bluuebunny/crossref_metadata_2025_split huggingface dataset:
Normal male fertility in a mouse model of KPNA2 deficiency
Authors: Rother Franziska , Hweidi Dalia Abu , Hartmann Enno , Bader Michael 
Published: May 2024

ABSTRACTThe nuclear transport of proteins is mediated by karyopherins and has been implicated to be crucial for germ cell and embryonic development. Deletion of distinct members of the karyopherin alpha family has been shown to cause male and female infertility in mice. Using a genetrap approach, we established mice deficient for KPNA2 (KPNA2 KO) and investigated the role of this protein in male germ cell development and fertility. Breeding of male KPNA2 KO mice leads to healthy offsprings in all cases albeit the absence of KPNA2 resulted in a reduction in sperm number by 60%. Analyses of the KPNA2 expression in wild-type mice revealed a strong KPNA2 presence in meiotic germ cells of all stages while a rapid decline is found in round spermatids. The high KPNA2 expression throughout all meiotic stages of sperm development suggests a possible function of KPNA2 during this phase, hence in its absence the spermatogenesis is not completely blocked. In KPNA2 KO mice, a higher portion of sperms presented with morphological abnormalities in the head and neck region, but a severe spermiogenesis defect was not found. Thus, we conclude that the function of KPNA2 in round spermatids is dispensable, as our mice do not show any signs of infertility. Our data provide evidence that KPNA2 is not crucial for male germ cell development and fertility.
Neuropeptide Y co-opts neuronal ensembles for memory lability and stability
Authors: Wu Yan-Jiao , Gu Xue , Kong Yalei , Yang Shuo , Wang Huan , Xu Miao , Wang Qi , Yi Xin , Lin Ze-Jie , Jiao Zhi-Han , Cheung Hoiyin , Zhao Xin-Yu , Bian Xin , Jiang Qin , Li Ying , Zhu Michael X. , Wang Lu-Yang , Li Yulong , Huang Ju , Li Qian , Li Wei-Guang , Xu Tian-Le 
Published: May 2024

AbstractMemory engrams are formed by activity-dependent recruitment of distinct subsets of excitatory principal neurons (or neuronal ensembles) whereas inhibitory neurons pivot memory lability and stability1–5. However, the molecular logic for memory engrams to preferentially recruit specific type of interneurons over other subtypes remains enigmatic. Using activity-dependent single-cell transcriptomic profiling6–8in mice with training of cued fear memory and extinction, we discovered that neuropeptide Y (NPY)-expressing (NPY+) GABAergic interneurons in the ventral hippocampal CA1 (vCA1) region exert fast GABAergic inhibition to facilitate the acquisition of memory, but bifurcate NPY-mediated slow peptidergic inhibition onto distinct sub-ensembles underlying the extinction of single memory trace. Genetically encoded calcium and NPY sensors revealed that both calcium dynamics of NPY+neurons and their NPY release in vCA1 ramp up as extinction learning progresses while behavioral state switches from “fear-on” to “fear-off”. Bidirectional manipulations of NPY+neurons or NPY itself demonstrated NPY is both necessary and sufficient to control the rate and degree of memory extinction by acting on two physically non-overlapping sub-ensembles composed of NPY1R- and NPY2R-expressing neurons. CRISPR/Cas9-mediated knockout of NPY2R or NPY1R further unravels that NPY co-opts its actions on these two sub-ensembles to gate early fast and late slow stages of extinction. These findings exemplify the intricate spatiotemporal orchestration of slow peptidergic inhibitions from single subtype of GABAergic interneurons to fine-tune engram lability verse stability of memory.
Advancing species identification: A non-invasive molecular approach through spider silk proteome analysis
Authors: Yamamoto Phillip K , Takasuka Keizo , Mori Masaru , Masuda Takeshi , Kono Nobuaki 
Published: May 2024

ABSTRACTSpecies identification is crucial in various scientific disciplines such as biology, ecology, medicine, and agriculture. While traditional methods rely on morphological characteristics, DNA barcoding has gained popularity due to its molecular biology approach. Nonetheless, DNA barcoding can be problematic for small animals such as insects, as it requires damaging their bodies for DNA extraction, impacting subsequent breeding and experiments. In this paper, we propose a non-invasive molecular method for species identification that examines the protein composition of animal produced biomaterials. We chose spider silk, with species-specific protein sequences, as our subject of analysis. First, we established a universal silk-dissolving method that applies to silks from various species. We constructed a bioinformatics pipeline employing metrics of significant difference through proteomic analysis to identify spider species by analyzing peptide sequences present in silk proteins. As a result, we achieved a species identification accuracy of 86% across15 species. An appropriate reference dataset was successfully created, in addition, we also discovered some species are difficult to distinguish due to sequence similarities. This technology has been confirmed to be applicable to spider webs taken from the field. This non-invasive approach can complement DNA barcoding, especially in situations where it is infeasible, such as in studies involving spider-parasitoid wasps that eat spiders. Furthermore, it can be applied to other organisms that release biological substances, such as silkworm pupae, termite digestive enzymes, and tick saliva, aiding in species identification and pest control efforts.
Identifiability investigation of within-host models of acute virus infection
Authors: Liyanage Yuganthi R. , Heitzman-Breen Nora , Tuncer Necibe , Ciupe Stanca M. 
Published: May 2024

AbstractUncertainty in parameter estimates from fitting within-host models to empirical data limits the model’s ability to uncover mechanisms of infection, disease progression, and to guide pharmaceutical interventions. Understanding the effect of model structure and data availability on model predictions is important for informing model development and experimental design. To address sources of uncertainty in parameter estimation, we use four mathematical models of influenza A infection with increased degrees of biological realism. We test the ability of each model to reveal its parameters in the presence of unlimited data by performing structural identifiability analyses. We then refine the results by predicting practical identifiability of parameters under daily influenza A virus titers alone or together with daily adaptive immune cell data. Using these approaches, we present insight into the sources of uncertainty in parameter estimation and provide guidelines for the types of model assumptions, optimal experimental design, and biological information needed for improved predictions.Author summaryWithin-host models of virus infections fitted to data have improved our understanding of mechanisms of infection, disease progression, and allowed us to provide guidelines for pharmaceutical interventions. Given their predictive power, it is essential that we properly uncover and address uncertainty in model predictions and parameter estimation. Here, we focus on the effect of model structure and data availability on our ability to uncover unknown parameters. To address these questions, we use four mathematical models of influenza A infection with increased degrees of biological realism. We test the ability of each model to reveal its parameters in the presence of unlimited data by performing structural identifiability analysis. We then refine the results by predicting practical identifiability of parameters under daily influenza A virus titers alone or together with daily adaptive immune cell data. Using these approaches, we present insights into the sources of uncertainty in parameter estimations and provide guidelines for the types of model assumptions, optimal experimental design, and biological information needed for improved predictions.
Can drinking water, sanitation, handwashing, and nutritional interventions reduce antibiotic use in young children?
Authors: Ercumen Ayse , Mertens Andrew N. , Butzin-Dozier Zachary , Jung Da Kyung , Ali Shahjahan , Achando Beryl S. , Rao Gouthami , Hemlock Caitlin , Pickering Amy J. , Stewart Christine P. , Tan Sophia T. , Grembi Jessica A. , Benjamin-Chung Jade , Wolfe Marlene , Ho Gene G. , Rahman Md. Ziaur , Arnold Charles D. , Dentz Holly N. , Njenga Sammy M , Meerkerk Dorie , Chen Belinda , Nadimpalli Maya , Islam Mohammad Aminul , Hubbard Alan E. , Null Clair , Unicomb Leanne , Rahman Mahbubur , Colford John M. , Luby Stephen P. , Arnold Benjamin F. , Lin Audrie 
Published: May 2024

AbstractFrequent antibiotic use in areas with high infection burdens can lead to antimicrobial resistance and microbiome alterations. Reducing pathogen exposure and child undernutrition can reduce infections and subsequent antibiotic use. We assessed effects of water, sanitation, handwashing (WSH) and nutrition interventions on pediatric antibiotic use in Bangladesh and Kenya, using longitudinal data from birth cohorts (at ages 3-28 months) enrolled in the WASH Benefits cluster-randomized trials. Over 50% of children used antibiotics at least once in the last 90 days. In Bangladesh, the prevalence of using antibiotics at least once was 10-14% lower in groups receiving WSH (prevalence ratio [PR]=0.90 (0.82-0.99)), nutrition (PR=0.86 (0.78-0.94)), and nutrition+WSH (PR=0.86 (0.79-0.93)) interventions. The prevalence of using antibiotics multiple times was 24-35% lower in intervention arms. Intervention effects were strongest when the birth cohort was younger. In Kenya, interventions did not affect antibiotic use. Improving WSH and nutrition can reduce antibiotic use in some low- and middle-income settings. Studies should assess whether such reductions translate to reduced carriage of antimicrobial resistance.
Incubation period, serial interval, generation time and reproduction number of mpox clade I
Authors: Marziano Valentina , Guzzetta Giorgio , Longini Ira , Merler Stefano 
Published: May 2024

AbstractWe estimate that the generation time of mpox clade I is distinctly longer than clade IIb and may depend on the transmission route (mean 17.5 days in households vs. 11.4 in hospitals). We estimate a mean reproduction number of 1.22-1.33 in the Democratic Republic of the Congo between August 2023-March 2024.
Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases
Authors: Mitchell Jonathan , Camacho Niedzica , Shea Patrick , Stopsack Konrad H. , Joseph Vijai , Burren Oliver , Dhindsa Ryan , Nag Abhishek , Berchuck Jacob E. , O’Neill Amanda , Abbasi Ali , Zoghbi Anthony W. , Alegre-Díaz Jesus , Kuri-Morales Pablo , Berumen Jaime , Tapia-Conyer Roberto , Emberson Jonathan , Torres Jason M. , Collins Rory , Wang Quanli , Goldstein David , Matakidou Athena , Haefliger Carolina , Anderson-Dring Lauren , March Ruth , Jobanputra Vaidehi , Dougherty Brian , Carss Keren , Petrovski Slavé , Kantoff Philip W. , Offit Kenneth , Mucci Lorelei A. , Pomerantz Mark , Fabre Margarete A. 
Published: May 2024

AbstractThe etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants inSAMHD1as well as genes in the DNA damage response pathway (BRCA2,ATMandCHEK2) are associated with the risk of overall prostate cancer. We also found that rare damaging variants inAOX1andBRCA2were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single-variant level, we found rare non-synonymous variants in three genes (HOXB13,CHEK2,BIK) significantly associated with increased risk of overall prostate cancer and in four genes (ANO7,SPDL1,AR,TERT) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.
Cross-platform Clinical Proteomics using the Charité Open Standard for Plasma Proteomics (OSPP)
Authors: Wang Ziyue , Farztdinov Vadim , Sinn Ludwig Roman , Tober-Lau Pinkus , Ludwig Daniela , Freiwald Anja , Amari Fatma , Textoris-Taube Kathrin , Niewienda Agathe , Welter Anna Sophie , Wei Alan An Jung , Luckau Luise , Kurth Florian , Selbach Matthias , Hartl Johannes , Mülleder Michael , Ralser Markus 
Published: May 2024

AbstractThe role of plasma and serum proteomics in characterizing human disease, identifying biomarkers, and advancing diagnostic technologies is rapidly increasing. However, there is an ongoing need to improve proteomic workflows in terms of accuracy, reproducibility, platform transferability, and cost-effectiveness. Here, we present the CharitéOpen PeptideStandard forPlasmaProteomics(OSPP), a panel of 211 extensively pre-selected, stable-isotope-labeled peptides combined in an open, versatile, and cost-effective internal standard for targeted and untargeted proteomic studies. The selected peptides are well suited for chemical synthesis, and distribute well over the captured analytical dynamic range and chromatographic gradients, and show consistent quantification properties across platforms, in serum, as well as in EDTA-, citrate, and heparin plasma. Quantifying proteins that function in a wide range of biological processes, including several that are routinely used in clinical tests or are targets of FDA-approved drugs, the OSPP quantifies proteins that are important for human disease. On an acute COVID-19 in-patient cohort, we demonstrate the application of the OSPP to i) achieve patient classification and biomarker identification ii) generate comparable quantitative proteomics data with both targeted and untargeted approaches, and iii) estimate peptide quantities for successful cross-platform alignment of proteomic data. The OSPP adds low costs per proteome sample, thus making the use of an internal standard accessible. In addition to the standards, corresponding spectral libraries and optimized acquisition methods for several platforms are made openly available.
Cognitive Behavioural Therapy in Adults with Psychogenic Non-Epileptic Seizures: A Systematic Review and Meta-Analysis of Randomised Controlled Trials
Authors: Moro Pierludovico , Lattanzi Simona , Beier Christoph P , Bonaventura Carlo Di , Irelli Emanuele Cerulli 
Published: May 2024

AbstractBackgroundRandomised controlled clinical trials (RCTs) investigating cognitive-behavioural therapy (CBT) among adults with psychogenic non-epileptic seizures (PNES) has become increasingly available, prompting the opportunity to critically appraise the efficacy and safety of CBT in this population.MethodsWe conducted a systematic review and meta-analysis including RCTs comparing CBT in addition to standardised medical treatment (SMT) versus SMT alone for adults with PNES. The primary outcome was seizure freedom at the end of treatment. Secondary outcomes included measures of quality of life, anxiety and depression assessed via standardised clinical questionnaires.ResultsThree RCTs were included comprising 228 participants treated with CBT and 222 with SMT. The intervention was significantly associated with seizure freedom (Odds Ratio [OR] 1.98; 95% confidence interval [CI] 1.14, 3.46; p = 0.02; I2 = 0%), reductions in anxiety (standardised mean difference [SMD] −0.21; 95% CI −0.41, −0.003; p = 0.047; I2 = 0%) and improvements in quality of life (SMD 0.34; 95% CI 0.12, 0.57; p = 0.003; I2 = 0%) at the end of treatment. Conversely, no significant differences between groups were observed regarding depression symptoms (SMD −0.19; 95% CI −0.39, 0.02; p = 0.08; I2= 0%). There was no statistically significant increase in the risk of suicidal ideation and self-harm with CBT (OR 2.11; 95% CI 0.81, 5.48; p = 0.13; I2= 0%) nor were there differences in terms of discontinuation rates during follow-up (OR 0.92; 95% CI 0.49, 1.72; p = 0.79; I2= 7%).ConclusionsThere is high-quality evidence supporting the efficacy and safety of CBT in treating PNES. Future research should investigate whether combining CBT with other therapeutic methods could potentially enhance treatment efficacy.
Molecular Myelin Dysfunction in the Most Common Inherited Peripheral Neuropathies – CMT1A and HNPP
Authors: Moss Kathryn R. , Gutierrez Dave , Mi Ruifa , Cetinkaya-Fisgin Aysel , Höke Ahmet 
Published: May 2024

AbstractIncreased and decreased dosage of thePeripheral Myelin Protein 22(PMP22) gene cause dysmyelinating peripheral neuropathy. Charcot-Marie-Tooth Disease Type 1A (CMT1A,PMP22duplication) and Hereditary Neuropathy with Liability to Pressure Palsies (HNPP,PMP22deletion) are the most common inherited peripheral neuropathies, yet gaps remain about their pathophysiology and pathomechanims. Our previous results with CMT1A model mice demonstrate that muscle atrophy occurs without evidence of secondary axon degeneration suggesting that primary myelin dysfunction may contribute to functional deficits in CMT1A and motivating investigation of myelin dysfunction. Here we used CMT1A and HNPP model mice and confocal immunofluorescence imaging of teased tibial nerve fibers to determine how altered PMP22 expression disrupts myelin integrity and reveal CMT1A and HNPP pathomechanisms. We identified dramatic changes to molecular machinery at Schmidt-Lanterman incisures (SLIs) and Nodes of Ranvier that led us to propose two potential pathomechanisms for CMT1A and HNPP: impaired metabolic support and axonal ion disequilibrium. We also developed a working model for these pathomechanims that is driven by PMP22-mediated regulation of adherens junctions. Ongoing studies are aimed at testing these proposed pathomechanisms and determining how altered PMP22 and adherens junctions cause these defects. This work will provide insight into CMT1A and HNPP pathogenesis and may reveal novel approaches for developing therapeutics.
Key role of Pro230 in the hinge region on the IgG architecture and function
Authors: Koseki Yuuki , Yamaguchi Yuki , Aoyama Michihiko , Tada Minoru , Senoo Akinobu , Ishii-Watabe Akiko , Uchihashi Takayuki , Uchiyama Susumu , Kato Koichi , Yanaka Saeko , Caaveiro Jose M.M. 
Published: May 2024

AbstractImmunoglobulin G (IgG) is a molecule that plays an important role in biological defense; IgG molecules have been applied as drugs due to their high specificity for antigens and their ability to activate immunity via effector molecules on immune cells. On the other hand, the flexibility of the hinge region makes it difficult to apply conventional structural biology approaches due to its dynamic conformational changes, and the mechanism of action of the molecule as a whole has not been elucidated. Here, we introduced a deletion amino acid mutation in the hinge region to elucidate the role of the hinge region and its effect on the structure and function of the IgG molecule. Deletion of Pro230 resulted in the formation of a half-molecular in which the interaction between heavy chains was lost. We elucidated the mechanism of half-IgG formation by structural analysis using nuclear magnetic resonance (NMR) measurements and by disulfide quantification using peptide mapping using LC-MS/MS. For this purpose, a new NMR stable isotope labeling method was introduced. Finally, cell assay revealed that the IgG half-molecules have specific FcγRI-mediated activity. This report provides new insights into the higher-order structure formation of IgG molecules and is expected to contribute to the elucidation of the molecular basis of the Fcγ receptor-mediated activation mechanism of the immune system.
A regulatory gene network that couples floral transition to shoot apical meristem morphology in Arabidopsis
Authors: de Olalla Enric Bertran Garcia , Rodríguez-Maroto Gabriel , Cerise Martina , Vayssières Alice , Severing Edouard , Sampere Yaiza López , Wang Kang , Schäfer Sabine , Formosa-Jordan Pau , Coupland George 
Published: May 2024

AbstractPlants flower in response to environmental signals. These signals change the shape and developmental identity of the shoot apical meristem (SAM), causing it to form flowers and inflorescences rather than leaves. How the changes in SAM shape and identity are coordinated is poorly understood. Using genetics, confocal microscopy and RNA sequencing, we show that reciprocal repression of the APETALA2 (AP2) and SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) transcription factors in the SAM is crucial in coupling these processes. During vegetative development, AP2 repressesSOC1transcription to delay floral transition. Later,SOC1is activated during floral transition in response to environmental cues and repressesAP2transcription. However, during floral transition and prior to its stable repression by SOC1, AP2 rapidly promotes an increase in the size, and changes in the morphology, of the SAM. Thus, direct reciprocal repression of AP2 and SOC1 couples floral transition and changes in SAM morphology, which initiate inflorescence development.
Unveiling Gene Perturbation Effects through Gene Regulatory Networks Inference from single-cell transcriptomic data
Authors: Corridori Clelia , Romeike Merrit , Nicoletti Giorgio , Buecker Christa , Suweis Samir , Azaele Sandro , Martello Graziano 
Published: May 2024

1AbstractPhysiological and pathological processes are governed by a network of genes called gene regulatory networks (GRNs). By reconstructing GRNs, we can accurately model how cells behave in their natural state and predict how genetic changes will affect them. Transcriptomic data of single cells are now available for a wide range of cellular processes in multiple species. Thus, a method building predictive GRNs from single-cell RNA sequencing (scRNA-seq) data, without any additional prior knowledge, could have a great impact on our understanding of biological processes and the genes playing a key role in them. To this aim, we developed IGNITE (Inference of Gene Networks using Inverse kinetic Theory and Experiments), an unsupervised machine learning framework designed to infer directed, weighted, and signed GRNs directly from unperturbed single-cell RNA sequencing data. IGNITE uses the GRNs to generate gene expression data upon single and multiple genetic perturbations. IGNITE is based on the inverse problem for a kinetic Ising model, a model from statistical physics that has been successfully applied to biological networks. We tested IGNITE on murine pluripotent stem cells (PSCs) transitioning from the naïve to formative states. Using as input only scRNA-seq data of unperturbed PSCs, IGNITE simulated single and triple gene knockouts. Comparison with experimental data revealed high accuracy, up to 74%, outperforming currently available methods. In sum, IGNITE identifies predictive GRNs from scRNA-seq data without additional prior knowledge and faithfully simulates single and multiple gene perturbations. Applications of IGNITE range from studying cell differentiation to identifying genes specifically active under pathological conditions.