Search Results (6,307)

Morchella spp. is a type of valuable and rare edible fungi cultivated in soil. Optimization of the cultivation medium for Morchella spp. is key to obtaining high-efficiency production in an ecologically friendly manner. Recently, the sustainable resource utilization of agricultural waste has gathered attention. Specifically, reusing tomato substrate, mushroom residues, and coconut shells can lower the production costs and reduce environmental pollution, demonstrating remarkable ecological and economic benefits. To determine the soil microbial communities of Morchella spp. using different culture medias and influencing factors, this study analysed the relative abundance of bacterial and fungal communities in natural soil, soil with 5% tomato substrate, soil with 5% mushroom residues, and soil with 5% coconut shells using Illumina NovaSeq high-throughput sequencing. In addition, intergroup differences, soil physiochemical properties, and product quality were also determined. Results demonstrated that agricultural waste consisting of mushroom residues, waste tomato substrate, and coconut shells can improve the efficiency of Morchella spp. cultivation. When considering yield and quality, mushroom residue achieved the highest yield (soil nutrient enrichment), followed by tomato substrate (water holding + grass carbon nutrient). All three types of agricultural waste promoted early fruiting, significantly increased polysaccharide, crude protein, and potassium content, and lowered crude fat and fibre. In regard to soil improvement, the addition of different materials optimized the soil’s physical structure (reducing volume weight and increasing water holding capacity) and chemical properties (enrichment of nitrogen, phosphorus, and potassium, regulating nitrogen and medium trace elements). For microbial regulation, the added materials significantly increased the abundance of beneficial bacteria (e.g., Actinomycetota, Gemmatimonadota and Devosia) and strengthened nitrogen’s fixation/nitration/decomposition functions. In the mushroom residue group, the abundance of Bacillaceae was positively related to yield. Moreover, it inhibited pathogenic fungi like Mortierella and Trichoderma, and lowered fungal diversity to decrease ecological competition. In summary, mushroom residues have nutrient releasing and microbial regulation advantages, while tomato substrate and coconut shells are new high-efficiency resources. These increase yield through the “physiochemical–microorganism” collaborative path. Future applications may include regulating the function of microorganisms and optimizing waste preprocessing technologies to achieve sustainability. Full article

Integrating information and communication technology (ICT) into STEM education enhances instructional quality and cultivates students’ interdisciplinary problem-solving. STEM teachers’ attitudes—driven by perceived ease of use (PEOU) and perceived usefulness (PU)—are pivotal in ICT adoption, and pre-service training offers a vital opportunity to shape these attitudes. Yet, empirical studies investigating how specific training strategies influence ICT attitudes via PEOU and PU remain scarce. Using a mixed-methods approach combining questionnaires and interviews, the results indicate that pre-service training significantly improved STEM teachers’ attitudes toward ICT-enhanced teaching. Socially interactive strategies (role models and collaboration) enhanced attitudes via PEOU by boosting confidence and reducing technology-related anxiety, cognitive design strategies (reflection and instructional design) operated through PU by emphasizing ICT’s pedagogical value, and experiential feedback strategies (authentic experience and feedback) influenced attitudes through both PEOU and PU, fostering integrated technical and pedagogical development. These findings support an integrated SQD–TAM framework and provide practical guidance for designing pre-service STEM teacher programs to promote sustained ICT adoption in China, and meanwhile highlights the importance of strategically sequencing training to cultivate both technological competence and pedagogical insight among future STEM educators. Full article

Controlled demolition is a critical engineering practice that enables the safe and efficient dismantling of structures while minimizing risks to the surrounding environment. This study presents, for the first time, a detailed, structured framework for understanding the fundamental principles of controlled demolition by outlining key procedures, methodologies, and directions for future research. Through original, carefully designed charts and full-scale numerical simulations, including two 23-story building scenarios with different delay and blasting sequences, this paper provides real-life insights into the effects of floor-to-floor versus axis-by-axis delays on structural collapse behavior, debris spread, and toppling control. Beyond traditional techniques, this study explores how emerging technologies, such as real-time structural monitoring via object tracking, LiDAR scanning, and Unmanned Aerial Vehicle (UAV)-based inspections, can be further advanced through the integration of artificial intelligence (AI). The potential Deep learning (DL) and Machine learning (ML)-based applications of tools like Convolutional Neural Network (CNN)-based digital twins, YOLO object detection, and XGBoost classifiers are highlighted as promising avenues for future research. These technologies could support real-time decision-making, automation, and risk assessment in demolition scenarios. Furthermore, vision-language models such as SAM and Grounding DINO are discussed as enabling technologies for real-time risk assessment, anomaly detection, and adaptive control. By sharing insights from full-scale observations and proposing a forward-looking analytical framework, this work lays a foundation for intelligent and resilient demolition practices. Full article

Background: With the advancement of the next-generation sequencing technology, it is becoming more cost-effective to obtain plastomes from genome skimming data at shallow sequencing depth. Artemisia is a species-rich genus, comprising species of great medicinal or economic value. However, plastomes of Artemisia have not been thoroughly and comparatively analyzed, and the phylogenetic relationships within the genus are still not well resolved. Methods: In this study, 19 Artemisia plastomes were obtained from genome skimming data. Together with the plastomes retrieved from the public database, comparative analyses of their structure were also conducted. We further used sequences of plastomes and nuclear internal transcribed spacer sequences to conduct phylogenetic reconstruction. Results: The Artemisia plastomes are conserved in terms of structure, GC content, gene number, and order. Some regions, i.e., accD, ccsA, ndhE, ycf1, ccsA-ndhD, trnG^GCC-trnfM^CAU, were found to be variable and could be chosen as candidates for the DNA barcode. Phylogenetic analyses also confirmed that the four subgenera of Artemisia are not monophyletic. The incongruence between plastid and nuclear phylogenies indicated that hybridization events have occurred during the evolution of the genus. Conclusions: Reconstructed phylogenies using plastome sequences and nuclear internal transcribed spacers improved our understanding of the phylogenetic backbone of Artemisia. In the future, more taxa of Artemisia should be sequenced and analyzed to clarify the evolutionary history. Full article

Base editing represents a major breakthrough in the field of genome editing in recent years. By fusing deaminases with the CRISPR/Cas system, it enables precise single-base modifications of DNA. This review systematically summarizes the development of base editing technologies, including cytosine base editors (CBEs), adenine base editors (ABEs), and glycosylase base editors (GBEs), with a particular focus on their applications in crop improvement as well as future trends and prospects. We highlight advances in the creation of novel germplasm with enhanced stress resistance and desirable agronomic traits through base editing in rice, wheat, maize, potato, and other crops, particularly for improving herbicide resistance, disease resistance, and grain quality. Furthermore, we analyze factors that influence base editing efficiency, noting that challenges remain, such as PAM sequence constraints, limited base conversion types, off-target effects, narrow editing windows, and efficiency variation. Future efforts should aim to optimize deaminase activity, expand PAM compatibility, and develop versatile tools to facilitate the broad application of base editing in molecular breeding. This review provides a timely reference for researchers and breeders, offering theoretical guidance and practical insights into harnessing base editing for crop genetic improvement. Full article

Background/Objectives: Urinary tract infections (UTIs) represent a considerable challenge within the field of clinical medicine, as they are responsible for significant morbidity and intensify the operational pressures encountered by healthcare systems. Conventional diagnostic approaches, which include symptom evaluation, dipstick urinalysis, and standard urine culture, often demonstrate inadequacies in identifying atypical clinical manifestations, infections with low bacterial counts, or pathogens that show growth difficulties under typical laboratory conditions. These limitations undermine diagnostic accuracy and hinder timely therapeutic measures. Methods: The present manuscript is a systematic review conducted in accordance with PRISMA guidelines. A structured search was performed in PubMed, Scopus, and Google Scholar, yielding 573 records, of which 107 studies were included for qualitative synthesis. The primary aim of this systematic review is to evaluate both conventional and emerging diagnostic methods for UTIs, with specific objectives of assessing their clinical applicability, limitations, and potential to improve patient outcomes. Results: Recent progress in diagnostic technologies offers promising alternatives. Molecular-based assays, such as multiplex polymerase chain reaction, matrix-assisted laser desorption ionization mass spectrometry, and next-generation sequencing, have substantially improved both the precision and efficiency of pathogen identification. Furthermore, contemporary techniques for evaluating antimicrobial susceptibility, including microfluidic systems and real-time phenotypic resistance assays, enable clinicians to execute targeted therapeutic strategies with enhanced efficacy. Results of this synthesis indicate that while conventional diagnostics remain the cornerstone for uncomplicated cases, innovative molecular and phenotypic approaches demonstrate superior performance in detecting low-count bacteriuria, atypical pathogens, and resistance determinants, particularly in complicated and recurrent infections. These innovations support antimicrobial stewardship by reducing dependence on empirical antibiotic treatment and lessening the risk of resistance emergence. Conclusions: Nonetheless, the incorporation of these technologies into clinical practice requires careful consideration of implementation costs, standardization protocols, and the necessary training of healthcare professionals. In conclusion, this systematic review highlights that emerging molecular diagnostics and resistance-profiling tools offer substantial promise in complementing or enhancing traditional methods, but their widespread adoption will depend on robust validation, cost-effectiveness, and integration into clinical workflows. Full article

Staphylococcus aureus is a globally crucial foodborne pathogen that can cause diarrhea, vomiting, and bloodstream infection in immunocompromised individuals. S. aureus has three predominant sequence types (STs) (ST7, ST188 and ST398) that are prevalent clones in both food and clinical cases. This study aimed to screen ST-specific targets for S. aureus ST7, ST188 and ST398, and then developed a novel rapid and accurate assay for the detection of these three predominant S. aureus STs in food. A total of 505 Staphylococcus strain genome sequences including 371 sequences of 58 different STs and 134 other non-target S. aureus ST genome sequences were subjected to pan-genome analysis; we successfully screened five novel ST-specific targets (group_10498 and group_10499 target for S. aureus ST7, group_9415 and group_9419 target for S. aureus ST188, group_9911 target for S. aureus ST398). The excellent specificity and sensitivity of all the targets were confirmed by PCR assays. Based on these molecular targets, mPCR and qPCR methods were developed for specifically identifying S. aureus’ three predominant STs without non-target bacterial interference. The limits of detection (LODs) for the mPCR assay in artificially contaminated milk were determined to be 10⁴ CFU/mL for ST7, 10⁵ CFU/mL for ST188, and 10⁴ CFU/mL for ST398, while the LODs achieved by the qPCR method were 8.6 × 10² CFU/mL, 1.2 × 10² CFU/mL, and 6.4 × 10³ CFU/mL, respectively. The testing results for actual food samples suggested that the developed mPCR or qPCR assays could be used as an alternative to standard MLST analysis, for the rapid and reliable identification of S. aureus STs. The novel molecular detection technology established in this study provides an efficient and reliable detection method for the prevention and control of predominant S. aureus ST contamination in food and has important application potential and promotion prospects. Full article

Maize stalk rot (MSR) is one of the most devastating fungal diseases affecting maize worldwide. In recent years, biological control agents have emerged as an environmentally friendly and highly attractive strategy for managing MSR. In this study, two Bacillus strains—B. subtilis KP3P9 and B. siamensis K13C—were shown to effectively inhibit the growth of the MSR pathogen Fusarium graminearum in vitro. Pot experiments showed that inoculation with KP3P9 significantly increased plant height, stem width, above-ground part fresh weight, and total plant fresh weight, whereas K13C significantly improved the stem width and under-ground part fresh weight of maize seedlings (p < 0.05), demonstrating their plant-growth-promoting potential. Moreover, both strains markedly reduced the disease severity indices (DSIs) of maize seedlings, indicating that they can enhance maize resistance to the pathogen. Whole-genome sequencing using Oxford Nanopore (ONT) and Illumina technologies showed that the complete genomes of KP3P9 and K13C contained biosynthetic gene clusters involved in the biosynthesis of antimicrobial secondary metabolites, including fengycin, bacillibactin, subtilin, pulcherriminic acid, subtilosin A, bacilysin, and others. Moreover, both strains exhibited strong antagonistic activity against F. solani (the causal pathogen of apple replant disease), as well as F. oxysporum f. sp. cubense race 1 (Foc1) and tropical race 4 (FocTR4) (pathogens responsible for banana wilt disease), with inhibition rates exceeding 70% in vitro. These results indicate that KP3P9 and K13C are promising biocontrol agents for MSR and other devastating Fusarium diseases. Full article

Nucleic acid aptamers are single-stranded DNA or RNA molecules that can bind to a target with high specificity and affinity, as screened by the Systematic Evolution of Ligands by Exponential Enrichment (SELEX). In recent years, SELEX technologies have been significantly advanced for the screening of aptamers for a variety of target molecules, cells, and even bacteria and viruses. By integrating recent advances of emerging technologies with SELEX, novel screening technologies for nucleic acid aptamers have emerged with improved screening efficiency, reduced production costs and enhanced aptamer performance for a wide range of applications in medical diagnostics, drug delivery, and environmental monitoring. Aptasensors utilize aptamers to detect a wide range of analytes, allowing for the accurate identification and determination of small molecules, proteins, and even whole cells with remarkable specificity and sensitivity. Further optimization of the aptasensor can be achieved by aptamer truncation, which not only maintains the high specificity and affinity of the aptamer binding with the target analytes, but also reduces the manufacturing cost. Predictive models also demonstrate the powerful capability of determination of the minimal functional sequences by simulation of aptamer–target interaction processes, thus effectively shortening the aptamer screening procedure and reducing the production costs. This paper summarizes the research progress of protein-targeted aptamer screening in recent years, introduces several typical aptasensors at present, discusses the optimization methods of aptasensors by combining efficient SELEX with advanced predictive algorithms or post-SELEX processes, as well as the challenges and opportunities faced by aptasensors. Full article

Climate change is intensifying droughts, heatwaves, dust storms, and rainfall variability across Eastern Europe, undermining yields and soil stability. In Ukraine, decades of underinvestment and wartime damage have led to widespread degradation of field shelterbelts, while the adoption of agroforestry remains constrained by tenure ambiguity, fragmented responsibilities, and limited access to finance. This study develops a policy-and-technology framework to restore agroforestry at scale under severe fiscal and institutional constraints. We apply a three-stage approach: (i) a national baseline (post-1991 legislation, statistics) to diagnose the biophysical and legal drivers of shelterbelt decline, including wartime damage; (ii) a comparative synthesis of international support models (governance, incentives, finance); and (iii) an assessment of transferability of digital monitoring, reporting, and verification (MRV) tools to Ukraine. We find that eliminating tenure ambiguities, introducing targeted cost sharing, and enabling access to payments for ecosystem services and voluntary carbon markets can unlock financing at scale. A digital MRV stack—Earth observation, UAV/LiDAR, IoT sensors, and AI—can verify tree establishment and survival, quantify biomass and carbon increments, and document eligibility for performance-based incentives while lowering transaction costs relative to field-only surveys. The resulting sequenced policy package provides an actionable pathway for policymakers and donors to finance, monitor, and scale shelterbelt restoration in Ukraine and in similar resource-constrained settings. Full article

Typhoid fever, caused by Salmonella enterica subsp. enterica serovar Typhi (S. typhi), remains a major public health concern, particularly in low-resource settings with poor sanitation. The emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains have significantly complicated treatment, especially in vulnerable pediatric populations. This study aimed to characterize the genetic profiles of drug resistance in MDR and XDR S. typhi isolates from pediatric patients. Methods: A cross-sectional study was conducted on 800 blood samples from pediatric typhoid patients. S. typhi isolates were identified using the BacT/ALERT 3D system, followed by culture on MacConkey and blood agar. Antimicrobial susceptibility was assessed using the disk diffusion method according to CLSI 2022 guidelines. Whole-genome sequencing (WGS) was performed on 29 isolates using Illumina MiSeq technology, and resistance genes and mutations were analyzed. Results: Antimicrobial susceptibility testing revealed that 68 (48.57%) of S. typhi isolates were XDR and 61 (43.57%) were MDR, exhibiting widespread resistance to ciprofloxacin, ampicillin, chloramphenicol, ceftriaxone, and co-trimoxazole. WGS identified key resistance genes across all 29 isolates, including bla_CTX-M-15, bla_TEM-1B, qnrS1, aac(6′)-Iaa, catA1, dfraA7, sul1, qacEΔ1, and the gyrA-S83F mutation. Notably, gyrA-S83F and qnrS1 were detected in all isolates and strongly correlated with ciprofloxacin resistance. Virulence genes were consistently present in all isolates, indicating a high pathogenic potential. The IncY plasmid, found in four (14%) isolates, was linked to resistance against third-generation cephalosporins, including ceftriaxone. Conclusion: This study underscores the alarming prevalence of MDR and XDR S. typhi isolates among pediatric patients, driven by resistance genes such as bla_CTX-M-15, bla_TEM-1B, and gyrA-S83F. These findings highlight the urgent need for targeted therapeutic strategies and robust surveillance systems to combat the growing threat of drug-resistant typhoid fever. Full article

Dairy products harbor complex and dynamic microbial communities that contribute to their sensory properties, safety, and cultural distinctiveness. Raw milk contains a diverse microbiota shaped by seasonality, storage conditions, lactation stage, animal health, farm management, and genetics, serving as a variable starting point for further processing. Fermentation, whether spontaneous or starter driven, selects for subsets of lactic acid bacteria (LAB), yeasts, and molds, resulting in microbial succession that underpins both artisanal and industrial products such as kefir and cheese. Kefir represents a balanced LAB–yeast symbiosis, with species composition influenced by grain origin, milk type, and processing parameters, whereas the cheese microbiota reflects the interplay of starter and non-starter LAB, coagulants, ripening conditions, and “house microbiota”. Methodological factors—including DNA extraction, sequencing platform, and bioinformatic pipelines—further impact the reported microbial profiles, highlighting the need for standardization across studies. This review synthesizes current knowledge on raw milk, kefir, and cheese microbiomes, emphasizing the biological, technological, environmental, and methodological factors shaping microbial diversity. A holistic understanding of these drivers is essential to preserve product authenticity, ensure safety, and harness microbial resources for innovation in dairy biotechnology. Full article

We investigated the use of gravel packing sand control technology in multi-lateral horizontal wells to support the development of natural gas hydrate reservoirs. An experimental apparatus was developed to investigate the effects of well configurations and operational parameters on ultra-light sand packing behavior and to estimate the field operational parameters through the application of similarity criteria. The results showed that the ultra-light sand packing process includes four stages in a single horizontal main bore, i.e., sand bank formation, alpha-wave, beta-wave, and simultaneous annulus packing, and two stages in lateral wellbores: a sand bank formation and then an alpha-wave pattern or an initial alpha-wave pattern followed by a slope pattern. At comparable injection rates and sand concentrations, the packing sequence is predominantly governed by leakage rates and the quantity of lateral wellbores. When the lateral wellbore is 1 m and the leakage rate exceeds 20%, the lateral packs first. When the lateral wellbore is 2 m and the leakage rate is below 30%, the main bore packs first. For the field prototype (480 m main bore and 200 m lateral wellbore), the deviation angle of lateral wellbores should be controlled within 30°, and it is recommended that the distance between the junction point and the heel of the horizontal main bore be 160 m. When the leakage rates exceed 50%, the recommended injection rates are less than 1.69 m³/min. When the leakage rates range from 10 to 50%, the recommended injection rates range from 1.69 to 3.38 m³/min, with predicted end-of-packing pressures ranging from 6.56 to 19.92 MPa. This study provides valuable insights into the development of gravel packing sand control technologies in a multi-lateral horizontal well for hydrate reservoirs. Full article

Recent advances in computational tools, particularly machine learning (ML), deep learning (DL), and structure-based modeling, are transforming aptamer research by accelerating discovery and enhancing biosensor development. This review synthesizes progress in predictive algorithms that model aptamer–target interactions, guide in silico sequence optimization, and streamline design workflows for both laboratory and point-of-care diagnostic platforms. We examine how these approaches improve key aspects of aptasensor development, such as aptamer selection, sensing surface immobilization, signal transduction, and molecular architecture, which contribute to greater sensitivity, specificity, and real-time diagnostic capabilities. Particular attention is given to illuminating the technological and experimental advances in structure-switching aptamers, dual-aptamer systems, and applications in electrochemical, optical, and lateral flow platforms. We also discuss current challenges such as the standardization of datasets and interpretability of ML models and highlight future directions that will support the translation of aptamer-based biosensors into scalable, point-of-care and clinically deployable diagnostic solutions. Full article

In recent years, symptoms of Twig Cankers and Shoot Blight (TCSB) have re-emerged in several Italian peach orchards, particularly within key production areas of the Emilia-Romagna region. The fungal pathogen Diaporthe amygdali is recognized as the primary causal agent of TCSB, leading to the rapid desiccation of shoots, flowers, leaves, and branches, often accompanied by resin exudation from cankers that appear in late winter or early spring. Given Italy’s position as the second-largest peach producer in Europe, ensuring sustainable yields and high fruit quality necessitates a deeper understanding of D. amygdali biology and the development of effective diagnostic and management tools. This study employed a hybrid whole-genome sequencing strategy, combining Illumina short-read and PacBio long-read technologies, to generate the first high-quality genome assembly of D. amygdali isolated from peach. The genome analysis revealed candidate virulence genes and other factors involved in pathogenicity, deepening our understanding of the infection strategies employed by D. amygdali. These findings may support the potential development of sustainable, effective strategies against TCSB, ultimately supporting resilient peach production in Italy and beyond. Full article