Search Results (5,078)

Engineering of a bifunctional enzyme that combines DNA-dependent DNA polymerase and reverse transcriptase (RT) activities is a highly promising biotechnological goal, as it would enable one-enzyme RT-PCR. For this purpose, we selected the high-fidelity Pyrococcus furiosus (Pfu) DNA polymerase as engineering scaffold. The selection of amino acid residues for replacement was carried out based on a multi-sequence alignment of diverse DNA polymerases and literature data, which allowed us to target amino acids, which presumably are triggers of the RT activity appearance. Six mutant variants of the Pfu enzyme were created and their activity was analyzed. Through enzymatic screening, we identified the Pfu-M6 variant, which exhibits dual DNA-dependent and RNA-dependent DNA polymerase activity. This thermostable enzyme retains its inherent DNA polymerase function and has acquired the ability to catalyze reverse transcription under standard PCR conditions, which allows the created mutant form to be used for efficient amplification of DNA starting from an RNA template. Full article

G protein-coupled receptors (GPCRs) are considered the largest and most variable family of transmembrane receptors regulating physiological processes such as toxicological responses and insecticide resistance development. The present study investigated the responses of Methuselah (Mth), belonging to GPCR family B in the Diamondback Moth (DBM), Plutella xylostella, to chlorantraniliprole (CAP). Genome-wide identification and phylogenetic analysis of Pxmth genes revealed their evolutionary relationships and functional classifications. Expression profiling demonstrated significant overexpression of Pxmth2 in the CAP-resistant strain. Additionally, the tertiary and secondary structures of Pxmth2 were characterized, providing insights into its functional role. Silencing Pxmth2 via RNA interference (RNAi) reduced resistance of DBM to CAP and suppressed downstream stress-associated genes (CYP6B6, CYP6B7, CYP6BF1), increasing susceptibility to the insecticide. The function of Pxmth2 was further explored using a transgenic line of Drosophila melanogaster engineered to overexpress the gene; flies overexpressing Pxmth2 exhibited a significantly increased resistance to CAP compared to controls. These findings indicate that Pxmth2 contributes to CAP resistance in DBM and highlights potential molecular targets for improving pest management strategies. Full article

We investigated the use of a rubric-guided peer-review activity in two first-year engineering calculus groups (N = 38). The intervention involved three phases: (1) students completed a short integration worksheet and predicted their own score, (2) they engaged in peer marking both before and after an instructor-led solution walk-through with explicit criteria, and (3) they later took a midterm test and completed a post-activity questionnaire. To examine ability-level effects, we applied a dual-perspective quartile approach that classified both reviewers and reviewees (targets) by their instructor-assigned marks. Results showed that peer-grading error decreased by 3–5 points across all reviewer–target combinations, with the largest reduction observed when lower-achieving students graded the work of similarly low-achieving peers. Mid-achieving students also improved the calibration, cutting self-assessment error by half. Performance gains carried over to subsequent assessments: average midterm scores increased significantly for the bottom two quartiles. Survey responses (≥3.4/5) indicated that 60–70% of students found the activity beneficial for their understanding and exam preparation. Overall, the study demonstrates that rubric-guided peer review and assessment, when analyzed through a novel dual-lens quartile framework, can sharpen feedback accuracy, improve self-evaluation and enhance exam performance for mid- and lower-performing students while offering equity-oriented implications for assessment design. Full article

Precision Feeding Systems (PFS) demonstrate transformative potential in advancing sustainable and efficient production within modern animal husbandry. However, existing research lacks a synthesis of PFS applications in livestock farming and offers little targeted guidance for China’s rapidly growing rabbit industry. The objective of this review is to bridge this gap by synthesizing current knowledge on PFS technologies—including sensor networks, artificial intelligence (AI), automated controls, and data analytics—and providing a structured framework for their implementation in rabbit production. This study selects and analyzes 112 core references, establishing a foundational database for comprehensive evaluation. The key contributions of this work are threefold: first, it outlines the core components and operational mechanisms of PFS; second, it identifies major challenges such as sensor reliability in dynamic environments, data security risks, limited explainability of AI models, and interoperability barriers; and third, it proposes a customized strategy for PFS adoption in rabbit farming, emphasizing phased implementation, cross-system integration, and iterative optimization. The primary outcomes and advantages of adopting such a system include significant improvements in feed efficiency, resource utilization, animal welfare, and waste reduction—critical factors given rabbits’ sensitive digestive systems and precise nutritional needs. Furthermore, this review outlines a future research agenda aimed at developing resilient sensors, explainable AI frameworks, and multi-objective optimization engines to enhance the commercial scalability and sustainability of PFS in rabbit husbandry and beyond. Full article

Ultrasound-responsive micro/nanobubbles (MNBs) are promising tools for targeted cancer therapy due to their controllable acoustic activation and real-time imaging. Despite extensive research, the quantitative relationship between bubble structure, acoustic response, and therapeutic efficacy remains poorly understood. This knowledge gap hinders parametric design and clinical standardization. This review summarizes recent advances from an engineering perspective, highlighting how structural parameters—such as size, shell, gas core, and ligand density—affect acoustic sensitivity and drug release. Furthermore, the roles of microfluidic electroporation and cell membrane coating are discussed in terms of controllable fabrication and preservation of biological functions, highlighting their significance for reproducible and predictable therapies. In conclusion, this review establishes a “Structure-Response-Efficacy (S-R-E)” framework to summarize the core relationships between structural design and acoustic modulation. We propose an engineering strategy based on a standardized parameter system to guide the predictable design and clinical translation of ultrasound-based theranostic platforms. Full article

Hydroxytyrosol (HXT), a phenolic compound from olive, shows great potential as a neuroprotective agent and a translational target for claim-ready nutrition and food products. Human studies increasingly report benefits for vascular function, inflammatory tone, and early cognitive/psychomotor outcomes, consistent with engagement of redox and signalling pathways (Keap1–Nrf2–ARE, PI3K/Akt–ERK, and AMPK–SIRT1–PGC-1α). HXT is rapidly absorbed and likely reaches the brain, acting on endothelial and microglial targets. On the neurovascular axis, it reduces oxidative stress, preserves nitric-oxide bioavailability, lower inflammatory markers, and favourable intrinsic connectivity. For product development, bitterness from oleuropein-rich inputs can be mitigated by hydrolysis, followed by structure-guided delivery to balance sensory quality with exposure. Viable formats include cyclodextrin inclusion, microencapsulation, and (micro)emulsions in lipid matrices, plus stability engineering for aqueous systems (acidification, chelation, low-oxygen handling, or barrier packaging). Matrix effects are consequential; some proteins and fibers may decrease HXT bioaccessibility, whereas lipid phases and microstructured carriers often enhance it. Clinically, recommended doses are ~7–15 mg/day chronically and ~30–60 mg acutely. As conclusions of this review, future work should prioritize harmonized pharmacokinetics–pharmacodynamics readouts, cognition anchored to a compact neurovascular/blood–brain barrier biomarker core, and head-to-head comparisons of manufacturable delivery formats. Full article

Coagulation–flocculation, historically reliant on simple inorganic salts, has evolved into a technically sophisticated process that is central to the removal of turbidity, suspended solids, organic matter, and an expanding array of micropollutants from complex wastewaters. This review synthesizes six decades of research, charting the transition from classical aluminum and iron salts to high-performance polymeric, biosourced, and hybrid coagulants, and examines their comparative efficiency across multiple performance indicators—turbidity removal (>95%), COD/BOD reduction (up to 90%), and heavy metal abatement (>90%). Emphasis is placed on recent innovations, including magnetic composites, bio–mineral hybrids, and functionalized nanostructures, which integrate multiple mechanisms—charge neutralization, sweep flocculation, polymer bridging, and targeted adsorption—within a single formulation. Beyond performance, the review highlights persistent scientific gaps: incomplete understanding of molecular-scale interactions between coagulants and emerging contaminants such as microplastics, per- and polyfluoroalkyl substances (PFAS), and engineered nanoparticles; limited real-time analysis of flocculation kinetics and floc structural evolution; and the absence of predictive, mechanistically grounded models linking influent chemistry, coagulant properties, and operational parameters. Addressing these knowledge gaps is essential for transitioning from empirical dosing strategies to fully optimized, data-driven control. The integration of advanced coagulation into modular treatment trains, coupled with IoT-enabled sensors, zeta potential monitoring, and AI-based control algorithms, offers the potential to create “Coagulation 4.0” systems—adaptive, efficient, and embedded within circular economy frameworks. In this paradigm, treatment objectives extend beyond regulatory compliance to include resource recovery from coagulation sludge (nutrients, rare metals, construction materials) and substantial reductions in chemical and energy footprints. By uniting advances in material science, process engineering, and real-time control, coagulation–flocculation can retain its central role in water treatment while redefining its contribution to sustainability. In the systems envisioned here, every floc becomes both a vehicle for contaminant removal and a functional carrier in the broader water–energy–resource nexus. Full article

With the increasing age and traffic load of highway networks in China, preventive maintenance has become a critical strategy for extending pavement service life and improving infrastructure sustainability. However, the lack of standardized post-evaluation systems has hindered the scientific assessment of maintenance effectiveness. This study proposes a systematic post-evaluation framework for highway preventive maintenance projects based on the Hazard Analysis and Critical Control Points (HACCP)-Inspired methodology (Applying Principles of Hazard Analysis and CCP Identification). Adopting a full life-cycle perspective, the framework identifies critical control points (CCPs) across pre-, mid-, and post-implementation phases, targeting six key dimensions: ecological and environmental hazards, resource utilization hazard, engineering safety risks, engineering quality risks, socioeconomic benefit hazards, and social living environment hazards. A multi-level evaluation indicator system is constructed using hierarchical clustering and weighted through the Analytic Hierarchy Process (AHP). The framework is applied to a preventive maintenance project on the Jinghuan Expressway in Tianjin, China, demonstrating strong practical applicability. The final evaluation score of 84.1 out of 100 confirms the technical adequacy of the project while revealing areas for improvement in clean energy adoption and substructure monitoring. This framework provides a robust basis for standardizing post-evaluation practices and promoting sustainable highway maintenance management. Full article

The integration of nanotheranostics into cancer treatment represents a transformative shift in oncology, combining precision diagnostics with targeted therapeutic interventions. This manuscript explores the advancements in nanotechnology-driven cancer therapies, highlighting the role of engineered nanoparticles, such as liposomes, dendrimers, polymeric micelles, and virus-like particles, in enhancing drug delivery, real-time imaging, and tumor-specific targeting. Additionally, emerging therapies, including immunotherapy, gene editing, and chromophore-assisted light inactivation (CALI), are discussed in the context of personalized medicine. The convergence of these strategies is poised to redefine cancer treatment paradigms, improving therapeutic efficacy while minimizing systemic toxicity. This review outlines the key challenges, current limitations, and future directions in nanotheranostic applications, emphasizing the need for interdisciplinary collaboration to optimize their clinical translation. Full article

Real-Time PCR (qPCR) is an extensively used biomolecular tool for the detection and quantification of nucleic acids for a variety of applications, spanning from clinical to environmental settings. However, qPCR relies on an external calibration curve and can be susceptible to inhibition caused by pollutants that are commonly found in environmental samples. More recently, droplet digital PCR (ddPCR) was proven to be the method of choice for detection and quantification when a target is present at a low abundance. While it has been extensively utilized in clinical studies, only a small amount of data is available for complex samples, which are often characterized by a low target concentration and high abundances of non-target and PCR inhibitors. In this study, ddPCR and qPCR assays were performed on the same DNA serial dilutions with both Eva/SYBR Green and TaqMan chemistry. The comparative analysis was conducted on seven different samples taken from environmental and engineered settings. Ammonia-oxidizing bacteria (AOB) were chosen as the target, as they are ubiquitous and widespread and responsible for a fundamental environmental process in the global biogeochemical nitrogen cycle and in engineered settings such as wastewater treatment plants (WWPTs). ddPCR produced precise, reproducible, and statistically significant results in all samples, also showing an increased sensitivity to detecting AOB in complex samples characterized by low levels of the target and low target/non-target ratios. Full article

Although the Dung Beetle Optimizer (DBO) is a promising new metaheuristic for global optimization, it often struggles with premature convergence and lacks the necessary precision when applied to complex optimization challenges. Therefore, we developed the Multi-Strategy Improved Dung Beetle Optimizer (MIDBO), an algorithm that incorporates several new strategies to enhance the performance of the standard DBO. The algorithm enhances initial population diversity by improving the distribution uniformity of the Circle chaotic map and combining it with a dynamic opposition-based learning strategy for initialization. A nonlinear oscillating balance factor and an improved foraging strategy are introduced to achieve a dynamic equilibrium between the algorithm’s global search and local refinement, thereby accelerating convergence. A multi-population differential co-evolutionary mechanism is designed, wherein the population is partitioned into three categories according to fitness, with each category using a unique mutation operator to execute targeted searches and avoid local optima. A comparative study against multiple metaheuristics on the CEC2017 and CEC2022 benchmarks was performed to comprehensively evaluate MIDBO’s performance. The practical effectiveness of the MIDBO algorithm was validated by applying it to three practical engineering challenges. The results demonstrate that MIDBO significantly outperformed the other algorithms, a success attributed to its superior optimization performance. Full article

In the past decade, research on recombinant oncolytic viral agents in the treatment of solid tumors has evolved from the initial stage of simple genetic engineering to the current stage of multiple pipelines of parallel clinical application and combination therapy. Compared with T-VEC, the classical therapeutic agent that only expresses GM-CSF, which was approved in 2015, most new oncolytic virus designs include diverse gene constructs to reduce toxic effects, enhance multiple antitumor immunity, avoid immune clearance, or enhance tumor targeting. The single route of administration that activates the inflammatory tumor immune microenvironment by intratumoral injection is no longer sufficient to meet the treatment needs of refractory solid tumors. In this review, we illustrated the construction patterns of typical recombinant oncolytic viral agents and their latest clinical trial progress. Secondly, we summarized the underlying mechanisms of the combined application of antiviral and antitumor immunity in the field of solid tumor immunotherapy. Finally, we explored the feasibility of the intravenous application of oncolytic viruses and their future development directions. We believe that the diversified treatment design of oncolytic viruses will bring more surprises to the immunotherapy of refractory tumors. Full article

Neurodegenerative diseases, including Alzheimer’s disease (AD) and Parkinson’s disease (PD), present a growing public health challenge globally. Recent advancements in neurotechnology and neuroengineering have significantly enhanced brain–computer interfaces, artificial intelligence, and organoid technologies, making them pivotal instruments for diagnosis, monitoring, disease modeling, treatment development, and rehabilitation of various diseases. Nonetheless, the majority of neural interface platforms focus on unidirectional control paradigms, neglecting the need for co-adaptive systems where both the human user and the interface continually learn and adapt. This selected review consolidates information from neuroscience, artificial intelligence, and organoid engineering to identify the conceptual underpinnings of co-adaptive and symbiotic human–machine interaction. We emphasize significant shortcomings in the advancement of long-term AI-facilitated co-adaptation, which permits individualized diagnostics and progression tracking in Alzheimer’s disease and Parkinson’s disease. We concentrate on incorporating deep learning for adaptive decoding, reinforcement learning for bidirectional feedback, and hybrid organoid–brain–computer interface platforms to mimic disease dynamics and expedite therapy discoveries. This study outlines the trends and limitations of the topics at hand, proposing a research framework for next-generation AI-enhanced neural interfaces targeting neurodegenerative diseases and neurological disorders that are both technologically sophisticated and clinically viable, while adhering to ethical standards. Full article

This study introduces an autonomous framework for grasping moving objects on a conveyor belt, enabling unsupervised detection, grasping, and categorization. The work focuses on two common object shapes—cylindrical cans and rectangular cartons—transported at a constant speed of 3–7 cm/s on the conveyor, emulating typical scenarios. The proposed framework combines a vision-based neural network for object detection, a target localization algorithm, and a deep reinforcement learning model for robotic control. Specifically, a YOLO-based neural network was employed to detect the 2D position of target objects. These positions are then converted to 3D coordinates, followed by pose estimation and error correction. A Proximal Policy Optimization (PPO) algorithm was then used to provide continuous control decisions for the robotic arm. A tailored reinforcement learning environment was developed using the Gymnasium interface. Training and validation were conducted on a 7-degree-of-freedom (7-DOF) robotic arm model in the PyBullet physics simulation engine. By leveraging transfer learning and curriculum learning strategies, the robotic agent effectively learned to grasp multiple categories of moving objects. Simulation experiments and randomized trials show that the proposed method enables the 7-DOF robotic arm to consistently grasp conveyor belt objects, achieving an approximately 80% success rate at conveyor speeds of 0.03–0.07 m/s. These results demonstrate the potential of the framework for deployment in automated handling applications. Full article

Bacterial vaginosis (BV) is a highly prevalent vaginal infection characterized by a dysbiotic shift in the vaginal microbiota, with Gardnerella vaginalis acting as a principal pathogen. Despite its association with adverse reproductive outcomes, BV remains underexplored from both mechanistic and therapeutic standpoints. Standard antibiotic regimens frequently fail due to high recurrence rates driven by multidrug-resistant (MDR) G. vaginalis strains and biofilm formation. In response, natural compounds and nutraceuticals, owing to their intrinsic antibacterial, antibiofilm, and immunomodulatory properties, have emerged as promising candidates for alternative BV therapies. In this paper, we first compile and critically evaluate preclinical and clinical evidence on the efficacy of plant extracts, essential oils (EOs), probiotics, vitamins, proteins, fatty acids, and enzymes against G. vaginalis, emphasizing their mechanistic insights in restoring vaginal microbial balance. Next, we focus on the integration of these bioactive agents into engineered nanosystems, such as lipid-based nanoparticles (LNPs), polymeric carriers, and inorganic nanostructures, to overcome limitations related to solubility, stability, and targeted delivery. Nonetheless, comparative studies, combination therapies, and recent patent developments are discussed to highlight how naturally derived molecules can enhance antimicrobial potency and reduce cytotoxicity. In conclusion, these platforms demonstrate superior in vitro and in vivo efficacy, offering a paradigm shift in the management of BV. Key challenges include scalable manufacturing, regulatory approval, and comprehensive safety assessment. Future research should prioritize standardized nanoparticle (NP) synthesis, detailed pharmacokinetic and toxicity profiling, and well-designed clinical trials to validate nature-inspired, nanoengineered therapies against G. vaginalis-induced BV. Full article