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Dialysis withdrawal has become an accepted treatment option for patients with kidney failure and is one of the leading causes of death in patients receiving dialysis in high-income countries. Despite its increasing acceptance, dialysis withdrawal currently lacks a clear, consistent definition. The processes and outcomes of dialysis withdrawal have wide temporal and geographical variability, attributed to dialysis patient selection, influence from cultural, religious and spiritual beliefs, and availability of kidney replacement therapy and conservative kidney management. As a complex, evolving process, dialysis withdrawal poses an enormous challenge for clinicians and healthcare teams with various limitations precluding a peaceful and smooth transition between active dialysis and end-of-life care. In this review, we examine the current definitions of dialysis withdrawal, the temporal and geographical patterns of dialysis withdrawal, international barriers in the decision-making process (including dialysis withdrawal during the COVID-19 pandemic), and gaps in the current dialysis withdrawal recommendations for clinical consideration and future studies.

The aim of this study is to develop intelligent color recognition, mobile control, and monitoring system for a pick-and-place robotic arm for manufacturing systems. The demand for smart manufacturing factories with real-time control of fabricating processes and traceability of production information is increasing urgently. Generally speaking, a smart manufacturing facility is usually composed of sensing, computing, control, and communication technologies together. In this study, the three-tier architecture of the Internet of things (IoT) was adopted as a guideline to design mobile devices to control and monitor a color image recognition and alarm monitoring system by using Raspberry Pi and a web page database. The practical results and contributions of this study are as follows: With integrating the techniques of advanced BR PLC, mobile devices and APP, color image recognition, Raspberry Pi microcomputer, and MySQL database technologies together, (1) the mobile control and monitoring system is able to supervise a real-time manufacturing plant anywhere and anytime with mobile devices easily; (2) the color identification system can identify and classify different color work-piece precisely, and the identification results are recorded for remote database platform; (3) the collected data are analyzed and displayed on mobile devices through the web database for field operators and engineers promptly. It provides a very successful practical paradigm to promote conventional factories to meet industry 4.0.

The persistence of the HIV-1 reservoir is still the main obstacle to the cure of HIV. In clinical research, reliable biomarkers are needed to label it. HIV-1 DNA can be continuously detected in the HIV-1 reservoir. It has significant application value in diagnosing HIV-1 infection, the timing of antiretroviral therapy, the prediction of virus rebound, and monitoring treatment effects. The detection technology based on polymerase chain reaction (PCR) is the most commonly used HIV-1 DNA detection method in clinical practice. The continuous innovation and advancement of technology can accurately detect the total, integrated, and unintegrated HIV-1 DNA in infected cells using qualitative or quantitative methods. Different forms of HIV-1 DNA in infected cells have been increasingly reported as biomarkers in HIV infection monitoring and AIDS treatment-related research. This article reviews the progress of HIV-1 DNA.HIV-1储存库的持续存在是治愈HIV的主要障碍，在临床研究中，需要可靠的生物标志物对其进行标记。HIV-1 DNA在HIV-1储存库中可被持续检测到，在HIV-1感染诊断、预测病毒反弹和监测治疗效果等方面具有重要应用价值。PCR的检测技术是临床上常用的HIV-1 DNA检测方法，随着技术的不断创新与进步，可更准确地通过定性或定量检测感染细胞中总的、整合的和未整合的HIV-1 DNA。感染细胞中不同形式的HIV-1 DNA作为生物标志物在HIV感染监测和艾滋病治疗相关研究中报道日益增多。本文对感染细胞中HIV-1 DNA的检测方法及其作为生物标志物的临床应用进展进行综述。.

Sciatic nerve symptomatology may arise from both intra- and extra-neural pathology, at any point along descent from the sacral plexus to its bifurcation. The potential aetiology is broad, ranging from degenerative spinal disease to muscle, bony and vascular pathology. We present an extremely unusual case of position and exercise-induced nerve compression secondary to arteriovenous malformation and review the potential extraspinal causes, many of which may be ameliorated by surgical excision or decompression. We further discuss the usefulness of diagnostic imaging, specific clinical tests and histopathological tools that may aid in management.

Image stacking is a crucial method for micro or macro photography. It captures images at different focal planes and then merges them into a single, all-in-focus image with extended focus. This method has been extensively used for digital documentation by scientists working at museums or research institutions. However, the traditional image stacking method relies on expensive instruments to conduct precise image stacking using a computer-based stepper motor controller. In this study, we reported how to conduct image focus extensions with comparable quality to those done by a motorized stepper using a cost-effective instrument setting and an efficient manual stacking method. This method provides a shorter operation time and capability to capture images of living objects and high flexibility in obtaining the images of objects from cm to mm scale. However, it also has some limitations, including the inability to control aperture and exposure time, relatively short working distance at high magnification, requires additional steps to convert the video into images, and heavily relies on the user’s manual observation prior to a video recording. Nevertheless, the authors believe that the current method can be applied as an alternative method to conduct image stacking. The development of such an instrument and method offers a promising avenue for scientists to perform image stacking with greater flexibility and speed in macro photography.

Protozoa are eukaryotic, unicellular microorganisms that have an important ecological role, are easy to handle, and grow rapidly, which makes them suitable for ecotoxicity assessment. Previous methods for locomotion tracking in protozoa are largely based on software with the drawback of high cost and/or low operation throughput. This study aimed to develop an automated pipeline to measure the locomotion activity of the ciliated protozoan Tetrahymena thermophila using a machine learning-based software, TRex, to conduct tracking. Behavioral endpoints, including the total distance, velocity, burst movement, angular velocity, meandering, and rotation movement, were derived from the coordinates of individual cells. To validate the utility, we measured the locomotor activity in either the knockout mutant of the dynein subunit DYH7 or under starvation. Significant reduction of locomotion and alteration of behavior was detected in either the dynein mutant or in the starvation condition. We also analyzed how Tetrahymena locomotion was affected by the exposure to copper sulfate and showed that our method indeed can be used to conduct a toxicity assessment in a high-throughput manner. Finally, we performed a principal component analysis and hierarchy clustering to demonstrate that our analysis could potentially differentiate altered behaviors affected by different factors. Taken together, this study offers a robust methodology for Tetrahymena locomotion tracking in a high-throughput manner for the first time.

DeepLabCut (DLC) is a deep learning-based tool initially invented for markerless pose estimation in mammals. In this study, we explored the possibility of adopting this tool for conducting markerless cardiac physiology assessment in an important aquatic toxicology model of zebrafish (Danio rerio). Initially, high-definition videography was applied to capture heartbeat information at a frame rate of 30 frames per second (fps). Next, 20 videos from different individuals were used to perform convolutional neural network training by labeling the heart chamber (ventricle) with eight landmarks. Using Residual Network (ResNet) 152, a neural network with 152 convolutional neural network layers with 500,000 iterations, we successfully obtained a trained model that can track the heart chamber in a real-time manner. Later, we validated DLC performance with the previously published ImageJ Time Series Analysis (TSA) and Kymograph (KYM) methods. We also evaluated DLC performance by challenging experimental animals with ethanol and ponatinib to induce cardiac abnormality and heartbeat irregularity. The results showed that DLC is more accurate than the TSA method in several parameters tested. The DLC-trained model also detected the ventricle of zebrafish embryos even in the occurrence of heart abnormalities, such as pericardial edema. We believe that this tool is beneficial for research studies, especially for cardiac physiology assessment in zebrafish embryos.

The active site of methanol dehydrogenase (MDH) contains a rare disulfide bridge between adjacent cysteine residues. As a vicinal disulfide, the structure is highly strained, suggesting it might work together with the pyrroloquinoline quinone (PQQ) prosthetic group and the Ca2+ ion in the catalytic turnover during methanol (CH3OH) oxidation. We purify MDH from Methylococcus capsulatus (Bath) with the disulfide bridge broken into two thiols. Spectroscopic and high-resolution X-ray crystallographic studies of this form of MDH indicate that the disulfide bridge is redox active. We observe an internal redox process within the holo-MDH that produces a disulfide radical anion concomitant with a companion PQQ radical, as evidenced by an optical absorption at 408 nm and a magnetically dipolar-coupled biradical in the EPR spectrum. These observations are corroborated by electron-density changes between the two cysteine sulfurs of the disulfide bridge as well as between the bound Ca2+ ion and the O5-C5 bond of the PQQ in the high-resolution X-ray structure. On the basis of these findings, we propose a mechanism for the controlled redistribution of the two electrons during hydride transfer from the CH3OH in the alcohol oxidation without formation of the reduced PQQ ethenediol, a biradical mechanism that allows for possible recovery of the hydride for transfer to an external NAD+ oxidant in the regeneration of the PQQ cofactor for multiple catalytic turnovers. In support of this mechanism, a steady-state level of the disulfide radical anion is observed during turnover of the MDH in the presence of CH3OH and NAD+.

Water fleas are an important lower invertebrate model that are usually used for ecotoxicity studies. Contrary to mammals, the heart of a water flea has a single chamber, which is relatively big in size and with fast-beating properties. Previous cardiac chamber volume measurement methods are primarily based on ImageJ manual counting at systolic and diastolic phases which suffer from low efficiency, high variation, and tedious operation. This study provides an automated and robust pipeline for cardiac chamber size estimation by a deep learning approach. Image segmentation analysis was performed using U-Net and Mask RCNN convolutional networks on several different species of water fleas such as Moina sp., Daphnia magna, and Daphnia pulex. The results show that Mask RCNN performs better than U-Net at the segmentation of water fleas’ heart chamber in every parameter tested. The predictive model generated by Mask RCNN was further analyzed with the Cv2.fitEllipse function in OpenCV to perform a cardiac physiology assessment of Daphnia magna after challenging with the herbicide of Roundup. Significant increase in normalized stroke volume, cardiac output, and the shortening fraction was observed after Roundup exposure which suggests the possibility of heart chamber alteration after roundup exposure. Overall, the predictive Mask RCNN model established in this study provides a convenient and robust approach for cardiac chamber size and cardiac physiology measurement in water fleas for the first time. This innovative tool can offer many benefits to other research using water fleas for ecotoxicity studies.

The fin is known to play an important role in swimming for many adult fish, including zebrafish. Zebrafish fins consist of paired pectoral and pelvic with unpaired dorsal, anal, and caudal tail fins with specific functions in fish locomotion. However, there was no study comparing the behavior effects caused by the absence of each fin. We amputated each fin of zebrafish and evaluated their behavior performance in the 3D locomotion test using fractal dimension and entropy analyses. Afterward, the behavior recovery after the tail fin amputation was also evaluated, together with the fin regeneration process to study their relationship. Finally, we conducted a further study to confirm whether the observed behavior alterations were from pain elicited by fin amputation procedure or not by using lidocaine, a pain-relieving drug. Amputation in the caudal fin resulted in the most pronounced behavior alterations, especially in their movement complexity. Furthermore, we also found that their behavior was fully recovered before the caudal fin was fully regenerated, indicating that these behavioral changes were not majorly due to a mechanical change in tail length; instead, they may come from pain elicited from the fin amputation, since treatment with lidocaine could ameliorate the behavioral effects after the amputation procedure. However, lidocaine did not accelerate the behavior recovery process; instead, it caused the fishes to display some slight side effects. This study highlights the potential moderate severity of fin amputation in zebrafish and the importance of analgesia usage. However, side effects may occur and need to be considered since fin amputation is routinely conducted for various research, especially genomic screening.

Objective The San Francisco Declaration on Research Assessment (DORA) advocates for assessing biomedical research quality and impact, yet academic organizations continue to employ traditional measures such as Journal Impact Factor. We aimed to identify and prioritize measures for assessing research quality and impact. Methods We conducted a review of published and grey literature to identify measures of research quality and impact, which we included in an online survey. We assembled a panel of researchers and research leaders, and conducted a two-round Delphi survey to prioritize measures rated as high (rated 6 or 7 by ≥ 80% of respondents) or moderate (rated 6 or 7 by ≥ 50% of respondents) importance. Results We identified 50 measures organized in 8 domains: relevance of the research program, challenges to research program, or productivity, team/open science, funding, innovations, publications, other dissemination, and impact. Rating of measures by 44 panelists (60%) in Round One and 24 (55%) in Round Two of a Delphi survey resulted in consensus on the high importance of 5 measures: research advances existing knowledge, research plan is innovative, an independent body of research (or fundamental role) supported by peer-reviewed research funding, research outputs relevant to discipline, and quality of the content of publications. Five measures achieved consensus on moderate importance: challenges to research productivity, potential to improve health or healthcare, team science, collaboration, and recognition by professional societies or academic bodies. There was high congruence between researchers and research leaders across disciplines. Conclusions Our work contributes to the field by identifying 10 DORA-compliant measures of research quality and impact, a more comprehensive and explicit set of measures than prior efforts. Research is needed to identify strategies to overcome barriers of use of DORA-compliant measures, and to “de-implement” traditional measures that do not uphold DORA principles yet are still in use.

Aptamer selection against novel infections is a complicated and time-consuming approach. Synergy can be achieved by using computational methods together with experimental procedures. This study aims to develop a reliable methodology for a rational aptamer in silico et vitro design. The new approach combines multiple steps: (1) Molecular design, based on screening in a DNA aptamer library and directed mutagenesis to fit the protein tertiary structure; (2) 3D molecular modeling of the target; (3) Molecular docking of an aptamer with the protein; (4) Molecular dynamics (MD) simulations of the complexes; (5) Quantum-mechanical (QM) evaluation of the interactions between aptamer and target with further analysis; (6) Experimental verification at each cycle for structure and binding affinity by using small-angle X-ray scattering, cytometry, and fluorescence polarization. By using a new iterative design procedure, structure- and interaction-based drug design (SIBDD), a highly specific aptamer to the receptor-binding domain of the SARS-CoV-2 spike protein, was developed and validated. The SIBDD approach enhances speed of the high-affinity aptamers development from scratch, using a target protein structure. The method could be used to improve existing aptamers for stronger binding. This approach brings to an advanced level the development of novel affinity probes, functional nucleic acids. It offers a blueprint for the straightforward design of targeting molecules for new pathogen agents and emerging variants.

Cardiac arrhythmia has been defined as one of the abnormal heart rhythm symptoms, which is a common problem dealt with by cardiologists. Zebrafish were established as a powerful animal model with a transparent body that enables optical observation to analyze cardiac morphology and cardiac rhythm regularity. Currently, research has observed heart-related parameters in zebrafish, which used different approaches, such as starting from the use of fluorescent transgenic zebrafish, different software, and different observation methods. In this study, we developed an innovative approach by using the OpenCV library to measure zebrafish larvae heart rate and rhythm. The program is designed in Python, with the feature of multiprocessing for simultaneous region-of-interest (ROI) detection, covering both the atrium and ventricle regions in the video, and was designed to be simple and user-friendly, having utility even for users who are unfamiliar with Python. Results were validated with our previously published method using ImageJ, which observes pixel changes. In summary, the results showed good consistency in heart rate-related parameters. In addition, the established method in this study also can be widely applied to other invertebrates (like Daphnia) for cardiac rhythm measurement.

In many operational processes, a suitable combination of participating elements has a huge impact throughout the entire process. In the real environment, however, many combinations show less than expected results in the initial stage. In consideration of the many subjective and objective factors such as equipment, time, capital, materials, and so forth, it seems that the aforementioned combinations cannot be used to re-configure. It is important that these initial unsatisfactory combinations can gradually approach some equilibrium states or results through some rolling adjustment processes. In order to improve the above problem, this study attempts to use a game-theoretic dynamic procedure to establish a mechanism that can be dynamically modified under relative symmetry at any time during operational processes. Under such a dynamic procedure, an undesirable combination of participating elements can gradually approach a useful combination.

A catalyst constructed from graphene oxide and iridium chloride exhibited high activity and reliability for the selective transformation of benzylic alcohols into aromatic aldehydes or ketones. Instead of thermal reaction, the transformation was performed under ultrasonication, a green process with low byproduct, high atomic yield and high selectivity. Experimental data obtained from spherical-aberration corrected field emission TEM (ULTRA-HRTEM), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy and Raman spectra confirm the nanostructure of the title complex. Noticeably, the activity and selectivity for the transformation of benzylic alcohols remained unchanged within 25 catalytic cycles. The average turn over frequency is higher than 5000 h−1, while the total turnover number (TON) is more than one hundred thousand, making it a high greenness and eco-friendly process for alcohol oxidation.

Ractopamine (RAC) is a synthetic phenethanolamine, β–adrenergic agonist used as a feed additive to develop leanness and increase feed conversion efficiency in different farm animals. While RAC has been authorized as a feed additive for pigs and cattle in a limited number of countries, a great majority of jurisdictions, including the European Union (EU), China, Russia, and Taiwan, have banned its use on safety grounds. RAC has been under long scientific and political discussion as a controversial antibiotic as a feed additive. Here, we will present significant information on RAC regarding its application, detection methods, conflicts, and legal divisions that play a major role in controversial deadlock and why this issue warrants the attention of scientists, agriculturists, environmentalists, and health advocates. In this review, we highlight the potential toxicities of RAC on aquatic animals to emphasize scientific evidence and reports on the potentially harmful effects of RAC on the aquatic environment and human health.

The burden of type 2 diabetes and related complications has steadily increased over the last few decades and is one of the foremost global public health threats in the 21st century. Diabetes is one of the leading causes of chronic kidney disease and kidney failure and is an important contributor to the cardiovascular morbidity and mortality in this population. In addition, up to one in three patients who have received kidney transplants develop post-transplant diabetes, but the management of this common complication continues to pose a significant challenge for clinicians. In this review, we will describe the global prevalence and temporal trend of kidney failure attributed to diabetes mellitus in both developing and developed countries. We will examine the survival differences between treated kidney failure patients with and without type 2 diabetes, focusing on the survival differences in those on maintenance dialysis or have received kidney transplants. With the increased availability of novel hypoglycemic agents, we will address the potential impacts of these novel agents in patients with diabetes and kidney failure and in those who have developed post-transplant diabetes.

Over the last few years, environmental pollution, especially water pollution, has become a serious issue worldwide. Thus, methods that can help us understand the impact and effects of these pollutants, especially on aquatic animals, are needed. Behavioral assessment has emerged as a crucial tool in toxicology and pharmacology because many studies have shown, in multiple animal models, that various pharmacological compounds can alter behavior, with many of the findings being translatable to humans. Moreover, behavior study can also be used as a suitable indicator in the ecotoxicological risk assessment of pollutants. Several model organisms, especially rodent models, have been extensively employed for behavior studies. However, assessments using this model are generally time consuming, expensive, and require extensive facilities for housing experimental animals. Moreover, behavioral studies typically use different measurements and assessment tools, making comparisons difficult. In addition, even though behavioral phenomics has the potential to comprehensively illustrate the toxicities of chemicals, there is only a limited number of studies focusing on animal behavior using such a global approach. Here, we describe a phenomics approach that can be used to investigate the impact of pollutants using zebrafish. The approach consists of several behavioral tests, including response to a novel environment, mirror-reflection image, predator fish, and conspecifics, after exposure to a test chemical. Phenotype fingerprinting, a method for summarizing individual phenotypes based on the results of the behavioral tests, is then conducted to reduce data complexity and display the pattern of each compound on behavioral phenotypes in zebrafish. This approach may be useful to researchers studying the potential adverse effects of different pollutants. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Novel tank test Basic Protocol 2: Shoaling test Basic Protocol 3: Aggression test (mirror biting test) Basic Protocol 4: Social interaction test Basic Protocol 5: Fear response test Basic Protocol 6: PCA and heatmap clustering.

Tail coiling is a reflection response in fish embryos that can be used as a model for neurotoxic analysis. The previous method to analyze fish tail coiling is largely based on third-party software. In this study, we aim to develop a simple and cost-effective method called TCMacro by using ImageJ macro to reduce the operational complexity. The basic principle of the current method is based on the dynamic change of pixel intensity in the region of interest (ROI). When the fish tail is moving, the average intensity is increasing. In time when the fish freeze, the peak of mean intensity is maintaining at a relatively low level. By using the optimized macro settings and excel VBA scripts, all the tail coiling measurement processes can be archived with few operation steps with high precision. Three major endpoints of tail coiling counts, tail coiling duration and tail coiling intervals can be obtained in batch. To validate this established method, we tested the potential neurotoxic activity of Tricaine (methanesulfonate, MS-222) and psychoactive compound of caffeine. Zebrafish embryos after Tricaine exposure displayed significantly less tail coiling activity in a dose-dependent manner, and were comparable to manual counting through the Wilcoxon test and Pearson correlation double validation. Zebrafish embryos after caffeine exposure displayed significantly high tail coiling activity. In conclusion, the TCMacro method presented in this study provides a simple and robust method that is able to measure the relative tail coiling activities in zebrafish embryos in a high-throughput manner.

The use of chemicals to boost food production increases as human consumption also increases. The insectidal, nematicidal and acaricidal chemical carbofuran (CAF), is among the highly toxic carbamate pesticide used today. Alongside, copper oxide nanoparticles (CuO) are also used as pesticides due to their broad-spectrum antimicrobial activity. The overuse of these pesticides may lead to leaching into the aquatic environments and could potentially cause adverse effects to aquatic animals. The aim of this study is to assess the effects of carbofuran and copper oxide nanoparticles into the cardiovascular system of zebrafish and unveil the mechanism behind them. We found that a combination of copper oxide nanoparticle and carbofuran increases cardiac edema in zebrafish larvae and disturbs cardiac rhythm of zebrafish. Furthermore, molecular docking data show that carbofuran inhibits acetylcholinesterase (AChE) activity in silico, thus leading to impair cardiac rhythms. Overall, our data suggest that copper oxide nanoparticle and carbofuran combinations work synergistically to enhance toxicity on the cardiovascular performance of zebrafish larvae.

Background T helper 17 (Th17) cells play an important role in barrier protection in the gastrointestinal tract but are also key pathological drivers of Inflammatory Bowel Disease (IBD). Although a number of transcription factors governing Th17 differentiation have been identified, the intracellular signalling pathways regulating Th17 differentiation are poorly understood. Hedgehog (Hh) signalling controls cell-fate choices in numerous tissue compartments and is targetable by highly selective, clinically-approved small molecule inhibitors. However the role of Hh signalling in Th17 differentiation and effector function is unstudied. Methods We generated two conditional knockout mouse models targeting Hh signalling components Smo and Ihh to study Th17 differentiation in vitro by flow cytometry and gene expression analysis. For in vivo studies, T cell adoptive transfer colitis was performed using donor Ihh knockout T cells or heterozygote controls. Histological analysis, mouse weight, colon length/weight measurements, and flow cytometric analysis was performed. We supplement this with the use of two small-molecule Smo antagonists for in vitro and in vivo studies of Th17 function. To underscore the translational relevance of our findings, we conducted bioinformatic analyses of published gene expression datasets of human rectal biopsies from two large independent cohorts of Ulcerative Colitis patients and healthy controls. Results We find that intracellular Hh signalling, independently of extracellular Hh ligands, selectively drives differentiation and effector function of Th17 cells but not of other T helper cell lineages. We demonstrate in vivo that inhibition of the Hh pathway with either the clinically-approved small molecule inhibitor vismodegib or genetic ablation of Ihh in CD4+ T cells results in a significant decrease in histological and clinical readouts of disease severity as well as a significant reduction in IL-17a+ Th17 cells. Our bioinformatic analyses show that Hh component expression levels are upregulated in human Ulcerative Colitis patient samples and are closely correlated with expression of Th17 markers. Mechanistically we show that the T-cell-intrinsic Indian Hedgehog (Ihh) ligand signals via the signal transducer Smoothened to activate both canonical and non-canonical Hh pathways, through the Gli3 transcription factor and AMPK phosphorylation, respectively. Conclusion We uncover Hh signalling as a novel pathway controlling Th17 differentiation and pathogenicity in IBD with Gli3 acting as a newly-identified crucial regulatory transcription factor. Our work paves the way for the use of Hh inhibitors for the treatment of IBD.

Recently, medaka has been used as a model organism in various research fields. However, even though it possesses several advantages over zebrafish, fewer studies were done in medaka compared to zebrafish, especially with regard to its behavior. Thus, to provide more information regarding its behavior and to demonstrate the behavioral differences between several species of medaka, we compared the behavioral performance and biomarker expression in the brain between four medaka fishes, Oryzias latipes, Oryzias dancena, Oryzias woworae, and Oryzias sinensis. We found that each medaka species explicitly exhibited different behaviors to each other, which might be related to the different basal levels of several biomarkers. Furthermore, by phenomics and genomic-based clustering, the differences between these medaka fishes were further investigated. Here, the phenomic-based clustering was based on the behavior results, while the genomic-based clustering was based on the sequence of the nd2 gene. As we expected, both clusterings showed some resemblances to each other in terms of the interspecies relationship between medaka and zebrafish. However, this similarity was not displayed by both clusterings in the medaka interspecies comparisons. Therefore, these results suggest a re-interpretation of several prior studies in comparative biology. We hope that these results contribute to the growing database of medaka fish phenotypes and provide one of the foundations for future phenomics studies of medaka fish.

Catalysts, artificially or naturally generated, are often considered to be important factors in numerous chemical processes. Although each catalyst can act under its own characteristics, the efficiency of chemical interactions can be enhanced by a balanced combination of different catalysts. On the other hand, many game-theoretical results have been widely applied to seek the optimal or balanced state for efficiency regulation, resource control, portfolio allocation, and behavior simulation in modern academic literature. Based on game-theoretical approaches under actual chemical and biochemical environments, this article aims to analyze, construct, simulate, and derive the most efficient optimal or balanced combinations for a group of catalysts with different conditions and actions. In this article, a power index is proposed by simultaneously focusing on the factors and its active levels. In order to analyze the accuracy and rationality of this power index, we adopt usual axioms to offer some characterizations. In conjunction with the constructed game-theoretical results that are related to chemical and biochemical environments, this article further analyzes, verifies, and demonstrates the validity, accuracy, feasibility, plausibility, and applicability of the combination of catalysts with different conditions and actions.