bluuebunny/crossref_metadata_2025 huggingface dataset:
The role of platelet parameters for the diagnosis of preeclampsia among pregnant women attending at the University of Gondar Comprehensive Specialized Hospital antenatal care unit, Gondar, Ethiopia
Authors: Walle Muluken , Asrie Fikir , Gelaw Yemataw , Getaneh Zegeye
Published: February 2022

Background

Preeclampsia (PE) is a pregnancy‐related illness characterized by high blood pressure (BP) and proteinuria after the 20th gestational week (GW). Platelet (PLT) parameter changes are the common hematological abnormalities observed in PE patients. The main aim of this study was to assess the role of PLT parameters for PE diagnosis among pregnant women.

Methods

A comparative cross‐sectional study was conducted at the University of Gondar Specialized Hospital. A total of 126 pregnant women (63 normotensive [NT] and 63 PE) were recruited using a convenient sampling method. Three milliliter blood was collected from each participant, and PLT parameters were determined using Sysmex XS‐500i analyzer. An independent t‐test supplemented with receiver‐operating characteristics (ROC) were used for comparisons and diagnostic value of PLT parameters between the study groups.

Results

Platelet count (PC) was significantly lower in the PE group compared to that in the NT group, whereas mean platelet volume (MPV), platelet large cell ratio (P‐LCR), and platelet distribution width (PDW) were significantly higher in PE. MPV had the largest area under the curve (AUC) [0.91: 95% CI; 0.85–0.96] followed by PC [0.79: 95% CI; 0.72–0.87]. MPV can differentiate PE patients from NT pregnant women at cut‐off value ≥12.10 fl (84.1% sensitivity and 87.3% specificity) while PC can indicate PE at a cut‐off value ≤176.5 × 109/L (65.1% sensitivity and 87.3% specificity).

Conclusion

A decreased PC and an increased MPV, P‐LCR, and PDW can be used as a simple, cost‐effective, quick, and reliable method of PE screening. Of them, MPV is the best indicator of PE.
The phosphoinositide-3-kinase (PI3K)-delta inhibitor seletalisib impairs monocyte-derived dendritic cells maturation, APC function, and promotes their migration to CCR7 and CXCR4 ligands
Authors: Scopelliti Fernanda , Mercurio Laura , Cattani Caterina , Dimartino Valentina , Albanesi Cristina , Costanzo Gianfranco , Mirisola Concetta , Madonna Stefania , Cavani Andrea
Published: February 2022

PI3K pathway plays a crucial role in dendritic cells (DCs) functions, as it regulates different cellular processes, such as maturation and cytokines production. However, the specific role of PI3K p110δ isoform in human DCs has not been thoroughly addressed. In this study, we analyze the effects of seletalisib, a potent and specific inhibitor of PI3K p110δ, on phenotype and antigen-presenting functions of monocyte-derived DCs undergone maturation via LPS. Seletalisib treatment reduced membrane HLA-DR as well as CD83 and CD40 costimulatory molecules, whereas CD80 and CD86 expression was only partially affected. Additionally, DCs cultures showed reduced TNF-α, IL-10, and IL-12 and increased IL-23 secretion levels. This resulted in a reduced capacity of DCs to prime allogeneic T cells, with a strong decrease of Th1 differentiation. On the other hand, PI3K p110δ inhibitor seletalisib increased CXCR4 and CCR7 expression and augmented the DCs migration toward CCL19 and CXCL12 ligands. At molecular level, inhibition of PI3K p110δ isoform by seletalisib significantly down-regulated the phosphorylation of AKT and other downstream signaling molecules, such as ribosomal protein S6, 4E-BP1, and NF-κB p65. In contrast, seletalisib did not affect p38 MAP kinase phosphorylation or TLR-associated adapter molecule TIRAP in DCs. Our results indicate that PI3K p110δ can serve as an important regulatory signal for DCs, and selective inhibition of PI3K p110δ isoform by seletalisib could be used for the prevention of exaggerated and harmful immune responses occurring in pathologic conditions, such as autoimmune disorders.
Synthesis of a dual carbon‐14‐labeled calcitonin gene‐related peptide receptor antagonist for use in a human absorption–distribution–metabolism–elimination study
Authors: Turley Wesley A. , Easter John A. , Burrell Richard C. , Bonacorsi Samuel J.
Published: February 2022

Oral calcitonin gene‐related peptide (CGRP) receptor antagonists have been shown to be effective in the acute and preventive treatment of migraine. CGRP receptor antagonists offer safety advantages over triptans because they are not active vasoconstrictors, which reduces cardiovascular risks. Bristol Myers Squibb discovered a high affinity CGRP receptor antagonist BMS‐927711 for the treatment of migraine now FDA approved as Nurtec® ODT (rimegepant). Dual‐labeled [14C]‐BMS‐927711 was prepared and used in a human absorption–distribution–metabolism–elimination (ADME) study. A dual‐labeled analog of BMS‐927711 was required to fully track the compound's metabolic transformation. The carbon‐14‐labeled synthesis of both right side and left side portions of [14C]‐BMS‐927711 is described.
Optimized multi‐axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole‐brain high‐isotropic‐resolution quantitative imaging
Authors: Cao Xiaozhi , Liao Congyu , Iyer Siddharth Srinivasan , Wang Zhixing , Zhou Zihan , Dai Erpeng , Liberman Gilad , Dong Zijing , Gong Ting , He Hongjian , Zhong Jianhui , Bilgic Berkin , Setsompop Kawin
Published: February 2022

Purpose

To improve image quality and accelerate the acquisition of 3D MR fingerprinting (MRF).

Methods

Building on the multi‐axis spiral‐projection MRF technique, a subspace reconstruction with locally low‐rank constraint and a modified spiral‐projection spatiotemporal encoding scheme called tiny golden‐angle shuffling were implemented for rapid whole‐brain high‐resolution quantitative mapping. Reconstruction parameters such as the locally low‐rank regularization parameter and the subspace rank were tuned using retrospective in vivo data and simulated examinations. B0 inhomogeneity correction using multifrequency interpolation was incorporated into the subspace reconstruction to further improve the image quality by mitigating blurring caused by off‐resonance effect.

Results

The proposed MRF acquisition and reconstruction framework yields high‐quality 1‐mm isotropic whole‐brain quantitative maps in 2 min at better quality compared with 6‐min acquisitions of prior approaches. The proposed method was validated to not induce bias in T1 and T2 mapping. High‐quality whole‐brain MRF data were also obtained at 0.66‐mm isotropic resolution in 4 min using the proposed technique, where the increased resolution was shown to improve visualization of subtle brain structures.

Conclusions

The proposed tiny golden‐angle shuffling, MRF with optimized spiral‐projection trajectory and subspace reconstruction enables high‐resolution quantitative mapping in ultrafast acquisition time.
Sampling Methods and Survey Designs for Larval Lampreys
Authors: Clemens Benjamin J. , Harris Julianne E. , Starcevich Steven J. , Evans Thomas M. , Skalicky Joseph J. , Neave Fraser , Lampman Ralph T.
Published: February 2022

Knowledge of the biology, distribution, and abundance of lampreys (Petromyzontiformes) is critical to inform conservation actions for native species and to inform control measures for the invasive Sea Lamprey Petromyzon marinus of the Laurentian Great Lakes. Lampreys have complex life cycles that include a freshwater larval stage in which they burrow into substrates consisting of fine sediment and organic matter. The larval stage is frequently targeted in research and monitoring; given this interest, a review of survey designs and methods is needed. Our review identified 12 different sampling methods for larval lampreys and focused on one common method—backpack electrofishing in wadeable habitats. Our review also identified eight research and monitoring questions that have been addressed for larval lampreys in field studies, including distribution, species identification, life stage occurrence, abundance, length frequency, habitat use, residence and movement phenology, and species status. Each question provides unique information and poses distinct challenges to data acquisition and interpretation. The objectives guide decisions about study design and scope of inference. The scope of inference is determined by the size, spatial distribution, selection method, and number of sampling units within and across habitats, which determine the spatial and temporal scales under which results can be interpreted. The sampling unit size can span orders of magnitude from microhabitats to river drainages, ultimately informing management decisions at several spatial scales. The intended scope of inference and the interaction between biological questions and the fiscal and logistical capabilities of the study are integral considerations when designing an effective larval lamprey survey.
Room‐Temperature Processed Lateral Trench‐Metal–Insulator–Semiconductor Schottky Barrier Diodes with Amorphous Gallium Oxide (a‐Ga2O3) Thin Films on Single‐Crystal Silicon <100>
Authors: Ebrahimi-Darkhaneh Hadi , Shamsi Zeshaan , Banda Martin G. R. , Quevedo-Lopez Manuel , Colombo Luigi , Banerjee Sanjay K.
Published: February 2022

This article proposes a novel design approach for the fabrication of lateral Schottky barrier diodes (SBD) using a wide bandgap oxide semiconductor on silicon. Structural and electrical properties of the fabricated device are reported and compared with published data. The metal–insulator–semiconductor (MIS) Schottky barrier is realized between the room‐temperature sputtered Al/a‐Ga2O3 on single‐crystal <100> boron‐doped silicon substrate (p‐type). The device fabrication process is implemented entirely at room temperature. The proposed trench diode yields an ideality factor of 1.65 and a rectification ratio of ≈1 × 106 at ±5.0 V. The extracted specific ON resistance is 78 mΩ cm2, and the breakdown voltage is not observed for 180 V for a 200‐nm‐thin layer of a‐Ga2O3. Due to such low‐temperature process, simple fabrication steps, and notably high Baliga's figure‐of‐merit (BFOM), the proposed diode is, therefore, promising for power electronics applications.
International external validation of a stratification tool to identify branch‐duct intraductal papillary mucinous neoplasms at lowest risk of progression
Authors: Overbeek Kasper A. , van Leeuwen Nikki , Tacelli Matteo , Anwar Muhammad S. , Yousaf Muhammad N. , Chhoda Ankit , Arcidiacono Paolo Giorgio , Gonda Tamas A. , Wallace Michael B. , Capurso Gabriele , Farrell James J. , Cahen Djuna L. , Bruno Marco J.
Published: February 2022

Background

Identifying branch‐duct intraductal papillary mucinous neoplasms (BD‐IPMNs) at lowest risk of progression may allow for a reduced intensity of surveillance.

Objective

We aimed to externally validate the previously developed Dutch‐American Risk stratification Tool (DART‐1; https://rtools.mayo.edu/DART/), which identifies cysts at low risk of developing worrisome features (WFs) or high‐risk stigmata (HRS).

Methods

Three prospective cohorts of individuals under surveillance for BD‐IPMNs were combined, independent from the original development cohort. We assessed the performance (discrimination and calibration) of DART‐1, a multivariable Cox‐proportional logistic regression model with five predictors for the development of WFs or HRS.

Results

Of 832 individuals (mean age 77 years, SD 11.5) under surveillance for a median of 40 months (IQR 44), 163 (20%) developed WFs or HRS. DART‐1's discriminative ability (C‐statistic 0.68) was similar to that in the development cohort (0.64–0.72) and showed moderate calibration. DART‐1 adequately estimated the risk for patients in the middle risk quintile, and slightly underestimated it in the lowest quintiles. Their range of predicted versus observed 3‐year risk was 0%–0% versus 0%–3.7% for Q1; 0.3%–0.4% versus 3%–11% for Q2; and 2.6%–3% versus 2.4%–9.8% for Q3. The development of WFs or HRS was associated with pancreatic cancer (p < 0.001). Vice versa, in absence of WFs or HRS, the risk of malignancy was low (0.3%).

Conclusions

The performance of DART‐1 to predict the development of WFs or HRS in BD‐IPMN was validated in an external international cohort, with a discriminative ability equal as in the development cohort. Risk estimations were most accurate for patients with BD‐IPMNs in the middle risk quintile and slightly underestimated in the lowest quintiles.
A device to simulate contaminant transfer and surface and subsurface flow through intact soil monoliths
Authors: Hachgenei Nico , Nord Guillaume , Spadini Lorenzo , Mora Henri , Courvoisier François , Sutra Jean‐François , Vandervaere Jean‐Pierre , Legoût Cédric , Morel Marie‐Christine , Martins Jean , Lespine Anne , Duwig Celine
Published: February 2022

Many contaminants of agricultural origin are released into rural environments, particularly at the soil surface. Their fate has been extensively investigated in repacked soils, but only few studies have addressed their transport in structurally preserved natural soils. Much remains unknown about their fate and transfer within and between environmental compartments, while the susceptibility of these compartments to the contaminants adverse effects can vary considerably. The lack of studies regarding surface and subsurface transfer of contaminants through intact soil compared with studies on repacked soil led us to propose a device and protocol for sampling intact soil monoliths (60 × 30 × 22 cm3, length, width, depth [LWD]) without heavy machinery. This is achieved by a modular design with removable top and bottom lid and a protocol of cutting the soil and replacing the affected bottom soil with a drainage layer of glass beads. The device allows the application of artificial rainfall events with simultaneous highly resolved quantification of infiltration excess overland flow and drainage discharge. It is designed to facilitate the collection of samples for physical, biological, and chemical analyses that fulfill cleanliness standards for organic contaminant analysis at trace levels using only poorly reactive stainless steel and glass materials. Testing of the device was performed by measuring the transfer of the antiparasitic drug ivermectin (IVM) through and over a silt‐loam pasture soil. This test case illustrates how the device can be used to gain valuable information on the transfer of trace organic contaminants through topsoils.
Placing abortion in historical, legal, and clinical context in American medical school classrooms
Authors: Wolf Jacqueline H. , Broecker Jane D.
Published: February 2022

Abortion is one of the most commonly performed medical procedures in the United States. In 2018, physicians in the United States performed 189 abortions for every 1000 births. Abortion is also common in other countries; across the globe, tens of millions of women seek abortions annually. In the countries that have legalized abortion, ready access to the procedure, along with access to reliable contraception, have improved women's economic status, their health, their longevity, and their ability to care for their children. Yet, despite its prevalence and benefits, abortion has also been a magnet for political controversy in the United States and elsewhere. In the United States, where the controversy has not ebbed for 50 years, abortion laws in some states have become increasingly restrictive, particularly in the last decade. This commentary describes an innovative way to teach medical students about abortion and argues that teaching abortion to medical students in the United States and throughout the world has become more, rather than less, important. This article also argues that, given the importance of access to safe abortions for women's health and well‐being, medical schools are obligated to provide medical students with the comprehensive medical knowledge that will allow them, after becoming physicians, to accurately advise, and sensitively counsel, women seeking abortions. Medical schools are also obligated to arm medical students with the relevant historical and legal knowledge that will allow them to advocate for the comprehensive reproductive services that all women need—services that include safe, legal abortion.
Evaluating the impact of a social medicine course delivered in a local‐global context: A 10‐year multi‐site analysis
Authors: Voller Vanessa K. , Olirus Owilli Alex , Yang Andrew X. , Finnegan Amy C. , Westerhaus Michael
Published: February 2022

Amidst the COVID‐19 pandemic and social uprisings demanding social and racial equity worldwide, there is an increasing demand for health justice training for health workers. However, there are scant evidence‐based assessments of the impact of such courses. Between 2010 and 2020, SocMed—a 501(c)3 non‐profit social justice organization—offered two distinct courses about health equity, the social determinants of health, and social medicine to health workers through the University of Minnesota in Minneapolis, Minnesota and Saint Mary Hospital Lacor in Gulu, Uganda. This study assesses the immediate impact of the SocMed curriculum on participants measured by a pre‐course and post‐course survey. In Minnesota, paired pre‐course and post‐course survey responses (mean n = 69; SD = 23) spanned years 2016–2019, while Uganda paired pre‐course and post‐course survey responses (mean n = 64; SD = 21) spanned years 2012–2013 and 2017–2019. Findings indicate that the course improved participants’ knowledge in all 24 of the topics in the Minnesota course and 42 of 44 topics in the Uganda course (significant at p < 0.05).
Use of deep learning in the MRI diagnosis of Chiari malformation type I
Authors: Tanaka Kaishin W. , Russo Carlo , Liu Sidong , Stoodley Marcus A. , Di Ieva Antonio
Published: February 2022

Purpose

To train deep learning convolutional neural network (CNN) models for classification of clinically significant Chiari malformation type I (CM1) on MRI to assist clinicians in diagnosis and decision making.

Methods

A retrospective MRI dataset of patients diagnosed with CM1 and healthy individuals with normal brain MRIs from the period January 2010 to May 2020 was used to train ResNet50 and VGG19 CNN models to automatically classify images as CM1 or normal. A total of 101 patients diagnosed with CM1 requiring surgery and 111 patients with normal brain MRIs were included (median age 30 with an interquartile range of 23–43; 81 women with CM1). Isotropic volume transformation, image cropping, skull stripping, and data augmentation were employed to optimize model accuracy. K-fold cross validation was used to calculate sensitivity, specificity, and the area under receiver operating characteristic curve (AUC) for model evaluation.

Results

The VGG19 model with data augmentation achieved a sensitivity of 97.1% and a specificity of 97.4% with an AUC of 0.99. The ResNet50 model achieved a sensitivity of 94.0% and a specificity of 94.4% with an AUC of 0.98.

Conclusions

VGG19 and ResNet50 CNN models can be trained to automatically detect clinically significant CM1 on MRI with a high sensitivity and specificity. These models have the potential to be developed into clinical support tools in diagnosing CM1.
Chronic kidney disease predictors in obese adolescents
Authors: Mackowiak-Lewandowicz Katarzyna , Ostalska-Nowicka Danuta , Zaorska Katarzyna , Kaczmarek Elzbieta , Zachwieja Jacek , Witt Martin , Nowicki Michal
Published: February 2022

Background

Glomerular hyperfiltration, initiating development of obesity-related glomerulopathy, results in an enlargement of the glomeruli and unsealing of the filtration barrier. It can be followed by adaptive focal segmental glomerulosclerosis and chronic kidney disease (CKD). The aim of the study was to determine the expression pattern of lipid metabolism and selected kidney damage markers in obese adolescents and to identify potential factors which can predict CKD.

Methods

The study group consisted of 142 adolescents with a BMI z-score > 2. Sixty-two healthy and normal-weight individuals served as controls. The factors associated with the rate of glomerular filtration in obese adolescents were assessed by linear regression methods using univariate and multivariate analyses. The risk of developing CKD was estimated using the Fisher’s exact test.

Results

The study group was divided into “elevated,” “normal,” and “decreased” glomerular filtration rate (GFR) patients. Increased urine galectin-3 (Gal-3) concentration was diagnosed in all patients. “Decreased GFR” subjects expressed increased urine concentration of neutrophil gelatinase-associated lipocalin (NGAL) and daily megalin excretion. Thirty-nine study participants developed CKD. Increased uric acid (UA) concentration was associated with CKD development both in “normal” and “decreased GFR” patients. Additionally, in “normal” GFR patients, increased concentrations of cholesterol (Ch), triglycerides (TG), and NGAL were associated with CKD.

Conclusions

Increased serum concentrations of Ch, TG, and UA and increased urine concentration of NGAL might predict CKD development in obese adolescents with normal and decreased GFR.

Graphical abstract

A higher resolution version of the Graphical abstract is available as Supplementary information
Optimization algorithms as training approach with hybrid deep learning methods to develop an ultraviolet index forecasting model
Authors: Ahmed A. A. Masrur , Ahmed Mohammad Hafez , Saha Sanjoy Kanti , Ahmed Oli , Sutradhar Ambica
Published: February 2022

The solar ultraviolet index (UVI) is a key public health indicator to mitigate the ultraviolet-exposure related diseases. This study aimed to develop and compare the performances of different hybridised deep learning approaches with a convolutional neural network and long short-term memory referred to as CLSTM to forecast the daily UVI of Perth station, Western Australia. A complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is incorporated coupled with four feature selection algorithms (i.e., genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and differential evolution (DEV)) to understand the diverse combinations of the predictor variables acquired from three distinct datasets (i.e., satellite data, ground-based SILO data, and synoptic mode climate indices). The CEEMDAN-CLSTM model coupled with GA appeared to be an accurate forecasting system in capturing the UVI. Compared to the counterpart benchmark models, the results demonstrated the excellent forecasting capability (i.e., low error and high efficiency) of the recommended hybrid CEEMDAN-CLSTM model in apprehending the complex and non-linear relationships between predictor variables and the daily UVI. The study inference can considerably enhance real-time exposure advice for the public and help mitigate the potential for solar UV-exposure-related diseases such as melanoma.
Simulating chalcogen bonding using molecular mechanics: a pseudoatom approach to model ebselen
Authors: Fellowes Thomas , White Jonathan M.
Published: February 2022

The organoselenium compound ebselen has recently been investigated as a treatment for COVID-19; however, efforts to model ebselen in silico have been hampered by the lack of an efficient and accurate method to assess its binding to biological macromolecules. We present here a Generalized Amber Force Field modification which incorporates classical parameters for the selenium atom in ebselen, as well as a positively charged pseudoatom to simulate the σ-hole, a quantum mechanical phenomenon that dominates the chemistry of ebselen. Our approach is justified using an energy decomposition analysis of a number of density functional theory–optimized structures, which shows that the σ-hole interaction is primarily electrostatic in origin. Finally, our model is verified by conducting molecular dynamics simulations on a number of simple complexes, as well as the clinically relevant enzyme SOD1 (superoxide dismutase), which is known to bind to ebselen.
Treatment with Polyethylene Glycol–Conjugated Fungal d-Amino Acid Oxidase Reduces Lung Inflammation in a Mouse Model of Chronic Granulomatous Disease
Authors: Nunoi Hiroyuki , Xie Peiyu , Nakamura Hideaki , Aratani Yasuaki , Fang Jun , Nishimura Toyoki , Kataoka Hiroaki , Maeda Hiroshi , Matsukura Makoto
Published: February 2022

Abstract

Chronic granulomatous disease (CGD) is a primary immunodeficiency wherein phagocytes are unable to produce reactive oxygen species (ROS) owing to a defect in the nicotinamide adenine dinucleotide phosphate oxidase (NADPH) complex. Patients with CGD experience bacterial and fungal infections and excessive inflammatory disorders. Bone marrow transplantation and gene therapy are theoretically curative; however, residual pathogenic components cause inflammation and/or organic damage in patients. Moreover, antibiotic treatments may not help in preventing excessive inflammation due to the residual presence of fungal cell wall β-glucan. Thus, better treatment strategies against CGD are urgently required. Polyethylene glycol–conjugated recombinant porcine d-amino acid oxidase (PEG-pDAO) supplies ROS to defective NADPH oxidase in neutrophils of patients with CGD, following which the neutrophils regain bactericidal activity in vitro. In this study, we employed an in vivo nonviable Candida albicans (nCA)–induced lung inflammation model of gp91-phox knockout CGD mice and supplied novel PEG conjugates of Fusarium spp. d-amino acid oxidase (PEG-fDAO), as it exhibits higher enzyme activity than PEG-pDAO. The body weight, lung weight, and lung pathology were evaluated using three experimental strategies with the in vivo lung inflammation model to test the efficacy of the ROS-generating enzyme replacement therapy with PEG-fDAO. The lung weight and pathological findings suggest the condition was ameliorated by administration PEG-fDAO, followed by intraperitoneal injection of d-phenylalanine or d-proline. Although a more precise protocol is essential, these data reveal the targeted delivery of PEG-fDAO to the nCA-induced inflammation site and show that PEG-fDAO can be used to treat inflammation in CGD in vivo.
Benchmarking ensemble docking methods in D3R Grand Challenge 4
Authors: Gan Jessie Low , Kumar Dhruv , Chen Cynthia , Taylor Bryn C. , Jagger Benjamin R. , Amaro Rommie E. , Lee Christopher T.
Published: February 2022

The discovery of new drugs is a time consuming and expensive process. Methods such as virtual screening, which can filter out ineffective compounds from drug libraries prior to expensive experimental study, have become popular research topics. As the computational drug discovery community has grown, in order to benchmark the various advances in methodology, organizations such as the Drug Design Data Resource have begun hosting blinded grand challenges seeking to identify the best methods for ligand pose-prediction, ligand affinity ranking, and free energy calculations. Such open challenges offer a unique opportunity for researchers to partner with junior students (e.g., high school and undergraduate) to validate basic yet fundamental hypotheses considered to be uninteresting to domain experts. Here, we, a group of high school-aged students and their mentors, present the results of our participation in Grand Challenge 4 where we predicted ligand affinity rankings for the Cathepsin S protease, an important protein target for autoimmune diseases. To investigate the effect of incorporating receptor dynamics on ligand affinity rankings, we employed the Relaxed Complex Scheme, a molecular docking method paired with molecular dynamics-generated receptor conformations. We found that Cathepsin S is a difficult target for molecular docking and we explore some advanced methods such as distance-restrained docking to try to improve the correlation with experiments. This project has exemplified the capabilities of high school students when supported with a rigorous curriculum, and demonstrates the value of community-driven competitions for beginners in computational drug discovery.
A Review on Metal Ion Sensors Derived from Chalcone Precursor
Authors: Mahesha Priyanka , Shetty Nitinkumar S. , Kulkarni Suresh D.
Published: February 2022

Disclosure of new molecular probes as chromogenic and fluorogenic cation sensors is scientifically exigent work. Recently chalcone derivatives gained more attention because of their structural variability. A suitable donor and acceptor groups separated by delocalized π-orbitals display excellent chromogenic and fluorogenic properties because of intramolecular charge transfer (ICT). These designed molecular frameworks provide the coordination sites to the incoming metal ions results in small changes in the optical properties. In a typical sensing behavior, coordination leads to a large conjugation plane with the probe resulted in hypo/hyperchromic shifts or red/blue shifts. In this review, we tried to converge the reported chalcone-derived sensors and explored the design, synthesis, metal ion sensing mechanism, and practical application of the probes. We expect that this review gives a basic outline for researchers to explore the field of chalcone-based sensors further.
Long-term dynamic of nestedness in bird assemblages inhabiting fragmented landscapes
Authors: Dondina Olivia , Orioli Valerio , Tirozzi Pietro , Bani Luciano
Published: February 2022

Context

Nestedness is a common pattern of species assemblages in fragmented landscapes. The spatial pattern and ecological drivers of nested communities have been widely explored, but few studies investigated their long-term variability.

Objectives

To investigate the variability of nestedness and species-specific fragment occupancy of forest birds in a fragmented landscape affected by environmental changes over 16 years.

Methods

Data were obtained from the Monitoring Program of Breeding Birds in Lombardy (northern Italy). For two study periods (1997–2001, 2013–2017), we tested for overall nestedness and for sites and species nestedness independently using the NODF metric. We tested for nestedness drivers (variable selection on multiple linear regression models) and evaluated the effect of species ecological traits on fragment occupancy changes (variable selection on multiple linear regression model).

Results

The community showed a significant nestedness driven by both selective extinction and selective colonization in both study periods. Sites nestedness was significant in the second study period only. Over 16 years the effect of distance from source areas was completely lost and only local isolation conditions drove selective colonization in the second study period. Between the two study periods, we discovered a general occupancy decrease of interior species and a significant occupancy increase of generalist species characterized by large size and large minimum area requirement.

Conclusions

Nestedness drivers of the investigated community significantly varied over time probably because of both environmental and demographic changes. Long-term studies are crucial to explore spatial pattern changes and to address management strategies for species conservation in fragmented landscapes.
Phenotypic and functional alterations of peritoneal macrophages in lupus-prone mice
Authors: Tejon Gabriela , Valdivieso Nicolás , Flores-Santibañez Felipe , Barra-Valdebenito Verónica , Martínez Víctor , Rosemblatt Mario , Sauma Daniela , Bono María Rosa
Published: February 2022

Background

Several studies have demonstrated the contribution of innate immune cells, including macrophages, in promoting systemic lupus erythematosus (SLE). Macrophages, one of the most abundant cell populations in the peritoneal cavity, are considered multifunctional cells with phenotypic plasticity. However, the functional properties of peritoneal macrophages in steady-state and during the progression of SLE remain poorly defined.

Methods and results

Using the [NZB × NZW]F1 (BWF1) murine model of SLE, we analyzed the phenotype and function of peritoneal macrophages during the disease’s onset. We found a higher frequency of peritoneal macrophages and B1a cells in BWF1-diseased mice than age-matched controls. Additionally, macrophages from diseased animals expressed lower levels of CD206, MHC-II, and Sirpα. RNAseq analysis identified 286 differentially expressed genes in peritoneal macrophages from diseased-BWF1 mice compared to control mice. Functional experiments demonstrate that peritoneal macrophages from diseased-BWF1 mice secrete higher levels of pro-inflammatory cytokines when activated with TLR7 and TLR9 agonists, and they were less efficient in suppressing the activation and proliferation of peritoneal LPS-activated B cells. These data demonstrate that peritoneal macrophages from BWF1-diseased mice present phenotypic and functional alterations shifting to a more pro-inflammatory state.

Conclusions

The increase of macrophages with an altered phenotype and function together with the accumulation of B1a cells in the peritoneal cavity of diseased-BWF1 mice may promote the progression of the disease. Advancing awareness of the role and phenotype of peritoneal macrophages in SLE may contribute to a better understanding of these types of diseases and the development of novel therapies.
Joint Income-Wealth Inequality: Evidence from Lucerne Tax Data
Authors: Gallusser David , Krapf Matthias
Published: February 2022

Using tax data from the Swiss canton of Lucerne, we study how measures of economic inequality change if they account for income and wealth rather than income alone. Joint income-wealth, the sum of labor income and annuitized wealth, serves as a measure of combined inequality of income and wealth. Inequality measured using joint income-wealth is higher than measured using income alone. We refine existing annuitization techniques by introducing heterogeneous returns. The joint distribution of labor income and annuitized wealth displays strong tail dependence at the top and a negative association for negative annuitized wealth. A decomposition shows that the underlying marginal distributions of labor income and annuitized wealth account for most of joint income-wealth inequality, whereas their association matters only in the tails.
Exploiting probability density function of deep convolutional autoencoders’ latent space for reliable COVID-19 detection on CT scans
Authors: Sarv Ahrabi Sima , Piazzo Lorenzo , Momenzadeh Alireza , Scarpiniti Michele , Baccarelli Enzo
Published: February 2022

We present a probabilistic method for classifying chest computed tomography (CT) scans into COVID-19 and non-COVID-19. To this end, we design and train, in an unsupervised manner, a deep convolutional autoencoder (DCAE) on a selected training data set, which is composed only of COVID-19 CT scans. Once the model is trained, the encoder can generate the compact hidden representation (the hidden feature vectors) of the training data set. Afterwards, we exploit the obtained hidden representation to build up the target probability density function (PDF) of the training data set by means of kernel density estimation (KDE). Subsequently, in the test phase, we feed a test CT into the trained encoder to produce the corresponding hidden feature vector, and then, we utilise the target PDF to compute the corresponding PDF value of the test image. Finally, this obtained value is compared to a threshold to assign the COVID-19 label or non-COVID-19 to the test image. We numerically check our approach’s performance (i.e. test accuracy and training times) by comparing it with those of some state-of-the-art methods.
Possibility, relevant similarity, and structural knowledge
Authors: Schoonen Tom
Published: February 2022

Recently, interest has surged in similarity-based epistemologies of possibility. However, it has been pointed out that the notion of ‘relevant similarity’ is not properly developed in this literature. In this paper, I look at the research done in the field of analogical reasoning, where we find that one of the most promising ways of capturing relevance in similarity reasoning is by relying on the predictive analogy similarity relation. This takes relevant similarity to be based on shared properties that have structural relations to the property of interest. I argue that if we base our epistemology of possibility on similarity reasoning on the predictive analogy similarity relation, we require prior knowledge of the specifics of these structural relations. I discuss a number of possible responses to this on behalf of the similarity theorists given their methodological approach to the epistemology of modality more generally. They could either opt for making explicit the metaphysics underlying these structural relations, in which case they need to spell out how we can come to know these relations. Or they could opt for developing a theory that explains why we do not need to have explicit knowledge of these structural relations; for example by suggesting that we make use of epistemic shortcuts.
Multi-phase Fine-Tuning: A New Fine-Tuning Approach for Sign Language Recognition
Authors: Sarhan Noha , Lauri Mikko , Frintrop Simone
Published: February 2022

In this paper, we propose multi-phase fine-tuning for tuning deep networks from typical object recognition to sign language recognition (SLR). It extends the successful idea of transfer learning by fine-tuning the network’s weights over several phases. Starting from the top of the network, layers are trained in phases by successively unfreezing layers for training. We apply this novel training approach to SLR, since in this application, training data is scarce and differs considerably from the datasets which are usually used for pre-training. Our experiments show that multi-phase fine-tuning can reach significantly better accuracy in fewer training epochs compared to previous fine-tuning techniques
Evidence of the persistence and consistency of social signatures
Authors: Li Yue , Bond Robert M.
Published: February 2022

Human social networks are composed of multiple dynamic and overlapping communication networks, in which membership changes over time. However, less well understood are whether and how our communication patterns are similar or different over time and across various modes of communication. Here, we use data on the frequency of phone calls, text messages, and in-person interactions to examine the social signatures of more than 700 students in a university setting. Our analysis shows that although there is substantial turnover in participants’ networks, participants’ social signatures are persistent across time and consistent across communication modes. Further, we find that communication networks that are mediated via phone calls or text messages are more stable than are in-person networks. Our results show that, likely due to limitations in cognitive and emotional resources, people maintain networks of relatively stable size and structure their communication within those networks in predictable patterns. Our findings may help with formalizing social network theories, explaining individual-level attitudes and behaviors and aggregate-level social phenomena, and making predictions and detecting abnormalities in applied fields.
Camera traps reveal overlap and seasonal variation in the diel activity of arboreal and semi-arboreal mammals
Authors: Gracanin Ana , Mikac Katarina M.
Published: February 2022

Our study aimed to investigate seasonal variation in the activity of arboreal and semi-arboreal mammals and investigate their overlap in temporal activity, as well temporal shifts in activity because of behavioural interference. In our camera trapping study in a fragmented landscape in south-eastern Australia, a total of ten arboreal and semi-arboreal species were found, with 35,671 independent observations recorded over 6517 camera trap nights. All species were found to be nocturnal; however, a notable number of daytime observations were made for several species (i.e. brown antechinus,Antechinus stuartii; sugar glider,Petaurus breviceps; bush rat,Rattus fuscipes; brown rat,Rattus norvegicus). Seasonal variations in diel activity were observed through an increase in crepuscular activity in spring and summer for antechinus, sugar gliders, brown rats,brushtail possums,Trichosurus vulpeculaand ringtail possums,Pseudocheirus peregrinus.Diel activity overlap between species was high, that is 26/28 species comparisons had overlap coefficients (Δ) > 0.75. The species pair with the least amount of overlap was between southern bobucks,Trichosurus cunninghamiand brown antechinus (Δ4 = 0.66). The species pair with the most overlap was between the native sugar glider and introduced brown rat (Δ4 = 0.93). When comparing the activity of sugar gliders in sites with low and high abundance of brown rats, sugar gliders appear to shift their activity relative to the brown rats. Similarly, behavioural interference was also observed between antechinus and sugar gliders, and when comparing sites of low and high abundance of sugar glider, antechinus had a shift in activity. Our work provides some of the first quantification of temporal patterns for several of the species in this study, and the first for a community of arboreal and semi-arboreal mammals. Our results indicate that some shifts in behaviour are potentially occurring in response to behavioural interference, allowing for coexistence by means of temporal partitioning.
Defining organizational AI governance
Authors: Mäntymäki Matti , Minkkinen Matti , Birkstedt Teemu , Viljanen Mika
Published: February 2022

Artificial intelligence (AI) governance is required to reap the benefits and manage the risks brought by AI systems. This means that ethical principles, such as fairness, need to be translated into practicable AI governance processes. A concise AI governance definition would allow researchers and practitioners to identify the constituent parts of the complex problem of translating AI ethics into practice. However, there have been few efforts to define AI governance thus far. To bridge this gap, this paper defines AI governance at the organizational level. Moreover, we delineate how AI governance enters into a governance landscape with numerous governance areas, such as corporate governance, information technology (IT) governance, and data governance. Therefore, we position AI governance as part of an organization’s governance structure in relation to these existing governance areas. Our definition and positioning of organizational AI governance paves the way for crafting AI governance frameworks and offers a stepping stone on the pathway toward governed AI.
Sovereign Debt and Socio-Economic Rights Beyond Crisis
Authors: Scali Emma Luce
Published: February 2022

This book offers a distinctive critical discussion of the relationship between sovereign debt and socio-economic human rights in the context of the contemporary global neoliberal economic order, going beyond strictly 'post-crisis' approaches and emphasising the structural character and consistent growth of public and private indebtedness. It reflects on the implications of mounting debt for the actual ability of States to realise human rights in a world of escalating indebtedness, inequality and insecurity. It expands existing definitions of neoliberalism by reflecting in particular on neoliberalism's epistemological underpinnings, and provides a comprehensive and systematic analysis of the 2009 Greek debt crisis and the main elements of post-crisis developments in international and EU law, arguing that the 'neoliberalisation of law' has essentially been advanced in the wake of the Eurozone debt crisis.
Some Indigenous Perspectives on Artifact Collecting and Archaeologist–Collector Collaboration
Authors: Kelley Alan D. , Neller Angela J. , Gover Carlton Shield Chief ,   AAP Thematic-Issue Editors
Published: February 2022

This article attempts to bring Indigenous voices into the ongoing conversation about collecting practices and the archaeological record. The issue editors solicited responses to open-ended questions about those subjects from members of their own and issue contributors' networks of Indigenous collaborators and contacts. Alan D. Kelley (Deputy Tribal Historic Preservation Officer, Iowa Tribe of Kansas and Nebraska), Angela J. Neller (Curator, Wanapum Heritage Center, Washington), and Carlton Shield Chief Gover (PhD student in archaeology at the University of Colorado and member of the Skiri Band of the Pawnee Nation of Oklahoma) offered the answers reported here. We do not pretend to reflect the innumerable and highly varied Indigenous perspectives on the collection of their ancestors' material culture, but we do hope to plant the seeds of a more inclusive conversation than has been the norm in archaeology.
Research on lateral dynamics safety margins of carrier-based aircraft arresting
Authors: Zhang Z. , Peng Y. , Liang T. , Wei X. , Wang Y.
Published: February 2022

For the safety problems caused by the limited landing space of the deck during the arresting process of the carrier-based aircraft, a dynamic model of the carrier-based aircraft’s landing and arresting is built. Based on the batch simulation method, the lateral dynamics safety envelope of the aircraft during the arresting was defined, and the dynamic response of the key points in the envelope during the arresting process was investigated. Subsequently, the influence of engine thrust and aircraft quality on the arresting safety envelope was studied based on reasonable safety evaluation indicators, and the safety status envelope of the deck arresting was given. Then, the particular Hamilton-Jacobi partial differential equation is used to obtain the lateral dynamics safety envelope of the carrier-based aircraft in the process of landing and arresting by backward inversion. Results indicate that engine thrust and landing quality have little effect on the yaw angle in the arresting safety boundary during the arresting. Additionally, with the engine thrust and landing quality increase, the maximum safe off-centre distance gradually decreases, and the safety boundary decreases accordingly. During the phase of landing glide, the engine thrust and quality have little effect on the maximum safe eccentric distance. When the engine thrust is increased by 40%, the maximum safe yaw angle is reduced from 0.3°, and the safety boundary is reduced by 4.2%. When the aircraftquality increases by 40%, the maximum safe yaw angle is reduced by 0.4°, and the safety boundary is reduced by 2.8%. The findings of this paper can provide framework for the research on theaircraft-to-carrier dynamic matching characteristics of the carrier-based system, and is of great significance to the research on improving the safety of the carrier-based aircraft landing arresting.
Can machine learning models trained using atmospheric simulation data be applied to observation data?
Authors: Matsuoka Daisuke
Published: February 2022

Atmospheric simulation data present richer information in terms of spatiotemporal resolution, spatial dimension, and the number of physical quantities compared to observational data; however, such simulations do not perfectly correspond to the real atmospheric conditions. Additionally, extensive simulation data aids machine learning-based image classification in atmospheric science. In this study, we applied a machine learning model for tropical cyclone detection, which was trained using both simulation and satellite observation data. Consequently, the classification performance was significantly lower than that obtained with the application of simulation data. Owing to the large gap between the simulation and observation data, the classification model could not be practically trained only on the simulation data. Thus, the representation capability of the simulation data must be analyzed and integrated into the observation data for application in real problems.