bluuebunny/crossref_metadata_2025 huggingface dataset:
COVID-19 or seasonal influenza? How to distinguish in people younger than 65 years old — — A retrospective observational cohort study comparing the 2009 pandemic influenza A H1N1 with 2022 SARS-CoV-2 Omicron BA.2 outbreaks in China
Authors: Zhong Wen , Wu Yisong , Yue Wenxiang , Fang Jiabin , Xie Baosong , Xu Nengluan , lin Ming , Zhu Xiongpeng , Su Zhijun , Chen Yusheng , Li Hong , Li Hongru
Published: March 2023

Objective

This study attempted to explore the difference of clinical characteristics in H1N1 influenza infection and SARS-CoV-2 Omicron infection in people younger than 65 years old, in order to better identify the two diseases.

Methods

A total of 127 H1N1 influenza patients diagnosed from May 2009 to July 2009 and 3265 patients diagnosed and identified as SARS-CoV-2 Omicron BA.2 variant from March 2022 to May 2022 were admitted in this study. Through the 1 : 2 match based on age (The difference is less than 2 years), gender and underlying diseases, 115 patients with H1N1 infection and 230 patients with SARS-CoV-2 Omicron BA.2 infection(referred to as H1N1 group and Omicron group) were included in the statistics. The clinical manifestations of H1N1 group were compared with those of Omicron group. Logistic regression was performed to analyze the possible independent risk factors of H1N1 group and Omicron group. And multiple linear regression was used to analyze the factors for time for nucleic acid negativization (NAN).

Results

The median age of the two groups was 21 [11,26] years. Compared with the H1N1 group, the Omicron group had lower white blood cell count and CRP levels, less fever, nasal congestion, sore throat, cough, sputum and headache, while more olfactory loss, muscle soreness and LDH abnormalities. The Omicron group used less antibiotics and antiviral drugs, and the NAN time was longer (17 [14,20] VS 4 [3,5], P < 0.001). After logistic regression, it was found that fever, cough, headache, and increased white blood cell count were more correlated with the H1N1 group, while muscle soreness and LDH abnormalities were more correlated with the Omicron group. After analyzing the factors of NAN time, it was found that fever (B 1.529, 95 % CI [0.149,2.909], P = 0.030) significantly predicted longer NAN time in Omicron patients.

Conclusion

This study comprehensively evaluated the similarities and differences in clinical characteristics between SARS-CoV-2 Omicron infection and 2009 H1N1 influenza infection, which is of great significance for a better understanding for these diseases.
The Bacterial Profile and Antibiotic Susceptibility Pattern in Respiratory Tract Samples from ART-Experienced HIV-Positive Adults in Uganda
Authors: Gloria Lubega , Andrew Abaasa , Ochola Willyfred , Kikaire Bernard , Lutaakome Joseph , Rugazira Eugene , Mayanja Yunia
Published: March 2023

Introduction

Microbial infections are a major cause of morbidity and mortality among people living with HIV (PLWH). Respiratory tract infections (RTIs) are responsible for approximately 70% of illnesses among PLWH. Drug resistant bacteria are highly prevalent among PLWH and this is a public health concern.

Methods

This is a retrospective analysis of data collected during the COSTOP trial between 2011 and 2013. Sputum collected on spot from participants presenting with a productive cough was examined using Gram, Ziehl-Neelsen stains and cultured on suitable bacteriological media. Antimicrobial sensitivity testing was done on isolated pathogens, by disc diffusion technique.

Results

We included 687 participants with mean age 41.3 (SD 8.2) years of whom 76.4% were female. Two hundred one sputum samples grew bacteria;Moraxella species(27.4%),Streptococcus pneumoniae(25.4%),Haemophilus influenza(22.4%),Mycobacterium species(4.5%),Pseudomonas species(4.0%),Staphylococcus aureus(4.0%),Escherichia coli(1.0%),Klebsiella species(1.0%), other bacteria (10.4%). A higher monthly income greater than or equal to 30$ (aOR= 0.63, 95%CI: 0.40-0.99) and longer duration since HIV diagnosis (aOR= 1.06, 95%CI: 1.0-1.11) were found to be independently associated with a positive bacterial culture. Moraxellasp, H.influenzaand Pseudomonas had zero sensitivity towards cotrimoxazole. Sensitivity to erythromycin was low among Moraxellasp(28.6%), H.influenza(31.6%) and S.aureus(42.9%) and other bacteria (42.9%). Most isolates were sensitive to Amoxicillin + Clavulanic acid and ceftriaxone.

Conclusion

There is a very low sensitivity of isolated bacteria to commonly prescribed antibiotics that are more available through the national supply chain, which is of public health concern. Urgent steps to tackle the high antimicrobial resistance among PLWH is required.
Functional brain changes after pharmacological interventions in post-traumatic stress disorder: A systematic review of clinical trials
Authors: Lotfinia Shahab , Afshar Amin , Yaseri Aram , Olff Miranda , Quidé Yann
Published: March 2023

Background

Posttraumatic stress disorder (PTSD) is a complex and heterogeneous mental health condition that can develop after exposure to a traumatic event. Clinical trials have used new pharmacological agents to treat PTSD, but their associated neural correlates remain unclear. The present systematic review aims to summarise the changes in brain function associated with the use these pharmacological agents in PTSD.

Methods

Clinical trials using functional magnetic resonance imaging (fMRI), either at rest or during the performance of tasks, were included if they compared the effects of pharmacological agents in patients with PTSD to either trauma-exposed controls or never exposed to trauma healthy controls.

Results

Twelve studies were included, of which eight used intranasal oxytocin, two used hydrocortisone, and one used Tolcapone. Oxytocin administration was associated with normalisation of functional connectivity between the ventromedial prefrontal cortex and amygdala, as well as enhanced the function of brain regions specifically involved in emotion processing (e.g., amygdala), working memory (e.g., dorsolateral prefrontal cortex), reward (putamen). Hydrocortisone did not influence brain function at rest or during the performance of an autobiographical memory task, while tolcapone was associated with increased function in frontal, parietal and striatal regions during the performance of an emotional working memory task.

Conclusions

This systematic review identified preliminary evidence for normalizing brain function after use of alternative pharmacological agents to first-line pharmacological treatments.
Bounds on the Ultrasensitivity of Biochemical Reaction Cascades
Authors: Pajoh-Casco Marcello , Vinujudson Abishek , Enciso German
Published: March 2023

The ultrasensitivity of a dose response function can be quantifiably defined using the generalized Hill coefficient of the function. Our group examined an upper bound for the Hill coefficient of the composition of two functions, namely the product of their individual Hill coefficients. We proved that this upper bound holds for compositions of Hill functions, and that there are instances of counterexamples that exist for more general sigmoidal functions. Additionally, we tested computationally other types of sigmoidal functions, such as the logistic and inverse trigonometric functions, and we provided evidence that in these cases the inequality also holds. We show that in large generality there is a limit to how ultrasensitive the composition of two functions can be, which has applications to understanding signaling cascades in biochemical reactions.
Modeling functional cell types in spike train data
Authors: Zdeblick Daniel N. , Shea-Brown Eric T. , Witten Daniela M. , Buice Michael A.
Published: March 2023

A major goal of computational neuroscience is to build accurate models of the activity of neurons that can be used to interpret their function in circuits. Here, we explore usingfunctional cell typesto refine single-cell models by grouping them into functionally relevant classes. Formally, we define a hierarchical generative model for cell types, single-cell parameters, and neural responses, and then derive an expectation-maximization algorithm with variational inference that maximizes the likelihood of the neural recordings. We apply this “simultaneous” method to estimate cell types and fit single-cell models from simulated data, and find that it accurately recovers the ground truth parameters. We then apply our approach toin vitroneural recordings from neurons in mouse primary visual cortex, and find that it yields improved prediction of single-cell activity. We demonstrate that the discovered cell-type clusters are well separated and generalizable, and thus amenable to interpretation. We then compare discovered cluster memberships with locational, morphological, and transcriptomic data. Our findings reveal the potential to improve models of neural responses by explicitly allowing for shared functional properties across neurons.

Author Summary

Computational neuroscience has its roots in fitting and interpreting predictive models of the activity of individual neurons. In recent years, more attention has focused on models of how ensembles of neurons work together to perform computations. However, fitting these more complex models to data is challenging, limiting our ability to use them to understand real neural systems. One idea that has improved our understanding of populations of neurons iscell types, where neurons of the same type have similar properties. While the idea of cell types is old, recent work has focused on functional cell types, where the properties of interest are derived from fitted predictive models of the activity of single neurons. In this work, we develop a method thatsimultaneouslyfits a predictive model of each neuron’s activity and groups neurons into functional cell types. Compared to existing techniques, this method produces more accurate models of single-cell neural activity and better groupings of neurons into types. This method can thus contribute in using cell types to better understanding the components of neural systems based on our increasingly rich observations of their functional responses.
Simultaneous mapping of epigenetic inter-haplotype, inter-cell and inter-individual variation via the discovery of jointly regulated CpGs in pooled sequencing data
Authors: Planterose Jiménez Benjamin , Kolar Brontë , Kayser Manfred , Vidaki Athina
Published: March 2023

In the post-GWAS era, great interest has arisen in the mapping of epigenetic inter-individual variation towards investigating the emergence of phenotype in health and disease. Relevant DNA methylation methodologies – epigenome-wide association studies (EWAS), methylation quantitative traitloci(mQTL) mapping and allele-specific methylation (ASM) analysis – can each map certain sources of epigenetic variation and all depend on matching phenotypic/genotypic data. Here, to avoid these requirements, we developed Binokulars, a novel randomization test that identifies signatures of joint CpG regulation from reads spanning multiple CpGs. We tested and benchmarked our novel approach against EWAS and ASM on pooled whole-genome bisulfite sequencing (WGBS) data from whole blood, sperm and combined. As a result, Binokulars simultaneously discovered regions associated with imprinting, cell type- and tissue-specific regulation, mQTL, ageing and other (still unknown) epigenetic processes. To verify examples of mQTL and polymorphic imprinting, we developed JRC_sorter, another novel tool that classifies regions based on epigenotype models, which we deployed on non-pooled WGBS data from cord blood. In the future, this approach can be applied on larger pools to simultaneously map and characterise inter-haplotype, inter-cell and inter-individual variation in DNA methylation in a cost-effective fashion, a relevant pursuit towards phenome-mapping in the post-GWAS era.
Metabolomics investigation of post-mortem human pericardial fluid
Authors: Chighine Alberto , Stocchero Matteo , Ferino Giulio , De-Giorgio Fabio , Conte Celeste , Nioi Matteo , d’Aloja Ernesto , Locci Emanuela
Published: March 2023

Introduction

Due to its peculiar anatomy and physiology, the pericardial fluid is a biological matrix of particular interest in the forensic field. Despite this, the available literature has mainly focused on post-mortem biochemistry and forensic toxicology, while to the best of authors’ knowledge post-mortem metabolomics has never been applied. Similarly, estimation of the time since death or Post-Mortem Interval based on pericardial fluids has still rarely been attempted.

Objectives

We applied a metabolomic approach based on1H Nuclear Magnetic Resonance Spectroscopy to ascertain the feasibility of monitoring post-mortem metabolite changes on human pericardial fluids with the aim of building a multivariate regression model for Post-Mortem Interval estimation.

Methods

Pericardial fluid samples were collected in 24 consecutive judicial autopsies, in a time frame ranging from 16 to 170 hours after death. The only exclusion criterion was the quantitative and/or qualitative alteration of the sample. Two different extraction protocols were applied for low molecular weight metabolites selection, namely ultrafiltration and liquid-liquid extraction. Our metabolomic approach was based on the use of1H Nuclear Magnetic Resonance and multivariate statistical data analysis.

Results

The pericardial fluid samples treated with the two experimental protocols did not show significant differences in the distribution of the metabolites detected. A post-mortem interval estimation model based on 18 pericardial fluid samples was validated with an independent set of 6 samples, giving a prediction error of 33 - 34 hours depending on the experimental protocol used. By narrowing the window to post-mortem intervals below 100 hours, the prediction power of the model was significantly improved with an error of 13-15 hours depending on the extraction protocol. Choline, glycine, ethanolamine, and hypoxanthine were the most relevant metabolites in the prediction model.

Conclusion

The present study, although preliminary, shows that PF samples collected from a real forensic scenario represent a biofluid of interest for post-mortem metabolomics, with particular regard to the estimation of the time since death.
HIV-differentiated metabolite N-Acetyl-L-Alanine dysregulates human natural killer cell responses toMycobacterium tuberculosisinfection
Authors: Yang Baojun , Mukherjee Tanmoy , Radhakrishnan Rajesh , Paidipally Padmaja , Ansari Danish , John Sahana , Vankayalapati Ramakrishna , Tripathi Deepak , Yi Guohua
Published: March 2023

Background

Mycobacterium tuberculosis(Mtb) has latently infected over two billion people worldwide (LTBI) and causes 1.8 million deaths each year. Human immunodeficiency virus (HIV) co-infection with Mtb will affect the Mtb progression and increase the risk of developing active tuberculosis by 10-20 times compared to the HIV-LTBI+ patients. It is crucial to understand how HIV can dysregulate immune responses in LTBI+ individuals.

Methods

Plasma samples collected from healthy and HIV-infected individuals were investigated by liquid chromatography-mass spectrometry (LC-MS), and the metabolic data were analyzed using an online platform Metabo-Analyst. ELISA, surface and intracellular staining, flow cytometry, quantitative reverse transcription PCR (qRT-PCR) were performed by standard procedure to determine the surface markers, cytokines and other signaling molecule expression. Seahorse extra cellular flux assays were used to measure the mitochondrial oxidative phosphorylation and glycolysis.

Results

Six metabolites were significantly less abundant, and two were significantly higher in abundance in HIV+ individuals compared to healthy donors. One of the HIV-upregulated metabolites, N-Acetyl-L-Alanine (ALA), inhibits pro-inflammatory cytokine IFN-□ production by NK cells of LTBI+ individuals. ALA inhibits glycolysis of LTBI+ individuals’ NK cells in response toMtb.

Conclusions

Our findings demonstrate that HIV infection enhances plasma ALA levels to inhibit NK cell-mediated immune responses toMtbinfection, offering a new understanding of the HIV-Mtbinteraction and providing the implication of nutrition intervention and therapy for HIV-Mtbco-infected patients.
Coarse-Grained Molecular Simulations and Ensemble-Based Mutational Profiling of Protein Stability in the Different Functional Forms of the SARS-CoV-2 Spike Trimers : Balancing Stability and Adaptability in BA.1, BA.2 and BA.2.75 Variants
Authors: Verkhivker Gennady , Alshahrani Mohammed , Gupta Grace
Published: March 2023

The evolutionary and functional studies suggested that the emergence of the Omicron variants can be determined by multiple fitness trade-offs including the immune escape, binding affinity, conformational plasticity, protein stability and allosteric modulation. In this study, we embarked on a systematic comparative analysis of the conformational dynamics, electrostatics, protein stability and allostery in the different functional states of spike trimers for BA.1, BA.2, and BA.2.75 variants. Using efficient and accurate coarse-grained simulations and atomistic reconstruction of the ensembles, we examined conformational dynamics of the spike trimers that agrees with the recent functional studies, suggesting that BA.2.75 trimers are the most stable among these variants. A systematic mutational scanning of the inter-protomer interfaces in the spike trimers revealed a group of conserved structural stability hotspots that play a key role in modulation of functional dynamics and are also involved in the inter-protomer couplings through local contacts and interaction networks with the Omicron mutational sites. The results of mutational scanning provided evidence that BA.2.75 trimers are more stable than BA.2 and comparable in stability to BA.1 variant. Using dynamic network modeling of the S Omicron BA.1, BA.2 and BA.2.75 trimers we showed that the key network positions driving long-range signaling are associated with the major stability hotspots that are inter-connected along potential communication pathways, while sites of Omicron mutations may often correspond to weak spots of stability and allostery but are coupled to the major stability hotspots through interaction networks. The presented analysis of the BA.1, BA.2 and BA.2.75 trimers suggested that thermodynamic stability of BA.1 and BA.2.75 variants may be intimately linked with the residue interaction network organization that allows for a broad ensemble of allosteric communications in which signaling between structural stability hotspots may be modulated by the Omicron mutational sites. The findings provided plausible rationale for mechanisms in which Omicron mutations can evolve to balance thermodynamic stability and conformational adaptability in order to ensure proper tradeoff between stability, binding and immune escape.
Aging Atlas Reveals Cell-Type-Specific Regulation of Pro-longevity Strategies
Authors: Gao Shihong Max , Qi Yanyan , Zhang Qinghao , Mohammed Aaron S. , Lee Yi-Tang , Guan Youchen , Li Hongjie , Fu Yusi , Wang Meng C.
Published: March 2023

Organism aging occurs at the multicellular level; however, how pro-longevity mechanisms slow down aging in different cell types remains unclear. We generated single-cell transcriptomic atlases across the lifespan ofCaenorhabditis elegansunder different pro-longevity conditions (http://mengwanglab.org/atlas). We found cell-specific, age-related changes across somatic and germ cell types and developed transcriptomic aging clocks for different tissues. These clocks enabled us to determine tissue-specific aging-slowing effects of different pro-longevity mechanisms, and identify major cell types sensitive to these regulations. Additionally, we provided a systemic view of alternative polyadenylation events in different cell types, as well as their cell-type-specific changes during aging and under different pro-longevity conditions. Together, this study provides molecular insights into how aging occurs in different cell types and how they respond to pro-longevity strategies.
A live-cell platform to isolate phenotypically defined subpopulations for spatial multi-omic profiling
Authors: Khatib Tala O. , Amanso Angelica M. , Pedro Brian , Knippler Christina M. , Summerbell Emily R. , Zohbi Najdat M. , Konen Jessica M. , Mouw Janna K. , Marcus Adam I.
Published: March 2023

Numerous techniques have been employed to deconstruct the heterogeneity observed in normal and diseased cellular populations, including single cell RNA sequencing,in situhybridization, and flow cytometry. While these approaches have revolutionized our understanding of heterogeneity, in isolation they cannot correlate phenotypic information within a physiologically relevant live-cell state, with molecular profiles. This inability to integrate a historical live-cell phenotype, such as invasiveness, cell:cell interactions, and changes in spatial positioning, with multi-omic data, creates a gap in understanding cellular heterogeneity. We sought to address this gap by employing lab technologies to design a detailed protocol, termed Spatiotemporal Genomics and Cellular Analysis (SaGA), for the precise imaging-based selection, isolation, and expansion of phenotypically distinct live-cells. We begin with cells stably expressing a photoconvertible fluorescent protein and employ live cell confocal microscopy to photoconvert a user-defined single cell or set of cells displaying a phenotype of interest. The total population is then extracted from its microenvironment, and the optically highlighted cells are isolated using fluorescence activated cell sorting. SaGA-isolated cells can then be subjected to multi-omics analysis or cellular propagation forin vitroorin vivostudies. This protocol can be applied to a variety of conditions, creating protocol flexibility for user-specific research interests. The SaGA technique can be accomplished in one workday by non-specialists and results in a phenotypically defined cellular subpopulation for integration with multi-omics techniques. We envision this approach providing multi-dimensional datasets exploring the relationship between live-cell phenotype and multi-omic heterogeneity within normal and diseased cellular populations.
Integrating metabolic scaling and coexistence theories
Authors: Saavedra Serguei , Arroyo José Ignacio , Deng Jie , Marquet Pablo A. , Kempes Christopher P.
Published: March 2023

Metabolic scaling theory has been pivotal in formalizing the expected energy expenditures across populations as a function of body size. Coexistence theory has provided a mathematization of the tolerated effects of environmental perturbations on a given set of interacting populations as a function of interspecific interactions. Yet, it has been challenging to explain how coexistence patterns observed in ecological communities, such as the inverse relationship between population abundance and mean body size, can be unified under both theories. Here, we provide the foundation for a tractable, scalable, and extendable framework to study the coexistence of resource-mediated competing populations as a function of their mean body size. For a fixed thermal domain and response, this integration reveals that the metabolically predicted -3/4 power dependence of carrying capacity on body size specifies the distribution of environmental carrying capacities that tends to maximize the tolerance to random environmental perturbations within large communities. In line with empirical observations, our integration predicts that such a distribution leads to equilibrium biomasses that are independent from body size, and consequently, to equilibrium abundances that are inversely related to body size. This integration opens new opportunities to increase our understanding of how metabolic scaling relationships at the population level can shape processes at the community level.
Impact of in vivo cyclic reprogramming on the choroid plexus
Authors: Lopez Jessica Avila , Abboud Clauda , Ibrahim Maged , Ahumada Javier Rocha , Avino Mariano , Plourde Mélanie , Fernandes Karl , Bentzinger C. Florian , Laurent Benoit
Published: March 2023

In vivo reprogramming using the transient expression of Oct3/4, Sox2, Klf4 and c□Myc (OSKM) transcription factors can be used to induce tissue regeneration. A cyclic regime for short□term OSKM expression has been shown to promote regeneration of several organs however its impact on the brain remains largely unknown. We investigated the effects of a cyclic short-term OSKM expression on the choroid plexus (CP), a highly vascularized tissue found within the brain ventricles which is responsible for producing the cerebrospinal fluid (CSF). Transient reprogramming was done on 8-week-old mice carrying the polycistronic OSKM cassette under tetracycline operator (tetO) and confirmed the successful transient reprogramming. We then performed the analysis of the CP at cellular and molecular levels. The CP tissue exhibited minor morphological changes in height and area of epithelial cells. We did not observe any significant differences in the integrity of the brain-CSF barrier but noticed an increase of NKCC1 expression, a protein involved in CSF production. A whole transcriptome analysis (RNA-seq) was also carried on the tissue and showed no difference in gene expression after the transient reprogramming, at the exception of blood-related genes. Our results indicate that surprisingly the CP mainly remains insensible to in vivo transient reprogramming as only morphological and protein changes were observed in the tissue, suggesting that translational changes might be at stake during the reprogramming process but are not present at the transcriptomic level. Our results also highlight that more tailored strategies need to be developed for exploring the potential of CP reprogramming in regenerative medicine.
Cerebellar Activity in PINK1 Knockout Rats during Volitional Gait
Authors: DeAngelo Valerie , Hilliard Justin D , Chiang Chia-Han , Viventi Jonathan , McConnell George C
Published: March 2023

Preclinical models of Parkinson’s disease are imperative to gain insight into the neural circuits that contribute to gait dysfunction in advanced stages of the disease. The PTEN-induced putative kinase 1 (P1) knockout (KO) early onset model of Parkinson’s disease may be a useful rodent model to study the effects of neurotransmitter degeneration caused by loss of P1 function on brain activity during volitional gait. The goal of this study was to measure changes in neural activity at the cerebellar vermis (CBLv) at 8 months of age. Gait deficits, except run speed, were not significantly different from age-matched wild-type (WT) controls as previously reported. P1KO (n=4) and WT (n=4) rats were implanted with a micro-electrocorticographic array placed over CBLv lobules VI (a, b, and c) and VII. Local field potential recordings were obtained during volitional gait across a runway. Power spectral analysis and coherence analysis were used to quantify network oscillatory activity in frequency bands of interest. CBLv power was hypoactive in the beta (VIb, VIc, and VII) and alpha (VII) bands at CBLv lobules VIb, VIc, and VII in P1KO rats compared to WT controls during gait (p<0.05). These results suggest that gait improvement in P1KO rats at 8 months may be a compensatory mechanism attributed to movement corrections caused by decreased inhibition of the alpha band of CBLv lobule VII and beta band of lobules VIb, VIc, and VII. The P1KO model may be a valuable tool for understanding the circuit mechanisms underlying gait dysfunction in early-onset Parkinson’s disease patients with functional loss of P1. Future studies investigating the CBLv as a potential biomarker and therapeutic target for the treatment of gait dysfunction in Parkinson’s disease are warranted.
Personalized Risk Prediction for Cancer Survivors: A Bayesian Semi-parametric Recurrent Event Model with Competing Outcomes
Authors: Nguyen Nam H , Shin Seung Jun , Dodd-Eaton Elissa B , Ning Jing , Wang Wenyi
Published: March 2023

Multiple primary cancers are increasingly more frequent due to improved survival of cancer patients. Characteristics of the first primary cancer largely impact the risk of developing subsequent primary cancers. Hence, model-based risk characterization of cancer survivors that captures patient-specific variables is needed for healthcare policy making. We propose a Bayesian semi-parametric framework, where the occurrence processes of the competing cancer types follow independent non-homogeneous Poisson processes and adjust for covariates including the type and age at diagnosis of the first primary. Applying this framework to a historically collected cohort with families presenting a highly enriched history of multiple primary tumors and diverse cancer types, we have derived a suite of age-to-onset penetrance curves for cancer survivors. This includes penetrance estimates for second primary lung cancer, potentially impactful to ongoing cancer screening decisions. Using Receiver Operating Characteristic (ROC) curves, we have validated the good predictive performance of our models in predicting second primary lung cancer, sarcoma, breast cancer, and all other cancers combined, with areas under the curves (AUCs) at 0.89, 0.91, 0.76 and 0.68, respectively. In conclusion, our framework provides covariate-adjusted quantitative risk assessment for cancer survivors, hence moving a step closer to personalized health management for this unique population.
Drug-tolerant persister B-cell precursor acute lymphoblastic leukemia cells
Authors: Zhang Mingfeng , Yang Lu , Chen David , Heisterkamp Nora
Published: March 2023

Reduced responsiveness of precursor B-acute lymphoblastic leukemia (BCP-ALL) to chemotherapy can be inferred when leukemia cells persist after 28 days of initial treatment. Survival of these long-term persister (LTP) / minimal residual disease (MRD) cells is partly due to bone marrow stromal cells that protect them under conditions of chemotherapy stress. We used RNA-seq to analyse BCP-ALL cells that survived a long-term, 30-day vincristine chemotherapy treatment while in co-culture with bone marrow stromal cells. RNAs of as many as 10% of the protein-encoding genes were differentially expressed. There was substantial overlap with genes associated with MRD cell persistence reported in other studies. The top pathway regulated in the LTP cells was that involving p53, a master regulator of a spectrum of responses relevant to drug resistance and cytotoxic drug exposure including control of autophagy. We tested a select number of genes for contribution to BCP-ALL cell survival using Cas9/CRISPR in a 2-step selection, initially for overall effect on cell fitness, followed by 21 days of exposure to vincristine. Many genes involved in autophagy and lysosomal function were found to contribute to survival both at steady-state and during drug treatment. We also identified MYH9, NCSTN and KIAA2013 as specific genes contributing to fitness of BCP-ALL cells. CD44 was not essential for growth under steady state conditions but was needed for survival of vincristine treatment. Finally, although the drug transporter ABCC1/MRP1 is not overexpressed in BCP-ALL, a functional gene was needed for DTP cells to survive treatment with vincristine. This suggests that addition of possible ABCC1 inhibitors during induction therapy could provide benefit in eradication of minimal residual disease in patients treated with a chemotherapy regimen that includes vincristine.
Boundary updating as a source of history effect on decision uncertainty
Authors: Lee Heeseung , Lee Sang-Hun
Published: March 2023

When sorting a sequence of stimuli into binary classes, current choices are often negatively correlated with recent stimulus history. This phenomenon—dubbed the repulsive bias—can be explained by boundary updating, a process of shifting the class boundary to previous stimuli. This explanation implies that recent stimulus history can also influence “decision uncertainty,” the probability of making incorrect decisions, since it depends on the location of the boundary. However, there have been no previous efforts to elucidate the impact of previous stimulus history on decision uncertainty. Here, from the boundary-updating process that accounts for the repulsive bias, we derived a prediction that decision uncertainty increases as current choices become more congruent with previous stimuli. We confirmed this prediction in behavioral, physiological, and neural correlates of decision uncertainty. Our work demonstrates that boundary updating offers a principled account of how previous stimulus history concurrently relates to choice bias and decision uncertainty.
OsNLP3/4-OsRFL module regulates nitrogen-promoted panicle architecture in rice
Authors: Wu Jie , Sun Liang-Qi , Zhang Zi-Sheng , Song Ying , Bai Yu , Wan Guang-Yu , Wang Jing-Xian , Xia Jin-Qiu , Zhang Zheng-Yi , Xiang Cheng-Bin
Published: March 2023

Rice panicles, a major component of yield, are regulated by phytohormones and nutrients. How mineral nutrients promote panicle architecture remains largely unknown. Here, we report that NIN-LIKE PROTEIN3 and 4 (OsNLP3/4) are crucial positive regulators of rice panicle architecture in response to nitrogen (N). Loss-of- function mutants of eitherOsNLP3orOsNLP4produced smaller panicles with reduced primary and secondary branches and fewer grains compared with wild type, whereas their overexpression plants showed the opposite phenotypes. Notably, the OsNLP3/4-regulated panicle architecture was positively correlated with N availability. OsNLP3/4 directly bind to the promoter ofOsRFLand activate its expression to promote inflorescence meristem development. Furthermore, OsRFL activatesOsMOC1expression by binding to its promoter. Our findings reveal the novel N- responsive OsNLP3/4-OsRFL-OsMOC1 module that integrates N availability to regulate panicle architecture, shedding light on how nutrient signals regulate panicle architecture and providing candidate targets for the improvement of crop yield.
Migration and establishment of progenitor pool of melanocytes is governed by SEMA3E-PLXND1 signaling
Authors: Subramaniam Yogaspoorthi , Sharma Babita , Aggarwal Ayush , Raja Desingu Ayyappa , Gupta Iti , Ghazi Madeeha , Sivasubbu Sridhar , Natarajan Vivek T
Published: March 2023

Vertebrate pigmentation is an outcome of an interplay of several signaling pathways that result in immense diversity of pigment patterns observed across the animal kingdom. Transitory nature of these signaling events impedes deciphering pathways that control migration and establishment of melanocyte stem cells (McSC), necessary for pigment patterning. Using zebrafish and cultured mammalian melanocytes, we uncover a hitherto unknown role for Plexin D1 signaling. This pathway directs migration by F-actin modulation and further dictates subsequent functional states of melanocytes through a transcriptional response. In zebrafish, abrogation of PLXND1 derails melanocyte migration and reduces mid-line melanophores emerging from the regeneration competent McSC pool. In cultured melanocytes, activation of PLXND1 by the ligand semaphorin 3E reduces the velocity of migration, influences directional correlation, and promotes movement towards positive cues such as SCF. PLXND1 activation results in EGFR signaling necessary for McSC establishment, and induces GNAS, an effector of MC1R pathway involved in melanocyte maturation. Identification of this long-range secreted negative chemotactic signaling provides a missing player and enriches reaction diffusion model for pigment patterning.
Early Detection of Lung Cancer in the NLST Dataset*
Authors: Mukherjee Pritam , Brezhneva Anna , Napel Sandy , Gevaert Olivier
Published: March 2023

Lung Cancer is the leading cause of cancer mortality in the U.S. The effectiveness of standard treatments, including surgery, chemotherapy or radiotherapy, depends on several factors like type and stage of cancer, with the survival rate being much worse for later cancer stages. The National Lung Screening Trial (NLST) established that patients screened using low-dose Computed Tomography (CT) had a 15 to 20 percent lower risk of dying from lung cancer than patients screened using chest X-rays. While CT excelled at detecting small early stage malignant nodules, a large proportion of patients (>25%) screened positive and only a small fraction (<10%) of these positive screens actually had or developed cancer in the subsequent years. We developed a model to distinguish between high and low risk patients among the positive screens, predicting the likelihood of having or developing lung cancer at the current time point or in subsequent years non-invasively, based on current and previous CT imaging data. However, most of the nodules in NLST are very small, and nodule segmentations or even precise locations are unavailable. Our model comprises two stages: the first stage is a neural network model trained on the Lung Image Database Consortium (LIDC-IDRI) cohort which detects nodules and assigns them malignancy scores. The second part of our model is a boosted tree which outputs a cancer probability for a patient based on the nodule information (location and malignancy score) predicted by the first stage. Our model, built on a subset of the NLST cohort (n= 1138) shows excellent performance, achieving an area under the receiver operating characteristics curve (ROC AUC) of 0.85 when predicting based on CT images from all three time points available in the NLST dataset.
A whole blood-based transcriptional risk score for nonobese type 2 diabetes predicts dynamic changes in glucose metabolic traits
Authors: Hou Yanan , Dai Huajie , Chen Na , Zhao Zhiyun , Wang Qi , Hou Tianzhichao , Zheng Jie , Wang Tiange , Li Mian , Lin Hong , Wang Shuangyuan , Zheng Ruizhi , Lu Jieli , Xu Yu , Chen Yuhong , Liu Ruixin , Ning Guang , Wang Weiqing , Bi Yufang , Wang Jiqiu , Xu Min
Published: March 2023

Background

The performance of peripheral blood transcriptional markers in evaluating the risk of type 2 diabetes (T2D) with normal weight is unknown. We developed a whole blood-based transcriptional risk score (wb-TRS) for nonobese T2D and assessed its contributions to disease risk and dynamic changes in glucose metabolism.

Methods and findings

We developed the wb-TRS in 1105 participants aged ≥40 years and in normal weight for up to 10 years from a well-defined community-based cohort with blood transcriptome data and validated it in an external dataset (253 overweight/obese participants from a dietary intervention trial with 3 repeated transcriptome data). Potential biology significance and causal inference were also explored. The wb-TRS included 144 transcripts. Compared to the lowest tertile, wb-TRS in tertile 3 associated with 8.68-folds (95% confidence interval [CI], 3.51-21.5), and each 1-unit increment associated with 2.57-folds (95% CI, 1.86-3.56) higher risk of nonobese T2D, after adjustments for traditional risk factors. Furthermore, baseline wb-TRS was significantly associated with dynamic changes in average, daytime, nighttime and 24h glucose and HbA1c, and area under the curve of glucose measured in the continuous glucose monitoring during 6-month of intervention. The wb-TRS improved the predicting performance for nonobese T2D in a model with fasting glucose, triglycerides and demographic and anthropometric parameters. Mitch analysis implicated oxidative phosphorylation, cholesterol metabolism and mTORC1 signaling involved in nonobese T2D pathogenesis. Transcriptome-wide Mendelian randomization supported causal effects of gene transcripts such as RAB1A and GCC1-PAX4 on nonobese T2D risk.

Conclusions

A whole blood based nonobese T2D associated TRS was validated to predict dynamic changes in glucose metabolism. These findings also suggested several genes and biological pathways that might involve in the pathogenesis of nonobese T2D.
Sedentary time in adults with cystic fibrosis: A prospective observational cross-sectional study
Authors: Bishop Ines , Cobb Robyn , Hall Kathleen , Kuys Suzanne
Published: March 2023

Objective

Adults with cystic fibrosis remain susceptible to comorbidities associated with high sedentary time, increasing their risk of poor health outcomes. Evidence about sedentary time in adults with cystic fibrosis is limited. This study investigated sedentary time and physical activity in adults with cystic fibrosis across disease severity groups and the relationship with clinical measures.

Methods

A SenseWear armband was worn by adults with cystic fibrosis, measuring sedentary time, time spent in moderate-vigorous physical activity and steps per day. Lung function, quadriceps strength, exercise capacity and health-related quality of life were assessed.

Results

On average, the armband was worn for 20 hours (Standard Deviation (SD) 6) over 6 (SD 1) days. Forty-eight participants (28 males) spent 815 (SD 379) minutes sedentary, 137 (SD 13) minutes engaged in moderate-vigorous physical activity and took 5660 (SD 2749) steps per day. Sedentary time did not vary across disease severity groups nor correlate with clinical measures.

Conclusions

Adults with cystic fibrosis spent a large proportion of time in sedentary behaviours, took insufficient steps, but conversely engaged in sufficient moderate-vigorous physical activity. Targeted interventions to break up sedentary time are required to reduce the risk of adverse health outcomes in this population.

Impact

Adults with cystic fibrosis spend a large proportion of their time sedentary, placing them at risk of future metabolic disorders. Interventions to break up sedentary time are needed.
Domain-adaptive neural networks improve supervised machine learning based on simulated population genetic data
Authors: Mo Ziyi , Siepel Adam
Published: March 2023

Investigators have recently introduced powerful methods for population genetic inference that rely on supervised machine learning from simulated data. Despite their performance advantages, these methods can fail when the simulated training data does not adequately resemble data from the real world. Here, we show that this “simulation mis-specification” problem can be framed as a “domain adaptation” problem, where a model learned from one data distribution is applied to a dataset drawn from a different distribution. By applying an established domain-adaptation technique based on a gradient reversal layer (GRL), originally introduced for image classification, we show that the effects of simulation mis-specification can be substantially mitigated. We focus our analysis on two state-of-the-art deep-learning population genetic methods—SIA, which infers positive selection from features of the ancestral recombination graph (ARG), and ReLERNN, which infers recombination rates from genotype matrices. In the case of SIA, the domain adaptive framework also compensates for ARG inference error. Using thedomain-adaptive SIA (dadaSIA) model, we estimate improved selection coefficients at selected loci in the 1000 Genomes CEU population. We anticipate that domain adaptation will prove to be widely applicable in the growing use of supervised machine learning in population genetics.

Author Summary

Population genetic simulation is a powerful tool in the study of evolution. A number of supervised machine learning methods have been developed that take advantage of inexpensive simulations as training data. Despite their outstanding performance in benchmarks, these models can fail when the simulated training data deviate from the real data. In this work, we employed domain adaptation techniques to address this “simulation mis-specification” problem by training the machine learning model jointly with simulated and real data. We performed extensive benchmark experiments to demonstrate the improvement of the domain-adaptive models over standard machine learning models in the presence of different types of mis-specification. In addition, we applieddadaSIA, a domain-adaptive selection inference model, to improve the estimates of selection coefficients at selected loci in a European population. The domain adaptation framework proposed in our work is widely applicable to models relying on synthetic training data and therefore opens the door to many more applications in population genetics.
Title: AKI and CKD Worsen Outcomes in Experimental Sepsis: Creating a Reverse-translational Model of Acute Peritoneal Infection and Recovery in an Immunocompromised Rodent
Authors: Floyd Deana F. , Colbert James T. , Furgeson Seth B. , Montford John R
Published: March 2023

Introduction

Infection is a leading cause of morbidity and mortality in individuals with kidney disease. Both acute kidney injury (AKI), and chronic kidney disease (CKD) are clinical states that have been associated with higher risk of incident infection, and poor outcomes once infection has been established. A variety of host-and pathogen-specific factors are implicated as potential causes for these disparate outcomes including an altered host microbiome, innate and adaptive immune defects, and poor renal clearance and cytokines. However, there remains significant difficulty in modeling both human kidney disease and infection into an animal host. Likewise, there remains a poor understanding of the mechanisms underlying the unique immunodeficiency imparted by AKI and CKD, and if either condition imparts disparate risk.

Methods

C57BL/6J mice were given vehicle or aristolochic acid (AA) to create AKI (control, AKI groups) or CKD (control, CKD groups). Donor mice from all four groups underwent sterile cecal dissection and creation of cecal slurry (CS) preparations, which was later injected into separate mice in a matched host-recipient manner, at either high or lower doses. Animals were clinically monitored for either 24- or 72-hours after inoculation, then euthanized. Animal survival, sepsis severity, temperature, weights, and transcutaneous glomerular filtration rate (tGFR) were tracked longitudinally throughout the study. Histology for kidney injury, peripheral blood flow cytometry for leukocyte counts, plasma cytokines, and typical markers for organ injury were determined.

Results

Compared to controls, animals with AKI experienced much more severe sepsis across virtually all tracked metrics, and no animals with AKI survived high-dose CS injection past 24-hours. AKI mice manifested with a peripheral defect in leukocytes early after sepsis, with severe and persistent cytopenias, and a dramatically heightened early pro-inflammatory cytokine response. Septic CKD mice also had worse outcomes than controls, though less severe, and occurring later than in animals with AKI. Interestingly, animals with AKI had worse clinical outcomes and evidence of organ injury than mice with CKD at any dose or time-point after inoculation, despite a higher mean baseline measured GFR.

Conclusions

Rodents with established AKI and CKD experience worse clinical outcomes and organ injury versus controls in a CS model intraperitoneal live-bacterial infection. Additionally, mice with AKI experienced earlier and more severe morbidity and mortality than animals with CKD.