular bioenergetics and stress responses, which has implications for cancer research, metabolic disease modelling and the development of serum-free culture systems for regenerative medicine. Full article

Background: Pain is a complex phenomenon characterized by unpleasant experiences with profound heterogeneity influenced by biological, psychological, and social factors. According to the National Health Interview Survey, 50.2 million U.S. adults (20.5%) experience pain on most days, with the annual cost of prescription medication for pain reaching approximately USD 17.8 billion. Theranostic pain nanomedicine therefore emerges as an attractive analgesic strategy with the potential for increased efficacy, reduced side-effects, and treatment personalization. Theranostic nanomedicine combines drug delivery and diagnostic features, allowing for real-time monitoring of analgesic efficacy in vivo using molecular imaging. However, clinical translation of these nanomedicines are challenging due to complex manufacturing methodologies, lack of standardized quality control, and potentially high costs. Quality by Design (QbD) can navigate these challenges and lead to the development of an optimal pain nanomedicine. Our lab previously reported a macrophage-targeted perfluorocarbon nanoemulsion (PFC NE) that demonstrated analgesic efficacy across multiple rodent pain models in both sexes. Here, we report PFC-free, biphasic nanoemulsions formulated with a biocompatible and non-immunogenic plant-based coconut oil loaded with a COX-2 inhibitor and a clinical-grade, indocyanine green (ICG) near-infrared fluorescent (NIRF) dye for parenteral theranostic analgesic nanomedicine. Methods: Critical process parameters and material attributes were identified through the FMECA (Failure, Modes, Effects, and Criticality Analysis) method and optimized using a 3 × 2 full-factorial design of experiments. We investigated the impact of the oil-to-surfactant ratio (w/w) with three different surfactant systems on the colloidal properties of NE. Small-scale (100 mL) batches were manufactured using sonication and microfluidization, and the final formulation was scaled up to 500 mL with microfluidization. The colloidal stability of NE was assessed using dynamic light scattering (DLS) and drug quantification was conducted through reverse-phase HPLC. An in vitro drug release study was conducted using the dialysis bag method, accompanied by HPLC quantification. The formulation was further evaluated for cell viability, cellular uptake, and COX-2 inhibition in the RAW 264.7 macrophage cell line. Results: Nanoemulsion droplet size increased with a higher oil-to-surfactant ratio (w/w) but was no significant impact by the type of surfactant system used. Thermal cycling and serum stability studies confirmed NE colloidal stability upon exposure to high and low temperatures and biological fluids. We also demonstrated the necessity of a solubilizer for long-term fluorescence stability of ICG. The nanoemulsion showed no cellular toxicity and effectively inhibited PGE2 in activated macrophages. Conclusions: To our knowledge, this is the first instance of a celecoxib-loaded theranostic platform developed using a plant-derived hydrocarbon oil, applying the QbD approach that demonstrated COX-2 inhibition. Full article

The focal “hot spot” neuropathologies in COVID-19 infection are revealing footprints of a hidden underlying collapse of a novel ultrafast ultradian Piezo2 signaling system within the nervous system. Paradoxically, the same initiating pathophysiology may underpin the systemic findings in COVID-19 infection, namely the multiorgan SARS-CoV-2 infection-induced vascular pathologies and brain–body-wide systemic pro-inflammatory signaling, depending on the concentration and exposure to infecting SARS-CoV-2 viruses. This common initiating microdamage is suggested to be the primary damage or the acquired channelopathy of the Piezo2 ion channel, leading to a principal gateway to pathophysiology. This Piezo2 channelopathy-induced neural switch could not only explain the initiation of disrupted cell–cell interactions, metabolic failure, microglial dysfunction, mitochondrial injury, glutamatergic synapse loss, inflammation and neurological states with the central involvement of the hippocampus and the medulla, but also the initiating pathophysiology without SARS-CoV-2 viral intracellular entry into neurons as well. Therefore, the impairment of the proposed Piezo2-induced quantum mechanical free-energy-stimulated ultrafast proton-coupled tunneling seems to be the principal and critical underlying COVID-19 infection-induced primary damage along the brain axes, depending on the loci of SARS-CoV-2 viral infection and intracellular entry. Moreover, this initiating Piezo2 channelopathy may also explain resultant autonomic dysregulation involving the medulla, hippocampus and heart rate regulation, not to mention sleep disturbance with altered rapid eye movement sleep and cognitive deficit in the short term, and even as a consequence of long COVID. The current opinion piece aims to promote future angles of science and research in order to further elucidate the not entirely known initiating pathophysiology of SARS-CoV-2 infection. Full article

Cetraria islandica (L.) Ach. (CI) is a lichen from the Parmeliaceaea family used in medicine. However, the low solubility of CI secondary metabolites in water limits the application of lichen extract and compounds. It prompted us to study the systems of cyclodextrins (CDs) (β-CD, γ-CD, HP-β-CD, and HP-γ-CD) with the CI acetone or CI methanol extracts prepared using grinding and solvent evaporation methods. The content of fumarprotocetraric acid (FPCA), a key CI metabolite, was quantified using HPLC. CD–extract systems were characterized by X-ray powder diffraction (XRPD) and Fourier-transform infrared (FTIR) spectroscopy. Biological activity was evaluated using cell-free assays: a Folin–Ciocalteu analysis, DPPH test, acetylcholinesterase, butyrylcholinesterase, and tyrosinase inhibitions. Dissolution profiles were also assessed. The best biological and physicochemical results were obtained for systems prepared with HP-β-CD and HP-γ-CD via solvent evaporation, showing higher activity and enhanced FPCA release compared to the pure extracts. To the best of our knowledge, this is the first study to report the preparation and characterization of CD-based systems with CI extracts. The obtained results encourage us to continue our research on CI to improve the physicochemical properties of its active compounds. Full article

Background and Objectives: Metabolic tumor volume (MTV) and inflammation-based indices have recently gained attention as potential prognostic markers of diffuse large B-cell lymphoma (DLBCL). We aimed to evaluate the prognostic significance of metabolic and systemic inflammatory parameters in predicting treatment response, relapse, and overall survival (OS) in patients with DLBCL. Materials and Methods: This retrospective cohort study included 70 patients with DLBCL. Clinical characteristics, laboratory values, and metabolic parameters, including maximum standardized uptake value (SUVmax^liver and SUVmax), heterogeneity indices HI1 and HI2, and MTV were analyzed. Survival outcomes were assessed using Kaplan–Meier and log-rank tests. Receiver operating characteristic analyses helped evaluate the diagnostic performance of the selected biomarkers in predicting relapse and mortality. Univariate and multivariate logistic regression analyses were conducted to identify the independent predictors. Results: The mean OS and mean relapse-free survival (RFS) were 71.6 ± 7.4 and 38.7 ± 2.9 months, respectively. SUVmax^liver ≤ 22 and HI2 > 62.3 were associated with a significantly shorter OS. High lactate dehydrogenase (LDH) levels and HI2 > 87.9 were significantly associated with a reduced RFS. LDH, SUVmax^liver, and HI2 had a significant predictive value for relapse. SUVmax^liver and HI2 levels were also predictive of mortality; SUVmax^liver ≤ 22 and HI2 > 62.3 independently predicted mortality, while HI2 > 87.9 independently predicted relapse. MTV was not significantly associated with survival. Conclusions: Metabolic tumor burden and inflammation-based markers, particularly SUVmax^liver and HI2, are significant prognostic indicators of DLBCL and may enhance risk stratification and aid in identifying patients with an increased risk of relapse or mortality, potentially guiding personalized therapy. Full article

The XPO1 (exportin 1) gene encodes exportin 1 protein responsible for transporting proteins and RNA from the nucleus to the cytoplasm. It has been used as a biomarker for lymphoma detection. XPO1^E571K mutation has been frequently observed and identified as a good prognostic indicator for lymphoma patients. The detection of a target molecule released by lymphoma cells into blood circulation (cell-free circulating tumor DNA, cfDNA) is a better method than tissue biopsy. However, cfDNA concentration in blood circulation is very low in cancer patients. Therefore, a precise and sensitive method is needed. In this study, cfDNA was extracted, and then the XPO1 gene was detected and amplified using conventional PCR. Sanger sequencing was employed to verify the DNA sequences. FAST-COLD-PCR was developed to detect XPO1^E571K gene mutation using a CFX96 Touch Real-Time PCR System. The optimal critical temperature (Tc) was 73.3 °C, allowing selective amplification of XPO1^E571K mutant DNA while wild-type XPO1 could not be amplified. XPO1^E571K gene mutation can be detected by this method with high specificity and sensitivity in lymphoma patients. This approach facilitates rapid and straightforward detection in a timely manner after the diagnosis. Accordingly, the optimized FAST-COLD-PCR conditions can be used as a prototype for XPO1^E571K mutant detection in lymphoma patients. Full article

Background: Acute leukemia (AL) is the most prevalent pediatric malignancy and is frequently associated with systemic iron dysregulation, often leading to iron overload. This study aimed to characterize the regulatory mechanisms of iron metabolism in children with AL, considering treatment stages and associated clinical parameters. Methods: A total of 149 children were stratified into four groups: newly diagnosed AL (n = 43), patients post-chemotherapy (n = 55), patients following hematopoietic cell transplantation (HCT; n = 32), and healthy controls (n = 19). Serum concentrations of matriptase-2 (TMPRSS6), neogenin-1 (NEO1), and soluble hemojuvelin (sHJV) were quantified using ELISA. Results: Compared to healthy children, significantly higher serum concentrations of TMPRSS6 and NEO1 were found in patients post-chemotherapy and post-HCT, while sHJV levels were markedly decreased. Higher TMPRSS6 and NEO1 levels and lower sHJV were associated with increased ferritin levels and greater numbers of transfused packed red blood cell (PRBC) units. sHJV negatively correlated with TMPRSS6, NEO1, ferritin, C-reactive protein (CRP), and PRBC transfusions. TMPRSS6 and NEO1 showed a positive correlation. Among the analyzed biomarkers, Kaplan–Meier analysis revealed no statistically significant associations with overall survival (OS) or event-free survival (EFS) within the chemotherapy and HCT subgroups. Conclusions: AL in pediatric patients is associated with profound disruptions of systemic iron homeostasis. Our investigation identified notable perturbations in TMPRSS6, NEO1, and sHJV, suggesting that these proteins could contribute mechanistically to the pathophysiological alterations underlying iron dysregulation observed in pediatric AL. Full article

The development of scalable, non-invasive tools to assess tumor responsiveness to structurally active immunoformulations remains a critical unmet need in solid tumor immunotherapy. Here, we introduce a real-time, ex vivo functional system to classify tumor cell lines exposed to a phospholipoproteomic platform, without relying on cytotoxicity, co-culture systems, or molecular profiling. Tumor cells were monitored using IncuCyte^® S3 (Sartorius) real-time imaging under ex vivo neutral conditions. No dendritic cell components or immune co-cultures were used in this mode. All results are derived from direct tumor cell responses to structurally active formulations. Using eight human tumor lines, we captured proliferative behavior, cell death rates, and secretomic profiles to assign each case into stimulatory, inhibitory, or neutral categories. A structured decision-tree logic supported the classification, and a Functional Stratification Index (FSI) was computed to quantify the response magnitude. Inhibitory lines showed early divergence and high IFN-γ/IL-10 ratios; stimulatory ones exhibited a proliferative gain under balanced immune signaling. The results were reproducible across independent batches. This system enables quantitative phenotypic screening under standardized, marker-free conditions and offers an adaptable platform for functional evaluation in immuno-oncology pipelines where traditional cytotoxic endpoints are insufficient. This approach has been codified into the STIP (Structured Traceability and Immunophenotypic Platform), supporting reproducible documentation across tumor models. This platform contributes to upstream validation logic in immuno-oncology workflows and supports early-stage regulatory documentation. Full article