The goal of this article was to review studies on distal humerus fracture plates (DHFPs) to understand the biomechanical influence of systematically changing the plate or screw variables. The problem is that DHFPs are commonly used surgically, although complications can still occur, and it is unclear if implant configurations are always optimized using biomechanical criteria. A systematic search of the PubMed database was conducted to identify English-language biomechanical optimization studies of DHFPs that parametrically altered plate and/or screw variables to analyze their influence on engineering performance. Intraarticular and extraarticular fracture (EAF) data were separated and organized under commonly used biomechanical outcome metrics. The results identified 52 eligible DHFP studies, which evaluated various plate and screw variables. The most common plate variables evaluated were geometry, hole type, number, and position. Fewer studies assessed screw variables, with number and angle being the most common. However, no studies examined nonmetallic materials for plates or screws, which may be of interest in future research. Also, articles used various combinations of biomechanical outcome metrics, such as interfragmentary fracture motion, bone, plate, or screw stress, number of loading cycles to failure, and overall stiffness (Os) or failure strength (Fs). However, no study evaluated the bone stress under the plate to examine bone \"stress shielding,\" which may impact bone health clinically. Surgeons treating intraarticular and extraarticular distal humerus fractures should seriously consider two precontoured, long, thick, locked, and parallel plates that are secured by long, thick, and plate-to-plate screws that are located at staggered levels along the proximal parts of the plates, as well as an extra transfracture plate screw. Also, research engineers could improve new studies by perusing recommendations in future work (e.g., studying alternative nonmetallic materials or \"stress shielding\"), clinical ramifications (e.g., benefits of locked plates), and study quality (e.g., experimental validation of computational studies).

Control algorithms have been proposed based on knowledge related to nature-inspired mechanisms, including those based on the behavior of living beings. This paper presents a review focused on major breakthroughs carried out in the scope of applied control inspired by the gravitational attraction between bodies. A control approach focused on Artificial Potential Fields was identified, as well as four optimization metaheuristics: Gravitational Search Algorithm, Black-Hole algorithm, Multi-Verse Optimizer, and Galactic Swarm Optimization. A thorough analysis of ninety-one relevant papers was carried out to highlight their performance and to identify the gravitational and attraction foundations, as well as the universe laws supporting them. Included are their standard formulations, as well as their improved, modified, hybrid, cascade, fuzzy, chaotic and adaptive versions. Moreover, this review also deeply delves into the impact of universe-inspired algorithms on control problems of dynamic systems, providing an extensive list of control-related applications, and their inherent advantages and limitations. Strong evidence suggests that gravitation-inspired and black-hole dynamic-driven algorithms can outperform other well-known algorithms in control engineering, even though they have not been designed according to realistic astrophysical phenomena and formulated according to astrophysics laws. Even so, they support future research directions towards the development of high-sophisticated control laws inspired by Newtonian/Einsteinian physics, such that effective control-astrophysics bridges can be established and applied in a wide range of applications.

Lipase has high economic importance and is widely used in biodiesel, food, detergents, cosmetics, and pharmaceutical industries. The rapid development of synthetic biology and system biology has not only paved the way for comprehensively understanding the efficient operation mechanism of Aspergillus niger cell factories but also introduced a new technological system for creating and optimizing high-efficiency A. niger cell factories. In this review, all relevant data on microbial lipase enzyme sources and general properties are gathered and updated. The relationship between A. niger strain morphology and protein production is discussed. The safety of A. niger strain is investigated to ensure product safety. The biotechnologies and factors influencing lipase expression in A. niger are summarized. This review focuses on various strategies to improve lipase expression in A. niger. The summary of these methods and the application of the gene editing technology CRISPR/Cas9 system can further improve the efficiency of constructing the engineered lipase-producing A. niger.

Despite their widespread applications in sectors such as pulp and paper, textile, food and beverage, pharmaceuticals, and biofuel production, laccases encounter challenges related to their activity and stability under varying reaction conditions. This review accumulates data on the complex interplay between laccase characteristics and reaction conditions for maximizing their efficacy in diverse biotechnological processes. Benefits of organic media such as improved substrate selectivity and reaction control, and their risks such as enzyme denaturation and reduced activity are reported. Additionally, the effect of reaction conditions such as pH and temperature on laccase activity and stability are gathered and reported. Sources like Bacillus pumilus, Alcaligenes faecalis, Bacillus clausii, and Bacillus tequilensis SN4 are producing laccases that are both thermo-active and alkali-active. Additionally, changes induced by the presence of various substances within reaction media such as metals, inhibitors, and organic solvents are also reported. Bacillus pumilus and Bacillus licheniformis LS04 produce the most resistant laccases in this case. Finally, the remarkable laccases have been highlighted and the proper laccase source for each industrial application is suggested.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s13205-024-04015-5.

Non-antibiotic adjuncts may improve Helicobacter pylori infection control. Our aim was to emphasize curcumin benefits in controlling H. pylori infection. We discussed publications in English mostly published since 2020 using keyword search. Curcumin is the main bioactive substance in turmeric. Curcumin inhibited H. pylori growth, urease activity, three cag genes, and biofilms through dose- and strain-dependent activities. Curcumin also displayed numerous anticancer activities such as apoptosis induction, anti-inflammatory and anti-angiogenic effects, caspase-3 upregulation, Bax protein enhancement, p53 gene activation, and chemosensitization. Supplementing triple regimens, the agent increased H. pylori eradication success in three Iranian studies. Bioavailability was improved by liposomal preparations, lipid conjugates, electrospray-encapsulation, and nano-complexation with proteins. The agent was safe at doses of 0.5->4 g daily, the most common (in 16% of the users) adverse effect being gastrointestinal upset. Notably, curcumin favorably influences the intestinal microbiota and inhibits Clostridioides difficile. Previous reports showed the inhibitory effect of curcumin on H pylori growth. Curcumin may become an additive in the therapy of H. pylori infection, an adjunct for gastric cancer control, and an agent beneficial to the intestinal microbiota. Further examination is necessary to determine its optimal dosage, synergy with antibiotics, supplementation to various eradication regimens, and prophylactic potential.

Fengycin is an important member of the lipopeptide family with a wide range of applications in the agricultural, food, medical and cosmetic industries. However, its commercial application is severely hindered by low productivity and high cost. Therefore, numerous studies have been devoted to improving the production of fengycin. We summarize these studies in this review with the aim of providing a reference and guidance for future researchers. This review begins with an overview of the synthesis mechanism of fengycin via the non-ribosomal peptide synthetases (NRPS), and then delves into the strategies for improving the fengycin production in recent years. These strategies mainly include fermentation optimization and metabolic engineering, and the metabolic engineering encompasses enhancement of precursor supply, application of regulatory factors, promoter engineering, and application of genome-engineering (genome shuffling and genome-scale metabolic network model). Finally, we conclude this review with a prospect of fengycin production.

OBJECTIVE: One minute of operating room (OR) time costs $36 to 37. However, ORs are notoriously inefficient. There is growing literature on improving OR efficiency, but no formal review of this topic within otolaryngology has been performed. This study reviews and synthesizes the current literature on improving OR efficiency within otolaryngology.
METHODS: MEDLINE, EMBASE, Web of Science, CINAHL, Cochrane Library, preprints.org, and medRxiv were searched on November 4, 2022.
METHODS: Published English studies were included if they reported on metrics for improving OR efficiency within otolaryngology. There were no publication date restrictions. Articles were screened by 2 reviewers. Preferred Reporting Items for Systematic Reviews and Meta-analysis reporting for scoping reviews was followed.
RESULTS: The search yielded 9316 no-duplicate articles; 129 articles were included. Most of the studies reported on head and neck procedures (n = 52/129). The main tactics included surgical considerations: hemostatic devices, techniques, and team/simultaneous approaches; anesthetic considerations: local anesthetic and laryngeal mask airways; procedure location considerations: procedures outside of the OR and remote technologies; standardization: equipment, checklists, and personnel; scheduling considerations: use of machine learning for booking, considering patient/surgeon factors, and utilizing dedicated OR time/multidisciplinary teams for on-call cases.
CONCLUSIONS: The current literature brings to attention numerous strategies for improving OR efficiency within otolaryngology. Applying these strategies and implementing novel techniques to manage surgical cases may assist in offloading overloaded health care systems and improving access to care while facilitating patient safety and outcomes. Anticipated barriers to implementation include resistance to change, funding, and the current strain on health care systems and providers.

Deep Reinforcement Learning (DRL) has gained significant adoption in diverse fields and applications, mainly due to its proficiency in resolving complicated decision-making problems in spaces with high-dimensional states and actions. Deep Deterministic Policy Gradient (DDPG) is a well-known DRL algorithm that adopts an actor-critic approach, synthesizing the advantages of value-based and policy-based reinforcement learning methods. The aim of this study is to provide a thorough examination of the latest developments, patterns, obstacles, and potential opportunities related to DDPG. A systematic search was conducted using relevant academic databases (Scopus, Web of Science, and ScienceDirect) to identify 85 relevant studies published in the last five years (2018-2023). We provide a comprehensive overview of the key concepts and components of DDPG, including its formulation, implementation, and training. Then, we highlight the various applications and domains of DDPG, including Autonomous Driving, Unmanned Aerial Vehicles, Resource Allocation, Communications and the Internet of Things, Robotics, and Finance. Additionally, we provide an in-depth comparison of DDPG with other DRL algorithms and traditional RL methods, highlighting its strengths and weaknesses. We believe that this review will be an essential resource for researchers, offering them valuable insights into the methods and techniques utilized in the field of DRL and DDPG.

The global community is actively pursuing alternative energy sources to mitigate environmental concerns and decrease dependence on fossil fuels. Biodiesel, recognized as a clean and eco-friendly fuel with advantages over petroleum-based alternatives, has been identified as a viable substitute. However, its commercialization encounters challenges due to costly production processes. Establishing a more efficient supply chain for mass production and distribution could surmount these obstacles, rendering biodiesel a cost-effective solution. Despite numerous review articles across various renewable energy supply chain domains, there remains a gap in the literature specifically addressing the biodiesel supply chain network design. This research entails a comprehensive systematic literature review (SLR) focusing on the design of biodiesel supply chain networks. The primary objective is to formulate an economically, environmentally, and socially optimized supply chain framework. The review also seeks to offer a holistic overview of pertinent technical terms and key activities involved in these supply chains. Through this SLR, a thorough examination and synthesis of existing literature will yield valuable insights into the design and optimization of biodiesel supply chains. Additionally, it will identify critical research gaps in the field, proposing the exploration of fourth-generation feedstocks, integration of multi-channel chains, and the incorporation of sustainability and resilience aspects into the supply chain network design. These proposed areas aim to address existing knowledge gaps and enhance the overall effectiveness of biodiesel supply chain networks.

Meta-session autoregulation, a person-adaptive form of exercise prescription that adjusts training variables according to daily fluctuations in performance considering an individual\'s daily fitness, fatigue, and readiness-to-exercise is commonly used in sports-related training and may be beneficial for non-athlete populations to promote exercise adherence. To guide refinement of meta-session autoregulation, it is crucial to examine the existing literature and synthesize how these procedures have been practically implemented. Following PRIMSA guidelines a scoping review of two databases was conducted from August 2021 to September 2021 to identify and summarize the selected measures of readiness-to-exercise and decision-making processes used to match workload to participants in meta-session autoregulatory strategies, while also evaluating the methodological quality of existing study designs using a validated checklist. Eleven studies reported utilizing a form of meta-session autoregulation for exercise. Primary findings include: (i) readiness-to-exercise measures have been divided into either objective or subjective measures, (ii) measures of subjective readiness measures lacked evidence of validity, and (iii) fidelity to autoregulatory strategies was not reported. Results of the risk of bias assessment indicated that 45% of the studies had a poor-quality score. Existing implementations of meta-session autoregulation are not directly translatable for use in health promotion and disease prevention settings. Considerable refinement research is required to optimize this person-adaptive strategy prior to estimating effects related to exercise adherence and/or health and fitness outcomes. Based on the methodological deficits uncovered, researchers implementing autoregulation strategies would benefit reviewing existing models and frameworks created to guide behavioral intervention development.