bluuebunny/crossref_metadata_2025 huggingface dataset:
Global trend analysis of diabetes mellitus incidence, mortality, and mortality-to-incidence ratio from 1990 to 2019
Authors: Balooch Hasankhani Mohammadreza , Mirzaei Hossein , Karamoozian Ali
Published: December 2023

Diabetes Mellitus (DM) is a common chronic disease and a public health challenge worldwide. The present study aimed to analyze the trend in DM incidence, mortality, and mortality-to-incidence ratio (MIR) world over 30 years. The age-standardized DM incidence and mortality rates for both genders and different countries of the world from 1990 to 2019 were extracted from the Global Burden of Disease (GBD) study and the Human Development Index (HDI) was obtained for all countries from the United Nations Development Program (UNDP) database. The mean trends for the indicators for developing countries, developed countries, and all countries were evaluated using Generalized Estimating Equations (GEE) and the spline model. The estimates showed that the global mean trend of DM incidence from 1990 to 2019 followed an upward trend with an annual increase of 3.73 cases per 100,000 people. The global mean of DM mortality followed an upward trend with an annual increase of 0.43 cases until 2005 followed by a downward trend after this year with an annual decrease of 0.14 and the global mean MIR followed a downward trend during the same period with an annual decrease of 0.001 per 100,000 people. Besides, the mean incidence of DM in developing countries followed an upward trend similar to the trend in developed countries. Additionally, the mean mortality rate due to DM in developing countries increased with a slope of 0.62 until 2005 and then decreased with a slope of 0.02, and the mean MIR trend in the developed and developing countries showed a downward trend. Thus, developed countries followed a relatively faster decrease in MIR than developing countries.The data from the present study show the increased incidence of DM has made it one of the most important health concerns in the world, and if this issue is not addressed, this disease can cause more concerns for communities in the coming years. This being so, more DM prevention and control programs need to be put into practice.
Forecasting the carbon footprint of civil buildings under different floor area growth trends and varying energy supply methods
Authors: Teng Jiaying , Yin Hang
Published: December 2023

The energy consumption and carbon footprint of buildings are significantly impacted by variations in building area and the number of households. Therefore, it is crucial to forecast the growth trend of building area and number of households. A validated time series model is used to predict the new building area in Jilin Province from 2023 to 2030. The new building area in Jilin Province is expected to exhibit two trends of growth in the future: rapid growth (S1) and slow growth (S2). By 2030, under the S1 growth trend, the residential construction area and public building construction area in Jilin Province are expected to be 30.26 Mm2 (million square meters) and 7.23 Mm2, respectively. If the future floor area grows slowly under the S2 trend, the new floor area of different types will be 8.26 Mm2 and 1.33 Mm2 by 2030, respectively. The population growth shows a downward trend. Therefore, the energy consumption and carbon footprint of new buildings with different growth trends of floor areas and the number of households can be predicted. The energy consumption of new buildings shows an increasing trend from 0.32 Mtce in 2023 to 0.55 Mtce in 2030 under the S1 trend and a slight downward trend under the S2 trend. The carbon footprint is expected to be reduced by 0.017–0.311 million tons of CO2 when using heat pumps to supply 10–50% of the heat and wind and solar to supply 10–50% of the electricity. For every 10% increase in the use of ultra-low energy buildings, the energy consumption of civil buildings decreases in the range of 0.0063–0.028 Mtce. If the use of heat pumps and renewable energy increases by 10%, the energy consumption of civil buildings decreases in the range of 0.0054–0.0249 Mtce.
Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls
Authors: Di Credico Andrea , Weiss Amélie , Corsini Massimo , Gaggi Giulia , Ghinassi Barbara , Wilbertz Johannes H. , Di Baldassarre Angela
Published: December 2023

Parkinson’s disease (PD) is the second most common neurodegenerative disease and is characterized by the loss of midbrain dopaminergic neurons. Endocrine disrupting chemicals (EDCs) are active substances that interfere with hormonal signaling. Among EDCs, bisphenols (BPs) and perfluoroalkyls (PFs) are chemicals leached from plastics and other household products, and humans are unavoidably exposed to these xenobiotics. Data from animal studies suggest that EDCs exposure may play a role in PD, but data about the effect of BPs and PFs on human models of the nervous system are lacking. Previous studies demonstrated that machine learning (ML) applied to microscopy data can classify different cell phenotypes based on image features. In this study, the effect of BPs and PFs at different concentrations within the real-life exposure range (0.01, 0.1, 1, and 2 µM) on the phenotypic profile of human stem cell-derived midbrain dopaminergic neurons (mDANs) was analyzed. Cells exposed for 72 h to the xenobiotics were stained with neuronal markers and evaluated using high content microscopy yielding 126 different phenotypic features. Three different ML models (LDA, XGBoost and LightGBM) were trained to classify EDC-treated versus control mDANs. EDC treated mDANs were identified with high accuracies (0.88–0.96). Assessment of the phenotypic feature contribution to the classification showed that EDCs induced a significant increase of alpha-synuclein (αSyn) and tyrosine hydroxylase (TH) staining intensity within the neurons. Moreover, microtubule-associated protein 2 (MAP2) neurite length and branching were significantly diminished in treated neurons. Our study shows that human mDANs are adversely impacted by exposure to EDCs, causing their phenotype to shift and exhibit more characteristics of PD. Importantly, ML-supported high-content imaging can identify concrete but subtle subcellular phenotypic changes that can be easily overlooked by visual inspection alone and that define EDCs effects in mDANs, thus enabling further pathological characterization in the future.
Thyroid hormone-regulated chromatin landscape and transcriptional sensitivity of the pituitary gland
Authors: Cho Young-Wook , Fu Yulong , Huang Chen-Che Jeff , Wu Xuefeng , Ng Lily , Kelley Kevin A. , Vella Kristen R. , Berg Anders H. , Hollenberg Anthony N. , Liu Hong , Forrest Douglas
Published: December 2023

Thyroid hormone (3,5,3’-triiodothyronine, T3) is a key regulator of pituitary gland function. The response to T3 is thought to hinge crucially on interactions of nuclear T3 receptors with enhancers but these sites in pituitary chromatin remain surprisingly obscure. Here, we investigate genome-wide receptor binding in mice using tagged endogenous thyroid hormone receptor β (TRβ) and analyze T3-regulated open chromatin using an anterior pituitary-specific Cre driver (Thrbb2Cre). Strikingly, T3 regulates histone modifications and chromatin opening primarily at sites that maintain TRβ binding regardless of T3 levels rather than at sites where T3 abolishes or induces de novo binding. These sites associate more frequently with T3-activated than T3-suppressed genes. TRβ-deficiency blunts T3-regulated gene expression, indicating that TRβ confers transcriptional sensitivity. We propose a model of gene activation in which poised receptor-enhancer complexes facilitate adjustable responses to T3 fluctuations, suggesting a genomic basis for T3-dependent pituitary function or pituitary dysfunction in thyroid disorders.
Atsttrin regulates osteoblastogenesis and osteoclastogenesis through the TNFR pathway
Authors: Liu Kaiwen , Wang Zihao , Liu Jinbo , Zhao Wei , Qiao Fei , He Qiting , Shi Jie , Meng Qunbo , Wei Jianlu , Cheng Lei
Published: December 2023

Osteoporosis is a systemic metabolic bone disorder for which inflammatory cytokines play an important role. To develop new osteoporosis treatments, strategies for improving the microenvironment for osteoblast and osteoclast balance are needed. Tumor necrosis factor-α (TNF-α) plays an important role in the initiation and development of osteoporosis. Atsttrin is an engineered protein derived from the growth factor, progranulin (PGRN). The present study investigates whether Atsttrin affects osteoclast formation and osteoblast formation. Here we show Atsttrin inhibits TNF-α-induced osteoclastogenesis and inflammation. Further mechanistic investigation indicates Atsttrin inhibits TNF-α-induced osteoclastogenesis through the TNFR1 signaling pathway. Moreover, Atsttrin rescues TNF-α-mediated inhibition of osteoblastogenesis via the TNFR1 pathway. Importantly, the present study indicates that while Atsttrin cannot directly induce osteoblastogenesis, it can significantly enhance osteoblastogenesis through TNFR2-Akt-Erk1/2 signaling. These results suggest that Atsttrin treatment could potentially be a strategy for maintaining proper bone homeostasis by regulating the osteoclast/osteoblast balance. Additionally, these results provide new insights for other bone metabolism-related diseases.
Nitrogen and sulfur metabolisms encoded in prokaryotic communities associated with sea ice algae
Authors: Bellas Christopher M , Campbell Karley , Tranter Martyn , Sánchez-Baracaldo Patricia
Published: December 2023

Sea ice habitats harbour seasonally abundant microalgal communities, which can be highly productive in the spring when the availability of light increases. An active, bloom-associated prokaryotic community relies on these microalgae for their organic carbon requirements, however an analysis of the encoded metabolic pathways within them is lacking. Hence, our understanding of biogeochemical cycling within sea ice remains incomplete. Here, we generated metagenomic assembled genomes from the bottom of first-year sea ice in northwestern Hudson Bay, during a spring diatom bloom. We show that the prokaryotic community had the metabolic potential to degrade algal derived dimethylsulphoniopropionate and oxidise sulfur. Facultative anaerobic metabolisms, specifically, dissimilatory nitrate reduction and denitrification were also prevalent here, suggesting some sea ice prokaryotes are metabolically capable of adapting to fluctuating oxygen levels during algal bloom conditions. Such denitrification could be an important loss of fixed-N2 in the changing Arctic marine system.
Enhanced fetal hematopoiesis in response to symptomatic SARS-CoV-2 infection during pregnancy
Authors: Alkobtawi Mansour , Ngô Qui Trung , Chapuis Nicolas , Fontaine Romain H. , El Khoury Mira , Tihy Matthieu , Hachem Nawa , Jary Aude , Calvez Vincent , Fontenay Michaela , Tsatsaris Vassilis , Aractingi Sélim , Oulès Bénédicte
Published: December 2023

Background

Pregnant women and their fetuses are particularly susceptible to respiratory pathogens. How they respond to SARS-CoV-2 infection is still under investigation.

Methods

We studied the transcriptome and phenotype of umbilical cord blood cells in pregnant women infected or not with SARS-CoV-2.

Results

Here we show that symptomatic maternal COVID-19 is associated with a transcriptional erythroid cell signature as compared with asymptomatic and uninfected mothers. We observe an expansion of fetal hematopoietic multipotent progenitors skewed towards erythroid differentiation that display increased clonogenicity. There was no difference in inflammatory cytokines levels in the cord blood upon maternal SARS-CoV-2 infection. Interestingly, we show an activation of hypoxia pathway in cord blood cells from symptomatic COVID-19 mothers, suggesting that maternal hypoxia may be triggering this fetal stress hematopoiesis.

Conclusions

Overall, these results show a fetal hematopoietic response to symptomatic COVID-19 in pregnant mothers in the absence of vertically transmitted SARS-CoV-2 infection which is likely to be a mechanism of fetal adaptation to the maternal infection and reduced oxygen supply.
Target-triggered dual signal amplification based on HCR-enhanced nanozyme activity for the sensitive visual detection of Escherichia coli
Authors: Yan Hangli , Wu Linghao , Wang Jingyu , Zheng Yi , Zhao Fengxia , Bai Qinqin , Hu Hongmei , Liang Hao , Niu Xiangheng
Published: December 2023

The detection of foodborne pathogens is crucial for food hygiene regulation and disease diagnosis.
Facile fabrication of carbon nanotube hollow microspheres as a fiber coating for ultrasensitive solid-phase microextraction of phthalic acid esters in tea beverages
Authors: Song Xin-Li , Liu Yu-Qing , He Fei-Yan , Wu Yi-Yao , Wang Dong-Dong , Lv Hui , Wang Xue-Shan , Sun Zhong-Guan , Cheng Can-Ling , Liao Ke-Chao , Chen Yue
Published: December 2023

Multiwalled carbon nanotubes hollow microspheres were utilized as a fiber coating for the SPME of PAEs from tea beverages.
Probing the nanoscale driving forces for adsorbate-induced Rh50Pd50 nanoparticle reconstruction via mean-field models of multi-faceted nanoparticles
Authors: Wang Shuqiao , Hensley Alyssa J. R.
Published: December 2023

Adsorbate-induced bimetallic nanoparticle reconstruction via mean-field models.
Facile synthesis of ZnIn2S4@ZnS composites for efficient photocatalytic hydrogen precipitation
Authors: Yuan Xixi , Li Peng , Wang Siyu , Liu Puyu , Zhao Jianwei , Wang Tao , Chang Kun
Published: December 2023

A ZnIn2S4@ZnS catalyst synthesized through a two-step process exhibits better photocatalytic H2 production performance (2.873 mmol g−1 h−1) than ZnIn2S4 (0.229 mmol g−1 h−1) under visible light due to the efficient interfacial electron transfer.
From particles to films: production of Cs2AgBiBr6-based perovskite solar cells and enhancement of cell performance via ionic liquid utilization at the TiO2/perovskite interface
Authors: Öcebe Arzu , Kaya İsmail Cihan
Published: December 2023

BMIMPF6 at the TiO2/perovskite interface resulted in improved crystallinity and increased grain size of the Cs2AgBiBr6 film formed from particles.
Diphosphene with a phosphineborane tether and its rhodium complex
Authors: Tsurusaki Akihiro , Takechi Shingo , Kamikawa Ken
Published: December 2023

A cationic rhodium complex with a bidentate ligand including a diphosphene (PP bond) and a phosphineborane was synthesized and characterized. The reactivity and the catalytic activity of this complex were investigated.
Reduction of nitrite to nitric oxide and generation of reactive chalcogen species by mononuclear Fe(ii) and Zn(ii) complexes of thiolate and selenolate
Authors: Atta Sayan , Mandal Amit , Saha Rahul , Majumdar Amit
Published: December 2023

A comparative study of isostructural Zn(ii) and Fe(ii) compounds for their reactivity with nitrite, transfer of the coordinated thiolate/selenolate and generation and transfer of reactive sulfur/selenium species is presented.
Soluble dietary fibers from solid-state fermentation of wheat bran by the fungus Cordyceps cicadae and their effects on colitis mice
Authors: Wang Hua , Li Menglin , Jiao Furong , Ge Wenxiu , Liu Rui , Zhi Zijian , Wu Tao , Sui Wenjie , Zhang Min
Published: December 2023

The structure of soluble dietary fiber of unfermented wheat bran (UFSDF) and fermented wheat bran of Isaria cicadae Miq. (FSDF) and their effects on mice with colitis were studied. Results showed that FSDF had better anti-inflammatory effect.
Dietary oleacein, a secoiridoid from extra virgin olive oil, prevents collagen-induced arthritis in mice
Authors: Rosillo María Ángeles , Villegas Isabel , Vázquez-Román Victoria , Fernández-Santos José María , Ortega-Vidal Juan , Salido Sofía , González-Rodríguez María Luisa , Alarcón-de-la-Lastra Catalina
Published: December 2023

Nutritional therapy has been considered a promising approach in RA management. OLA might provide a new dietary strategy in immunoinflammatory-mediated diseases.
Impact of high conductivity on particle transport to liquid droplets for liquid marble formation
Authors: Thomas Casey A. , Lobel Benjamin T. , Ireland Peter M. , Wanless Erica J. , Cayre Olivier J. , Webber Grant B.
Published: December 2023

Observing the interplay between material conductivity, cohesion and density for electrostatic liquid marble formation using metal-shell polymer particles.
Advanced and personalized healthcare through integrated wearable sensors (versatile)
Authors: Garg Mayank , Parihar Arpana , Rahman Md. Saifur
Published: December 2023

Applications of integrated wearable sensors for the monitoring of human vital signs and clinically relevant biomarkers.
Real-time visualization of latent fingermarks with level 3 details based on a solid state emissive organic fluorophore using the powder dusting method
Authors: Shabashini Arivalagan , Richard Sathiaraj , Panda Manas K. , Panja Sumit K. , Nandi Ganesh Chandra
Published: December 2023

A water-soluble organic fluorescent probe (Py-Pr-OH) is synthesized and applied for latent fingermarks (LFMs) detection via the powder dusting method. The amphiphilic probe provides LFM imaging with high contrast, and low background interference.
Nanomolar level electrochemical sensing of explosive material sodium azide by a hexagonal boron nitride modified glassy carbon electrode
Authors: J. S. Arya Nair , K. Y. Sandhya
Published: December 2023

A schematic showing the enhancement in the current response for sodium azide in DPV on modification of a GCE with hexagonal boron nitride nanosheets (h-BNNSs).
Anisotropic functionalized platelets: percolation, porosity and network properties
Authors: Karner Carina , Bianchi Emanuela
Published: December 2023

Anisotropic functionalized platelets are able to model the assembly behaviour of molecular systems in two-dimensions thanks to the unique combination of steric and bonding constraints.
Trifunctional electrocatalysts based on a bimetallic nanoalloy and nitrogen-doped carbon with brush-like heterostructure
Authors: Irmawati Yuyun , Tan Davin Adinata , Balqis Falihah , Iskandar Ferry , Sumboja Afriyanti
Published: December 2023

1D–1D heterostructured FeCo-N-doped carbon with brush-like structure has abundant active sites and interconnected conductive networks. The catalyst shows remarkable activities in oxygen reduction, oxygen evolution, and hydrogen evolution reactions.
Reprocessable and chemically recyclable poly(acylhydrazone–imine) covalent adaptable networks with enhanced mechanical strength and creep resistance
Authors: Bao Chunyang , Liu Jie , Yin Yanlong , Liu Jie , Xin Zhirong
Published: December 2023

A room temperature chemically recyclable poly(acylhydrazone–imine) covalent adaptable network with high mechanical strength and creep resistance was constructed by designing synergetic hydrogen bonds and acylhydrazone bonds in a single polymer network.
The quantitative pyrrole protection of l-phenylalanine/l-phenylalaninol in aqueous media and rationally updating the mechanisms of the Clauson-Kaas reaction through DFT study
Authors: Qin Yuan , Cao Pei , Parmar Virinder S. , Liu Yonghong , Gao Chenghai , Liu Kai
Published: December 2023

Quantitative pyrrole protection was achieved through a self-driven pathway by the combinational assistance of solvent water and dissociative weak H+.
Enhanced electrical and magnetic properties of (Co, Yb) co-doped ZnO memristor for neuromorphic computing
Authors: Elboughdiri Noureddine , Iqbal Shahid , Abdullaev Sherzod , Aljohani Mohammed , Safeen Akif , Althubeiti Khaled , Khan Rajwali
Published: December 2023

Functional comparison between a biological synapse and a memristor.
Influence of reaction variables on the surface chemistry of cellulose nanofibers derived from palm oil empty fruit bunches
Authors: Martínez-Ramírez Andrea P. , Rincón-Ortiz Sergio A. , Baldovino-Medrano Víctor G. , Blanco-Tirado Cristian , Combariza Marianny Y.
Published: December 2023

Nanocellulose from palm oil empty fruit bunch (EFB) fibers shows varied surface chemistry influenced by reaction time and primary oxidizing agent. EFB fibers are a valuable raw source to produce sustainable and functional materials.
Dynamic covalent synthesis
Authors: Cougnon Fabien B. L. , Stefankiewicz Artur R. , Ulrich Sébastien
Published: December 2023

Toward organic self-synthesis using encoded synthons and programmed processes: we summarize here the design principles and the recent achievements which illustrate the power of dynamic covalent synthesis for making complex covalent architectures.
Catalytic acceptorless dehydrogenative borylation of styrenes enabled by a molecularly defined manganese complex
Authors: Das Kuhali , Kundu Abhishek , Sarkar Koushik , Adhikari Debashis , Maji Biplab
Published: December 2023

A highly chemo- and regioselective acceptorless dehydrogenative borylation of alkenes is reported employing a molecularly defined Mn(i)-complex as a catalyst with a detailed study of different mechanistic parameters.
Responsive macrocyclic and supramolecular structures powered by platinum
Authors: Soto Miguel A. , MacLachlan Mark J.
Published: December 2023

Platinum's recent evolution spans from responsive complexes to multicomponent assemblies. This Perspective Article explores the role of this metal in designing macrocycles and polymers that reshape or restructure in response to external stimuli.
Electrochemical assembly of isoxazoles via a four-component domino reaction
Authors: Zhao Yuanyuan , Li Xinyue , Homölle Simon L. , Wang Bin , Ackermann Lutz
Published: December 2023

Electrochemical annulation via a four-component domino reaction enabled the assembly of valuable 3,5-di-substituted isoxazole motifs. The exceptional versatility of this approach is highlighted by its capacity for late-stage diversification.
Effects of a Concurrent Working Memory Task on Speech Acoustics in Parkinson's Disease
Authors: Dragicevic Daria A. , Dahl Kimberly L. , Perkins Zoe , Abur Defne , Stepp Cara E.
Published: December 2023

Purpose:

The purpose of this study was to determine the effect of a concurrent working memory task on acoustic measures of speech in individuals with Parkinson's disease (PD).

Method:

Individuals with PD and age- and sex-matched controls performed a speaking task with and without a Stroop-like concurrent working memory task. Cepstral peak prominence, low-to-high spectral energy ratio, fundamental frequency (
f
o
) standard deviation, articulation rate, pause duration, articulatory–acoustic vowel space, relative
f
o
, mean voice onset time (VOT), and VOT variability were calculated for each condition. Mixed-model analyses of variance were performed to determine the effects of group, condition (presence of the concurrent working memory task), and their interaction on the acoustic measures.

Results:

All measures except for VOT variability, mean pause duration, and relative
f
o
offset differed between people with and without PD. Cepstral peak prominence, articulation rate, and relative
f
o
offset differed as a function of condition. However, no measures indicated disparate effects of condition as a function of group.

Conclusion:

Although differentially impactful on limb motor function in PD, here a concurrent working memory task was not found to be differentially disruptive to speech acoustics in PD.

Supplemental Material:

https://doi.org/10.23641/asha.24759648
Reinventing Production: A Case Study on implementing the strategic Innovations in Sustainable Remanufacturing
Authors: Sharma Aman , Bhong Mahesh , Patil Pravin P. , Saraswat Manish , Vinod Kumar S. , Manjunatha  , Shakier Hussein Ghafel
Published: December 2023

The understanding of sustainable remanufacturing as an innovative method has come about as a solution to the ecological difficulties posed by industrial manufacturing. The present study investigates the concept of industrial reinvention via a review of novel practices in the field of remanufacturing. Remanufacturing is an organizational strategy that seeks to increase the operational lifecycle of items, hence reducing the production of waste and maximizing resource use. The remanufacturing process includes a thorough set of phases, involving removal, repair, and enhancement, with the goal of rebuilding already utilized products to their former functionality as well as performance standards. This study examines the current state of procedures, methods, and strategies that contribute to the evolution of the remanufacturing operation in an environmentally friendly form. The abstract underlines the urgent requirement for sustainable solutions in industrial production as a response to problems with the environment. The idea of remanufacturing has been suggested as an effective way to solve these issues. This recent discussion presents an easy-to-understand representation of the remanufacturing process, emphasizing its essential relevance in increasing the lifespan of goods and decreasing the production of waste. The subsequent section of the abstract describes the primary objective of the research, which is the investigation of novel methods in the field of green remanufacturing. The paper aims to investigate multiple methods, tools, and strategies that are currently impacting the emergence of remanufacturing companies.
Harmonizing Molecular Mysteries: A Comprehensive Review of Ultrasonic, Acoustic, and Volumetric Studies in Complex Solutions
Authors: Choudhary Mashahid Hussain , Chakraborty Nabaparna
Published: December 2023

Understanding non-ideal mixtures of liquids and gases in thermodynamics is paramount for processes marked by significant entropy changes. This article delves into the pivotal role of ultrasonic and acoustic studies in unraveling the intricate behaviour of complex solutions. These studies provide profound insights into molecular interactions, structural properties, and thermodynamic characteristics. Notably, they find widespread applications in diverse industries, including pharmaceuticals, food processing, clinical analysis, and petroleum engineering. This qualitative exploration sheds light on the underlying molecular forces, particularly the influence of hydrogen bonding. Recent advancements in the field, such as the investigation of ionic liquids combined with molecular solvents and the analysis of volumetric and acoustic properties in binary mixtures, underscore their practical importance. This overview offers a comprehensive understanding of how ultrasonic and acoustic studies drive progress in multiple sectors. They play a pivotal role in enhancing the stability of drug formulations, optimizing food-grade mixtures, and ensuring strict compliance with industry standards in the petrochemical sector.
An alarming picture of larval fish assemblages entrained into the cooling system of the Kozienice Power Plant (Poland) revealed by DNA metabarcoding
Authors: Nowak Michał , Mikołajczyk Tomasz , Mikołajczyk Łukasz , Janik-Superson Katarzyna , Jeziorski Sergiusz , Krawczyk Dawid , Skowronek Dariusz , Wawręty Robert
Published: December 2023

The annual entrainment of early life history stages of fishes (ELH) into the cooling system of the largest power plant in the Vistula River basin was assessed using passive capture techniques and DNA metabarcoding. Hydrological and thermal conditions during the 2022 breeding season were also analyzed. A total of 5,011 ELH individuals identified to four families and 23 species were recorded. ELH densities upstream of the power plant were an order of magnitude higher than they were downstream. Along with the phenology of occurrence and species composition of drift, this indicated very high (probably close to 100%) ELH mortality during passage through the cooling system. Taking into account low water discharge at constantly high water intake during the season, the absolute estimate of ELH individuals entrained into the cooling system was > 103 × 106. The power plant entrains a notable proportion of one-quarter to one-half of the total ELH drifting by, especially during low-flow periods. Together with the very high abundance of two invasive Ponto-Caspian gobies, the magnitude of the entrainment of ELH into the Kozienice Power Plant presents a truly alarming picture.
Einbindung und Umgang von Notfallsanitätern bei ungeplanten
außerklinischen Geburten: Ein Online-Survey
Authors: Gebhard Josina , Graf Joachim , Abele Harald , Pauluschke-Fröhlich Jan
Published: December 2023

Einleitung Ungeplante außerklinische Geburten sind im
Rettungsdienst sehr selten und es gibt Hinweise darauf, dass sich
Notfallsanitäter mit diesem Einsatzbild nicht wohl fühlen. Es
zeigt sich gleichzeitig eine erhöhte Morbidität und
Mortalität für sowohl die Mutter als auch das Neugeborene. Die
Ziele der vorliegenden Querschnittstudie sind, Unsicherheiten von
Notfallsanitätern in Zusammenhang mit ungeplanten
außerklinischen Geburten zu identifizieren, die Gründe
hierfür zu analysieren und mögliche
Unterstützungsmaßnahmen abzuleiten.

Material und Methoden Es handelt sich bei dieser Studie um eine
quantitative Querschnittsstudie, die den Umgang von Notfallsanitätern
mit ungeplanten außerklinischen Geburten anhand eines selbst
entwickelten Fragebogens untersucht. An der Online-Umfrage nahmen 65
Teilnehmer*innen im Zeitraum vom 06.04.2022 bis 30.04.2022 teil.
Für die statistische Datenanalyse wurde SPSS verwendet. Die zentrale
Tendenz verschiedener Einflussgrößen wurde dabei mit Hilfe des
Mann- Whitney-U-Tests untersucht, das Signifikanzniveau ist α
>0,05.

Ergebnisse Im Durschnitt bewerteten die Teilnehmenden die Vorbereitung
Median (IQR): 2,0 (1,0) und die Sicherheit 3,0 (1,0) mit den
durchzuführenden Maßnahmen, sowie das Wissen über
ungeplante außerklinische Geburten 2,0 (1,0) mittelmäßig
gut. Die teilnehmenden Notfallsanitäter*innen hatten vor allem
Schwierigkeiten mit der Dokumentation des Geburtsverlaufes 3,0 (1,0). Es
herrscht ein großer Respekt vor der außerklinischen
Geburtsbegleitung 1,0 (1,0). Es scheint, dass die Teilnahme an einer
interdisziplinären Simulation einen positiven Einfluss auf den Umgang,
die Vorbereitung und die Sicherheit bei den durchzuführenden
Maßnahmen nimmt (p=0,016).

Schlussfolgerung Es konnten Unsicherheiten sowie mögliche
Gründe für diese identifiziert sowie mögliche
Verbesserungsvorschläge für die
Notfallsanitäter*innen bei außerklinischen
Geburtsbetreuung erarbeitet werden. Dabei stellen zum Beispiel spezifische
Geburtsprotokolle und die Teilnahme an einer Simulation eine gute
Möglichkeit zur Unterstützung dar.
4D-Elektromagnetische Navigationsbronchoskopie zur Diagnostik peripherer Rundherde
Authors: Bitter Thomas , Seeba Tielko , Schroeder-Richter Jörn , Fröhlich Michael , Duaer Wissam , Abidi Wael , Kindermann Markus Peter
Published: December 2023

Hintergrund Die Abklärung peripherer Rundherde stellt eine besondere Herausforderung in der interventionellen Bronchologie dar, weswegen zunehmend Navigationssysteme wie die elektromagnetische Navigation (ENB) verwendet werden. Die 4D-ENB stellt eine innovative Weiterentwicklung der ENB dar. Durch In- und Exspirations-CT-Aufnahmen soll die atemabhängige CT-to-body-Divergenz überwunden und damit die Treffsicherheit peripherer Herde erhöht werden. Ziel dieser Arbeit ist eine Vorstellung des 4D-ENB-Verfahrens und die Präsentation erster klinischer Daten und Erfahrungen.

Methode Wir beschreiben retrospektiv die Resultate der ersten 9 konsekutiven Patienten mit PPN, die am Klinikum Braunschweig mittels 4D-ENB als unimodale Diagnostiktechnik untersucht wurden.

Resultate Von den ersten 9 mittels 4D-ENB untersuchten PPNs war eine erfolgreiche Navigation und Punktion des Herdes bei 8 Patienten (89%) möglich. Eine diagnostisch wegweisende Biopsie konnte bei 6 von 9 Patienten (67%) erreicht werden. Signifikante Komplikationen ergaben sich bei den Untersuchungen nicht.

Schlussfolgerung Unsere ersten Daten lassen die 4D-ENB als eine vielversprechende neue Alternative zur Abklärung von PPNs erscheinen. Um die diagnostische Ausbeute weiter zu verbessern, sollte die 4D-ENB aufgrund der fehlenden Echtzeitvisualisierung bevorzugt kombiniert mit radialem endobronchialem Ultraschall und/oder Fluoroskopie im Rahmen multimodaler Diagnostikkonzepte eingesetzt werden.
Einfluss von fetomaternalen Risikofaktoren auf die Mortalität
und Morbidität von Extremfrühgeborenen
Authors: Winkler Paula , Cloppenburg Eva , Heep Axel , Malik Eduard , Lüdders Dörte , Lange Matthias
Published: December 2023

Einleitung Die Behandlung von Schwangeren bei drohender Frühgeburt
stellt eine interdisziplinäre Herausforderung dar. An der Grenze der
Lebensfähigkeit spielen fetomaternale Risikofaktoren (RF) eine
entscheidende Rolle in der individuellen Beratung und den
Therapieansätzen.

Methoden An einem Level-1-Perinatalzentrum (PNZ) wurden in einer
retrospektiven Beobachtungsstudie zwischen 2017 und 2020 alle
Frühgeborenen (FG) mit einem Gestationsalter (GA) zwischen
230/7 und 246/7 Schwangerschaftswochen
(SSW) erfasst, die postnatal mit einem kurativen Therapieansatz behandelt
wurden. Eingeteilt in zwei Gruppen (230/7
–236/7 und
240/7–246/7 SSW) wurden die FG unter
Berücksichtigung der fetomaternalen RF hinsichtlich der
Mortalität und Morbidität verglichen. Analysiert wurden 13
definierte RF und deren prognostische Relevanz für das
Überleben.

Ergebnisse Es wurden 41 Mütter mit 48 FG eingeschlossen.
Ausgeschlossen wurden 9 FG, die primär palliativ behandelt wurden. Die
Überlebensraten der Gruppen (n=21, n=27) zeigten keine
signifikanten Unterschiede (66,7% versus 74,1%,
p=0,750). Bei steigender Anzahl an RF wurde eine signifikant
höhere Mortalität beobachtet (p=0,004), schwerwiegend
waren hypertensive Schwangerschaftserkrankungen und ein vorzeitiger
Blasensprung. Die Morbiditätsdaten zeigten keine signifikanten
Unterschiede.

Schlussfolgerung Die vorliegenden Daten bezüglich der
Mortalität entsprachen den nationalen Daten. Die Morbidität
dieser FG konnte erfasst werden. Durch die Berücksichtigung der RF
lässt sich die Vorhersage der Überlebenswahrscheinlichkeit
präzisieren.
Reha nach Kreuzband-OP – Die Phasen in der
Physiotherapie
Authors: Harms Oliver
Published: December 2023

Das Ziel jeder postoperativen Behandlung bei Gelenkoperationen ist die
Verminderung von Schmerz, die Unterstützung und Verkürzung der
Heilungszeit, der Aufbau von Muskelmasse sowie die Erhöhung der
Gelenkstabilität und Gelenkbeweglichkeit. Zusätzlich sollen
Propriozeption, Balance und Koordination neu ausgebildet werden. Alle
Maßnahmen zusammen fördern eine schnelle Rehabilitation,
verhindern degenerative Gelenkserkrankungen und helfen Komplikationen wie
sekundäre Tendinopathien oder Verklebungen von Gewebe zu erkennen. Wir
zeigen, was dabei wichtig ist, und welche Maßnahmen in den einzelnen
postoperativen Phasen angezeigt und sinnvoll sind.
Building a core rule-based decision tree to explain the causes of insolvency in small and medium-sized enterprises more easily
Authors: Lee Sanghoon , Choi Keunho , Yoo Donghee
Published: December 2023

This study proposes a harmonic average of support and confidence method (HSC), which is a new way to select important rules from the many rules in the decision tree and thereby build a core rule-based decision tree (CorDT) that more easily explains the insolvency factors related to small and medium-sized enterprises (SMEs) using the HSC. To this end, an insolvency prediction model for SMEs was developed using a decision tree algorithm and technological feasibility assessment data as non-financial datasets. We divided these datasets into three types, a general type, a technology development type and a toll processing type applying characteristics of SMEs. We also applied a cost-sensitive approach and several data balancing techniques to construct the same proportion of healthy and insolvent company samples in the datasets. As a result, the insolvency prediction model applied using the synthetic minority over-sampling technique (SMOTE), an over-sampling technique, showed the highest performance with an average hit ratio of 77.6%. Next, we selected important rules by applying HSC to the decision trees with the highest performance and built CorDTs for three types of SMEs using the selected rules. Finally, using the developed CorDTs, we explained the causes of insolvency by type of SME and presented insolvency prevention strategies customized to the three types of SMEs.
The symbiotic relationship and collaboration between commercial banks and fintechs in Turkey
Authors: Nabiyev Abdul Baghi , Ovenc Gokhan
Published: December 2023

Fintech startups have forced traditional banks to change their business models using new IT-enabled technologies. These startups have become a potential threat to the financial industry in recent years. Therefore, traditional banks form strategic alliances with fintech startups to gain a competitive advantage and improve their technological infrastructure. This study examines which form of collaboration banks prefer with fintech firms and in which segment these firms operate. Using a hand-collected dataset, the probit model is applied to analyze 430 bank-fintech alliances in Turkey in 2021. The results indicate that in Turkey, large banks tend to collaborate with fintech startups in a product-related manner rather than investing in them. Large banks prefer to form partnerships with non-payment fintech startups rather than payment service fintechs. Lastly, young fintech startups mainly operate in payment services, and those established in Istanbul are likely to form strategic partnerships with commercial banks in this area.
Quantifying the impact of uninformative features on the performance of supervised classification and dimensionality reduction algorithms
Authors: Lei Weihua , Zanchettin Cleber , Ho Zoey E. , Nunes Amaral Luís A.
Published: December 2023

Machine learning approaches have become critical tools in data mining and knowledge discovery, especially when attempting to uncover relationships in high-dimensional data. However, researchers have noticed that a large fraction of features in high-dimensional datasets are commonly uninformative (too noisy or irrelevant). Because optimal feature selection is an NP-hard task, it is essential to understand how uninformative features impact the performance of machine learning algorithms. Here, we conduct systematic experiments on algorithms from a wide range of taxonomy families using synthetic datasets with different numbers of uninformative features and different numbers of patterns to be learned. Upon visual inspection, we classify these algorithms into four groups with varying robustness against uninformative features. For the algorithms in three of the groups, we find that when the number of uninformative features exceeds the number of data instances per pattern to be learned, the algorithms fail to learn the patterns. Finally, we investigate whether increasing the distinguishability of patterns or adding training instances can mitigate the effect of uninformative features. Surprisingly, we find that uninformative features still cause algorithms to suffer big losses in performance, even when patterns should be easily distinguishable. Analyses of real-world data show that our conclusions hold beyond the synthetic datasets we study systematically.
Data-driven design for enhanced efficiency of Sn-based perovskite solar cells using machine learning
Authors: Rumman Abdul Hamid , Sahriar Miah Abdullah , Islam Md Tohidul , Shorowordi Kazi Md , Carbonara Joaquin , Broderick Scott , Ahmed Saquib
Published: December 2023

In this study, a novel three-step learning-based machine learning (ML) methodology is developed utilizing 26 000 experimental records from The Perovskite Database Project. A comprehensive set of 29 features encompassing both categorical and numerical data was utilized to train various ML models for various solar cell performance metrics, including open-circuit voltage (VOC), short-circuit current (JSC), fill factor (FF), and power conversion efficiency (PCE). The model accuracy was assessed using four key metrics: mean absolute error, mean square error, root mean square error, and R2 score. Among the constructed models, random forest (RF) emerged as the standout performer, boasting an R2 score of 0.70 for PCE. This RF model was then used for prediction on the large, optimized design pool of Sn-based perovskite data with intent to probe a viable non-toxic substitute to the standard Pb-based absorber. A three-step algorithm was tailored, which led to the discovery of a new set of feature combinations, showcasing a PCE improvement over the existing peak performance of Sn-based devices. The key aspects identified were device architecture, dimensionality, and deposition procedures for essential layers, including the electron transport layer, the hole transport layer, the perovskite absorber layer, and the back-contact. Through consideration of these features, an impressive increase in PCE was achieved. There was a 28.35% increase in PCE from 12.24% to 15.71% for architecture optimization and a 24.6% increase in PCE from 12.24% to 15.25% for deposition method optimization. This study additionally addresses the effective implementation of target encoding applied to a diverse set of categorical feature labels. The data-driven methodology proposed in this study allows scientists to efficiently identify an optimal architecture and deposition parameters for non-toxic Sn-based perovskite materials with a much higher anticipated device PCE compared to traditional trial-and-error analyses. Further exploration and exploitation of the current investigation is expected to lead to successful and sustainable development of highly efficient Sn-based perovskite solar cells.
Two centuries of biodiversity discovery and loss in Singapore
Authors: Chisholm Ryan A. , Kristensen Nadiah P. , Rheindt Frank E. , Chong Kwek Yan , Ascher John S. , Lim Kelvin K. P. , Ng Peter K. L. , Yeo Darren C. J. , Meier Rudolf , Tan Heok Hui , Giam Xingli , Yeoh Yi Shuen , Seah Wei Wei , Berman Laura M. , Tan Hui Zhen , Sadanandan Keren R. , Theng Meryl , Jusoh Wan F. A. , Jain Anuj , Huertas Blanca , Tan David J. X. , Ng Alicia C. R. , Teo Aloysius , Yiwen Zeng , Cho Tricia J. Y. , Sin Y. C. Keita
Published: December 2023

There is an urgent need for reliable data on the impacts of deforestation on tropical biodiversity. The city-state of Singapore has one of the most detailed biodiversity records in the tropics, dating back to the turn of the 19th century. In 1819, Singapore was almost entirely covered in primary forest, but this has since been largely cleared. We compiled more than 200 y of records for 10 major taxonomic groups in Singapore (>50,000 individual records; >3,000 species), and we estimated extinction rates using recently developed and novel statistical models that account for “dark extinctions,” i.e., extinctions of undiscovered species. The estimated overall extinction rate was 37% (95% CI [31 to 42%]). Extrapolating our Singapore observations to a future business-as-usual deforestation scenario for Southeast Asia suggests that 18% (95% CI [16 to 22%]) of species will be lost regionally by 2100. Our extinction estimates for Singapore and Southeast Asia are a factor of two lower than previous estimates that also attempted to account for dark extinctions. However, we caution that particular groups such as large mammals, forest-dependent birds, orchids, and butterflies are disproportionately vulnerable.
Biomimetic noncationic lipid nanoparticles for mRNA delivery
Authors: Wang Changrong , Zhao Caiyan , Wang Weipeng , Liu Xiaoqing , Deng Hongzhang
Published: December 2023

Although the tremendous progress has been made for mRNA delivery based on classical cationic carriers, the excess cationic charge density of lipids was necessary to compress mRNA through electrostatic interaction, and with it comes inevitably adverse events including the highly inflammatory and cytotoxic effects. How to develop the disruptive technologies to overcome cationic nature of lipids remains a major challenge for safe and efficient mRNA delivery. Here, we prepared noncationic thiourea lipids nanoparticles (NC-TNP) to compress mRNA by strong hydrogen bonds interaction between thiourea groups of NC-TNP and the phosphate groups of mRNA, abandoning the hidebound and traditional electrostatic force to construct mRNA-cationic lipids formulation. NC-TNP was a delivery system for mRNA with simple, convenient, and repeatable preparation technology and showed negligible inflammatory and cytotoxicity side effects. Furthermore, we found that NC-TNP could escape the recycling pathway to inhibit the egress of internalized nanoparticles from the intracellular compartment to the extracellular milieu which was a common fact in mRNA-LNP (lipid nanoparticles) formulation. Therefore, NC-TNP-encapsulated mRNA showed higher gene transfection efficiency in vitro and in vivo than mRNA-LNP formulation. Unexpectedly, NC-TNP showed spleen targeting delivery ability with higher accumulation ratio (spleen/liver), compared with traditional LNP. Spleen-targeting NC-TNP with mRNA exhibited high mRNA-encoded antigen expression in spleen and elicited robust immune responses. Overall, our work establishes a proof of concept for the construction of a noncationic system for mRNA delivery with good inflammatory safety profiles, high gene transfection efficiency, and spleen-targeting delivery to induce permanent and robust humoral and cell-mediated immunity for disease treatments.
Promoting the efficiency and selectivity of NO
3
−
−to−NH
3
reduction on Cu−O−Ti active sites via preferential glycol oxidation with holes
Authors: Chen Ruimin , Shen Shujie , Wang Kaiwen , Wang Jielin , Yang Weiping , Li Xin , Li Jieyuan , Dong Fan
Published: December 2023

The combined reductive and oxidative reaction is the essence of a solar-driven photoredox system. Unfortunately, most of these efforts focus on the specific half-reactions, and the key roles of complete photoredox reactions have been overlooked. Taking the nitrate reduction reaction (NO
3
−
RR) as a typical multiple-electrons involved process, the selective reduction of the NO
3
−
into ammonia (NH
3
) synthesis with high efficiency is still a grand challenge. Herein, a rational oxidative half-reaction is tailored to achieve the selective conversion of NO
3
−
to NH
3
on Cu−O−Ti active sites. Through the coupled NO
3
−
RR with glycol oxidation reaction system, a superior NH
3
photosynthesis rate of 16.04 ± 0.40 mmol g
cat
−1
h
−1
with NO
3
−
conversion ratio of 100% and almost 100% of NH
3
selectivity is reached on Cu−O−Ti bimetallic oxide cluster−anchored TiO
2
nanosheets (CuO
x
@TNS) catalyst. A combination of comprehensive in situ characterizations and theoretical calculations reveals the molecular mechanism of the synergistic interaction between NO
3
−
RR and glycol oxidation pair on CuOx@TNS. The introduction of glycol accelerates the h
+
consumption for the formation of alkoxy (•R) radicals to avoid the production of •OH radicals. The construction of Cu−O−Ti sites facilitates the preferential oxidation of glycol with h
+
and enhances the production of e
−
to participate in NO
3
−
RR. The efficiency and selectivity of NO
3
−
−to−NH
3
synthesis are thus highly promoted on Cu−O−Ti active sites with the accelerated glycol oxidative half-reaction. This work upgrades the conventional half photocatalysis into a complete photoredox system, demonstrating the tremendous potential for the precise regulation of reaction pathway and product selectivity.