Research Resources Research Articles

Genomes of autotetraploid wild and cultivated Ziziphus mauritiana reveal polyploid evolution and crop domestication.

Indian jujube (Ziziphus mauritiana) holds a prominent position in the global fruit and pharmaceutical markets. Here, we report the assemblies of haplotype-resolved, telomere-to-telomere genomes of autotetraploid wild and cultivated Indian jujube plants using a two-stage assembly strategy. The generation of these genomes permitted in-depth investigations into the divergence and evolutionary history of this important fruit crop. Using a graph-based pan-genome constructed from eight monoploid genomes, we identified structural variation (SV)-FST hotspots and SV hotspots. Gap-free genomes provide a means to obtain a global view of centromere structures. We identified presence-absence variation-related genes in four monoploid genomes (cI, cIII, wI, and wIII) and resequencing populations. We also present the population structure and domestication trajectory of the Indian jujube based on the resequencing of 73 wild and cultivated accessions. Metabolomic and transcriptomic analyses of mature fruits of wild and cultivated accessions unveiled the genetic basis underlying loss of fruit astringency during domestication of Indian jujube. This study reveals mechanisms underlying the divergence, evolution, and domestication of the autotetraploid Indian jujube and provides rich and reliable genetic resources for future research.

G4LDB 3.0: a database for discovering and studying G-quadruplex and i-motif ligands.

Non-canonical nucleic acid structures, such as G-quadruplex (G4) and i-Motif (iM), have garnered significant research interest because of their unique structural properties and biological activities. Thousands of small molecules targeting G4/iM structures have been developed for various chemical and biological applications. In response to the growing interest in G4-targeting ligands, we launched the first G4 Ligand Database (G4LDB) in 2013. Here, we introduce G4LDB 3.0 (http://www.g4ldb.com), an upgraded version featuring extensive enhancements in content and functionality. The new version includes over 4800 G4/iM ligands and approximately 51 000 activity entries. Key upgrades include advanced search capabilities, dynamic knowledge graphs, enhanced data visualization, along with a new dynamic analysis function that automatically displays ligand structure clustering results and chemical space distribution. With these updates, G4LDB 3.0 further evolves into a comprehensive resource and valuable research tool. The significant improvements address the increasing demand for efficient data handling and user experience, highlighting the critical role of G4LDB in advancing research on G-quadruplexes and i-motifs.

A Trend Analysis of Project-based Learning in Chemistry Experiment: A Bibliometric Analysis

Project-based learning is a global trend, widely adopted across countries. Project-based learning has developed diversely by emphasizing interdisciplinary, cross-domain, and regional collaboration. To provide in-depth resources for researchers and educators on project-based learning in chemistry experiments, this study aims to make a bibliometric analysis on the topic of project-based learning globally using publication characteristics analysis. The database used in this study used Scopus and obtained 5900 articles from 2018-2023. Bibliometric analysis was analyzed using VOSviewer and Microsoft Excel. The results of the bibliometric analysis show that Boone, C.D. is the author with the highest number of citations on the research topic, Project-based learning in a chemistry experiment. The United States is the most productive country in researching this topic, with 1351 articles. The most influential journal with the highest number of articles is the Journal of Physics Conference Series, with 243 articles. The major contextualized learning literatures in this study tend to fall into broad groups such as Project-based Learning, Education, and STEM Education. These findings suggest the need for multidisciplinary and cross-disciplinary studies on project-based learning research on chemistry learning and advocate for the inclusion of project-based learning research in education from a broader geographical context.

RPFdb v3.0: an enhanced repository for ribosome profiling data and related content.

RPFdb (http://www.rpfdb.org or http://sysbio.gzzoc.com/rpfdb/) is a comprehensive repository dedicated to hosting ribosome profiling (Ribo-seq) data and related content. Herein, we present RPFdb v3.0, a significant update featuring expanded data content and improved functionality. Key enhancements include (i) increased data coverage, now encompassing 5018 Ribo-seq datasets and 2343 matched RNA-seq datasets from 496 studies across 34 species; (ii) implementation of translation efficiency, combining Ribo-seq and RNA-seq data to provide gene-specific translation efficiency; (iii) addition of pausing score, facilitating the identification of condition-specific triplet amino acid motifs with enhanced ribosome enrichment; (iv) refinement of open reading frame (ORF) annotation, leveraging RibORF v2.0 for more sensitive detection of actively translated ORFs; (v) introduction of a resource hub, curating advances in translatome sequencing techniques and data analytics tools to support a panoramic overview of the field; and (vi) redesigned web interface, providing intuitive navigation with dedicated pages for streamlined data retrieval, comparison and visualization. These enhancements make RPFdb a more powerful and user-friendly resource for researchers in the field of translatomics. The database is freely accessible and regularly updated to ensure its continued relevance to the scientific community.

National stakeholder consultation on how to measure care home residents' quality of life.

The Developing research resources And minimum data set for Care Homes' Adoption and use or DACHA study aims to create a prototype minimum data set combining residents' information recorded by care homes with their data held in health and social care data sets. The DACHA minimum data set will contain information on quality of life. Internationally and in the UK, there is no consensus on collecting information on quality of life in a standardised format equivalent to the consensus for health measures. This paper describes an online consultation with stakeholder representatives about how to measure the quality of life of residents in UK older-adult care homes, for inclusion in the DACHA minimum data set. We drew on principles of the Delphi technique, identifying participants knowledgeable about living, working in and visiting care homes, and preference scoring. We used a bespoke online research engagement platform (Thiscovery, www.thiscovery.org, Cambridge, UK) to engage the participants. Participants included care home staff and managers, old age specialists (clinical/research), commissioners/providers/regulators, primary care professionals, relatives/family carers of care home residents. The consultation is complementary to DACHA's research and patient and public involvement and engagement activities, which have involved people living in care homes; thus, care home residents were not included in this consultation. The first round asked 30 participants to rank the most important principles and domains to consider when measuring quality of life in care homes. Responses to round 1 informed the selection of quality of life measures that round 2 (September 2022) participants were asked to report their familiarity with and confidence in a range of outcome measures all of which met the criteria identified as important in round 1. Recruitment was extended in round 2, and 72 individuals participated. Based on the rankings and the qualitative feedback in round 2, we included four of the shortlisted quality of life outcome measures in DACHA's prototype minimum data set for care homes. The qualitative feedback suggested a shared understanding across the different representative groups about the strengths and limitations of the selected measures. This work makes an important contribution, understanding the opportunities that quality of life measures pose for different stakeholder groups as regular users of care home resident data. In future DACHA work, interviews and focus groups will collect further data about the perceptions of care home staff who completed measures during the pilot study and about the usefulness of the data collected via these measures. The quality-of-life section of the DACHA minimum data set can contribute to informing similar care home data sets internationally. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme as award number NIHR127234.

PROTA: A Robust Tool for Protamine Prediction Using a Hybrid Approach of Machine Learning and Deep Learning

Protamines play a critical role in DNA compaction and stabilization in sperm cells, significantly influencing male fertility and various biotechnological applications. Traditionally, identifying these proteins is a challenging and time-consuming process due to their species-specific variability and complexity. Leveraging advancements in computational biology, we present PROTA, a novel tool that combines machine learning (ML) and deep learning (DL) techniques to predict protamines with high accuracy. For the first time, we integrate Generative Adversarial Networks (GANs) with supervised learning methods to enhance the accuracy and generalizability of protamine prediction. Our methodology evaluated multiple ML models, including Light Gradient-Boosting Machine (LIGHTGBM), Multilayer Perceptron (MLP), Random Forest (RF), eXtreme Gradient Boosting (XGBOOST), k-Nearest Neighbors (KNN), Logistic Regression (LR), Naive Bayes (NB), and Radial Basis Function-Support Vector Machine (RBF-SVM). During ten-fold cross-validation on our training dataset, the MLP model with GAN-augmented data demonstrated superior performance metrics: 0.997 accuracy, 0.997 F1 score, 0.998 precision, 0.997 sensitivity, and 1.0 AUC. In the independent testing phase, this model achieved 0.999 accuracy, 0.999 F1 score, 1.0 precision, 0.999 sensitivity, and 1.0 AUC. These results establish PROTA, accessible via a user-friendly web application. We anticipate that PROTA will be a crucial resource for researchers, enabling the rapid and reliable prediction of protamines, thereby advancing our understanding of their roles in reproductive biology, biotechnology, and medicine.

Biogas production and techno‐economic feasibility studies of setting up household biogas technology in Africa: A critical review

AbstractThis critical review examines the potential of household biogas technology in Africa, focusing on biogas production and techno‐economic feasibility studies. The review highlights the benefits of biogas technology, including renewable energy generation, waste management, and improved public health. A significant portion of Africa's rural population, approximately 60%, grapples with limited access to reliable power sources. The study analyzes various biogas production systems, including anaerobic digesters and biomass gasifiers, and evaluates their economic viability in different African contexts. The review identifies key factors influencing the adoption of household biogas technology, including policy and regulatory frameworks, financing mechanisms, and public awareness. Biogas production stands out as one of the promising renewable energy sources. However, it also discusses the challenges and limitations of implementing this technology on a continental scale. The study analyzes various biogas production systems, including anaerobic digesters and biomass gasifiers, and evaluates their economic viability in different African contexts. The review identifies key factors influencing the adoption of household biogas technology, including policy and regulatory frameworks, financing mechanisms, and public awareness. The study concludes by recommending strategies for scaling up biogas technology in Africa, including capacity building, technology transfer, and innovative financing models. The review aims to provide a comprehensive resource for researchers, policymakers, and practitioners working towards sustainable energy solutions in Africa.

Ecological flow research in response to hydrological variation: A case study of the Jinsha River Basin, China

Climate change and human activities have altered the natural state of rivers to a certain extent, leading to runoff variation and impacting the stability of riverine ecosystems. The ecological flow has emerged to balance the water relationship between humanity and riverine ecosystems and to safeguard the health and biodiversity of rivers. Presently, the scientific quantification of riverine ecological flow has become a focal point in water resource research. Addressing the quantification of ecological flow under hydrological variation conditions, the cumulative deviation method (CDM) and Pettitt methods were firstly employed to detect breakpoints in the runoff sequences. Then, the natural monthly runoff post-variation was restored using the Soil and Water Assessment Tool (SWAT) model, i.e., natural runoff restoration, and three testing methods were employed to determine the optimal hydrological distribution functions for natural monthly runoff. Subsequently, an improved frequency calculation method was used to calculate the ecological flow. The Jinsha River Basin was selected as the study area, and four crucial sections in the mainstream of the Jinsha River were studied, including Zhimenda (ZMD), Shigu (SG), Xiaodeshi (XDS), and Pingshan (PS). The results indicated: (1) the runoff sequences (1960–2017) at the four crucial sections exhibit different breakpoint times, with breakpoint years being 2004, 1986, 2005, and 1996, respectively; (2) the SWAT model, in simulating runoff at the four crucial sections, exhibited NSE values all exceeding 0.85, and r values all surpassing 0.9, demonstrating its effective ability to restore natural runoff in the Jinsha River basin; (3) the optimal hydrological distribution functions for natural monthly runoff at the four sections varied, and most natural monthly runoff conforms to the Generalized Extreme Value (GEV) distribution; (4) the average annual ecological flows for the ZMD, SG, XDS, and PS sections were 296 m3/s, 992 m3/s, 1238 m3/s, and 2755 m3/s, and the ecological flows derived using the improved frequency calculation method under the optimal hydrological distribution functions were more rational. This study can provide a scientific basis for the optimal allocation of water resources and the protection of riverine ecosystems in the Jinsha River basin.

A Survey on Vision-Based Anti Unmanned Aerial Vehicles Methods

The rapid development and widespread application of Unmanned Aerial Vehicles (UAV) have raised significant concerns about safety and privacy, thus requiring powerful anti-UAV systems. This survey provides an overview of anti-UAV detection and tracking methods in recent years. Firstly, we emphasize the key challenges of existing anti-UAV and delve into various detection and tracking methods. It is noteworthy that our study emphasizes the shift toward deep learning to enhance detection accuracy and tracking performance. Secondly, the survey organizes some public datasets, provides effective links, and discusses the characteristics and limitations of each dataset. Next, by analyzing current research trends, we have identified key areas of innovation, including the progress of deep learning techniques in real-time detection and tracking, multi-sensor fusion systems, and the automatic switching mechanisms that adapt to different conditions. Finally, this survey discusses the limitations and future research directions. This paper aims to deepen the understanding of innovations in anti-UAV detection and tracking methods. Hopefully our work can offer a valuable resource for researchers and practitioners involved in anti-UAV research.

The turnover intention of internal controllers of Vietnamese commercial banks in the context of COVID-19

Internal control plays an important role in managing the risks of banking system activities. Controllers are always under pressure from control activities due to the bank’s diverse activities. The resignation of internal controllers is relatively common in commercial banks. It is also a matter of concern for the banking and finance industry, which coordinates economic resources for the country, especially when the internal control period occurs again with the pandemic. The study aims to explore the turnover intention of internal controllers in the context of COVID-19 in Vietnamese commercial banks. The study uses the convenience sampling method to collect data from 339 respondents who are working or worked as internal controllers in commercial banks. The study was surveyed in 2023. The study uses quantitative methods for exploratory factor analysis. Ordinary least squares process the data to test the hypotheses. Some factors affect the turnover intention of internal controllers, such as occupational awareness, employment conditions, office environment, and career opportunities, in the context of COVID-19. The result is a useful resource for researchers to comprehensively understand issues related to the turnover intention of internal controllers in the banking industry. The study supports managers of commercial banks in planning the strategic objectives of human resource stabilization for the stable growth of the banking system.

A comprehensive review on crack detection schemes and modelling techniques in high-speed rotor systems

ABSTRACT The combination of a rotor and bearings plays a pivotal role in various industrial applications, including gas turbines, compressors, turbochargers, aircraft engines, and wind generators. Ensuring the structural integrity of the rotor-bearing assembly during static and dynamic conditions is most important, as any failure could lead to unpredictable losses. Due to their continuous operation, high-speed rotors are more susceptible to faults such as misalignment, bow, eccentricity, and cracks. Among these faults, cracks are the most predominant fault that affects the system’s reliability. Despite significant advancements in rotor dynamics, cracks still threaten the integrity and performance of the rotor-bearing assembly. This review paper aims to thoroughly review the challenges and issues associated with crack formation in high-speed rotor systems. Various crack detection methods are also explored using vibration signals obtained from the rotor-bearing unit and their associated processing techniques. This study also gives an extensive overview of different crack modelling and analysis techniques. Furthermore, a novel rotor-bearing model is modelled using the finite element method, and the numerical results obtained from this model are validated with the existing literature model. This review paper will serve as a valuable resource for researchers that offers insights into the latest advancements and emphasises the importance of crack detection for ensuring the reliability of high-speed rotor systems.

An Overview of the Recent Advances in Antimicrobial Resistance.

Antimicrobial resistance (AMR), frequently considered a major global public health threat, requires a comprehensive understanding of its emergence, mechanisms, advances, and implications. AMR's epidemiological landscape is characterized by its widespread prevalence and constantly evolving patterns, with multidrug-resistant organisms (MDROs) creating new challenges every day. The most common mechanisms underlying AMR (i.e., genetic mutations, horizontal gene transfer, and selective pressure) contribute to the emergence and dissemination of new resistant strains. Therefore, mitigation strategies (e.g., antibiotic stewardship programs-ASPs-and infection prevention and control strategies-IPCs) emphasize the importance of responsible antimicrobial use and surveillance. A One Health approach (i.e., the interconnectedness of human, animal, and environmental health) highlights the necessity for interdisciplinary collaboration and holistic strategies in combating AMR. Advancements in novel therapeutics (e.g., alternative antimicrobial agents and vaccines) offer promising avenues in addressing AMR challenges. Policy interventions at the international and national levels also promote ASPs aiming to regulate antimicrobial use. Despite all of the observed progress, AMR remains a pressing concern, demanding sustained efforts to address emerging threats and promote antimicrobial sustainability. Future research must prioritize innovative approaches and address the complex socioecological dynamics underlying AMR. This manuscript is a comprehensive resource for researchers, policymakers, and healthcare professionals seeking to navigate the complex AMR landscape and develop effective strategies for its mitigation.

Biomimetic Adaptive Building Façade Modeling for Sustainable Urban Freshwater Ecosystems: Integration of Nature's Water-Harvesting Strategy into Sun-Breakers.

Urban freshwater ecosystems have many critical functions, such as providing water to all living things and supporting biodiversity. Factors such as water pollution, increased water consumption, habitat loss, climate change, and drought threaten the health of urban freshwater ecosystems. Looking for solutions to these challenges, this article aims to recycle water and return it to its life cycle using a climate-sensitive water collection strategy. The model focuses on the biomimetic method as a basic strategy. In this regard, the concept of water-harvesting has been examined in detail by conducting a deep literature review, including architecture and engineering disciplines. With all these data obtained, a synthesis/integration study was carried out by developing a model proposal based on adaptive building façade elements to solve the water problems experienced in cities. The model proposal, which is directly related to the titles of "Clean Water and Sanitation (SDG 6)" and "Sustainable Cities and Communities (SDG 11)", which are among the Sustainable Development Goals (SDGs), aims to provide different perspectives on the disciplines with its superficial and functional features. In this context, it is anticipated that the article will become an indispensable resource for other researchers working on the subject.

Investigation of the Perspectives of Medical Faculty Students in Different Terms on Anatomy Education

Aim: The science of anatomy, which has a great importance in medical and health sciences, examines the human body, the systems that make up the body, the organs that make up the systems and the relations of organs with each other. As a cornerstone of medical education, students' perspectives on anatomy evolve with technological advancements and their journey to becoming physicians. The aim of this study is to investigate of the perspectives of medical faculty students in different terms on anatomy education. Material and Methods: A total of 557 medical faculty students from Terms I to VI participated in the study.The survey prepared in Google Forms was sent to the students online via the WhatsApp application. Descriptive statistical analyses were used on the data. Results: Analysis revealed that Term I-III students valued anatomy education more, while Term IV-VI students prioritized clinical practices. Term I-III students saw cadaver-based anatomy education as professionally important, whereas Term IV-VI students favored using 3-D anatomy materials in education. Conclusion: We believe the anatomy curriculum should be reviewed and updated to enhance students' professional development. Integrating clinical sciences into a multidisciplinary approach may shift the perspectives of Term IV-VI students. This study will serve as a valuable resource for future research in medical and health sciences education.

An Alternative Method for Synthesizing N,2,3-Trimethyl-2H-indazol-6-amine as a Key Component in the Preparation of Pazopanib

Due to its application as an anti-cancer drug, pazopanib (1) has attracted the interest of many researchers, and several studies on pazopanib synthesis have been reported over the years. This paper provides a novel route for synthesizing N,2,3-trimethyl-2H-indazol-6-amine (5), which is a crucial building block in the synthesis of pazopanib from 3-methyl-6-nitro-1H-indazole (6). By alternating between the reduction and two methylation steps, compound 5 was obtained in a yield comparable (55%) to what has been reported (54%). It is noteworthy that the last step of N2-methylation also yielded N,N,2,3-tetramethyl-2H-indazol-6-amine (5′) as a novel compound. Furthermore, the data presented in this paper can serve as a valuable resource for future research aimed at further refining the process of synthesizing pazopanib and its derivatives.

Population-Level Administrative Data: A Resource to Advance Psychological Science

Population-level administrative data—data on individuals’ interactions with administrative systems, such as health-care, social-welfare, criminal-justice, and education systems—are a fruitful resource for research into behavior, development, and well-being. However, administrative data are underutilized in psychological science. Here, we review advantages of population-level administrative data for psychological research and provide examples of advances in psychological theory arising from administrative data studies. We focus on advantages in three areas: the collection and recording of population-level administrative data, the data’s large scale, and unique data linkages. We also describe ethical issues as well as methodological considerations and limitations in population administrative data research and outline future directions to enable psychological scientists to more fully capitalize on administrative data resources.

Data-driven classification and explainable-AI in the field of lung imaging.

Detecting lung diseases in medical images can be quite challenging for radiologists. In some cases, even experienced experts may struggle with accurately diagnosing chest diseases, leading to potential inaccuracies due to complex or unseen biomarkers. This review paper delves into various datasets and machine learning techniques employed in recent research for lung disease classification, focusing on pneumonia analysis using chest X-ray images. We explore conventional machine learning methods, pretrained deep learning models, customized convolutional neural networks (CNNs), and ensemble methods. A comprehensive comparison of different classification approaches is presented, encompassing data acquisition, preprocessing, feature extraction, and classification using machine vision, machine and deep learning, and explainable-AI (XAI). Our analysis highlights the superior performance of transfer learning-based methods using CNNs and ensemble models/features for lung disease classification. In addition, our comprehensive review offers insights for researchers in other medical domains too who utilize radiological images. By providing a thorough overview of various techniques, our work enables the establishment of effective strategies and identification of suitable methods for a wide range of challenges. Currently, beyond traditional evaluation metrics, researchers emphasize the importance of XAI techniques in machine and deep learning models and their applications in classification tasks. This incorporation helps in gaining a deeper understanding of their decision-making processes, leading to improved trust, transparency, and overall clinical decision-making. Our comprehensive review serves as a valuable resource for researchers and practitioners seeking not only to advance the field of lung disease detection using machine learning and XAI but also from other diverse domains.

Laboratory maintenance and care of Rhodnius prolixus (Hemiptera: Reduviidae) and other Triatominae

Abstract Triatomines (Hemiptera: Reduviidae) are hematophagous insects that transmit Trypanosoma cruzi, the etiological agent for Chagas disease, to humans and other mammals. As medically important vectors, species such as Rhodnius prolixus (Hemiptera: Reduviidae) have long been used as a model organism for physiological studies. Laboratory rearing of triatomines is needed to support vector and parasite research. Many environmental conditions, such as suitable housing containers, light source and duration, temperature, humidity, and density, must be addressed when adapting triatomines from a natural habitat for artificial rearing to create conditions for optimal growth and survival. Food source is also an important factor, as triatomines are considered the obligate blood feeders. Parasites and pathogens present risks not only for triatomines but also for the laboratorians handling them. Equipping an insectary space should apply best practices to ensure community, personnel, and insect health. Various triatomine colonies have been maintained in the Centers for Disease Control and Prevention (CDC) Entomology Branch insectary for over 25 years and have more recently been made available to the research community through the Biodefense and Emerging Infections Research Resources Repository (BEI Resources). The CDC Rhodnius prolixus genome has been characterized and thus represents an opportunity for continued model organism research. In addition to fulfilling requests for live triatomines, inquiries are received for support in establishing new and troubleshooting existing laboratory colonies. To accompany the extensive MR4 manual, Methods in Anopheles Research, procedures for triatomine husbandry have been developed and are shared here to address the aforementioned topics.

‘Don’t panic, don’t panic’: an analysis of a purported pro-eating disorder website/online content moral panic and legal and policy responses

ABSTRACT It has been argued that newspaper responses to pro-eating disorder websites, within the United Kingdom (UK), constitute a moral panic. It is feared that moral panics may spur rash legal/policy responses. My analysis indicates that the consideration of pro-eating disorder websites by British newspaper journalists and others does not constitute a moral panic. I argue that the misuse of the moral panic concept exemplifies the dominance of emotivism within contemporary culture and may trivialise potential online harms and serve as an apologia for surveillance/digital capitalism. I contend that pro-eating disorder websites are potentially harmful and assess legal and policy responses, such as the Online Safety Act 2023 and the advancement of the digital commons. I also contend that the increase in the number of people suffering with eating disorders within the UK should be addressed by devoting more resources for research into, and the prevention and treatment of, eating disorders.

Long-read de novo genome assembly of Gulf toadfish (Opsanus beta)

BackgroundThe family Batrachoididae are a group of ecologically important teleost fishes with unique life histories, behavior, and physiology that has made them popular model organisms. Batrachoididae remain understudied in the realm of genomics, with only four reference genome assemblies available for the family, with three being highly fragmented and not up to current assembly standards. Among these is the Gulf toadfish, Opsanus beta, a model organism for serotonin physiology which has recently been bred in captivity.ResultsHere we present a new, de novo genome and transcriptome assemblies for the Gulf toadfish using PacBio long read technology. The genome size of the final assembly is 2.1 gigabases, which is among the largest teleost genomes. This new assembly improves significantly upon the currently available reference for Opsanus beta with a final scaffold count of 62, of which 23 are chromosome scale, an N50 of 98,402,768, and a BUSCO completeness score of 97.3%. Annotation with ab initio and transcriptome-based methods generated 41,076 gene models. The genome is highly repetitive, with ~ 70% of the genome composed of simple repeats and transposable elements. Satellite DNA analysis identified potential telomeric and centromeric regions.ConclusionsThis improved assembly represents a valuable resource for future research using this important model organism and to teleost genomics more broadly.