Search Results (1,003)

The increasing prevalence of common cold viruses and bacteria in daily life has heightened interest in sterilization lamp technologies. Compared with traditional mercury-based ultraviolet (UV) lamps, modern UV lamps offer advantages including extended operational lifespan, high energy efficiency, compact form factor, and the absence of hazardous materials, rendering them both safer and environmentally sustainable. In particular, UV-C LED lamps, which emit at short wavelengths, are capable of disrupting the molecular structure of DNA or RNA in microbial cells, thereby inhibiting cellular replication and achieving effective disinfection and sterilization. Conventional UV-C LED sterilization lamp driver circuits frequently employ a two-stage architecture, which requires a large number of components, occupies substantial physical space, and exhibits reduced efficiency due to multiple stages of power conversion. To address these limitations, this paper proposes a UV-C LED sterilization lamp driver circuit for an AC voltage supply, employing boundary conduction mode (BCM) control with integrated power factor correction (PFC). The proposed single-stage, single-switch topology combines a buck PFC converter and a flyback converter while recovering transformer leakage energy to further improve efficiency. Compared with conventional two-stage designs, the proposed circuit reduces the number of power switches and components, thereby lowering manufacturing cost and enhancing overall energy conversion efficiency. The operating principles of the proposed driver circuit are analyzed, and a prototype is developed for a 110 V AC input with an output specification of 10.8 W (90 V/0.12 A). Experimental results demonstrate that the prototype achieves an efficiency exceeding 92%, a power factor of 0.91, an output voltage ripple of 1.298%, and an output current ripple of 4.44%. Full article

Drought is a leading constraint on plant productivity and will intensify with climate change. Plant acclimation emerges from a multilayered regulatory system that integrates signaling, transcriptional reprogramming, RNA-based control, and chromatin dynamics. Within this hierarchy, non-coding RNAs (ncRNAs) provide a unifying regulatory layer; microRNAs (miRNAs) modulate abscisic acid and auxin circuits, oxidative stress defenses, and root architecture. This balances growth with survival under water-deficient conditions. Small interfering RNAs (siRNAs) include 24-nucleotide heterochromatic populations that operate through RNA-directed DNA methylation, which positions ncRNA control at the transcription–chromatin interface. Long non-coding RNAs (lncRNAs) act in cis and trans, interact with small RNA pathways, and can serve as chromatin-associated scaffolds. Circular RNAs (circRNAs) are increasingly being detected as responsive to drought. Functional studies in Arabidopsis and maize (e.g., ath-circ032768 and circMED16) underscore their regulatory potential. This review consolidates ncRNA biogenesis and function, catalogs drought-responsive modules across model and crop species, especially cereals, and outlines methodological priorities, such as long-read support for isoforms and back-splice junctions, stringent validation, and integrative multiomics. The evidence suggests that ncRNAs are tractable entry points for enhancing drought resilience while managing growth–stress trade-offs. Full article

Nucleic acid strand displacement reactions (SDRs) are fundamental building blocks of dynamic DNA nanotechnology. A detailed understanding of their kinetics is crucial for designing efficient sequences and regulating reaction networks with applications in biosensing, synthetic biology, biocomputing, and medical diagnostics. Since the development of toehold-mediated strand displacement, researchers have devised many strategies to adjust reaction kinetics. These efforts have expanded the available tools in DNA nanotechnology. This review summarizes the basic principles and recent advances in activation strategies, emphasizing the role of strand proximity as a central driving force. Proximity-based approaches include toehold docking, associative toeholds, remote toeholds, and allosteric designs, as well as strategies that operate without explicit toehold motifs. These methods enable flexible and scalable construction of DNA reaction networks. We further discuss how combining different activation and kinetic control approaches gives rise to dynamic networks with complex and dissipative behaviors, providing new directions for DNA-based nanotechnology. Full article

The aim of our study is to determine the changes in the biomarkers CXCL-16, CCL-20, GDF-15, and CD8a, which play an immunological role in CHB patients according to viral load to determine their diagnostic potential and to investigate their relationships with hematological parameters and non-invasive fibrosis indices. Our study included 96 chronic hepatitis B patients and 30 healthy individuals as a control group. The patients were divided into three groups based on their serum HBV DNA levels: mild (0–10² IU/mL), moderate (10³–10⁵ IU/mL), and severe viral load (10⁶–10⁸ IU/mL). HBV DNA levels were determined by the real-time PCR (Anatolia, Istanbul, Turkey) method. CXCL-16, GDF-15, and CD8a levels in patient serum were quantitatively determined by the ELISA method (Elabscience, Wuhan, China), and CCL-20 levels were determined by the ELISA method BT LAB, Shanghai, China). ROC (Receiver Operating Characteristics) and HUM (Hypervolume Under Manifold) analyses were used to determine the diagnostic efficacy of the biomarkers. ROC analyses showed that GDF-15 (AUC = 0.920) and CCL-20 (AUC = 0.751) had “very good” and “good” diagnostic values, respectively, in predicting hepatitis B disease. HUM analyses revealed that all biomarkers have good potential when it comes to distinguishing the severity of the disease. This study has shown that the biomarkers GDF-15 and CCL-20 may be potential diagnostic biomarkers in detecting the presence of chronic hepatitis B, and the biomarkers CXCL-16, CCL-20, GDF-15, and CD8a may be potential diagnostic biomarkers in determining the severity of the disease. These findings suggest that these biomarkers, which can be measured by the simpler and more economical ELISA method, could be a supportive tool for the HBV DNA test. The clinical use of these biomarkers can be expanded with future prospective studies. Full article

Pulmonary neuroendocrine tumors (PULMONARY NETs) are heterogeneous tumors ranging from well-differentiated to highly aggressive neoplasms. The aim of this study is to prospectively test pre-operative circulating free DNA (cfDNA) in PULMONARY NET patients undergoing surgery and evaluate its relationship to clinicopathological features. From February to December 2024, 136 patients with suspected primary lung cancer underwent pre-operative blood sampling, of whom 21 were diagnosed with PULMONARY NETs. Total cell-free nucleic acid extraction was performed using the Genexus Purification System (Thermofisher). cfDNA was quantified using a fluorometric assay with the Qubit dsDNA HS Assay kit (Thermofisher) and a capillary electrophoresis-based assay (cell-free DNA ScreenTape kit) on the Tape Station 4200 systems (Agilent). A cfDNA quality assessment was also obtained (cfDNA sizing and % cfDNA). Most patients had Stage I (18/21.85.7%) typical carcinoids (16/21.76.2%). Nodal involvement was detected in one patient (0.5%). Six months after surgery, all patients were alive without recurrence. Larger tumors presented higher levels of cfDNA. The mean tumor size in patients with cfDNA > 40 ng was 266 mm (±16.7 mm), compared to 13.2 mm (±7.3 mm) for cfDNA < 40 ng (p-value = 0.018). Higher levels of cfDNA were observed in patients with pStages greater than IA (p-value = 0.007). Although limited by a small sample group and biases of a surgical series, we observed that larger/advanced PULMONARY NETs presented higher cfDNA levels pre-operatively. Full article

In recent years, there has been rapid advancement in single-molecule techniques, driven by their unparalleled precision in studying molecules whose sizes are beyond the diffraction limit. Among these techniques, optoplasmonic whispering gallery mode sensing has demonstrated great potential in label-free single-molecule characterization. It combines the principles of localized surface plasmon resonance (LSPR) and whispering gallery mode (WGM) sensing, offering exceptional sensing capabilities, even at the level of single ions. However, current optoplasmonic WGM sensing operates in a multiplexed channel, making it challenging to focus on individual binding sites of analyte molecules. In this article, we characterize different binding sites of DNA analyte molecules hybridizing to docking strands on the optoplasmonic WGM sensor, using the ratio of the resonance shift between sequential polar WGM modes. We identify specific docking sites that undergo transient interactions and eventually hybridize with the complementary analyte strands permanently. Full article

Emerging evidence highlights the critical role of phagocytosis-related genes in CRC progression, underscoring the need for novel phagocytosis-based prognostic models to predict clinical outcomes. In this study, a four-gene (SPHK1, VSIG4, FCGR2B and FPR2) signature associated with CRC prognosis was developed using single-sample gene set enrichment analysis (ssGSEA), least absolute shrinkage and selection operator (LASSO) regression, and univariate Cox analysis. Pathway enrichment analysis was conducted on the prognostic genes, along with evaluations of the tumor microenvironment and sensitivity to immunotherapy and chemotherapy across the high- and low-risk groups. Prognostic gene validation was performed via quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry (IHC) using CRC cDNA and tissue microarrays. High-risk patients showed enhanced responsiveness to immunotherapy, while chemotherapy sensitivity varied across risk subgroups. qRT-PCR results revealed upregulation of SPHK1 and FPR2 in cancer tissues, whereas FCGR2B and VSIG4 were downregulated. IHC assays confirmed increased SPHK1 and FPR2 expression in cancer samples. Single-cell RNA sequencing analysis demonstrated a decrease in SPHK1 and FCGR2B, while VSIG4 and FPR2 progressively increased during macrophage differentiation. These findings provide a potential framework for targeted therapy. Full article

Huge amounts of water and chemicals have been injected into subsurface oil reservoirs in secondary and tertiary oil recovery processes. Although the effects of injected water and chemicals on microbial communities have been investigated, knowledge about their long-term dynamic changes in oil reservoirs remains limited. To address this gap, we used 16S rRNA sequencing from cDNA and chemical analysis to track the dynamic changes in microbial communities in oil reservoirs under a long-term flooding operation over three years and five months using bio-chemical flooding in the Daqing Oilfield, China. Researchers observed dynamic changes in microbial composition and diversity during the flooding process. Long-term bio-chemical drainage leads to alterations in dominant bacterial community structure, with a decrease in methanogenic archaeal abundance. Bacterial metabolic functions remained stable, but archaeal functions changed notably. Our results indicate that the microbial community and its functions in the oil reservoirs have experienced significant dynamic changes under the long-term flooding intervention of bio-chemical flooding, which opens up a new window for further understanding the impact of injected water and chemicals on microbial community in oil reservoirs and expands our knowledge about the role of microbial community changes in reservoirs under the flooding process. Full article

Skin cancer is the most common cancer worldwide. The incidence of skin cancer has been increasing worldwide. Nearly 75% of all skin cancers are basal cell carcinomas (BCC), cutaneous squamous cell carcinoma (cSCC) represents approximately 20%, and those remaining are melanomas (4%) or other rare tumors (1%). Given the high cure rates and the ability to histologically confirm tumor clearance, surgical therapy is the gold standard for the treatment of skin cancer. Conventional surgery is the most employed technique for the removal of non-melanoma skin cancer (NMSCs). Mohs Micrographic Surgery (MMS) is the most precise surgical method for the treatment of non-melanoma skin cancer, allowing for 100% margin evaluation, being the gold-standard method for surgical treatment of non-melanoma skin cancer. Whenever it is possible to obtain wide margins (4 to 6 mm), cure rates vary from 70% to 99%. Imiquimod, a synthetic imidazoquinolinone amine, is a topical immune response modifier approved by the U.S. Food and Drug Administration (FDA) for the treatment of external anogenital warts, actinic keratosis (AK), and superficial basal cell carcinoma (sBCC). The efficacy of imiquimod is primarily attributed to its ability to modulate both innate and adaptive immune responses, as well as its direct effects on cancer cells. Imiquimod exerts its immunomodulatory effects by activating Toll-like receptors 7 and 8 (TLR7/8) on various immune cells, including dendritic cells, macrophages, and natural killer (NK) cells. Upon binding to these receptors, imiquimod triggers the MyD88-dependent signaling pathway, leading to the activation of nuclear factor kappa B (NF-κB) and interferon regulatory factors (IRFs). This cascade leads to the production of pro-inflammatory cytokines, including interferon-alpha (IFN-α), tumor necrosis factor-alpha (TNF-α), interleukin-12 (IL-12), and interleukin-6 (IL-6). These cytokines enhance local inflammation, recruit additional immune cells to the tumor site, and stimulate antigen presentation, thereby promoting an anti-tumor immune response. Radiation therapy (RTh) may be employed as a primary treatment to BCC. It may also be employed as an adjuvant treatment to surgery for SCC and aggressive subtypes of BCC. RTh triggers both direct and indirect DNA damage on cancer cells and generates reactive oxygen species (ROS) within cells. ROS trigger oxidative damage to DNA, proteins, and lipids, exacerbating the cellular stress and contributing to tumor cell death. Recently, immunotherapy emerged as a revolutionary treatment for all stages of SCC. Cemiplimab is a human programmed cell death 1 (PD-1)-blocking antibody that triggers a response to over 50% of patients with locally advanced and metastatic SCC. A randomized clinical trial (RCT) published in 2022 revealed that cemiplimab was highly effective in the neoadjuvant treatment of large SCCs. The drug promoted a significant tumor size decrease, enabling organ-sparing operations and a much better cosmetic effect. A few months ago, a RCT of cemiplimab on adjuvant therapy for locally aggressive SCC was published. Interestingly, cemiplimab was administered to patients with local or regional cutaneous squamous cell carcinoma after surgical resection and postoperative radiotherapy, at high risk for recurrence owing to nodal features, revealed that cemiplimab led to much lower risks both of locoregional recurrence and distant recurrence. Full article

Many countries around the world feature raw fish in their cuisine, which is valued for its unique flavor. However, raw fish may be easily contaminated with foodborne pathogens including Listeria monocytogenes, Salmonella, Vibrio parahaemolyticus, and Staphylococcus aureus. Herein, a method was established that integrated a multiplex polymerase chain reaction (PCR) and high-resolution melting (HRM) curve assay for the simultaneous detection of these four foodborne pathogens. The target genes of the bacteria were amplified by PCR and subsequently analyzed using HRM. Differentiation was achieved based on the melting temperature (Tm) values of their respective amplicons. The detection limit of the PCR-HRM assay was 0.02–0.1 ng/µL. In addition, the Tm remained nearly constant across various concentrations of genomic DNA derived from the target bacteria. The assay demonstrated perfect specificity (8/8) and a sensitivity of 5/5 for L. monocytogenes, 2/2 for Salmonella, 3/3 for V. parahaemolyticus, and 3/3 for S. aureus. No significant interference occurred when genomic DNA from the four target bacteria was co-extracted with DNA from eight non-target strains. Furthermore, the assay offers advantages including operational simplicity, high efficiency, accurate results, reduced detection time, and lower costs, rendering it well-suited for food safety applications in the aquatic products processing industry. Full article

Grapevine cultivars (Vitis vinifera L.) generally exhibit relatively high tolerance to drought stress. In contrast, the drought tolerance of other Vitis species and their hybrids used as rootstocks differs considerably. In order to attain a better understanding of the molecular basis of drought tolerance in grapevine, we conducted a comparative transcriptomic analysis of roots of drought-stressed Cabernet Sauvignon (CS, Vitis vinifera L.) and rootstock of Kober 5BB (V. berlandieri × V. riparia) using the Affymetrix Vitis Genome Array Version 2.0. We identified 1279 (745 upregulated and 534 downregulated) and 1925 (807 upregulated and 118 downregulated) differentially expressed genes in 5BB and CS. Numerous genes that are putatively involved in aquaporins, proline-rich protein, reactive oxygen species, osmoprotection, and lipid transfer were differentially expressed in response to drought stress in both genotypes. When gene ontology analyses were examined, it was observed that CS and 5BB genotypes were associated with the highest number of similar genes in both the molecular function (protein binding, catalytic activity, and DNA binding) and the biological process (metabolic process and translation) categories. The identification of different regulated genes between 5BB and CS roots is expected to help advance our understanding of molecular mechanisms operating during drought stress in grapevine roots. Full article

The Atlas cedar Cedrus atlantica is a relict and endemic conifer from Morocco and Algeria, although plantations may be found in several locations aside from its natural range. Recurrent droughts have been widely related to Atlas cedar dieback, growth decline, and mortality, but the genetic basis of potential adaptive capacity is unknown. We used the double digest restriction-site associated DNA sequencing technique (ddRAD-seq) to describe the genetic structure and variability of Atlas cedar along an aridity gradient in Morocco. Furthermore, we investigated the potential genetic origin of three Spanish plantations, also along an aridity gradient. The obtained single nucleotide polymorphisms (SNPs) were used to perform genotype–environment associations (GEAs) to define SNPs related to bioclimatic variables of temperature and precipitation. The vulnerability of this species to environmental variations was also estimated by its risk of non-adaptedness (RONA). Population structure showed a divergence between the Moroccan natural stands and some of the Spanish plantations, with each Moroccan nucleus being genetically distinct. The genetic variability was significantly lower in plantations than in natural populations. The drier Spanish plantations (easternmost) were genetically very similar to the driest Moroccan population (southernmost), suggesting that as its origin. A total of 41 loci under selection were obtained with the Moroccan dataset. In relation to temperature and precipitation variables, isothermality showed the highest number of associated loci (10) in GEA studies, and genotype–phenotype associations (GPAs) showed one locus associated with the Specific Leaf Area. RONA value was higher in the southernmost High Atlas population, where rising temperature was the main driver of expected genetic offset by allele frequency changes under the worst emissions scenario. In contrast, Spanish plantations would need smaller genetic changes to cope with the expected climate change. Likely gene flow from southern to northern areas suggests a latitudinal heading, where Spanish plantations might operate as an assisted migration. Moreover, one locus showed a northern/southern pattern in saplings but not in adults, suggesting a potential latitudinal pattern of selection. Our results are discussed on the basis of their management and conservation. Full article

Background: Probabilistic genotyping software has become an essential tool in forensic genetics, particularly for interpreting complex DNA mixtures. Previous studies measured the impact of considering widely divergent statistical approaches in quantifying evidence, both inter- and intra-software. At a much smaller scale, this data-driven study shows how different models implemented on distinct versions of the same tool may affect the results. Among the available tools, EuroForMix stands out as a quantitative, open-source software that models various aspects of the DNA profile, including artefacts like stutter peaks. Its freeware nature allowed the use of both versions 1.9.3. and 3.4.0, between which several updates were made, including the possibility to model both back and forward stutter, compared to only modeling back stutters inputted by the expert in the earlier version. Methods: A total of 156 real casework sample pairs (comprising mixtures with two or three estimated contributors and associated reference) from the Portuguese Scientific Police Laboratory were analyzed using both software versions. The same input data, containing alleles and artefactual peaks, were used to reflect operational conditions. Statistical measurements were compared and further investigated. Results: Most Likelihood Ratio values differed in less than one order of magnitude across versions. However, exceptions were found in more complex samples, such as those with more contributors, unbalanced contributions, or greater degradation. Conclusions: This work emphasizes the relevance of model selection in forensic evidence quantification, even when considering different versions of the same tool. The impact of different models in statistical evaluation depends on several factors, such as sample technical conditions, genotypic profiles, and population distribution. Full article

Background: Cervical cancer is among the most prevalent malignancies in women worldwide, and early detection of epigenetic alterations such as Deoxyribose Nucleic Acid (DNA) methylation is of utmost significance for improving clinical results. This study introduces a novel deep learning-based framework for predicting DNA methylation in cervical cancer, utilizing a UNet architecture integrated with an innovative one-hot character encoding technique. Methods: Two encoding strategies, monomer and dimer, were systematically evaluated for their ability to capture discriminative features from DNA sequences. Experiments were conducted on Cytosine–Guanine (CG) sites using varying sequence window sizes of 100 bp, 200 bp, and 300 bp, and sample sizes of 5000, 10,000, and 20,000. Model validation was performed on promoter regions of five cervical cancer-associated genes: miR-100, miR-138, miR-484, hTERT, and ERVH48-1. Results: The dimer encoding strategy, combined with a 300-base pair window and 5000 CG sites, emerged as the optimal configuration. The proposed framework demonstrated better predictive performance, with an accuracy of 91.60%, sensitivity of 96.71%, specificity of 87.32%, and an Area Under the Receiver Operating Characteristic (AUROC) score of 96.53, significantly outperforming benchmark deep learning models, including Convolutional Neural Networks and MobileNet. Validation on promoter regions further confirmed the robustness of the model, as it accurately identified 86.27% of methylated CG sites and maintained a strong AUROC of 83.99, demonstrating its precision–recall balance and practical relevance during validation in promoter-region genes. Conclusions: These findings establish the potential of the proposed UNet-based approach as a reliable and scalable tool for early detection of epigenetic modifications. Thus, the work contributes significantly to improving biomarker discovery and diagnostics in cervical cancer research. Full article

The growing digitization of healthcare has amplified concerns about the privacy and security of medical images, as conventional encryption methods often fail to provide sufficient protection. To address this gap, we propose a privacy-enhancing image encryption algorithm that integrates SHA-256 hashing, block-wise processing (16 × 16 with zero-padding), DNA encoding with XOR operations, and logistic map-driven key generation into a unified framework. This synergistic design balances efficiency and robustness by embedding data integrity verification, ensuring high sensitivity to initial conditions, and achieving strong diffusion through dynamic DNA rules. Experimental results confirm that the scheme achieves high NPCR (0.997), UACI (0.289), entropy (7.995), and PSNR (27.89 dB), outperforming comparable approaches while maintaining scalability to large image formats and robustness under compression (JPEG quality factors 90 and 70). These findings demonstrate that the proposed method offers an efficient and resilient solution for securing medical images, ensuring confidentiality, integrity, and practical applicability in real-world healthcare environments. Full article