bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of Polyesters in Fused Deposition Modeling for Biomedical Applications
Authors: Grivet‐Brancot Arianna , Boffito Monica , Ciardelli Gianluca 
Published: April 2022

AbstractIn recent years, 3D printing techniques experience a growing interest in several sectors, including the biomedical one. Their main advantage resides in the possibility to obtain complex and personalized structures in a cost‐effective way impossible to achieve with traditional production methods. This is especially true for fused deposition modeling (FDM), one of the most diffused 3D printing methods. The easy customization of the final products’ geometry, composition, and physicochemical properties is particularly interesting for the increasingly personalized approach adopted in modern medicine. Thermoplastic polymers are the preferred choice for FDM applications, and a wide selection of biocompatible and biodegradable materials is available to this aim. Moreover, these polymers can also be easily modified before and after printing to better suit the body environment and the mechanical properties of biological tissues. This review focuses on the use of thermoplastic aliphatic polyesters for FDM applications in the biomedical field. In detail, the use of poly(ε‐caprolactone), poly(lactic acid), poly(lactic‐co‐glycolic acid), poly(hydroxyalkanoate)s, thermoplastic poly(ester urethane)s, and their blends is thoroughly surveyed, with particular attention to their main features, applicability, and workability. The state‐of‐the‐art is presented and current challenges in integrating the additive manufacturing technology in the medical practice are discussed.
Sustainable Synthesis of Non‐Isocyanate Polyurethanes Based on Renewable 2,3‐Butanediol
Authors: Kirchberg Anja , Khabazian Esfahani Masood , Röpert Marie‐Christin , Wilhelm Manfred , Meier Michael A. R. 
Published: April 2022

AbstractIn this work, three different cyclic carbonates are obtained from renewable diols and transformed into carbamates by reacting them with renewable 11‐amino undecanoic acid methyl ester to synthesize non‐isocyanate poly(ester urethane)s in a sustainable manner. A procedure using 2,3‐butanediol (2,3‐BDO) as a renewable starting material to synthesize a cyclic carbonate with dimethyl carbonate (DMC) is introduced, catalyzed by 1,5,7‐triazabicylco[4.4.0]dec‐5‐ene (TBD). Three purification strategies, i.e., column chromatography, extraction, and distillation, are compared regarding their E‐Factors. Propylene glycol (PG) and ethylene glycol (EG) are used as alternative starting materials to broaden the substrate scope and compare material properties, their cyclic carbonates likewise react to carbamates with 11‐amino undecanoic acid methyl ester. All carbamates are then polymerized in a bulk polycondensation reaction, yielding non‐isocyanate polyurethanes (NIPUs), specifically poly (ester urethane)s, with molecular weights (Mn) up to 10 kDa. Complete characterization is reported using differential scanning calorimetric (DSC), size exclusion chromatographic measurements (SEC), 1H‐NMR as well as IR spectroscopy. The rheological properties of the poly(ester urethane)s are investigated in the framework of small amplitude oscillatory shear (SAOS) and uniaxial elongation.
Quantifying dominant bacterial genera detected in metagenomic data from fish eggs and larvae using genus‐specific primers
Authors: Najafpour Babak , Pinto Patricia I. S. , Canario A. V. M. , Power Deborah M. 
Published: April 2022

AbstractThe goal of this study was to design genus‐specific primers for rapid evaluation of the most abundant bacterial genera identified using amplicon‐based sequencing of the 16S rRNA gene in fish‐related samples and surrounding water. Efficient genus‐specific primers were designed for 11 bacterial genera including Alkalimarinus, Colwellia, Enterovibrio, Marinomonas, Massilia, Oleispira, Phaeobacter, Photobacterium, Polarbacerium, Pseudomonas, and Psychrobium. The specificity of the primers was confirmed by the phylogeny of the sequenced polymerase chain reaction (PCR) amplicons that indicated primers were genus‐specific except in the case of Colwellia and Phaeobacter. Copy number of the 16S rRNA gene obtained by quantitative PCR using genus‐specific primers and the relative abundance obtained by 16S rRNA gene sequencing using universal primers were well correlated for the five analyzed abundant bacterial genera. Low correlations between quantitative PCR and 16S rRNA gene sequencing for Pseudomonas were explained by the higher coverage of known Pseudomonas species by the designed genus‐specific primers than the universal primers used in 16S rRNA gene sequencing. The designed genus‐specific primers are proposed as rapid and cost‐effective tools to evaluate the most abundant bacterial genera in fish‐related or potentially other metagenomics samples.
Prodromal X‐Linked Dystonia‐Parkinsonism is Characterized by a Subclinical Motor Phenotype
Authors: Steinhardt Julia , Hanssen Henrike , Heldmann Marcus , Sprenger Andreas , Laabs Björn‐Hergen , Domingo Aloysius , Reyes Charles Jourdan , Prasuhn Jannik , Brand Max , Rosales Raymond , Münte Thomas F. , Klein Christine , Westenberger Ana , Oropilla Jean Q. , Diesta Cid , Brüggemann Norbert 
Published: May 2022

AbstractBackgroundEarly diagnosis in patients with neurodegenerative disorders is crucial to initiate disease‐modifying therapies at a time point where progressive neurodegeneration can still be modified.ObjectivesThe objective of this study was to determine whether motor or non‐motor signs of the disease occur as indicators of a prodromal phase of X‐linked dystonia‐parkinsonism (XDP), a highly‐penetrant monogenic movement disorder with striking basal ganglia pathology.MethodsIn addition to a comprehensive clinical assessment, sensor‐based balance and gait analyses were performed in non‐manifesting mutation carriers (NMCs), healthy controls (HCs), and patients with XDP. Gradient‐boosted trees (GBT) methodology was utilized to classify groups of interest.ResultsThere were no clinically overt disease manifestations in the NMCs. Balance analysis, however, revealed a classification accuracy of 90% for the comparison of NMC versus HC. For the gait analysis, the best‐performing GBT‐based model showed a balanced accuracy of 95% (NMC vs. HC; walking at maximum speed). Using a separate analysis of genetic modifiers, several gait parameters correlated strongly with the estimated age at disease onset in the NMC group.ConclusionsOur study unraveled balance and gait abnormalities in NMCs that preceded the onset of XDP. These findings demonstrate prodromal motor changes among NMCs who will develop XDP with a very high likelihood in the future. Gait abnormalities had a predictive value for the estimated age at onset highlighting the impact of genetic modifiers in personalized treatment in monogenic neurodegenerative disorders. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
LC–MS Characterization and Quantification of Known and Unknown (Poly)phenol Metabolites—Possible Pitfalls and Their Avoidance
Authors: Clifford Michael N. , Kuhnert Nikolai 
Published: April 2022

AbstractThis review focuses on the LC–MS characterization and quantification of dietary (poly)phenols and their metabolites. It draws attention to errors, omissions, and misunderstandings that appear frequently in published papers, and suggests strategies for their avoidance. Aspects covered include the use of authentic standards and surrogate reference materials, the importance of collecting and archiving Total Ion Current MS data, the limitations of using on‐line compilations of accurate mass MS data to assign unknown components when multiple isomers are possible, and the often understated magnitude of person‐to‐person variation that may significantly impact at population level any potential health benefit.
Toward automatic beam angle selection for pencil‐beam scanning proton liver treatments: A deep learning–based approach
Authors: Kaderka Robert , Liu Keng‐Chi , Liu Lawrence , VanderStraeten Reynald , Liu Tyng‐Luh , Lee Kuang‐Min , Tu Yi‐Chin Ethan , MacEwan Iain , Simpson Daniel , Urbanic James , Chang Chang 
Published: April 2022

AbstractBackgroundDose deposition characteristics of proton radiation can be advantageous over photons. Proton treatment planning, however, poses additional challenges for the planners. Proton therapy is usually delivered with only a small number of beam angles, and the quality of a proton treatment plan is largely determined by the beam angles employed. Finding the optimal beam angles for a proton treatment plan requires time and experience, motivating the investigation of automatic beam angle selection methods.PurposeA deep learning–based approach to automatic beam angle selection is proposed for the proton pencil‐beam scanning treatment planning of liver lesions.MethodsWe cast beam‐angle selection as a multi‐label classification problem. To account for angular boundary discontinuity, the underlying convolution neural network is trained with the proposed Circular Earth Mover's Distance–based regularization and multi‐label circular–smooth label technique. Furthermore, an analytical algorithm emulating proton treatment planners’ clinical practice is employed in post‐processing to improve the output of the model. Forty‐nine patients that received proton liver treatments between 2017 and 2020 were randomly divided into training (n = 31), validation (n = 7), and test sets (n = 11). AI‐selected beam angles were compared with those angles selected by human planners, and the dosimetric outcome was investigated by creating plans using knowledge‐based treatment planning.ResultsFor 7 of the 11 cases in the test set, AI‐selected beam angles agreed with those chosen by human planners to within 20° (median angle difference = 10°; mean = 18.6°). Moreover, out of the total 22 beam angles predicted by the model, 15 (68%) were within 10° of the human‐selected angles. The high correlation in beam angles resulted in comparable dosimetric statistics between proton treatment plans generated using AI‐ and human‐selected angles. For the cases with beam angle differences exceeding 20°, the dosimetric analysis showed similar plan quality although with different emphases on organ‐at‐risk sparing.ConclusionsThis pilot study demonstrated the feasibility of a novel deep learning–based beam angle selection technique. Testing on liver cancer patients showed that the resulting plans were clinically viable with comparable dosimetric quality to those using human‐selected beam angles. In tandem with auto‐contouring and knowledge‐based treatment planning tools, the proposed model could represent a pathway for nearly fully automated treatment planning in proton therapy.
Nutrition risk assessed by Nutritional Risk Screening 2002 is associated with in‐hospital mortality in older patients with COVID‐19
Authors: Can Busra , Senturk Durmus Nurdan , Olgun Yıldızeli Sehnaz , Kocakaya Derya , Ilhan Birkan , Tufan Asli 
Published: April 2022

AbstractBackgroundAlthough numerous studies have been performed to determine predictors of coronavirus disease 2019 (COVID‐19) mortality, studies that address the geriatric age group are limited. The aim of this study was to investigate the utility of the Nutritional Risk Screening 2002 (NRS‐2002) and the Geriatric 8 (G8) screening tools in predicting clinical outcomes in older adults hospitalized with COVID‐19.MethodsPatients aged ≥60 years who were hospitalized with COVID‐19 in the second wave of the pandemic were included in the study. COVID‐19 infection was demonstrated by a positive real‐time reverse transcriptase–polymerase chain reaction on nasopharyngeal swab or positive radiological findings. Disease severity was determined as defined by the National Institutes of Health. Patient demographics, laboratory values on admission, comorbidities, and medications were recorded. The NRS‐2002 and the G8 screening tools were performed for all patients by the same geriatrician. Primary outcome was in‐hospital mortality.ResultsA total of 121 patients were included. Mean age was 75 ± 9 years, and 51% were female. Mean body mass index was 27 ± 4.5 kg/m2. Sixty‐nine percent of the patients had nutrition risk according to the NRS‐2002. Eighty‐nine percent of the patients had a G8 score ≤14. In‐hospital mortality occurred in 26 (22%) patients. Older age and having nutrition risk as determined by the NRS‐2002 were independently associated with a higher risk of in‐hospital mortality in older patients with COVID‐19.ConclusionThe NRS‐2002 tool provides rapid assessment for risk stratification in hospitalized older patients with COVID‐19.
Continuous approximation formulas for location problems
Authors: Carlsson John Gunnar , Jones Bo 
Published: April 2022

AbstractThe majority of research in the continuous approximation paradigm has emphasized routing problems, such as the travelling salesman problem and the vehicle routing problem. This article instead focuses on continuous approximation formulas for problems involving location, specifically the ‐medians, ‐dispersion, and generalized minimum spanning tree problems. We contribute bounds for constants that describe the growth rate of the cost of these problems as the number of demand points becomes large, and conduct computational experiments that verify that they provide a good approximation in practice.
Mitochondrial genome variations, mitochondrial‐nuclear compatibility, and their association with metabolic diseases
Authors: Ludwig‐Słomczyńska Agnieszka H. , Rehm Markus 
Published: May 2022

AbstractTwo genomes regulate the energy metabolism of eukaryotic cells: the nuclear genome, which codes for most cellular proteins, and the mitochondrial genome, which, together with the nuclear genome, coregulates cellular bioenergetics. Therefore, mitochondrial genome variations can affect, directly or indirectly, all energy‐dependent cellular processes and shape the metabolic state of the organism. This review provides a current and up‐to‐date overview on how codependent these two genomes are, how they appear to have coevolved, and how variations within the mitochondrial genome might be associated with the manifestation of metabolic diseases. This review summarizes and structures results obtained from epidemiological studies that identified links between mitochondrial haplogroups and individual risks for developing obesity and diabetes. This is complemented by findings on the compatibility of mitochondrial and nuclear genomes and cellular bioenergetic fitness, which have been acquired from well‐controlled studies in conplastic animal models. These elucidate, more mechanistically, how single‐nucleotide variants can influence cellular metabolism and physiology. Overall, it seems that certain mitochondrial genome variations negatively affect mitochondrial‐nuclear compatibility and are statistically linked with the onset of metabolic diseases, whereas, for others, greater uncertainty exists, and additional research into this exciting field is required.
Expression patterns and prognostic relevance of subtype‐specific transcription factors in surgically resected small‐cell lung cancer: an international multicenter study
Authors: Megyesfalvi Zsolt , Barany Nandor , Lantos Andras , Valko Zsuzsanna , Pipek Orsolya , Lang Christian , Schwendenwein Anna , Oberndorfer Felicitas , Paku Sandor , Ferencz Bence , Dezso Katalin , Fillinger Janos , Lohinai Zoltan , Moldvay Judit , Galffy Gabriella , Szeitz Beata , Rezeli Melinda , Rivard Christopher , Hirsch Fred R , Brcic Luka , Popper Helmut , Kern Izidor , Kovacevic Mile , Skarda Jozef , Mittak Marcel , Marko‐Varga Gyorgy , Bogos Krisztina , Renyi‐Vamos Ferenc , Hoda Mir Alireza , Klikovits Thomas , Hoetzenecker Konrad , Schelch Karin , Laszlo Viktoria , Dome Balazs 
Published: April 2022

AbstractThe tissue distribution and prognostic relevance of subtype‐specific proteins (ASCL1, NEUROD1, POU2F3, YAP1) present an evolving area of research in small‐cell lung cancer (SCLC). The expression of subtype‐specific transcription factors and P53 and RB1 proteins were measured by immunohistochemistry (IHC) in 386 surgically resected SCLC samples. Correlations between subtype‐specific proteins and in vitro efficacy of various therapeutic agents were investigated by proteomics and cell viability assays in 26 human SCLC cell lines. Besides SCLC‐A (ASCL1‐dominant), SCLC‐AN (combined ASCL1/NEUROD1), SCLC‐N (NEUROD1‐dominant), and SCLC‐P (POU2F3‐dominant), IHC and cluster analyses identified a quadruple‐negative SCLC subtype (SCLC‐QN). No unique YAP1‐subtype was found. The highest overall survival rates were associated with non‐neuroendocrine subtypes (SCLC‐P and SCLC‐QN) and the lowest with neuroendocrine subtypes (SCLC‐A, SCLC‐N, SCLC‐AN). In univariate analyses, high ASCL1 expression was associated with poor prognosis and high POU2F3 expression with good prognosis. Notably, high ASCL1 expression influenced survival outcomes independently of other variables in a multivariate model. High POU2F3 and YAP1 protein abundances correlated with sensitivity and resistance to standard‐of‐care chemotherapeutics, respectively. Specific correlation patterns were also found between the efficacy of targeted agents and subtype‐specific protein abundances. In conclusion, we investigated the clinicopathological relevance of SCLC molecular subtypes in a large cohort of surgically resected specimens. Differential IHC expression of ASCL1, NEUROD1, and POU2F3 defines SCLC subtypes. No YAP1‐subtype can be distinguished by IHC. High POU2F3 expression is associated with improved survival in a univariate analysis, whereas elevated ASCL1 expression is an independent negative prognosticator. Proteomic and cell viability assays of human SCLC cell lines revealed distinct vulnerability profiles defined by transcription regulators. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Incidences and characteristics of primary lung malignancies in childhood in Germany: An analysis of population‐based data from German cancer registries
Authors: Abele Michael , Voggel Sarah , Bremensdorfer Claudia , Spix Claudia , Erdmann Friederike , Kuhlen Michaela , Redlich Antje , Ebinger Martin , Lang Peter , Schneider Dominik T. , Brecht Ines B. 
Published: April 2022

AbstractBackground: Primary lung malignancies are a heterogeneous group of cancers that occur very rarely in childhood. Due to limited knowledge of their epidemiologic and clinical features, these tumors present a challenge to the treating physicians. This study aimed to increase the knowledge about the occurrence of primary lung malignancies in childhood in Germany.Materials and methods: Pseudonymized data of cases recorded at the German Center for Cancer Registry Data (ZfKD) between 1990 and 2017 were retrieved. Primary lung malignancies were identified using the ICD‐ and ICD‐O classification. Numbers were compared to those reported to the German Childhood Cancer Registry (GCCR). Crude incidence rates were calculated using the ZfKD database.Results: A total of 168 patients diagnosed with primary lung malignancies in the age below 19 years were identified from the ZfKD. The median age at diagnosis was 13 years. The most common tumor entities were lung carcinoids (n = 49), lung carcinoma (n = 36), and pleuropulmonary blastoma (n = 14). An unexpected accumulation of lung cancer cases was noted in the first year of life without a clearly specified histopathological diagnosis. A substantial discrepancy in the numbers of primary lung malignancies between ZfKD and GCCR was found.Conclusions: We present population‐based data on the occurrence of primary childhood lung malignancies in Germany, which were more frequent than previously anticipated but likely remained underreported. For better understanding and optimal treatment of these entities, cancer registration needs to be improved through mandatory reporting to the GCCR and regular data sharing between GCCR, population‐based and clinical cancer registries.
Experimental and numerical investigation of high‐velocity impact effects on composite sandwich panel with M‐shaped core reinforced by nano‐SiO2
Authors: Khaledi Himan , Rostamiyan Yasser , Seyyedi Seyyed Masoud 
Published: April 2022

AbstractThis article has experimentally and numerically investigated the high‐velocity impact resistance of the composite sandwich panel with an M‐shaped lattice core reinforced by nano‐SiO2. For this purpose, firstly, a glass fiber resin epoxy sandwich panel has been fabricated in the laboratory. In this regard, the vacuum‐assisted resin transfer molding (VARTM) method has been used to achieve a laminate without any fault. In order to improve the impact resistance of the composite, the nano‐SiO2 were added to the resin epoxy matrix as filler with the ratios of 1%, 2%, and 3% of the composite's total weight. A scanning electron microscope (SEM) has been utilized to observe the microscopic structure of the composites, and it shows an exceptional homogeneous mixture of nano‐SiO2 particles in the resin epoxy matrix. From the experiment results, it was figured out that by adding 1 to 3 wt% of nano‐SiO2 into the composite, the output velocity of the projectile decreases. On the other hand, the results showed that when the projectile collides with the core of the sandwich panel, it remains in the sandwich panel and its output velocity will be zero. However, when the projectile does not completely collide with the core, the output velocity of the projectile will not be zero. In order to validate the results, a finite element analysis (FEA) has been developed to simulate the high‐velocity impact test. Then the experimental data has been compared to numerical simulation and good agreement was observed.
Review on engineering designing of electromagnetic interference shielding materials using additive manufacturing
Authors: Verma Sarika , Dhangar Manish , Mili Medha , Bajpai Harsh , Dwivedi Umesh , Kumari Neelam , Khan Mohammed Akram , Bhargaw Hari Narayan , Hashmi Sayed Azhar Rasheed , Srivastava Avanish Kumar 
Published: April 2022

AbstractRecently 3D printing or additive manufacturing has been one of the most popular techniques for fabricating material. 3D printing or additive manufacturing has taken over the modern material fabrication industry in a revolutionary manner. The present review focuses on designing electromagnetic interference (EMI) shielding materials by 3D printing. The various raw materials such as polylactic acid (PLA), polypropylene, graphene, carbon nanotube (CNT), multiwalled carbon nanotube (MCNT), and so forth, can be successfully used for making effective EMI shielding performances in different frequency ranges. These raw materials have prepared diverse shapes, dimensions, and compositions to attenuate the incident radiations over the shielding material's surface and ultimately protect the electronic devices. When mixed with carbon nanotubes, PLA has been shown 8–15 dB, 30 dB, and 67 dB EMI SE in different frequency ranges, a material with ABS and CNT have −3 to −16 dB reflection loss in X‐band frequency. Also graphene nanofilm/MWCNT composition has shown EMI SE as high as 43–54 dB in X‐band ranges when printed with poly jet printing. These properties gave a cutting‐edge rivalry to the conventional fabrication method and proved that 3D printing is better when designing innovation for EMI shielding materials