bluuebunny/crossref_metadata_2025 huggingface dataset:
Population estimates of shorebirds on the Atlantic Coast of southern South America generated from large-scale, simultaneous, volunteer-led surveys
Authors: Faria Fernando A. , Aldabe Joaquín , Almeida Juliana B. , Bonanno Juan J. , Bugoni Leandro , Clay Robert , Garcia-Walther Julian , González Agustina M. , Lesterhuis Arne , Nunes Guilherme T. , Senner Nathan R.
Published: March 2024

Population abundance and trend estimates are crucial to science, management, and conservation. Shorebirds, which are abundant in many coastal habitats and play important roles in coastal ecosystems, are facing some of the most dramatic population declines of any group of birds globally. However, accurate and up-to-date population estimates are lacking for most shorebird species. We thus conducted comprehensive, simultaneous, and community scientist-led surveys of the entire Atlantic Coast of southern South America — stretching from central Brazil to Tierra del Fuego — to gather counts of shorebirds that we combined with remote sensing analyses and two-step hurdle models that accounted for presence and abundance. Our objectives were to estimate shorebird densities by habitat, identify high-concentration areas, understand the environmental factors affecting their distributions, and provide population estimates for both Nearctic and Neotropical species. We counted a total of 37,207 shorebirds of 17 species and, from those counts, estimated that nearly 1.1 million shorebirds use the region’s coastline. We also found that shorebirds occurred in the highest densities in shallow water wetland habitats and that fewer shorebirds occupied areas that were further away from estuaries. Although not directly comparable, our results suggest the population sizes of the Nearctic species whose nonbreeding ranges are predominantly in southern South America may have declined substantially since previous estimates. At the same time, our study represents the first empirically derived population estimates for Neotropical breeding shorebird species and indicates that they are far more abundant than previously thought. Taken together, our results highlight the power of community scientists to carry out structured protocols at continental scales and generate critical data for a group of at-risk species.
Longitudinal Analysis Over Decades Reveals the Development and Immune Implications of Type I Interferon Autoantibodies in an Aging Population
Authors: Fernbach Sonja , Mair Nina K. , Abela Irene A. , Groen Kevin , Kuratli Roger , Lork Marie , Thorball Christian W. , Bernasconi Enos , Filippidis Paraskevas , Leuzinger Karoline , Notter Julia , Rauch Andri , Hirsch Hans H. , Huber Michael , Günthard Huldrych F. , Fellay Jacques , Kouyos Roger D. , Hale Benjamin G. ,   The Swiss HIV Cohort Study
Published: March 2024

Pre-existing autoantibodies (autoAbs) neutralizing type I interferons (IFN-Is: IFNα, IFNβ, IFNω) have recently been described as significant contributors to the severity of viral infectious diseases. Here, we explore the development and consequences of anti-IFN-I autoAbs at high-resolution using retrospective samples and data from 1876 well-treated individuals >65 years of age enrolled in the Swiss HIV Cohort Study, a nationwide, longitudinal cohort with up to 35 years of follow-up. Approximately 1.9% of individuals developed anti-IFN-I autoAbs, with a median onset age of ∼63 years (range 45-80). Once developed, anti-IFN-I autoAbs persisted for life, and generally increased in titer over years. Most individuals developed distinct neutralizing and non-neutralizing anti-IFN-I autoAb repertoires at discrete times that selectively targeted various combinations of IFNα, IFNβ, and IFNω. Longitudinal analyses further revealed that emergence of neutralizing anti-IFNα autoAbs correlated with reduced IFN-stimulated gene (ISG) levels, indicating impairment of innate immunity. Patient data review suggested that prior recorded viral infections and autoimmune history influence the likelihood of mounting anti-IFN-I autoAbs. Indeed, systematic measurements in biobanked samples revealed significant enrichment of pre-existing autoreactivity against clinically relevant autoantigens in individuals who later developed anti-IFN-I autoAbs. In this context, we describe lifelong neutralizing anti-IFNα autoAbs (and impaired innate immunity), that manifested in an individual following IFNα therapy, and who was retrospectively found to have had pre-existing autoreactivity to β2-glycoprotein-I before IFNα treatment. Our decades-spanning longitudinal analyses illuminate the development and immune implications of anti-IFN-I autoAbs in an aging population, and support a ‘two-hit’ hypothesis whereby loss of self-tolerance prior to immune-triggering with endogenous or exogenous IFN-I may pose a risk for developing late-onset, lifelong IFN-I functional deficiency.
Identification of an evolutionary conserved binding motif responsible for the recruitment of NMD factors to the UPF1 helicase
Authors: Barbarin-Bocahu Irène , Ulryck Nathalie , Rigobert Amandine , Ruiz Gutierrez Nadia , Decourty Laurence , Raji Mouna , Garkhal Bhumika , Le Hir Hervé , Saveanu Cosmin , Graille Marc
Published: March 2024

The nonsense-mediated mRNA decay (NMD) pathway clears eukaryotic cells of mRNAs containing premature termination codons (PTC) or normal stop codons located in specific contexts. It therefore plays an important role in gene expression regulation. The precise molecular mechanism of the NMD pathway has long been considered to differ substantially from yeast to metazoa, despite the involvement of universally conserved factors such as the central ATP-dependent RNA-helicase Upf1. Here we describe the crystal structure of the yeast Upf1 bound to its recently identified but yet uncharacterized partner Nmd4, show that Nmd4 stimulates Upf1 ATPase activity and that this interaction contributes to the elimination of NMD substrates. We also demonstrate that a region of Nmd4 critical for the interaction with Upf1 in yeast is conserved in the metazoan SMG6 protein, another major NMD factor. We show that this conserved region is involved in the interaction of SMG6 with UPF1, and that mutations in this region affect the levels of endogenous human NMD substrates. Our results support the universal conservation of the NMD mechanism in eukaryotes.
PopGenPlayground:a population genomics analysis pipeline
Authors: Wolfsberger Walter W. , Shchubelka Khrystyna , Oleksyk Olga T. , Hasynets Yaroslava , Patskun Silvia , Vakerych Mykhailo , Kish Roman , Mirutenko Violeta , Mirutenko Vladislav , Cotoraci Coralia Adina , Pop Calin , Neagu Olimpia , Baltă Cornel , Herman Hildegard , Mare Paula , Dumitra Simona , Papiu Horatiu , Hermenean Anca , Oleksyk Taras K.
Published: March 2024

Background

Population genomic projects are essential in the current drive to map the genome diversity of human populations across the globe. Various barriers persist hindering these efforts, and the lack of bioinformatic expertise and reproducible standardized population-scale analysis is one of the major challenges limiting their discovery potential. Scalable, automated, user-friendly pipelines can help researchers with minimum programming skills to tackle these issues without extensive training.

Results

PopGenPlayground(PGP), is a streamlined, single-command computation pipeline designed for human population genomics analysis based onSnakemakeworkflow management system. Developed to automate secondary analysis of a previously published national genome project, it leverages the publicly available genomic databases for comparative analysis and annotation of variant calls.

Conclusions

PGP presents a multi-platform robust population analysis pipeline, that reduces the time and the expertise levels to perform the main core of population analysis for a national genome project. PGP provides a comprehensive secondary analysis tool and can be used to perform analysis on a personal computer or using a remote high-performance computing platform.
Characterization and Organization of Telomeric-Linked Helicase (TLH) Gene Families inFusarium oxysporum
Authors: Salimi Sahar , Abdi M. Foad , Rahnama Mostafa
Published: March 2024

Telomere-linked RecQ helicase (TLH) genes have been reported in several fungi and a choanoflagellate in the regions adjacent to the terminal telomere repeats. In this study, we explore the Telomere-linked RecQ helicase (TLH) genes in four strains ofFusarium oxysporum, offering new insights into their genomic structure, functional motifs, and impact on chromosomal ends. We conducted a comprehensive analysis, comparing the TLH genes ofF. oxysporumwith those previously identified in other organisms and uncovering significant similarities. Through comparative genomics, we identified conserved protein motifs across these genes, including a TLH domain, C2H2, and RecQ helicase motifs. Our phylogenetic analysis positions theF. oxysporumTLH genes in a cluster with other known TLHs, suggesting a shared evolutionary origin. Mutation analysis revealed a relatively low level of deleterious mutations in TLH gene paralogs, with a notable proportion of full-size structures maintained across strains. Analysis of subtelomeric sequences indicates that a region with almost identical sequences flanks the majority of chromosome ends, termed TLH-containing region (TLHcr), across these strains. The presence of TLHcrs at chromosome ends, either as single entities or in arrays, underscores their potential role in telomere function and genome stability. Our findings provide a detailed examination of TLH genes in four strains ofF. oxysporum, laying the groundwork for future studies on their biological significance and evolutionary history in fungal genomes.
Changes in Walking Function and Neural Control following Pelvic Cancer Surgery with Reconstruction
Authors: Li Geng , Ao Di , Vega Marleny M. , Zandiyeh Payam , Chang Shuo-Hsiu , Penny A.N. , Lewis Valerae O. , Fregly Benjamin J.
Published: March 2024

Surgical planning and custom prosthesis design for pelvic cancer patients is challenging due to the unique clinical characteristics of each patient and the significant amount of pelvic bone and hip musculature often removed. Limb-sparing internal hemipelvectomy surgery with custom prosthesis reconstruction has become a viable option for this patient population. However, little is known about how post-surgery walking function and neural control change from pre-surgery conditions. This case study combined comprehensive human movement data collection with personalized neuromusculoskeletal computer modeling to provide a thorough assessment of pre-to post-surgery changes in walking function and neural control for a single pelvic sarcoma patient who received internal hemipelvectomy surgery with custom prosthesis reconstruction. Extensive walking data (video motion capture, ground reaction, and EMG) were collected from the patient before surgery and after plateau in recovery after surgery. Pre- and post-surgery personalized neuromusculoskeletal computer models of the patient were then constructed using the patient’s pre- and post-surgery walking data. These models were used to calculate the patient’s pre- and post-surgery joint motions, joint moments, and muscle synergies. The calculated muscle synergies were described by time-invariant synergy vectors and time-varying synergy activations, were consistent with the patient’s experimental EMG data, and produced the patient’s experimental joint moments found via inverse dynamics. The patient’s post-surgery walking function was marked by a slower self-selected walking speed coupled with several compensatory mechanisms necessitated by lost or impaired hip muscle function, while the patient’s post-surgery neural control demonstrated a dramatic change in coordination strategy (as evidenced by modified synergy vectors) with little change in recruitment timing (as evidenced by conserved synergy activations). Furthermore, the patient’s post-surgery muscle activations were fitted accurately using the patient’s pre-surgery synergy activations but poorly using the patient’s pre-surgery synergy vectors. These results provide valuable information about which aspects of post-surgery walking function could potentially be improved through modifications to surgical decisions, custom prosthesis design, or rehabilitation protocol, as well as how computational simulations could be formulated to predict post-surgery walking function reliably given a patient’s pre-surgery walking data and the planned surgical decisions and custom prosthesis design.
Can AI-generated clinical vignettes in Japanese be used medically and linguistically?
Authors: Yanagita Yasutaka , Yokokawa Daiki , Uchida Shun , Li Yu , Uehara Takanori , Ikusaka Masatomi
Published: March 2024

Background

Creating clinical vignettes requires considerable effort. Recent developments in generative artificial intelligence (AI) for natural language processing have been remarkable and may allow for the easy and immediate creation of diverse clinical vignettes.

Objective

In this study, we evaluated the medical accuracy and grammatical correctness of AI-generated clinical vignettes in Japanese and verified their usefulness.

Methods

Clinical vignettes in Japanese were created using the generative AI model GPT-4-0613. The input prompts for the clinical vignettes specified the following seven elements: 1) age, 2) sex, 3) chief complaint and time course since onset, 4) physical findings, 5) examination results, 6) diagnosis, and 7) treatment course. The list of diseases integrated into the vignettes was based on 202 cases considered in the management of diseases and symptoms in Japan’s Primary Care Physicians Training Program. The clinical vignettes were evaluated for medical and Japanese-language accuracy by three physicians using a five-point scale. A total score of 13 points or above was defined as “sufficiently beneficial and immediately usable with minor revisions,” a score between 10 and 12 points was defined as “partly insufficient and in need of modifications,” and a score of 9 points or below was defined as “insufficient.”

Results

Regarding medical accuracy, of the 202 clinical vignettes, 118 scored 13 points or above, 78 scored between 10 and 12 points, and 6 scored 9 points or below. Regarding Japanese-language accuracy, 142 vignettes scored 13 points or above, 56 scored between 10 and 12 points, and 4 scored 9 points or below. Overall, 97% (196/202) of vignettes available with some modifications.

Conclusions

Overall, 97% of the clinical vignettes proved practically useful, based on confirmation and revision by Japanese medical physicians. Given the significant effort required by physicians to create vignettes without AI assistance, the use of GPT is expected to greatly optimize this process.
Establishing the Automatic Identification of Clinical Trial Cohorts from Electronic Health Records by Matching Normalized Eligibility Criteria and Patient Clinical Characteristics
Authors: Lee K. , Mai Y. , Liu Z. , Raja K. , Jun T. , Ma M. , Wang T. , Ai L. , Calay E. , Oh W. , Schadt E. , Wang X.
Published: March 2024

The use of electronic health records (EHRs) holds the potential to enhance clinical trial activities. However, the identification of eligible patients within EHRs presents considerable challenges. We aimed to develop a pipeline for phenotyping eligibility criteria, enabling the identification of patients from EHRs with clinical characteristics that match those criteria. We utilized clinical trial eligibility criteria and patient EHRs from the Mount Sinai Database. The criteria and EHR data were normalized using national standard terminologies and in-house databases, facilitating computability and queryability. The pipeline employed rule-based pattern recognition and manual annotation. Our pipeline normalized 367 out of 640 unique eligibility criteria attributes, covering various medical conditions including non-small cell lung cancer, small cell lung cancer, prostate cancer, breast cancer, multiple myeloma, ulcerative colitis, Crohn’s disease, non-alcoholic steatohepatitis, and sickle cell anemia. 174 were encoded with standard terminologies and 193 were normalized using the in-house reference tables. The agreement between automated and manual normalization was high (Cohen’s Kappa = 0.82), and patient matching demonstrated a 0.94 F1 score. Our system has proven effective on EHRs from multiple institutions, showing broad applicability and promising improved clinical trial processes, leading to better patient selection, and enhanced clinical research outcomes.
Identification of Novel Gene variants for Autism Spectrum Disorder in an Indian Patient using Whole Exome Sequencing
Authors: Yadav Prashasti , Roychowdhury Saileyee , Mukherjee Nilanjan , Mukherjee Reema , Roy Sudipta Kumar , Bhattacharjee Soumen , Das Parimal
Published: March 2024

Background

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent deficits in social communication and interaction, along with restricted and repetitive behaviour patterns, interests or activities. Its prevalence has risen over the past few years, being four times more common in boys than girls. The cause of ASD is unclear, its etiology involves genetic, environmental, and gene-environment interactions. While past studies highlighted clinical genetic risks, genetic complexity of ASD, with variants of diverse frequencies, type, and inheritance patterns, requires further exploration for better management of disease. Researches have shown that the whole exome sequencing can be used to identify genetic variants associated with genetically heterogeneous conditions. The purpose of this study is to identify genetic variants by employing whole exome sequencing in an Indian ASD patient.

Methods

A female patient of age within 0-5 years, having characteristic features like hyperactivity and language impairment, was investigated and diagnosed using DSM-5 criteria. Peripheral blood sample collection was done followed by DNA extraction and whole exome sequencing. Variants analysis, identification and annotation were done using bioinformatics tools and databases. Identified pathogenic variants were reconfirmed by Sanger sequencing.

Results and conclusion

Our study uncover four genetic variations, comprising three missense variations inKIF1A(c.3839C>T),SETD5(c.314A>C),MAPK81P3(c.2849C>T), and one-stop gain variation inERMARD(c.1523G>A). TheERMARDstop gain variation, predicted to induce nonsense-mediated decay, alter normal protein function through truncation and classified as likely pathogenic based on the ACMG guidelines and current available scientific evidence. In conclusion, we identified a likely pathogenic variant inERMARDalong with three missense variants inKIF1A, SETD5andMAPK81P3respectively. These findings suggest the potential contribution ofERMARDmutations to ASD susceptibility, emphasizing the need for further validation through functional studies.
Multiplex single-cell analysis of serotonergic neuron function in planarians reveals widespread effects in diverse cell types
Authors: Emili Elena , Rodríguez-Fernández Dianalí , Pérez-Posada Alberto , García-Castro Helena , Solana Jordi
Published: March 2024

Neurons function by interacting with each other and with other cell types, often exerting organism-wide regulation. Serotonergic neurons play a systemic role in processes such as appetite, sleep and motor control. Functional studies in the planarianSchmidtea mediterraneahave shown that impairment of serotonergic neurons results in systemic effects. Studying neurons and the tissues they interact with is challenging using either bulk or single-cell analysis techniques. While bulk methods merge the information from all cell types, single-cell methods show promise in overcoming this limitation. However, current single-cell approaches encounter other challenges including stress of cell dissociation, high cost, multiplexing capacity, batch effects, replication and statistical analysis. Here we used ACME and SPLiT-seq to generate a multiplex single-cell analysis of serotonergic neuron function in planarians by inhibitingpitxandlhx1/5-1, two transcription factors expressed in them. We recovered single-cell transcriptomic profiles of 47,292 cells from knockdown and control animals, including biological and technical replicates. Our results show that epidermal, muscular and the recently described parenchymal cell types are affected the most by serotonergic neuron impairment. By computationally dissecting each cell type, we elucidated gene expression changes in each, including changes in epidermis cilia genes and myofiber genes in muscle. Interestingly, parenchymal cells downregulate genes involved in neurotransmitter recycling, suggesting a glial-like function of these recently described enigmatic cell types. Our results will allow disentangling the complexity of serotonergic neuron inhibition by studying the downstream effectors and the affected tissues, and offer new data on the function of parenchymal cells in planarians. Ultimately, our results pave the way for dissecting complex phenotypes through multiplex single-cell transcriptomics.
Learning-Based Estimation of Fitness Landscape Ruggedness for Directed Evolution
Authors: Towers Sebastian , James Jessica , Steel Harrison , Kempf Idris
Published: March 2024

Directed evolution is a method for engineering biological systems or components, such as proteins, wherein desired traits are optimised through iterative rounds of mutagenesis and selection of fit variants. The process of protein directed evolution can be envisaged as navigation over high-dimensional landscapes with numerous local maxima, mapping every possible variant of a protein to its fitness. The performance of any strategy in navigating such a landscape is dependent on several parameters, including its ruggedness. However, this information is generally unavailable at the outset of an experiment, and cannot be computed using analytical methods. Here we propose a learning-based method for estimating landscape ruggedness from a mutating population, using only population average performance data. This method uses a short period of exploration at the beginning of an experiment to predict the ruggedness, subsequently guiding the choice of high-performing parameters for directed evolution control. We then simulate this approach on two real-world protein fitness landscapes, demonstrating an improvement upon the performance of standard strategies, particularly on rugged landscapes. In addition to improving the overall outcomes of directed evolution, this method has the advantage of being readily deployable in laboratory settings, even in configurations that exclusively capture average population measures. Given the rapidly expanding application space of engineered proteins, the products of improved directed evolution are relevant in medicine, agriculture and manufacturing.
A novel tomato inter-specific (Solanum lycopersicumvar.cerasiformeandS. pimpinellifolium) MAGIC population facilitates trait association and candidate gene discovery in untapped exotic germplasm
Authors: Arrones Andrea , Antar Oussama , Pereira-Dias Leandro , Solana Andrea , Ferrante Paola , Aprea Giuseppe , Plazas Mariola , Prohens Jaime , Díez María José , Giuliano Giovanni , Gramazio Pietro , Vilanova Santiago
Published: March 2024

We developed a novel eight-way tomato multi-parental advanced generation inter-cross (MAGIC) population to improve the accessibility of the genetic resources of tomato relatives to geneticists and breeders. The inter-specific MAGIC population (ToMAGIC) was obtained by inter-crossing four accessions each ofSolanum lycopersicumvar.cerasiforme(SLC) andS. pimpinellifolium(SP), which respectively are the weedy relative and the ancestor of cultivated tomato. The eight exotic ToMAGIC founders were selected based on a representation of the genetic diversity and geographical distribution of the two taxa. The resulting MAGIC population comprises 354 lines which were genotyped using a new 12k tomato Single Primer Enrichment Technology (SPET) panel and yielded 6,488 high-quality SNPs. The genotyping data revealed a high degree of homozygosity (average 93.69%), an absence of genetic structure, and a balanced representation (11.62% to 14.16%) of the founder genomes. To evaluate the potential of the ToMAGIC population for tomato genetics and breeding, a proof-of-concept was conducted by phenotyping it for fruit size, plant pigmentation, leaf morphology, and earliness traits. Genome-wide association studies (GWAS) identified strong associations for the studied traits, pinpointing both previously identified and novel candidate genes near or within the linkage disequilibrium blocks. Domesticated alleles for fruit size were recessive and were found, at low frequencies, in wild/ancestral populations. Our findings demonstrate that the newly developed ToMAGIC population is a valuable resource for genetic research in tomato, offering significant potential for identifying new genes that govern key traits in tomato breeding. ToMAGIC lines displaying a pyramiding of traits of interest could have direct applicability for integration into breeding pipelines providing untapped variation for tomato breeding.
3D Transcranial ultrasound localization microscopy reveals major arteries in the sheep brain
Authors: Coudert Antoine , Denis Louise , Chavignon Arthur , Bodard Sylvain , Naveau Mikael , Sistiaga Palma Pro , Saulnier Romaric , Orset Cyrille , Vivien Denis , Chappard Christine , Couture Olivier
Published: March 2024

Objective

Stroke, a leading cause of mortality and disability globally, demands swift and accurate diagnosis for effective treatment. Although MRI and CT scans serve as conventional methods, their accessibility remains a challenge, prompting exploration into alternative, portable, and non-ionizing imaging solutions like ultrasound with reduced costs. While Ultrasound Localization Microscopy (ULM) displays potential in high-resolution vessel imaging, its 2D constraints limit its emergency utility.

Materials and Methods

This study delves into the feasibility of 3D ULM with multiplexed probe for transcranial vessel imaging in sheep brains, emulating human skull characteristics. Three sheep underwent 3D ULM imaging, compared with angiographic MRI, while skull characterization was conducted in vivo using ultrashort bone MRI sequences and ex vivo via micro CT.

Results and conclusions

The study showcased 3D ULM’s ability to highlight vessels, down to the Circle of Willis, yet within a confined 3D field-of-view. Future enhancements in signal, aberration correction, and human trials hold promise for a portable, volumetric, transcranial ultrasound angiography system.

Summary statement

3D Ultrasound localization microscopy, using a low-frequency matrix probe, enables transcranial reconstruction of the main vessels in sheep brains.
Natural Induction: Spontaneous adaptive organisation without natural selection
Authors: Buckley Christopher L. , Lewens Tim , Levin Mike , Millidge Beren , Tschantz Alec , Watson Richard A.
Published: March 2024

Evolution by natural selection is believed to be the only possible source of spontaneous adaptive organisation in the natural world. This places strict limits on the kinds of systems that can exhibit adaptation spontaneously, i.e. without design. Physical systems can show some properties relevant to adaptation without natural selection or design. 1) The relaxation, or local energy minimisation, of a physical system constitutes a natural form of optimisation insomuch as it finds locally optimal solutions to the frustrated forces acting on it or between its components. 2) When internal structure ‘gives way’ or accommodates to a pattern of forcing on a system this constitutes learning insomuch as it can store, recall and generalise past configurations. Both these effects are quite natural and general, but in themselves insufficient to constitute non-trivial adaptation. However, here we show that the recurrent interaction of physical optimisation and physical learning together results in significant spontaneous adaptive organisation. We call this adaptation by natural induction. The effect occurs in dynamical systems described by a network of viscoelastic connections subject to occasional disturbances. When the internal structure of such a system accommodates slowly across many disturbances and relaxations, it spontaneously learns to preferentially visit solutions of increasingly greater quality (exceptionally low energy). We show that adaptation by natural induction thus produces network organisations that improve problem-solving competency with experience. We note that the conditions for adaptation by natural induction, and its adaptive competency, are different from those of natural selection. We therefore suggest that natural selection is not the only possible source of spontaneous adaptive organisation in the natural world.
A Root Mean Square Deviation Estimation Algorithm (REA) and its use for improved RNA Structure Prediction
Authors: Kalampaliki Agoritsa , Dimopoulos Alexandros C. , Reczko Martin
Published: March 2024

The 3D structure of RNA is crucial for biotechnological applications and to comprehend its biological function. Recent developments using AlphaFold-inspired deep neural networks improved the prediction of 3D structure from RNA sequence, but evaluation of the accuracy of these predictions is still necessary. We present the RMSD Estimation Algorithm (REA), a feed-forward neural network to predict the root-mean-square deviation (RMSD) of a 3D RNA structure from its experimentally determined counterpart using its Molprobity [1] stereochemical validation features. It is trained on structures predicted by the DeepFoldRNA [2] and trRosettaRNA [3] transformer-based deep neural networks on a set of 182 models of RNA structures with pseudoknots. We compare REA with ARES [4], a deep learning algorithm that predicts the RMSD by extracting geometric patterns with equivariant convolution, assessing the prediction accuracy on RNAs with and without pseudoknots. REA outperformed ARES on both test sets with smaller absolute difference between the true and the predicted RMSD. Using a combination of REA and a Support Vector Regression (SVR) trained on the same data as REA, we can select RNA structures predicted with DeepFoldRNA, trRosettaRNA and Rhofold [5] to achieve a significantly higher prediction accuracy than any of the prediction methods used alone. This was shown on a validation set with 261 novel RNA chains extracted from the Nonredundant 3D Structure Dataset [5] and a test set with 55 novel RNA chains from RNA-Puzzles [5]. Our selection based prediction method can easily incorporate additional prediction algorithms.
Cisplatin reprogramming of protein phosphorylation
Authors: Qi Luyu , Zhou Yang , Hou Yinzhu , Luo Qun , Xu Yan , Liu Xingkai , Yu Wanchen , Xin Bobo , Huang Yaolong , Han Juanjuan , Li Xiangjun , Zhang Yanyan , Jia Feifei , Fang Tiantian , Wang Shijun , Sadler Peter J. , Zhao Yao , Wang Fuyi
Published: March 2024

Cisplatin is a DNA-targeting chemotherapeutic. We have mapped cisplatin damage to specific genes in human lung cancer cells. Surprisingly, cisplatin targets the majority of protein kinase genes and protein phosphatase genes in the human genome. This suggests that cisplatin can reprogram protein phosphorylation genome-wide. We have profiled the protein expression and phosphorylation in human testicular cancer cells subjected to cisplatin treatment, since testicular cancer is curable by cisplatin. We demonstrate that most downregulated proteins are encoded by cisplatin damaged genes. These proteins include a series of protein kinases and protein phosphatases, leading to significant changes in the phosphorylation level of >600 proteins in testicular cancer cells. Hence, reprograming of protein phosphorylation is proteome-wide. Importantly, the reprogrammed protein phosphorylation activates G2/M DNA-damage checkpoint regulation and ATM signalling pathways, causing cell cycle arrest at the G2/M phase. These findings suggest that specific protein phosphorylation pathways are potential new targets for platinum drug design.
LogoMotif: a comprehensive database of transcription factor binding site profiles in Actinobacteria
Authors: Augustijn Hannah E. , Karapliafis Dimitris , Joosten Kristy , Rigali Sébastien , van Wezel Gilles P. , Medema Marnix H.
Published: March 2024

Actinobacteria undergo a complex multicellular life cycle and produce a wide range of specialized metabolites, including the majority of the antibiotics. These biological processes are controlled by intricate regulatory pathways, and to better understand how they are controlled we need to augment our insights into the transcription factor binding sites. Here, we present LogoMotif (https://logomotif.bioinformatics.nl), an open-source database for characterized and predicted transcription factor binding sites in Actinobacteria, along with their cognate position weight matrices and hidden Markov models. Genome-wide predictions of binding site locations inStreptomycesmodel organisms are supplied and visualized in interactive regulatory networks. In the web interface, users can freely access, download and investigate the underlying data. With this curated collection of actinobacterial regulatory interactions, LogoMotif serves as a basis for binding site predictions, thus providing users with clues on how to elicit the expression of genes of interest and guide genome mining efforts.

Highlights

Actinobacterial regulatory networks are key for compound discovery, including antibiotics.

Contains ∼400 validated and ∼12,100 predicted interactions, presented in interactive networks.

Serves as foundation for regulatory predictions in the gene cluster detection tool, antiSMASH.

LogoMotif’s data and algorithms provide knowledge on expression and functional inference of genes.

LogoMotif aids in the discovery of novel chemistry within Actinobacteria and beyond.

Graphical abstract
Photosymbiont density is correlated with constitutive and induced immunity in the facultatively symbiotic coral,Astrangia poculata
Authors: Changsut Isabella V. , Borbee Erin M. , Womack Haley R. , Shickle Alicia , Sharp Koty H. , Fuess Lauren E.
Published: March 2024

Scleractinian corals, essential ecosystem engineers that form the base of coral reef ecosystems, have faced unprecedented mortality in recent decades due climate-change related stressors, including disease outbreaks. Despite this emergent threat to corals, many questions still remain regarding mechanisms underlying observed variation in disease susceptibility. Emergent data suggests at least some degree of variation in disease response may be linked to variability in the relationship between host corals and their algal photosymbionts (Family Symbiodineaceae). Still, the nuances of connections between symbiosis and immunity in cnidarians, including scleractinian corals, remain poorly understood. Here we leveraged an emergent model species, the facultatively symbiotic, temperate, scleractinian coralAstrangia poculata, to investigate associations between symbiont density and both constitutive and induced immunity. We used a combination of controlled immune challenges with heat-inactivated pathogens and transcriptomic analyses. Our results demonstrate thatA. poculatamounts a robust initial response to pathogenic stimuli that is highly similar to responses documented in tropical corals. Furthermore, we document positive associations between symbiont density and both constitutive and induced immune responses, in agreement with recent preliminary studies inA. poculata. A suite of immune genes, including those coding for antioxidant peroxidoxin biosynthesis, are constitutively positively associated with symbiont density inA. poculata. Furthermore, variation in symbiont density is associated with distinct patterns of immune response; low symbiont density corals induce preventative immune mechanisms whereas high symbiont density corals mobilize energetic resources to fuel humoral immune responses. In summary, our study reveals the need for more nuanced study of symbiosis-immune interplay across diverse scleractinian corals, preferably including quantitative energy budget analysis for full disentanglement of these complex associations and their effects on pathogen susceptibility.
Metastable condensates suppress conversion to amyloid fibrils
Authors: Das Tapojyoti , Zaidi Fatima , Farag Mina , Ruff Kiersten M. , Messing James , Taylor J. Paul , Pappu Rohit V. , Mittag Tanja
Published: March 2024

Stress granules form via co-condensation of RNA binding proteins with prion-like low complexity domains (PLCDs) and RNA molecules released by stress-induced polysomal runoff. Homotypic interactions among PLCDs can drive amyloid fibril formation and this is enhanced by ALS-associated mutations. We find that homotypic interactions that drive condensation versus fibril formation are separable for A1-LCD, the PLCD of hnRNPA1. These separable interactions lead to condensates that are metastable versus fibrils that are globally stable. Metastable condensates suppress fibril formation, and ALS-associated mutations enhance fibril formation by weakening condensate metastability. Mutations designed to enhance A1-LCD condensate metastability restore wild-type behaviors of stress granules in cells even when ALS-associated mutations are present. This suggests that fibril formation can be suppressed by enhancing condensate metastability through condensate-driving interactions.

One-Sentence Summary

In PLCDs, fibril formation driven by zipper motifs is suppressed by condensation-driving interactions mediated by stickers.
Imaging of cellular dynamicsin vitroandin situ: from a whole organism to sub-cellular imaging with self-driving, multi-scale microscopy
Authors: Daetwyler Stephan , Mazloom-Farsibaf Hanieh , Zhou Felix Y. , Segal Dagan , Sapoznik Etai , Westcott Jill M. , Brekken Rolf A. , Danuser Gaudenz , Fiolka Reto
Published: March 2024

Many biological processes span multiple time and length scales, including developmental processes and cancer metastasis. While light-sheet fluorescence microscopy (LSFM) has become a fast and efficient method for imaging of organisms, cells and sub-cellular dynamics, simultaneous observations across these scales have remained challenging. Moreover, continuous high-resolution imaging inside living organisms has mostly been limited to few hours as regions of interest quickly move out of view due to sample movement and growth. Here, we present a self-driving, multi-resolution light-sheet microscope platform controlled by a custom Python-based software, to simultaneous observe and quantify sub-cellular dynamics and entire organismsin vitroandin vivoover hours of imaging. We apply the platform to the study of developmental processes, cancer invasion and metastasis, and we provide quantitative multi-scale analysis of immune-cancer cell interactions in zebrafish xenografts.
The aging-induced long non-coding RNAMIRIALcontrols endothelial cell and mitochondrial function
Authors: Kohnle Caroline , Koziarek Susanne , Warwick Timothy , Theodorou Kosta , Fischer Ariane , Juni Rio Putra , Muhly-Reinholz Marion , Busscher Denise , Lam Frederike , Vetter Felix , Wagner Julian U. G. , Sommer Janina , Gimbel Anna Theresa , Stanicek Laura , Günther Stefan , Wittig Ilka , Maegdefessel Lars , Leisegang Matthias S. , Brandes Ralf P. , Dimmeler Stefanie , Boon Reinier A.
Published: March 2024

Aims

Vascular aging is characterized by the progressive deterioration of endothelial function. Long non-coding RNAs (lncRNAs) are critical regulators of gene expression and protein function. However, their involvement in aging-related dysregulation of endothelial cell function remains largely unknown. Here, we aim to characterize the aging-regulated lncRNAMIRIALin endothelial cells.

Methods + Results

We identifiedMirialas an aging-induced lncRNA in RNA-sequencing data of mouse cardiac endothelial cells. In human umbilical vein endothelial cells (HUVECs), gapmer-mediated knockdown ofMIRIALled to decreases in proliferation, migration and basal angiogenic sprouting. Additionally,MIRIALknockdown led to increased mitochondrial mass, spare respiratory capacity, and vascular endothelial growth factor (VEGF)-stimulated sprouting. Mechanistically, we demonstrate thatMIRIALforms anRNA·DNA:DNA triple helix (triplex) with a regulatory region of the quiescence-promoting Forkhead Box O1 (FOXO1) gene, thus inducing its expression. The formation of this triplex involves anAluelement within theMIRIALtranscript, representing a previously undescribed mechanism of action for a lncRNA. Further, we generated a globalMirialknockout mouse line of. Angiogenic sprouting of aortic rings fromMirialknockout mice was reduced under basal conditions, but increased after VEGF administration, validating thein vitroangiogenic phenotype. Importantly, cardiac contractile function after acute myocardial infarction is severely reduced inMirialknockout mice, as compared to wild-type littermates.

Conclusions

The lncRNAMIRIALis an aging-induced regulator of endothelial quiescence and metabolism.

Translational Perspective

LncRNAs often exhibit cell-type or tissue-specific expression and regulation, rendering them potentially druggable targets requiring lower doses and having fewer side effects compared to protein targets. Our current research highlights, that loss ofMirialcorrelates with adverse outcomes post-acute myocardial infarction in a murine model. Dysregulation ofMIRIALin various human pathological conditions, such as ischemic heart disease, abdominal aortic aneurysm, cancer, and aging, indicates its potential as a diagnostic marker. Mechanistically,MIRIALregulates endothelial quiescence by modulatingFOXO1expression, suggesting it as a promising therapeutic target to counteract the age-related decline in endothelial cell function.
Temporal Trends in Stroke Management and Outcomes between 2011 and 2020: Results from a Nationwide Multicenter Registry
Authors: Park Tai Hwan , Hong Keun-Sik , Cho Yong-Jin , Ryu Wi-Sun , Kim Dong-Eog , Park Man-Seok , Choi Kang-Ho , Kim Joon-Tae , Kang Jihoon , Kim Beom-Joon , Han Moon-Ku , Lee Jun , Cha Jae-Kwan , Kim Dae-Hyun , Kim Jae Guk , Lee Soo Joo , Kwon Jee-Hyun , Kim Wook-Joo , Shin Dong-Ick , Yum Kyu Sun , Sohn Sung Il , Hong Jeong-Ho , Choi Jay Chol , Lee Byung-Chul , Yu Kyung-Ho , Oh Mi-Sun , Park Jong-Moo , Kang Kyusik , Lee Kyungbok , Lee Sang-Hwa , Jeong Hae-Bong , Park Kwang-Yeol , Lee Ji Sung , Lee Juneyoung , Gorelick Philip B. , Bae Hee-Joon
Published: March 2024

Background

There have been significant advancements in the treatment of ischemic stroke including stent retrievers for endovascular thrombectomy, new oral anticoagulants for atrial fibrillation, dual antiplatelet therapy for stroke prevention, and statins for atherosclerotic stroke. This study aims to evaluate temporal trends of these treatments and related clinical outcomes through a decade-long trend analysis, utilizing data from a comprehensive, national, multicenter stroke registry. We also seek to identify areas in need of improvement.

Methods

This analysis involved patients with ischemic stroke or transient ischemic attack registered prospectively in the Clinical Research Center for Stroke-Korea-National Institute of Health (CRCS-K-NIH) registry between 2011 and 2020. We examined temporal trends in risk factors, etiologic subtypes, acute management strategies, and outcomes for up to one year post-stroke. Generalized linear mixed models were employed to account for center clustering.

Results

Among 77,662 patients over 10 years, the average age increased by 2.2 years in men and 2.4 years in women. Notably, in-hospital neurological deterioration, 3-month and 1-year mortality, and cumulative incidence of recurrent stroke within one year showed significant decreases over time after adjustments for age, sex, and initial stroke severity (Ptrend’s< 0.01). However, functional outcomes at 3 months and 1 year remained unchanged. The use of endovascular thrombectomy increased from 5.4% in 2011 to 10.6% in 2020. There was also an increase in the prescription of anticoagulants for atrial fibrillation, dual antiplatelet therapy, statins, and stroke unit care. Contrarily, the rate of intravenous thrombolysis showed a slight decline.

Conclusions

This study points to a reduction in mortality and risk of recurrent stroke over the past decade, paralleling enhancement in acute and preventive stroke management. Nevertheless, the decline in use of intravenous thrombolysis and the stagnation of functional outcomes may signal the need for further investigation to identify underlying causes of these trends and counterstrategies to mitigate risks.
Machine Learning for Predicting Therapeutic Outcomes in Acute Myeloid Leukemia Patients
Authors: Karathanasis Nestoras , Papasavva Panayiota , Oulas Anastasis , Spyrou George M
Published: March 2024

Background and Objective

The standard of care inAcute Myeloid Leukemiapatients has remained essentially unchanged for nearly 40 years. Due to the complicated mutational patterns within and between individual patients and a lack of targeted agents for most mutational events, implementing individualized treatment for AML has proven difficult. We reanalysed theBeatAML datasetemployingMachine Learning algorithms. The BeatAML project entails patients extensively characterized at the molecular and clinical levels and linked to drug sensitivity outputs. Our approach capitalizes on the molecular and clinical data provided by theBeatAML datasetto predict theex vivodrug sensitivity for the 122 drugs evaluated by the project.

Methods

We utilized ElasticNet, which produces fully interpretable models, in combination with a two-step training protocol that allowed us to narrow down computations. We automated the genes’ filtering step by employing two metrics, and we evaluated all possible data combinations to identify the best training configuration settings per drug.

Results

We report a Pearson correlation across all drugs of 0.36 when clinical and RNA sequencing data were combined, with the best-performing models reaching a Pearson correlation of 0.67. When we trained using the datasets in isolation, we noted that RNA Sequencing data (Pearson: 0.36) attained three times the predictive power of whole exome sequencing data (Pearson: 0.11), with clinical data falling somewhere in between (Pearson 0.26). Lastly, we present a paradigm of clinical significance. We used our models’ prediction as ahealth management scoreto rank an individual’s expected response to treatment. We identified 78 patients out of 89 (88%) that the proposed drug was more potent than the administered one based on theirex vivodrug sensitivity data.

Conclusions

In conclusion, our reanalysis of the BeatAML dataset using Machine Learning algorithms demonstrates the potential for individualized treatment prediction in Acute Myeloid Leukemia patients, addressing the longstanding challenge of treatment personalization in this disease. By leveraging molecular and clinical data, our approach yields promising correlations between predicted drug sensitivity and actual responses, highlighting a significant step forward in improving therapeutic outcomes for AML patients.

Highlights

Machine learning can predict response to treatment in Acute Myeloid Leukemia patients.

RNA sequencing data are more informative than whole exome sequencing and clinical data in predicting drug response in Acute Myeloid Leukemia patients.

Drug response predictions could be used as a health management score to rank the individual’s expected response to treatment.

We identified a more potent drug than the administered one for 88% (78 out of 89) of the patients examined.