bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the health hazard originated via pesticide chemicals in human through rabbit model in agricultural production system in Bangladesh
Authors: Shaikat Amir Hossan , Khan Shahneaz Ali , Imtiaz Mohammed Ashif , Pasha Md Ridoan , Sultana Jabin , Saif Arfanul , Alam Mohammad Rashedul
Published: April 2022

Background

The use of chemical pesticides in developing countries like Bangladesh and their impacts on human health and food security is a global concern. Bangladesh is an agricultural dependent country for the growing population demand for food security and food safety. We conduct this study to assess public health threats of commonly utilised pesticides including malathion and nitrobenzene in female rabbit model.

Methods

Thirty New Zealand White healthy rabbit was divided randomly into three groups; and subjected to distilled water as control, malathion@ 5 mg/kg body weight and nitrobenzene@ 5 mg/kg body i.p daily for the next 15 days. Hematology, serum biochemistry and hormonal assay were performed.

Results

Red blood cell (RBC) concentrations (TEC, Hb, PCV%) were reduced in rabbits exposed to malathion and nitrobenzene. The neutrophil and eosinophil percentage were increased in the malathion and nitrobenzene exposed juvenile rabbit group. We found that serum aspartate aminotransferase (AST) and creatinine were increased in the nitrobenzene exposed group in infants, whereas malathion exposure increased serum alanine aminotransferase (ALT). In contrast, the juvenile group exposed to malathion increased the ALT level. There was no change in AST or creatinine levels in juvenile rabbits exposed to malathion or nitrobenzene. Serum estradiol levels were significantly lower in rabbits exposed to malathion and nitrobenzene. Serum testosterone concentration was increased in juvenile rabbits exposed to malathion and nitrobenzene, but progesterone was decreased in malathion exposed juvenile rabbits.

Conclusion

However, this study highlights the importance of rigorous monitoring and testing of agricultural products. In addition, strengthen research and extension in the fields of agro economy, organic farming, local universities and farmer associations.
Home sweet home: spatiotemporal distribution and site fidelity of the reef manta ray (Mobula alfredi) in Dungonab Bay, Sudan
Authors: Knochel Anna M. , Hussey Nigel E. , Kessel Steven T. , Braun Camrin D. , Cochran Jesse E. M. , Hill Graham , Klaus Rebecca , Checkchak Tarik , Elamin El Hassen Nasereldin M. , Younnis Mohammed , Berumen Michael L.
Published: April 2022

Background

Reef manta ray (Mobula alfredi) populations along the Northeastern African coastline are poorly studied. Identifying critical habitats for this species is essential for future research and conservation efforts. Dungonab Bay and Mukkawar Island National Park (DMNP), a component of a UNESCO World Heritage Site in Sudan, hosts the largest knownM. alfrediaggregation in the Red Sea.

Methods

A total of 19 individuals were tagged using surgically implanted acoustic tags and tracked within DMNP on an array of 15 strategically placed acoustic receivers in addition to two offshore receivers. Two of these acoustically monitoredM. alfrediwere also equipped with satellite linked archival tags and one individual was fitted with a satellite transmitting tag. Together, these data are used to describe approximately two years of residency and seasonal shifts in habitat use.

Results

Tagged individuals were detected within the array on 96% of monitored days and recorded an average residence index of 0.39 across all receivers. Detections were recorded throughout the year, though some individuals were absent from the receiver array for weeks or months at a time, and generalized additive mixed models showed a clear seasonal pattern in presence with the highest probabilities of detection occurring in boreal fall. The models indicated thatM. alfredipresence was highly correlated with increasing chlorophyll-a levels and weakly correlated with the full moon. Modeled biological factors, including sex and wingspan, had no influence on animal presence. Despite the high residency suggested by acoustic telemetry, satellite tag data and offshore acoustic detections in Sanganeb Atoll and Suedi Pass recorded individuals moving up to 125 km from the Bay. However, all these individuals were subsequently detected in the Bay, suggesting a strong degree of site fidelity at this location.

Conclusions

The current study adds to growing evidence thatM. alfrediare highly resident and site-attached to coastal bays and lagoons but display seasonal shifts in habitat use that are likely driven by resource availability. This information can be used to assist in managing and supporting sustainable ecotourism within the DMNP, part of a recently designated UNESCO World Heritage Site.
Thoracic low grade glial neoplasm with concurrent H3 K27M and PTPN11 mutations
Authors: Argenziano Michael G. , Furnari Julia L. , Miller Michael L. , Sun Yu , Banu Matei A. , Neira Justin A. , Snuderl Matija , Bruce Jeffrey N. , Welch Mary , McCormick Paul , Canoll Peter
Published: April 2022

We present the case of a 41-year-old man who developed worsening mid-thoracic back pain and imaging revealed a well-circumscribed intramedullary tumor in the thoracic spinal cord. Subtotal resection was performed, and histopathological analysis showed a cytologically bland, minimally proliferative glial neoplasm. Sequencing revealed H3 K27M and an activating PTPN11 mutation. Serial imaging revealed slow tumor regrowth over a three year period which prompted a second resection. The recurrent tumor displayed a similar low grade-appearing histology and harbored the same H3 K27M and PTPN11 mutations as the primary. While the prognostic importance of isolated H3 K27M in spinal gliomas is well-known, the combination of these two mutations in spinal low grade glioma has not been previously reported. Importantly, PTPN11 is a component of the MAPK signaling pathway. Thus, as building evidence shows that low grade-appearing gliomas harboring H3 K27M mutations along with BRAF or FGFR1 mutations have a relatively more favorable course compared to isolated H3 K27M-mutant midline gliomas, the present case provides new evidence for the prognostic importance of activating mutations in other components of the MAPK signaling pathway. This case further highlights the importance of clinico-radio-pathologic correlation when incorporating evolving genetic data into the integrated diagnosis of rare neuroepithelial tumors.
Fibroblast growth factor receptor 4 promotes glioblastoma progression: a central role of integrin-mediated cell invasiveness
Authors: Gabler Lisa , Jaunecker Carola Nadine , Katz Sonja , van Schoonhoven Sushilla , Englinger Bernhard , Pirker Christine , Mohr Thomas , Vician Petra , Stojanovic Mirjana , Woitzuck Valentin , Laemmerer Anna , Kirchhofer Dominik , Mayr Lisa , LaFranca Mery , Erhart Friedrich , Grissenberger Sarah , Wenninger-Weinzierl Andrea , Sturtzel Caterina , Kiesel Barbara , Lang Alexandra , Marian Brigitte , Grasl-Kraupp Bettina , Distel Martin , Schüler Julia , Gojo Johannes , Grusch Michael , Spiegl-Kreinecker Sabine , Donoghue Daniel J. , Lötsch Daniela , Berger Walter
Published: April 2022

Glioblastoma (GBM) is characterized by a particularly invasive phenotype, supported by oncogenic signals from the fibroblast growth factor (FGF)/ FGF receptor (FGFR) network. However, a possible role of FGFR4 remained elusive so far. Several transcriptomic glioma datasets were analyzed. An extended panel of primary surgical specimen-derived and immortalized GBM (stem)cell models and original tumor tissues were screened for FGFR4 expression. GBM models engineered for wild-type and dominant-negative FGFR4 overexpression were investigated regarding aggressiveness and xenograft formation. Gene set enrichment analyses of FGFR4-modulated GBM models were compared to patient-derived datasets. Despite widely absent in adult brain, FGFR4 mRNA was distinctly expressed in embryonic neural stem cells and significantly upregulated in glioblastoma. Pronounced FGFR4 overexpression defined a distinct GBM patient subgroup with dismal prognosis. Expression levels of FGFR4 and its specific ligands FGF19/FGF23 correlated both in vitro and in vivo and were progressively upregulated in the vast majority of recurrent tumors. Based on overexpression/blockade experiments in respective GBM models, a central pro-oncogenic function of FGFR4 concerning viability, adhesion, migration, and clonogenicity was identified. Expression of dominant-negative FGFR4 resulted in diminished (subcutaneous) or blocked (orthotopic) GBM xenograft formation in the mouse and reduced invasiveness in zebrafish xenotransplantation models. In vitro and in vivo data consistently revealed distinct FGFR4 and integrin/extracellular matrix interactions. Accordingly, FGFR4 blockade profoundly sensitized FGFR4-overexpressing GBM models towards integrin/focal adhesion kinase inhibitors. Collectively, FGFR4 overexpression contributes to the malignant phenotype of a highly aggressive GBM subgroup and is associated with integrin-related therapeutic vulnerabilities.
Deep learning from multiple experts improves identification of amyloid neuropathologies
Authors: Wong Daniel R. , Tang Ziqi , Mew Nicholas C. , Das Sakshi , Athey Justin , McAleese Kirsty E. , Kofler Julia K. , Flanagan Margaret E. , Borys Ewa , White Charles L. , Butte Atul J. , Dugger Brittany N. , Keiser Michael J.
Published: April 2022

Pathologists can label pathologies differently, making it challenging to yield consistent assessments in the absence of one ground truth. To address this problem, we present a deep learning (DL) approach that draws on a cohort of experts, weighs each contribution, and is robust to noisy labels. We collected 100,495 annotations on 20,099 candidate amyloid beta neuropathologies (cerebral amyloid angiopathy (CAA), and cored and diffuse plaques) from three institutions, independently annotated by five experts. DL methods trained on a consensus-of-two strategy yielded 12.6–26% improvements by area under the precision recall curve (AUPRC) when compared to those that learned individualized annotations. This strategy surpassed individual-expert models, even when unfairly assessed on benchmarks favoring them. Moreover, ensembling over individual models was robust to hidden random annotators. In blind prospective tests of 52,555 subsequent expert-annotated images, the models labeled pathologies like their human counterparts (consensus model AUPRC = 0.74 cored; 0.69 CAA). This study demonstrates a means to combine multiple ground truths into a common-ground DL model that yields consistent diagnoses informed by multiple and potentially variable expert opinions.
Functionality of early medieval roasters studied using archaeobotany and chromatography: preliminary studies
Authors: Lisowska Ewa , Rosiak Angelina , Sady-Bugajska Agata , Kałużna-Czaplińska Joanna
Published: April 2022

Roasters are clay, quadrilateral vessels that are found in areas of whole Slavic region. For years, there has been a discussion on their functionality, in which various concepts of their use keep appearing. In this paper we present the results of botanical and gas chromatographic studies carried out on several fragments of roasters that originated in the Sudetes Mountain area and Sudetic Foreland. The analyzed artefacts in total of 26 pieces come from three early medieval sites: Gilów, Jelenia Góra–Grabary and Kamieniec Ząbkowicki. The obtained results allowed to concluding that these were the vessels used for thermal processing of cereal grains in both processes of food processing and food preservation. The results made it possible to move the beginnings of agrarian activity in the Sudetes Mountains by 400 years, earlier than it was thought, which has a key meaning for observation of the economy development in mountainous areas in the early Middle Ages.
Comparing traditional news and social media with stock price movements; which comes first, the news or the price change?
Authors: Smith Stephen , O’Hare Anthony
Published: April 2022

Twitter has been responsible for some major stock market news in the recent past, from rogue CEOs damaging their company to very active world leaders asking for brand boycotts, but despite its impact Twitter has still not been as impactful on markets as traditional news sources. In this paper we examine whether daily news sentiment of several companies and Twitter sentiment from their CEOs have an impact on their market performance and whether traditional news sources and Twitter activity of heads of government impact the benchmark indexes of major world economies over a period spanning the outbreak of the SAR-COV-2 pandemic. Our results indicate that there is very limited correlation between Twitter sentiment and price movements and that this does not change much when returns are taken relative to the market or when the market is calm or turbulent. There is almost no correlation under any circumstances between non-financial news sources and price movements, however there is some correlation between financial news sentiment and stock price movements. We also find this correlation gets stronger when returns are taken relative to the market. There are fewer companies correlated in both turbulent and calm economic times. There is no clear pattern to the direction and strength of the correlation, with some being strongly negatively correlated and others being strongly positively correlated, but in general the size of the correlation tends to indicate that price movement is driving sentiment, except in the turbulent economic times of the SARS-COV-2 pandemic in 2020.
Multivariate cryptocurrency prediction: comparative analysis of three recurrent neural networks approaches
Authors: Hansun Seng , Wicaksana Arya , Khaliq Abdul Q. M.
Published: April 2022

As a new type of currency introduced in the new millennium, cryptocurrency has established its ecosystems and attracts many people to use and invest in it. However, cryptocurrencies are highly dynamic and volatile, making it challenging to predict their future values. In this research, we use a multivariate prediction approach and three different recurrent neural networks (RNNs), namely the long short-term memory (LSTM), the bidirectional LSTM (Bi-LSTM), and the gated recurrent unit (GRU). We also propose simple three layers deep networks architecture for the regression task in this study. From the experimental results on five major cryptocurrencies, i.e., Bitcoin (BTC), Ethereum (ETH), Cardano (ADA), Tether (USDT), and Binance Coin (BNB), we find that both Bi-LSTM and GRU have similar performance results in terms of accuracy. However, in terms of the execution time, both LSTM and GRU have similar results, where GRU is slightly better and has lower variation results on average.
The impact of ensemble learning on surgical tools classification during laparoscopic cholecystectomy
Authors: Jaafari Jaafar , Douzi Samira , Douzi Khadija , Hssina Badr
Published: April 2022

Laparoscopic surgery also know as minimally invasive surgery (MIS), is a type of surgical procedure that allows a surgeon to examine the organs inside of the abdomen without having to make large incisions in the skin. It unifies the competence and skills of highly trained surgeons with the power and precision of machines. Furthermore, surgical instruments are inserted through the abdomen with the help of a laparoscope, which is a tube with a high-intensity light and a high-resolution camera at the end. In addition, recorded videos from this type of surgery have become a steadily more important information source. However, MIS videos are often very long, thereby, navigating through these videos is time and effort consuming. The automatic identification of tool presence in laparoscopic videos leads to detecting what tools are used at each time in surgery and helps in the automatic recognition of surgical workflow. The aim of this paper is to predict surgical tools from laparoscopic videos using three states of the arts CNNs, namely: VGG19, Inception v-4, and NASNet-A. In addition, an ensemble learning method is proposed, combining the three CNNs, to solve the tool presence detection problem as a multi-label classification problem. The proposed methods are evaluated on a dataset of 80 cholecystectomy videos (Cholec80 dataset). The results present an improvement of approximately 6.19% and a mean average precision of 97.84% when the ensemble learning method is applied.
NLP-based platform as a service: a brief review
Authors: Pais Sebastião , Cordeiro João , Jamil M. Luqman
Published: April 2022

Natural language processing (NLP) refers to the field of study that focuses on the interactions between human language and computers. It has recently gained much attention for analyzing human language computationally and has spread its applications for various tasks such as machine translation, information extraction, summarization, question answering, and others. With the rapid growth of cloud computing services, merging NLP in the cloud is a significant benefit. It allows researchers to conduct NLP-related experiments on large amounts of data handled by big data techniques while harnessing the cloud’s vast, on-demand computing power. However, it has not sufficiently spread its tools and applications as a service in the cloud and there is little literature available that discusses the scope of interdisciplinary work. NLP, cloud Computing, and big data are vast domains and contain their challenges and potentials. By overcoming those challenges and integrating these fields, great potential for NLP and its applications can be unleashed. This paper presents a survey of NLP in cloud computing with a key focus on the comparison of cloud-based NLP services, challenges of NLP and big data while emphasizing the necessity of viable cloud-based NLP services. In the first part of this paper, an overview of NLP is presented by discussing different levels of NLP and components of natural language generation (NLG), followed by the applications of NLP. In the second part, the concept of cloud computing is discussed that highlights the architectural layers and deployment models of cloud computing and cloud-hosted NLP services. In the third part, the field of big data in the cloud is discussed with an emphasis on NLP. Furthermore, information extraction via NLP techniques within big data is introduced.
An intelligent literature review: adopting inductive approach to define machine learning applications in the clinical domain
Authors: Sabharwal Renu , Miah Shah J.
Published: April 2022

Big data analytics utilizes different techniques to transform large volumes of big datasets. The analytics techniques utilize various computational methods such as Machine Learning (ML) for converting raw data into valuable insights. The ML assists individuals in performing work activities intelligently, which empowers decision-makers. Since academics and industry practitioners have growing interests in ML, various existing review studies have explored different applications of ML for enhancing knowledge about specific problem domains. However, in most of the cases existing studies suffer from the limitations of employing a holistic, automated approach. While several researchers developed various techniques to automate the systematic literature review process, they also seemed to lack transparency and guidance for future researchers. This research aims to promote the utilization of intelligent literature reviews for researchers by introducing a step-by-step automated framework. We offer an intelligent literature review to obtain in-depth analytical insight of ML applications in the clinical domain to (a) develop the intelligent literature framework using traditional literature and Latent Dirichlet Allocation (LDA) topic modeling, (b) analyze research documents using traditional systematic literature review revealing ML applications, and (c) identify topics from documents using LDA topic modeling. We used a PRISMA framework for the review to harness samples sourced from four major databases (e.g., IEEE, PubMed, Scopus, and Google Scholar) published between 2016 and 2021 (September). The framework comprises two stages—(a) traditional systematic literature review consisting of three stages (planning, conducting, and reporting) and (b) LDA topic modeling that consists of three steps (pre-processing, topic modeling, and post-processing). The intelligent literature review framework transparently and reliably reviewed 305 sample documents.
Potential for the use of large unstructured data resources by public innovation support institutions
Authors: Cetera Wiesław , Gogołek Włodzimierz , Żołnierski Aleksander , Jaruga Dariusz
Published: April 2022

Effective programming of research and development (R&D) support, adjusted to the actual potential of beneficiaries, requires the use of modern analytical tools. An efficient R&D support system requires up-to-date data on technological trends, ongoing (and planning) research, market needs and developing innovation. The most popular programming methods were based on the analysis of data with a 4 to 5-year time delay until recently. Having described the method of refining information from unstructured data, we explore how to make it possible not only to solve the issue of up-to-date data but to identify of the latest trends in R&D activities.

The analytical tools we describe were already fully functional in 2018 and are constantly being improved. The article presents the potential of one tool that can be applied in public support institutions. Methods of identifying and diagnosing technology trends are presented within the case study of the electric car technology trend. The presented case study shows the effectiveness of the method we developed for identifying and diagnosing areas requiring support from public funds. Public institutions, including public institutions supporting R&D and innovation processes, can apply tools that allow an increase in the quality of public support programmes offered, but also beneficial for the quality of strategic resources management within the institution itself. The comparison of the predictions made by the described tools with the classifications made by experts, the former are more accurate and precise. Moreover, the results of the analyses performed by the presented model are not influenced by distorting factors—fads, trends, political pressures, or processes with an unidentified, non-substantive background. It should be emphasized that the accuracy of the whole model is 0.84. The described tools and methods are already directly applicable in many areas related to the support of R&D activity worldwide. The article presents a solution that effectively enables the management of more precise programmes supporting innovative activities used for the first time in Poland. It is also one of the first uses of these methods by public administration in the world. Our approach not only strengthens improved adjustment of the support offered for R&D activity, but also makes it possible to apply and improve management methods in public institutions.
Investigation into the combustion kinetics and spontaneous ignition of sweet sorghum as energy resource
Authors: Luthfi Numan , Ohkoshi Tappei , Tamaru Yutaka , Fukushima Takashi , Takisawa Kenji
Published: April 2022

This study investigated the combustion kinetics and spontaneous ignition of sweet sorghum using thermogravimetric analysis and the Frank-Kamenetskii theory. The aim was to determine the proper operating conditions for a direct combustion reactor and predict the safe ambient temperature limits for given silo designs. Oxidative heating rates of 2, 5, and 10 °C/min were set up. Graphical observation shows that combustion was composed of two different stages representing the overlapping processes of pyrolysis and char oxidation, at 131–336 °C and 336–475 °C, respectively. Samples were found to ignite at 215 °C and were extinguished at 433 °C. Different heating rates shifted combustion characteristics to higher temperatures and increased reactivity for ignition and combustion indices up to 12 and 10 times higher. The Friedman method determined the apparent activation energies representing the combustion reaction by 132.91 kJ/mol. Regarding spontaneous ignition, the temperature safe limits were predicted to be 83–84 °C and 84–87 °C for cylindrical and box silos with diameter and height of 15 and 10 m, respectively. Calculations of silos were designed within the limits of certain dimension ratios.

Graphical Abstract
Insights into the microbiome assembly during different growth stages and storage of strawberry plants
Authors: Olimi Expedito , Kusstatscher Peter , Wicaksono Wisnu Adi , Abdelfattah Ahmed , Cernava Tomislav , Berg Gabriele
Published: April 2022

Background

Microbiome assembly was identified as an important factor for plant growth and health, but this process is largely unknown, especially for the fruit microbiome. Therefore, we analyzed strawberry plants of two cultivars by focusing on microbiome tracking during the different growth stages and storage using amplicon sequencing, qPCR, and microscopic approaches.

Results

Strawberry plants carried a highly diverse microbiome, therein the bacterial familiesSphingomonadaceae(25%),Pseudomonadaceae(17%), andBurkholderiaceae(11%); and the fungal familyMycosphaerella(45%) were most abundant. All compartments were colonized by high number of bacteria and fungi (107–1010marker gene copies per g fresh weight), and were characterized by high microbial diversity (6049 and 1501 ASVs); both were higher for the belowground samples than in the phyllosphere. Compartment type was the main driver of microbial diversity, structure, and abundance (bacterial: 45%; fungal: 61%) when compared to the cultivar (1.6%; 2.2%). Microbiome assembly was strongly divided for belowground habitats and the phyllosphere; only a low proportion of the microbiome was transferred from soil via the rhizosphere to the phyllosphere. During fruit development, we observed the highest rates of microbial transfer from leaves and flowers to ripe fruits, where most of the bacteria occured inside the pulp. In postharvest fruits, microbial diversity decreased while the overall abundance increased. Developing postharvest decay caused byBotrytis cinereadecreased the diversity as well, and induced a reduction of potentially beneficial taxa.

Conclusion

Our findings provide insights into microbiome assembly in strawberry plants and highlight the importance of microbe transfer during fruit development and storage with potential implications for food health and safety.
What is real change in submaximal cardiorespiratory fitness in older adults? Retrospective analysis of a clinical trial
Authors: Hall Michelle , Lima Yuri Lopes , Huschtscha Zoya , Dobson Fiona , Costa Ricardo J. S.
Published: April 2022

Objective

To assess the test–retest reliability of submaximal cardiorespiratory fitness in healthy active older adults.

Methods

This was a retrospective analysis of 41 adults enrolled in a clinical trial [mean (sd) aged 59 yrs (7); 29% females; and body mass index 24.5 kg/m2 (3.3)]. Cardiorespiratory fitness was assessed using a cycle ergometer 6 weeks apart. The initial workload was 1 W per kilogram of free fat mass (W/kg FFM) and increased by 0.5 W/kg FFM every 3 min until participants could not maintain the speed at ≥ 60 rpm, they reached a rating of perceived exertion of 15–17, and/or obtained a respiratory exchange ratio (RER) of 1.000. Reliability of $${V}{\text{O}}_{2}$$

V

O
2

, heart rate and RER was assessed for each workload, and for $${V}{\text{O}}_{2}$$

V

O
2

, when RER reached 1.00. Reliability was examined as the intraclass correlation coefficient (ICC(2,1)), Bland–Altman plots, standard error of measurement (SEM and SEM%), and the minimal detectable change (MDC).

Results

Test–retest agreement ranged between (ICC(2,1) 0.44–0.84) with no discernible systematic differences between assessments. The SEM% for absolute and relative $${V}{\text{O}}_{2}$$

V

O
2

ranged between 13.0 to 20.2%, and 13.8 to 26.3%, respectively. The MDC90% for absolute and relative $${V}{\text{O}}_{2}$$

V

O
2

ranged between 30.4% to 47.1%, and 32.2% to 61.4%, respectively. The lowest SEMs% and MDCs% for both absolute and relative $${V}{\text{O}}_{2}$$

V

O
2

were observed for workloads at 2.5 W kg/FFM (~ 13% and ~ 31%, respectively).

Conclusions

Although at least modest relative reliability was consistently demonstrated, the smaller measurement error associated with absolute and relative $${V}{\text{O}}_{2}$$

V

O
2

at 2.5 W kg/FFM may indirectly suggest that submaximal cardiorespiratory fitness can be monitored more confidently at higher workloads. Findings provide critical information to determine how much change is considered ‘real change’ in repeated measures of cardiorespiratory fitness using a submaximal graded exercise testing protocol in healthy active older adults.
The Role of Sports Clothing in Thermoregulation, Comfort, and Performance During Exercise in the Heat: A Narrative Review
Authors: Di Domenico Isaiah , Hoffmann Samantha M. , Collins Paul K.
Published: April 2022

The aims of this review are to (1) summarise the current research of sports clothing as it relates to thermoregulation, comfort, and performance during exercise in the heat, (2) identify methodological limitations and gaps in the knowledge base of sports clothing, and (3) provide recommendations for exercise testing protocols to accurately assess the impact of sports clothing in athletic populations during exercise in the heat. Sports clothing consists of lightweight and breathable fabrics, surface treatments, and various designs which aim to enhance sweat evaporation and comfort during exercise in the heat. Sports clothing comprised of natural, synthetic, and chemically treated fabrics has been investigated during exercise of varying durations (15–120 min), intensities (20–70% VO2 max) and types (fixed intensity, incremental, self-paced), and in an array of climatic conditions (18–40 °C, 20–60% relative humidity). To date, few studies have identified significant differences in thermo-physiological, perceptual, and performance measures between natural and synthetic fabrics or compared the effect of chemical treatments to their non-treated equivalent on such measures during exercise. Collectively, previous wearer trials have failed to replicate the upper limit of training and competition demands when assessing sports clothing in endurance-trained individuals who regularly train and compete in hot and humid climates. Clothing comfort has also been evaluated using simple scales which fail to capture intricate detail pertaining to psychological and sensorial parameters. The incorporation of protocols using hot and humid climates (≥ 30 °C, ≥ 70% relative humidity) and longer exercise durations (> 45 min) is warranted. Future research should also consider exploring the effect of sports clothing on thermal, physiological, perceptual, and performance measures between males and females, and assessing clothing comfort using a multi-dimensional approach.
Sequential activation of M1 and M2 phenotypes in macrophages by Mg degradation from Ti-Mg alloy for enhanced osteogenesis
Authors: Liang Luxin , Song Deye , Wu Kai , Ouyang Zhengxiao , Huang Qianli , Lei Guanghua , Zhou Kun , Xiao Jian , Wu Hong
Published: April 2022

Background

Even though the modulatory effects of Magnisum (Mg) and its alloys on bone-healing cells have been widely investigated during the last two decades, relatively limited attention has been paid on their inflammation-modulatory properties. Understanding the activation process of macrophages in response to the dynamic degradation process of Mg as well as the relationship between macrophage phenotypes and their osteogenic potential is critical for the design and development of advanced Mg-based or Mg-incorporated biomaterials.

Methods

In this work, a Ti-0.625 Mg (wt.%) alloy fabricated by mechanical alloying (MA) and subsequent spark plasma sintering (SPS) was employed as a material model to explore the inflammatory response and osteogenic performance in vitro and in vivo by taking pure Ti as the control. The data analysis was performed following Student’s t-test.

Results

The results revealed that the macrophages grown on the Ti-0.625 Mg alloy underwent sequential activation of M1 and M2 phenotypes during a culture period of 5 days. The initially increased environmental pH (~ 8.03) was responsible for the activation of M1 macrophages, while accumulated Mg
2+
within cells contributed to the lateral M2 phenotype activation. Both M1 and M2 macrophages promoted osteoblast-like SaOS-2 cell maturation. In vivo experiment further showed the better anti-inflammatory response, regenerative potentiality and thinner fibrous tissue layer for the Ti-0.625 Mg alloy than pure Ti.

Conclusion

The results highlighted the roles of Mg degradation in the Ti-0.625 Mg alloy on the sequential activation of macrophage phenotypes and the importance of modulating M1-to-M2 transition in macrophage phenotypes for the design and development of inflammation-modulatory biomaterials.
Thermosensitive core-rigid micelles of monomethoxy poly(ethylene glycol)-deoxy cholic acid
Authors: Han Jin Ok , Lee Hyun Jung , Jeong Byeongmoon
Published: April 2022

Background

Thermosensitive micelles with rigid cores that exhibit a reversible lower critical solution temperature at 30–35 °C can be applied for drug delivery.

Method

Hydrophilic monomethoxy poly(ethylene glycol) was conjugated to hydrophobic deoxycholic acid to prepare monomethoxy poly(ethylene glycol)-deoxycholic acid (mPEG-DC). Micelle formation and thermosensitive solution behavior were studied using various methods, including hydrophobic dye solubilization, transmission electron microscopy, dynamic light scattering, turbidity measurement, microcalorimetry, and
1
H-NMR spectroscopy. Drug release from the thermosensitive micelles was demonstrated using estradiol, a model drug.

Results

The mPEG-DC formed micelles with a critical micelle concentration of 0.05 wt.% and an average size of 15 nm. Aqueous mPEG-DC solutions exhibit a lower critical solution temperature (LCST) that is independent of concentration and reversible over heating and cooling cycles. The LCST transition is an entropically driven process involving dehydration of the PEG shell. The thermosensitive mPEG-DC micelles with rigid DC cores were applied as an estradiol delivery system in which estradiol was released, without initial burst, over the 16 days in a diffusion-controlled manner.

Conclusions

This study suggests that mPEG-DCs form thermosensitive micelles with rigid cores that can function as an excellent diffusion-controlled hydrophobic drug delivery system without initial burst release.

Graphical Abstract

Thermosensitive core-rigid micelles of monomethoxy poly(ethylene glycol)-deoxy cholic acid
Complete atrioventricular block under epidural ropivacaine infusion in a patient with first-degree atrioventricular block and myasthenia gravis: a case report
Authors: Hashimoto Takuma , Kuratomi Shinobu , Yoshimura Hayashi
Published: April 2022

Background

First-degree atrioventricular block (AVB) may lead to complete AVB. Herein, we present a case of a complete AVB under thoracic epidural catheter infusion of ropivacaine with fentanyl in a patient with first-degree AVB and myasthenia gravis.

Case presentation

A 74-year-old woman with first-degree AVB underwent thymectomy for myasthenia gravis. Continuous thoracic epidural catheter infusion of 0.2% ropivacaine with fentanyl was initiated at 15 min before the end of the surgery. At 9 h postoperatively, the electrocardiogram showed a 10-s-long pause due to complete AVB. Thus, a temporary pacemaker was implanted, and at 19 h postoperatively on postoperative day 1, cardiac pacing was initiated and lasted approximately 30 s. After catheter removal, she had no further episodes of complete AVB.

Conclusion

First-degree AVB may lead to complete AVB under the influence of thoracic epidural infusion of ropivacaine in patients with myasthenia gravis.
The biobehavioural effectiveness of spiritual-hypnosis-assisted therapy in PTSD with childhood trauma
Authors: Lesmana Cokorda Bagus Jaya , Suryani Luh Ketut , Tiliopoulos Niko
Published: April 2022

Background

Posttraumatic Stress Disorder (PTSD) is a serious psychological trauma disorder. Treatment of psychological trauma tends to focus on patients' memory. Clinical Spiritual-Hypnosis Assisted Therapy is a culturally sensitive treatment that combines elements of psychodynamic hypnosis, cognitive–behavioral and humanistic therapies.

Methods

The current interventional single-blind randomized control study assessed the biobehavioural effectiveness of spiritual-hypnosis on cortisol and PTSD symptomatology in adults with childhood trauma. Participants were divided into spiritual hypnosis (n = 15) and a control group (n = 14) that received fluoxetine. This study used PCL-C & CTQ to screen the presence and severity of PTSD symptoms.

Results

Spiritual hypnosis was significantly better than fluoxetine at reducing PTSD symptoms, while both treatments had similar effects on cortisol modification.

Conclusions

Spiritual-Hypnosis Assisted Therapy for PTSD patients with childhood trauma appears to have a noteworthy effect in reducing PTSD clinical symptoms and results in a comparable to the pharmacological treatment modification of the HPA axis cortisol markers.
Impact of body mass index on urinary solutes in Egyptian adolescents
Authors: Mahfouz Nermine N. , Abd El-Shaheed Azza , Fahmy Reham F. , Sallam Sara F. , El-Zayat Salwa Refat , Sibaii Hiba , EL-Kassaby Mahitab I. , Mourad Hagar H.
Published: April 2022

Background

High body mass index constitutes a risk for nephrolithiasis in the context of metabolic syndrome. The majority of these renal stones are either composed of Urate or Calcium Oxalate. We aimed to evaluate the ratios of urinary Calcium and Uric Acid to urinary Creatinine as an early alarming pathological sign in overweight and obese adolescents. Ninety adolescents of both sexes participated in the study. Anthropometric measures were fulfilled, and calculation of body mass index and waist to height ratio were assessed. Urinary Calcium and urinary Uric Acid to Creatinine ratios were estimated in an early morning spot urine sample.

Results

Males and females had comparable values for solutes/Creatinine ratios. A highly significant negative correlation was detected between urinary Urate/Creatinine ratio and age of the child (P-value 0.001). Adolescents with higher body mass index had higher urinary Calcium/Creatinine and higher urinary Urate/Creatinine ratios but P-values were insignificant in our research.

Conclusion

At the age range of 10 to 18 years, the sex of the adolescent has an equivocal effect on urinary concentration of both Calcium and Uric Acid. Urinary solutes/Creatinine ratio decrease significantly by age in adolescence. Overweight and obesity tend to be risk factors for higher urinary solutes ‘concentration.
Multiple congenital visceral abnormalities as a rare cause of pulmonary arterial hypertension
Authors: Rabiee Parham , Saedi Sedigheh
Published: April 2022

Background

Pulmonary arterial hypertension (PAH) is a rare, progressive disorder. PAH is caused by a wide spectrum of pathologies but the cause remains undetermined on many occasions and patients are classified in the idiopathic group.

Case presentation

Here we report a young woman with rare congenital visceral abnormalities presenting with severe pulmonary hypertension.

Conclusions

Pulmonary hypertension is a complex disorder. Search for uncommon conditions that lead to pulmonary hypertension is necessary to determine the best management options.
Borehole magnetometry to determine the depth of reinforced foundations in telecommunication towers
Authors: Santos Matheus Carlos de Souza , Mendonça Carlos Alberto , Souza Tiago de Jesus , Hemsi Paulo Scarano , Gandolfo Otávio Coaracy Brasil
Published: April 2022

Technical information about deep foundations of built structures may in some cases be unavailable or incomplete due to the lack of construction documentation and electronic media in which the reports are stored. This problem is particularly relevant for telecommunication towers constructed two-to-three decades ago but still under operation and subject to new loading demands from expanding networks. Nondestructive evaluation with geophysical methods has been applied to determine the depth to the bottom of deep foundations, a key parameter to evaluate their bearing capacity and settlements. This is done by lowering a borehole magnetometry (BM) sensor down a drillhole installed close to the unknown structure, thereby measuring the magnetic field along the testing drillhole. Determining the bottom depth of the structure using BM data configures an edge detection problem: a classical problem in magnetic data interpretation, but in this case with poor data coverage (only a profile close to the structure) to characterize a complex magnetization distribution. Common practices to locate pile bottom from characteristic peak or inflection points in the observed magnetic anomaly may work at some sites but usually fail to account for the complex anomaly patterns from built structures. We summarize a set of numerical and field-work applications showing that no single characteristic attribute of the observed field can undoubtedly be used to determine the foundation depth. We verify that most of the measured field along the testing drillhole is disturbed by fields from facilities at the ground surface and develop a data inversion procedure enforcing data fitting to measurements at the lower portions of the drillhole. The efficacy of this technique is illustrated with field tests in different geologic scenarios with results compared with as-built documentation and/or independent evaluation with other methods.
Accelerating 2D and 3D frequency-domain seismic wave modeling through interpolating frequency-domain wavefields by deep learning
Authors: Cao Wenzhong , Li Quanli , Zhang Jie , Zhang Wei
Published: April 2022

An attractive feature of finite-difference modeling in the frequency domain is the low recomputation cost to simulate seismic waves for many sources through the same velocity model. However, it is time consuming if many frequencies are involved for solving the linear wave equations, particularly, for large 3D velocity models. We propose accelerating the modeling by applying deep learning. Because similarity appears among the wavefields in near frequencies, we can extract similar features and reconstruct the unknown wavefields by deep learning. We compute fewer frequency-domain wavefields with a large frequency interval by conventional modeling methods, such as finite-difference methods, and then interpolate more frequency-domain wavefields with a small frequency interval by applying deep learning. Numerical examples demonstrate that the U-Net, which is trained by the data on 10 2D simple-layered models, can be used to interpolate the data on SEG Advanced Modeling models and also can be used to interpolate the data on the 3D layered model and 3D overthrust model. A series of tests on perturbation models prove that the U-Net performance is still good when the root-mean-square value of the velocity model perturbation relative to the initial model is up to 15%. Compared with traditional modeling methods, the computational time of interpolating by applying deep learning is negligible, especially for 3D models. After the network is trained, the acceleration strategy helps to reduce the runtime by approximately 50% for a modeling problem because the U-Net can be used to interpolate 50% of the data that would otherwise need to be modeled. Although training the model will take some time, good generalization of the U-Net, especially for 3D problems, enhances its benefits on the application for frequency-domain forward modeling.
Hepcidin and Erythroferrone Complement the Athlete Biological Passport in the Detection of Autologous Blood Transfusion
Authors: BREENFELDT ANDERSEN ANDREAS , BEJDER JACOB , BONNE THOMAS C. , SØRENSEN HENRIK , SØRENSEN HELLE , JUNG GRACE , GANZ TOMAS , NEMETH ELIZABETA , SECHER NIELS H. , JOHANSSON PÄR I. , NORDSBORG NIKOLAI BAASTRUP
Published: April 2022

Purpose

We investigated whether hepcidin and erythroferrone (ERFE) could complement the athlete biological passport (ABP) in indirectly detecting a 130-mL packed red blood cells (RBC) autologous blood transfusion. Endurance performance was evaluated.

Methods

Forty-eight healthy men (n = 24) and women (n = 24) participated. Baseline samples were collected weekly followed by randomization to a blood transfusion (BT, n = 24) or control group (CON, n = 24). Only the BT group donated 450 mL whole blood from which 130 mL red blood cell was reinfused 4 wk later. Blood samples were collected 3, 7, 14, 21, and 28 d after donation, and 3, 6, and 24 h and 2, 3, and 6 d after reinfusion. In the CON group samples were collected with the same frequency. Endurance performance was evaluated by a 650-kCal time trial (n = 13) before and 1 and 6 d after reinfusion.

Results

A time–treatment effect existed (P < 0.05) for hepcidin and ERFE. Hepcidin was increased (P < 0.01) ~110 and 89% 6 and 24 h after reinfusion. Using an individual approach (99% specificity, e.g., allowing 1:100 false-positive), sensitivities, i.e., true positives, of 30% and 61% was found for hepcidin and ERFE, respectively. For the ABP, the most sensitive marker was Off-hr score ([Hb] (g·L−1) − 60 × √RET%) (P < 0.05) with a maximal sensitivity of ~58% and ~9% after donation and reinfusion, respectively. Combining the findings for hepcidin, ERFE, and the ABP yielded a sensitivity across all time-points of 83% after reinfusion in BT. Endurance performance increased 24 h (+6.4%, P < 0.01) and 6 d after reinfusion (+5.8%, P < 0.01).

Conclusions

Hepcidin and ERFE may serve as biomarkers in an antidoping context after an ergogenic, small-volume blood transfusion.
Bargaining over Contingent Contracts under Incomplete Information
Authors: de Clippel Geoffroy , Fanning Jack , Rozen Kareen
Published: April 2022

We study bargaining over contingent contracts in problems where private information becomes public or verifiable when the time comes to implement the agreement. We suggest a simple, two-stage game that incorporates important aspects of bargaining. We characterize equilibria in which parties always reach agreement, and study their limits as bargaining frictions vanish. Under mild regularity conditions, we show all interim-efficient limits belong to Myerson’s (1984) axiomatic solution. Furthermore, all limits must be interim efficient if equilibrium beliefs satisfy no-signaling-what-you-don’ t-know. Results extend to other bargaining protocols. (JEL C78, D82, D83, D86)
Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages?
Authors: Guerrieri Veronica , Lorenzoni Guido , Straub Ludwig , Werning Iván
Published: April 2022

Motivated by the effects of the COVID-19 pandemic, we present a theory of Keynesian supply shocks: shocks that reduce potential output in a sector of the economy, but that, by reducing demand in other sectors, ultimately push aggregate activity below potential. A Keynesian supply shock is more likely when the elasticity of substitution between sectors is relatively low, the intertemporal elasticity of substitution is relatively high, and markets are incomplete. Fiscal policy can display a smaller multiplier, but the insurance benefit of fiscal transfers can be enhanced. Firm exits and job destruction can amplify and propagate the shock. (JEL D52, E23, E24, E32, E62, I12, I18)