bluuebunny/crossref_metadata_2025_split huggingface dataset:
TomoTwin: generalized 3D localization of macromolecules in cryo-electron tomograms with structural data mining
Authors: Rice Gavin , Wagner Thorsten , Stabrin Markus , Sitsel Oleg , Prumbaum Daniel , Raunser Stefan 
Published: May 2023

AbstractCryogenic-electron tomography enables the visualization of cellular environments in extreme detail, however, tools to analyze the full amount of information contained within these densely packed volumes are still needed. Detailed analysis of macromolecules through subtomogram averaging requires particles to first be localized within the tomogram volume, a task complicated by several factors including a low signal to noise ratio and crowding of the cellular space. Available methods for this task suffer either from being error prone or requiring manual annotation of training data. To assist in this crucial particle picking step, we present TomoTwin: an open source general picking model for cryogenic-electron tomograms based on deep metric learning. By embedding tomograms in an information-rich, high-dimensional space that separates macromolecules according to their three-dimensional structure, TomoTwin allows users to identify proteins in tomograms de novo without manually creating training data or retraining the network to locate new proteins.
Early alterations in the MCH system link aberrant neuronal activity and sleep disturbances in a mouse model of Alzheimer’s disease
Authors: Calafate Sara , Özturan Gökhan , Thrupp Nicola , Vanderlinden Jeroen , Santa-Marinha Luísa , Morais-Ribeiro Rafaela , Ruggiero Antonella , Bozic Ivan , Rusterholz Thomas , Lorente-Echeverría Blanca , Dias Marcelo , Chen Wei-Ting , Fiers Mark , Lu Ashley , Vlaeminck Ine , Creemers Eline , Craessaerts Katleen , Vandenbempt Joris , van Boekholdt Luuk , Poovathingal Suresh , Davie Kristofer , Thal Dietmar Rudolf , Wierda Keimpe , Oliveira Tiago Gil , Slutsky Inna , Adamantidis Antoine , De Strooper Bart , de Wit Joris 
Published: May 2023

AbstractEarly Alzheimer’s disease (AD) is associated with hippocampal hyperactivity and decreased sleep quality. Here we show that homeostatic mechanisms transiently counteract the increased excitatory drive to CA1 neurons in AppNL-G-F mice, but that this mechanism fails in older mice. Spatial transcriptomics analysis identifies Pmch as part of the adaptive response in AppNL-G-F mice. Pmch encodes melanin-concentrating hormone (MCH), which is produced in sleep–active lateral hypothalamic neurons that project to CA1 and modulate memory. We show that MCH downregulates synaptic transmission, modulates firing rate homeostasis in hippocampal neurons and reverses the increased excitatory drive to CA1 neurons in AppNL-G-F mice. AppNL-G-F mice spend less time in rapid eye movement (REM) sleep. AppNL-G-F mice and individuals with AD show progressive changes in morphology of CA1-projecting MCH axons. Our findings identify the MCH system as vulnerable in early AD and suggest that impaired MCH-system function contributes to aberrant excitatory drive and sleep defects, which can compromise hippocampus-dependent functions.
Pareto optimization with small data by learning across common objective spaces
Authors: Tan Chin Sheng , Gupta Abhishek , Ong Yew-Soon , Pratama Mahardhika , Tan Puay Siew , Lam Siew Kei 
Published: May 2023

AbstractIn multi-objective optimization, it becomes prohibitively difficult to cover the Pareto front (PF) as the number of points scales exponentially with the dimensionality of the objective space. The challenge is exacerbated in expensive optimization domains where evaluation data is at a premium. To overcome insufficient representations of PFs, Pareto estimation (PE) invokes inverse machine learning to map preferred but unexplored regions along the front to the Pareto set in decision space. However, the accuracy of the inverse model depends on the training data, which is inherently scarce/small given high-dimensional/expensive objectives. To alleviate this small data challenge, this paper marks a first study on multi-source inverse transfer learning for PE. A method to maximally utilize experiential source tasks to augment PE in the target optimization task is proposed. Information transfers between heterogeneous source-target pairs is uniquely enabled in the inverse setting through the unification provided by common objective spaces. Our approach is tested experimentally on benchmark functions as well as on high-fidelity, multidisciplinary simulation data of composite materials manufacturing processes, revealing significant gains to the predictive accuracy and PF approximation capacity of Pareto set learning. With such accurate inverse models made feasible, a future of on-demand human-machine interaction facilitating multi-objective decisions is envisioned.
Identifying appropriate prediction models for estimating hourly temperature over diverse agro-ecological regions of India
Authors: Bal Santanu Kumar , Pramod V. P. , Sandeep V. M. , Manikandan N. , Sarath Chandran M. A. , Subba Rao A. V. M. , Vijaya Kumar P. , Vanaja M. , Singh V. K. 
Published: May 2023

AbstractThe present study tests the accuracy of four models in estimating the hourly air temperatures in different agroecological regions of the country during two major crop seasons, kharif and rabi, by taking daily maximum and minimum temperatures as input. These methods that are being used in different crop growth simulation models were selected from the literature. To adjust the biases of estimated hourly temperature, three bias correction methods (Linear regression, Linear scaling and Quantile mapping) were used. When compared with the observed data, the estimated hourly temperature, after bias correction, is reasonably close to the observed during both kharif and rabi seasons. The bias-corrected Soygro model exhibited its good performance at 14 locations, followed by the WAVE model and Temperature models at 8 and 6 locations, respectively during the kharif season. In the case of rabi season, the bias-corrected Temperature model appears to be accurate at more locations (21), followed by WAVE and Soygro models at 4 and 2 locations, respectively. The pooled data analysis showed the least error between estimated (uncorrected and bias-corrected) and observed hourly temperature from 04 to 08 h during kharif season while it was 03 to 08 h during the rabi season. The results of the present study indicated that Soygro and Temperature models estimated hourly temperature with better accuracy at a majority of the locations situated in the agroecological regions representing different climates and soil types. Though the WAVE model worked well at some of the locations, estimation by the PL model was not up to the mark in both kharif and rabi seasons. Hence, Soygro and Temperature models can be used to estimate hourly temperature data during both kharif and rabi seasons, after the bias correction by the Linear Regression method. We believe that the application of the study would facilitate the usage of hourly temperature data instead of daily data which in turn improves the precision in predicting phenological events and bud dormancy breaks, chilling hour requirement etc.
In vitro ruminal degradability of wheat straw cultivated with white-rot fungi adapted to mushroom farming conditions
Authors: Martens Siriwan D. , Wildner Vicki , Zeyner Annette , Steinhöfel Olaf 
Published: May 2023

AbstractBiological treatment of cereal straw for ruminant nutrition purposes might present an environmentally friendly option of valorizing a widely available by-product of grain production for farming systems with low external input. Several strains of white-rot fungi have been selected in the past under mostly controlled laboratory conditions for their capacity of lignin degradation. The study adapted to conditions on farm for upscaling purposes. The development of the in vitro straw digestibility with two different moistening pre-treatments and inoculated with three different fungi species, namely Pleurotus ostreatus, Ceriporiopsis subvermispora and Volvariella volvacea, was determined up to 42 days of fermentation with five sampling times. The effect of physical straw pre-treatments on nutritional parameters was evaluated. The neutral detergent fiber digestibility (NDFD30h), enzymatically soluble organic substance (ELOS) and the gas production (Hohenheim Feed value Test, HFT) as indicators for in vitro ruminal degradability decreased over time independent of the fungus: HFT, ELOS and NDFD30h by up to 50, 35 and 30% of the original straw. Remoistening and autoclaving the straw increased the gas production significantly by 2.6 mL/200 g dry matter (DM), and ELOS and NDFD30h by 45 and 51 g/kg DM compared to the original straw (34.9 mL/200 mg DM, 342 g/kg DM, 313 g/kg NDF).
Effect of Bacillus subtilis on mechanical and self-healing properties in mortar with different crack widths and curing conditions
Authors: Yamasamit Nattapong , Sangkeaw Panisa , Jitchaijaroen Wittaya , Thongchom Chanachai , Keawsawasvong Suraparb , Kamchoom Viroon 
Published: May 2023

AbstractThis research aimed to investigate the effectiveness of Bacillus subtilis (B. subtilis) in self-healing cracks in concrete and enhancing concrete strength through microbial induced calcium carbonate precipitation (MICP). The study evaluated the ability of the mortar to cover cracks within 28 days, taking into account the width of the crack, and observed the recovery of strength after self-healing. The use of microencapsulated endospores of B. subtilis was also examined for its impact on the strength of concrete. The compressive, splitting tensile, and flexural strengths of normal mortar were compared to those of biological mortar, and it was found that biological mortar had a higher strength capacity. Microstructure analysis using SEM and EDS showed that bacterial growth increased calcium production, contributing to the improved mechanical properties of the bio-mortar.
Usefulness of gastric aspirates for diagnosing nontuberculous mycobacteriosis
Authors: Shimoda Masafumi , Morimoto Kozo , Yoshiyama Takashi , Tanaka Yoshiaki , Furuuchi Koji , Fujiwara Keiji , Ito Masashi , Nishimura Masashi , Yoshimori Kozo , Ohta Ken 
Published: May 2023

AbstractDistinguishing between nontuberculous mycobacterial pulmonary disease (NTM-PD) and pulmonary tuberculosis (TB) is difficult. We aimed to evaluate the usefulness of gastric aspirate examination for NTM-PD diagnosis and for differentiating NTM-PD from other diseases, including pulmonary TB. We retrospectively collected data for 491 patients with negative sputum smears or a lack of sputum production at Fukujuji Hospital. We compared 31 patients with NTM-PD to 218 patients with other diseases (excluding 203 with pulmonary TB). Additionally, we compared 81 patients with NTM cultured from at least one sputum or bronchoscopy sample to the other 410 patients. Gastric aspirate examination for NTM-PD diagnosis showed 74.2% sensitivity and 99.0% specificity for culture positivity. There was no significant difference between the nodular bronchiectatic disease and cavitary disease types for culture positivity (p = 0.515). The significance of NTM isolation from gastric aspirate showed 64.2% sensitivity and 99.8% specificity for culture positivity. Gastric aspirate examination revealed NTM in one TB patient, allowing TB to be ruled out in 98.1% of patients with NTM cultured from gastric aspirates. Gastric aspirate examination is helpful for early-stage NTM diagnosis and ruling out pulmonary TB. This could lead to more accurate and timely treatment.
Machine learning predictive model for aspiration screening in hospitalized patients with acute stroke
Authors: Park Dougho , Son Seok Il , Kim Min Sol , Kim Tae Yeon , Choi Jun Hwa , Lee Sang-Eok , Hong Daeyoung , Kim Mun-Chul 
Published: May 2023

AbstractDysphagia is a fatal condition after acute stroke. We established machine learning (ML) models for screening aspiration in patients with acute stroke. This retrospective study enrolled patients with acute stroke admitted to a cerebrovascular specialty hospital between January 2016 and June 2022. A videofluoroscopic swallowing study (VFSS) confirmed aspiration. We evaluated the Gugging Swallowing Screen (GUSS), an early assessment tool for dysphagia, in all patients and compared its predictive value with ML models. Following ML algorithms were applied: regularized logistic regressions (ridge, lasso, and elastic net), random forest, extreme gradient boosting, support vector machines,k-nearest neighbors, and naïve Bayes. We finally analyzed data from 3408 patients, and 448 of them had aspiration on VFSS. The GUSS showed an area under the receiver operating characteristics curve (AUROC) of 0.79 (0.77–0.81). The ridge regression model was the best model among all ML models, with an AUROC of 0.81 (0.76–0.86), an F1 measure of 0.45. Regularized logistic regression models exhibited higher sensitivity (0.66–0.72) than the GUSS (0.64). Feature importance analyses revealed that the modified Rankin scale was the most important feature of ML performance. The proposed ML prediction models are valid and practical for screening aspiration in patients with acute stroke.
Neutrophil membrane biomimetic delivery system (Ptdser‐NM‐Lipo/Fer‐1) designed for targeting atherosclerosis therapy
Authors: Li Wei , Liu Chang , Wang Sichuan , Liu Naifeng 
Published: May 2023

AbstractAtherosclerosis is a progressive inflammatory disease characterised by excessive lipid accumulation and inflammatory cell infiltration and is the basis of most cardiovascular diseases and peripheral arterial diseases. Therefore, an effectively targeted delivery system is urgently needed to deliver ferroptosis‐specific inhibitors to the site of arterial plaque and the inflammatory microenvironment. Inspired by the fact that neutrophils can be recruited to arterial plaques under the action of adhesion molecules and chemokines, the authors developed a neutrophil membrane hybrid liposome nano‐mimetic system (Ptdser‐NM‐Lipo/Fer‐1) that delivers Ferrostatin‐1 (Fer‐1) to the atherosclerotic plaque effectively, which is composed of Fer‐1‐loaded Ptdser‐modified liposomes core and neutrophils shell. Fer‐1 was released at the AS plaque site to remove reactive oxygen species (ROS) and improve the inflammatory microenvironment. In vitro ROS clearance experiments have shown that 50 μmol/ml Fer‐1 can significantly remove ROS produced by H2O2‐induced MOVAS cells and Ptdser‐NM‐Lipo/Fer‐1 revealed a 3‐fold increase in the inhibition rate of ROS than free Fer‐1 in induced‐RAW264.7, demonstrating its superior ROS‐cleaning effect. Based on the interaction of adhesion molecules, such as vascular cell adhesion molecule 1, ICAM‐1, P‐selectin, E‐selectin, and chemokines released in the inflamed site, the aorta in NM‐Lipo‐treated mice displayed 1.3‐fold greater radiant efficiency than platelet membrane‐Lipo‐treated mice. Meanwhile, due to the modification of the Ptdser, the aorta in Ptdser‐NM‐Lipo/Fer‐1‐treated mice exhibited the highest fluorescence intensity, demonstrating its excellent targeting ability for atherosclerosis. Therefore, we present a specific formulation for the treatment of atherosclerosis with the potential for novel therapeutic uses.
Human Derived Dermal Fibroblasts as in Vitro Research Tool to Study
Circadian Rhythmicity in Psychiatric Disorders
Authors: Palm Denise , Uzoni Adriana , Kronenberg Golo , Thome Johannes , Faltraco Frank 
Published: May 2023

AbstractA number of psychiatric disorders are defined by persistent or recurrent
sleep-wake disturbances alongside disruptions in circadian rhythm and
altered clock gene expression. Circadian rhythms are present not only in the
hypothalamic suprachiasmatic nucleus but also in peripheral tissues. In this
respect, cultures of human derived dermal fibroblasts may serve as a
promising new tool to investigate cellular and molecular mechanisms
underlying the pathophysiology of mental illness. In this article, we
discuss the advantages of fibroblast cultures to study psychiatric disease.
More specifically, we provide an update on recent advances in modeling
circadian rhythm disorders using human fibroblasts.
Overexpression and RNAi-mediated Knockdown of Two 3β-hydroxy-Δ5-steroid dehydrogenase Genes in Digitalis lanata Shoot Cultures Reveal Their Role in Cardenolide
Biosynthesis
Authors: Leykauf Tim , Klein Jan , Ernst Mona , Dorfner Maja , Ignatova Anastasiia , Kreis Wolfgang , Lanig Harald , Munkert Jennifer 
Published: May 2023

Abstract3β-hydroxy-Δ5-steroid dehydrogenases (3βHSDs) are supposed to be involved in 5β-cardenolide biosynthesis. Here, a novel 3βHSD (Dl3βHSD2) was isolated from Digitalis
lanata shoot cultures and expressed in E. coli. Recombinant Dl3βHSD1 and Dl3βHSD2 shared 70% amino acid identity, reduced various 3-oxopregnanes and oxidised
3-hydroxypregnanes, but only rDl3βHSD2 converted small ketones and secondary alcohols efficiently. To explain these differences in substrate specificity, we established homology
models using borneol dehydrogenase of Salvia rosmarinus (6zyz) as the template. Hydrophobicity and amino acid residues in the binding pocket may explain the difference in enzyme
activities and substrate preferences. Compared to Dl3βHSD1, Dl3βHSD2 is weakly expressed in D. lanata shoots. High constitutive expression of Dl3βHSDs was realised by
Agrobacterium-mediated transfer of Dl3βHSD genes fused to the CaMV-35S promotor into the genome of D. lanata wild type shoot cultures. Transformed shoots
(35S:Dl3βHSD1 and 35S:Dl3βHSD2) accumulated less cardenolides than controls. The levels of reduced glutathione (GSH), which is known to inhibit cardenolide formation, were
higher in the 35S:Dl3βHSD1 lines than in the controls. In the 35S:Dl3βHSD1 lines cardenolide levels were restored after adding of the substrate pregnane-3,20-dione in
combination with buthionine-sulfoximine (BSO), an inhibitor of GSH formation. RNAi-mediated knockdown of the Dl3βHSD1 yielded several shoot culture lines with strongly reduced
cardenolide levels. In these lines, cardenolide biosynthesis was fully restored after addition of the downstream precursor pregnan-3β-ol-20-one, whereas upstream precursors such as
progesterone had no effect, indicating that no shunt pathway could overcome the Dl3βHSD1 knockdown. These results can be taken as the first direct proof that Dl3βHSD1 is indeed
involved in 5β-cardenolide biosynthesis.
Fäkaler Mikrobiota-Transfer (FMT) in Deutschland – Status und Perspektive
Authors: Stallmach Andreas , von Müller Lutz , Storr Martin , Link Alexander , Konturek Peter C. , Solbach Philipp Christoph , Weiss Karl Heinz , Wahler Steffen , Vehreschild Maria J. G. T. 
Published: May 2023

Zusammenfassung
Einführung Der Fäkale Mikrobiota-Transfer (FMT) ist eine
Behandlung zur Modulation der gastrointestinalen Mikrobiota. Der Einsatz bei rezidivierender
Clostridioides-difficile-Infektion (rCDI) ist europaweit etabliert und wird in nationalen und internationalen Leitlinien
empfohlen. Der FMT ist in Deutschland im Fallpauschalensystem der Krankenhäuser kodierfähig.
Eine auf dieser Kodierung basierende umfassende Erhebung zur Häufigkeit des Einsatzes fehlt
bislang.
Material und Methodik Berichte des Instituts für das
Entgeltsystem im Krankenhaus (InEK), des Statistischen Bundesamtes (DESTATIS) und
Qualitätsberichte der Krankenhäuser 2015–2021 wurden auf FMT-Kodierung hin untersucht und im
Rahmen einer strukturierten Expertenkonsultation bewertet.
Ergebnisse Zwischen 2015 und 2021 wurden von 175 Krankenhäusern
1.645 FMT-Verfahren kodiert. Von 2016 bis 2018 waren dies jährlich im Median 293 (274–313)
FMT, gefolgt von einem konstanten Rückgang in den folgenden Jahren auf 119 FMT im Jahr 2021.
Patienten/-innen mit FMT waren zu 57,7% weiblich, im Median 74 Jahre alt und der FMT wurde zu
72,2% koloskopisch appliziert. Bei 86,8 % der Fälle wurde eine CDI
als Hauptdiagnose genannt, gefolgt von 7,6% eine Colitis ulcerosa.
Diskussion In Deutschland wird der FMT seltener eingesetzt als im
europäischen Vergleich. Eine Anwendungshürde ist die behördliche Einordnung des FMT als nicht
zugelassenes Arzneimittel, die zu erheblich höherem Aufwand bei Herstellung und Verabreichung
führt und eine Erstattung erschwert. Die Europäische Kommission hat kürzlich eine Verordnung
vorgeschlagen, den FMT als Transplantation einzuordnen. Dies könnte die regulatorische
Situation des FMT in Deutschland perspektivisch verändern und so zu einem flächendeckenden
Angebot eines in Leitlinien empfohlenen Therapieverfahrens beitragen.
Palladium-Catalyzed Synthesis of Benzofuran Spiroketals Derived from Cholesterol; NMR and X-ray Characterization
Authors: Iglesias-Arteaga Martin A. , García-Santos William H. , Quiroz-Mendoza Ariadna M. , Mayorquín-Torres Martha C. , Flores-Álamo Marcos 
Published: May 2023

AbstractThe synthesis of two diastereomeric steroid spiroketals bearing a 2,3-dihydrobenzofuran moiety is described. The structure of the obtained compounds was elucidated by combined 1D and 2D NMR techniques and corroborated by X-ray crystallography studies.
Unimolecular dissociation of C6H6–C6H5Cl, C6H6–C6H3Cl3, and C6H6–C6Cl6 complexes using machine learning approach
Authors: Deb Basudha , Anal S. R. Ngamwal , Mahanta Himashree , Yogita  , Paul Amit Kumar 
Published: May 2023

The application of Machine Learning (ML) algorithms in chemical sciences, particularly computational chemistry, is a vastly emerging area of modern research. While many applications of ML techniques have already been in place to use ML based potential energies in various dynamical simulation studies, specific applications are also being successfully tested. In this work, the ML algorithms are tested to calculate the unimolecular dissociation time of benzene–hexachlorobenzene, benzene–trichlorobenzene, and benzene–monochlorobenzene complexes. Three ML algorithms, namely, Decision-Tree-Regression (DTR), Multi-Layer Perceptron, and Support Vector Regression are considered. The algorithms are trained with simulated dissociation times as functions (attributes) of complexes’ intramolecular and intermolecular vibrational energies. The simulation data are used for an excitation temperature of 1500 K. Considering that the converged result is obtained with 1500 trajectories, an ML algorithm trained with 700 simulation points provides the same dissociation rate constant within statistical uncertainty as obtained from the converged 1500 trajectory result. The DTR algorithm is also used to predict 1000 K simulation results using 1500 K simulation data.
Depletion-driven antiferromagnetic, paramagnetic, and ferromagnetic behavior in quasi-two-dimensional buckled colloidal solids
Authors: Hill Analisa , Tanaka Michio , Aptowicz Kevin B. , Mishra Chandan K. , Yodh A. G. , Ma Xiaoguang 
Published: May 2023

We investigate quasi-two-dimensional buckled colloidal monolayers on a triangular lattice with tunable depletion interactions. Without depletion attraction, the experimental system provides a colloidal analog of the well-known geometrically frustrated Ising antiferromagnet [Y. Han et al., Nature 456, 898–903 (2008)]. In this contribution, we show that the added depletion attraction can influence both the magnitude and sign of an Ising spin coupling constant. As a result, the nearest-neighbor Ising “spin” interactions can be made to vary from antiferromagnetic to para- and ferromagnetic. Using a simple theory, we compute an effective Ising nearest-neighbor coupling constant, and we show how competition between entropic effects permits for the modification of the coupling constant. We then experimentally demonstrate depletion-induced modification of the coupling constant, including its sign, and other behaviors. Depletion interactions are induced by rod-like surfactant micelles that change length with temperature and thus offer means for tuning the depletion attraction in situ. Buckled colloidal suspensions exhibit a crossover from an Ising antiferromagnetic to paramagnetic phase as a function of increasing depletion attraction. Additional dynamical experiments reveal structural arrest in various regimes of the coupling-constant, driven by different mechanisms. In total, this work introduces novel colloidal matter with “magnetic” features and complex dynamics rarely observed in traditional spin systems.