bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optogenetic manipulation and photoacoustic imaging using a near-infrared transgenic mouse model
Authors: Kasatkina Ludmila A. , Ma Chenshuo , Matlashov Mikhail E. , Vu Tri , Li Mucong , Kaberniuk Andrii A. , Yao Junjie , Verkhusha Vladislav V. 
Published: May 2022

AbstractOptogenetic manipulation and optical imaging in the near-infrared range allow non-invasive light-control and readout of cellular and organismal processes in deep tissues in vivo. Here, we exploit the advantages of Rhodopseudomonas palustris BphP1 bacterial phytochrome, which incorporates biliverdin chromophore and reversibly photoswitches between the ground (740–800 nm) and activated (620–680 nm) states, to generate a loxP-BphP1 transgenic mouse model. The mouse enables Cre-dependent temporal and spatial targeting of BphP1 expression in vivo. We validate the optogenetic performance of endogenous BphP1, which in the activated state binds its engineered protein partner QPAS1, to trigger gene transcription in primary cells and living mice. We demonstrate photoacoustic tomography of BphP1 expression in different organs, developing embryos, virus-infected tissues and regenerating livers, with the centimeter penetration depth. The transgenic mouse model provides opportunities for both near-infrared optogenetics and photoacoustic imaging in vivo and serves as a source of primary cells and tissues with genomically encoded BphP1.
Modelling the pyrenoid-based CO2-concentrating mechanism provides insights into its operating principles and a roadmap for its engineering into crops
Authors: Fei Chenyi , Wilson Alexandra T. , Mangan Niall M. , Wingreen Ned S. , Jonikas Martin C. 
Published: May 2022

AbstractMany eukaryotic photosynthetic organisms enhance their carbon uptake by supplying concentrated CO2 to the CO2-fixing enzyme Rubisco in an organelle called the pyrenoid. Ongoing efforts seek to engineer this pyrenoid-based CO2-concentrating mechanism (PCCM) into crops to increase yields. Here we develop a computational model for a PCCM on the basis of the postulated mechanism in the green alga Chlamydomonas reinhardtii. Our model recapitulates all Chlamydomonas PCCM-deficient mutant phenotypes and yields general biophysical principles underlying the PCCM. We show that an effective and energetically efficient PCCM requires a physical barrier to reduce pyrenoid CO2 leakage, as well as proper enzyme localization to reduce futile cycling between CO2 and HCO3−. Importantly, our model demonstrates the feasibility of a purely passive CO2 uptake strategy at air-level CO2, while active HCO3− uptake proves advantageous at lower CO2 levels. We propose a four-step engineering path to increase the rate of CO2 fixation in the plant chloroplast up to threefold at a theoretical cost of only 1.3 ATP per CO2 fixed, thereby offering a framework to guide the engineering of a PCCM into land plants.
Neoantigen quality predicts immunoediting in survivors of pancreatic cancer
Authors: Łuksza Marta , Sethna Zachary M. , Rojas Luis A. , Lihm Jayon , Bravi Barbara , Elhanati Yuval , Soares Kevin , Amisaki Masataka , Dobrin Anton , Hoyos David , Guasp Pablo , Zebboudj Abderezak , Yu Rebecca , Chandra Adrienne Kaya , Waters Theresa , Odgerel Zagaa , Leung Joanne , Kappagantula Rajya , Makohon-Moore Alvin , Johns Amber , Gill Anthony , Gigoux Mathieu , Wolchok Jedd , Merghoub Taha , Sadelain Michel , Patterson Erin , Monasson Remi , Mora Thierry , Walczak Aleksandra M. , Cocco Simona , Iacobuzio-Donahue Christine , Greenbaum Benjamin D. , Balachandran Vinod P. 
Published: May 2022

AbstractCancer immunoediting1is a hallmark of cancer2that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice1,3, whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features—‘non-selfness’ based on neoantigen similarity to known antigens4,5, and ‘selfness’ based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer.
Deep Visual Proteomics defines single-cell identity and heterogeneity
Authors: Mund Andreas , Coscia Fabian , Kriston András , Hollandi Réka , Kovács Ferenc , Brunner Andreas-David , Migh Ede , Schweizer Lisa , Santos Alberto , Bzorek Michael , Naimy Soraya , Rahbek-Gjerdrum Lise Mette , Dyring-Andersen Beatrice , Bulkescher Jutta , Lukas Claudia , Eckert Mark Adam , Lengyel Ernst , Gnann Christian , Lundberg Emma , Horvath Peter , Mann Matthias 
Published: May 2022

AbstractDespite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance measurements. Here, we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high-sensitivity mass spectrometry. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. By individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and uncharacterized proteins. In an archived primary melanoma tissue, DVP identified spatially resolved proteome changes as normal melanocytes transition to fully invasive melanoma, revealing pathways that change in a spatial manner as cancer progresses, such as mRNA splicing dysregulation in metastatic vertical growth that coincides with reduced interferon signaling and antigen presentation. The ability of DVP to retain precise spatial proteomic information in the tissue context has implications for the molecular profiling of clinical samples.
Global gridded GDP data set consistent with the shared socioeconomic pathways
Authors: Wang Tingting , Sun Fubao 
Published: May 2022

AbstractThe vulnerability, exposure and resilience of socioeconomic activities to future climate extremes call for high-resolution gridded GDP in climate change adaptation and mitigation research. While global socioeconomic projections are provided mainly at the national level, and downscaling approaches using nighttime light (NTL) images or gridded population data can increase the uncertainty due to limitations. Therefore, we adopt an NTL-population-based approach, which exhibits higher accuracy in socioeconomic disaggregation. Gross regional product of over 800 provinces, which covering over 60% of the global land surface and accounted for more than 80% of GDP in 2005, were used as input. We present a first set of comparable spatially explicit global gridded GDP projections with fine spatial resolutions of 30 arc-seconds and 0.25 arc-degrees for the historical period of 2005 and for 2030–2100 at 10-year intervals under the five SSPs, accounting for the two-child policy in China. This gridded GDP projection dataset can broaden the applicability of GDP data, the availability of which is necessary for socioeconomic and climate change research.
Monitoring microseismicity of the Hengill Geothermal Field in Iceland
Authors: Grigoli Francesco , Clinton John F. , Diehl Tobias , Kaestli Philipp , Scarabello Luca , Agustsdottir Thorbjorg , Kristjansdottir Sigridur , Magnusson Rognvaldur , Bean Christopher J. , Broccardo Marco , Cesca Simone , Dahm Torsten , Hjorleifsdottir Vala , Cabrera Banu Mena , Milkereit Claus , Nooshiri Nima , Obermann Anne , Racine Roman , Rinaldi Antonio Pio , Ritz Vanille , Sanchez-Pastor Pilar , Wiemer Stefan 
Published: May 2022

AbstractInduced seismicity is one of the main factors that reduces societal acceptance of deep geothermal energy exploitation activities, and felt earthquakes are the main reason for closure of geothermal projects. Implementing innovative tools for real-time monitoring and forecasting of induced seismicity was one of the aims of the recently completed COSEISMIQ project. Within this project, a temporary seismic network was deployed in the Hengill geothermal region in Iceland, the location of the nation’s two largest geothermal power plants. In this paper, we release raw continuous seismic waveforms and seismicity catalogues collected and prepared during this project. This dataset is particularly valuable since a very dense network was deployed in a seismically active region where thousand of earthquakes occur every year. For this reason, the collected dataset can be used across a broad range of research topics in seismology ranging from the development and testing of new data analysis methods to induced seismicity and seismotectonics studies.
Holistic health record for Hidradenitis suppurativa patients
Authors: Tricarico Paola Maura , Moltrasio Chiara , Gradišek Anton , Marzano Angelo V , Flacher Vincent , Boufenghour Wacym , von Stebut Esther , Schmuth Matthias , Jaschke Wolfram , Gams Matjaž , Boniotto Michele , Crovella Sergio 
Published: May 2022

AbstractHidradenitis suppurativa (HS) is a recurrent inflammatory skin disease with a complex etiopathogenesis whose treatment poses a challenge in the clinical practice. Here, we present a novel integrated pipeline produced by the European consortium BATMAN (Biomolecular Analysis for Tailored Medicine in Acne iNversa) aimed at investigating the molecular pathways involved in HS by developing new diagnosis algorithms and building cellular models to pave the way for personalized treatments. The objectives of our european Consortium are the following: (1) identify genetic variants and alterations in biological pathways associated with HS susceptibility, severity and response to treatment; (2) design in vitro two-dimensional epithelial cell and tri-dimensional skin models to unravel the HS molecular mechanisms; and (3) produce holistic health records HHR to complement medical observations by developing a smartphone application to monitor patients remotely. Dermatologists, geneticists, immunologists, molecular cell biologists, and computer science experts constitute the BATMAN consortium. Using a highly integrated approach, the BATMAN international team will identify novel biomarkers for HS diagnosis and generate new biological and technological tools to be used by the clinical community to assess HS severity, choose the most suitable therapy and follow the outcome.
Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data
Authors: Nielsen Andreas Holm , Iosifidis Alexandros , Karstoft Henrik 
Published: May 2022

AbstractClassifying the state of the atmosphere into a finite number of large-scale circulation regimes is a popular way of investigating teleconnections, the predictability of severe weather events, and climate change. Here, we investigate a supervised machine learning approach based on deformable convolutional neural networks (deCNNs) and transfer learning to forecast the North Atlantic-European weather regimes during extended boreal winter for 1–15 days into the future. We apply state-of-the-art interpretation techniques from the machine learning literature to attribute particular regions of interest or potential teleconnections relevant for any given weather cluster prediction or regime transition. We demonstrate superior forecasting performance relative to several classical meteorological benchmarks, as well as logistic regression and random forests. Due to its wider field of view, we also observe deCNN achieving considerably better performance than regular convolutional neural networks at lead times beyond 5–6 days. Finally, we find transfer learning to be of paramount importance, similar to previous data-driven atmospheric forecasting studies.
Fusion of expert uncertain assessment in FMEA based on the negation of basic probability assignment and evidence distance
Authors: Yuan Yusong , Tang Yongchuan 
Published: May 2022

AbstractFailure mode and effects analysis (FMEA) has been widely used for potential risk modeling and management. Expert evaluation is used to model the risk priority number to determine the risk level of different failure modes. Dempster–Shafer (D–S) evidence theory is an effective method for uncertain information modeling and has been adopted to address the uncertainty in FMEA. How to deal with conflicting evidence from different experts is an open issue. At the same time, different professional backgrounds of experts may lead to different weights in modeling the evaluation. How to model the relative weight of an expert is an important problem. We propose an improved risk analysis method based on triangular fuzzy numbers, the negation of basic probability assignment (BPA) and the evidence distance in the frame of D–S evidence theory. First, we summarize and organize the expert’s risk analysis results. Then, we model the expert’s assessments based on the triangular fuzzy numbers as BPAs and calculate the negation of BPAs. Third, we model the weight of expert based on the evidence distance in the evidence theory. Finally, the Murphy’s combination rule is used to fuse the risk assessment results of different experts and calculate the new risk priority number (RPN). At the end of this paper, we apply the proposed method to analyze seventeen failure modes of aircraft turbine blades. The experimental results verify the rationality and effectiveness of this method.
Mapping microbiome-redox spectrum and evaluating Microbial-Redox Index in chronic gastritis
Authors: Panigrahi Manas Kumar , Kaliaperumal Venkatesh , Akella Abhishek , Venugopal Giriprasad , Ramadass Balamurugan 
Published: May 2022

AbstractPeptic ulcer disease (PUD) and chronic gastritis are prevalent in developing countries. The role of oxidative stress in the pathogenesis of gastrointestinal mucosal disorders is well recognized. In PUD, the gastric mucosa and its associated microbiome are subject to diet and stress-induced oxidative perturbations. Tissue redox potential (ORP) measurement can quantify oxidative stress, reflecting the balance between prooxidants and antioxidants. This study hypothesizes that the oxidative stress quantified by tissue ORP will be associated with characteristic changes in the mucosa-associated microbiome in PUD and gastritis. In addition, we propose using relative microbial abundance as a quantitative marker of mucosal health. Endoscopy was performed to obtain gastric mucosal biopsies from ten PUD and ten non-ulcer dyspepsia (NUD) patients. The tissue ORP was measured directly with a microelectrode using a biopsy specimen. A second specimen from an adjacent site was subjected to 16s rRNA gene sequencing. From the OTUs, the relative abundance of the microbial taxon in each of the samples was derived. We analyzed the genome of the predominant species for genes encoding the utilization of oxygen as an electron acceptor in respiration and for the presence of antioxidant defense mechanisms. The organisms were then grouped based on their established and inferred redox traits. Shannon diversity index and Species richness were calculated on rarefied data. The relative abundance of organisms that prefer high ORP over those that favor low ORP is conceived as the “Microbial Redox Index (MRI),” an indicator of mucosal health. In the gastric mucosa, aerobic species predominate and are more diverse than the anaerobes. The predominant aerobes are Helicobacter pylori and Sphingobacterium mizutaii. The abundance of these two species had an inverse correlation with the abundance of low ORP preferring anaerobes. Their relative abundance ratio (Microbial Redox Index) correlated with the tissue oxidation–reduction potential (ORP), a direct measure of oxidative stress. Correlation analysis also revealed that the abundance of all anaerobes inversely correlated with the dominant aerobic taxa. In addition, Shannon and Species richness diversity indices, the probable indicators of mucosal health, were negatively correlated with Microbial Redox Index. Using PUD as a prototype mucosal disease, this article describes a generalized approach to infer and quantify mucosal oxidative stress by analyzing the relative abundance of microorganisms that preferentially grow at the extremes of the tissue redox potential. This ratiometric Microbial Redox Index can also be assessed using simple qPCR without the need for sequencing. The approach described herein may be helpful as a widely applicable quantitative measure of mucosal health with prognostic and therapeutic implications.
Genome-wide identification of carbapenem-resistant Gram-negative bacterial (CR-GNB) isolates retrieved from hospitalized patients in Bihar, India
Authors: Kumari Namrata , Kumar Mukesh , Katiyar Amit , Kumar Abhay , Priya Pallavi , Kumar Bablu , Biswas Nihar Ranjan , Kaur Punit 
Published: May 2022

AbstractCarbapenemase-producing clinical isolates are becoming more common over the world, posing a severe public health danger, particularly in developing nations like India. Carbapenem-resistant Gram-negative bacterial (CR-GNB) infection has become a fast-expanding global threat with limited antibiotic choice and significant mortality. This study aimed to highlight the carbapenem-resistance among clinical isolates of hospital admitted patients in Bihar, India. A cross-sectional study was conducted with 101 clinical isolates of Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa. All GNB isolates were tested for their antimicrobial susceptibility using Kirby-Bauer disc diffusion method. Double disc synergy test / modified Hodge test (DDST/MHT) were used to detect carbapenemase production by these isolates. Subsequently, these isolates were evaluated for carbapenem-resistance genes using whole-genome sequencing method. The overall percentage of carbapenem-resistance among GNB was (17/101) 16.8%. The genomic analysis of antimicrobial-resistance (AMR) demonstrates a significantly high prevalence of blaCTX-M followed by blaSHV, blaTEM, blaOXA, and blaNDM β-lactam or carbapenem resistance genes among clinical isolates of GNB. Co-occurrence of blaNDM with other beta-lactamase-encoding genes was found in 70.6% of carbapenemase-producing isolates. Our study highlights the mechanism of carbapenem-resistance to curb the overwhelming threat posed by the emergence of drug-resistance in India.
Age-period-cohort analysis of lung cancer mortality in China and Australia from 1990 to 2019
Authors: Wang Ning , Xu Zhiwei , Lui Chi-Wai , Wang Baohua , Hu Wenbiao , Wu Jing 
Published: May 2022

AbstractLung cancer (LC) is the leading cause of cancer death in China and Australia, the countries with different socioenvironmental contexts in the Western Pacific Region. Comparing the age-period-cohort effect on LC mortality (LCM) between the two countries can help plan interventions and draw lessons for countries in the region. We collected LCM estimates between 1990 and 2019 from the GBD 2019. Age-period-cohort modelling was applied to compute the net drift, local drift, cross-sectional age curve, longitudinal age curve, and the rate ratios (RRs) of period and cohort. China had a higher LC age-standardized mortality rate than Australia in 2019 (men: 58.10 [95% uncertainty interval (UI): 46.53, 70.89] vs. 30.13 [95% UI: 27.88, 32.31]/100,000 population; women: 22.86 [95% UI: 18.52, 27.52] vs. 17.80 [95% UI: 15.93, 19.34]/100,000 population). Period and cohort effects on LCM improved more markedly among Australian men (RR for period effect, from 1.47 [95% confidence interval (CI) 1.41, 1.53] to 0.79 [95% CI 0.75, 0.84]; RR for cohort effect, from 2.56 [95% CI 2.44, 2.68] to 0.36 [95% CI 0.11, 1.18]) and Chinese women (RR for period effect, from 1.06 [95% CI 1.01, 1.11] to 0.85 [95% CI 0.82, 0.89]; RR for cohort effect, from 0.71 [95% CI 0.65, 0.78] to 0.51 [95% CI 0.26, 1.03]) during the study period and birth cohort. The LCM in Chinese population aged 65 to 79 and Australian women aged 75 to 79 increased. Smoking and particulate matter (PM) contributed most to LCM in China, while smoking and occupational carcinogens contributed most in Australia. Decreasing period and cohort risks for LCM attributable to smoking and PM were more remarkable in Australia than in China. The LCM attributable to occupational carcinogens was higher in Australia than in China, particularly for those aged 60 to 79. Vigorous tobacco and PM control, which brought a substantial decline in LCM in Australia, may help reduce LCM in China. Australia should highlight LC prevention among people with occupational exposure. Chinese aged ≥ 65 and Australian women aged ≥ 75 should be the priorities for LC interventions.
Modeling pulsativity in the hypothalamic–pituitary–adrenal hormonal axis
Authors: Churilov Alexander N. , Milton John G. 
Published: May 2022

AbstractA new mathematical model for biological rhythms in the hypothalamic–pituitary–adrenal (HPA) axis is proposed. This model takes the form of a system of impulsive time-delay differential equations which include pulsatile release of adrenocorticotropin (ACTH) by the pituitary gland and a time delay for the release of glucocorticoid hormones by the adrenal gland. Numerical simulations demonstrate that the model’s response to periodic and circadian inputs from the hypothalamus are consistent with those generated by recent models which do not include a pulsatile pituitary. In contrast the oscillatory phenomena generated by the impulsive delay equation mode occur even if the time delay is zero. The observation that the time delay merely introduces a small phase shift suggesting that the effects of the adrenal gland are “downstream” to the origin of pulsativity. In addition, the model accounts for the occurrence of ultradian oscillations in an isolated pituitary gland. These observations suggest that principles of pulse modulated control, familiar to control engineers, may have an increasing role to play in understanding the HPA axis.