bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends in diabetes incidence and associated risk factors among people living with HIV in the current treatment era, 2008-2018
Authors: Spieler Gabriel , Westfall Andrew O. , Long Dustin M. , Cherrington Andrea , Burkholder Greer A. , Funderburg Nicholas , Raper James L. , Overton Edgar T. , Willig Amanda L.
Published: May 2022

People with HIV (PWH) have an increased risk for diabetes mellitus. Our objectives were to characterize the prevalence and incidence of diabetes in a cohort of people with HIV (PWH), and to evaluate both traditional and HIV-specific risk factors contributing to incident diabetes diagnoses. We conducted a retrospective study of a Southeastern US academic HIV clinic. All PWH age > 18 years of age who attended at least two clinic visits between 2008 and 2018 were evaluated to assess time to diabetes incidence. Laboratory, demographic, clinical, medication and diagnoses data were extracted from the Clinic EMR. Diabetes was defined when at least two of the following three criteria were met: (1) laboratory data consistent with a diagnosis as defined by the ADA SOC (Hgb A1C ≥ 6.5% and/or 2 glucose results >200 mg/dl (at least 30 days apart)), (2) diagnosis of diabetes in the EMR, or (3) exposure to diabetes medication. Time to Diabetes incidence was computed from the entire clinic population for each study year. Univariate Cox proportional hazard models were developed to evaluate associations between each baseline factor and time to DM. Multivariable Cox proportional hazard regression models with time-dependent covariates were created to evaluate the independent association between significant parameters from univariate analyses and time to incident DM. From 4113 PWH included in the analysis, we identified 252 incident cases of diabetes. In multivariable analysis, BMI classification, liver disease, steroid exposure, and use of Integrase Inhibitors were associated with incident diabetes. Additional associated factors included lower CD4 cell counts, duration of HIV infection, exposure to non-statin lipid lowering therapy, and dyslipidemia. Incident diabetes rates are increasing at an alarming rate among PWH. Diabetes prevalence increased from 8.8% in 2008 to 14% in 2018. Both traditional and HIV-related risk factors, particularly body weight, steroid exposure, and use of Integrase Inhibitors, were associated with incident diabetes. Notably, several of the risk factors identified are modifiable and should be targeted for intervention.
Medical text prediction and suggestion using generative pre-trained transformer models with dental medical notes
Authors: Sirriani Joseph , Sezgin Emre , Claman Daniel , Linwood Simon L
Published: May 2022

Background

Generative pre-trained transformer (GPT) models are one of the latest large pre-trained natural language processing (NLP) models, which enables model training with limited datasets, and reduces dependency on large datasets which are scarce and costly to establish and maintain. There is a rising interest to explore the use of GPT models in healthcare.

Objective

We investigate the performance of GPT-2 and GPT-Neo models for medical text prediction using 374,787 free-text dental notes.

Methods

We fine-tune pre-trained GPT-2 and GPT-Neo models for next word prediction on a dataset of over 374,000 manually written sections of dental clinical notes. Each model was trained on 80% of the dataset, validated on 10%, and tested on the remaining 10%. We report model performance in terms of next word prediction accuracy and loss. Additionally, we analyze the performance of the models on different types of prediction tokens for categories. We annotate each token in 100 randomly sampled notes by category (e.g. Names, Abbreviations, Clinical Terms, Punctuation, etc.) and compare the performance of each model by token category.

Results

Models present acceptable accuracy scores (GPT-2: 76%, GPT-Neo: 53%), and the GPT-2 model also performs better in manual evaluations, especially for names, abbreviations, and punctuation. The results suggest that pre-trained models have the potential to assist medical charting in the future. We share the lessons learned, insights, and suggestions for future implementations.

Conclusion

The results suggest that pre-trained models have the potential to assist medical charting in the future. Our study presented one of the first implementations of the GPT model used with medical notes.
Learning to suppress likely distractor locations in visual search is driven by the local distractor frequency
Authors: Allenmark Fredrik , Zhang Bei , Shi Zhuanghua , Müller Hermann J.
Published: May 2022

Salient but task-irrelevant distractors interfere less with visual search when they appear in a display region where distractors have appeared more frequently in the past (‘distractor-location probability cueing’). This effect could reflect the (re-)distribution of a global, limited attentional ‘inhibition resource’. Accordingly, changing the frequency of distractor appearance in one display region should also affect the magnitude of interference generated by distractors in a different region. Alternatively, distractor-location learning may reflect a local response (e.g., ‘habituation’) to distractors occurring at a particular location. In this case, the local distractor frequency in one display region should not affect distractor interference in a different region. To decide between these alternatives, we conducted three experiments in which participants searched for an orientation-defined target while ignoring a more salient orientation distractor that occurred more often in one vs. another display region. Experiment 1 varied the ratio of distractors appearing in the frequent vs. rare regions (60/40–90/10), with a fixed global distractor frequency. The results revealed the cueing effect to increase with increasing probability ratio. In Experiments 2 and 3, one (‘test’) region was assigned the same local distractor frequency as in one of the conditions of Experiment 1, but a different frequency in the other region – dissociating local from global distractor frequency. Together, the three experiments showed that distractor interference in the test region was not significantly influenced by the frequency in the other region, consistent with purely local learning. We discuss the implications for theories of statistical distractor-location learning.

Public Significance Statement

We are frequently distracted by salient visual stimuli which are irrelevant to the task at hand. Previous studies have shown that ‘knowledge’ of the location(s) where a distractor is most likely to occur helps the observer to mitigate distraction. In this study we compared different theories of how the frequency and spatial distribution of distractor occurrence in different locations could influence the ability to avoid distraction. The results favored a local learning account: the ability to avoid distraction by distractors occuring in a particular spatial region is primarily influenced by how often distractors have occurred in that region.
Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization
Authors: Geadah Victor , Horoi Stefan , Kerg Giancarlo , Wolf Guy , Lajoie Guillaume
Published: May 2022

Neurons in the brain have rich and adaptive input-output properties. Features such as heterogeneous f-I curves and spike frequency adaptation are known to place single neurons in optimal coding regimes when facing changing stimuli. Yet, it is still unclear how brain circuits exploit single-neuron flexibility, and how network-level requirements may have shaped such cellular function. To answer this question, a multi-scaled approach is needed where the computations of single neurons and neural circuits must be considered as a complete system. In this work, we use artificial neural networks to systematically investigate single-neuron input-output adaptive mechanisms, optimized in an end-to-end fashion. Throughout the optimization process, each neuron has the liberty to modify its nonlinear activation function, parametrized to mimic f-I curves of biological neurons, and to learn adaptation strategies to modify activation functions in real-time during a task. We find that such networks show much-improved robustness to noise and changes in input statistics. Importantly, we find that this procedure recovers precise coding strategies found in biological neurons, such as gain scaling and fractional order differentiation/integration. Using tools from dynamical systems theory, we analyze the role of these emergent single-neuron properties and argue that neural diversity and adaptation play an active regularization role, enabling neural circuits to optimally propagate information across time.
Aggression and multimodal signaling in noise in a common urban songbird
Authors: Önsal Çağla , Yelimlieş Alper , Akçay Çağlar
Published: May 2022

Anthropogenic noise may disrupt signals used to mediate aggressive interactions, leading to more physical aggression between opponents. One solution to this problem is to switch signaling effort to a less noisy modality (e.g., the visual modality). In the present study we investigate aggressive behaviors and signaling in urban and rural male European robins (Erithacus rubecula) in response to simulated intrusions with or without experimental noise. First, we predicted that urban birds, living in noisier habitats, would be generally more aggressive than rural birds. We also predicted that during simulated intrusions with experimental noise, robins would increase their physical aggression and show a multi-modal shift, i.e., respond with more visual threat displays and sing fewer songs. Finally, we expected the multi-modal shift in response to noise to be stronger in urban birds compared to rural birds. The results showed that urban birds were more aggressive than rural robins, but an increase in aggression with experimental noise was seen only in the rural birds. Urban but not rural birds decreased their song rate in response to noise. Contrary to the multi-modal shift hypothesis, however, there was no evidence of a concurrent increase in visual signals. These results point to a complex role of immediate plasticity and longer-term processes in affecting communication during aggressive interactions under anthropogenic noise.

Significance Statement

Human activity has an enormous effect on wildlife, including on their social behavior. Animals living in urban areas often tend to be more aggressive than those living in rural areas, which may be due to urban acoustic noise making communication between individuals more difficult. In a study with a common songbird, the European robin, we investigated the role of urban acoustic noise in aggression and territorial communication. Urban robins were more aggressive than rural robins, and additional noise in the territory increased aggression in rural but not urban robins. While urban robins decreased their singing effort with additional noise, they did not increase visual signals concurrently. These results suggest that noise can indeed make animals behave more aggressively although the effect may depend on how noisy it is already. These results further our understanding of how human-made noise changes animal communication and social behavior.
Generic solving of physiologically-based kinetic models in support of next generation risk assessment due to chemicals
Authors: Charles Sandrine , Gestin Ophelia , Bruset Jérémie , Lamonica Dominique , Baudrot Virgile , Chaumot Arnaud , Geffard Olivier , Lacoue-Labarthe Thomas , Lopes Christelle
Published: May 2022

Increasing the confidence in using in vitro and in silico model-based data to aid the chemical risk assessment process is one, if not the most, important challenge currently facing regulatory authorities. A particularly crucial concern is to fully take advantage of scientifically valid Physiologically-Based Kinetic (PBK) models. Nevertheless, risk assessors remain still unwilling in employing PBK models within their daily work. Indeed, PBK models are not often included in current official guidance documents. In addition, most users have limited experience in using modelling in general. So, the complexity of PBK models, together with a lack to evaluation methods of their performances, certainly contributes to their under-use in practical risk assessment.

This paper proposes an innovative and unified modelling framework, in both the writing of PBK equations as matrix ordinary differential equations (ODE), and in its exact solving simply expressed with matrix products. This generic PBK solution allows to consider as many as state-variables as needed to quantify chemical absorption, distribution, metabolism and excretion processes within living organisms when exposed to chemical substances. This generic PBK model makes possible any compartmentalisation to be considered, as well as all appropriate inter-connections between compartments and with the external medium.

We first introduce our PBK modelling framework, with all intermediate steps from the matrix ODE to the exact solution. Then we apply this framework to bioaccumulation testing, before illustrating its concrete use through complementary case studies in terms of species, compounds and model complexity.

Abstract Figure
Tensor Decomposition and Principal Component Analysis-Based Unsupervised Feature Extraction Outperforms State-of-the-Art Methods When Applied to Histone Modification Profiles
Authors: Roy Sanjiban Sekhar , Taguchi Y-h.
Published: May 2022

Identification of histone modification from datasets that contain high-throughput sequencing data is difficult. Although multiple methods have been developed to identify histone modification, most of these methods are not specific for histone modification but are general methods that aim to identify protein binding to the genome. In this study, tensor decomposition (TD) and principal component analysis (PCA)-based unsupervised feature extraction with optimized standard deviation were successfully applied to gene expression and DNA methylation. The proposed method was used to identify histone modification. Histone modification along the genome is binned within the region of lengthL. Considering principal components (PCs) or singular value vectors (SVVs) that TD or PCA attributes to samples, we can select PCs or SVVs attributed to regions. The selected PCs and SVVs further attributeP-values to regions, and adjusted P-values are used to select regions. The proposed method identified various histone modifications successfully and outperformed various state-of-the-art methods. This method is expected to serve as ade factostandard method to identify histone modification.
Alternative Factor Prescribing after Low-Dose Recombinant Factor VIIa Protocol in Cardiac Surgery
Authors: Momenzadeh Amanda , Meyer Jesse G. , De Leon Noelle , Tsourounis Candy
Published: May 2022

Background

Safety concerns exist with the off-label use of recombinant factor VIIa (rFVIIa, Novoseven RT®) for refractory bleeding in cardiac surgery, including increased risk of thromboembolism. A rFVIIa protocol was implemented in December 2015 to standardize rFVIIa for cardiac surgery related hemorrhage.

Methods

We performed a retrospective, observational review of rFVIIa in adult cardiac surgery patients pre-protocol (January 2015 to November 2015) vs. post-protocol (December 2015 to March 2016). Study outcomes were rate of rFVIIa administration, rFVIIa dosing characteristics, length of stay, mortality, readmission rate, need for re-exploration, and rate of 4-factor Prothrombin Complex Concentrates (PCC; Kcentra®) administration.

Results

There was a significant reduction in percentage of cardiac surgery cases receiving rFVIIa pre-vs. post-protocol (14.3 vs. 5.2%, p=0.015). Average total dose per patient decreased between groups (81.4 vs. 56.6 mcg/kg, p=0.059). In-hospital mortality, length of stay, need for re-exploration, readmission rates and 30-day mortality did not differ. Although 4-four-factor PCC significantly increased post-protocol (2.5% vs. 8%, p=0.02), overall use of factor products, rFVIIa or 4-factor PCC, did not change between study periods (16.8% vs. 13%, p=0.416). Mean cost of either rFVIIa or 4-factor PCC pre-protocol was significantly higher than that post-protocol ($8,778 vs. $4,421, p=0.0008).

Conclusions

The use of rFVIIa decreased after implementation of a rFVIIa protocol targeting 30 mcg/kg/dose without compromising morbidity or mortality outcomes. Four-factor PCC use significantly increased during the study, but the overall cost was reduced. Institutions wanting to implement a rFVIIa protocol should take careful measures to concurrently address off-label use of 4-factor PCC.
BA.2.12.1, BA.4 and BA.5 escape antibodies elicited by Omicron infection
Authors: Cao Yunlong , Yisimayi Ayijiang , Jian Fanchong , Song Weiliang , Xiao Tianhe , Wang Lei , Du Shuo , Wang Jing , Li Qianqian , Chen Xiaosu , Yu Yuanling , Wang Peng , Zhang Zhiying , Liu Pulan , An Ran , Hao Xiaohua , Wang Yao , Wang Jing , Feng Rui , Sun Haiyan , Zhao Lijuan , Zhang Wen , Zhao Dong , Zheng Jiang , Yu Lingling , Li Can , Zhang Na , Wang Rui , Niu Xiao , Yang Sijie , Song Xuetao , Chai Yangyang , Hu Ye , Shi Yansong , Zheng Linlin , Li Zhiqiang , Gu Qingqing , Shao Fei , Huang Weijin , Jin Ronghua , Shen Zhongyang , Wang Youchun , Wang Xiangxi , Xiao Junyu , Xie Xiaoliang Sunney
Published: May 2022

SARS-CoV-2 Omicron sublineages BA.2.12.1, BA.4 and BA.5 exhibit higher transmissibility over BA.21. The new variants’ receptor binding and immune evasion capability require immediate investigation. Here, coupled with Spike structural comparisons, we show that BA.2.12.1 and BA.4/BA.5 exhibit comparable ACE2-binding affinities to BA.2. Importantly, BA.2.12.1 and BA.4/BA.5 display stronger neutralization evasion than BA.2 against the plasma from 3-dose vaccination and, most strikingly, from post-vaccination BA.1 infections. To delineate the underlying antibody evasion mechanism, we determined the escaping mutation profiles2, epitope distribution3 and Omicron neutralization efficacy of 1640 RBD-directed neutralizing antibodies (NAbs), including 614 isolated from BA.1 convalescents. Interestingly, post-vaccination BA.1 infection mainly recalls wildtype-induced humoral memory. The resulting elicited antibodies could neutralize both wildtype and BA.1 and are enriched on non-ACE2-competing epitopes. However, most of these cross-reactive NAbs are heavily escaped by L452Q, L452R and F486V. BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1; nevertheless, these NAbs are largely escaped by BA.2/BA.4/BA.5 due to D405N and F486V, and react weakly to pre-Omicron variants, exhibiting poor neutralization breadths. As for therapeutic NAbs, Bebtelovimab4 and Cilgavimab5 can effectively neutralize BA.2.12.1 and BA.4/BA.5, while the S371F, D405N and R408S mutations would undermine most broad sarbecovirus NAbs. Together, our results indicate that Omicron may evolve mutations to evade the humoral immunity elicited by BA.1 infection, suggesting that BA.1-derived vaccine boosters may not achieve broad-spectrum protection against new Omicron variants.
A mutation-level covariate model for mutational signatures
Authors: Kahane Itay , Leiserson Mark D.M. , Sharan Roded
Published: May 2022

Mutational processes and their exposures in particular genomes are key to our understanding of how these genomes are shaped. However, current analyses assume that these processes are uniformly active across the genome without accounting for potential covariates such as strand or genomic region that could impact such activities. Here we suggest the first mutation-covariate models that explicitly model the effect of different covariates on the exposures of mutational processes. We apply these models to test the impact of replication strand on these processes and compare them to strand-oblivious models across a range of data sets. Our models capture replication strand specificity, point to signatures affected by it, and score better on held-out data compared to standard models that do not account for mutation-level covariate information.
Raising the bar for patient experience during care transitions in Canada: A repeated cross-sectional survey evaluating a patient-oriented discharge summary at Ontario hospitals
Authors: Okrainec Karen , Chaput Audrey , Rac Valeria E. , Tomlinson George , Matelski John , Robson Mark , Troup Amy , Krahn Murray , Hahn-Goldberg Shoshana
Published: May 2022

Background

Patient experience when transitioning home from hospital is an important quality metric linked to improved patient outcomes. We evaluated the impact of a hospital-based care transition intervention, patient-oriented discharge summary (PODS), on patient experience across Ontario acute care hospitals.

Methods

We used a repeated cross-sectional study design to compare yearly positive responses to four questions centered on discharge communication from the Canadian Patient Experience Survey (2016-2020) among three hospital cohorts with various levels of PODS implementation. Logistic regression using a binomial likelihood accounting for site level clustering was used to assess continuous linear time trends among cohorts and cohort differences during the post-implementation period. This research had oversight from a public advisory group of patient and caregiver partners from across the province.

Results

512,288 responses were included with mean age 69 ± 14 years (females) and 61 ± 20 years (males). Compared to non-implementation hospitals, hospitals with full implementation (>50% discharges) reported higher odds for having discussed the help needed when leaving hospital (OR=1.18, 95% CI=1.02-1.37) and having received information in writing about what symptoms to look out for (OR=1.44, 95%=1.17-1.78) post-implementation. The linear time trend was also significant when comparing hospitals with full versus no implementation for having received information in writing about what symptoms to look out for (OR=1.05, 95% CI=1.01-1.09).

Interpretation

PODS implementation was associated with higher odds of positive patient experience, particularly for discharge planning. Further efforts should center on discharge management, specifically: understanding of medications and what to do if worried once home.
Characterization of Extensive Diversity In Immunoglobulin Light Chain Variable Germline Genes Across Biomedically Important Mouse Strains
Authors: Kos Justin T. , Safonova Yana , Shields Kaitlyn M. , Silver Catherine A. , Lees William D. , Collins Andrew M. , Watson Corey T.
Published: May 2022

The light chain immunoglobulin genes of biomedically relevant mouse strains are poorly documented in current germline gene databases. We previously showed that IGH loci of wild-derived mouse strains representing the major mouse subspecies contained 247 germline IGHV sequences not curated in the international ImMunoGeneTics (IMGT) information system, which is the most commonly used database that curates the germline repertoires used for sequence alignment in AIRR-seq analysis. Despite containing levels of polymorphism similar to the IGH locus, the germline gene content and diversity of the light chain loci have not been comprehensively cataloged. To explore the extent of germline light chain repertoire diversity across mouse strains commonly used in the biomedical sciences, we performed AIRR-seq analysis and germline gene inference for 18 inbred mouse strains, including the four wild-derived strains with diverse sub-species origins. We inferred 1582 IGKV and 63 IGLV sequences, representing 459 and 22 unique IGKV and IGLV sequences. Of the unique inferred germline IGKV and IGLV sequences, 67.8% and 59%, respectively, were undocumented in IMGT. Across strains we observed germline IGKV sequences shared by three distinct IGK haplotypes and a more conserved IGLV germline repertoire. In addition, J gene inference indicated a novel IGK2 allele shared between PWD/PhJ and MSM/MsJ and a novel IGLJ1 allele for LEWES/EiJ and IGLJ2 allele for MSM/MsJ. Finally, a combined IGHV, IGKV, and IGLV phylogenetic analysis of wild-derived germline repertoires displayed reduced germline diversity for the light chain repertoire compared to the heavy chain repertoire, suggesting potential evolutionary differences between the two chains.
Leveraging spatio-temporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models
Authors: Bornhofen Elesandro , Fè Dario , Lenk Ingo , Greve Morten , Didion Thomas , Jensen Christian Sig , Asp Torben , Janss Luc
Published: May 2022

Joint modeling of correlated multi-environment and multi-harvest data of perennial crop species may offer advantages in prediction schemes and a better understanding of the underlying dynamics in space and time. The goal of the present study was to investigate the relevance of incorporating the longitudinal dimension of within-season multiple harvests of biomass yield and nutritive quality traits of forage perennial ryegrass (Lolium perenneL.) in a reaction norm model setup that additionally accounts for genotype-environment interactions. Genetic parameters and accuracy of genomic breeding value predictions were investigated by fitting three random regression (random coefficients) linear mixed models (gRRM) using Legendre polynomial functions to the data. All models accounted for heterogeneous residual variance and moving average-based spatial adjustments within environments. The plant material consisted of 381 bi-parental family pools and four check varieties of diploid perennial ryegrass evaluated in eight environments for biomass yield and nutritive quality traits. The longitudinal dimension of the data arose from multiple harvests performed four times annually. The specified design generated a total of 16,384 phenotypic data points for each trait. Genomic DNA sequencing was performed using DNA nanoball-based technology (DNBseq) and yielded 56,645 single nucleotide polymorphisms (SNPs) which were used to calculate the allele frequency-based genomic relationship matrix used in all genomic random regression models. Biomass yield’s estimated additive genetic variance and heritability values were higher in later harvests. The additive genetic correlations were moderate to low in early measurements and peaked at intermediates, with fairly stable values across the environmental gradient, except for the initial harvest data collection. This led to the conclusion that complex genotype-by-environment interaction (G×E) arises from spatial and temporal dimensions in the early season, with lower re-ranking trends thereafter. In general, modeling the temporal dimension with a second-order orthogonal polynomial in the reaction norm mixed model framework improved the accuracy of genomic estimated breeding value prediction for nutritive quality traits, but no gain in prediction accuracy was detected for dry matter yield. This study leverages the flexibility and usefulness of gRRM models for perennial ryegrass research and breeding and can be readily extended to other multi-harvest crops.
Role of aIF5B in archaeal translation initiation
Authors: Kazan Ramy , Bourgeois Gabrielle , Lazennec-Schurdevin Christine , Larquet Eric , Mechulam Yves , Coureux Pierre-Damien , Schmitt Emmanuelle
Published: May 2022

In eukaryotes and in archaea late steps of translation initiation involve the two initiation factors e/aIF5B and e/aIF1A. In eukaryotes, the role of eIF5B in ribosomal subunit joining is established and structural data showing eIF5B bound to the full ribosome were obtained. To achieve its function, eIF5B collaborates with eIF1A. However, structural data illustrating how these two factors interact on the small ribosomal subunit have long been awaited. The role of the archaeal counterparts, aIF5B and aIF1A, remains to be extensively addressed. Here, we study the late steps of Pyrococcus abyssi translation initiation. Using in vitro reconstituted initiation complexes and light scattering, we show that aIF5B bound to GTP accelerates subunit joining without the need for GTP hydrolysis. We report the crystallographic structures of aIF5B bound to GDP and GTP and analyze domain movements associated to these two nucleotide states. Finally, we present the cryo-EM structure of an initiation complex containing 30S bound to mRNA, Met-tRNAiMet, aIF5B and aIF1A at 2.7 Å resolution. Structural data shows how archaeal 5B and 1A factors cooperate to induce a conformation of the initiator tRNA favorable to subunit joining. Archaeal and eukaryotic features of late steps of translation initiation are discussed.
Impatiens banensp. nov. &I. etugeisp. nov. (Balsaminaceae), threatened lowland species of the Cross-Sanaga Interval, Cameroon
Authors: Cheek Martin , Darbyshire Iain , Onana Jean Michel
Published: May 2022

We describe two range-restricted new species to science from the genusImpatiens(Balsaminaceae), both threatened, from the Cross-Sanaga Interval of western Cameroon. The first,Impatiens banen, appears to be restricted to an open seepage microhabitat on granitic inselbergs in the lowland-submontane forest zone of the Ebo Forest in Littoral Region and is provisionally assessed using the 2012 IUCN standard as Vulnerable. Sharing characters withImpatiens burtoniiandI. mannii, it differs from both, and appears to be unique in Camerooninter alia1) in the bicolored united lateral petals, the upper petals being white, while the lower petals are an intense pink-purple, 2) the hairy, filamentous spur, purple with a white apex, is curved along its length (through nearly 360°), almost describing a circle. Inselberg-specific species are unusual inImpatiens.

The second species,Impatiens etugei, of theI. macropteraaggregate, is restricted to rocks in the Mutel River of the Kom Wum Forest Reserve of NorthWest Region and is assessed as Critically Endangered. Having similarities withI. mackeyanaandI. letouzeyi, it differs from other species in the aggregateinter aliaby having opposite leaves (vs always alternate), flower exterior white (vs pink or pink-purple), and in the dorsal petal having a pair of lateral projections (vs projections absent).
A new machine learning based computational framework identifies therapeutic targets and unveils influential genes in pancreatic islet cells
Authors: Turki Turki , Taguchi Y-h.
Published: May 2022

Pancreatic islets comprise a group of cells that produce hormones regulating blood glucose levels. Particularly, the alpha and beta islet cells produce glucagon and insulin to stabilize blood glucose. When beta islet cells are dysfunctional, insulin is not secreted, inducing a glucose metabolic disorder. Identifying effective therapeutic targets against the disease is a complicated task and is not yet conclusive. To close the wide gap between understanding the molecular mechanism of pancreatic islet cells and providing effective therapeutic targets, we present a computational framework to identify potential therapeutic targets against pancreatic disorders. First, we downloaded three transcriptome expression profiling datasets pertaining to pancreatic islet cells (GSE87375, GSE79457, GSE110154) from the Gene Expression Omnibus database. For each dataset, we extracted expression profiles for two cell types. We then provided these expression profiles along with the cell types to our proposed constrained optimization problem of a support vector machine and to other existing methods, selecting important genes from the expression profiles. Finally, we performed (1) an evaluation from a classification perspective which showed the superiority of our methods against the baseline; and (2) an enrichment analysis which indicated that our methods achieved better outcomes. Results for the three datasets included 44 unique genes and 10 unique transcription factors (SP1, HDAC1, EGR1, E2F1, AR, STAT6, RELA, SP3, NFKB1, and ESR1) which are reportedly related to pancreatic islet functions, diseases, and therapeutic targets.
Light-dependent modulation of protein localization and function in living bacteria cells
Authors: McQuillen Ryan , Yang Xinxing , Bohrer Christopher H. , McCausland Joshua W. , Xiao Jie
Published: May 2022

Most bacteria lack membrane-enclosed organelles to compartmentalize cellular processes. In lieu of physical compartments, bacterial proteins are often recruited to macromolecular scaffolds at specific subcellular locations to carry out their functions. Consequently, the ability to modulate a protein’s subcellular location with high precision and speed bears the potential to manipulate its corresponding cellular functions. Here we demonstrate that the CRY2/CIB1 system from Arabidopsis thaliana can be used to rapidly direct proteins to different subcellular locations inside live E. coli cells including the nucleoid, the cell pole, membrane, and the midcell division plane. We further show that such light-induced re-localization can be used to rapidly inhibit cytokinesis in actively dividing E. coli cells. Finally, we demonstrate that the CRY2/CIBN binding kinetics can be modulated by green light, adding a new dimension of control to the system.
Fc-engineered antibodies leverage neutrophils to drive control ofMycobacterium tuberculosis
Authors: Irvine Edward B. , Peters Joshua M. , Lu Richard , Grace Patricia S. , Sixsmith Jaimie , Wallace Aaron , Schneider Matthew , Shin Sally , Karpinski Wiktor , Hsiao Jeff C. , van Woudenbergh Esther , Casadevall Arturo , Bryson Bryan D. , Cavacini Lisa , Alter Galit , Fortune Sarah M.
Published: May 2022

Novel vaccination and therapeutic strategies are urgently needed to mitigate the tuberculosis (TB) epidemic. While extensive efforts have focused on potentiating cell-mediated immunity to controlMycobacterium tuberculosis(Mtb) infection, less effort has been invested in exploiting the humoral immune system to combatMtb. Emerging data point to a role for antibodies in microbial control ofMtb, however the precise mechanism(s) of this control remain incompletely understood. Here we took an antibody Fc-engineering approach to determine whether Fc-modifications could improve the ability of antibodies to restrictMtb, and to define Fc-mediated mechanism(s) antibodies leverage for this restriction. Using an antibody specific to the capsular polysaccharide α-glucan, we engineer a panel of Fc variants to augment or dampen select antibody effector functions, rationally building antibodies with enhanced capacity to promoteMtbrestriction in a human whole blood model of infection. Surprisingly, restrictive Fc-engineered antibodies driveMtbcontrol in a neutrophil, not monocyte, dependent manner. Using single cell RNA sequencing, we show that restrictive antibodies promote neutrophil survival and expression of cell intrinsic antimicrobial programs. These data provide a roadmap for exploiting Fc-engineered antibodies as a novel class of TB therapeutics able to harness the protective functions of neutrophils to achieve disease control.
Arc-Expressing Accessory Olfactory Bulb Interneurons Support Chemosensory Social Behavioral Plasticity
Authors: Zuk Kelsey E. , Cansler Hillary L. , Wang Jinxin , Meeks Julian P.
Published: May 2022

The accessory olfactory system (AOS) is critical for the development and expression of social behavior. The first dedicated circuit in the AOS, the accessory olfactory bulb (AOB), exhibits cellular and network plasticity in male and female mice after social experience. In the AOB, interneurons called internal granule cells (IGCs) express the plasticity-associated immediate-early gene Arc following intermale aggression or mating. Here, we sought to better understand how Arc-expressing IGCs shape AOB information processing and social behavior in the context of territorial aggression. We used “ArcTRAP” (Arc-CreERT2) transgenic mice to selectively and permanently label Arc-expressing IGCs following male-male resident-intruder interactions. Using whole-cell patch clamp electrophysiology, we found that Arc-expressing IGCs display increased intrinsic excitability for several days after a single resident-intruder interaction. Further, we found that Arc-expressing IGCs maintain this increased excitability across repeated resident-intruder interactions, during which resident mice increase or “ramp” their aggression. We tested the hypothesis that Arc-expressing IGCs participate in ramping aggression. Using a combination of ArcTRAP mice and chemogenetics (Cre-dependent hM4D(Gi)-mCherry AAV injections), we found that disruption of Arc-expressing IGC activity during repeated resident-intruder interactions abolishes the ramping aggression exhibited by resident male mice. This work shows that Arc-expressing AOB IGC ensembles are activated by specific chemosensory environments, and play an integral role in the establishment and expression of sex-typical social behavior. These studies identify a population of plastic interneurons in an early chemosensory circuit that display physiological features consistent with simple memory formation, increasing our understanding of central chemosensory processing and mammalian social behavior.

Significance statement

The accessory olfactory system (AOS) plays a vital role in rodent chemosensory social behavior. We studied experience-dependent plasticity in the accessory olfactory bulb (AOB) and found that internal granule cells (IGCs) expressing the immediate-early gene Arc after the resident-intruder paradigm increase their excitability for several days. We investigated the roles of these Arc-expressing IGCs on chemosensory social behavior by chemogenetically manipulating their excitability during repeated social interactions. We found that inhibiting these cells eliminated intermale aggressive ramping behavior. These studies identify a population of plastic interneurons in an early chemosensory circuit that display physiological features consistent with simple memory formation, increasing our understanding of central chemosensory processing and mammalian social behavior.
Microbiome signatures inAcropora cervicornisare associated with genotypic resistance to elevated nutrients and heat stress
Authors: Palacio-Castro Ana M. , Rosales Stephanie M. , Dennison Caroline E. , Baker Andrew C.
Published: May 2022

The staghorn coral,Acropora cervicornis, was once abundant in the Caribbean, but now is listed as critically endangered. To recoverA. cervicornispopulations, restoration efforts have focused on preserving genetic diversity and increasing coral cover. However, identifying stress-resistant corals can help to increase restoration success, by allocating genotypes to reefs where they are more likely to survive. We assessed the performance (growth, survivorship, and photochemical efficiency) and characterized the microbiome (prokaryotes) of sixA. cervicornisgenotypes that were maintained at control temperatures (~26 °C) and either ambient nutrients or elevated nutrients (elevated NH4, and elevated NH4+ PO4) for > 2 months. We then compared how these parameters changed when the corals were exposed to heat-stress (3-weeks at ~31.5 °C). We found that exposure to elevated nutrients reducedA. cervicornisperformance under control temperatures and heat stress. However, there was a wide range of variation among genotypes, with three genotypes maintaining relatively higher survivorship and growth rates when exposed to nutrients alone, and nutrients followed by heat stress. Heat stress alone changed the microbial composition among genotypes more than elevated nutrients alone, but heat stress also interacted with nutrient pre-exposure to affect microbial communities. The relative abundance ofMidichloriaceaeandSpirochaetaceaevaried by coral genotype and a high abundance of these bacterial taxa was a positive predictor of coral survivorship rate, suggesting a microbial signature that could aid in identifying resistantA. cervicornisgenotypes. Our findings suggest there is significant variation among genotypes in the response ofA. cervicornisto elevated nutrients and temperatures. Resistant genotypes may be identifiable via their microbiomes and prioritized for outplanting at sites characterized by high levels of nutrient pollution. Large-scale microbiome screening may help expedite targeted outplanting and could be tested and extended to facilitate the identification of genotypes with other resistance characteristics.
Characterization and mu opioid receptor sensitivity of neuropeptide Y interneurons in the nucleus accumbens
Authors: Retzlaff Cassandra L. , Rothwell Patrick E.
Published: May 2022

Inhibitory interneurons represent less than 5% of neurons within the nucleus accumbens, but are critical for proper microcircuit function within this brain region. In the dorsal striatum, neuropeptide Y is expressed by two interneuron subtypes (low-threshold spiking interneurons and neurogliaform interneurons) that exhibit mu opioid receptor sensitivity in other brain regions. However, few studies have assessed the molecular and physiological properties of neuropeptide Y interneurons within the nucleus accumbens. We used a transgenic reporter mouse to identify and characterize neuropeptide Y interneurons in acute nucleus accumbens brain slices. Nearly all cells exhibited electrophysiological properties of low-threshold spiking interneurons, with almost no neurogliaform interneurons observed among neuropeptide Y interneurons. We corroborated this pattern using fluorescent in situ hybridization, and also identified a high level of mu opioid receptor expression by low-threshold spiking interneurons, which led us to examine the functional consequences of mu opioid receptor activation in these cells using electrophysiology. Mu opioid receptor activation caused a reduction in the rate of spontaneous action potentials in low-threshold spiking interneurons, as well as a decrease in optogenetically-evoked GABA release onto medium spiny neurons. The latter effect was more robust in female versus male mice, and when the postsynaptic medium spiny neuron expressed the Drd1 dopamine receptor. This work is the first to examine the physiological properties of neuropeptide Y interneurons in the nucleus accumbens, and show they may be an important target for mu opioid receptor modulation by endogenous and exogenous opioids.
TIR-catalyzed ADP-ribosylation reactions produce signaling molecules for plant immunity
Authors: Jia Aolin , Huang Shijia , Song Wen , Wang Junli , Meng Yonggang , Sun Yue , Xu Lina , Laessle Henriette , Jirschitzka Jan , Hou Jiao , Zhang Tiantian , Yu Wenquan , Hessler Giuliana , Li Ertong , Ma Shoucai , Yu Dongli , Gebauer Jan , Baumann Ulrich , Liu Xiaohui , Han Zhifu , Chang Junbiao , Parker Jane E. , Chai Jijie
Published: May 2022

Plant pathogen-activated immune signaling by nucleotide-binding leucine-rich repeat (NLR) receptors with an N-terminal Toll/Interleukin-1 receptor (TIR) domain converges on Enhanced Disease Susceptibility 1 (EDS1) and its direct partners Phytoalexin Deficient 4 (PAD4) or Senescence-Associated Gene 101 (SAG101). TIR-encoded NADases produce signaling molecules to promote exclusive EDS1-PAD4 and EDS1-SAG101 interactions with helper NLR sub-classes. Here we show that TIR-containing proteins catalyze adenosine diphosphate (ADP)-ribosylation of adenosine triphosphate (ATP) and ADP ribose (ADPR) via ADPR polymerase-like and NADase activity, forming ADP-ribosylated ATP (ADPr-ATP) and ADPr-ADPR (di-ADPR), respectively. Specific binding of di-ADPR or ADPr-ATP allosterically promotes EDS1-SAG101 interaction with helper NLR N requirement gene 1A (NRG1A)in vitroandin planta. Our data reveal an enzymatic activity of TIRs that enables specific activation of the EDS1-SAG101-NRG1 immunity branch.
The global randomization test: A Mendelian randomization falsification test for the exclusion restriction assumption
Authors: Millard Louise AC , Smith George Davey , Tilling Kate
Published: May 2022

Mendelian randomization may give biased causal estimates if the instrument affects the outcome not solely via the exposure of interest (violating the exclusion restriction assumption). We demonstrate use of a global randomization test as a falsification test for the exclusion restriction assumption. Using simulations, we explored the statistical power of the randomization test to detect an association between a genetic instrument and a covariate set due to a) selection bias or b) horizontal pleiotropy, compared to three approaches examining associations with individual covariates: i) Bonferroni correction for the number of covariates, and ii) correction for the effective number of independent covariates and iii) an r2 permutation-based approach. We conducted proof-of-principle analyses in UK Biobank, using CRP as the exposure and coronary heart disease (CHD) as the outcome. In simulations, power of the randomization test was higher than the other approaches for detecting selection bias when the correlation between the covariates was low (R2< 0.1), and at least as powerful as the other approaches across all simulated horizontal pleiotropy scenarios. In our applied example, we found strong evidence of selection bias using all approaches (e.g., global randomization test p<0.002). We identified 51 of the 58 CRP genetic variants as horizontally pleiotropic, and estimated effects of CRP on CHD attenuated somewhat to the null when excluding these from the genetic risk score (OR=0.956 [95% CI: 0.918, 0.996] versus 0.970 [95% CI: 0.900, 1.046] per 1-unit higher log CRP levels). The global randomization test can be a useful addition to the MR researcher’ s toolkit.
Craniodental traits predict feeding performance and dietary hardness in a community of Neotropical free‐tailed bats (Chiroptera: Molossidae)
Authors: Villalobos‐Chaves David , Santana Sharlene E.
Published: May 2022

Form–function studies have established a strong link between dental morphology and the mechanical properties of food items, with animals evolving tooth shapes theoretically ideal for their diets. However, information on how teeth perform under natural conditions is rare, which limits the understanding of how dental morphology influences dietary ecology and niche partitioning within animal communities.

Free‐tailed bats (Chiroptera: Molossidae) are a diverse clade of aerial insectivorous mammals that exhibit an outstanding variation in size and craniodental traits, which have been directly related to ecological segregation among sympatric species.

We investigate the mechanisms that allow functional dietary specialization and trophic segregation among sympatric free‐tailed bat species inhabiting a Neotropical forest. To do so, we coupled data on 3D dental topographic metrics, head and skull dimensions, field‐collected feeding performance and dietary hardness measurements.

We found that evolved differences in molar topography and skull size vary in tandem with the mechanical demands of prey items naturally consumed by sympatric molossid species. This may be explained by feeding performance capabilities resulting from both molar shape and the overall size of the feeding apparatus, which seem to allow efficient processing of prey items with specific mechanical properties. For instance, smaller bats with higher molar topographic values (sharper, more complex molars) and more gracile heads mainly feed on softer insects, whereas bigger bats with lower molar topographic values (blunter, less complex molars) and more robust heads mostly feed on tougher insects. Species with a broader range of sizes, craniodental morphologies and insect hardness are also present in the community.

These results illustrate how the morphology and size of feeding structures, and how they perform, may facilitate trophic segregation among sympatric insectivorous bats. Similar mechanisms may help structure other communities of insectivorous mammals, therefore the approaches presented here could be used to generate a better understanding of the ecomorphological traits and processes that underlie their diversity.

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