bluuebunny/crossref_metadata_2025_split huggingface dataset:
BIM‐Modellierung von Bestandsgebäuden – eine Studie zu Aufwand und Effizienz
Authors: Marx Peter , Teferle Félicia Norma Rebecca , Thewes Andreas , Schäfer Markus 
Published: July 2024

AbstractIm vom Bundesministerium für Bildung und Forschung geförderten Projekt „FHprofUnt 2018: BIM Bauen im Bestand (BIM‐BiB)“ wurde der Campus der Hochschule Trier mittels terrestrischem Laserscanner vermessen und die gewonnenen Daten in BIM‐Modelle der Gebäude des Campus überführt. Diese Studie untersucht die Effizienz von Bestandsvermessungen durch 3D‐Scanner, der Punktwolkenerstellung und ‐nachbearbeitung sowie der BIM‐Modellierung von Bestandsgebäuden anhand der gewonnenen Aufwandswerte. Die Ergebnisse zeigen, dass die Anwendung terrestrischer Laserscanner für Bestandsvermessungen eine effiziente Methode ist, Bearbeitung und Erstellung hochwertiger Punktwolken jedoch noch sehr zeitintensiv sind und die eigentliche BIM‐Modellierung die beiden erstgenannten Arbeitsbereiche im Aufwand stark übertrifft. Zur Erläuterung der vorgestellten Ergebnisse wird auf den aktuellen Stand der Technik und die projektspezifischen Probleme eingegangen. Die gewonnenen Daten und ihre Auswertung decken Schwachstellen in der Effizienz der heute zur Verfügung stehenden Methoden auf und beleuchten Forschungsmöglichkeiten, um den Prozess der Modellierung von Bestandsgebäuden wirtschaftlicher zu gestalten.
A truncation mutant of adenomatous polyposis coli impairs apical cell extrusion through elevated epithelial tissue tension
Authors: Gan Wan J. , Giri Rabina , Begun Jakob , Abud Helen E. , Hardeman Edna C. , Gunning Peter W. , Yap Alpha S. , Noordstra Ivar 
Published: July 2024

AbstractTissue tension encompasses the mechanical forces exerted on solid tissues within animal bodies, originating from various sources such as cellular contractility, interactions with neighboring cells and the extracellular matrix. Emerging evidence indicates that an imbalance in such forces can influence structural organization, homeostasis, and potentially contribute to disease. For instance, heightened tissue tension can impede apical cell extrusion, leading to the retention of apoptotic or transformed cells. In this study, we investigate the potential role of adenomatous polyposis coli (APC) in modulating tissue tension. Our findings reveal that expression of an APC truncation mutant elevates epithelial tension via the RhoA/ROCK pathway. This elevation induces morphological alterations and hampers apoptotic cell extrusion in cultured epithelial cells and organoids, both of which could be mitigated by pharmacologically restoring the tissue tension. This raises the possibility that APC mutations may exert pathogenetic effects by altering tissue mechanics.
Robust and smart: Inference on phenotypic plasticity of Coffea canephora reveals adaptation to alternative environments
Authors: Ferrão Maria Amélia G. , Riva‐Souza Elaine M. , Azevedo Camila , Volpi Paulo S. , Fonseca Aymbiré F. A. , Ferrão Romario G. , Montagnon Christopher , Ferrão Luis Felipe V. 
Published: July 2024

AbstractCoffee is an important crop with economic and social importance in several countries. With a daily consumption estimated at 2.2 billion cups, its sustainability is facing critical challenges given the projected climate changes. Coffea arabica, which represents ∼60% of the global market coffee is a delicate crop, quite susceptible to diseases and biotic stresses. Developing climate‐resilience cultivars is necessary, and it includes coffee plants adapted to new farming conditions that can meet the demand for biotic and abiotic tolerance and quality. In this context, Coffea canephora emerges as a potential candidate if the crop combines plasticity and cupping quality. Plant plasticity refers to adjusted phenotypic performance when grown in different environments, a fact that may help mitigate the detrimental effect of climate changes. In this study, using a multiple environment trial, we combined genomic and genotype‐by‐environment analyses to answer the following main question: How the climate effects may affect the phenotypic plasticity in C. canephora? Our contributions in this paper are fourfold: (i) we draw attention to the cupping quality and yield performance of C. canephora cultivars when evaluated in high‐altitude and cold weather, (ii) we compared C. arabica and C. canephora phenotypic plasticity and highlight genotypes with broad and specific adaptation to certain environmental conditions, and finally, (iii) using stochastic simulation, we emphasize the potential of molecular breeding in the long term in coffee. Altogether, we present an emerging view on how C. canephora could be a valid alternative for climate‐smart cultivars in a projected scenario of altered climatic conditions.
Gene pyramiding for achieving enhanced disease and insect multiple resistance in Coffea arabica
Authors: Feitosa Francielle de Matos , Santos Iara Gonçalves dos , Pereira Antonio Alves , de Oliveira Antonio Carlos Baião , Caixeta Eveline Teixeira 
Published: July 2024

AbstractDeveloping a new coffee cultivar can take up to 25 years using traditional approaches. The implementation of molecular tools into the coffee breeding pipeline can speed up the development of high‐yielding varieties with multiple resistance to pests and diseases. This study aimed to verify the presence of gene pyramiding for resistance to coffee berry disease (CBD) and coffee leaf rust and access the breeding potential of a breeding population of coffee (Coffea arabica L.) that presents partial phenotypic resistance to coffee leaf miner. A progeny of 128 individuals was evaluated in 2019 during the coffee maturation stage for 11 agronomic traits. The individuals were genotyped for four loci related to rust and CBD resistance. Gene pyramiding was verified based on the presence of markers linked with the resistance alleles. Genetic parameters were estimated, and a selection index was used to rank the individuals based on the phenotypic evaluation. Gene pyramiding for rust and CBD was detected in ∼82% of the individuals. Moreover, the phenotypic evaluation of rust indicated high levels of resistance, confirmed by the presence of the resistance alleles. Ninety‐five percent of the 38 top‐ranked individuals presented resistance alleles and could be used in an interpopulation recurrent selection scheme with marker‐assisted selection. The studied coffee population has the potential to be used in coffee breeding programs since it presents vigorous individuals with low levels of coffee leaf miner incidence (CLMI) and gene pyramiding for CBD and rust resistance, the main pest and diseases of this crop.
The effect of incidental ethanol exposures on the formation of blood phosphatidylethanol
Authors: Reisfield Gary M. , Teitelbaum Scott A. , Jones Joseph T. , Lewis Ben 
Published: July 2024

AbstractBlood phosphatidylethanol (PEth), a metabolite of ethanol, is emerging as a direct biomarker of choice for characterizing ethanol consumption in clinical, research, and forensic contexts. An accumulating body of evidence, and a recent international consensus conference, supports a cutoff of 20 μg/L of PEth (16:0/18:1) to distinguish abstinence from beverage ethanol consumption. There is a dearth of research, however, on whether exposures to nonbeverage ethanol sources are sufficient to produce PEth concentrations that exceed this cutoff. To explore this possibility, we recruited 30 participants, who indicated past‐90‐day abstinence from beverage alcohol, to characterize their past‐30‐day nonbeverage ethanol exposures (including source, frequency, and intensity of exposures) and to undergo PEth testing. Two of the 30 participants (6.7%) produced PEth concentrations ≥20 μg/L. One of these participants (PEth = 26 μg/L) reported multiple ethanol exposure sources, including near‐daily intensive exposures to ethanol vapor. The other participant (PEth = 49 μg/L) reported only once‐daily use of an ethanol‐containing mouthwash; the veracity of his abstinence claim is refuted. The results of this study support a rebuttable presumption that PEth ≥20 μg/L is indicative of beverage ethanol consumption. They suggest, however, that intensive, incidental alcohol exposures have the potential, under unusual circumstances, to result in PEth concentrations that modestly exceed this threshold.
Understanding Europium and Terbium Speciation and Ion Pairing in Carbonate Complexes Using Advanced Spectroscopy Techniques
Authors: Hege Nicole , Poore Andrew T , Galley Shane S , Reinhart Benjamin J , Tian Shiliang , Jackson Jessica A , Shafer Jenifer 
Published: July 2024

Lanthanide (Ln) elements are critical materials that are typically extracted/mined together. Their separation by solvent extraction from acidic media is well known; however, there are few studies in basic media with carbonate anions. We investigated the complexation of Eu(III) and Tb(III) carbonates as solids and solutions in alkaline K2CO3, wherein we sought to access a Tb(IV) carbonate complex through ozonolysis. L3‐edge XANES of Eu and Tb carbonate solids, colorless solutions, and a red‐hued Tb solution (obtained by ozonolysis) all showed Ln(III) cations. The absence of evidence for a Tb(IV) complex was confirmed through XAS and EPR analyses, despite the solution exhibiting a deep red color. For solids and solutions, EXAFS results indicate molecular Ln(III)‐carbonato anions. In terms of the Eu(III) carbonate coordination number, the coordination does not change upon dissolution of the solid sample. Furthermore, EXAFS for the solutions revealed evidence for the association of potassium cations with the Ln(III)‐carbonato anions. This direct observation of contact ion pairing by EXAFS at room temperature is rare. The insights into Ln(III) carbonate complexation and solution speciation afforded by XANES‐EXAFS, FT‐IR, and EPR provides perspectives that serve as benchmarks for future computational and experimental efforts focused on caustic‐side solvent extraction of Ln(III) ions.
A targeting nanoplatform for chemo‐photothermal synergistic therapy of small‐cell lung cancer
Authors: Yin Moli , Liu Lei , Yan Yu , Wang Huiyan , Li Wenliang , Dong Yuan , Kong Guangyao 
Published: July 2024

AbstractThe precise delivery of drugs to tumor sites and the thermoresistance of tumors remain major challenges in photothermal therapy (PTT). Somatostatin receptor 2 (SSTR2) is proposed as an ideal target for the precise treatment of SCLC. We developed a targeting nano‐drug delivery system comprising anti‐SSTR2 monoclonal antibody (MAb) surface‐modified nanoparticles co‐encapsulating Cypate and gambogic acid (GA). The formed SGCPNs demonstrated excellent monodispersity, physiological stability, preferable biocompatibility, and resultant efficient photothermal conversion efficacy. SGCPNs were quickly internalized by SSTR2‐overexpressing SCLC cells, triggering the release of GA under acidic and near‐infrared (NIR) laser irradiation environments, leading to their escape from lysosomes to the cytosol and then diffusion into the nucleus. SGCPNs can not only decrease the cell survival rate but also inhibit the activity of heat shock protein 90 (HSP90). SGCPNs can be precisely delivered to xenograft tumors of SSTR2‐positive SCLC in vivo. Upon NIR laser irradiation, therapy of SGCPNs showed significant tumor regression. In conclusion, SGCPNs provide a new chemo‐photothermal synergistic treatment strategy for targeting SCLC.
Trends in breast cancer incidence by estrogen receptor status in the United States, 2004–2020
Authors: Jiang Chenxi , Giaquinto Angela N. , Jemal Ahmedin , Sung Hyuna 
Published: July 2024

AbstractDivergent trends of breast cancer incidence by subtype have been reported in the United States and elsewhere; however, it remains unknown whether this trend has continued until the era of the COVID‐19 pandemic. Using high‐quality population‐based cancer registry data, representing 83% of the US population, this study examined breast cancer incidence rates by estrogen receptor (ER) status in women aged 20–84 years from 2004 to 2020. The incidence rate of ER‐positive cancer increased by 1.75% per year from 2004 to 2009 (95% confidence interval [CI] = 1.26%–3.15%) and has slowed to a 0.87% annual increase (95% CI = 0.41%–1.03%) from 2009 to 2019, followed by a 10.2% reduction from 2019 to 2020. Trends were generally similar across race and ethnicity, although young women (20–49 years), Asian or Pacific Islander, and Hispanic women experienced steady increases until 2019. The incidence rate of ER‐negative cancer decreased by 3.13% annually (95% CI = −4.2% to −2.55%) from 2004 to 2012, and the decrease stabilized from 2012 to 2019 (annual percent change: 0.55%; 95% CI = −1.30% to 0.92%), followed by a 6.0% reduction from 2019 to 2020, with trends generally consistent by age and across racial and ethnic groups. The stabilization of the steep decline in ER‐negative cancer suggests a departure from the encouraging trajectories projected in earlier studies. Coupled with the deceleration in the rise of ER‐positive cancer, the latest trend signals a potential stabilization in the previous rise of the proportional burden of ER‐positive cancer. Understanding the impact of the pandemic on each subtype of breast cancer individually may provide a more comprehensive insight into its long‐term sequelae on survival and mortality.
Malnutrition in hospitalized adults in the United States, 2016–2019
Authors: Bhasin Ajay , Huang Lynn , Shieh Meng‐Shoiu , Pekow Penelope , Lindenauer Peter K. , Lagu Tara 
Published: July 2024

AbstractBackgroundMalnutrition in hospitalized patients is associated increased length of stay, cost, readmission, and death. No recent studies have examined trends in prevalence or outcomes of hospitalized patients with a diagnosis of malnutrition.ObjectivesTo study the prevalence of malnutrition diagnostic codes and associated hospital outcomes in the United States between 2016 and 2019.MethodsWe conducted a retrospective trends study to identify use of malnutrition codes in hospitalizations in the National Inpatient Sample between 2016 and 2019. We used direct standardization by logistic regression to adjust outcomes of percutaneous gastrostomy tube placement, mechanical ventilation, and death for age, Gagne comorbidity score, and sex. We then used linear regression to test for trends over time by malnutrition type.ResultsAcross all hospitalizations, codes for diagnoses of nonsevere malnutrition and severe malnutrition were present in 3.7% and 4.1% of hospitalizations, respectively. Codes for any malnutrition increased over time, from 6.6% in 2016 to 8.6% in 2018 (p = .03). Codes for severe malnutrition increased from 3.3% to 4.7% (p = .01). Among hospitalizations with coded severe malnutrition diagnoses, there was a statistically significant decrease in adjusted rate of death over time (−0.54% per year, p = .03) which was not seen in hospitalizations without coded malnutrition diagnoses.ConclusionsUse of malnutrition diagnosis codes increased significantly from 2016 to 2019. During this time, mortality among hospitalizations with a diagnosis code for severe malnutrition decreased. Though the increased prevalence of malnutrition codes may represent a change in the clinical characteristics of hospitalized patients, the decline in mortality suggests some of the increase may be due to lower threshold for coding and assignment of the diagnosis to less ill patients.
Programme science in action: lessons from an observational study of HIV prevention programming for key populations in Lusaka, Zambia
Authors: Sikazwe Izukanji , Musheke Maurice , Chiyenu Kanema , Ngosa Benard , Pry Jake M. , Mulubwa Chama , Zimba Martin , Sakala Martin , Sakala Mphatso , Somwe Paul , Nyirenda Goodwin , Savory Theodora , Bolton‐Moore Carolyn , Herce Michael E. 
Published: July 2024

AbstractIntroductionOptimizing uptake of pre‐exposure prophylaxis (PrEP) for individuals at risk of HIV acquisition has been challenging despite clear scientific evidence and normative guidelines, particularly for key populations (KPs) such as men who have sex with men (MSM), female sex workers (FSWs), transgender (TG) people and persons who inject drugs (PWID). Applying an iterative Programme Science cycle, building on the effective programme coverage framework, we describe the approach used by the Centre for Infectious Disease Research in Zambia (CIDRZ) to scale up PrEP delivery and address inequities in PrEP access for KP in Lusaka, Zambia.MethodsIn 2019, CIDRZ partnered with 10 local KP civil society organizations (CSOs) and the Ministry of Health (MOH) to offer HIV services within KP‐designated community safe spaces. KP CSO partners led KP mobilization, managed safe spaces and delivered peer support; MOH organized clinicians and clinical commodities; and CIDRZ provided technical oversight. In December 2021, we introduced a community‐based intervention focused on PrEP delivery in venues where KP socialize. We collected routine programme data from September 2019 to June 2023 using programme‐specific tools and the national electronic health record. We estimated the before‐after effects of our intervention on PrEP uptake, continuation and equity for KP using descriptive statistics and interrupted time series regression, and used mixed‐effects regression to estimate marginal probabilities of PrEP continuity.ResultsMost (25,658) of the 38,307 (67.0%) Key Population Investment Fund beneficiaries were reached with HIV prevention services at community‐based venues. In total, 23,527 (61.4%) received HIV testing services, with 15,508 (65.9%) testing HIV negative and found PrEP eligible, and 15,241 (98.3%) initiating PrEP. Across all programme quarters and KP types, PrEP uptake was >90%. After introducing venue‐based PrEP delivery, PrEP uptake (98.7% after vs. 96.5% before, p < 0.001) and the number of initiations (p = 0.014) increased significantly. The proportion of KP with ≥1 PrEP continuation visit within 6 months of initiation was unchanged post‐intervention (46.7%, 95% confidence interval [CI]: 45.7%, 47.6%) versus pre‐intervention (47.2%, 95% CI: 45.4%, 49.1%).ConclusionsApplying Programme Science principles, we demonstrate how decentralizing HIV prevention services to KP venues and safe spaces in partnership with KP CSOs enabled successful community‐based PrEP delivery beyond the reach of traditional facility‐based services.
Prevalence of malnutrition and impact on 30‐day hospital readmission in adults receiving home care and ambulatory care: A descriptive cohort study
Authors: Goharian Leila , Keller Heather , Desai Sameer 
Published: July 2024

AbstractBackgroundLittle is known about the prevalence of malnutrition among patients receiving home care (HC) and ambulatory care (AC) services. Further, the risk of hospital readmission in malnourished patients transitioning from hospital to HC or AC is also not well established. This study aims to address these two gaps.MethodsA descriptive cohort study of newly referred HC and AC patients between January and December 2019 was conducted. Nutrition status was assessed by clinicians using the Mini Nutritional Assessment–Short Form (MNA‐SF). Prevalence of malnutrition and at risk of malnutrition (ARM) was calculated, and a log‐binomial regression model was used to estimate the relative risk of hospital readmission within 30 days of discharge for those who were malnourished and referred from hospital.ResultsA total of 3704 MNA‐SFs were returned, of which 2402 (65%) had complete data. The estimated prevalence of malnutrition and ARM among newly referred HC and AC patients was 21% (95% CI: 19%–22%) and 55% (95% CI: 53%–57%), respectively. The estimated risk of hospital readmission for malnourished patients was 2.7 times higher (95% CI: 1.9%–3.9%) and for ARM patients was 1.9 times higher (95% CI: 1.4%–2.8%) than that of patients with normal nutrition status.ConclusionThe prevalence of malnutrition and ARM among HC and AC patients is high. Malnutrition and ARM are correlated with an increased risk of hospital readmission 30 days posthospital discharge.
Proton spot dose estimation based on positron activity distributions with neural network
Authors: Zhang Ruilin , Mu Dengyun , Ma Qiuhui , Wan Lin , Xiao Peng , Qi Pengyuan , Liu Gang , Zhang Sheng , Yang Kunyu , Yang Zhiyong , Xie Qingguo 
Published: July 2024

AbstractBackgroundPositron emission tomography (PET) has been investigated for its ability to reconstruct proton‐induced positron activity distributions in proton therapy. This technique holds potential for range verification in clinical practice. Recently, deep learning‐based dose estimation from positron activity distributions shows promise for in vivo proton dose monitoring and guided proton therapy.PurposeThis study evaluates the effectiveness of three classical neural network models, recurrent neural network (RNN), U‐Net, and Transformer, for proton dose estimating. It also investigates the characteristics of these models, providing valuable insights for selecting the appropriate model in clinical practice.MethodsProton dose calculations for spot beams were simulated using Geant4. Computed tomography (CT) images from four head cases were utilized, with three for training neural networks and the remaining one for testing. The neural networks were trained with one‐dimensional (1D) positron activity distributions as inputs and generated 1D dose distributions as outputs. The impact of the number of training samples on the networks was examined, and their dose prediction performance in both homogeneous brain and heterogeneous nasopharynx sites was evaluated. Additionally, the effect of positron activity distribution uncertainty on dose prediction performance was investigated. To quantitatively evaluate the models, mean relative error (MRE) and absolute range error (ARE) were used as evaluation metrics.ResultsThe U‐Net exhibited a notable advantage in range verification with a smaller number of training samples, achieving approximately 75% of AREs below 0.5 mm using only 500 training samples. The networks performed better in the homogeneous brain site compared to the heterogeneous nasopharyngeal site. In the homogeneous brain site, all networks exhibited small AREs, with approximately 90% of the AREs below 0.5 mm. The Transformer exhibited the best overall dose distribution prediction, with approximately 92% of MREs below 3%. In the heterogeneous nasopharyngeal site, all networks demonstrated acceptable AREs, with approximately 88% of AREs below 3 mm. The Transformer maintained the best overall dose distribution prediction, with approximately 85% of MREs below 5%. The performance of all three networks in dose prediction declined as the uncertainty of positron activity distribution increased, and the Transformer consistently outperformed the other networks in all cases.ConclusionsBoth the U‐Net and the Transformer have certain advantages in the proton dose estimation task. The U‐Net proves well suited for range verification with a small training sample size, while the Transformer outperforms others at dose‐guided proton therapy.