bluuebunny/crossref_metadata_2025 huggingface dataset:
Large-language-model-based 10-year risk prediction of cardiovascular disease: insight from the UK biobank data
Authors: Han Changho , Kim Dong Won , Kim Songsoo , You Seng Chan , Bae SungA , Yoon Dukyong
Published: May 2023

Background

Conventional cardiovascular risk prediction models provide insights into population-level risk factors and have been widely adopted in clinical practice. However, these models have limited generalizability and flexibility. Large language models (LLMs) have demonstrated remarkable proficiency for use in various industries.

Methods

In this study, we have investigated the feasibility of Large Language Models (LLMs) such as ChatGPT-3.5, ChatGPT-4, and Bard for predicting 10-year cardiovascular risk of a patient. We used data from the UK Biobank Cohort, a major biomedical database in the UK, and the Korean Genome and Epidemiology Study (KoGES), a large-scale prospective study in Korea, for additional validation and multi-institutional research. These databases provided a wide array of information including age, sex, medical history, lipid profile, blood pressure, and physical measurement. Based on these data, we generated language sentences for individual analysis and input these into the LLM to derive results. The performance of the LLMs was then compared with the Framingham Risk Score (FRS), a conventional risk prediction model, using this real-world data. We confirmed the model performance of both the LLMs and FRS, evaluating their accuracy, sensitivity, specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV), and F1 score. Their performance in predicting 10-year cardiovascular risk was compared through Kaplan-Meier survival analysis and Cox-hazard ratio analysis.

Findings

GPT-4 achieved performance comparable to the FRS in cardiovascular risk prediction in both the UK Biobank {accuracy (0·834 vs· 0·773) and F1 score (0·138 vs· 0·132)} and KoGES {accuracy (0·902 vs· 0·874)}. The Kaplan–Meier survival analysis of GPT-4 demonstrated distinct survival patterns among groups, which revealed a strong association between the GPT risk prediction output and survival outcomes. The additional analysis of limited variables using GPT-3·5 indicated that ChatGPT’s prediction performance was preserved despite the omission of a few variables in the prompt, especially without physical measurement data

Interpretation

This study proposed that ChatGPT can achieve performance comparable to conventional models in predicting cardiovascular risk. Furthermore, ChatGPT exhibits enhanced accessibility, flexibility, and the ability to provide user-friendly outputs. With the evolution of LLMs, such as ChatGPT, studies should focus on applying LLMs to various medical scenarios and subsequently optimizing their performance.
Breast cancer risk based on a deep learning predictor of senescent cells in normal tissue
Authors: Heckenbach Indra , Powell Mark , Fuller Sophia , Henry Jill , Rysdyk Sam , Cui Jenny , Teklu Amanuel Abraha , Verdin Eric , Benz Christopher , Scheibye-Knudsen Morten
Published: May 2023

Background

The ability to predict future risk of cancer development in non-malignant biopsies is poor. Cellular senescence has been associated with cancer as either a barrier mechanism restricting autonomous cell proliferation or a tumor-promoting microenvironmental mechanism that secretes pro-inflammatory paracrine factors. With most work done in non-human models and the heterogenous nature of senescence the precise role of senescent cells in the development of cancer in humans is not well understood. Further, more than one million non-malignant breast biopsies are taken every year that could be a major source of risk-stratification for women.

Methods

We applied single cell deep learning senescence predictors based on nuclear morphology to histological images of 4,411 H&E-stained breast biopsies from healthy female donors. Senescence was predicted in the epithelial, stromal, and adipocyte compartments using predictor models trained on cells induced to senescence by ionizing radiation (IR), replicative exhaustion (RS), or antimycin A, Atv/R and doxorubicin (AAD) exposures. To benchmark our senescence-based prediction results we generated 5-year Gail scores, the current clinical gold standard for breast cancer risk prediction.

Findings

We found significant differences in adipocyte-specific IR and AAD senescence prediction for the 86 out of 4,411 healthy women who developed breast cancer an average 4.8 years after study entry. Risk models demonstrated that individuals in the upper median of scores for the adipocyte IR model had a higher risk (OR=1.71 [1.10-2.68], p=0.019), while the adipocyte AAD model revealed a reduced risk (OR=0.57 [0.36-0.88], p=0.013). Individuals with both adipocyte risk factors had an OR of 3.32 ([1.68-7.03], p<0.001). Alone, 5-year Gail scores yielded an OR of 2.70 ([1.22-6.54], p=0.019). When combining Gail scores with our adipocyte AAD risk model, we found that individuals with both of these risk predictors had an OR of 4.70 ([2.29-10.90], p<0.001).

Interpretation

Assessment of senescence with deep learning allows considerable prediction of future cancer risk from non-malignant breast biopsies, something that was previously impossible to do. Furthermore, our results suggest an important role for microscope image-based deep learning models in predicting future cancer development. Such models could be incorporated into current breast cancer risk assessment and screening protocols.

Funding

This study was funded by the Novo Nordisk Foundation (#NNF17OC0027812), and by the National Institutes of Health (NIH) Common Fund SenNet program (U54AG075932).
Modelling NHS 111 demand for primary care services: a discrete event simulation
Authors: Pilbery Richard , Smith Madeleine , Green Jonathan , Chalk Daniel , O’Keeffe Colin
Published: May 2023

Background

Almost half of the 16,650,745 calls to NHS 111 each year are triaged to a primary care disposition. However, there is evidence that contact with a primary care service occurs in less than 50% of cases and triage time frames are frequently not met. This can result in increased utilisation of other healthcare services.

This feasibility study aimed to modelin-silicothe current healthcare system for patients triaged to a primary care disposition and determine the effect of reconfiguring the system to ensure a timely primary care service contact.

Methods

Data from the Connected Yorkshire research database were used to develop a model and Discrete Event Simulation in Python, using the SimPy package. This included all 111 calls made in 2021 by callers registered with a Bradford GP who were triaged to a primary care disposition, and their subsequent healthcare system access during the following 72 hours.

We simulated 100 runs of one year of 111 calls and calculated the mean difference and 95% confidence intervals in primary care contacts, emergency ambulance (999) calls and avoidable ED attendances.

Results

The simulation of the current system estimated that there would be 39,283 (95%CI 39,237–39,328) primary care contacts, 2,042 (95%CI 2,032–2,051) 999 calls and 1,120 (95%CI 1,114–1,127) avoidable ED attendances. Modifying the model to ensure a timely primary care response resulted in a mean increase in primary care contacts of 37,748 (95%CI 37,667–37,829), a mean reduction in 999 calls of -449 (95%CI -461– -436) and a mean reduction in avoidable ED attendance of -26 (95%CI -35– -17).

Conclusion

In this simulated study, ensuring timely contact with a primary care service would lead to a significant reduction in 999 and 111 calls, and ED attendances (although not avoidable ED attendance). However, this is likely to be impractical given the need to almost double current primary care service provision. Further economic and qualitative research is needed to determine whether this intervention would be cost effective and acceptable to both patients and primary care clinicians.
Classification of colon cancer patients into Consensus Molecular Subtypes using Support Vector Machines
Authors: Kochan Necla , Dayanc Barıs Emre
Published: May 2023

Objective

The molecular heterogeneity of colon cancer has made classification of tumors a requirement for effective treatment. One of the approaches for molecular subtyping of colon cancer patients is the Consensus Molecular Subtypes (CMS) developed by the Colorectal Cancer Subtyping Consortium (CRCSC). CMS-specific RNA-Seq dependent classification approaches are recent with relatively low sensitivity and specificity. In this study, we aimed to classify patients into CMS groups using RNA-seq profiles.

Methods

We first identified subtype specific and survival associated genes using Fuzzy C-Means (FCM) algorithm and log-rank test. Then we classified patients using Support Vector Machines with Backward Elimination methodology.

Results

We optimized RNA-seq based classification using 25 genes with minimum classification error rate. Here we report the classification performance using precision, sensitivity, specificity, false discovery rate and balanced accuracy metrics.

Conclusion

We present the gene list for colon cancer classification with minimum classification error rates. We observed the lowest sensitivity but highest specificity with CMS3-associated genes, which is significant due to low number of patients in the clinic for this group.
Rare variants of the glucagon-like peptide-1 receptor (GLP1R) gene are overrepresented in a severe obesity cohort and associated with type 2 diabetes in the UK Biobank
Authors: Handley Dale , Almansoori Sumaya , Sato Mitra S. , Amin Hasnat , Alsters Suzanne , Chahal Harvinder , Purkayastha Sanjay , Murphy Kevin G. , van Haelst Mieke , le Roux Carel W , Tan Tricia , Walters Robin G , Drenos Fotios , Blakemore Alexandra I
Published: May 2023

Introduction

Glucagon-like peptide 1 (GLP1) agonists are highly effective agents for the treatment of obesity and type 2 diabetes (T2D). GLP-1 is also implicated in outcomes of bariatric surgery, including appetite changes and T2D remission. Rare, potentially deleterious mutations in the glucagon-like peptide 1 receptor gene (GLP1R) may, therefore, have important implications for pathogenesis of obesity and T2D, and for response to therapeutic interventions.

Methods

A custom Axion genotyping array, including 117 rare predicted-deleteriousGLP1Rmutations (MAF<0.01 in gnomAD, CADD-PHRED m >= 15), was used to screen 1714 unrelated adults with BMI >35 kg/m2from the PMMO study. We also examined the UK Biobank (UKB) exome sequence dataset for rare, predicted-deleteriousGLP1Rvariants and tested their effects on weight and glycaemia-related traits.

Results

Thirty-four PMMO participants carried one of the 117GLP1Rvariants screened (11 might have been expected using the sum of their gnomAD control MAFs). These 8 variants were associated with T2D in the UKB and subsequent gene-level analysis of the UKB exome sequence dataset (629/39,274 carriers) confirmed that rareGLP1Rvariants are associated with increased risk of T2D (OR=1.58), as well as with higher HbA1c levels (p= 0.039). Furthermore, our data highlight a potential interaction of these variants with body mass index.

Conclusion

Rare, potentially deleteriousGLP1Rmutations is associated with increased T2D risk, as well as higher HbA1c in UKB participants without diabetes. Future studies should examine the implications ofGLP1Rmutations for response to GLP1 agonist treatment and explore the observed interactions with obesity in T2D risk, including in larger cohorts with obesity.
The SENTINEL study of differentiated service delivery models for HIV treatment in Malawi, South Africa, and Zambia: research protocol for a prospective cohort study
Authors: Pascoe Sophie , Huber Amy , Mokhele Idah , Lekodeba Nkgomeleng , Ntjikelane Vinolia , Sande Linda , Tcherini Timothy , Haimbe Prudence , Rosen Sydney ,   the AMBIT SENTINEL study team
Published: May 2023

Background

Many countries in sub-Saharan Africa are rapidly scaling up “differentiated service delivery” (DSD) models for HIV treatment to improve the quality of care, increase access, reduce costs, and support the continued expansion and sustainability of antiretroviral therapy (ART) programs. Although there is some published evidence about the health outcomes of patients in DSD models, little is known about their impacts on healthcare providers’ job satisfaction, patients’ quality of life, costs to providers or patients, or how DSD models affect resource allocation at the facility level.

Methods

SENTINEL is a multi-year observational study that will collect detailed data about DSD models for ART delivery and related services from 12 healthcare facilities in Malawi, 24 in South Africa, and 12 in Zambia. The first round of SENTINEL included a patient survey, provider survey, provider time-and-motion observations, and facility resource use inventory. A survey of clients testing for HIV and a supplement to the facility resource use component to describe service delivery integration will be added for the second round. The patient survey will ask up to 10 patients enrolled in each DSD model at each study site about their experiences in HIV care and in DSD models, costs incurred seeking treatment, and preferences for HIV service delivery. The provider survey will ask up to 10 providers per site about the impact of DSD models on their positions and clinics. The time-and-motion component will directly observe the time use of a sample of providers implementing DSD models. Finally, the resource utilization component will collect facility-level data about DSD model availability and enrollment and the human and other resources needed to implement them. SENTINEL is planned to include four or more approximately annual rounds of data collection between 2021 and 2026.

Discussion

As national DSD programs for HIV treatment mature, it is important to understand how individual healthcare facilities are interpreting and implementing national guidelines and how healthcare workers and clients are adapting to new models of service delivery. SENTINEL will help policy makers and program managers understand the benefits and costs of differentiated service delivery and improve resource allocation going forward.
Imputation Accuracy Across Global Human Populations
Authors: Cahoon Jordan L. , Rui Xinyue , Tang Echo , Simons Christopher , Langie Jalen , Chen Minhui , Lo Ying-Chu , Chiang Charleston W. K.
Published: May 2023

Genotype imputation is now fundamental for genome-wide association studies but lacks fairness due to the underrepresentation of populations with non-European ancestries. The state-of-the-art imputation reference panel released by the Trans-Omics for Precision Medicine (TOPMed) initiative contains a substantial number of admixed African-ancestry and Hispanic/Latino samples to impute these populations with nearly the same accuracy as European-ancestry cohorts. However, imputation for populations primarily residing outside of North America may still fall short in performance due to persisting underrepresentation. To illustrate this point, we curated genome-wide array data from 23 publications published between 2008 to 2021. In total, we imputed over 43k individuals across 123 populations around the world. We identified a number of populations where imputation accuracy paled in comparison to that of European-ancestry populations. For instance, the mean imputation r-squared (Rsq) for 1-5% alleles in Saudi Arabians (N=1061), Vietnamese (N=1264), Thai (N=2435), and Papua New Guineans (N=776) were 0.79, 0.78, 0.76, and 0.62, respectively. In contrast, the mean Rsq ranged from 0.90 to 0.93 for comparable European populations matched in sample size and SNP content. Outside of Africa and Latin America, Rsq appeared to decrease as genetic distances to European reference increased, as predicted. Further analysis using sequencing data as ground truth suggested that imputation software may over-estimate imputation accuracy for non-European populations than European populations, suggesting further disparity between populations. Using 1496 whole genome sequenced individuals from Taiwan Biobank as a reference, we also assessed a strategy to improve imputation for non-European populations with meta-imputation, which can combine results from TOPMed with smaller population-specific reference panels. We found that meta-imputation in this design did not improve Rsq genome-wide. Taken together, our analysis suggests that with the current size of alternative reference panels, meta-imputation alone cannot improve imputation efficacy for underrepresented cohorts and we must ultimately strive to increase diversity and size to promote equity within genetics research.
pH-responsive upconversion mesoporous silica nanospheres for combined multimodal diagnostic imaging and targeted photodynamic and photothermal cancer therapy
Authors: Palanikumar L. , Kalmouni Mona , Houhou Tatiana , Abdullah Osama , Ali Liaqat , Pasricha Renu , Thomas Sneha , Afzal Ahmed J. , Barrera Francisco N. , Magzoub Mazin
Published: May 2023

Photodynamic therapy (PDT) and photothermal therapy (PTT) have garnered considerable interest as non-invasive cancer treatment modalities. However, these approaches remain limited by low solubility, poor stability and inefficient targeting of many common photosensitizers (PSs) and photothermal agents (PTAs). To overcome these limitations, we have designed biocompatible and biodegradable tumor-targeted upconversion nanospheres with imaging capabilities. The multifunctional nanospheres consist of a sodium yttrium fluoride core doped with lanthanides (ytterbium, erbium and gadolinium) and bismuth selenide (NaYF4:Yb/Er/Gd,Bi2Se3) within a mesoporous silica shell that encapsulates a PS, Chlorin e6 (Ce6), in its pores. NaYF4:Yb/Er converts deeply penetrating near-infrared (NIR) light to visible light, which excites the Ce6 to generate cytotoxic reactive oxygen species (ROS), while the PTA Bi2Se3efficiently converts absorbed NIR light to heat. Additionally, Gd enables magnetic resonance imaging (MRI) of the nanospheres. The mesoporous silica shell is coated with lipid/polyethylene glycol (DPPC/cholesterol/DSPE-PEG) to ensure retention of the encapsulated Ce6 and minimize interactions with serum proteins and macrophages that impede tumor targeting. Finally, the coat is functionalized with the acidity-triggered rational membrane (ATRAM) peptide, which promotes specific and efficient internalization into cancer cells within the mildly acidic tumor microenvironment. Following uptake by cancer cellsin vitro, NIR laser irradiation of the nanospheres caused substantial cytotoxicity due to ROS production and hyperthermia. The nanospheres facilitated tumor MRI and thermal imaging, and exhibited potent NIR laser light-induced antitumor effectsin vivovia combined PDT and PTT, with no observable toxicity to healthy tissue, thereby substantially prolonging survival. Our results demonstrate that the ATRAM-functionalized, lipid/PEG-coated upconversion mesoporous silica nanospheres (ALUMSNs) offer multimodal diagnostic imaging and targeted combinatorial cancer therapy.
Extinct and extant termites reveal the fidelity of behavior fossilization in amber
Authors: Mizumoto Nobuaki , Hellemans Simon , Engel Michael S , Bourguignon Thomas , Buček Aleš
Published: May 2023

Fossils encompassing multiple individuals provide rare direct evidence of behavioral interactions among extinct organisms. However, the fossilization process can alter the spatial relationship between individuals and hinder behavioral reconstruction. Here, we report a Baltic amber inclusion preserving a female-male pair of the extinct termite speciesElectrotermes affinis. The head-to-abdomen contact in the fossilized pair resembles the tandem courtship behavior of extant termites, although their parallel body alignment differs from the linear alignment typical of tandem runs. To solve this inconsistency, we simulated the first stage of amber formation, the immobilization of captured organisms, by exposing living termite tandems to sticky surfaces. We found that the posture of the fossilized pair matches trapped tandems and differs from untrapped tandems. Thus, the fossilized pair likely is a tandem running pair, representing the first direct evidence of the mating behavior of extinct termites. Furthermore, by comparing the positions of partners on a sticky surface and in the amber inclusion, we estimated to 67% the probability that the leader role in the fossilized tandem was performed by a male. Our results demonstrate that past behavioral interactions can be reconstructed despite the spatial distortion of body poses during fossilization. Our taphonomic approach clarifies how certain behaviors can be inferred from fossil occurrences.
Synchrony of Bird Migration with Avian Influenza Global Spread; Implications for Vulnerable Bird Orders
Authors: Yang Qiqi , Wang Ben , Lemey Phillipe , Dong Lu , Mu Tong , Wiebe R. Alex , Guo Fengyi , Trovão Nídia Sequeira , Park Sang Woo , Lewis Nicola , Tsui Joseph , Bajaj Sumali , Cheng Yachang , Yang Luojun , Haba Yuki , Li Bingying , Zhang Guogang , Pybus Oliver G. , Tian Huaiyu , Grenfell Bryan
Published: May 2023

Highly pathogenic avian influenza virus (HPAIV) A H5 clade 2.3.4.4 has caused worldwide outbreaks in domestic poultry, occasional spillover to humans, and increasing deaths of diverse species of wild birds since 2014. Wild bird migration is currently acknowledged as an important ecological process contributing to the global dispersal of HPAIV H5. However, it is unclearhow seasonal bird migration facilitates global virus dispersal, andwhich avian species are exposed to HPAI H5 clade 2.3.4.4 viruses and where. To shed light on ongoing global outbreaks, we sought to explore these questions through phylodynamic analyses based on empirical data of bird movement tracking and virus genome sequences. First, based on viral phylogeography and bird migration networks, we demonstrate that seasonal bird migration can explain salient features of the global dispersal of clade 2.3.4.4. Second, we detect synchrony between the seasonality of bird annual cycle phases and virus lineage movements. We reveal the differing vulnerable bird orders at geographical origins and destinations of HPAIV H5 lineage movements. Notably, we highlight the potential importance of relatively under-discussed Suliformes and Ciconiiformes, in addition to Anseriformes and Charadriiformes, in virus lineage movements. Our study provides a phylodynamic framework that links the bird movement ecology and genomic epidemiology of avian influenza; it highlights the importance of integrating bird behaviour and life history in avian influenza studies.
treespat:an R package for spatial tree diversity analysis
Authors: Chianucci F. , Puletti N. , Cesaretti L.
Published: May 2023

Forest structure is a key element in understanding functionality and resilience of forest ecosystems. Analyses of forest structure and diversity have traditionally employed non-spatial measures, due to the simplicity of such approach. However, spatial structure can provide a deeper understanding of tree patterns, but widespread use of a spatially-explicit approach has been often limited by the complexity of theoretical equations and formulas, and the lack of freely distributed tools to calculate such spatial indices. To fill this gap we created the R packagetreespat, which allows to calculate some of the most diffuse stand-level spatial diversity indices. The document describes theory, basic definition and example application for using thetreespatpackage.

Abstract Figure
Uncertainty in the mating strategy causes bias and inaccuracy in estimates of genetic parameters in honeybees
Authors: Kistler Tristan , Brascamp Evert W. , Basso Benjamin , Bijma Piter , Phocas Florence
Published: May 2023

Background

With the increased number of honeybee breeding plans worldwide, records from queens with diversified mating strategies need to be considered. Breeding queens might be inseminated with drones produced by a single drone-producing queen (DPQ), or by a group of sister-DPQs. Often, only the dam of DPQ(s) is reported in the pedigree. Furthermore, datasets might include colony phenotypes from DPQs that were open mated in different locations. Using simulation, we investigated the impact of the mating strategy on estimates of genetic parameters and breeding values, when the DPQs were treated in different ways in the statistical evaluation model. We quantify the bias and standard error of estimates when breeding queens are mated to a single or a group of DPQs, assuming that this information is either known or not. We also investigated two alternative strategies to accommodate phenotypes of open-mated DPQs in the genetic evaluation, adding either a dummy pseudo sire in the pedigree, or a non-genetic effect to the statistical evaluation model to account for the origin of the DPQs’ mates.

Results

When breeding queens were inseminated with semen from drones of a single DPQ and this was known, estimates of genetic parameters and genetic trends were more precise. If they were inseminated using drones from a single or a group of DPQs, and this information was not known, erroneous assumptions led to considerable bias in the estimates. For colony phenotypes of open-mated DPQs, adding a dummy pseudo sire in the pedigree for each mating location led to considerable overestimation of genetic variances, while correcting for the mating area by adding a non-genetic effect in the evaluation model gave unbiased estimates.

Conclusions

Knowing only the dam of the DPQ(s) in the mating may lead to erroneous assumptions on how DPQs were used and cause severe biases in estimates of genetic parameters and genetic trends. Therefore, keeping track in the pedigree of which DPQ(s), and not only which dam of DPQ(s) are used, is recommended. Records from DPQ colonies with queens open mated to a heterogeneous drone population can be integrated by adding non-genetic effects to the statistical evaluation model.
Histopathological Domain Adaptation with Generative Adversarial Networks Bridging the Domain Gap Between Thyroid Cancer Histopathology Datasets
Authors: Dee William , Ibrahim Rana Alaaeldin , Marouli Eirini
Published: May 2023

Deep learning techniques are increasingly being used to classify medical imaging data with high accuracy. Despite this, due to often limited training data, these models can lack sufficient generalizability to predict unseen test data, produced in a different domain, with comparable performance. This study focuses on thyroid histopathology image classification and investigates whether a Generative Adversarial Network (GAN), trained with just 156 patient samples, can produce high quality synthetic images to sufficiently augment training data and improve overall model generalizability. Utilizing a StyleGAN2-ADA approach, the generative network produced images with an FID score of 5.05, matching state-of-the-art GAN results in non-medical domains with comparable dataset sizes. Augmenting the training data with these GAN-generated images increased model generalizability significantly when tested on external data, improving overall accuracy and F1 scores by 36% and 42% respectively. Most importantly, this performance improvement was observed on minority class images, tumour subtypes which are known to suffer from high levels of inter-observer variability when classified by trained pathologists.
Direct mass spectrometry-based detection and antibody sequencing of Monoclonal Gammopathy of Undetermined Significance from patient serum – a case study
Authors: Peng Weiwei , den Boer Maurits A. , Tamara Sem , Mokiem Nadia J. , van der Lans Sjors P.A. , Schulte Douwe , Haas Pieter-Jan , Minnema Monique C. , Rooijakkers Suzan H.M. , van Zuilen Arjan D. , Heck Albert J.R. , Snijder Joost
Published: May 2023

Monoclonal gammopathy of undetermined significance (MGUS) is a plasma cell disorder, characterized by the presence of a predominant monoclonal antibody (i.e., M-protein) in serum, without clinical symptoms. Here we present a case study in which we detect MGUS by liquid-chromatography coupled with mass spectrometry (LC-MS) profiling of IgG1 in human serum. We detected a Fab-glycosylated M-protein and determined the full heavy and light chain sequences by bottom-up proteomics techniques using multiple proteases, further validated by top-down LC-MS. Moreover, the composition and location of the Fab-glycan could be determined in CDR1 of the heavy chain. The outlined approach adds to an expanding mass spectrometry-based toolkit to characterize monoclonal gammopathies such as MGUS and multiple myeloma, with fine molecular detail. The ability to detect monoclonal gammopathies and determine M-protein sequences straight from blood samples by mass spectrometry provides new opportunities to understand the molecular mechanisms of such diseases.
Recovery from anhydrobiosis in the tardigradeParamacrobiotus experimentalis: better to be young than old and in a group than alone
Authors: Nagwani Amit Kumar , Melosik Iwona , Kaczmarek Łukasz , Kmita Hanna
Published: May 2023

Desiccation-tolerant organisms can survive dehydration in a state of anhydrobiosis. Tardigrades can recover from anhydrobiosis at any life stage and are considered among the toughest animals on Earth. However, the factors that influence recovery from anhydrobiosis are not well understood. The study aimed to evaluate the effect of sex, age, the presence of other individuals and the combination of the number and duration of anhydrobiosis episodes on the recovery ofParamacrobiotus experimentalis. The activity of 1,200 individuals for up to 48 hours after rehydration was evaluated using ANOVA. Age was the main factor influencing return to activity, followed by the combination of number and duration of anhydrobiosis episodes, influence of the presence of other individuals, and sex. More individuals returned to activity after repeated short than repeated long anhydrobiosis episodes and older individuals were less likely to recover than younger individuals. In addition, when compared to single animals, the presence of other individuals resulted in higher number of active animals after dehydration and rehydration. The effect of sex was significant, but there was no general tendency for one sex to recover from anhydrobiosis better than the other one. The results contribute to a better understanding of the anhydrobiosis ability ofPam. experimentalisand provide background for full explanation of molecular, cellular and environmental mechanisms of anhydrobiosis.
Estimating recent and historical effective population size of marine and freshwater sticklebacks
Authors: Feng Xueyun , Löytynoja Ari , Merilä Juha
Published: May 2023

Effective population size (Ne) is a quantity of central importance in evolutionary biology and population genetics, but often notoriously challenging to estimate. Analyses ofNeare further complicated by the many interpretations of the concept and the alternative approaches to quantifyNeutilising widely different properties of the data. On the other hand, alternative methods are informative for different time scales such that a set of complementary methods should allow piecing together the entire continuum ofNefrom a few generations before the present to the distant past. To test this in practice, we inferred the continuum ofNefor 45 nine-spined stickleback populations (Pungitius pungitius) using whole-genome data. We found that the marine populations had the largest historical and recentNe, followed by coastal and other freshwater populations. We identified the impact of both recent and historical gene flow on theNeestimates obtained from different methods and found that simple summary statistics are informative in comprehending the events in the very recent past. Overall, our analyses showed that the coalescence-based trajectories ofNein the recent past and the LD-based estimates of near-contemporaryNeare incongruent, though in some cases the incongruence might be explained by specific demographic events. Despite still lacking accuracy and resolution for the very recent past, the sequentially Markovian coalescent-based methods seem to provide the most meaningful interpretation of the real-lifeNevarying across time.
Coevolution increases robustness to extinctions in mutualistic but not antagonistic communities
Authors: Pedraza Fernando , Gawecka Klementyna A. , Bascompte Jordi
Published: May 2023

Co-extinctions may exacerbate the current biodiversity crisis. Yet, we do not understand all the factors that shape the robustness of communities to the loss of species. Here we analyse how coevolution influences the robustness of mutualistic and antagonistic communities. We find that coevolution increases robustness in mutualism but reduces it in antagonism. These differences are due to coevolution altering the density of interactions in communities. The largest changes to robustness occur when coevolutionary selection is strong. Yet, the effect size of coevolution on robustness depends on the size of the community. Our results may broaden the suite of mechanisms affecting the resilience of ecological communities. These insights may inform efforts to reduce the risk of species loss in the face of global change.
HOIL1 regulates group 3 innate lymphoid cell numbers in the colon and protects against systemic dissemination, colonic ulceration, and lethality fromCitrobacter rodentiuminfection
Authors: Hartley Victoria L. , Qaqish Arwa M. , Wood Matthew J. , Studnicka Brian T. , Iwai Kazuhiro , Liu Ta-Chiang , MacDuff Donna A.
Published: May 2023

HOIL1-deficient patients experience chronic intestinal inflammation and diarrhea as well as increased susceptibility to certain bacterial infections. HOIL1 is a component of the linear ubiquitin chain assembly complex (LUBAC) that regulates immune signaling pathways including NF-κB-activating pathways. We have shown previously that HOIL1 is essential for survival followingCitrobacter rodentiumgastrointestinal infection of mice, but the mechanism of protection by HOIL1 was not examined.C. rodentiumis a murine model for human attaching and effacing (A/E) pathogens, enteropathogenic and enterohemorrhagicEscherichia coli,that cause diarrhea and food-borne illnesses, and lead to severe disease in children and immunocompromised individuals. In this study, we found thatC. rodentiuminfection caused severe colitis and dissemination ofC. rodentiumto systemic organs inHoil1-/-mice. HOIL1 was important in radiation-resistant cells and in the innate immune response to limit early replication ofC. rodentiumin the intestine, and to modulate induction of inflammatory cytokines. Using cell type-specific knock-out mice, we found that HOIL1 was dispensable in intestinal epithelial cells (IEC), but was required in CD11c- and lysozyme 2-expressing myeloid cells to prevent weight loss and systemic dissemination ofC. rodentium. While HOIL1-deficiency did not affect populations of neutrophils or macrophages, dendritic cells and group 3 innate lymphoid cell (ILC3) numbers were reduced, resulting in a defect in IL-22 induction duringC. rodentiuminfection. Understanding the role HOIL1 plays in limiting the pathogenesis of A/E lesion-forming bacteria will provide further insights into the innate immune response to gastrointestinal pathogens and inflammatory disorders.
Ethnopharmacological disease classification and bioprospecting: the diversity of plant drugs used to treat cancer
Authors: Thompson Jamie , Hawkins Julie
Published: May 2023

Cancer is a highly-diverse disease and as the second-leading cause of death worldwide is a focus of drug discovery research. Natural products have been shown to be a useful source of novel molecules for the treatment of cancer. It is likely there are many plants with undiscovered molecules of therapeutic value, however identifying new leads from among the vast diversity of plants is very challenging. Traditional knowledge might inform bioprospecting by predicting lineages of plants rich in therapeutically useful molecules. Here, we characterise the phylogenetic diversity of plants used traditionally to manage cancer. We demonstrate the independent and repeated targeting of specific lineages of plants by different peoples in different parts of the world. That the same lineages are used to treat different cancers is suggestive of independent discovery of therapeutic value. However, the lineages we report here as rich in plants used traditionally to treat cancer coincide with those for other ethnobotanical applications, and contain few plants with proven anti-cancer activity. It is likely that the traditional knowledge recorded and explored here is shaped by selection of plants conferring milder effects for treating wider symptoms, such as tiredness or nausea, rather than for halting tumour growth. Accurate prediction of useful plant lineages for cancer management requires more nuanced information than is commonly provided in ethnobotanical records.
Long-read genome assemblies for the study of chromosome expansion:Drosophila kikkawai,Drosophila takahashii,Drosophila bipectinata, andDrosophila ananassae
Authors: Leung Wilson , Torosin Nicole , Cao Weihuan , Reed Laura K , Arrigo Cindy , Elgin C R Sarah , Ellison Christopher E
Published: May 2023

Flow cytometry estimates of genome sizes among species ofDrosophilashow a 3-fold variation, ranging from ∼127 Mb inDrosophila mercatorumto ∼400 Mb inDrosophila cyrtoloma. However, the assembled portion of the Muller F Element (orthologous to the fourth chromosome inDrosophila melanogaster) shows a nearly 14-fold variation in size, ranging from ∼1.3 Mb to > 18 Mb. Here, we present chromosome-level long read genome assemblies for fourDrosophilaspecies with expanded F Elements ranging in size from 2.3 Mb to 20.5 Mb. Each Muller Element is present as a single scaffold in each assembly. These assemblies will enable new insights into the evolutionary causes and consequences of chromosome size expansion.
Biochemical Pathways Represented by Gene Ontology Causal Activity Models Identify Distinct Phenotypes Resulting from Mutations in Pathways
Authors: Hill David P , Drabkin Harold J , Smith Cynthia L , Van Auken Kimberly M , D’Eustachio Peter
Published: May 2023

Gene inactivation can affect the process(es) in which that gene acts and causally downstream ones, yielding diverse mutant phenotypes. Identifying the genetic pathways resulting in a given phenotype helps us understand how individual genes interact in a functional network. Computable representations of biological pathways include detailed process descriptions in the Reactome Knowledgebase, and causal activity flows between molecular functions in Gene Ontology-Causal Activity Models (GO-CAMs). A computational process has been developed to convert Reactome pathways to GO-CAMs. Laboratory mice are widely used models of normal and pathological human processes. We have converted human Reactome GO-CAMs to orthologous mouse GO-CAMs, as a resource to transfer pathway knowledge between humans and model organisms. These mouse GO-CAMs allowed us to define sets of genes that function in a causally connected way. To demonstrate that individual variant genes from connected pathways result in similar but distinguishable phenotypes, we used the genes in our pathway models to cross-query mouse phenotype annotations in the Mouse Genome Database (MGD). Using GO-CAM representations of two related but distinct pathways, gluconeogenesis and glycolysis, we show that individual causal paths in gene networks give rise to discrete phenotypic outcomes resulting from perturbations of glycolytic and gluconeogenic genes. The accurate and detailed descriptions of gene interactions recovered in this analysis of well-studied processes suggest that this strategy can be applied to less well-understood processes in less well-studied model systems to predict phenotypic outcomes of novel gene variants and to identify potential gene targets in altered processes.

Genes act in interconnected biological pathways, so single mutations can yield diverse phenotypes. To use the large body of mouse functional gene annotations, we converted human Gene Ontology-Causal Activity Models (GO-CAMs) of glucose metabolism to orthologous mouse GO-CAMs. We then queried phenotypes for mouse genes in these GO-CAMs and identified gene networks associated with discrete phenotypic outcomes due to perturbations of glycolysis and gluconeogenesis. This strategy can be extended to less well-understood processes and model systems to predict phenotypic outcomes.
High-throughput phenotyping of single nucleotide variants by linking transcriptomes to genotypes in single cells
Authors: Cooper Sarah E. , Coelho Matthew A. , Strauss Magdalena E. , Gontarczyk Aleksander M. , Wu Qianxin , Garnett Mathew J. , Marioni John C. , Bassett Andrew R.
Published: May 2023

CRISPR screens with single-cell transcriptomic readouts are a valuable tool to understand the effect of genetic perturbations, but are currently limited because genotypes are inferred from the guide RNA identity. We have developed a technique that couples single-cell genotyping to transcriptomics of the same cells to enable screening for the effects of single nucleotide variants. Analysis of variants tiling across theJAK1gene demonstrates the importance of determining the precise genetic perturbation and classifies missense variants into three functional categories.
Genetic evidence for functions of Chloroplast CA inPyropia yezoensis: decreased CCM but increased starch accumulation
Authors: Zhang Baoyu , Liu Xueying , Xie Xiujun , Huan Li , Wang Hong , Shao Zhizhuo , Wang Guangce
Published: May 2023

To adapt to the change of intertidal environment, intertidal macroalgae have evolved complicated Ci utilization mechanism. However, our knowledge regarding the CO2 concentrating mechanism (CCM) of macroalgae is limited. Carbonic anhydrase (CA), a key component of CCM, plays important roles in many physiological reactions in various organisms. While there are a large number of genes encoding CA in the Pyropia yezoensis genome, the exact function of specific CA in P. yezoensis remains elusive. To explore the specific function of chloroplast CA in intertidal macroalgae, we produced chloroplast-localized βCA1 knockdown mutants of P. yezoensis through RNA interference, and Pyca1i mutants showed a notable decrease in leaf area and overall biomass, as well as decreased soluble protein and unsaturated fatty acid content under different DIC conditions. However, Pyca1i mutants showed relatively higher starch content compared to the wild-type. The activity of enzymes involved in Calvin cycle, photorespiration, Pentose-phosphate pathway and floridean starch synthesis of P.yezoensis indicated an effective starch accumulation pathway after interference of βCA1. All results suggest that the decreased activity of PyβCA1 impaired the CCM and development of thalli of P.yezoensis, but stimulated starch accumulation in the cytoplasm through feedback to the photorespiration pathway and PP pathway to replenish intermediates for the Calvin cycle. This study is the first to explore the specific function of chloroplast CA in intertidal macroalgae using genomic technology. The results provide valuable insights into the adaption mechanisms of intertidal macroalgae to their environment.
COATi: statistical pairwise alignment of protein-coding sequences
Authors: García Mesa Juan J. , Zhu Ziqi , Cartwright Reed A.
Published: May 2023

Sequence alignment is an essential method in bioinformatics and the basis of many analyses, including phylogenetic inference, ancestral sequence reconstruction, and gene annotation. Sequence artifacts and errors made during alignment reconstruction can impact downstream analyses leading to erroneous conclusions in comparative and functional genomic studies. For example, abiological frameshifts and early stop codons are common artifacts found in protein coding sequences that have been annotated in reference genomes. While such errors are eventually fixed in the reference genomes of model organisms, many genomes used by researchers contain these artifacts, and researchers often discard large amounts of data in comparative genomic studies to prevent artifacts from impacting results. To address this need, we present COATi, a statistical, codon-aware pairwise aligner that supports complex insertion-deletion models and can handle artifacts present in genomic data. COATi allows users to reduce the amount of discarded data while generating more accurate sequence alignments.
Wired together, change together: Spike timing modifies transmission in converging assemblies
Authors: Spivak Lidor , Someck Shirly , Levi Amir , Sivroni Shir , Stark Eran
Published: May 2023

Precise timing of neuronal spikes may lead to changes in synaptic connectivity and is thought to be crucial for learning and memory. However, the effect of spike timing on neuronal connectivity in the intact brain remains unknown. Using closed-loop optogenetic stimulation in CA1 of freely-moving mice, we generated new spike patterns between presynaptic pyramidal cells (PYRs) and postsynaptic parvalbumin-immunoreactive (PV) cells. This stimulation led to spike transmission changes which occurred together across all presynaptic PYRs connected to the same postsynaptic PV cell. The precise timing of all presynaptic and postsynaptic cells spikes impacted transmission changes. These findings reveal an unexpected plasticity mechanism, wherein spike timing of a whole cell assembly has a more substantial impact on effective connectivity than that of individual cell pairs.
Improving malaria case management with artemisinin-based combination therapies and malaria rapid diagnostic tests in private medicine retail outlets in sub-Saharan Africa: a systematic review
Authors: Goodman Catherine , Tougher Sarah , Shang Terrissa Jing , Visser Theodoor
Published: May 2023

Private medicine retailers (PMRs) such as pharmacies and drug stores account for a substantial share of treatment-seeking for fever and malaria, but there are widespread concerns about quality of care, including inadequate access to malaria rapid diagnostic tests (RDTs) and artemisinin-based combination therapies (ACTs). This review synthesizes evidence on the effectiveness of interventions to improve malaria case management in PMRs in sub-Saharan Africa (PROSPERO #2021:CRD42021253564). We included quantitative studies evaluating interventions supporting RDT and/or ACT sales by PMR staff, with a historical or contemporaneous control group, and outcomes related to care received. We searched Medline Ovid, Embase Ovid, Global Health Ovid, Econlit Ovid and the Cochrane Library; unpublished studies were identified by contacting key informants. We conducted a narrative synthesis by intervention category. We included 41 papers, relating to 34 studies. There was strong evidence that small and large-scale ACT subsidy programmes (without RDTs) increased the market share of quality-assured ACT in PMRs, including among rural and poorer groups, with increases of over 30 percentage points in most settings. Interventions to introduce or enhance RDT use in PMRs led to RDT uptake among febrile clients of over two-thirds and dispensing according to RDT result of over three quarters, though some studies had much poorer results. Introducing Integrated Community Case Management (iCCM) was also effective in improving malaria case management. However, there were no eligible studies on RDT or iCCM implementation at large scale. There was limited evidence that PMR accreditation (without RDTs) increased ACT uptake. Key evidence gaps include evaluations of RDTs and iCCM at large scale, evaluations of interventions including use of digital technologies, and robust studies of accreditation and other broader PMR interventions.