bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nup62 is recruited to pathological condensates and promotes TDP-43 insolubility in C9orf72 and sporadic ALS/FTLD.
Authors: Gleixner Amanda , Verdone Brandie Morris , Otte Charlton , Ramesh Nandini , Gale Jenna , Mauna Jocelyn , Mann Jacob , Copley Katie , Daley Elizabeth , Ortega Juan , Cicardi Maria , Kiskinis Evangelos , Kofler Julia , Pandey Udai , Trotti Davide , Donnelly Christopher 
Published: February 2021

Abstract
Amyotrophic lateral sclerosis (ALS) and Frontotemporal Lobar Degeneration (FTLD) share clinical, neuropathological, and genetic features. This includes common genetic disease-causing mutations such as the expanded G4C2 repeat in the C9orf72 gene (C9-ALS/FTLD) and cytoplasmic and insoluble protein depositions of the TDP-43 in degenerating regions of the brain and spinal cord. Proposed mechanisms of toxicity in C9-ALS/FTLD are the production of repeat expansion transcripts and their dipeptide repeat proteins (DPRs) products which are hypothesized to drive nucleocytoplasmic transport defects. The nuclear pore complex (NPC) regulates nucleocytoplasmic trafficking by creating a selectivity and permeability barrier comprised of phenylalanine glycine nucleoporins (FG nups). However, the relationship between FG nups and TDP-43 pathology remains elusive. Here, we define two mechanisms through which TDP-43 promotes Nup62 nuclear depletion and cytoplasmic in C9-ALS/FTLD and sALS/FTLD. In C9-ALS/FTLD, poly-GR initiates the formation of TDP-43 containing stress granules (SGs) that trigger the nuclear loss and recruitment of Nup62 in vitro and in vivo. When colocalized, cytoplasmic TDP-43:Nup62 assemblies mature into insoluble inclusions through an interaction within the TDP-43 nuclear localization sequence (NLS) suggesting Nup62 promotes deleterious phase transitions. Absent of poly-GR, aberrant TDP-43 phase transitions in the cytoplasm recruits and mislocalizes Nup62 into pathological inclusions. The result of these cytoplasmic Nup62 and TDP-43 interactions are pathological and insoluble TDP-43:Nup62 assemblies that are observed in C9-ALS/FTLD and sALS/FTLD CNS tissue.
Effect of Temperature on the Dielectric and Magnetic Properties of NiFe2O4@MgFe2O4 and ZnFe2O4@MgFe2O4 Core-Shell
Authors: Roumaih Kheled 
Published: February 2021

Abstract
The core-shell NiFe2O4@MgFe2O4 (NiF@MgF) and ZnFe2O4@MgFe2O4 (ZnF@MgF) are stable nanocomposites. The experimental results showed perfect dielectric and magnetic properties different than their components. The experimental data revealed that the mutual effect between the core and the shell increases the space charge polarization. Also, the samples showed semiconducting-metallic behavior, which varies according to the temperatures and the frequencies. Furthermore, the magnetization M(T) was studied using the Faraday balance method of all samples. The obtained results of M(T) exhibit good magnetic properties of the core-shell samples, particularly the sample ZnF@MgF, where it possesses magnetization higher than the pure ferrite phase (MgFe2O4) and Curie temperature (TCm) higher than the room temperature, and this is new for Zn-ferrite. Besides, the effective magnetic moment (µEff) and the Curie-Weiss constant (θ) were obtained from the magnetic susceptibility χ(T) protocols.
Noise Analysis and Massive MIMO Modelling in VLC for 5G Networks using EKF with SCFDM
Authors: Rajesh Sindhuja , Shankar Arathi R 
Published: February 2021

Abstract
Visible Light Communications (VLC) is the type of communication, which processes high-speed data transmission using the visible Light Emitting Diodes (LED). The VLC acts as an important supplementary that is used to define the hotspots for heterogeneous networks and plays an important role for 5G networks in wireless communications. However, performance of visible light systems is affected by various noises and Allan variance is used to analyze such noises in 5G networks. The Massive Multiple-Input and Multiple-Output (M-MIMO) technique is used for noise modeling which utilizes the mitigation circuit to find whether the noise is white noise, shot noise, random walk noises or typical noises. The existing Kalman Filter approach failed to attain the required bandwidth and higher spectral efficiency. Therefore, to achieve high data rates, the spectral efficient technologies such as Single Carrier Frequency Division Multiplexing (SCFDM) is performed in the research. The Allan Variance is utilized for analyzing the time-series that extracts the noise features of the data and the major noise is verified and considered by the M-MIMO technique. The present research uses the Extended Kalman Filter (EKF) which determines the observation models and the state transition that does not need linear functions to define the states. The proposed SCFDM was constructed based on the VLC for 5G networks that analyzes in terms of Bit Error Rate (BER) and Signal to Noise Ratio (SNR). The proposed SCFDM obtains a high SNR of 14% for the channels with white LED option when compared to the existing methods.
Clinical Outcomes and Independent Risk Factors for 90-day Mortality in Critically-ill Patients Infected with SARS CoV-2: A Multicenter Study in Turkish Intensive Care Units
Authors: Gundogan Kursat , Akbudak Ismail Hakki , Hanci Pervin , Halacli Burcin , Temel Sahin , Gullu Zuhal , Inci Kamil , Bilir Yeliz , Bozkurt Firdevs Tugba , Yildirim Fatma , Simsek Meltem , Yuksel Recep Civan , Eren Esma , Altintas Neriman Defne , Talan Leyla , Elay Gulseren , Guven Goksel , Kara Iskender , Aydin Emre , Yilmaz Seda , Mengi Tugce , Sari Sema , Akbas Turkay , Cinleti Burcu Acar , Ayhan Nazire Ates , Ozbek Deniz Aral , Sahin Taha Koray , Acikgoz Asli , Esbah Ali Umit , Firat Ahmet , Aydemir Ferhan , Gurkok Mehmet Cagatay , Zerman Avsar , Gumus Ayca , Turkoglu Melda , Aydogdu Muge , Ulu Ramazan , Celik Jale Bengi , Balci Canan , Kirakli Cenk , Karakoc Emre , Ozyilmaz Ezgi , Ersoy Ebru Ortac , Ocal Serpil , Sen Irem Akin , Tor Ibrahim Hakki , Comert Bilgin , Ergan Begum , Saracoglu Kemal Tolga , Ergil Julide , Yuksel Ummu Gulsum , Tutar Nuri , Sungur Murat , Topeli Arzu 
Published: February 2021

Abstract
PurposeThere are limited data on long-term outcome of COVID-19 from different parts of the world. The aim of this study was to determine risk factors of 90-day mortality in critically-ill patients infected with SARS-CoV-2 in Turkish ICUs. MethodsPatients with COVID-19 from26 ICUs in Turkey were included in the study. Demographics, clinical characteristics, laboratory variables, treatment, and survival data were recorded. ResultsA total of 421 patients were included. The median age was 67 (IQR: 57-76) years, and 251 patients (59.6%) were men. 90-day mortality rate was 55.1%. Factors independently associated with 90-day mortality were invasive mechanical ventilation (HR 4.09 [95% CI: 2.20-7.63]), lactate level > 2 mmol/L (2.78 [1.93-4.01]), age ≥ 60 years (2.45 [1.48-4.06)]), cardiac arrhythmia during ICU stay (2.01 [1.27-3.20]), vasopressor treatment (1.94 [1.32-2.84]), positive fluid balance of ≥ 600 ml/per day (1.68 [1.21-2.34]), PaO2/FiO2 ratio of ≤ 150 mmHg (1.66 [1.18-2.32], and ECOG score ≥ 1 (1.42 [1.00-2.02]. ConclusionThis study has shown that long-term mortality was high in critically-ill COVID-19 patients in Turkish ICUs. Invasive mechanical ventilation, high lactate level, older age, presence of cardiac arrhythmia, need for vasopressor treatment, positive fluid balance, severe hypoxemia and not having fully-active performance were related with mortality.
In vivo human molecular neuroimaging of dopaminergic vulnerability along the Alzheimer’s disease phases
Authors: Perani Daniela , Sala Arianna , Caminiti Silvia Paola , Presotto Luca , Pilotto Andrea , Liguori Claudio , Chiaravalloti Agostino , Garibotto Valentina , Frisoni Giovanni Battista , D’Amelio Marcello , Paghera Barbara , Schillaci Orazio , Mercuri Nicola , Padovani Alessandro 
Published: February 2021

Abstract
Background

Preclinical and pathology evidence suggest an involvement of brain dopamine (DA) circuitry in Alzheimer’s Disease (AD). We in vivo investigated, if, when and in which target regions, DA signaling and molecular connectivity are damaged along the AD course.

Methods

We retrospectively selected 16 amyloid-positive subjects with mild cognitive impairment due to AD (AD-MCI), 22 amyloid-positive patients with probable AD dementia (AD-D) and 74 healthy controls, all with available [123I]FP-CIT-SPECT imaging. We tested whether nigrostriatal vs. mesocorticolimbic dopaminergic targets present binding potential loss, via MANCOVA, and alterations in molecular connectivity, via partial-correlation analysis. Results were deemed significant at p<0.05, after Bonferroni correction for multiple comparisons.

Results

We found significant reductions of dopamine transporter density in both AD-MCI and AD-D compared to controls. Dopaminergic deficits were prominent in the major targets of the ventrotegmental-mesocorticolimbic pathway, namely the ventral striatum and the hippocampus, in both clinical groups, and in the cingulate gyrus, in patients with dementia only. Within the nigrostriatal projections, only the dorsal caudate nucleus showed reduced dopaminergic transporter density, in both groups. Molecular connectivity assessment revealed a widespread loss of inter-connections among subcortical and cortical targets of the mesocorticolimbic network only (poor overlap with the control group as expressed by a Dice coefficient < 0.25), and no alterations of the nigrostriatal network (high overlap with controls, Dice coefficient = 1).

Conclusion

Local and system-level alterations of the mesocorticolimbic dopaminergic circuitry characterize AD, already in prodromal disease phases. These results might foster new therapeutic strategies for AD. The clinical correlates of these findings deserve to be carefully considered within the emergence of both neuropsychiatric symptoms and cognitive deficits.
Impact of Covid-19 Disease and National Lockdown on Outcomes of Emergency Surgery. Results From A Retrospective Comparative Cohort Study In A Tertiary Referral Teaching Hospital
Authors: Ciarleglio Francesco Antonio , Rigoni Marta , Mereu Liliana , Cai Tommaso , Carrara Alessandro , Malossini Gianni , Tateo Saverio , Tirone Giuseppe , Johansen Truls E Bjerklund , Benetollo Pier Paolo , Ferro Antonio , Guarrera Giovanni Maria , Grattarola Mario , Nollo Giandomenico , Brolese Alberto 
Published: February 2021

Abstract
BACKGROUND: The aim of this retrospective comparative study was to assess the impact of the COVID-19 related disease on emergency surgery, comparing clinical main outcomes in the period March –May 2019 (Group 1) with the same period in Covid-19 Italian lockdown (March-May 2020, Group 2).METHODS: A comparison (Group 1 versus 2) was performed between the demographic, anamnestic, surgical, clinical and management features.RESULTS: 246 patients were included, 137 in Group 1 and 109 in Group 2 (p=0.03). No significant differences in peri-operative characteristics were registered. A declared delay in access to hospital and SARS-CoV-2 preoperatively infection rates were 15.5% and 5.8% respectively in Group 2. The overall morbidity (OR=2.22, 95%CI=1.08-4.55, p=0.03) and 30-day mortality (OR=1.34, 95%CI=0.33-5.50, =0.68) increased significantly in Group 2. Delayed access cohort demonstrated a close correlation with increased morbidity (OR=3.19, 95%CI=0.89-11.44, p=0.07), blood transfusion (OR=5.13, 95%CI=1.05-25.15, p=0.04) and a 30-day mortality risk (OR=8.00, 95%CI=1.01-63.23, p=0.05). Positive SARS-CoV-2 patients had higher risk of blood transfusion (20% vs 7.8%, p= 0.37), ICU admissions (20% vs 2.6%, p= 0.17) and median LOS (9 days vs 4 days, p= 0.11). CONCLUSIONS: This article provides enhanced understanding of the effects of the COVID-19 pandemic on patients access to emergency surgical care. Our findings suggest that COVID-19 changed the quality of surgical care with poorer prognosis and higher morbidity rates. A delayed Emergency Department access and a “filter effect” induced by a COVID-fear in the population resulted in only the most severe cases reaching the Emergency Department in time.
Targeting SARS-CoV-2 receptor-binding domain to cells expressing CD40 improves protection to infection in convalescent macaques
Authors: Marlin Romain , Godot Véronique , Cardinaud Sylvain , Galhaut Mathilde , Coleon Severin , Zurawski Sandra , Dereuddre-Bosquet Nathalie , Cavarelli Mariangela , Gallouet Anne-Sophie , Prague Mélanie , Maisonnasse Pauline , Dupaty Léa , Fenwick Craig , Naninck Thibaut , Lemaitre Julien , Gomez-Pacheco Mario , Kahlaoui Nidhal , Contreras Vanessa , Relouzat Francis , Fang Raphael Ho Tsong , Wang Zhiqing , III Jerome Ellis , Chapon Catherine , Centlivre Mireille , Szurgot Inga , Liljeström Peter , Werf Sylvie van der , Pantaleo Giuseppe , Thiébaut Rodolphe , Zurawski Gerard , Levy Yves , Grand Roger Le 
Published: February 2021

Abstract
Controlling the circulation of the recently emerged SARS-CoV-2 in the human populations requires massive vaccination campaigns. Achieving sufficient worldwide vaccination coverage will require additional approaches to first generation of approved viral vector and mRNA vaccines. Subunit vaccines have excellent safety and efficacy records and may have distinct advantages, in particular when immunizing individuals with vulnerabilities or when considering the vaccination of children and pregnant women. We have developed a new generation of subunit vaccines with enhanced immunogenicity by the targeting of viral antigens to CD40-expressing antigen-presenting cells, thus harnessing their intrinsic immune-stimulant properties. Here, we demonstrate that targeting the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein to CD40 (αCD40.RBD) induces significant levels of specific T and B cells, with a long-term memory phenotype, in a humanized mouse model. In addition, we demonstrate that a single dose of the αCD40.RBD vaccine, injected without adjuvant, is sufficient to boost a rapid increase in neutralizing antibodies in convalescent non-human primates (NHPs) exposed six months previously to SARS-CoV-2. Such vaccination thus significantly improved protection against a new high-dose virulent challenge versus that in non-vaccinated convalescent animals. Viral dynamics modelling showed the high efficiency of the vaccine at controlling the viral dissemination.
The Link Between Bacterial Inflammagens, Leaky Gut Syndrome and
Colorectal Cancer
Authors: de Waal Greta M , de Villiers Willem J.S. , Pretorius Etheresia 
Published: February 2021

:
There is a causal relationship between cancer (including colorectal cancer), chronic systemic inflammation and persistent infections, and the presence of dysregulated circulating inflammatory markers. It is known that aberrant clot formation and coagulopathies occur in systemic inflammation. In colorectal cancer, there is close link between gut dysbiosis and an inflammatory profile. In this review we present evidence of the connection between gut dysbiosis, the entry of bacteria into the internal environment and the presence of their highly potent inflammagenic molecules, such as lipopolysaccharide and lipoteichoic acid, in circulation. These bacterial components may act as one of the main drivers of the inflammatory process (including hypercoagulation) in colorectal cancer. We review literature that points to the role of these bacterial inflammagens and how they contribute to colorectal carcinogenesis. Insight into the factors that promote carcinogenesis is crucial to effectively prevent and screen for colorectal cancer. Early diagnosis of an activated coagulation system and the detection of bacterial components in circulation and also in the tumour microenvironment, could therefore be important, and may also, together with modulation of the gut microbiota, serve as potential therapeutic targets.
The Impact of Uncontrolled Hypertension on the Longitudinal Systolic
Function of the Left Ventricle
Authors: Bendiab Nabila Soufi Taleb , Benkhedda Salim , Henaoui Latifa , Tani Abderrahim Meziane 
Published: February 2021

Background:
The assessment of the longitudinal component of left ventricular (LV)
function is of major clinical importance for the early detection of LV contractile impairment. The
aim of this study was to determine the impact of uncontrolled hypertension, on LV longitudinal systolic
performance.

Methods:
The study population included 400 hypertensive patients: 271 patients with uncontrolled
blood pressure (BP) and 112 without controlled BP, all patients underwent a complete ultrasound
evaluation with the calculation of the LV mass, evaluation of diastolic function as well as longitudinal
systolic function.

Results:
Conventional echo demonstrated that uncontrolled patients had increased LV mass (P
0.007), LA (left auricular) dimension (P 0.004), left ventricular wall thickness and impairment of
diastolic function (E/E’6 ± 2.1 vs 7.4 ±3.0 P=0.001) while no affection of systolic function could
be detected. By deformation imaging, there was a reduction in longitudinal strain (apical 4 view
-16.2 ±2.9 vs -18.2± 2.6 P 0.02, apical 3 view -17.3 ± 3.3 vs. -18.9 ± 4.1 P 0.01). Similarly, systolic
strain rate (SRsys) and early diastolic SR (SRe) reduced significantly in longitudinal direction.

Conclusion:
Although EF was not different between uncontrolled patients and controls, LV longitudinal
strain and strain rate by 2D speckle tracking were lower in the uncontrolled group.
Multi-Class Breast Cancer Classification Using Ensemble of Pretrained models and Transfer Learning
Authors: Singh Sanjay Kumar , Rao Perumalla Murali Mallikarjuna , Khamparia Aditya , Bhushan Bharat , Podder Prajoy 
Published: February 2021

Aims:
Early detection of breast cancer has reduced many deaths. Earlier CAD systems
used to be the second opinion for radiologists and clinicians. Machine learning and deep learning
have brought tremendous changes in medical diagnosis and imagining.

Background:
Breast cancer is the most commonly occurring cancer in women and it is the second
most common cancer overall. According to the 2018 statistics, there were over 2million cases all
over the world. Belgium and Luxembourg have the highest rate of cancer.

Objective:
A method for breast cancer detection has been proposed using Ensemble learning. 2-
class and 8-class classification is performed.

Method:
To deal with imbalance classification, the authors have proposed an ensemble of pretrained
models.

Result:
98.5% training accuracy and 89% of test accuracy are achieved on 8-class classification.
Moreover, 99.1% and 98% train and test accuracy are achieved on 2 class classification.

Conclusion:
it is found that there are high misclassifications in class DC when compared to the
other classes, this is due to the imbalance in the dataset. In the future, one can increase the size of
the datasets or use different methods. In implement this research work, authors have used 2 Nvidia
Tesla V100 GPU’s in google cloud platform.
Natural Product as Substrates of ABC Transporters: A Review
Authors: Chen Xuan-Yu , Wang Jing-Quan , Yang Yuqi , Li Jing , Chen Zhe-Sheng 
Published: February 2021

Background:
To date, many compounds extracted from natural products have anti-tumor
activity, such as citronellol, ellagitannin-containing pomegranate extract, etc. Evidence from
clinical context shows that multidrug resistance is an obstacle that impedes the effectiveness of natural
products, such as chemotherapeutic agents, paclitaxel and vincristine. Overexpression of ATP-
Binding Cassette (ABC) transporters is the leading cause of MDR. Therefore, it is crucial to investigate
whether these natural products are substrates of MDR-associated ABC transporters,
which may benefit the development of their clinical usage.

Objective:
This review summarizes the latest insight on natural products possessing substrate profile and analyzed some possible regularity to provide direction for future drug discovery.

Conclusion:
The anti-tumor effects of natural products are constantly being explored, but the drug
resistance issues cannot be ignored, which limits their prospects as anti-tumor drugs to a certain extent.
At the same time, some natural products are taken as a daily diet, and their possible role in increasing
the drug resistance of the substrate should arouse the attention of clinical cancer patients.
Extracting Drug Names and Associated Attributes From Discharge Summaries: Text Mining Study
Authors: Alfattni Ghada , Belousov Maksim , Peek Niels , Nenadic Goran 
Published: February 2021

Background
Drug prescriptions are often recorded in free-text clinical narratives; making this information available in a structured form is important to support many health-related tasks. Although several natural language processing (NLP) methods have been proposed to extract such information, many challenges remain.

Objective
This study evaluates the feasibility of using NLP and deep learning approaches for extracting and linking drug names and associated attributes identified in clinical free-text notes and presents an extensive error analysis of different methods. This study initiated with the participation in the 2018 National NLP Clinical Challenges (n2c2) shared task on adverse drug events and medication extraction.

Methods
The proposed system (DrugEx) consists of a named entity recognizer (NER) to identify drugs and associated attributes and a relation extraction (RE) method to identify the relations between them. For NER, we explored deep learning-based approaches (ie, bidirectional long-short term memory with conditional random fields [BiLSTM-CRFs]) with various embeddings (ie, word embedding, character embedding [CE], and semantic-feature embedding) to investigate how different embeddings influence the performance. A rule-based method was implemented for RE and compared with a context-aware long-short term memory (LSTM) model. The methods were trained and evaluated using the 2018 n2c2 shared task data.

Results
The experiments showed that the best model (BiLSTM-CRFs with pretrained word embeddings [PWE] and CE) achieved lenient micro F-scores of 0.921 for NER, 0.927 for RE, and 0.855 for the end-to-end system. NER, which relies on the pretrained word and semantic embeddings, performed better on most individual entity types, but NER with PWE and CE had the highest classification efficiency among the proposed approaches. Extracting relations using the rule-based method achieved higher accuracy than the context-aware LSTM for most relations. Interestingly, the LSTM model performed notably better in the reason-drug relations, the most challenging relation type.

Conclusions
The proposed end-to-end system achieved encouraging results and demonstrated the feasibility of using deep learning methods to extract medication information from free-text data.