bluuebunny/crossref_metadata_2025 huggingface dataset:
Tradeoffs and Synergies Across Global Climate Change Adaptations in the Food‐Energy‐Water Nexus
Authors: Torhan S. , Grady C. A. , Ajibade I. , Galappaththi E. K. , Hernandez R. R. , Musah‐Surugu J. I. , Nunbogu A. M. , Segnon A. C. , Shang Y. , Ulibarri N. , Campbell D. , Joe E. T. , Penuelas J. , Sardans J. , Shah M. A. R. ,   the Global Adaptation Mapping Team
Published: March 2022

Food‐energy‐water (FEW) systems are increasingly vulnerable to natural hazards and climate change risks, yet humans depend on these systems for their daily needs, wellbeing, and survival. We investigated how adaptations related to FEW vulnerabilities are occurring and what the global community can learn about the interactions across these adaptations. We conducted a global analysis of a data set derived from scientific literature to present the first large scale assessment (n = 1,204) of evidence‐based FEW‐related climate adaptations. We found that the most frequently reported adaptations to FEW vulnerabilities by continent occurred in Africa (n = 495) and Asia (n = 492). Adaptations targeting food security were more robustly documented than those relevant to water and energy security, suggesting a greater global demand to address food security. Determining statistically significant associations, we found a network of connections between variables characterizing FEW‐related adaptations and showed interconnectedness between a variety of natural hazards, exposures, sectors, actors, cross‐cutting topics and geographic locations. Connectivity was found between the vulnerabilities food security, water, community sustainability, and response to sea level rise across cities, settlements, and key infrastructure sectors. Additionally, generalized linear regression models revealed potential synergies and tradeoffs among FEW adaptations, such as a necessity to synergistically adapt systems to protect food and water security and tradeoffs when simultaneously addressing exposures of consumption and production vs. poverty. Results from qualitative thematic coding showcased that adaptations documented as targeting multiple exposures are still limited in considering interconnectivity of systems and applying a nexus approach in their responses. These results suggest that adopting a nexus approach to future FEW‐related adaptations can have profound benefits in the management of scarce resources and with financial constraints.
Diagnosing Two‐Way Coupling in Decadal North Atlantic SST Variability Using Time‐Evolving Self‐Organizing Maps
Authors: Gu Qinxue , Gervais Melissa
Published: March 2022

Decadal variability in the North Atlantic plays a critical role in modulating regional and global climate. To identify the complex spatiotemporal patterns associated with decadal variability and diagnose mechanisms responsible spatially and over time simultaneously, we debut a novel application of a machine learning method—evolution self‐organizing maps. This time‐evolving framework is applied to a Community Earth System Model pre‐industrial simulation to identify 10‐year consecutive spatiotemporal evolutions of winter sea surface temperature (SST). Here we focus on a single evolution that transitions from SST patterns typically associated with a positive North Atlantic Oscillation (NAO) to a positive Atlantic Multidecadal Variability to a weak negative NAO and find that it can occur over just a 10‐year period. This method facilitates a new examination of buoyancy‐driven and wind‐driven ocean circulations as well as ocean‐atmosphere transient‐eddy feedbacks that confirms the importance of coupled atmosphere‐ocean dynamics in producing this decadal variability.
Trapped Under Ice: Spatial and Seasonal Dynamics of Dissolved Organic Matter Composition in Tundra Lakes
Authors: Kurek Martin R. , Frey Karen E. , Guillemette François , Podgorski David C. , Townsend‐Small Amy , Arp Christopher D. , Kellerman Anne M. , Spencer Robert G. M.
Published: March 2022

Arctic lakes store, modify, and transport large quantities of carbon from terrestrial environments to the atmosphere; however, the spatial and temporal relationships between quantity and composition of dissolved organic matter (DOM) have not been well characterized across broad arctic regions. Moreover, most arctic lake DOM compositions have been examined during the ice‐free summer, whereas DOM cycling between the ice‐covered winter months and summer have not been addressed. To resolve these spatial and seasonal uncertainties in DOM cycling, we sampled a series of arctic lakes from the North Slope of Alaska across a latitudinal gradient in the winter and summer over 3 years. Samples were analyzed for dissolved organic carbon concentration and DOM composition was characterized using optical and fluorescence properties combined with molecular‐level analysis using Fourier transform‐ion cyclotron resonance mass spectrometry. Tundra lake DOM properties including aromaticity and molecular stoichiometries were similar to other northern high‐latitude lakes, but optical parameters related to aromaticity and molecular weight were greater in major arctic rivers and in coastal lakes in the North Slope region. DOM composition was highly seasonal, with ice exclusion concentrating microbially processed DOM in the winter water columns, potentially influencing DOM cycling the following summer. However, the greatest variations in DOM composition were related to lake depth and likely other physical features including morphology and bathymetry. As the Arctic warms, we expect changes in hydrology and ice cover to enhance under‐ice microbial DOM processing, early summer photodegradation, and ultimately carbon fluxes to the atmosphere after ice‐out.
The Alps Are Dusted with Nanoplastics
Authors: Kish Stacy
Published: March 2022

A new study finds the lofted pollutants came from major European cities, but further study is required to fully understand the plastics’ transport and deposition processes.
Orbital Observations of a Marker Horizon at Gale Crater
Authors: Weitz Catherine M. , Lewis Kevin W. , Bishop Janice L. , Thomson Bradley J. , Arvidson Raymond E. , Grant John A. , Seelos Kimberly D. , Ettenborough Ivy
Published: March 2022

A dark‐toned, indurated, smooth horizon, and (or) bed (herein called “marker horizon”) is exposed across much of the northwestern, southwestern, and southeastern portions of Mount Sharp in Gale crater. Compact Reconnaissance Imaging Spectrometer for Mars spectra taken from the marker horizon exhibit evidence for the presence of high calcium pyroxene and other basaltic minerals in contrast to the hydrated sulfate signatures associated with strata above and below it. Mean dips for the marker horizon and sulfate‐bearing strata are 1–5° with almost all azimuths radially away from the center of Mount Sharp. The marker horizon thickness varies between <1 and 3 m and its elevation changes by 1.6 km across the mound. Surface slopes along the sulfate‐bearing strata above and below the marker horizon are typically 20°–40° compared to <5° surface slopes on the marker horizon. Features observed on the marker horizon include ridges, fractures, faults, layering, oval depressions, small craters, and possible yardangs/indurated bedforms. We interpret the marker horizon to be a single unit that formed contemporaneously across Mount Sharp during the same depositional sequence that created the sulfate‐bearing strata. Plausible formation mechanisms for the marker horizon include (1) emplacement of a more indurated sulfate unit, either from (a) primary deposition or (b) secondary diagenesis; (2) deposition of a more resistant sandstone unit during a brief drier period; (3) emplacement of a volcanic ash deposit laid down in the midst of the sulfate formation period; or (4) a lag deposit created during a drier period. Based on our observations, origins (1a) and (3) are the most plausible.
Patient-derived pancreatic cancer-on-a-chip recapitulates the tumor microenvironment
Authors: Haque Muhammad R. , Wessel Caitlin R. , Leary Daniel D. , Wang Chengyao , Bhushan Abhinav , Bishehsari Faraz
Published: March 2022

The patient population suffering from pancreatic ductal adenocarcinoma (PDAC) presents, as a whole, with a high degree of molecular tumor heterogeneity. The heterogeneity of PDAC tumor composition has complicated treatment and stalled success in clinical trials. Current in vitro techniques insufficiently replicate the intricate stromal components of PDAC tumor microenvironments (TMEs) and fail to model a given tumor’s unique genetic phenotype. The development of patient-derived organoids (PDOs) has opened the door for improved personalized medicine since PDOs are derived directly from patient tumors, thus preserving the tumors’ unique behaviors and genetic phenotypes. This study developed a tumor-chip device engineered to mimic the PDAC TME by incorporating PDOs and stromal cells, specifically pancreatic stellate cells and macrophages. Establishing PDOs in a multicellular microfluidic chip device prolongs cellular function and longevity and successfully establishes a complex organotypic tumor environment that incorporates desmoplastic stroma and immune cells. When primary cancer cells in monoculture were subjected to stroma-depleting agents, there was no effect on cancer cell viability. However, targeting stroma in our tumor-chip model resulted in a significant increase in the chemotherapy effect on cancer cells, thus validating the use of this tumor-chip device for drug testing.
Gene expression study in monocytes: evidence of inflammatory dysregulation in early-onset obsessive-compulsive disorder
Authors: Rodríguez Natalia , Lázaro Luisa , Ortiz Ana E. , Morer Astrid , Martínez-Pinteño Albert , Segura Alex G. , Gassó Patricia , Mas Sergi
Published: March 2022

Obsessive-compulsive disorder (OCD) has a complex etiology that seems to include immune dysfunction and alterations in circulating monocytes. To investigate the immune basis and the functional dysregulation of monocytes in this disease, we analyzed gene expression in the peripheral monocytes of pediatric patients with OCD (N = 102) compared to controls (N = 47). We examined gene expression in primary cultures of peripheral monocytes from participants, under basal conditions and under exposure to lipopolysaccharide (LPS) to stimulate immune response. Whole-genome expression was assessed in 8 patients and 8 controls. Differentially expressed genes were identified followed by protein-protein interaction network construction and functional annotation analysis to identify the genes and biological processes that are altered in the monocytes of OCD patients. We also explored the expression levels of selected genes in monocytes from the other participants using qPCR. Several changes in gene expression were observed in the monocytes of OCD patients, with several immune processes involved under basal conditions (antigen processing and presentation, regulation of immune system and leukocyte cell adhesion) and after LPS stimulation (immune and inflammatory response, cytokine production and leukocyte activation). Despite the qPCR analysis provided no significant differences between patients and controls, high correlations were observed between the expression levels of some of the genes and inflammatory markers (i.e., T helper 17 and regulatory T cell levels, total monocyte and proinflammatory monocyte subset levels, and the cytokine production by resting and stimulated monocytes) of the study participants. Our findings provide more evidence of the involvement of monocyte dysregulation in early-onset OCD, indicating a proinflammatory predisposition and an enhanced immune response to environmental triggers.
Tctp regulates the level and localization of Foxo for cell growth in Drosophila
Authors: Nam Sujin , Le Thao Phuong , Chung SeYeon , Choi Kwang-Wook
Published: March 2022

Regulation of cell size is crucial for organ development. Insulin signaling regulates organ size by antagonizing the subgroup O of forkhead box transcription factor (Foxo) through 14-3-3 in Drosophila. However, mechanisms for controlling the level and the nuclear localization of Foxo in developing organs are not well understood. Here, we investigate the role of Drosophila Translationally controlled tumor protein (Tctp) and its interacting partner 14-3-3 in Foxo regulation during organ development. Foxo overexpression in the developing eye disc results in growth inhibition. We show that Tctp overexpression antagonizes the Foxo effect by downregulating the Foxo level in the eye disc. Foxo overexpression or knockdown of Tctp in the larval salivary gland results in reduced gland size, mainly due to reduced cell size by defects in endoreplication. Whereas 14-3-3ζ knockdown has a negligible effect, knockdown of 14-3-3ε mimics the effect of Foxo overexpression or Tctp knockdown, suggesting an isoform-specific role of 14-3-3. Unlike nuclear enrichment of the endogenous Foxo in the salivary gland, overexpressed Foxo protein is largely distributed in the cytoplasm, and this mislocalization is restored by Tctp overexpression. Opposite to the effect of Tctp overexpression, Tctp knockdown increases cytoplasmic Foxo levels while decreasing nuclear Foxo levels. Together, our data suggest that Tctp and 14-3-3ε play critical roles in cell growth by reducing cytoplasmic Foxo levels. Knockdown of human TCTP also elevates the level of cytoplasmic FOXO1 in HeLa cells, suggesting that human TCTP may have a conserved role in downregulating FOXO in human cells.
Fibre optic distributed acoustic sensing of volcanic events
Authors: Jousset Philippe , Currenti Gilda , Schwarz Benjamin , Chalari Athena , Tilmann Frederik , Reinsch Thomas , Zuccarello Luciano , Privitera Eugenio , Krawczyk Charlotte M.
Published: March 2022

Understanding physical processes prior to and during volcanic eruptions has improved significantly in recent years. However, uncertainties about subsurface structures distorting observed signals and undetected processes within the volcano prevent volcanologists to infer subtle triggering mechanisms of volcanic phenomena. Here, we demonstrate that distributed acoustic sensing (DAS) with optical fibres allows us to identify volcanic events remotely and image hidden near-surface volcanic structural features. We detect and characterize strain signals associated with explosions and locate their origin using a 2D-template matching between picked and theoretical wave arrival times. We find evidence for non-linear grain interactions in a scoria layer of spatially variable thickness. We demonstrate that wavefield separation allows us to incrementally investigate the ground response to various excitation mechanisms. We identify very small volcanic events, which we relate to fluid migration and degassing. Those results provide the basis for improved volcano monitoring and hazard assessment using DAS.
Northwestern Pacific tropical cyclone activity enhanced by increased Asian dust emissions during the Little Ice Age
Authors: Yang Yang , Piper David J. W. , Xu Min , Gao Jianhua , Jia Jianjun , Normandeau Alexandre , Chu Dongdong , Zhou Liang , Wang Ya Ping , Gao Shu
Published: March 2022

Instrumental records reveal that intense tropical cyclone (TC) activity varies with tropical sea surface temperature (SST) on annual-decadal scales. Drivers of intense TC activity at the centennial-millennial scale are less clear, due to the sparseness of pre-observational reconstructions. Here, we present a new 2 kyr continuous activity record of intense TCs from offshore eastern China. Our reconstruction indicates that this site witnessed enhanced TC activity during relatively warm periods, with a widespread increase in TC activity during the later part of the Little Ice Age. This latter observation reveals that enhanced TC activity was synchronized with increased Asian dust emissions during the Little Ice Age. TC activity was also lower in the late Roman Warm Period, when SST was higher but Asian dust emissions were lower than in the early phase. Such patterns suggest a centennial-millennial link between TC climatology and a combination of SST changes and Asian dust levels.
Double helical π-aggregate nanoarchitectonics for amplified circularly polarized luminescence
Authors: Wang Yuan , Niu Dian , Ouyang Guanghui , Liu Minghua
Published: March 2022

The canonical double helical π-stacked array of base pairs within DNA interior has inspired the interest in supramolecular double helical architectures with advanced electronic, magnetic and optical functions. Here, we report a selective-recognized and chirality-matched co-assembly strategy for the fabrication of fluorescent π-amino acids into double helical π-aggregates, which show exceptional strong circularly polarized luminescence (CPL). The single crystal structure of the optimal combination of co-assemblies shows that the double-stranded helical organization of these π-amino acids is cooperatively assisted by both CH-π and hydrogen-bond arrays with chirality match. The well-defined spatial arrangement of the π-chromophores could effectively suppress the non-radiative decay pathways and facilitate chiral exciton couplings, leading to superior CPL with a strong figure of merit (glum = 0.14 and QY = 0.76). Our findings might open a new door for developing DNA-inspired chiroptical materials with prominent properties by enantioselective co-assembly initiated double helical π-aggregation.
SHAPE-guided RNA structure homology search and motif discovery
Authors: Morandi Edoardo , van Hemert Martijn J. , Incarnato Danny
Published: March 2022

The rapidly growing popularity of RNA structure probing methods is leading to increasingly large amounts of available RNA structure information. This demands the development of efficient tools for the identification of RNAs sharing regions of structural similarity by direct comparison of their reactivity profiles, hence enabling the discovery of conserved structural features. We here introduce SHAPEwarp, a largely sequence-agnostic SHAPE-guided algorithm for the identification of structurally-similar regions in RNA molecules. Analysis of Dengue, Zika and coronavirus genomes recapitulates known regulatory RNA structures and identifies novel highly-conserved structural elements. This work represents a preliminary step towards the model-free search and identification of shared and conserved RNA structural features within transcriptomes.
Associations with response to Poly(ADP-ribose) Polymerase (PARP) inhibitors in patients with metastatic breast cancer
Authors: Desnoyers A. , Nadler M. , Wilson B. E. , Stajer S. , Amir E.
Published: March 2022

PARP inhibitors (PARPi) have modest antitumor activity in patients with advanced breast cancer and mutation in BRCA. It is unclear whether some subgroups derive greater benefit from treatment. MEDLINE and EMBASE were searched from inception to March 2021 to identify trials of PARPi in patients with metastatic breast cancer. Objective response rate (ORR) and clinical benefit rate (CBR) to PARPi were extracted and pooled in a meta-analysis using the Mantel Haenszel random effects model. Meta-regression explored the influence of patient and tumor characteristics on ORR and CBR. For randomized trials, hazard ratio comparing PARPi to control therapy were pooled using inverse variance and random effects. Analysis included 43 studies comprising 2409 patients. Among these, 1798 (75%) patients had BRCA mutations and 1146 (48%) were triple negative. In 10 studies (28%; n = 680 patients), the PARPi was given in combination with platinum-based chemotherapy. Weighted mean ORR was 45%; 64% when combined with platinum vs 37% with PARPi monotherapy (p < 0.001). Previous platinum-based chemotherapy was associated with lower ORR (p = 0.02). Compared to standard chemotherapy, progression-free survival was improved (HR 0.64, p < 0.001), but there was no difference in overall survival (HR 0.87, p = 0.06). There were no differences in ORR or CBR between BRCA1 and BRCA2 mutations. PARPi are more active in combination with platinum than as monotherapy, with lower response if given as monotherapy after platinum exposure. Significant improvements in ORR translated to modest improvement in progression-free, but not overall survival. There was no association between ORR and BRCA mutations.
Surrounding road density of child care centers in Australia
Authors: Han Chunlei , Xu Rongbin , Wei Xiaoyan , Zhang Yajuan , Liu Jiahui , Zhang Yuguo , Ye Tingting , Wang Siwei , Yu Wenhua , Guo Suying , Han Kun , Ding Yimin , Wang Jinfeng , Guo Yuming , Li Shanshan
Published: March 2022

High surrounding road density could increase traffic-related air pollution, noise and the risk of traffic injuries, which are major public health concerns for children. We collected geographical data for all childcare centers (16,146) in Australia and provided the data on the road density surrounding them. The road density was represented by the child care center’s nearest distance to main road and motorway, and the length of main road/motor way within 100~1000-meter buffer zone surrounding the child care center. We also got the data of PM2.5 concentration from 2013 to 2018 and standard Normalized Difference Vegetation Index (NDVI) data from 2013 to 2019 according to the longitude and latitude of the child care centers. This data might help researchers to evaluate the health impacts of road density on child health, and help policy makers to make transportation, educational and environmental planning decisions to protect children from exposure to traffic-related hazards in Australia.
A residential labeled dataset for smart meter data analytics
Authors: Pereira Lucas , Costa Donovan , Ribeiro Miguel
Published: March 2022

Smart meter data is a cornerstone for the realization of next-generation electrical power grids by enabling the creation of novel energy data-based services like providing recommendations on how to save energy or predictive maintenance of electric appliances. Most of these services are developed on top of advanced machine-learning algorithms, which rely heavily on datasets for training, testing, and validation purposes. A limitation of most existing datasets, however, is the scarcity of labels. The SustDataED2 dataset described in this paper contains 96 days of aggregated and individual appliance consumption from one household in Portugal. The current and voltage waveforms were sampled at 12.8 kHz, and the individual consumption of 18 appliances was sampled at 0.5 Hz. The dataset also contains the timestamps of the ON-OFF transitions of the monitored appliances for the entire deployment duration, providing the necessary ground truth for the evaluation of machine learning problems, particularly Non-Intrusive Load Monitoring. The data is accessible in easy-to-use audio and comma-separated formats.
Tissue-engineered collagenous fibrous cap models to systematically elucidate atherosclerotic plaque rupture
Authors: Wissing T. B. , Van der Heiden K. , Serra S. M. , Smits A. I. P. M. , Bouten C. V. C. , Gijsen F. J. H.
Published: March 2022

A significant amount of vascular thrombotic events are associated with rupture of the fibrous cap that overlie atherosclerotic plaques. Cap rupture is however difficult to predict due to the heterogenous composition of the plaque, unknown material properties, and the stochastic nature of the event. Here, we aim to create tissue engineered human fibrous cap models with a variable but controllable collagen composition, suitable for mechanical testing, to scrutinize the reciprocal relationships between composition and mechanical properties. Myofibroblasts were cultured in 1 × 1.5 cm-sized fibrin-based constrained gels for 21 days according to established (dynamic) culture protocols (i.e. static, intermittent or continuous loading) to vary collagen composition (e.g. amount, type and organization). At day 7, a soft 2 mm ∅ fibrin inclusion was introduced in the centre of each tissue to mimic the soft lipid core, simulating the heterogeneity of a plaque. Results demonstrate reproducible collagenous tissues, that mimic the bulk mechanical properties of human caps and vary in collagen composition due to the presence of a successfully integrated soft inclusion and the culture protocol applied. The models can be deployed to assess tissue mechanics, evolution and failure of fibrous caps or complex heterogeneous tissues in general.
Tomato (Solanum lycopersicum L.) accumulation and allergenicity in response to nickel stress
Authors: Roccotiello Enrica , Nicosia Elena , Pierdonà Lorenzo , Marescotti Pietro , Ciardiello Maria Antonietta , Giangrieco Ivana , Mari Adriano , Zennaro Danila , Dozza Denise , Brancucci Michele , Mariotti Mauro
Published: March 2022

Vegetables represent a major source of Ni exposure. Environmental contamination and cultural practices can increase Ni amount in tomato posing significant risk for human health. This work assesses the tomato (Solanum lycopersicum L.) response to Ni on the agronomic yield of fruits and the related production of allergens. Two cultivars were grown in pots amended with Ni 0, 30, 60, 120, and 300 mg kg−1, respectively. XRF and ICP-MS analyses highlighted the direct increase of fruit Ni content compared to soil Ni, maintaining a stable biomass. Leaf water content increased at Ni 300 mg kg−1. Total protein content and individual allergenic components were investigated using biochemical (RP-HPLC and N-terminal amino acid sequencing) and immunological (inhibition tests of IgE binding by SPHIAa assay on the FABER testing system) methodologies. Ni affected the fruit tissue concentration of pathogenesis-related proteins and relevant allergens (LTP, profilin, Bet v 1-like protein and TLP). This study elucidates for the first time that tomato reacts to exogenous Ni, uptaking the metal while changing its allergenic profiles, with potential double increasing of exposure risks for consumers. This evidence highlighted the importance of adequate choice of low-Ni tomato cultivars and practices to reduce Ni uptake by potentially contaminated matrices.
A machine learning model to estimate myocardial stiffness from EDPVR
Authors: Babaei Hamed , Mendiola Emilio A. , Neelakantan Sunder , Xiang Qian , Vang Alexander , Dixon Richard A. F. , Shah Dipan J. , Vanderslice Peter , Choudhary Gaurav , Avazmohammadi Reza
Published: March 2022

In-vivo estimation of mechanical properties of the myocardium is essential for patient-specific diagnosis and prognosis of cardiac disease involving myocardial remodeling, including myocardial infarction and heart failure with preserved ejection fraction. Current approaches use time-consuming finite-element (FE) inverse methods that involve reconstructing and meshing the heart geometry, imposing measured loading, and conducting computationally expensive iterative FE simulations. In this paper, we propose a machine learning (ML) model that feasibly and accurately predicts passive myocardial properties directly from select geometric, architectural, and hemodynamic measures, thus bypassing exhaustive steps commonly required in cardiac FE inverse problems. Geometric and fiber-orientation features were chosen to be readily obtainable from standard cardiac imaging protocols. The end-diastolic pressure-volume relationship (EDPVR), which can be obtained using a single-point pressure-volume measurement, was used as a hemodynamic (loading) feature. A comprehensive ML training dataset in the geometry-architecture-loading space was generated, including a wide variety of partially synthesized rodent heart geometry and myofiber helicity possibilities, and a broad range of EDPVRs obtained using forward FE simulations. Latin hypercube sampling was used to create 2500 examples for training, validation, and testing. A multi-layer feed-forward neural network (MFNN) was used as a deep learning agent to train the ML model. The model showed excellent performance in predicting stiffness parameters$$a_f$$afand$$b_f$$bfassociated with fiber direction ($$R^2_{a_f}=99.471\%$$Raf2=99.471%and$$R^2_{b_f}=92.837\%$$Rbf2=92.837%). After conducting permutation feature importance analysis, the ML performance further improved for$$b_f$$bf($$R^2_{b_f}=96.240\%$$Rbf2=96.240%), and the left ventricular volume and endocardial area were found to be the most critical geometric features for accurate predictions. The ML model predictions were evaluated further in two cases: (i) rat-specific stiffness data measured using ex-vivo mechanical testing, and (ii) patient-specific estimation using FE inverse modeling. Excellent agreements with ML predictions were found for both cases. The trained ML model offers a feasible technology to estimate patient-specific myocardial properties, thus, bridging the gap between EDPVR, as a confounded organ-level metric for tissue stiffness, and intrinsic tissue-level properties. These properties provide incremental information relative to traditional organ-level indices for cardiac function, improving the clinical assessment and prognosis of cardiac diseases.
Identification, analysis of deleterious SNPs of the human GSR gene and their effects on the structure and functions of associated proteins and other diseases
Authors: Vyas Bharti , Bhowmik Ratul , Akhter Mymoona , Ahmad Farhan Jalees
Published: March 2022

Hereditary glutathione reductase deficiency, caused by mutations of the GSR gene, is an autosomal recessive disorder characterized by decreased glutathione disulfide (GSSG) reduction activity and increased thermal instability. This study implemented computational analysis to screen the most likely mutation that might be associated with hereditary glutathione reductase deficiency and other diseases. Using ten online computational tools, the study revealed four nsSNPs among the 17 nsSNPs identified as most deleterious and disease associated. Structural analyses and evolutionary confirmation study of native and mutant GSR proteins using the HOPE project and ConSruf. HOPE revealed more flexibility in the native GSR structure than in the mutant structure. The mutation in GSR might be responsible for changes in the structural conformation and function of the GSR protein and might also play a significant role in inducing hereditary glutathione reductase deficiency. LD and haplotype studies of the gene revealed that the identified variations rs2978663 and rs8190955 may be responsible for obstructive heart defects (OHDs) and hereditary anemia, respectively. These interethnic differences in the frequencies of SNPs and haplotypes might help explain the unpredictability that has been reported in association studies and can contribute to predicting the pharmacokinetics and pharmacodynamics of drugs that make use of GSR.
Variant landscape of the RYR1 gene based on whole genome sequencing of the Singaporean population
Authors: Foo Claribel Tian Yu , To Yi Hui , Irwanto Astrid , Ng Alvin Yu-Jin , Yan Benedict , Chew Sophia Tsong Huey , Liu Jianjun , Ti Lian Kah
Published: March 2022

The RYR1 gene codes for a ryanodine receptor which is a calcium release channel in the skeletal muscle sarcoplasmic reticulum. It is associated with Malignant Hyperthermia (MH) and congenital myopathies including Central Core Disease (CCD), Multiminicore Disease (MMD) and Congenital Fibre-Type Disproportion (CFTD). There is currently little information on the epidemiology of RYR1 variants in Asians. Our study aims to describe the RYR1 variant landscape in a Singapore cohort unselected for RYR1-associated conditions. Data was retrieved from the SG10K pilot project, where whole genome sequencing was performed on volunteers unselected and undetermined for RYR1-associated conditions. Variants were classified based on pathogenicity using databases ClinVar and InterVar. Allele frequencies of pathogenic variants were compared between Chinese, Indians and Malays. Using databases ExAC, GnomAD and GenomeAsia 100k study, we further compared local allele frequencies to those in Europe, America and Asia. Data was analysed using R Commander. Significant P value was set at p < 0.05. Majority of the RYR1 variants were missense mutations. We identified four pathogenic and four likely pathogenic RYR1 variants. All were related to the aforementioned RYR1-associated conditions. There were 6 carriers of RYR1 pathogenic variants amongst 4810 individuals, corresponding to an allele frequency of 0.06%. The prevalence of pathogenic variants was the highest amongst Indians (4 in 1127 individuals) (p = 0.030). Majority of pathogenic and likely pathogenic mutations were missense and located in mutational hotspots. These variants also occurred at higher frequencies in Asians than globally. This study describes the variant landscape of the RYR1 gene in Singapore. This knowledge will facilitate genetic screening for RYR1-related conditions.
Black pepper and tarragon essential oils suppress the lipolytic potential and the type II secretion system of P. psychrophila KM02
Authors: Tomaś Natalia , Myszka Kamila , Wolko Łukasz
Published: March 2022

Given the increasing consumer demand for raw, nonprocessed, safe, and long shelf-life fish and seafood products, research concerning the application of natural antimicrobials as alternatives to preservatives is of great interest. The aim of the following paper was to evaluate the effect of essential oils (EOs) from black pepper (BPEO) and tarragon (TEO), and their bioactive compounds: limonene (LIM), β-caryophyllene (CAR), methyl eugenol (ME), and β-phellandrene (PHE) on the lipolytic activity and type II secretion system (T2SS) of Pseudomonas psychrophila KM02 (KM02) fish isolates grown in vitro and in fish model conditions. Spectrophotometric analysis with the p-NPP reagent showed inhibition of lipolysis from 11 to 46%. These results were confirmed by RT-qPCR, as the expression levels of lipA, lipB, and genes encoding T2SS were also considerably decreased. The supplementation of marinade with BPEO and TEO contributed to KM02 growth inhibition during vacuum packaging of salmon fillets relative to control samples. Whole-genome sequencing (WGS) provided insight into the spoilage potential of KM02, proving its importance as a spoilage microorganism whose metabolic activity should be inhibited to maintain the quality and safety of fresh fish in the food market.
The gap between perceived mental health needs and actual service utilization in Australian adolescents
Authors: Islam Md Irteja , Yunus Fakir Md , Isha Samia Naz , Kabir Enamul , Khanam Rasheda , Martiniuk Alexandra
Published: March 2022

Despite being highly prevalent, adolescent mental health problems are undertreated. To better understand the mental health treatment gap, we assessed the prevalence and correlates of help-seeking, including perceived need for care and access to that care. Data were drawn from Young Minds Matter (YMM) survey—the second Australian child and adolescents survey of mental health and wellbeing. Parent-reported data and self-reported child data were combined into one dataset to analyse 2464 Australian adolescents aged 13–17 years. We employed bivariate and multivariate logistic regression models to assess the correlation between independent variables (professionally assessed with mental disorders only, self-reported self-harm/suicidality only and both) and their distribution over outcome variables (perceived need and service use). Mental disorders include depression, anxiety, ADHD and conduct disorder. Our study revealed 15.0%, 4.6% and 7.7% had professionally assessed with mental disorders only, self-reported self-harm/suicidality only and both, respectively. Overall, 47.4% and 27.5% of adolescents respectively perceived need for care and used services in the past-12-months. While among those only who perceived the need, only 53% of adolescents used any services. Professionally assessed with mental disorders only, self-reported self-harm/suicidality only and both were associated with higher likelihood of perceived need and service use (p < 0.001 for all). However, adolescents who self-reported self-harm/suicidality only were not found to be significantly associated with service use among those who perceived the need for care. Adolescents who perceived the need for mental health care but did not seek care represent a treatment gap. Our results suggest the importance of reducing the wide treatment gap that exists between need and care.
A greedy regression algorithm with coarse weights offers novel advantages
Authors: Jeffries Clark D. , Ford John R. , Tilson Jeffrey L. , Perkins Diana O. , Bost Darius M. , Filer Dayne L. , Wilhelmsen Kirk C.
Published: March 2022

Regularized regression analysis is a mature analytic approach to identify weighted sums of variables predicting outcomes. We present a novel Coarse Approximation Linear Function (CALF) to frugally select important predictors and build simple but powerful predictive models. CALF is a linear regression strategy applied to normalized data that uses nonzero weights + 1 or − 1. Qualitative (linearly invariant) metrics to be optimized can be (for binary response) Welch (Student) t-test p-value or area under curve (AUC) of receiver operating characteristic, or (for real response) Pearson correlation. Predictor weighting is critically important when developing risk prediction models. While counterintuitive, it is a fact that qualitative metrics can favor CALF with ± 1 weights over algorithms producing real number weights. Moreover, while regression methods may be expected to change most or all weight values upon even small changes in input data (e.g., discarding a single subject of hundreds) CALF weights generally do not so change. Similarly, some regression methods applied to collinear or nearly collinear variables yield unpredictable magnitude or the direction (in p-space) of the weights as a vector. In contrast, with CALF if some predictors are linearly dependent or nearly so, CALF simply chooses at most one (the most informative, if any) and ignores the others, thus avoiding the inclusion of two or more collinear variables in the model.
Observations on the stress related variations of soil radon concentration in the Gulf of Corinth, Greece
Authors: Karastathis Vassilios K. , Eleftheriou George , Kafatos Menas , Tsinganos Kanaris , Tselentis G-Akis , Mouzakiotis Evangelos , Ouzounov Dimitar
Published: March 2022

Our observations indicate a characteristic pattern in the long-term variation of soil radon concentrations, which seems to be consistent with the expected variation of regional stress in relation to seismicity. However, it seems that the major changes in radon level begin before the rock rapture, i.e. before the earthquake occurs. These conclusions have emerged after long-term observations with continuous and thorough real-time gamma-radiation monitoring in the seismically active area of the Gulf of Corinth, Greece. The recordings acquired close to a hot spring were of very high quality, implying that the deep hydraulic flow can possibly play a key role in the pre-earthquake variation of radon level. We were able to observe outstanding examples of radon level variations before significant seismic events in the Gulf of Corinth that cannot be attributed to other external factors such as atmospheric phenomena.
Exploring carbohydrate binding module fusions and Fab fragments in a cellulose-based lateral flow immunoassay for detection of cystatin C
Authors: Natarajan Satheesh , Joseph Jayaraj , França Prazeres Duarte Miguel
Published: March 2022

This paper presents a lateral flow assay (LFA) for the quantitative, fluorescence-based detection of the kidney biomarker cystatin C that features conjugates of capture antibodies and fusions of carbohydrate binding modules (CBM) with ZZ domains anchored on cellulose deposited over nitrocellulose (NC). The ZZ-CBM3 fusion provides a biomolecular interface between the cellulose layer and the Fc portion of the capture antibodies. By resorting to detection Fab fragments that lack the Fc portion we overcome the observed interference of full-length detection antibodies with the ZZ-CBM3 fusion at the test lines. Using the new LFA architecture, a linear concentration–response relationship was observed in the 0–10 ng/mL cystatin C concentration range, which is compatible with the clinically normal (5–120 ng/mL) and abnormal (> 250 ng/mL) levels of cystatin C, as long as proper dilutions are made. An inter assay CoV of 0.72% was obtained. Finally, mock urine samples characteristic of normal (100 ng/mL) and kidney tubular disease (4000 ng/mL) patients were successfully analyzed. Overall, we demonstrate an innovative LFA architecture that combines NC strips with layered cellulose, ZZ-CBM3 fusions and fluorescently labeled Fab fragments.
Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction
Authors: Ali Mumtaz , Deo Ravinesh C. , Xiang Yong , Prasad Ramendra , Li Jianxin , Farooque Aitazaz , Yaseen Zaher Mundher
Published: March 2022

Inadequate agricultural planning compounded by inaccurate predictions results in an inflated local market rate and prompts higher importation of wheat. To tackle this problem, this research has designed two-phase universal machine learning (ML) model to predict wheat yield (Wpred), utilizing 27 agricultural counties’ data within the Agro-ecological zone. The universal model, online sequential extreme learning machines coupled with ant colony optimization (ACO-OSELM) is developed, by incorporating the significant annual yield data lagged at (t − 1) as the model’s predictor to generate future yield at 6 test stations. In the first phase, ACO is adopted to search for suitable, statistically relevant data stations for model training, and the corresponding test station by virtue of a feature selection strategy. An annual wheat yield time-series input dataset is constructed utilizing data from each selected training station (1981–2013) and applied against 6 test stations (with each case modelled with 26 station data as the input) to evaluate the hybrid ACO-OSELM model. The partial autocorrelation function is implemented to deduce statistically significant lagged data, and OSELM is applied to generate Wpred. The two-phase hybrid ACO-OSELM model is tested within the 6 agricultural districts (represented as stations) of Punjab province, Pakistan and the results are benchmarked with extreme learning machine (ELM) and random forest (RF) integrated with ACO (i.e., hybrid ACO-ELM and hybrid ACO-RF models, respectively). The performance of the ACO-OSELM model was proven to be good in comparison to ACO-ELM and ACO-RF models. The hybrid ACO-OSELM model revealed its potential to be implemented as a decision-making system for crop yield prediction in areas where a significant association with the historical agricultural crop is well-established.
Half-integer anomalous currents in 2D materials from a QFT viewpoint
Authors: Dudal David , Matusalem Filipe , Mizher Ana Júlia , Rocha Alexandre Reily , Villavicencio Cristian
Published: March 2022

Charge carriers in Dirac/Weyl semi-metals exhibit a relativistic-like behavior. In this work we propose a novel type of intrinsic half-integer Quantum Hall effect in 2D materials, thereby also offering a topological protection mechanism for the current. Its existence is rooted in the 2D parity anomaly, without any need for a perpendicular magnetic field. We conjecture that it may occur in disturbed honeycomb lattices where both spin degeneracy and time reversal symmetry are broken. These configurations harbor two distinct gap-opening mechanisms that, when occurring simultaneously, drive slightly different gaps in each valley, causing a net anomalous conductivity when the chemical potential is tuned to be between the distinct gaps. Some examples of promising material setups that fulfill the prerequisites of our proposal are also listed to motivate looking for the effect at the numerical and experimental level.
Prognostic significance of AP-2α/γ targets as cancer therapeutics
Authors: Kołat Damian , Kałuzińska Żaneta , Bednarek Andrzej K. , Płuciennik Elżbieta
Published: March 2022

Identifying genes with prognostic importance could improve cancer treatment. An increasing number of reports suggest the existence of successful strategies based on seemingly “untargetable” transcription factors. In addition to embryogenesis, AP-2 transcription factors are known to play crucial roles in cancer development. Members of this family can be used as prognostic factors in oncological patients, and AP-2α/γ transcription factors were previously investigated in our pan-cancer comparative study using their target genes. The present study investigates tumors that were previously found similar with an emphasis on the possible role of AP-2 factors in specific cancer types. The RData workspace was loaded back to R environment and 3D trajectories were built via Monocle3. The genes that met the requirement of specificity were listed using top_markers(), separately for mutual and unique targets. Furthermore, the candidate genes had to meet the following requirements: correlation with AP-2 factor (through Correlation AnalyzeR) and validated prognostic importance (using GEPIA2 and subsequently KM-plotter or LOGpc). Eventually, the ROC analysis was applied to confirm their predictive value; co-dependence of expression was visualized via BoxPlotR. Some similar tumors were differentiated by AP-2α/γ targets with prognostic value. Requirements were met by only fifteen genes (EMX2, COL7A1, GRIA1, KRT1, KRT14, SLC12A5, SEZ6L, PTPRN, SCG5, DPP6, NTSR1, ARX, COL4A3, PPEF1 and TMEM59L); of these, the last four were excluded based on ROC curves. All the above genes were confronted with the literature, with an emphasis on the possible role played by AP-2 factors in specific cancers. Following ROC analysis, the genes were verified using immunohistochemistry data and progression-related signatures. Staining differences were observed, as well as co-dependence on the expression of e.g. CTNNB1, ERBB2, KRAS, SMAD4, EGFR or MKI67. In conclusion, prognostic value of targets suggested AP-2α/γ as candidates for novel cancer treatment. It was also revealed that AP-2 targets are related to tumor progression and that some mutual target genes could be inversely regulated.
Stent-based delivery of AAV2 vectors encoding oxidation-resistant apoA1
Authors: Hooshdaran Bahman , Pressly Benjamin B. , Alferiev Ivan S. , Smith Jonathan D. , Zoltick Philip W. , Tschabrunn Cory M. , Wilensky Robert L. , Gorman Robert C. , Levy Robert J. , Fishbein Ilia
Published: March 2022

In-stent restenosis (ISR) complicates revascularization in the coronary and peripheral arteries. Apolipoprotein A1 (apoA1), the principal protein component of HDL possesses inherent anti-atherosclerotic and anti-restenotic properties. These beneficial traits are lost when wild type apoA1(WT) is subjected to oxidative modifications. We investigated whether local delivery of adeno-associated viral (AAV) vectors expressing oxidation-resistant apoA1(4WF) preserves apoA1 functionality. The efflux of 3H-cholesterol from macrophages to the media conditioned by endogenously produced apoA1(4WF) was 2.1-fold higher than for apoA1(WT) conditioned media in the presence of hypochlorous acid emulating conditions of oxidative stress. The proliferation of apoA1(WT)- and apoA1(4FW)-transduced rat aortic smooth muscle cells (SMC) was inhibited by 66% ± 10% and 65% ± 11%, respectively, in comparison with non-transduced SMC (p < 0.001). Conversely, the proliferation of apoA1(4FW)-transduced, but not apoA1(WT)-transduced rat blood outgrowth endothelial cells (BOEC) was increased 41% ± 5% (p < 0.001). Both apoA1 transduction conditions similarly inhibited basal and TNFα-induced reactive oxygen species in rat aortic endothelial cells (RAEC) and resulted in the reduced rat monocyte attachment to the TNFα-activated endothelium. AAV2-eGFP vectors immobilized reversibly on stainless steel mesh surfaces through the protein G/anti-AAV2 antibody coupling, efficiently transduced cells in culture modeling stent-based delivery. In vivo studies in normal pigs, deploying AAV2 gene delivery stents (GDS) preloaded with AAV2-eGFP in the coronary arteries demonstrated transduction of the stented arteries. However, implantation of GDS formulated with AAV2-apoA1(4WF) failed to prevent in-stent restenosis in the atherosclerotic vasculature of hypercholesterolemic diabetic pigs. It is concluded that stent delivery of AAV2-4WF while feasible, is not effective for mitigation of restenosis in the presence of severe atherosclerotic disease.