Disease Research Research Articles

Machine learning quantification of Amyloid-β deposits in the temporal lobe of 131 brain bank cases

Accurate and scalable quantification of amyloid-β (Aβ) pathology is crucial for deeper disease phenotyping and furthering research in Alzheimer Disease (AD). This multidisciplinary study addresses the current limitations on neuropathology by leveraging a machine learning (ML) pipeline to perform a granular quantification of Aβ deposits and assess their distribution in the temporal lobe. Utilizing 131 whole-slide-images from consecutive autopsied cases at the University of California Davis Alzheimer Disease Research Center, our objectives were threefold: (1) Validate an automatic workflow for Aβ deposit quantification in white matter (WM) and gray matter (GM); (2) define the distributions of different Aβ deposit types in GM and WM, and (3) investigate correlates of Aβ deposits with dementia status and the presence of mixed pathology. Our methodology highlights the robustness and efficacy of the ML pipeline, demonstrating proficiency akin to experts’ evaluations. We provide comprehensive insights into the quantification and distribution of Aβ deposits in the temporal GM and WM revealing a progressive increase in tandem with the severity of established diagnostic criteria (NIA-AA). We also present correlations of Aβ load with clinical diagnosis as well as presence/absence of mixed pathology. This study introduces a reproducible workflow, showcasing the practical use of ML approaches in the field of neuropathology, and use of the output data for correlative analyses. Acknowledging limitations, such as potential biases in the ML model and current ML classifications, we propose avenues for future research to refine and expand the methodology. We hope to contribute to the broader landscape of neuropathology advancements, ML applications, and precision medicine, paving the way for deep phenotyping of AD brain cases and establishing a foundation for further advancements in neuropathological research.

Overcoming Barriers to Latino Participation in Alzheimer's Disease Research.

There is a critical need to increase Latino participation in research on Alzheimer's disease and related disorders (ADRD). Applying principles of community-based participatory research, we convened a community advisory board (CAB) to identify barriers and recommend strategies to increase participation of older Latinos in a longitudinal observational research study of ADRD at the Shiley-Marcos Alzheimer's Disease Research Center. Six major barriers were identified and programmatic changes to overcome them were implemented. Changes resulted in a nearly three-fold increase in the number of Latino individuals recruited, with the proportion of all newly recruited participants who were Latino increasing from 12.2% to 57.4%. Newer Latino recruits were more representative of the elderly Latino population in San Diego County than those recruited pre-CAB and remained highly agreeable to blood draw and neuroimaging, though less so to lumbar puncture and autopsy. Results demonstrate the value of CAB involvement in enhancing diversity in ADRD research.

3D Bioprinitng technologies for the enhancement and application of functional lung organoid models

Respiratory diseases, ranging from minor infections to serious chronic diseases and malignancies, negatively affect the respiratory system and are influenced by various environmental factors such as air pollution, occupational hazards, and tobacco smoke, as well as lifestyle, genetic causes, and infectious agents. The prevalence and severity of respiratory diseases requires the development of advanced models to better understand their pathophysiology and develop effective treatments. In this context, 3D bioprinting technology is emerging as an innovative tool to create functional lung organoid models. The use of induced pluripotent stem cells (iPSCs) and extracellular matrix (ECM) in bioprinting enables the development of organoids that closely mimic human lung tissue. Bioprinting-based organoids can better replicate the dynamic environment of the human lung, facilitating more accurate disease modeling and drug testing. In this review, we highlight the potential of bioprinted lung organoids in understanding the mechanisms of chronic respiratory diseases, testing the efficacy and safety of new drugs, and exploring regenerative medicine approaches. The integration of advanced bioprinting and organoid technologies is a promising field in respiratory disease research and treatment, offering new hope for patients suffering from lung diseases.

Heart Diseases Recognition Model Based on HRV Feature Extraction over 12-Lead ECG Signals.

Heart Rate Variability (HRV) refers to the capability of the heart rhythm to vary at different times, typically reflecting the regulation of the heart by the autonomic nervous system. In recent years, with advancements in Electrocardiogram (ECG) signal processing technology, HRV features reflect various aspects of cardiac activity, such as variability in heart rate, cardiac health status, and responses. We extracted key features of HRV and used them to develop and evaluate an automatic recognition model for cardiac diseases. Consequently, we proposed the HRV Heart Disease Recognition (HHDR) method, employing the Spectral Magnitude Quantification (SMQ) technique for feature extraction. Firstly, the HRV signals are extracted through electrocardiogram signal processing. Then, by analyzing parts of the HRV signal within various frequency ranges, the SMQ method extracts rich features of partial information. Finally, the Random Forest (RF) classification computational method is employed to classify the extracted information, achieving efficient and accurate cardiac disease recognition. Experimental results indicate that this method surpasses current technologies in recognizing cardiac diseases, with an average accuracy rate of 95.1% for normal/diseased classification, and an average accuracy of 84.8% in classifying five different disease categories. Thus, the proposed HHDR method effectively utilizes the local information of HRV signals for efficient and accurate cardiac disease recognition, providing strong support for cardiac disease research in the medical field.

Machine Learning Analysis in the Field of Heart Disease

Machine learning (ML) has emerged as a transformative force in cardiovascular disease research, offering innovative approaches to prevention, diagnosis, and treatment. This report provides an overview of the current landscape of ML applications in cardiology, highlighting its potential to revolutionize the field. Key ML algorithms such as Support Vector Machine (SVM), Random Forests, Adaboost, XGBoost, and Convolutional Neural Networks (CNN) are discussed for their unique capabilities in handling complex cardiovascular data and improving disease prediction and risk stratification. Notably, the integration of feature selection techniques with ML algorithms enables the identification of biomarkers and clinical indicators, facilitating personalized care and targeted interventions. The potential of ML extends to early disease diagnosis, patient stratification, and the design of new therapeutic strategies, thereby transforming cardiology into a domain of precision medicine. While the advancements are promising, there is a pressing need for further research to enhance the interpretability, generalizability, and integration of ML models into real-world healthcare settings. Collaborative efforts between ML experts, healthcare providers, and policymakers are essential to address regulatory, ethical, and privacy concerns and to fully harness the capabilities of ML in cardiovascular medicine.

Expectations of Katowice residents regarding the program assumptions of the European city of science Katowice 2024 in the field of medical and health sciences - questionnaire survey results

IntroductionScientific literacy has been the subject of studies for several decades, but there is much less interest in the social perception of science, traceability of key areas of scientific activity and social expectations regarding science. Proper recognition of such issues can significantly contribute to a better understanding of the causes of the crisis of trust in science and help to find an effective and socially acceptable solution to mitigate it. Our study was aimed at identifying and systematizing the public needs and expectations towards medical and health sciences, based on the example of the population of Katowice.Materials and methodsThe study was carried out using a mixed, qualitative-quantitative methodology. Based on the conclusions of the in-depth interviews, a questionnaire was constructed to check the level of awareness of residents of Katowice obtaining the title of the European City of Science 2024 and the respondents’ opinion on the development of medical and health sciences. 400 inhabitants of the city and/or people associated with it through their work or education took part in the questionnaire survey.ResultsOnly 7.8% of respondents had in-depth knowledge about the European City of Science 2024 project, with further 28.8% declaring some level of general knowledge of the issue. Study participants associated medical and health sciences with health promotion and clinical specialties (43% and 33,5% respectively). In terms of further development of medical and health sciences in Katowice study participants prioritized mainly development of research in chronic and lifestyle-related diseases (51%) and the need of development of prevention and health promotion (46.3%) as well as clinical medicine (32.8%). The inhabitants of the city recognize the resources of the city and the region in the field of medical sciences and health sciences as large and with high development potential.ConclusionsThe events organized as part of the European City of Science 2024 should become a good opportunity to promote and disseminate knowledge about the achievements and development potential of the City and the Region in the field of medical and health sciences.

Insights from a 7-Year Dementia Cohort (VALCODIS): ApoE Genotype Evaluation.

Background: The VALCODIS (Valencian Cognitive Diseases Study) cohort was designed and studied at the Hospital Universitari i Politècnic La Fe (Valencia, Spain) for the research of cognitive diseases, especially in the search for new biomarkers of Alzheimer's disease (AD). Methods: Participants in the VALCODIS cohort had cerebrospinal fluid (CSF) and blood samples, neuroimaging, and neuropsychological tests. The ApoE genotype was evaluated to identify its relationship with CSF biomarkers and neuropsychological tests in AD and non-AD participants. Results: A total of 1249 participants were included. They were mainly AD patients (n = 547) but also patients with other dementias (frontotemporal lobar dementia (n = 61), Lewy body dementia without AD CSF signature (n = 10), vascular dementia (n = 24) and other specific causes of cognitive impairment (n = 442), and patients with subjective memory complaints (n = 165)). In the ApoE genotype evaluation, significant differences were found for Aβ42 levels between genotypes in both AD and non-AD patients, as well as a negative correlation between tau values and a cognitive test in non-carriers and ε4 heterozygous. Conclusions: The VALCODIS cohort provides biologically diagnosed patients with demographical, clinical and biochemical data, and biological samples for further studies on early AD diagnosis. Also, the ApoE genotype evaluation showed correlations between CSF biomarkers and neuropsychological tests.

Pathogen and Host Associations of Soft Ticks Collected in South Texas.

Background: Soft ticks (Family: Argasidae) are vectors of relapsing fever Borrelia in the United States and are potential vectors of African swine fever virus, a pathogen that could have a devastating effect on the U.S. swine industry if introduced to the U.S. mainland. Much of the tick-borne disease research in the U.S. focuses on hard ticks, and less is known about the ecology of soft ticks. Some soft tick species found in the southern U.S. have a wide host range and may feed on cattle, swine, native and exotic ungulates, small mammals, reptiles, and humans. Because the feeding habit of most soft tick species involves taking short, repeated blood meals that may include multiple host species, pathogen transmission among hosts is a concern both for human and animal health. Materials and Methods: Sampling was carried out at four locations in south Texas using dry ice traps placed in or near animal burrows and other sheltering cracks and crevasses that may provide refuge for soft ticks. Collected ticks were identified and subsequently screened for Rickettsia and Borrelia species and for host bloodmeal detection using conventional polymerase chain reaction and Sanger sequencing for pathogen and host species identification. Results: In total, 256 ticks of two Ornithodorinae species were screened. Borrelia species were identified in three samples. Bloodmeal detections were made in 22 tick specimens, representing eight vertebrate host species. Conclusions: Results demonstrate that the soft tick species detected herein feed on a range of wildlife hosts in south Texas and are associated with agents of human disease.

Robotic Ultrasound and Novel Collagen Analyses for Polycystic Kidney Disease Research Using Mice.

3D imaging and histology are critical tools for assessing polycystic kidney disease ( PKD ) in patients and animal models. Magnetic resonance ( MR ) imaging provides micron resolution, but is time consuming, expensive, and access to equipment and expertise is limiting. Robotic ultrasound ( US ) imaging has lower spatial resolution but is faster, more cost effective, and accessible. Similarly, Picrosirius red ( PSR ) staining and brightfield microscopy is commonly used to assess fibrosis; however, alternative methods have been shown in non-kidney tissues to provide greater sensitivity and more detailed structural characterization. In this study, we evaluated the utility of robotic US and alternative methods of quantifying PSR staining for PKD research. We compared longitudinal total kidney volume ( TKV ) measurements using US and MR. We additionally compared PSR imaging and quantification using standard brightfield with that by circularly polarized light with hue analysis, and fluorescence imaging analyzed using CT-FIRE software for automatic detection of individual collagen fibers. Increased TKV was detected by US in Pkd1RC/RC vs wild type ( WT ) at timepoints spanning early to established disease. US inter-observer variability was greater but allowed scanning in 2-5 minutes/mouse while MR required 20-30 minutes/mouse. While no change in fibrotic index was detected in this cohort of relatively mild disease using brightfield, polarized light showed fibers skewed thinner in Pkd1RC/RC vs WT. Fluorescence imaging showed a higher density of collagen fibers in Pkd1RC/RC vs WT, and fibers were thinner and curvier with no change in length. Additionally, fiber density was higher in both glomeruli and tubules in Pkd1RC/RC , and glomeruli had a higher fiber density than tubules in Pkd1RC/RC , and trended higher in WT. These studies show robotic ultrasound is a rigorous imaging tool for pre-clinical PKD research. Additionally, they demonstrate the increased sensitivity of polarized and fluorescence analysis of PSR-stained collagen.

Articulating the ultimate objectives of research capacity strengthening programmes: Why this is important and how we might achieve it.

'Research capacity strengthening' (RCS) is an umbrella term that can be used to describe a wide variety of activities conducted in support of diverse objectives premised upon distinct, potentially opposing, views. Despite this, the ultimate objective of RCS activities is rarely made explicit which can be problematic when diverse objectives are possible. By 'ultimate' objective we are referring to the overarching (often long-term) goal an RCS initiative is intended to contribute towards (e.g. better population health) as opposed to the more immediate 'proximate' (often short-term) objectives of any such activity (e.g. improved capacity to undertake infectious disease research). We argue a need for those funding, designing and implementing RCS initiatives to make clear statements as to the ultimate objective that they foresee their respective initiative contributing towards as well as the proposed pathway and associated assumptions that underlie their approach. Examples of distinct ultimate objectives for RCS initiatives are presented alongside fictitious examples of how they may be transparently reported from both a funder and implementor perspective. Such transparency should be routine within the scope of funding calls for RCS activities (even when such activities are only a minor component of the call), subsequent applications to those calls and any description of an applied RCS activity/ies and/or the associated outcomes thereof. The process of determining one's ultimate objective will further cause funders and actors to think through their respective initiatives more thoroughly and make informed choices and better designed RCS projects. Doing so would reduce any ambiguity associated with the use of the term 'research capacity strengthening' and would provide a stronger foundation for robust programme evaluation.

Public perceptions of international genetic information sharing for biomedical research in China: a case study of the social media debate on the article “A Pangenome Reference of 36 Chinese Populations” published in Nature

BackgroundThe international disclosure of Chinese human genetic data continues to be a contentious issue in China, generating public debates in both traditional and social media channels. Concerns have intensified after Chinese scientists’ research on pangenome data was published in the prestigious journal Nature.MethodsThis study scrutinized microblogs posted on Weibo, a popular Chinese social media site, in the two months immediately following the publication (June 14, 2023–August 21, 2023). Content analysis was conducted to assess the nature of public responses, justifications for positive or negative attitudes, and the users’ overall knowledge of how Chinese human genetic information is regulated and managed in China.ResultsWeibo users displayed contrasting attitudes towards the article’s public disclose of pangenome research data, with 18% positive, 64% negative, and 18% neutral. Positive attitudes came primarily from verified government and media accounts, which praised the publication. In contrast, negative attitudes originated from individual users who were concerned about national security and health risks and often believed that the researchers have betrayed China. The benefits of data sharing highlighted in the commentaries included advancements in disease research and scientific progress. Approximately 16% of the microblogs indicated that Weibo users had misunderstood existing regulations and laws governing data sharing and stewardship.ConclusionsBased on the predominantly negative public attitudes toward scientific data sharing established by our study, we recommend enhanced outreach by scientists and scientific institutions to increase the public understanding of developments in genetic research, international data sharing, and associated regulations. Additionally, governmental agencies can alleviate public fears and concerns by being more transparent about their security reviews of international collaborative research involving Chinese human genetic data and its cross-border transfer.

Real-Time Monitoring of mtDNA Aggregation and Mitophagy Induced by a Fluorescent Platinum Complex in Living Cells.

Mitochondrial DNA (mtDNA) is pivotal for mitochondrial morphology and function. Upon mtDNA damage, mitochondria undergo quality control mechanisms, including fusion, fission, and mitophagy. Real-time monitoring of mtDNA enables a deeper understanding of its effect on mitochondrial function and morphology. Controllable induction and real-time tracking of mtDNA dynamics and behavior are of paramount significance for studying mitochondrial function and morphology, facilitating a deeper understanding of mitochondria-related diseases. In this work, a fluorescent platinum complex was designed and developed that not only induces mitochondrial DNA (mtDNA) aggregation but also triggers mitochondrial autophagy (mitophagy) through the MDV pathway for damaged mtDNA clearance in living cells. Additionally, this complex allows for the real-time monitoring of these processes. This complex may serve as a valuable tool for studying mitochondrial microautophagy and holds promise for broader applications in cellular imaging and disease research.

A review of MPTP-induced parkinsonism in adult zebrafish to explore pharmacological interventions for human Parkinson's disease.

Novel work in adult zebrafish, Danio rerio, to recapitulate human neurodegenerative disease has proven useful in both pharmaceutical development and research on genetic disease. Due to high genetic homology to humans, affordable husbandry, relatively quick life cycle breeding times, and robust embryo production, zebrafish offer a promising model to test pharmaceutical performance in a high throughput, in vivo setting. Currently, most research in zebrafish models of Parkinson's disease induces the disease in larval or embryonic stage organisms due to ease of administration, with advancement through developmental stages taking only a matter of days. The use of early-stage organisms limits the usability of zebrafish as models for adult disease and specifically age-related neurodegenerative conditions. Recently, researchers have sought to extend the usability of zebrafish into models for Parkinson's disease. Specifically, 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) has emerged as a prodrug that upon injection well-encompasses the biochemical mechanisms and symptomology associated with Parkinson's disease. By utilizing MPTP in an adult zebrafish model, advancements in Parkinson's disease research may be achieved. This paper highlights the recent research on this model, comparing it to the human form of Parkinson's disease.

Inflammatory bowel disease research

Inflammatory bowel disease research

Single-cell RNA sequencing in tuberculosis: Application and future perspectives.

Tuberculosis (TB) has one of the highest mortality rates among infectious diseases worldwide. The immune response in the host after infection is proposed to contribute significantly to the progression of TB, but the specific mechanisms involved remain to be elucidated. Single-cell RNA sequencing (scRNA-seq) provides unbiased transcriptome sequencing of large quantities of individual cells, thereby defining biological comprehension of cellular heterogeneity and dynamic transcriptome state of cell populations in the field of immunology and is therefore increasingly applied to lung disease research. Here, we first briefly introduce the concept of scRNA-seq, followed by a summarization on the application of scRNA-seq to TB. Furthermore, we underscore the potential of scRNA-seq for clinical biomarker exploration, host-directed therapy, and precision therapy research in TB and discuss the bottlenecks that need to be overcome for the broad application of scRNA-seq to TB-related research.

Determinants of possible inflammatory myocardial damage in acute intestinal infections in children

BACKGROUND: Non-coronary cardiomyopathies, including inflammatory cardiomyopathies, are one of the leading causes of disability and mortality in children and adults. Inflammatory cardiomyopathy in most cases is an outcome of myocarditis as a result of direct agent-dependent myocardial damage or autoimmune reactions in the absence of genetic predisposition. AIM: On the basis of clinical assessment of cardiovascular system changes, to develop a discriminant model to predict the possibility of myocardial damage of inflammatory genesis in acute intestinal infections (AII) in children. MATERIALS AND METHODS: In the Intestinal Infections Department of the Children’s Research and Clinical Center for Infectious Diseases of FMBA of Russia in the period 2020-2022, 33 children aged from 1 month to 13 years with AII of different etiology were consecutively observed, in whom, according to clinical, laboratory and instrumental examination data, for the first time in their lives, changes in cardiovascular system were detected. The sample was formed using an algorithm for diagnosing inflammatory myocardial lesions in points, the sum of which concluded that there were no or presence of such, which allowed us to identify group 1 (n = 24) and group 2 (n = 9), respectively. Etiological diagnosis of acute intestinal infections was performed in all children, clinical and laboratory data, results of a 12-channel electrocardiogram (ECG), transthoracic echocardiography (EchoCG) were evaluated. The differences in the groups were revealed using the Pearson chi-squared test and the Mann–Whitney test, which were considered reliable at p 0.05. The method of discriminant analysis was used. RESULTS: Functional systolic noise and increased cardiospecific enzymes were observed less frequently in group 1 than in group 2 (4.2%; 22.2% and 67%; 100%). Of the pathological ECG changes, violations of the repolarization process were observed (16.7%; 33.3%). No significant changes in the Echo-KG were detected. The viral etiology of acute intestinal infections dominated (79.2%; 88.9%). Changes in the hemogram were characterized by a high frequency of leukocytosis in group 1 (29.2%; 0%) and leukopenia in group 2 (4.2%; 22.2%). In group 1, there was a higher frequency of neutrophilosis (79.2%; 44.4%), rod-shaped shift (62.5%; 22.2%), thrombocytosis (29.2%; 0%), lymphocytopenia (95.8%; 55.6%; p 0.05), monocytosis (8.3%; 0%); increased C-reactive protein (41.7%; 33.3%), ALT (29.2%; 11.1%), urea (29.2%; 11.1%), leukocyturia (16.7%; 0%). CONCLUSIONS: Clinical evaluation of cardiovascular system changes in children with acute intestinal infections using a discriminant model allows to exclude myocardial damage of inflammatory genesis with high probability (95.7%), which is of practical importance.

Research Progress in the Construction and Application of In Vitro Vascular Models

The vascular system maintains cellular homeostasis by transporting oxygen, nutrients, and metabolic waste products. The vascular system is involved in a variety of fundamental physiological phenomena and is closely associated with human vascular diseases. Additionally, the stability of drugs in the vasculature affects their efficacy. Therefore, researchers have used vascular models to study vascular diseases, assess drug stability, and screen drugs. However, there are many shortcomings in the animal models and in vitro two-dimensional vascular models that have been extensively developed. In this paper, we specifically review the construction methods of in vitro vascular models and classify the specific methods into photolithography, soft lithography, self-assembly, template, 3D bioprinting, and laser degradation/cavitation. The first two are microfluidics-based methods and the last three are non-microfluidics-based methods. The vascular model construction methods reviewed in this paper overcome the shortcomings of traditional models—which cannot accurately reproduce the human vascular microenvironment—and can assist in the construction of in vitro 3D vascular models and tissue engineering vascularization. These models can be reused by perfusion devices, and the cells within the channels reside on biocompatible materials that are used to simulate the microenvironment and 3D cellular organization of the vasculature in vivo. In addition, these models are reproducible in shape and length, allowing experiments to be repeated, which is difficult to do with natural vessels. In vitro vascular models are widely used in research and drug screening for diseases associated with endothelial dysfunction, cancer, and other vascular abnormalities.

Short time-series expression transcriptome data reveal the gene expression patterns and potential biomarkers of blood infection with LPS and poly (I:C) in Mandarin fish (Siniperca chuatsi)

Blood transcriptomics has emerged as a vital tool for tracking the immune system and supporting disease diagnosis, prognosis, treatment, and research. The present study was conducted to analyze the gene expression profile and potential biomarker candidates using the whole blood of mandarin fish (Siniperca chuatsi) infected with LPS or poly (I:C) at 0 h, 3 h, 6 h, and 12 h. Our data suggest that 310 shared differentially expressed genes (DEGs) were identified among each comparison group after LPS infection, and 137 shared DEGs were identified after poly (I:C) infection. A total of 62 shared DEGs were differentially expressed in all compared groups after LPS or poly (I:C) infection. Pathways analysis for DEGs in all different compared groups showed that cytokine-cytokine receptor interaction was the most enrichment pathway. The expression levels of genes C-X-C chemokine receptor type 2-like (cxcr2), chemokine (C-C motif) receptor 9a (ccr9a), chemokine (C-C motif) receptor 9b (ccr9b), chemokine (C-X-C motif) receptor 4b (cxcr4b), and interleukin 10 receptor alpha (il10ra) were significantly different in all compared groups and most enriched in cytokine-cytokine receptor interaction pathway. The protein-protein interactions analysis among all shared DEGs showed that cxcr4 was the hub gene with the highest degree. The biomarker candidates discovered in this study may, following validation, prove effective as diagnostic tools in monitoring mandarin fish diseases.

Abstract We014: Creating Cell-specific Computational Models of Stem Cell-derived Cardiomyocytes Using Optical Experiments

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have gained traction as a powerful model in cardiac disease and therapeutics research, since iPSCs are self-renewing and can be derived from healthy and diseased patients without invasive surgery. However, current iPSC-CM differentiation methods produce cardiomyocytes with immature, fetal-like electrophysiological phenotypes, and the variety of maturation protocols in the literature results in phenotypic differences between labs. Heterogeneity of iPSC donor genetic backgrounds contributes to additional phenotypic variability. Several mathematical models of iPSC-CM electrophysiology have been developed to help understand the ionic underpinnings of, and to simulate, various cell responses, but these models individually do not capture the phenotypic variability observed in iPSC-CMs. Here, we tackle these limitations by developing a computational pipeline to calibrate cell preparation-specific iPSC-CM electrophysiological parameters. We used the genetic algorithm (GA), a heuristic parameter calibration method, to tune ion channel parameters in a mathematical model of iPSC-CM physiology. To systematically optimize an experimental protocol that generates sufficient data for parameter calibration, we created simulated datasets by applying various protocols to a population of in silico cells with known conductance variations, and we fitted to those datasets. We found that calibrating models to voltage and calcium transient data under 3 varied experimental conditions, including electrical pacing combined with ion channel blockade and changing buffer ion concentrations, improved model parameter estimates and model predictions of unseen channel block responses. This observation held regardless of whether the fitted data were normalized, suggesting that normalized fluorescence recordings, which are more accessible and higher throughput than patch clamp recordings, could sufficiently inform conductance parameters. Therefore, this computational pipeline can be applied to different iPSC-CM preparations to determine cell line-specific ion channel properties and understand the mechanisms behind variability in perturbation responses.

A comprehensive review of current practices, challenges, and future perspectives in Koi fish (Cyprinus carpio var. koi) cultivation.

The Koi fish (Cyprinus carpio var. koi) is an ornamental fish with a high selling value because of its attractive colors, color patterns, body shape, and swimming motion. Koi fish is extensively traded in the international fish market because of their popularity among hobbyists from numerous countries worldwide. This review discusses various aspects of Koi fish cultivation, including genetic involvement, selective breeding strategies, and management systems. By examining crucial factors such as water parameters, technological innovations, and evolving cultivation methods, this review explored their influence on the quality of Koi fish. Breakthrough technologies, such as ornamental fish warehousing and recirculation aquaculture systems, enhance breeding efficiency and profitability. Molecular sexing, feed optimization, and color enhancement strategies are central to pursuing superior Koi fish. Reproduction management, disease prevention, and risk reduction during transport underscore ongoing efforts to ensure their survival. Despite notable progress, several challenges remain, including limited genetic studies, gaps in disease research, and unexplored herbal alternatives. The active involvement of hobbyists and breeders in research initiatives is a pivotal force in unlocking the untapped potential. The holistic approaches to enhance production efficiency and improve care standards require further exploration, paving the way for a sustainable future in the evolving management of Koi fish cultivation.