bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultracold Feshbach molecules in an orbital optical lattice
Authors: Kiefer Yann , Hachmann Max , Hemmerich Andreas
Published: March 2023

Quantum gas systems provide a unique experimental platform to study the crossover between Bose–Einstein condensed molecular pairs and Bardeen–Cooper–Schrieffer superfluidity. The few studies in optical lattices have so far focused on the case when only the lowest Bloch band is populated, thus excluding orbital degrees of freedom. Here we demonstrate the preparation of ultracold Feshbach molecules of fermionic atoms in the second Bloch band of an optical square lattice. We cover a wide range of interaction strengths, including the regime of unitarity in the middle of the crossover. Binding energies and band relaxation dynamics are measured by means of a method resembling mass spectrometry. We find that the longest lifetimes arise for strongly interacting Feshbach molecules at the onset of unitarity. In the case of strong confinement in a deep lattice potential, we observe bound dimers also for negative values of the scattering length, extending previous findings for molecules in the lowest band.
Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning
Authors: Stahl Kolja , Graziadei Andrea , Dau Therese , Brock Oliver , Rappsilber Juri
Published: March 2023

While AlphaFold2 can predict accurate protein structures from the primary sequence, challenges remain for proteins that undergo conformational changes or for which few homologous sequences are known. Here we introduce AlphaLink, a modified version of the AlphaFold2 algorithm that incorporates experimental distance restraint information into its network architecture. By employing sparse experimental contacts as anchor points, AlphaLink improves on the performance of AlphaFold2 in predicting challenging targets. We confirm this experimentally by using the noncanonical amino acid photo-leucine to obtain information on residue–residue contacts inside cells by crosslinking mass spectrometry. The program can predict distinct conformations of proteins on the basis of the distance restraints provided, demonstrating the value of experimental data in driving protein structure prediction. The noise-tolerant framework for integrating data in protein structure prediction presented here opens a path to accurate characterization of protein structures from in-cell data.
Deep thermal profiling for detection of functional proteoform groups
Authors: Kurzawa Nils , Leo Isabelle Rose , Stahl Matthias , Kunold Elena , Becher Isabelle , Audrey Anastasia , Mermelekas Georgios , Huber Wolfgang , Mateus André , Savitski Mikhail M. , Jafari Rozbeh
Published: March 2023

The complexity of the functional proteome extends considerably beyond the coding genome, resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases but challenging to perform systematically. Here we applied thermal proteome profiling with deep peptide coverage to detect functional proteoform groups in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detected 15,846 proteoforms, capturing differently spliced, cleaved and post-translationally modified proteins expressed from 9,290 genes. We identified differential co-aggregation of proteoform pairs and established links to disease biology. Moreover, we systematically made use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach, thus, provides a powerful and unique tool for systematic detection and functional annotation of proteoform groups.
Multiomic signatures of body mass index identify heterogeneous health phenotypes and responses to a lifestyle intervention
Authors: Watanabe Kengo , Wilmanski Tomasz , Diener Christian , Earls John C. , Zimmer Anat , Lincoln Briana , Hadlock Jennifer J. , Lovejoy Jennifer C. , Gibbons Sean M. , Magis Andrew T. , Hood Leroy , Price Nathan D. , Rappaport Noa
Published: March 2023

Multiomic profiling can reveal population heterogeneity for both health and disease states. Obesity drives a myriad of metabolic perturbations and is a risk factor for multiple chronic diseases. Here we report an atlas of cross-sectional and longitudinal changes in 1,111 blood analytes associated with variation in body mass index (BMI), as well as multiomic associations with host polygenic risk scores and gut microbiome composition, from a cohort of 1,277 individuals enrolled in a wellness program (Arivale). Machine learning model predictions of BMI from blood multiomics captured heterogeneous phenotypic states of host metabolism and gut microbiome composition better than BMI, which was also validated in an external cohort (TwinsUK). Moreover, longitudinal analyses identified variable BMI trajectories for different omics measures in response to a healthy lifestyle intervention; metabolomics-inferred BMI decreased to a greater extent than actual BMI, whereas proteomics-inferred BMI exhibited greater resistance to change. Our analyses further identified blood analyte–analyte associations that were modified by metabolomics-inferred BMI and partially reversed in individuals with metabolic obesity during the intervention. Taken together, our findings provide a blood atlas of the molecular perturbations associated with changes in obesity status, serving as a resource to quantify metabolic health for predictive and preventive medicine.
Validated names for experimental studies on race and ethnicity
Authors: Crabtree Charles , Kim Jae Yeon , Gaddis S. Michael , Holbein John B. , Guage Cameron , Marx William W.
Published: March 2023

A large and fast-growing number of studies across the social sciences use experiments to better understand the role of race in human interactions, particularly in the American context. Researchers often use names to signal the race of individuals portrayed in these experiments. However, those names might also signal other attributes, such as socioeconomic status (e.g., education and income) and citizenship. If they do, researchers would benefit greatly from pre-tested names with data on perceptions of these attributes; such data would permit researchers to draw correct inferences about the causal effect of race in their experiments. In this paper, we provide the largest dataset of validated name perceptions to date based on three different surveys conducted in the United States. In total, our data include over 44,170 name evaluations from 4,026 respondents for 600 names. In addition to respondent perceptions of race, income, education, and citizenship from names, our data also include respondent characteristics. Our data will be broadly helpful for researchers conducting experiments on the manifold ways in which race shapes American life.
A kinematic, imaging and electromyography dataset for human muscular manipulability index prediction
Authors: Hernández Óscar G. , Lopez-Castellanos Jose M. , Jara Carlos A. , Garcia Gabriel J. , Ubeda Andres , Morell-Gimenez Vicente , Gomez-Donoso Francisco
Published: March 2023

Human Muscular Manipulability is a metric that measures the comfort of an specific pose and it can be used for a variety of applications related to healthcare. For this reason, we introduce KIMHu: a Kinematic, Imaging and electroMyography dataset for Human muscular manipulability index prediction. The dataset is comprised of images, depth maps, skeleton tracking data, electromyography recordings and 3 different Human Muscular Manipulability indexes of 20 participants performing different physical exercises with their arm. The methodology followed to acquire and process the data is also presented for future replication. A specific analysis framework for Human Muscular Manipulability is proposed in order to provide benchmarking tools based on this dataset.
A dataset for medical instructional video classification and question answering
Authors: Gupta Deepak , Attal Kush , Demner-Fushman Dina
Published: March 2023

This paper introduces a new challenge and datasets to foster research toward designing systems that can understand medical videos and provide visual answers to natural language questions. We believe medical videos may provide the best possible answers to many first aid, medical emergency, and medical education questions. Toward this, we created the and datasets and introduce the tasks of Medical Video Classification (MVC) and Medical Visual Answer Localization (MVAL), two tasks that focus on cross-modal (medical language and medical video) understanding. The proposed tasks and datasets have the potential to support the development of sophisticated downstream applications that can benefit the public and medical practitioners. Our datasets consist of 6,117 fine-grained annotated videos for the MVC task and 3,010 questions and answers timestamps from 899 videos for the MVAL task. These datasets have been verified and corrected by medical informatics experts. We have also benchmarked each task with the created and datasets and propose the multimodal learning methods that set competitive baselines for future research.
EUBUCCO v0.1: European building stock characteristics in a common and open database for 200+ million individual buildings
Authors: Milojevic-Dupont Nikola , Wagner Felix , Nachtigall Florian , Hu Jiawei , Brüser Geza Boi , Zumwald Marius , Biljecki Filip , Heeren Niko , Kaack Lynn H. , Pichler Peter-Paul , Creutzig Felix
Published: March 2023

Building stock management is becoming a global societal and political issue, inter alia because of growing sustainability concerns. Comprehensive and openly accessible building stock data can enable impactful research exploring the most effective policy options. In Europe, efforts from citizen and governments generated numerous relevant datasets but these are fragmented and heterogeneous, thus hindering their usability. Here, we present eubucco v0.1, a database of individual building footprints for ~202 million buildings across the 27 European Union countries and Switzerland. Three main attributes – building height, construction year and type – are included for respectively 73%, 24% and 46% of the buildings. We identify, collect and harmonize 50 open government datasets and OpenStreetMap, and perform extensive validation analyses to assess the quality, consistency and completeness of the data in every country. eubucco v0.1 provides the basis for high-resolution urban sustainability studies across scales – continental, comparative or local studies – using a centralized source and is relevant for a variety of use cases, e.g., for energy system analysis or natural hazard risk assessments.
Survey data on preferences and attitudes towards participatory irrigation management in India and Pakistan
Authors: Cooper Bethany , Crase Lin , Burton Michael , Pham Hung Duy
Published: March 2023

The data described in this paper were collected from four jurisdictions in south Asia, Assam and Bihar in India and Punjab and Sindh in Pakistan. The data were collected from farmer households involved in surface water irrigation with the aim of understanding the merits of participatory irrigation management (PIM) in different settings in south Asia. The data were collected using four structured survey instruments, which comprised three paper-based surveys and one online survey collected via tablets. This data can be used by researchers to empirically analyze: overall institutional performance and its relationship to agro-economic variables; drivers of compliance; gender differences and their impact on participation in water groups and perceptions of performance; preferred charging regimes and broader institutional arrangements for managing water at the local level. These data are unique, having been collected simultaneously across the four jurisdictions.
Chinese industrial air pollution emissions based on the continuous emission monitoring systems network
Authors: Tang Ling , Jia Min , Yang Junai , Li Ling , Bo Xin , Mi Zhifu
Published: March 2023

As the world’s largest industrial producer, China has generated large amount of industrial atmospheric pollution, particularly for particulate matter (PM), SO2 and NOx emissions. A nationwide, time-varying, and up-to-date air pollutant emission inventory by industrial sources has great significance to understanding industrial emission characteristics. Here, we present a nationwide database of industrial emissions named Chinese Industrial Emissions Database (CIED), using the real smokestack concentrations from China’s continuous emission monitoring systems (CEMS) network during 2015–2018 to enhance the estimation accuracy. This hourly, source-level CEMS data enables us to directly estimate industrial emission factors and absolute emissions, avoiding the use of many assumptions and indirect parameters that are common in existing research. The uncertainty analysis of CIED database shows that the uncertainty ranges are quite small, within ±7.2% for emission factors and ±4.0% for emissions, indicating the reliability of our estimates. This dataset provides specific information on smokestack concentrations, emissions factors, activity data and absolute emissions for China’s industrial emission sources, which can offer insights into associated scientific studies and future policymaking.
An intracochlear electrocochleography dataset - from raw data to objective analysis using deep learning
Authors: Schuerch Klaus , Wimmer Wilhelm , Dalbert Adrian , Rummel Christian , Caversaccio Marco , Mantokoudis Georgios , Gawliczek Tom , Weder Stefan
Published: March 2023

Electrocochleography (ECochG) measures electrophysiological inner ear potentials in response to acoustic stimulation. These potentials reflect the state of the inner ear and provide important information about its residual function. For cochlear implant (CI) recipients, we can measure ECochG signals directly within the cochlea using the implant electrode. We are able to perform these recordings during and at any point after implantation. However, the analysis and interpretation of ECochG signals are not trivial. To assist the scientific community, we provide our intracochlear ECochG data set, which consists of 4,924 signals recorded from 46 ears with a cochlear implant. We collected data either immediately after electrode insertion or postoperatively in subjects with residual acoustic hearing. This data descriptor aims to provide the research community access to our comprehensive electrophysiological data set and algorithms. It includes all steps from raw data acquisition to signal processing and objective analysis using Deep Learning. In addition, we collected subject demographic data, hearing thresholds, subjective loudness levels, impedance telemetry, radiographic findings, and classification of ECochG signals.
A significant, functional and replicable risk KTN1 variant block for schizophrenia
Authors: Mao Qiao , Lin Xiandong , Yin Qin , Liu Ping , Zhang Yong , Qu Shihao , Xu Jianying , Cheng Wenhong , Luo Xinqun , Kang Longli , Taximaimaiti Reyisha , Zheng Chengchou , Zhang Huihao , Wang Xiaoping , Ren Honggang , Cao Yuping , Lin Jie , Luo Xingguang
Published: March 2023

Cortical and subcortical structural alteration has been extensively reported in schizophrenia, including the unusual expansion of gray matter volumes (GMVs) of basal ganglia (BG), especially putamen. Previous genome-wide association studies pinpointed kinectin 1 gene (KTN1) as the most significant gene regulating the GMV of putamen. In this study, the role of KTN1 variants in risk and pathogenesis of schizophrenia was explored. A dense set of SNPs (n = 849) covering entire KTN1 was analyzed in three independent European- or African-American samples (n = 6704) and one mixed European and Asian Psychiatric Genomics Consortium sample (n = 56,418 cases vs. 78,818 controls), to identify replicable SNP-schizophrenia associations. The regulatory effects of schizophrenia-associated variants on the KTN1 mRNA expression in 16 cortical or subcortical regions in two European cohorts (n = 138 and 210, respectively), the total intracranial volume (ICV) in 46 European cohorts (n = 18,713), the GMVs of seven subcortical structures in 50 European cohorts (n = 38,258), and the surface areas (SA) and thickness (TH) of whole cortex and 34 cortical regions in 50 European cohorts (n = 33,992) and eight non-European cohorts (n = 2944) were carefully explored. We found that across entire KTN1, only 26 SNPs within the same block (r2 > 0.85) were associated with schizophrenia across ≥ 2 independent samples (7.5 × 10–5 ≤ p ≤ 0.048). The schizophrenia-risk alleles, which increased significantly risk for schizophrenia in Europeans (q < 0.05), were all minor alleles (f < 0.5), consistently increased (1) the KTN1 mRNA expression in 12 brain regions significantly (5.9 × 10–12 ≤ p ≤ 0.050; q < 0.05), (2) the ICV significantly (6.1 × 10–4 ≤ p ≤ 0.008; q < 0.05), (3) the SA of whole (9.6 × 10–3 ≤ p ≤ 0.047) and two regional cortices potentially (2.5 × 10–3 ≤ p ≤ 0.042; q > 0.05), and (4) the TH of eight regional cortices potentially (0.006 ≤ p ≤ 0.050; q > 0.05), and consistently decreased (1) the BG GMVs significantly (1.8 × 10–19 ≤ p ≤ 0.050; q < 0.05), especially putamen GMV (1.8 × 10–19 ≤ p ≤ 1.0 × 10–4; q < 0.05, (2) the SA of four regional cortices potentially (0.010 ≤ p ≤ 0.048), and (3) the TH of four regional cortices potentially (0.015 ≤ p ≤ 0.049) in Europeans. We concluded that we identified a significant, functional, and robust risk variant block covering entire KTN1 that might play a critical role in the risk and pathogenesis of schizophrenia.
Preparation of gypsum with high purity and whiteness from phosphogypsum for CO2 mineral sequestration
Authors: Zhang Man , Fan Xing
Published: March 2023

Phosphogypsum (PG) is a solid waste product generated during wet-process phosphoric acid production. Various impurities considerably reduce the purity, whiteness, and application range of PG. This article analyzes the physical properties of PG in detail and systematically examines the content and distribution of impurities. Based on the obtained results, a simple process for the efficient removal of almost all impurities in the PG is proposed. The purity and whiteness of the purified gypsum (CaSO4) significantly increased to 99% and 92%, respectively. The migration of impurities and the material balance of this process were then analyzed. Most importantly, the purified gypsum showed high CO2 sequestration efficiency for CO2 mineral sequestration, through which a high value-added CaCO3 product was obtained.
Clinical parameters predictors of malignant transformation of recurrent parotid pleomorphic adenoma
Authors: Pei Yu , Li Wenlu
Published: March 2023

Malignant transformation (MT) in recurrent parotid pleomorphic adenomas (PAs) is rare; therefore its occurrence lacks reliable predictive factors. Our goal was to clarify the predictors for MT of recurrent parotid PAs based on preoperative clinical parameters. Patients with a clinical diagnosis of recurrent parotid PA were retrospectively enrolled. The association between clinicopathologic variables and MT of PA was assessed using univariate and multivariate analyses. MT occurred in 11.8% of the 467 patients. In univariate analysis, three or more previous recurrences, newly developed facial nerve paralysis, difficulty in mouth opening, tumors with the largest tumor diameter ≥ 2.4 cm, and abnormal neck lymph node enlargement were associated with MT occurrence. Further, multivariate analysis showed that three or more previous recurrences, newly developed facial nerve paralysis, difficulty in mouth opening, and abnormal neck lymph node enlargement were independently related to MT. MT of recurrent PA was not uncommon. Clinical signs of malignancy included newly developed facial nerve paralysis, difficulty in mouth opening, three or more previous recurrences, and abnormal neck lymph node enlargement.
Group refractive index via auto-differentiation and neural networks
Authors: Alagappan G. , Png C. E.
Published: March 2023

In this article, using principles of automatic differentiation, we demonstrate a generic deep learning representation of group refractive index for photonic channel waveguides. It enables evaluation of group refractive indices in a split of second, without any traditional numerical calculations. Traditionally, the group refractive index is calculated by a repetition of the optical mode calculations via a parametric wavelength sweep of finite difference (or element) calculations. To the direct contrary, in this work, we show that the group refractive index can be quasi-instantaneously obtained from the auto-gradients of the neural networks that models the effective refractive index. We embed the wavelength dependence of the effective index in the deep learning model by applying the scaling property of the Maxwell’s equations and this eliminates the problems caused by the curse of dimensionality. This work portrays a very clear illustration on how physics-based derived optical quantities can be calculated instantly from the underlying deep learning models of the parent quantities using automatic differentiation.
Quantum causality emerging in a delayed-choice quantum Cheshire Cat experiment with neutrons
Authors: Wagner Richard , Kersten Wenzel , Lemmel Hartmut , Sponar Stephan , Hasegawa Yuji
Published: March 2023

We report an experiment with neutrons in a silicon perfect crystal interferometer, that realizes a quantum Cheshire Cat in a delayed choice setting. In our setup the quantum Cheshire Cat is established by spatially separating the particle and its property (i.e. the neutron and its spin) into the two different paths of the interferometer. The condition for a delayed choice setting is achieved by postponing the choice of path assignment for the quantum Cheshire Cat, i.e. which path is taken by the particle and which by its property, until the point in time when the neutron wave function has already split and entered the interferometer. The results of the experiment suggest not only the fact that the neutrons and its spin are separated and take different paths in the interferometer, but also quantum-mechanical causality is implied, insomuch that the behavior of a quantum system is affected by the choice of the selection at a later point in time.
Identification of two early blood biomarkers ACHE and CLEC12A for improved risk stratification of critically ill COVID-19 patients
Authors: Kattner Simone , Müller Jan , Glanz Karolina , Manoochehri Mehdi , Sylvester Caroline , Vainshtein Yevhen , Berger Marc Moritz , Brenner Thorsten , Sohn Kai
Published: March 2023

In order to identify biomarkers for earlier prediction of COVID-19 outcome, we collected blood samples from patients with fatal outcomes (non-survivors) and with positive clinical outcomes (survivors) at ICU admission and after seven days. COVID-19 survivors and non-survivors showed significantly different transcript levels for 93 genes in whole blood already at ICU admission as revealed by RNA-Seq. These differences became even more pronounced at day 7, resulting in 290 differentially expressed genes. Many identified genes play a role in the differentiation of hematopoietic cells. For validation, we designed an RT-qPCR assay for C-type lectin domain family 12 member A (CLEC12A) and acetylcholinesterase (ACHE), two transcripts that showed highest potential to discriminate between survivors and non-survivors at both time points. Using our combined RT-qPCR assay we examined 33 samples to accurately predict patient survival with an AUROC curve of 0.931 (95% CI = 0.814–1.000) already at ICU admission. CLEC12A and ACHE showed improved prediction of patient outcomes compared to standard clinical biomarkers including CRP and PCT in combination (AUROC = 0.403, 95% CI = 0.108–0.697) or SOFA score (AUROC = 0.701 95% CI = 0.451–0.951) at day 0. Therefore, analyzing CLEC12A and ACHE gene expression from blood may provide a promising approach for early risk stratification of severely ill COVID-19 patients.
Post-fumigation sub-lethal activities of phosphine and ethyl formate on survivorship, fertility and female sex pheromone production of Callosobruchus chinensis (L.)
Authors: Chiluwal Kashinath , Lee Byung Ho , Kwon Tae Hyung , Kim Junheon , Park Chung Gyoo
Published: March 2023

Phosphine (PH3) and ethyl formate (EF), the two popular fumigant disinfectants of stored product insect pests, are primarily evaluated for their knock down effects without considering their post-fumigation sub-lethal activities. The sub-lethal activities (adult survivorship, fecundity, sterility and female sex pheromone production) of the fumigants were evaluated on a field-to-storage insect pest adzuki bean beetle, Callosobruchus chinensis (L.). The adults’ survivorship and female fecundity, both were dose-dependently affected by sub-lethal PH3 and EF fumigation exposures. Hatchability of the eggs laid by fumigated female adults were also significantly affected. Gas-chromatography mass-spectrometry analysis of solid-phase micro-extraction from virgin fumigated C. cinensis females revealed that the PH3 LC25 (the lethal concentration required to kill the 25% of the population) fumigated female C. chinensis released significantly less amount of the pheromone components. In contrast, EF LC25 exposure did not affect the pheromone release. This study unveils the facts that the EF and PH3 fumigation have detrimental bioactivities against C. chinensis. Notably, this suggests to consider the sub-lethal EF and PH3 fumigation rather than the dose required to instantly kill all the C. chinensis individuals for disinfestation of stored adzuki bean.
Functional interaction between Vangl2 and N-cadherin regulates planar cell polarization of the developing neural tube and cochlear sensory epithelium
Authors: Nagaoka Tadahiro , Katsuno Tatsuya , Fujimura Kyoka , Tsuchida Kunihiro , Kishi Masashi
Published: March 2023

Although the core constituents of the Wnt/planar cell polarity (PCP) signaling have been extensively studied, their downstream molecules and protein–protein interactions have not yet been fully elucidated. Here, we show genetic and molecular evidence that the PCP factor, Vangl2, functionally interacts with the cell–cell adhesion molecule, N-cadherin (also known as Cdh2), for typical PCP-dependent neural development. Vangl2 and N-cadherin physically interact in the neural plates undergoing convergent extension. Unlike monogenic heterozygotes, digenic heterozygous mice with Vangl2 and Cdh2 mutants exhibited defects in neural tube closure and cochlear hair cell orientation. Despite this genetic interaction, neuroepithelial cells derived from the digenic heterozygotes did not show additive changes from the monogenic heterozygotes of Vangl2 in the RhoA–ROCK–Mypt1 and c-Jun N-terminal kinase (JNK)–Jun pathways of Wnt/PCP signaling. Thus, cooperation between Vangl2 and N-cadherin is at least partly via direct molecular interaction; it is essential for the planar polarized development of neural tissues but not significantly associated with RhoA or JNK pathways.
Reliable cell retention of mammalian suspension cells in microfluidic cultivation chambers
Authors: Schmitz Julian , Stute Birgit , Täuber Sarah , Kohlheyer Dietrich , von Lieres Eric , Grünberger Alexander
Published: March 2023

Microfluidic cultivation, with its high level of environmental control and spatio-temporal resolution of cellular behavior, is a well-established tool in today’s microfluidics. Yet, reliable retention of (randomly) motile cells inside designated cultivation compartments still represents a limitation, which prohibits systematic single-cell growth studies. To overcome this obstacle, current approaches rely on complex multilayer chips or on-chip valves, which makes their application for a broad community of users infeasible. Here, we present an easy-to-implement cell retention concept to withhold cells inside microfluidic cultivation chambers. By introducing a blocking structure into a cultivation chamber’s entrance and nearly closing it, cells can be manually pushed into the chamber during loading procedures but are unable to leave it autonomously in subsequent long-term cultivation. CFD simulations as well as trace substance experiments confirm sufficient nutrient supply within the chamber. Through preventing recurring cell loss, growth data obtained from Chinese hamster ovary cultivation on colony level perfectly match data determined from single-cell data, which eventually allows reliable high throughput studies of single-cell growth. Due to its transferability to other chamber-based approaches, we strongly believe that our concept is also applicable for a broad range of cellular taxis studies or analyses of directed migration in basic or biomedical research.
A framework for multi-sensor satellite data to evaluate crop production losses: the case study of 2022 Pakistan floods
Authors: Qamer Faisal Mueen , Abbas Sawaid , Ahmad Bashir , Hussain Abid , Salman Aneel , Muhammad Sher , Nawaz Muhammad , Shrestha Sravan , Iqbal Bilal , Thapa Sunil
Published: March 2023

In August 2022, one of the most severe floods in the history of Pakistan was triggered due to the exceptionally high monsoon rainfall. It has affected ~ 33 million people across the country. The agricultural losses in the most productive Indus plains aggravated the risk of food insecurity in the country. As part of the loss and damage (L&D) assessment methodologies, we developed an approach for evaluating crop-specific post-disaster production losses based on multi-sensor satellite data. An integrated assessment was performed using various indicators derived from pre- and post-flood images of Sentinel-1 (flood extent mapping), Sentinel-2 (crop cover), and GPM (rainfall intensity measurements) to evaluate crop-specific losses. The results showed that 2.5 million ha (18% of Sindh’s total area) was inundated out of which 1.1 million ha was cropland. The remainder of crop damage came from the extreme rainfall downpour, flash floods and management deficiencies. Thus approximately 57% (2.8 million ha) of the cropland was affected out of the 4.9 million ha of agricultural area in Sindh. The analysis indicated expected production losses of 88% (3.1 million bales), 80% (1.8 million tons), and 61% (10.5 million tons) for cotton, rice, and sugarcane. This assessment provided useful tools to evaluate the L&D of agricultural production and to develop evidence-based policies enabling post-flood recovery, rehabilitation of people and restoration of livelihood.
Suppression of CEBPδ recovers exhaustion in anti-metastatic immune cells
Authors: Yin Chenxue , Kato Masayoshi , Tomita Takeshi , Han Yibing , Hiratsuka Sachie
Published: March 2023

The pre-metastatic microenvironment consists of pro-metastatic and anti-metastatic immune cells in the early stages of cancer, when the primary tumor begins to proliferate. Redundantly, pro-inflammatory immune cells predominated during tumor growth. Although it is well known that pre-metastatic innate immune cells and immune cells fighting primary tumor cells become exhausted, the mechanism by which this occurs is unknown. We discovered that anti-metastatic NK cells were mobilized from the liver to the lung during primary tumor progression and that the transcription factor CEBPδ, which was upregulated in a tumor-stimulated liver environment, inhibited NK cell attachment to the fibrinogen-rich bed in pulmonary vessels and sensitization to the environmental mRNA activator. CEBPδ-siRNA treated anti-metastatic NK cells regenerated the binding proteins that support sitting in fibrinogen-rich soil, such as vitronectin and thrombospondin, increasing fibrinogen attachment. Furthermore, CEBPδ knockdown restored an RNA-binding protein, ZC3H12D, which captured extracellular mRNA to increase tumoricidal activity. Refreshed NK cells using CEBPδ-siRNA with anti-metastatic abilities would work at metastatic risk areas in the pre-metastatic phase, resulting in a reduction in lung metastasis. Furthermore, tissue-specific siRNA-based therapy in lymphocyte exhaustion may be beneficial in the treatment of early metastases.
The distribution of submerged macrophytes in response to intense solar radiation and salinity reveals hydrogen peroxide as an abiotic stress indicator
Authors: Asaeda Takashi , Rashid Md Harun , Liping Xia , Vamsi-Krishna Lekkala , Barnuevo Abner , Takeuchi Chihiro , Rahman Mizanur
Published: March 2023

The feasible condition for submerged macrophyte growth is hard to understand as many environmental factors contribute to establishing macrophyte distribution with different intensities generating excess reactive oxygen species (ROS). Among various kinds of ROS, hydrogen peroxide (H2O2) is relatively stable and can be measured accurately. Thus, for the quantification of submerged macrophyte species, H2O2 can be used to evaluate their distribution in a lake. Submerged macrophytes, such as Potamogeton anguillanus, were abundant in Lake Shinji. The largest biomass distribution was around 1.35 m deep, under low solar radiation intensity, and nearly no biomass was found less than 0.3 m deep, where solar radiation was high. Tissue H2O2 concentrations varied in response to the diurnal photosynthetically active radiation (PAR) intensity, which was followed by antioxidant activities, though slightly delayed. Laboratory experiments were conducted with different PAR intensities or salinity concentrations. A stable level of H2O2 was maintained up to about 200 μmol m−2 s−1 of PAR for 30 days, followed by a gradual increase as PAR increased. The H2O2 concentration increased with higher salinity. A change in Chlorophyll a (Chl-a) concentration is associated with an altering H2O2 concentration, following a unique negative relationship with H2O2 concentration. If H2O2 exceeded 45 μmol/gFW, the homeostasis collapsed, and H2O2 and Chl-a significantly declined afterward. The above findings indicate that H2O2 has a negative effect on the physiological condition of the plant. The increase in H2O2 concentration was prevented by antioxidant activities, which elevated with increasing H2O2 concentration.
A CAD system for automatic dysplasia grading on H&E cervical whole-slide images
Authors: Oliveira Sara P. , Montezuma Diana , Moreira Ana , Oliveira Domingos , Neto Pedro C. , Monteiro Ana , Monteiro João , Ribeiro Liliana , Gonçalves Sofia , Pinto Isabel M. , Cardoso Jaime S.
Published: March 2023

Cervical cancer is the fourth most common female cancer worldwide and the fourth leading cause of cancer-related death in women. Nonetheless, it is also among the most successfully preventable and treatable types of cancer, provided it is early identified and properly managed. As such, the detection of pre-cancerous lesions is crucial. These lesions are detected in the squamous epithelium of the uterine cervix and are graded as low- or high-grade intraepithelial squamous lesions, known as LSIL and HSIL, respectively. Due to their complex nature, this classification can become very subjective. Therefore, the development of machine learning models, particularly directly on whole-slide images (WSI), can assist pathologists in this task. In this work, we propose a weakly-supervised methodology for grading cervical dysplasia, using different levels of training supervision, in an effort to gather a bigger dataset without the need of having all samples fully annotated. The framework comprises an epithelium segmentation step followed by a dysplasia classifier (non-neoplastic, LSIL, HSIL), making the slide assessment completely automatic, without the need for manual identification of epithelial areas. The proposed classification approach achieved a balanced accuracy of 71.07% and sensitivity of 72.18%, at the slide-level testing on 600 independent samples, which are publicly available upon reasonable request.
Effect of bedding dip angle and dynamic load on spatial variation of microscopic failure stress of shale
Authors: Wang Miaomiao , Shao Xiaozhou , Pan Xiaohua
Published: March 2023

Physico-mechanical properties of shale are important parameters in evaluating the stability of potential wellbore and the design of hydraulic fracturing, which are primarily affected by their non-uniform spatial distribution of the microscopic physical–mechanical properties at particle scale. A series of constant strain rate experiments and stress-cycling experiments on shale specimens with different bedding dip angles were conducted to have a comprehensive understanding of the effect of the non-uniform distribution of microscopic failure stress on macroscopic physico-mechanical properties. According to the experimental results and Weibull distribution, we find that bedding dip angle and the dynamic load applying type affect the spatial distributions of microscopic failure stress. The values of crack damage stress (σcd), σcd/σucs (peak stress), εcd (strain at crack damage stress), Poissons' ratio (ν), elastic strain energy (Ue) and dissipated energy (Uirr) of the specimens with more uniform distribution of microscopic failure stress are overall higher, while εucs (peak strain)/εcd and elastic modulus (E) are lower. The dynamic load enables the spatial distributions of microscopic failure stress trend to be more homogeneous prior to the final failure with the increment of σcd/σucs, ν, Ue and Uirr and the decrement of E.
Exponential increase of transition rates in metastable systems driven by non-Gaussian noise
Authors: Baule Adrian , Sollich Peter
Published: March 2023

Noise-induced escape from metastable states governs a plethora of transition phenomena in physics, chemistry, and biology. While the escape problem in the presence of thermal Gaussian noise has been well understood since the seminal works of Arrhenius and Kramers, many systems, in particular living ones, are effectively driven by non-Gaussian noise for which the conventional theory does not apply. Here we present a theoretical framework based on path integrals that allows the calculation of both escape rates and optimal escape paths for a generic class of non-Gaussian noises. We find that non-Gaussian noise always leads to more efficient escape and can enhance escape rates by many orders of magnitude compared with thermal noise, highlighting that away from equilibrium escape rates cannot be reliably modelled based on the traditional Arrhenius–Kramers result. Our analysis also identifies a new universality class of non-Gaussian noises, for which escape paths are dominated by large jumps.
Predictive value of hyperglycemia on infection in critically ill patients with acute pancreatitis
Authors: Jin Yingzhi , Tao Shaoyu , Yu Guang , Li Chengyi , Hu Zanqun , Jiang Longjian
Published: March 2023

To analyze the predictive value of hyperglycemia on the extrapancreatic infection (EPI) and infected pancreatic necrosis (IPN) of severe patients with acute pancreatitis (AP). We enrolled 234 patients with acute pancreatitis admitted to the intensive care unit (ICU) of the Second Affiliated Hospital of Nanchang University from July 2017 to July 2022 for a retrospective cohort study. We collected maximum blood glucose values three times after admission to the ICU within 120 h (Glu1: 0–24 h, Glu2: 24–48 h, Glu3: 48–120 h), the levels of leucocyte, blood urea nitrogen (BUN), C-reactive protein (CRP), procalcitonin (PCT), and albumin within 24 h after admission to the ICU, and the BISAP and SIRS scores of all patients within 24 h. EPI was taken as the primary outcome indicator and IPN as the secondary outcome indicator. The accuracy of blood glucose values in predicting acute pancreatitis infection was measured by the area under the curve (AUC). A total of 56 patients appeared EPI. Univariate analysis showed that Glu3 was associated with IPN in critically ill patients with AP. Multivariate logistic regression analysis showed that Glu2, Glu3, and SIRS > 48 h were associated with EPI in critically ill patients with AP. The AUCs of Glu2 and Glu3 to predict EPI were 0.805(95%CI: 0.717–0.892) and 0.782(95%CI: 0.685–0.878), respectively, and the cutoff values were 12.60 mmol/L and 14.75 mmol/L, respectively. The AUC of Glu2 combined with Glu3 to predict EPI was 0.812(0.725–0.899). The maximum blood glucose on Day2-5 after admission to the ICU can predict infection in critically ill patients with AP. There are differences in etiology while glucose predicting infection. Patients with hypertriglyceridemia AP need to intervene blood glucose levels more actively and earlier, and control it more strictly.
Atrial fibrillation as a new prognosis factor in chronic patients after hospitalization: the CHRONIBERIA index
Authors: Suarez-Dono Javier , Novo-Veleiro Ignacio , Gude-Sampedro Francisco , Marinho Ricardo , Xavier-Pires Sara , Rocha Diana , Araújo-Correia João , Moreira Cecília , Beires Francisca , Pérez Danay , David Filipa , Vasco-Barreto J. , Del Corral-Beamonte Esther , Piñeiro-Fernández Juan-Carlos , Casariego-Vales Emilio , Diez-Manglano Jesús , Pose-Reino Antonio
Published: March 2023

A collaborative project in different areas of Spain and Portugal was designed to find out the variables that influence the mortality after discharge and develop a prognostic model adapted to the current healthcare needs of chronic patients in an internal medicine ward. Inclusion criteria were being admitted to an Internal Medicine department and at least one chronic disease. Patients’ physical dependence was measured through Barthel index (BI). Pfeiffer test (PT) was used to establish cognitive status. We conducted logistic regression and Cox proportional hazard models to analyze the influence of those variables on one-year mortality. We also developed an external validation once decided the variables included in the index. We enrolled 1406 patients. Mean age was 79.5 (SD = 11.5) and females were 56.5%. After the follow-up period, 514 patients (36.6%) died. Five variables were identified as significantly associated with 1 year mortality: age, being male, lower BI punctuation, neoplasia and atrial fibrillation. A model with such variables was created to estimate one-year mortality risk, leading to the CHRONIBERIA. A ROC curve was made to determine the reliability of this index when applied to the global sample. An AUC of 0.72 (0.7–0.75) was obtained. The external validation of the index was successful and showed an AUC of 0.73 (0.67–0.79). Atrial fibrillation along with an advanced age, being male, low BI score, or an active neoplasia in chronic patients could be critical to identify high risk multiple chronic conditions patients. Together, these variables constitute the new CHRONIBERIA index.
Study on thermal insulation cement and its thermal insulation characteristics for geothermal wells
Authors: Zhou Wei , Wang Chengwen , Meng Renzhou , Chen Zehua , Lu Haoxin , Chi Jialun
Published: March 2023

Reducing the heat loss in wellbore is the key for efficient development of geothermal resource. It is a reliable solution to establish a long-term stable wellbore with good thermal insulation through cementing. In this paper, the cement-based composite thermal insulation material was prepared by using cement as the cementing material, hollow glass beads, foaming agent and stabilizer as main raw materials, and other conventional admixtures. Foams and hollow glass beads can introduce gas with low thermal conductivity into cement, so as to improve the thermal insulation of composite material. Foams are produced by chemical forming process, using foaming agent, which is prepared according electrochemistry and thermodynamics, and the foam stabilizer helps foam distribute in cement slurry stably and uniformly. 10–13% hollow glass beads can significantly reduce the thermal conductivity of hardened cement, without significant adverse effects on the rheology and strength of the material. The thermal conductivity of the composite thermal insulation material can be as low as 0.2998 W·(m·K)−1, which is 62% lower than that of conventional cement, while the compressive strength is 6.10 MPa, meeting the engineering requirement. A thermal-conductivity prediction method is proposed correspondingly based on Maxwell model, and the prediction error of the newly established model is within 2%. This research can provide technical support for efficient development of geothermal resources.
Pre- and peri-natal hurricane exposure alters DNA methylation patterns in children
Authors: Kello Erin , Vieira Alexandre R. , Rivas-Tumanyan Sona , Campos-Rivera Maribel , Martinez-Gonzalez Karen G. , Buxó Carmen J. , Morou-Bermúdez Evangelia
Published: March 2023

Hurricane Maria was the worst recorded natural disaster to affect Puerto Rico. Increased stress in pregnant women during and in the aftermath of the hurricane may have induced epigenetic changes in their infants, which could affect gene expression. Stage of gestation at the time of the event was associated with significant differences in DNA methylation in the infants, especially those who were at around 20–25 weeks of gestation when the hurricane struck. Significant differences in DNA methylation were also associated with maternal mental status assessed after the hurricane, and with property damage. Hurricane Maria could have long lasting consequences to children who were exposed to this disaster during pregnancy.
Vole outbreaks may induce a tularemia disease pit that prevents Iberian hare population recovery in NW Spain
Authors: Rouco Carlos , Luque-Larena Juan José , Vidal Dolors , Mougeot François
Published: March 2023

Iberian hare populations have suffered severe declines during recent decades in Spain. Between 1970 and 1990s, a rapid increase in irrigation crop surface in NW Spain (Castilla-y-León region) was followed by a common vole massive range expansion and complete colonization of lowland irrigated agricultural landscapes from mountainous habitats. The subsequent large cyclic fluctuations in abundance of colonizing common voles have contributed to a periodic amplification of Francisellatularensis, the etiological agent that causes human tularemia outbreaks in the region. Tularemia is a fatal disease to lagomorphs, so we hypothesize that vole outbreaks would lead to disease spill over to Iberian hares, increasing prevalence of tularemia and declines among hare populations. Here we report on the possible effects that vole abundance fluctuations and concomitant tularemia outbreaks had on Iberian hare populations in NW Spain. We analysed hare hunting bag data for the region, which has been recurrently affected by vole outbreaks between 1996 and 2019. We also compiled data on F.tularensis prevalence in Iberian hares reported by the regional government between 2007 and 2016. Our results suggest that common vole outbreaks may limit the recovery of hare populations by amplifying and spreading tularemia in the environment. The recurrent rodent-driven outbreaks of tularemia in the region may result in a "disease pit" to Iberian hares: at low host densities, the rate of population growth in hares is lower than the rate at which disease-induced mortality increases with increased rodent host density, therefore, keeping hare populations on a low-density equilibrium. We highlight future research needs to clarify tularemia transmission pathways between voles and hares and confirm a disease pit process.