bluuebunny/crossref_metadata_2025_split huggingface dataset:
Attracting and developing STEMM talent toward excellence and innovation
Authors: Stoeger Heidrun , Luo Linlin , Ziegler Albert 
Published: February 2024

AbstractThis article provides an overview of science, technology, engineering, mathematics, and medical sciences (STEMM) talent development from first exposure to a STEMM domain to achieving eminence and innovation. To this end, a resource‐oriented model of STEMM talent development is proposed as a framework. It includes a three‐stage phase model based on Bloom (1985), with the main focus on interest development in the first stage, skill acquisition toward expertise and excellence in the second stage, and style formation toward eminence and innovation in the final stage. A literature review shows that from an educational perspective, each phase is mainly characterized by the focus that Bloom postulated. However, it is important that all three stages (i.e., interest development, skill acquisition, and style formation) occur in a stage‐typical manner. To explain how these primary objectives of STEMM development can be supported through STEMM talent education, Ziegler and Stoeger's (2011) educational and learning capital framework is used in the proposed resource‐based model. A literature review shows that consistent provisioning of the resources specified in the model is necessary for individuals to complete a learning pathway to STEMM eminence and innovation.
In situ short‐term responses of Amazonian understory plants to elevated CO2
Authors: Damasceno Amanda Rayane , Garcia Sabrina , Aleixo Izabela Fonseca , Menezes Juliane Cristina Gomes , Pereira Iokanam Sales , De Kauwe Martin G. , Ferrer Vanessa Rodrigues , Fleischer Katrin , Grams Thorsten E. E. , Guedes Alacimar V. , Hartley Iain Paul , Kruijt Bart , Lugli Laynara Figueiredo , Martins Nathielly Pires , Norby Richard J. , Pires‐Santos Julyane Stephanie , Portela Bruno Takeshi Tanaka , Rammig Anja , de Oliveira Leonardo Ramos , Santana Flávia Delgado , Santos Yago Rodrigues , de Souza Crisvaldo Cássio Silva , Ushida Gabriela , Lapola David Montenegro , Quesada Carlos Alberto Nobre , Domingues Tomas Ferreira 
Published: February 2024

AbstractThe response of plants to increasing atmospheric CO2 depends on the ecological context where the plants are found. Several experiments with elevated CO2 (eCO2) have been done worldwide, but the Amazonian forest understory has been neglected. As the central Amazon is limited by light and phosphorus, understanding how understory responds to eCO2 is important for foreseeing how the forest will function in the future. In the understory of a natural forest in the Central Amazon, we installed four open‐top chambers as control replicates and another four under eCO2 (+250 ppm above ambient levels). Under eCO2, we observed increases in carbon assimilation rate (67%), maximum electron transport rate (19%), quantum yield (56%), and water use efficiency (78%). We also detected an increase in leaf area (51%) and stem diameter increment (65%). Central Amazon understory responded positively to eCO2 by increasing their ability to capture and use light and the extra primary productivity was allocated to supporting more leaf and conducting tissues. The increment in leaf area while maintaining transpiration rates suggests that the understory will increase its contribution to evapotranspiration. Therefore, this forest might be less resistant in the future to extreme drought, as no reduction in transpiration rates were detected.
Regulation of metal homoeostasis by two F‐group bZIP transcription factors bZIP48 and bZIP50 in rice
Authors: Qing Tao , Xie Tian‐Ci , Zhu Qiao‐Yun , Lu Hai‐Ping , Liu Jian‐Xiang 
Published: February 2024

AbstractZinc (Zn) deficiency not only impairs plant growth and development but also has negative effects on human health. Rice (Oryza Sativa L.) is a staple food for over half of the global population, yet the regulation of Zn deficiency response in rice remains largely unknown. In this study, we provide evidence that two F‐group bZIP transcription factors, OsbZIP48/50, play a crucial role in Zn deficiency response. Mutations in OsbZIP48/50 result in impaired growth and reduced Zn/Fe/Cu content under Zn deficiency conditions. The N‐terminus of OsbZIP48/OsbZIP50 contains two Zn sensor motifs (ZSMs), deletion or mutation of these ZSMs leads to increased nuclear localization. Both OsbZIP48 and OsbZIP50 exhibit transcriptional activation activity, and the upregulation of 1117 genes involved in metal uptake and other processes by Zn deficiency is diminished in the OsbZIP48/50 double mutant. Both OsbZIP48 and OsbZIP50 bind to the promoter of OsZIP10 and activate the ZDRE cis‐element. Amino acid substitution mutation of the ZSM domain of OsbZIP48 in OsbZIP50 mutant background increases the content of Zn/Fe/Cu in brown rice seeds and leaves. Therefore, this study demonstrates that OsbZIP48/50 play a crucial role in regulating metal homoeostasis and identifies their downstream genes involved in the Zn deficiency response in rice.
Efficient border biosecurity inspection leverages superspreading to reduce biological invasion risk
Authors: Trouvé Raphaël , Robinson Andrew P. 
Published: February 2024

AbstractBiological invasions are a growing threat to biodiversity, food security, and economies. Rising pressure from increased global trade requires improving border inspection efficiency. Here, we depart from the conventional consignment‐by‐consignment approach advocated in current inspection standards. Instead, we suggest a broader perspective: evaluating border inspection regimes based on their ability to reduce propagule pressure across entire pathways. Additionally, we demonstrate that most biosecurity pathways exhibit superspreading behavior, that is, consignments from the same pathway have varying infestation rates and contain rare right‐tail events (also called overdispersion). We show that greater overdispersion leads to more pronounced diminishing returns, with consequences on the optimal allocation of sampling effort. We leverage these two insights to develop a simple and efficient border inspection regime that can significantly reduce propagule pressure compared to current standards. Our analysis revealed that consignment size is a key driver of biosecurity risk and that sampling proportional to the square root of consignment size is near optimal. In testing, our framework reduced propagule pressure by 31 to 38% compared to current standards. We also identified opportunities to further improve inspection efficiency by considering additional pathway characteristics (i.e., overdispersion parameters, zero inflation, relative risk, sampling cost, detectability) and developed solutions for these more complex scenarios. We anticipate our result will mitigate biological invasion risk with significant implications for biodiversity conservation, food security, and economies worldwide.
Alternative policy narratives of the future of climate change: Analyzing Finland's energy and climate strategy and news reports
Authors: Parkkinen Marjukka , Vikström Suvi 
Published: February 2024

AbstractIn this article, we examine the ways in which the futures of climate change and the climate change policy process are constructed as narratives—both explicitly and implicitly—in two different yet interconnected contexts that shape public climate discourse and debate: foresight‐based political decision‐making and journalism. The featured case is the National Energy and Climate Strategy of Finland for 2030. We employ and expand the Narrative Policy Framework to better understand the co‐existent, implicit narratives of the future in the contexts of policy and media. We construct two co‐existing yet contradictory underlying narratives of the future of climate change and climate policy. Our approach reveals that the prevailing master narrative of a desirable future is challenged by a co‐existing counter narrative where policies in the energy and climate strategy prioritize shorter‐term policy interests over climate change. Building on these findings, we argue that, in climate policy communication, communicators convey futures through narratives—both explicitly, as descriptions of what is perceived, hoped, and anticipated to happen, and implicitly, as the sum of the parts included and excluded.
Clinical efficacy of CO2 fractional laser in treating post‐burn hypertrophic scars in children: A meta‐analysis
Authors: Chen Yuan , Wei Wenlong , Li Xiaojian 
Published: February 2024

AbstractObjectiveTo evaluate and explore the efficacy of CO2 fractional laser in treating post‐burn hypertrophic scars in children through Meta‐analysis.MethodsEnglish databases (PubMed, Web of Science and The National Library of Medicine), as well as Chinese databases (China National Knowledge Infrastructure and Wanfang Data) were searched. RevMan 5.3 software was used to data analysis.ResultsA total of 10 pieces of literature were included, involving 413 children. Meta‐analysis showed that: (1) The average Vancouver Scar Scale after surgery was significantly lower than that before surgery [weight mean difference (WMD) = −3.56, 95% confidence interval (CI):−4.53,−2.58, p < 0.001]; (2) After CO2 fractional laser, pigmentation [WMD = −0.74, 95% CI:−1.10,−0.38, p < 0.001], pliability [WMD = −0.92, 95% CI:−1.20,−0.65, p < 0.001], vascularity [WMD = −0.77, 95% CI:−1.09,−0.46, p < 0.001], height [WMD = −0.57, 95% CI:−0.95,−0.19, p < 0.001] were improved compared with those before surgery. (3) The average Visual Analogue Scale (VAS) after surgery was significantly lower than that before surgery [WMD = −3.94, 95% CI:−5.69,−2.22, p < 0.001]. (4) Both Patient and Observer Scar Assessment Scale (POSAS)‐Observer [WMD = −3.98, 95% CI:−8.44,0.47, p < 0.001] and POSAS‐Patient [WMD = −4.98, 95% CI:−8.09,−1.87, p < 0.001] were significantly lower than those before surgery. (5) Erythema and vesicles were the most common complications after CO2 fractional laser therapy, with an incidence of 4.09%.ConclusionCO2 fractional laser is beneficial to the recovery of hypertrophic scar after burn in children, and can effectively improve the scar symptoms and signs in children, with desirable clinical efficacy.
Xenotransplantation literature update March 2023–November 2023
Authors: Kamberi Shani , Meier Raphael P. H. 
Published: February 2024

AbstractWe present an updated report highlighting significant developments in the field of xenotransplantation since March 2023. The past six months have witnessed significant strides in the field and the emergence of novel research that is expected to facilitate the journey towards clinical trials. We are reviewing here the most pertinent findings from March 2023 to November 2023.
A New Method for Assessing Total Cardiovascular Stiffness—Preliminary Data
Authors: Oliver Maggie , Kumar Senthil , Petroski Gregory F. , Manring Noah 
Published: February 2024

Abstract
This paper demonstrates a new method for assessing total cardiovascular stiffness using the following five hemodynamic parameters gathered during a routine echocardiogram: (1) left ventricular stroke volume, (2) left ventricular ejection period, (3) heart rate, (4) systolic blood pressure, and (5) diastolic blood pressure. This study uses eight volunteer patients undergoing a routine echocardiogram at the University of Missouri Hospitals. Pulse wave velocity (PWV) data was taken immediately after the echocardiogram and compared to the cardiovascular stiffness result obtained from the echocardiogram data. The R2 value for this comparison was 0.8499 which shows a good correlation. We hypothesize that our new method for assessing total cardiovascular stiffness may be considered equivalent to that of the PWV method.
Linear Moments-Based Monte Carlo Simulation for Reliability Analysis With Unknown Probability Distributions
Authors: Zhang Long-Wen , Zhao Yan-Gang 
Published: February 2024

AbstractWithin the realm of structural reliability analysis, the uncertainties tied to resistance and loads are conventionally embodied as random variables possessing established cumulative distribution functions (CDFs). Nevertheless, real-world scenarios often involve cases where the CDFs of random variables are unknown, necessitating the probabilistic traits of these variables solely through statistical moments. In this study, for the purpose of integrating random variables characterized by an unknown CDF into the framework of Monte Carlo simulation (MCS), a linear moments (L-moments)-based method is proposed. The random variables marked by an unknown CDF are rendered as a straightforward function of a standard normal random variable, and the formulation of this function is determined by utilizing the L-moments, which are typically attainable from the statistical data of the random variables. By employing the proposed approach, the generation of random numbers associated with variables with unknown CDFs becomes a straightforward process, utilizing those derived from a standard normal random variable constructed by using Box-Muller transform. A selection of illustrative examples is presented, in which the efficacy of the technique is scrutinized. This examination reveals that despite its simplicity, the method demonstrates a level of precision that qualifies it for incorporating random variables characterized by unspecified CDFs within the framework of MCS for purposes of structural reliability analysis.
Modeling the Thermal-Compression Flip-Chip Process by Finite Element Analysis
Authors: Huang Yue , Li Shang-Shu , Gao Yan-Pei , Zhu Hai-Bin , He Gao-Yin , Xie Xiao-Hui , Lin Chun 
Published: February 2024

Abstract
For the first time, finite element analysis (FEA) is applied to the thermal-compression flip-chip process in micro-electronics. By adding the bump height nonuniformity and the morphology variance, a common basal line is established. Although the experiment confirms the rate dependence of indium, an approximation is made to derive the material properties in FEA. The relative standard deviation (RSD) of deformation between the FEA model and the reality is around 1% when predicting the misaligned flip-chip specimen. Besides, the modeled bump characteristic with misalignment coincides with the cross-sectional scanning electron microscope (SEM) picture. The model could be served as a powerful tool to guide the manufacturing process.
Deep Learning Methods for Diagnosing Thyroid Cancer
Authors: Kaur Gurmanik , Busi Ram Babu , Talam Satyanarayana , Marlapalli Krishna 
Published: February 2024

Abstract
One of the prevalent, life-threatening disorders that has been on the rise in recent years is thyroid nodule. A frequent diagnostic technique for locating and identifying thyroid nodules is ultrasound imaging. However, it takes time and presents difficulties for the specialists to evaluate all of the slide images. Automated, reliable, and objective methods are required for accurately evaluating ultrasound images. Recent developments in deep learning have completely changed several facets of image analysis and computer-aided diagnostic (CAD) techniques that deal with the issue of identifying thyroid nodules. We reviewed the literature on the potential, constraints, and present deep learning applications for thyroid cancer detection and discussed the study's goals. We provided an overview of latest developments in the deep learning techniques for thyroid cancer diagnosis and addressed some of the difficulties and practical issues that can restrict the development of deep learning and its incorporation into healthcare setting.
Evaluation by Liquid Crystal Thermography of Transient Surface Temperature Distribution in Radiant Floor Cooling Applications and Assessment of Analytical and Numerical Models
Authors: Bizzarri Marco , Conti Paolo , Glicksman Leon R. , Schito Eva , Testi Daniele 
Published: February 2024

Abstract
The purpose of our study is to evaluate the surface temperature distribution on a radiant floor, particularly focusing on space cooling operations, to assess the presence of nonuniformities. In fact, knowing the temperature difference between the average superficial temperature and the coldest spot can be a useful indication for condensation prevention. Primarily, we performed an experimental campaign in test rooms using temperature sensors and liquid crystal thermography. This allowed us to evaluate the floor temperature distribution both on a local scale, influenced by the discontinuous presence of buried water pipes, and on a macroscale, influenced by internal use, objects, and boundary conditions of the surrounding space. Then, the experimental temperature field on the radiant floor surface has been compared with analytical and numerical models in steady-state and transient phases, respectively. The results indicate limited superficial temperature variations that become more significant at larger tube spacings and under transient conditions. In particular, the numerical transient analysis showed that shortly after a step change in the pipe's temperature boundary condition, a larger variation is locally observable on the floor, which then decays to the new steady-state conditions, presenting more uniformity. However, local effects are generally overshadowed by macro-effects, especially for practical scenarios where many objects, furnishings, and different boundary conditions are present. Finally, as a conservative guideline for the cooling system control, we recommend maintaining the average superficial floor temperature at least 1 °C above the dew point, to account for the described nonuniformities.
Vaginal community state types (CSTs) alter environmental cues and production of the
Staphylococcus aureus
toxic shock syndrome toxin-1 (TSST-1)
Authors: Maduta Carla S. , McCormick John K. , Dufresne Karine 
Published: February 2024

ABSTRACT

Menstrual toxic shock syndrome (mTSS) is a rare but life-threatening disease associated with the use of high-absorbency tampons. The production of the
Staphylococcus aureus
toxic shock syndrome toxin-1 (TSST-1) superantigen is involved in nearly all cases of mTSS and is tightly controlled by regulators responding to the environment. In the prototypic mTSS strain
S. aureus
MN8, the major repressor of TSST-1 is the carbon catabolite protein A (CcpA), which responds to glucose concentrations in the vaginal tract. Healthy vaginal
Lactobacillus
species also depend on glucose for both growth and acidification of the vaginal environment through lactic acid production. We hypothesized that interactions between the vaginal microbiota [herein referred to as community state types (CSTs)] and
S. aureus
MN8 depend on environmental cues and that these interactions subsequently affect TSST-1 production. Using
S. aureus
MN8 Δ
ccpA
growing in various glucose concentrations, we demonstrate that the supernatants from different CSTs grown in vaginally defined medium (VDM) could significantly decrease
tst
expression. When co-culturing CST species with MN8 ∆
ccpA
, we show that
Lactobacillus jensenii
completely inhibits TSST-1 production in conditions mimicking healthy menstruation or mTSS. Finally, we show that growing
S. aureus
in “unhealthy” or “transitional” CST supernatants results in higher interleukin 2 (IL-2) production from T cells. These findings suggest that dysbiotic CSTs may encourage TSST-1 production in the vaginal tract and further indicate that the CSTs are likely important for the protection from mTSS.

IMPORTANCE

In this study, we investigate the impact of the vaginal microbiota against
Staphylococcus aureus
in conditions mimicking the vaginal environment at various stages of the menstrual cycle. We demonstrate that
Lactobacillus jensenii
can inhibit toxic shock syndrome toxin-1 (TSST-1) production, suggesting the potential for probiotic activity in treating and preventing menstrual toxic shock syndrome (mTSS). On the other side of the spectrum, “unhealthy” or “transient” bacteria such as
Gardnerella vaginalis
and
Lactobacillus iners
support more TSST-1 production by
S. aureus
, suggesting that community state types are important in the development of mTSS. This study sets forward a model for examining contact-independent interactions between pathogenic bacteria and the vaginal microbiota. It also demonstrates the necessity of replicating the environment when studying one as dynamic as the vagina.
Kidney organoids reveal redundancy in viral entry pathways during ACE2-dependent SARS-CoV-2 infection
Authors: Vanslambrouck Jessica M. , Neil Jessica A. , Rudraraju Rajeev , Mah Sophia , Tan Ker Sin , Groenewegen Ella , Forbes Thomas A. , Karavendzas Katerina , Elliott David A. , Porrello Enzo R. , Subbarao Kanta , Little Melissa H. 
Published: February 2024

ABSTRACT

With a high incidence of acute kidney injury among hospitalized COVID-19 patients, considerable attention has been focussed on whether SARS-CoV-2 specifically targets kidney cells to directly impact renal function, or whether renal damage is primarily an indirect outcome. To date, several studies have utilized kidney organoids to understand the pathogenesis of COVID-19, revealing the ability for SARS-CoV-2 to predominantly infect cells of the proximal tubule (PT), with reduced infectivity following administration of soluble ACE2. However, the immaturity of standard human kidney organoids represents a significant hurdle, leaving the preferred SARS-CoV-2 processing pathway, existence of alternate viral receptors, and the effect of common hypertensive medications on the expression of ACE2 in the context of SARS-CoV-2 exposure incompletely understood. Utilizing a novel kidney organoid model with enhanced PT maturity, genetic- and drug-mediated inhibition of viral entry and processing factors confirmed the requirement for ACE2 for SARS-CoV-2 entry but showed that the virus can utilize dual viral spike protein processing pathways downstream of ACE2 receptor binding. These include TMPRSS- and CTSL/CTSB-mediated non-endosomal and endocytic pathways, with TMPRSS10 likely playing a more significant role in the non-endosomal pathway in renal cells than TMPRSS2. Finally, treatment with the antihypertensive ACE inhibitor, lisinopril, showed negligible impact on receptor expression or susceptibility of renal cells to infection. This study represents the first in-depth characterization of viral entry in stem cell-derived human kidney organoids with enhanced PTs, providing deeper insight into the renal implications of the ongoing COVID-19 pandemic.

IMPORTANCE
Utilizing a human iPSC-derived kidney organoid model with improved proximal tubule (PT) maturity, we identified the mechanism of SARS-CoV-2 entry in renal cells, confirming ACE2 as the sole receptor and revealing redundancy in downstream cell surface TMPRSS- and endocytic Cathepsin-mediated pathways. In addition, these data address the implications of SARS-CoV-2 exposure in the setting of the commonly prescribed ACE-inhibitor, lisinopril, confirming its negligible impact on infection of kidney cells. Taken together, these results provide valuable insight into the mechanism of viral infection in the human kidney.