bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis of the critical dose of radiation therapy in the incidence of Osteoradionecrosis in head and neck cancer patients: a case series
Authors: Iqbal Zain , Kyzas Panayiotis 
Published: September 2020

Abstract
Introduction
Osteoradionecrosis (ORN) is a dramatic complication following radiation therapy (RT) for head and neck tumours. Symptoms include pain, trismus, and malodour. ORN can present with exposed necrotic bone, an orocutaneous fistula, and/ or a pathological fracture.

Aims
To analyse the RT dose responsible for the pathogenesis of ORN and its associated risk factors.

Methods
The data of 17 patients from 2005 to 2017 were retrospectively reviewed from the Pinnacle(3), WebPublication, and Electronic patient records (EPR) provided by Christie Hospital and Pennine Acute NHS Trust.

Results
The mean RT dose that ORN sites received was 57.3 Gy. The mean onset duration for ORN after RT was 640.6 days. six patients (35.2%) developed ORN following post-RT dental extractions.

Conclusion
RT dosages of >57.3 Gy significantly increase the likelihood of developing ORN. Mandibular surgery, post-RT dental extraction, concurrent smoking, and alcohol abuse all amplify the risk of developing ORN.
COVID19: an announced pandemic
Authors: Platto Sara , Xue Tongtong , Carafoli Ernesto 
Published: September 2020

AbstractA severe upper respiratory tract syndrome caused by the new coronavirus has now spread to the entire world as a highly contagious pandemic. The large scale explosion of the disease is conventionally traced back to January of this year in the Chinese province of Hubei, the wet markets of the principal city of Wuhan being assumed to have been the specific causative locus of the sudden explosion of the infection. A number of findings that are now coming to light show that this interpretation of the origin and history of the pandemic is overly simplified. A number of variants of the coronavirus would in principle have had the ability to initiate the pandemic well before January of this year. However, even if the COVID-19 had become, so to say, ready, conditions in the local environment would have had to prevail to induce the loss of the biodiversity’s “dilution effect” that kept the virus under control, favoring its spillover from its bat reservoir to the human target. In the absence of these appropriate conditions only abortive attempts to initiate the pandemic could possibly occur: a number of them did indeed occur in China, and probably elsewhere as well. These conditions were unfortunately present at the wet marked in Wuhan at the end of last year.
2D and 3D convolutional neural networks for outcome modelling of locally advanced head and neck squamous cell carcinoma
Authors: Starke Sebastian , Leger Stefan , Zwanenburg Alex , Leger Karoline , Lohaus Fabian , Linge Annett , Schreiber Andreas , Kalinauskaite Goda , Tinhofer Inge , Guberina Nika , Guberina Maja , Balermpas Panagiotis , von der Grün Jens , Ganswindt Ute , Belka Claus , Peeken Jan C. , Combs Stephanie E. , Boeke Simon , Zips Daniel , Richter Christian , Troost Esther G. C. , Krause Mechthild , Baumann Michael , Löck Steffen 
Published: September 2020

AbstractFor treatment individualisation of patients with locally advanced head and neck squamous cell carcinoma (HNSCC) treated with primary radiochemotherapy, we explored the capabilities of different deep learning approaches for predicting loco-regional tumour control (LRC) from treatment-planning computed tomography images. Based on multicentre cohorts for exploration (206 patients) and independent validation (85 patients), multiple deep learning strategies including training of 3D- and 2D-convolutional neural networks (CNN) from scratch, transfer learning and extraction of deep autoencoder features were assessed and compared to a clinical model. Analyses were based on Cox proportional hazards regression and model performances were assessed by the concordance index (C-index) and the model’s ability to stratify patients based on predicted hazards of LRC. Among all models, an ensemble of 3D-CNNs achieved the best performance (C-index 0.31) with a significant association to LRC on the independent validation cohort. It performed better than the clinical model including the tumour volume (C-index 0.39). Significant differences in LRC were observed between patient groups at low or high risk of tumour recurrence as predicted by the model ($$p=0.001$$

p
=
0.001

). This 3D-CNN ensemble will be further evaluated in a currently ongoing prospective validation study once follow-up is complete.
Cilia interactome with predicted protein–protein interactions reveals connections to Alzheimer’s disease, aging and other neuropsychiatric processes
Authors: Karunakaran Kalyani B. , Chaparala Srilakshmi , Lo Cecilia W. , Ganapathiraju Madhavi K. 
Published: September 2020

AbstractCilia are dynamic microtubule-based organelles present on the surface of many eukaryotic cell types and can be motile or non-motile primary cilia. Cilia defects underlie a growing list of human disorders, collectively called ciliopathies, with overlapping phenotypes such as developmental delays and cognitive and memory deficits. Consistent with this, cilia play an important role in brain development, particularly in neurogenesis and neuronal migration. These findings suggest that a deeper systems-level understanding of how ciliary proteins function together may provide new mechanistic insights into the molecular etiologies of nervous system defects. Towards this end, we performed a protein–protein interaction (PPI) network analysis of known intraflagellar transport, BBSome, transition zone, ciliary membrane and motile cilia proteins. Known PPIs of ciliary proteins were assembled from online databases. Novel PPIs were predicted for each ciliary protein using a computational method we developed, called High-precision PPI Prediction (HiPPIP) model. The resulting cilia “interactome” consists of 165 ciliary proteins, 1,011 known PPIs, and 765 novel PPIs. The cilia interactome revealed interconnections between ciliary proteins, and their relation to several pathways related to neuropsychiatric processes, and to drug targets. Approximately 184 genes in the cilia interactome are targeted by 548 currently approved drugs, of which 103 are used to treat various diseases of nervous system origin. Taken together, the cilia interactome presented here provides novel insights into the relationship between ciliary protein dysfunction and neuropsychiatric disorders, for e.g. interconnections of Alzheimer’s disease, aging and cilia genes. These results provide the framework for the rational design of new therapeutic agents for treatment of ciliopathies and neuropsychiatric disorders.
Long-term motor skill training with individually adjusted progressive difficulty enhances learning and promotes corticospinal plasticity
Authors: Christiansen Lasse , Larsen Malte Nejst , Madsen Mads Just , Grey Michael James , Nielsen Jens Bo , Lundbye-Jensen Jesper 
Published: September 2020

AbstractMotor skill acquisition depends on central nervous plasticity. However, behavioural determinants leading to long lasting corticospinal plasticity and motor expertise remain unexplored. Here we investigate behavioural and electrophysiological effects of individually tailored progressive practice during long-term motor skill training. Two groups of participants practiced a visuomotor task requiring precise control of the right digiti minimi for 6 weeks. One group trained with constant task difficulty, while the other group trained with progressively increasing task difficulty, i.e. continuously adjusted to their individual skill level. Compared to constant practice, progressive practice resulted in a two-fold greater performance at an advanced task level and associated increases in corticospinal excitability. Differences were maintained 8 days later, whereas both groups demonstrated equal retention 14 months later. We demonstrate that progressive practice enhances motor skill learning and promotes corticospinal plasticity. These findings underline the importance of continuously challenging patients and athletes to promote neural plasticity, skilled performance, and recovery.
Iodine nanoparticle radiotherapy of human breast cancer growing in the brains of athymic mice
Authors: Hainfeld James F. , Ridwan Sharif M. , Stanishevskiy F. Yaroslav , Smilowitz Henry M. 
Published: September 2020

AbstractAbout 30% of breast cancers metastasize to the brain; those widely disseminated are fatal typically in 3–4 months, even with the best available treatments, including surgery, drugs, and radiotherapy. To address this dire situation, we have developed iodine nanoparticles (INPs) that target brain tumors after intravenous (IV) injection. The iodine then absorbs X-rays during radiotherapy (RT), creating free radicals and local tumor damage, effectively boosting the local RT dose at the tumor. Efficacy was tested using the very aggressive human triple negative breast cancer (TNBC, MDA-MB-231 cells) growing in the brains of athymic nude mice. With a well-tolerated non-toxic IV dose of the INPs (7 g iodine/kg body weight), tumors showed a heavily iodinated rim surrounding the tumor having an average uptake of 2.9% iodine by weight, with uptake peaks at 4.5%. This is calculated to provide a dose enhancement factor of approximately 5.5 (peaks at 8.0), the highest ever reported for any radiation-enhancing agents. With RT alone (15 Gy, single dose), all animals died by 72 days; INP pretreatment resulted in longer-term remissions with 40% of mice surviving 150 days and 30% surviving > 280 days.
Site-selective mapping of metastable states using electron-beam induced luminescence microscopy
Authors: Kumar R. , Martin L. I. D. J. , Poelman D. , Vandenberghe D. , De Grave J. , Kook M. , Jain M. 
Published: September 2020

AbstractMetastable states created by electron or hole capture in crystal defects are widely used in dosimetry and photonic applications. Feldspar, the most abundant mineral in the Earth’s crust (> 50%), generates metastable states with lifetimes of millions of years upon exposure to ionizing radiation. Although feldspar is widely used in dosimetry and geochronometry, the creation of metastable states and charge transfer across them is poorly understood. Understanding such phenomena requires next-generation methods based on high-resolution, site-selective probing of the metastable states. Recent studies using site-selective techniques such as photoluminescence (PL), and radioluminescence (RL) at 7 K have revealed that feldspar exhibits two near-infrared (NIR) emission bands peaking at 880 nm and 955 nm, which are believed to arise from the principal electron-trapping states. Here, we map for the first time the electron-trapping states in potassium-rich feldspar using spectrally-resolved cathodoluminescence microscopy at a spatial resolution of ~ 6 to 22 µm. Each pixel probed by a scanning electron microscope provides us a cathodoluminescence spectrum (SEM-CL) in the range 600–1000 nm, and elemental data from energy-dispersive x-ray (EDX) spectroscopy. We conclude that the two NIR emissions are spatially variable and, therefore, originate from different sites. This conclusion contradicts the existing model that the two emissions arise from two different excited states of a principal trap. Moreover, we are able to link the individual NIR emission peaks with the geochemical variations (K, Na and Fe concentration), and propose a model that explains the quenching of the NIR emission by Fe4+. Our study contributes to an improved understanding of charge storage in feldspathic minerals, with implications for developing sub-single grain (micrometer scale) measurement techniques in radiation dosimetry.
Novel targets identified by integrated proteomic and phosphoproteomic analysis in spermatogenesis of swamp buffalo (Bubalus bubalis)
Authors: Huang Yu-lin , Zhang Peng-fei , Fu Qiang , He Weng-tan , Xiao Kai , Zhang Ming 
Published: September 2020

AbstractTo understand mechanisms of spermatogenesis, the proteome and the phosphoproteome in prepubertal and pubertal swamp buffalo (Bubalus bubalis) testes were analyzed using tandem mass tag (TMT) coupled with liquid chromatography-tandem mass spectrometry (LC–MS/MS). In prepubertal testes, 80 proteins were overexpressed, 148 proteins were underexpressed, and 139 and 142 protein sites had higher and lower phosphorylation, respectively, compared to the levels in pubertal testes. Several of these proteins were associated with reproductive processes such as sexual reproduction, spermatogenesis, fertilization, and spermatid development. In particular, outer dense fiber protein 1 (ODF1), protein maelstrom homolog (MAEL), actin-like protein 7B (ACTL7B), tyrosine-(Y)-phosphorylation regulated (CABYR), and tripartite motif containing 36 (TRIM36) were upregulated with age at both the proteome and phosphoproteome levels. Combining proteome and phosphoproteome analysis can be effectively applied to study the protein/phosphorylation patterns of buffalo testes. These data provide new regulatory candidates and evidence for a complex network in spermatogenesis in buffalo testes, and serve as an important resource for exploring the physiological mechanism of spermatogenesis in mammals.
Automated rotator cuff tear classification using 3D convolutional neural network
Authors: Shim Eungjune , Kim Joon Yub , Yoon Jong Pil , Ki Se-Young , Lho Taewoo , Kim Youngjun , Chung Seok Won 
Published: September 2020

AbstractRotator cuff tear (RCT) is one of the most common shoulder injuries. When diagnosing RCT, skilled orthopedists visually interpret magnetic resonance imaging (MRI) scan data. For automated and accurate diagnosis of RCT, we propose a full 3D convolutional neural network (CNN) based method using deep learning. This 3D CNN automatically diagnoses the presence or absence of an RCT, classifies the tear size, and provides 3D visualization of the tear location. To train the 3D CNN, the Voxception-ResNet (VRN) structure was used. This architecture uses 3D convolution filters, so it is advantageous in extracting information from 3D data compared with 2D-based CNNs or traditional diagnosis methods. MRI data from 2,124 patients were used to train and test the VRN-based 3D CNN. The network is trained to classify RCT into five classes (None, Partial, Small, Medium, Large-to-Massive). A 3D class activation map (CAM) was visualized by volume rendering to show the localization and size information of RCT in 3D. A comparative experiment was performed for the proposed method and clinical experts by using randomly selected 200 test set data, which had been separated from training set. The VRN-based 3D CNN outperformed orthopedists specialized in shoulder and general orthopedists in binary accuracy (92.5% vs. 76.4% and 68.2%), top-1 accuracy (69.0% vs. 45.8% and 30.5%), top-1±1 accuracy (87.5% vs. 79.8% and 71.0%), sensitivity (0.92 vs. 0.89 and 0.93), and specificity (0.86 vs. 0.61 and 0.26). The generated 3D CAM provided effective information regarding the 3D location and size of the tear. Given these results, the proposed method demonstrates the feasibility of artificial intelligence that can assist in clinical RCT diagnosis.
Quantum circuit optimization using quantum Karnaugh map
Authors: Bae J.-H. , Alsing Paul M. , Ahn Doyeol , Miller Warner A. 
Published: September 2020

AbstractEvery quantum algorithm is represented by set of quantum circuits. Any optimization scheme for a quantum algorithm and quantum computation is very important especially in the arena of quantum computation with limited number of qubit resources. Major obstacle to this goal is the large number of elemental quantum gates to build even small quantum circuits. Here, we propose and demonstrate a general technique that significantly reduces the number of elemental gates to build quantum circuits. This is impactful for the design of quantum circuits, and we show below this could reduce the number of gates by 60% and 46% for the four- and five-qubit Toffoli gates, two key quantum circuits, respectively, as compared with simplest known decomposition. Reduced circuit complexity often goes hand-in-hand with higher efficiency and bandwidth. The quantum circuit optimization technique proposed in this work would provide a significant step forward in the optimization of quantum circuits and quantum algorithms, and has the potential for wider application in quantum computation.
Development and validation of a prediction model on severe maternal outcomes among pregnant women with pre-eclampsia: a 10-year cohort study
Authors: Tan Jing , Yang Min , Liao Yuan , Qi Yana , Ren Yan , Liu Chunrong , Huang Shiyao , Thabane Lehana , Liu Xinghui , Sun Xin 
Published: September 2020

AbstractPre-eclampsia is a severe hypertensive disorder of pregnancy and could lead to severe maternal morbidities and death. Our study aimed to develop and validate a prognostic prediction model for severe maternal outcomes among Chinese population with pre-eclampsia. We conducted a 10-year cohort study in a referral center by collecting all pregnant women who diagnosed as pre-eclampsia and delivered from 2005 to 2014. A composite of severe maternal outcomes, including maternal near-miss defined by World Health Organization, cortical blindness/retinal detachment, temporary facial paralysis and maternal death, were adopted. We used logistic regression model to develop Model 1 by retaining the predictors of p < 0.05, and further conducted Model 2 by adding quadratic terms and interaction terms to Model 1. We undertook a bootstrapping validation and estimated the model performance. A total of 397 pregnant women suffered from severe maternal outcomes among 2,793 eligible participants, with an incidence of 14.21% (95% confidence interval (CI) 12.91%–15.51%). Of 13 predictors were finally selected in Model 1. Combined with quadratic and interactive terms, the Model 2 showed higher area under the ROC curve (82.2%, 95% CI 79.6%–84.7%) and good calibration. By the bootstrapping validation, similar model performances were present.
Comparison of the incidences of anastomotic leakage when PDSII or LACLON are used in esophago-gastric conduit handsewn anastomosis after esophagectomy
Authors: Sato Yusuke , Motoyama Satoru , Wakita Akiyuki , Kawakita Yuta , Nagaki Yushi , Terata Kaori , Imai Kazuhiro , Minamiya Yoshihiro 
Published: September 2020

AbstractThe incidence of anastomotic leakage after esophagectomy remains around 10%. It was previously reported that PDSII rapidly loses tensile strength at pH 1.0 and pH 8.5. By contrast, LACLON degradation is reportedly insensitive to pH. We therefore compared LACLON with PDSII for esophago-gastric conduit, layer-to-layer, handsewn anastomosis. Between January 2016 and January 2020, 90 patients who received posterior mediastinal gastric conduit reconstruction with layer-to-layer handsewn anastomosis (51 using PDSII and 39 using LACLON) at Akita University Hospital were enrolled. The incidence of anastomotic leakage was significantly lower in the LACLON (2.6%, 1/39 patients) than PDSII group (15.7%, 8/51 patients) (p = 0.0268). Multivariable logistic analysis showed the risk of anastomotic leakage was significantly greater with PDSII than LACLON (odds ratio 11.01; 95% CI 1.326–277.64; p = 0.024). The percentages of time the pH was higher than 8 on the gastric conduit side of the anastomosis were 3.1%, 5.7%, 20.9% and 80.5%, respectively, in the four most recent patients. The present study showed that pH at the anastomosis soon after esophagectomy tends to be alkaline rather than acidic, which raises the possibility that this alkalinity facilitates the deterioration of surgical sutures including PDSII.
Dysregulation of metabolic pathways by carnitine palmitoyl-transferase 1 plays a key role in central nervous system disorders: experimental evidence based on animal models
Authors: Trabjerg Michael Sloth , Mørkholt Anne Skøttrup , Lichota Jacek , Oklinski Michal Krystian Egelund , Andersen Dennis Christian , Jønsson Katrine , Mørk Kasper , Skjønnemand Marie-Louise Nibelius , Kroese Lona John , Pritchard Colin Eliot Jason , Huijbers Ivo Johan , Gazerani Parisa , Corthals Angelique , Nieland John Dirk Vestergaard 
Published: September 2020

AbstractThe etiology of CNS diseases including multiple sclerosis, Parkinson’s disease and amyotrophic lateral sclerosis remains elusive despite decades of research resulting in treatments with only symptomatic effects. In this study, we provide evidence that a metabolic shift from glucose to lipid is a key mechanism in neurodegeneration. We show that, by downregulating the metabolism of lipids through the key molecule carnitine palmitoyl transferase 1 (CPT1), it is possible to reverse or slowdown disease progression in experimental models of autoimmune encephalomyelitis-, SOD1G93A and rotenone models, mimicking these CNS diseases in humans. The effect was seen both when applying a CPT1 blocker or by using a Cpt1a P479L mutant mouse strain. Furthermore, we show that diet, epigenetics, and microbiota are key elements in this metabolic shift. Finally, we present a systemic model for understanding the complex etiology of neurodegeneration and how different regulatory systems are interconnected through a central metabolic pathway that becomes deregulated under specific conditions.
High-resolution crystal structure and biochemical characterization of a GH11 endoxylanase from Nectria haematococca
Authors: Andaleeb Hina , Ullah Najeeb , Falke Sven , Perbandt Markus , Brognaro Hévila , Betzel Christian 
Published: September 2020

AbstractEnzymatic degradation of vegetal biomass offers versatile procedures to improve the production of alternative fuels and other biomass-based products. Here we present the three-dimensional structure of a xylanase fromNectria haematococca(NhGH11) at 1.0 Å resolution and its functional properties. The atomic resolution structure provides details and insights about the complex hydrogen bonding network of the active site region and allowed a detailed comparison with homologous structures. Complementary biochemical studies showed that the xylanase can catalyze the hydrolysis of complex xylan into simple xylose aldopentose subunits of different lengths. NhGH11 can catalyze the efficient breakdown of beechwood xylan, xylan polysaccharide, and wheat arabinoxylan with turnover numbers of 1730.6 ± 318.1 min−1, 1648.2 ± 249.3 min−1and 2410.8 ± 517.5 min−1respectively. NhGH11 showed maximum catalytic activity at pH 6.0 and 45 °C. The mesophilic character of NhGH11 can be explained by distinct structural features in comparison to thermophilic GH11 enzymes, including the number of hydrogen bonds, side chain interactions and number of buried water molecules. The enzymatic activity of NhGH11 is not very sensitive to metal ions and chemical reagents that are typically present in associated industrial production processes. The data we present highlights the potential of NhGH11 to be applied in industrial biomass degradation processes.