Search Results (8,439)

Root rot in Lycium barbarum, an economically vital crop, is a critical barrier to its sustainable development in China. To elucidate the underlying micro-ecological mechanisms, this study aimed to characterize and compare the rhizosphere microbial communities of healthy and diseased plants from the Qaidam Basin. We employed PacBio full-length amplicon sequencing to analyze bacterial and fungal populations, complemented by network analysis and in vitro antagonistic assays. The results indicated that while microbial species richness was similar, the community structures of healthy and diseased soils were fundamentally different, suggesting that the disease is primarily driven by microbial dysbiosis rather than species loss. Healthy soil was enriched with beneficial Trichoderma, whereas diseased soil was dominated by the pathogen Fusarium, with an abundance 6.7 times higher than that in healthy soil. Network analysis revealed the healthy fungal community was significantly more stable (modularity index: 0.818) than the diseased network (0.4131), where Fusarium occupied a core hub position. Crucially, Trichoderma strains isolated from healthy soil exhibited strong antagonistic activity against Fusarium, with an average inhibition rate exceeding 75%. This study identifies Fusarium as the key pathogen of Goji root rot and native Trichoderma as a potent biocontrol agent, providing a scientific basis for a sustainable, micro-ecological control strategy. Full article

Improving the energy efficiency of traditional production methods while preserving their cultural and economic value is a challenge aligned with the Sustainable Development Goals of the 2030 agenda. Refrigeration during cheese maturation is particularly energy-intensive, contributing significantly to greenhouse gas emissions and operating costs. An approach to make traditional cheese production more sustainable, through the development of a prototype ripening chamber with a natural refrigerant-based refrigeration system powered by renewable energy was studied. A dedicated system based on an Internet of Things architecture was developed using low-cost sensors, microcontroller units, and single-board computers to enable real-time measurement and monitoring of environmental variables and energy consumption throughout the ripening process. A comparative analysis was conducted using ewe’s milk cheese, produced and ripened with Protected Designation of Origin conditions, in both the prototype and the conventional chambers over four weeks, quantifying energy consumption and evaluating product quality. Results demonstrate the technical feasibility of energy efficient and sustainable refrigeration systems, as well as the possibility of retrofitting installed cheese ripening chambers with affordable IoT monitoring systems, while maintaining traditional cheese quality standards. Full article

Ammonia is a gas primarily produced for use in agriculture, refrigeration systems, chemical manufacturing, and power generation. Despite its benefits, improper management of ammonia poses significant risks to human health and the environment. Consequently, monitoring ammonia is essential for enhancing industrial safety and preventing leaks that can lead to environmental contamination. Given the abundance and diversity of studies on Internet of Things (IoT) systems for gas detection, the main objective of this paper is to systematically review the literature to identify emerging research trends and opportunities. This review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, focusing on sensor technologies, microcontrollers, communication technologies, IoT platforms, and applications. The main findings indicate that most studies employed sensors from the MQ family (particularly the MQ-135 and MQ-137), microcontrollers based on the Xtensa architecture (ESP32 and ESP8266) and ARM Cortex-A processors (Raspberry Pi 3B+/4), with Wi-Fi as the predominant communication technology, and Blynk and ThingSpeak as the primary cloud-based IoT platforms. The most frequent applications were agriculture and environmental monitoring. These findings highlight the growing maturity of IoT technologies in ammonia sensing, while also addressing challenges like sensor reliability, energy efficiency, and development of integrated solutions with Artificial Intelligence. Full article

Precise regulation of micropipette outlet flow is critical for fluorescence imaging in vivo micromanipulations. In such procedures, a micropipette with a micro-sized opening is driven by gas pressure to deliver internal solution into the in vivo environment. The outlet flow rate needs to be precisely regulated to ensure a uniform and stable fluorescence distribution. However, conventional manual pressure injection methods face inherent limitations, including insufficient precision and poor reproducibility. Existing commercial microinjection systems lack a quantitative relationship between pressure and flow rate. And existing calibration methods in the field of microfluidics suffer from a limited flow-rate measurement resolution, constraining the establishment of a precise pressure–flow quantitative relationship. To address these challenges, we developed a closed-loop pressure regulation system with 1 Pa-level control resolution and established a quantitative calibration of the pressure–flow relationship using a droplet-based method. The calibration revealed a linear relationship with a mean pressure–flow gain of 4.846 $\times {10}^{-17}{\mathrm{m}}^3·{\mathrm{s}}^{-1}·{\mathrm{P}\mathrm{a}}^{-1}$ (R² > 0.99). Validation results demonstrated that the system achieved the target outlet flow rate with a flow control error less than 10 fL/s. Finally, the application results in brain-slice environment confirmed its capability to maintain stable fluorescence imaging, with fluorescence intensity fluctuations around 1.3%. These results demonstrated that the proposed approach provides stable, precise, and reproducible flow regulation under physiologically relevant conditions, thereby offering a valuable tool for in vivo micromanipulation and detection. Full article

Background/Objectives: Type 2 Diabetes Mellitus (T2DM) represents a significant global health burden, frequently leading to severe complications such as peripheral neuropathy and both micro- and macrovascular dysfunctions. These complications are integral to the pathology of diabetic foot ulcers (DFUs) and are associated with an elevated risk of lower limb amputations. This study investigated lower extremity skeletal muscle perfusion in patients with T2DM and DFUs using [¹⁵O]H₂O PET imaging, in comparison to healthy controls. Methods: A total of 10 healthy controls and 26 patients with T2DM and DFUs were enrolled. Resting skeletal muscle perfusion was quantified using [¹⁵O]H₂O PET. Regional perfusion was assessed in multiple lower leg and foot muscle groups. Distal blood pressure was measured, and foot/leg perfusion ratios were calculated. Results: Patients with T2DM and DFUs exhibited a 58% higher median global foot resting perfusion compared to healthy controls. At the individual muscle level, median perfusion in the flexor hallucis brevis was elevated by up to 210% in the ulcerated foot compared to controls. No significant differences in perfusion were observed in the non-ulcerated foot. The foot/leg perfusion ratio was up to 58% higher in the ulcerated limb of T2DM patients compared to the controls. Conclusions: This study demonstrates localized alterations in skeletal muscle perfusion in patients with T2DM and DFUs, characterized by elevated resting foot perfusion in muscles adjacent to ulcerations. Understanding these perfusion dynamics may contribute to refined DFU management strategies. However, further research is needed to validate the clinical utility of [¹⁵O]H₂O PET imaging in guiding interventions and predicting treatment outcomes for DFUs. Full article

The current study focuses on axial ultrasonic vibration-assisted micro-milling as an advanced technique to improve the machining performance of Ti6Al4V, a material whose difficult-to-cut properties present a significant barrier to manufacturing the high-quality micro-components essential for aerospace and biomedical applications. A full factorial design was employed to evaluate the influence of feed-per-tooth (f_z), axial depth-of-cut (a_p), and ultrasonic vibration on cutting forces, surface roughness, burr formation, and tool wear. Experimental results demonstrate that ultrasonic assistance significantly reduces cutting forces by 20.09% and tool wear by promoting periodic tool–workpiece separation and improving chip evacuation. However, it increases surface roughness due to the formation of uniform micro-dimples, which may enhance tribological properties. Burr dimensions were primarily governed by feed-per-tooth, with higher feeds minimizing burr size. The study provides actionable insights into optimizing machining parameters for cutting Ti6Al4V, highlighting the trade-offs between force reduction, surface texture, and burr control. These findings contribute to advancing ultrasonic-assisted micro-milling for industrial applications, namely aerospace and biomedical applications requiring high precision and extended tool life. Full article

Neural networks are powerful, high-accuracy systems whose trained parameters represent a valuable intellectual property. Building models that reach top level performance is a complex task and requires substantial investments of time and money so protecting these assets is an increasingly important task. Extensive research has been carried out on Neural Network Watermarking, exploring the possibility of inserting a recognizable marker in a host model either in the form of a concealed bit-string or as a characteristic output, making it possible to confirm network ownership even in the presence of malicious attempts at erasing the embedded marker from the model. The study examines the applicability of Opt-FreeMark, a non-invasive post-training white-box watermarking technique, obtained by modifying and optimizing an already existing state-of-the-art technique for tiny neural networks. Here, “Tiny” refers to models intended for ultra-low-power deployments, such as those running on edge devices like sensors and micro-controllers. Watermark robustness is also demonstrated by simulating common model-modification attacks that try to eliminate it from the model while preserving performance; the results presented in the paper indicate that the watermarking scheme effectively protects the networks against these manipulations. Full article

Dysregulated microRNAs (miRNAs) have been implicated in the pathogenesis and progression of rectal adenocarcinoma. In this study, we aimed to identify miRNA alterations associated with the efficacy of neoadjuvant chemoradiotherapy in rectal cancer patients. High-throughput small RNA sequencing was performed to assess salivary miRNA expression profiles in 31 participants (11 rectal adenocarcinoma patients and 20 healthy volunteers). Paired saliva samples were collected from patients before and after chemoradiation. Tumor regression was classified according to the modified Ryan scheme into responders (tumor regression grade [TRG] 1–2, n = 10) and nonresponders (TRG3, n = 1). Bioinformatic integration of small non-coding RNA data revealed 37 miRNAs with distinct expression differences between patients and healthy controls. Furthermore, seven miRNAs showed significant alterations in response to radiotherapy. Among these, five candidates (hsa-miR-378a-3p, hsa-miR-203a-3p, hsa-miR-200a-5p, hsa-miR-361-5p, and hsa-miR-107) were successfully validated by RT-qPCR, displaying significantly increased salivary expression levels post-radiation compared with the pre-radiation samples (p < 0.05). Notably, hsa-miR-203a-3p, hsa-miR-200a-5p, and hsa-miR-361-5p demonstrated excellent discriminatory power for tumor regression grade (AUC > 0.7). Our findings support the involvement of specific salivary miRNAs in rectal adenocarcinoma tumor regression and highlight their potential as non-invasive biomarkers to evaluate treatment response following neoadjuvant chemoradiotherapy. Full article

Rotary Steerable System (RSS) enhances directional drilling efficiency by over 300% via dynamic bit adjustment during string rotation. This study aims to systematically address these bottlenecks, quantify technical boundaries, and propose actionable breakthrough paths for China’s RSS technology in shale gas development. To address China’s shale gas RSS bottlenecks, this study proposes a “Material-Algorithm-System” tri-level strategy centered on an innovative “Tri-loop System.” Key innovations include (1) silicon nitride–tungsten carbide composite coatings to enhance thermal resilience, tested to withstand 220 °C, reducing thermal failure risk by 40% compared to conventional materials; (2) downhole reinforcement learning optimization; (3) a “Tri-loop System” integrating downhole intelligent control, wellbore-surface bidirectional communication, and cloud monitoring, shortening downhole command response latency from over 5 s to less than 1 s. In practical shale gas development scenarios—such as the Sichuan Basin’s deep coalbed methane wells and Shengli Oilfield’s tight reservoirs—this tri-level strategy has proven effective: the high-frequency electromagnetic wave radar increased thin coal seam drilling encounter rate by 23%, while the piezoelectric ceramic micro-actuators reduced tool failure rate by 35% in 175–200 °C environments. This approach targets raising China’s shale gas RSS application rate to 60%, supporting sustainable oil and gas exploration. Full article

Membrane separation is a promising technology for emulsified wastewater treatment. However, conventional membrane often suffer from limitations such as low mechanical strength, the inherent “trade-off” effect between flux and separation efficiency, and poor antifouling properties. To address these challenges, we report a novel composite membrane (CFM-UiO-66-(COOH)₂) fabricated by in situ growth of functionalized UiO-66-(COOH)₂ on a mechanically robust collagen fiber membrane (CFM) substrate. The resulting composite leverages the inherent properties of the CFM, along with the controlled generation of charge-neutralization demulsification sites and size-sieving filtration layers from the UiO-66-(COOH)₂. This CFM-UiO-66-(COOH)₂ exhibited superwetting behavior and achieved efficient separation of cationic surfactant-stabilized oil-in-water micro- and nano-emulsions. Specifically, the CFM-UiO-66-(COOH)₂ achieved separation efficiencies exceeding 99.85% for various cationic O/W emulsions, with permeation fluxes ranging from 178.9 to 225.9 L·m⁻²·h⁻¹. The membrane also demonstrated robust antifouling properties, excellent acid/alkali resistance, high abrasion durability, and good biocompatibility. Importantly, stable performance was maintained over six consecutive separation cycles. These characteristics, combined with the electrostatic interactions between carboxyl groups on the UiO-66-(COOH)₂ and cationic contaminants, suggest that CFM-UiO-66-(COOH)₂ holds significant potential for practical and sustainable wastewater treatment applications. Full article

Wearable devices can be developed using hardware platforms such as Application Specific Integrated Circuits (ASICs), Graphics Processing Units (GPUs), Digital Signal Processors (DSPs), Micro controller Units (MCUs), or Field Programmable Gate Arrays (FPGAs), each with distinct advantages and limitations. ASICs offer high efficiency but lack flexibility. GPUs excel in parallel processing but consume significant power. DSPs are optimized for signal processing but are limited in versatility. CPUs provide low power consumption but lack computational power. FPGAs are highly flexible, enabling powerful parallel processing at lower energy costs than GPUs but with higher resource demands than ASICs. The combined use of FPGAs and CPUs balances power efficiency and computational capability, making it ideal for wearable systems requiring complex algorithms in far-edge computing, where data processing occurs onboard the device. This approach promotes green electronics, extending battery life and reducing user inconvenience. The primary goal of this work was to develop a versatile framework, similar to existing software development frameworks, but specifically tailored for mixed FPGA/MCU platforms. The framework was validated through a real-world use case, demonstrating significant improvements in execution speed and power consumption. These results confirm its effectiveness in developing green and smart wearable systems. Full article

Cold stress reduces horticultural crop yield and postharvest quality by disrupting membrane fluidity, redox equilibrium, and the cell wall structure. This results in chilling injury, tissue softening, and loss of color. Long noncoding RNAs (lncRNAs) have emerged as key integrators of plant cold signaling pathways. LncRNAs mediate the interaction between calcium signaling systems and transcriptional cascades while coordinating hormone signaling networks, including those involving abscisic acid, jasmonic acid, ethylene, salicylic acid, and brassinosteroids. LncRNAs influence gene regulation through chromatin-based guidance, sequestration of repressive complexes, natural antisense transcriptional interference, microRNA-centered competing endogenous RNA networks, and control of RNA splicing, stability, localization, and translation. Studies in horticultural species revealed that cold-responsive lncRNAs regulate processes essential for fruit firmness, antioxidant levels, and shelf-life, including lipid modification, reactive oxygen species balance, and cell wall or cuticle remodeling. This review aims to summarize tissue- and developmental stage-specific expression patterns and highlight experimental approaches to validate RNA function, including gene editing, transcript recovery, advanced sequencing, and analysis of protein-RNA interactions. Integrating these results will facilitate the development of precise molecular markers and nodes of regulatory networks that increase cold tolerance, and improve the quality of horticultural crops. Full article

From advanced research platforms to Unmanned Aerial Vehicles (UAVs), Micro Turbojet Engines (MTEs) have grown to be essential parts in many different kinds of applications. Extensive testing, encompassing analysis, alternative fuel suitability, performance characterization, and control system validation, supports their development. This survey examines the current state of MTE experimentation, along with information on experimental methods, sensor technologies, and new directions in corresponding research. Measurement techniques, alternative fuel effects, characterization of gaseous and particle emissions, and the utilization of experimental data to validate control systems and sophisticated engine models are among the recent advances in test bed design discussed here. Presenting an overall view, the aim is to highlight current challenges and inspire more MTE technology advancement. Full article

Background/Objectives: Aseptic loosening (AL) is among the most common causes of late failure following total hip arthroplasty (THA), often necessitating complex revision surgery. Current diagnostic tools, mainly based on clinical and radiological findings, are primarily able to identify advanced changes of periprosthetic osteolysis (PPOL). Therefore, early detection of AL remains a challenge. Circulating microRNAs (miRNAs) have emerged as promising, minimally invasive biomarkers in musculoskeletal disorders. This study investigates the expression of inflammation-related miRNAs let-7i-5p, let-7e-5p, miR-15a-5p, miR-30a-3p and miR-130a-3p in patients with confirmed AL after THA to evaluate their potential role in AL. Methods: AL patients undergoing revision were compared with asymptomatic post-THA individuals and controls with degenerative osteoarthritis. Preoperative, peripheral blood samples were collected; total RNA was extracted; and quantitative real-time PCR (qRT-PCR) was performed to quantify miRNA expression. The relative expression of miRNAs was calculated using the 2–ΔΔCt method after proper normalization of Ct values. Statistical analysis assessed differences between groups. Results: The under investigation miRNAs exhibited distinct expression patterns. Several targets demonstrated significant downregulation in AL patients, suggesting a potential link to inflammatory and osteolytic pathways like Toll-like receptor 4 (TLR4)–Nuclear Factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling, NLRP3 inflammasome activation and macrophage polarization. Conclusions: The observed alterations in circulating miRNAs support their capability as biomarkers for early detection of AL following THA. Larger cohorts could facilitate translation into routine clinical diagnostics. Full article

MicroRNAs (miRNAs), small non-coding RNAs, have emerged as promising diagnostic and prognostic biomarkers for various diseases. However, their role in the pathogenesis of type 2 diabetes mellitus (T2DM) remains insufficiently defined. This case–control study investigated associations between genetic variants in miRNA genes and susceptibility to T2DM in a Greek population. A total of 716 individuals with T2DM and 569 controls (HbA1c < 6.5% and fasting plasma glucose < 126 mg/dL) were included. Genomic DNA was extracted from whole blood and genotyped using the Illumina Infinium PsychArray platform. Polymorphisms in MIR124a, MIR27a, MIR146a, MIR34a, MIRLET7A2, MIR128a, MIR196a2, MIR499a, MIR4513, and MIR149 were analyzed, with all SNPs within 20 kb upstream and downstream of each gene assessed. Allele frequencies were compared between cases and controls using PLINK. Significant associations with increased T2DM risk were observed for rs1531212 (OR = 1.375, p = 0.018) in MIR23aHG (containing MIR27a) and rs6120777 (OR = 1.27, p = 0.018) in MYH7B, upstream of MIR499a. Conversely, rs2425012 (OR = 0.794, p = 0.018) upstream of MIR27a, as well as rs883517 (OR = 0.728, p = 0.024) and rs2961920 (OR = 0.80, p = 0.041) upstream of MIR146a, appeared protective. Under the dominant model, two additional associations emerged: rs3746435 (OR = 1.239, p = 0.025) in MYH7B (upstream of MIR499a) and rs3746444 (OR = 1.235, p = 0.046) in MIR499a. In conclusion, this study identifies three novel genetic variants near MIR27a and MIR499a that may influence susceptibility to T2DM. These findings warrant validation in larger cohorts and functional studies to clarify their role in T2DM pathogenesis. Full article