bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting progression and cognitive decline in amyloid-positive patients with Alzheimer’s disease
Authors: Dansson Hákon Valur , Stempfle Lena , Egilsdóttir Hildur , Schliep Alexander , Portelius Erik , Blennow Kaj , Zetterberg Henrik , Johansson Fredrik D. ,   for the Alzheimer’s Disease Neuroimaging Initiative (ADNI)
Published: September 2021

AbstractBackgroundIn Alzheimer’s disease, amyloid-β(Aβ) peptides aggregate in the lowering CSF amyloid levels - a key pathological hallmark of the disease. However, lowered CSF amyloid levels may also be present in cognitively unimpaired elderly individuals. Therefore, it is of great value to explain the variance in disease progression among patients with Aβpathology.MethodsA cohort ofn=2293 participants, of whomn=749 were Aβpositive, was selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database to study heterogeneity in disease progression for individuals with Aβpathology. The analysis used baseline clinical variables including demographics, genetic markers, and neuropsychological data to predict how the cognitive ability and AD diagnosis of subjects progressed using statistical models and machine learning. Due to the relatively low prevalence of Aβpathology, models fit only to Aβ-positive subjects were compared to models fit to an extended cohort including subjects without established Aβpathology, adjusting for covariate differences between the cohorts.ResultsAβpathology status was determined based on the Aβ42/Aβ40ratio. The best predictive model of change in cognitive test scores for Aβ-positive subjects at the 2-year follow-up achieved anR2score of 0.388 while the best model predicting adverse changes in diagnosis achieved a weightedF1score of 0.791. Aβ-positive subjects declined faster on average than those without Aβpathology, but the specific level of CSF Aβwas not predictive of progression rate. When predicting cognitive score change 4 years after baseline, the best model achieved anR2score of 0.325 and it was found that fitting models to the extended cohort improved performance. Moreover, using all clinical variables outperformed the best model based only on a suite of cognitive test scores which achieved anR2score of 0.228.ConclusionOur analysis shows that CSF levels of Aβare not strong predictors of the rate of cognitive decline in Aβ-positive subjects when adjusting for other variables. Baseline assessments of cognitive function accounts for the majority of variance explained in the prediction of 2-year decline but is insufficient for achieving optimal results in longer-term predictions. Predicting changes both in cognitive test scores and in diagnosis provides multiple perspectives of the progression of potential AD subjects.
Late reinfection with a different severe acute respiratory syndrome coronavirus-2 clade in a patient with refractory arterial hypertension: a case report
Authors: García-Abellán Javier , Galiana Antonio , Fernández-González Marta , Gonzalo-Jiménez Nieves , Ruiz-García Montserrat , Botella Angela , Sanchis Joan , Mascarell Paula , Falcón Selene , Masiá Mar , Gutiérrez Félix 
Published: September 2021

Abstract
Background
Differentiating between persistent infection with intermittent viral shedding and reinfection with severe acute respiratory syndrome coronavirus 2 remains challenging. Although a small number of cases with genomic evidence of second infection have been reported, limited information exists on frequency and determinants of reinfection, time between infections, and duration of immunity after the primary infection.

Case presentation
We report a reinfection with severe acute respiratory syndrome coronavirus 2 in a 52-year-old caucasian male whose primary infection was diagnosed in May 2020, during the first wave of the pandemic in Spain, and the second occurred 8 months later, in January 2021. We present a complete dataset including results from real-time polymerase chain reaction, serology, and genome sequencing confirming reinfection with a different clade. Noteworthy was that the patient was immunocompetent but had multiple cardiometabolic comorbidities, including refractory arterial hypertension, that might increase the individual risk in coronavirus disease 2019.

Conclusions
This case of reinfection with severe acute respiratory syndrome coronavirus 2 occurring several months after the primary infection reports the longest time interval between reinfection and initial infection described to date. It raises concerns on the duration of protective immunity, suggesting that it may begin to wane in patients who acquired the initial infection during the first wave of the pandemic. The potential contributing role of arterial hypertension and cardiometabolic comorbidities as risk factors for reinfection deserves investigation.
Translational models of 3-D organoids and cancer stem cells in gastric cancer research
Authors: Wuputra Kenly , Ku Chia-Chen , Kato Kohsuke , Wu Deng-Chyang , Saito Shigeo , Yokoyama Kazunari K. 
Published: September 2021

AbstractIt is postulated as a general concept of cancer stem cells (CSCs) that they can produce cancer cells overtly and repopulate cancer progenitor cells indefinitely. The CSC niche is part of a specialized cancer microenvironment that is important to keep the phenotypes of CSCs. Stem cell- and induced pluripotent stem cell (iPSC)-derived organoids with genetic manipulation are beneficial to the investigation of the regulation of the microenvironment of CSCs. It would be useful to assess the efficiency of the cancer microenvironment on initiation and progression of cancers. To identify CSCs in cancer tissues, normal cell organoids and gastric cancer organoids from the cancerous areas, as well as iPSCs, were established several years ago. However, many questions remain about the extent to which these cultures recapitulate the development of the gastrointestinal tract and the mechanism of Helicobacter pylori-induced cancer progression. To clarify the fidelity of human organoid models, we have noted several key issues for the cultivation of, and differences between, normal and cancerous organoids. We developed precise culture conditions for gastric organoids in vitro to improve the accuracy of the generation of organoid models for therapeutic and medical applications. In addition, the current knowledge on gastrointestinal CSC research, including the topic of CSC markers, cancer cell reprogramming, and application to target cancer cell plasticity through niches, should be reinforced. We discuss the progression of cancers derived from human gastric organoids and the identification of CSCs.
Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop
Authors: Ntie-Kang Fidele , Telukunta Kiran K. , Fobofou Serge A. T. , Chukwudi Osamor Victor , Egieyeh Samuel A. , Valli Marilia , Djoumbou-Feunang Yannick , Sorokina Maria , Stork Conrad , Mathai Neann , Zierep Paul , Chávez-Hernández Ana L. , Duran-Frigola Miquel , Babiaka Smith B. , Tematio Fouedjou Romuald , Eni Donatus B. , Akame Simeon , Arreyetta-Bawak Augustine B. , Ebob Oyere T. , Metuge Jonathan A. , Bekono Boris D. , Isa Mustafa A. , Onuku Raphael , Shadrack Daniel M. , Musyoka Thommas M. , Patil Vaishali M. , van der Hooft Justin J. J. , da Silva Bolzani Vanderlan , Medina-Franco José L. , Kirchmair Johannes , Weber Tilmann , Tastan Bishop Özlem , Medema Marnix H. , Wessjohann Ludger A. , Ludwig-Müller Jutta 
Published: September 2021

AbstractWe report the major conclusions of the online open-access workshop “Computational Applications in Secondary Metabolite Discovery (CAiSMD)” that took place from 08 to 10 March 2021. Invited speakers from academia and industry and about 200 registered participants from five continents (Africa, Asia, Europe, South America, and North America) took part in the workshop. The workshop highlighted the potential applications of computational methodologies in the search for secondary metabolites (SMs) or natural products (NPs) as potential drugs and drug leads. During 3 days, the participants of this online workshop received an overview of modern computer-based approaches for exploring NP discovery in the “omics” age. The invited experts gave keynote lectures, trained participants in hands-on sessions, and held round table discussions. This was followed by oral presentations with much interaction between the speakers and the audience. Selected applicants (early-career scientists) were offered the opportunity to give oral presentations (15 min) and present posters in the form of flash presentations (5 min) upon submission of an abstract. The final program available on the workshop website (https://caismd.indiayouth.info/) comprised of 4 keynote lectures (KLs), 12 oral presentations (OPs), 2 round table discussions (RTDs), and 5 hands-on sessions (HSs). This meeting report also references internet resources for computational biology in the area of secondary metabolites that are of use outside of the workshop areas and will constitute a long-term valuable source for the community. The workshop concluded with an online survey form to be completed by speakers and participants for the goal of improving any subsequent editions.
Effects of supplemental xylanase and xylooligosaccharides on production performance and gut health variables of broiler chickens
Authors: Singh Amit K. , Mishra Birendra , Bedford Michael R. , Jha Rajesh 
Published: September 2021

AbstractBackgroundThis study evaluated the effects of supplemental xylanase and xylooligosaccharides (XOS) in a corn-soybean meal (SBM)-based diet on growth performance and intestinal health of broilers. A total of 288 day-old chicks (Cobb 500) were allocated to 36 floor pens (8 birds/pen) equally in 9 dietary treatments in a 3 × 3 factorial arrangement. The treatments were combinations of 3 levels of xylanase (0, 0.005% and 0.01% Econase XT) and 3 levels of prebiotics (0, 0.005% and 0.01% XOS) added to basal mash diets formulated in three phases (starter, d 0–14; grower, d 15–28; finisher, d 29–42). The feed intake and body weights were recorded weekly. On d 42, ileal sections were collected for histomorphometric and gene expression analysis, and cecal content was collected for determining short-chain fatty acids (SCFA) and microbiota.ResultsXylanase linearly (P < 0.01) increased the average daily gain (ADG) in both the finisher and total period and the final body weight gain (FBWG, 2940 & 2932 vs. 2760 g) of broilers. XOS did not significantly increase either ADG or FBWG (P > 0.05). Supplemental xylanase and XOS did not affect average daily feed intake and feed conversion ratio (P > 0.05). Xylanase and XOS did not change villus height (VH) or crypt depth (CD) ratio (P > 0.05). However, xylanase exhibited a trend (P = 0.097) on VH:CD ratio. The inclusion of 0.01% XOS without xylanase increased the level of IL-10 (a marker of anti-inflammatory cytokine) and IL-4 (a T-cell differentiation cytokine) genes compared with control (P < 0.05). The acetate production was increased by xylanase (P < 0.01) and XOS (P < 0.05) without an additive effect. Xylanase increased total SCFA (P < 0.01) while XOS had a tendency to increase (P = 0.052). Alpha and beta diversity of microbiota among treatments were not different (P > 0.05). However, the mean proportion of familyRuminococcaceaewas increased by the supplemental 0.01% xylanase (P < 0.01).ConclusionIt can be concluded that XOS can enhance cecal fermentation, while xylanase can increase the body weight gain along with the fermentation metabolites in the ceca of broilers fed the corn-SBM-based diet but the effects may not always translate into an improved mucosal absorptive capacity and a better feed efficiency.
Unsupervised feature learning-based encoder and adversarial networks
Authors: Suryawati Endang , Pardede Hilman F. , Zilvan Vicky , Ramdan Ade , Krisnandi Dikdik , Heryana Ana , Yuwana R. Sandra , Kusumo R. Budiarianto Suryo , Arisal Andria , Supianto Ahmad Afif 
Published: September 2021

AbstractIn this paper, we propose a novel deep learning-based feature learning architecture for object classification. Conventionally, deep learning methods are trained with supervised learning for object classification. But, this would require large amount of training data. Currently there are increasing trends to employ unsupervised learning for deep learning. By doing so, dependency on the availability of large training data could be reduced. One implementation of unsupervised deep learning is for feature learning where the network is designed to “learn” features automatically from data to obtain good representation that then could be used for classification. Autoencoder and generative adversarial networks (GAN) are examples of unsupervised deep learning methods. For GAN however, the trajectories of feature learning may go to unpredicted directions due to random initialization, making it unsuitable for feature learning. To overcome this, a hybrid of encoder and deep convolutional generative adversarial network (DCGAN) architectures, a variant of GAN, are proposed. Encoder is put on top of the Generator networks of GAN to avoid random initialisation. We called our method as EGAN. The output of EGAN is used as features for two deep convolutional neural networks (DCNNs): AlexNet and DenseNet. We evaluate the proposed methods on three types of dataset and the results indicate that better performances are achieved by our proposed method compared to using autoencoder and GAN.
Leopard syndrome: the potential cardiac defect underlying skin phenotypes
Authors: Yue Xiaojie , Zhao Xiong , Dai Yefeng , Yu. Lan 
Published: September 2021

AbstractLEOPARD syndrome (OMIM #151,100) caused by a germline PTPN11 mutation are characterized as multisystemic anomalies and variable marked phenotypes such as multiple lentigines and cafe´-au-lait spots, electrocardiographic conduction abnormalities, ocular hypertelorism/obstructive cardiomyopathy, pulmonary stenosis, abnormal genitalia, retardation of growth, and deafness. Phenotype overlap complicates clinical discrimination within RASopathies, making the diagnosis of LEOPARD more confusing and challenging. Besides, LEOPARD patients do not usually present with all these typical clinical features, increasing the possibility of underdiagnosis or misdiagnosis.Herein, we report a case of LEOPARD syndrome in a patient who only presented with pigmented skin spots and was initially diagnosed with multiple acquired melanocytic nevi. Subsequent pathological examination confirmed the diagnosis of multiple lentigines rather than melanocytic nevi. A genetic study showed a germline PTPN11 (Tyr279Cys) mutation and raised the suspicion of LEOPARD syndrome. A subsequent ECG examination detected potential cardiac defects and confirmed the diagnosis of LEOPARD. We considered that the potential damage of other systems underlying the skin multiple lentigines should not be ignored. The diagnosis of LEOPARD syndrome in an early stage before cardiac damage has reached a serious and irreversible stage can be meaningful for patients to fully understand the potential risks, complications and prognosis of the disease and to take appropriate precautions to prevent the potential risk of cardiac damage.
Translation and validation of the Urdu version of the European organization for research and treatment of cancer core quality of life questionnaire (EORTC QLQ-C30) and brain module (QLQ-BN20) in primary brain tumor patients
Authors: Zahid Nida , Martins Russell Seth , Zahid Wajeeha , Khalid Wardah , Azam Iqbal , Bhamani Shireen Shehzad , Asad Nargis , Ahmad Khabir , Jabbar Adnan Abdul , Shamim Muhammad Shahzad , Khan Rashid Jooma , Javed Gohar , Bari Ehsan , Enam Syed Ather 
Published: September 2021

Abstract
Introduction
This study translated and validated the Urdu version of the European Organization for Research and Treatment of Cancer Quality of Life (QoL) Questionnaire (EORTC QLQ-C30) and Brain Module (QLQ-BN20) amongst patients with primary brain tumors (PBT) in Pakistan, and assessed the correlation of QoL with resilience, depression, and anxiety.

Methods
Translation of the EORTC QLQ-C30 and QLQ-BN20 was performed as per EORTC guidelines. A survey comprising of Urdu translations of EORTC QLQ-C30, QLQ-BN20, Wagnild and Young Resilience Scale (RS-14) and Hospital Anxiety and Depression Scale was administered to patients with PBT at a tertiary care hospital in Pakistan. Reliability (via Cronbach alpha), content validity index (CVI) scores, construct validity, and inter-scale correlations were assessed.

Results
Our sample consisted of 250 patients with PBT, most commonly glioma (46.8%) and meningioma (21.2%). All patients were able to understand the Urdu translations. The Cronbach alphas for the QLQ-C30 and the QLQ-BN20 were 0.860 and 0.880, respectively. The CVI scores for clarity and relevance were high for both the EORTC QLQ-C30 (0.98 and 0.96, respectively) and the QLQ-BN20 tool (0.81 and 0.95, respectively). The global QoL domain (EORTC QLQ-C30) showed significant positive correlations with resilience (r = 0.422), and significant negative correlations with depression (r =  − 0.541) and anxiety (r =  − 0.502). Strong inter-scale correlations were observed between physical functioning and insomnia (r =  − 0.690) and role functioning and insomnia (r =  − 0.641).

Conclusion
Our study confirms the Urdu versions of the EORTC QLQ-C30 and QLQ-BN20 as valid clinical tools for the measurement of QoL in primary brain tumors patients within the cultural and socioeconomic context of Pakistan.
Computational approach towards the design of artemisinin–thymoquinone hybrids against main protease of SARS-COV-2
Authors: de Oliveira Victor Moreira , da Rocha Matheus Nunes , Magalhães Emanuel Paula , da Silva Mendes Francisco Rogênio , Marinho Márcia Machado , de Menezes Ramon Róseo Paula Pessoa Bezerra , Sampaio Tiago Lima , dos Santos Hélcio Silva , Martins Alice Maria Costa , Marinho Emmanuel Silva 
Published: September 2021

Abstract
Background
The sanitary emergency installed in the world, generated by the pandemic of COVID-19, instigates the search for scientific strategies to mitigate the damage caused by the disease to different sectors of society. The disease caused by the coronavirus, SARS-CoV-2, reached 216 countries/territories, where about 199 million people were reported with the infection. Of these, more than 4 million died. In this sense, strategies involving the development of new antiviral molecules are extremely important. The main protease (Mpro) from SARS-CoV-2 is an important target, which has been widely studied for antiviral treatment. This work aims to perform a screening of pharmacodynamics and pharmacokinetics of synthetic hybrids from thymoquinone and artemisin (THY-ART) against COVID-19.

Results
Molecular docking studies indicated that hybrids of artemisinin and thymoquinone showed a relevant interaction with the active fraction of the enzyme Mpro, when compared to the reference drugs. Furthermore, hybrids show an improvement in the interaction of substances with the enzyme, mainly due to the higher frequency of interactions with the Thr199 residue. ADMET studies indicated that hybrids tend to permeate biological membranes, allowing good human intestinal absorption, with low partition to the central nervous system, potentiation for CYP-450 enzyme inhibitors, low risk of toxicity compared to commercially available drugs, considering mainly mutagenicity and cardiotoxicity, low capacity of hybrids to permeate the blood–brain barrier, high absorption and moderate permeability in Caco-2 cells. In addition, T1–T7 tend to have a better distribution of their available fractions to carry out diffusion and transport across cell membranes, as well as increase the energy of interaction with the SARS-CoV-2 target.

Conclusions
Hybrid products of artemisinin and thymoquinone have the potential to inhibit Mpro, with desirable pharmacokinetic and toxicity characteristics compared to commercially available drugs, being indicated for preclinical and subsequent clinical studies against SARS-CoV-2. Emphasizing the possibility of synergistic use with currently used drugs in order to increase half-life and generate a possible synergistic effect. This work represents an important step for the development of specific drugs against COVID-19.
Risk, demand, capacity and outcomes in adult specialist eating disorder services in South-East of England before and since COVID-19
Authors: Ayton Agnes , Viljoen David , Ryan Sharon , Ibrahim Ali , Ford Duncan 
Published: September 2021

Aims and methodThis is a longitudinal cohort study describing the demand, capacity and outcomes of adult specialist eating disorder in-patient services covering a population of 3.5 million in a South-East England provider collaborative before and since the COVID-19 pandemic, between July 2018 and March 2021.ResultsThere were 351 referrals for admission; 97% were female, 95% had a diagnosis of anorexia nervosa and 19% had a body mass index (BMI) <13. Referrals have increased by 21% since the start of pandemic, coinciding with reduced capacity. Waiting times have increased from 33 to 46 days. There were significant differences in outcomes between providers. A novel, integrated enhanced cognitive behaviour theapy treatment model showed a 25% reduction in length of stay and improved BMI on discharge (50% v. 16% BMI >19), compared with traditional eclectic in-patient treatment.Clinical implicationsIntegrated enhanced cognitive behaviour theapy reduced length of stay and improved outcomes, and can offer more effective use of healthcare resources.
Somatostatin Receptor Antagonism Reverses Glucagon Counterregulatory Failure in Recurrently Hypoglycemic Male Rats
Authors: Hoffman Emily G , Jahangiriesmaili Mahsa , Mandel Erin R , Greenberg Caylee , Aiken Julian , D’Souza Ninoschka C , Pasieka Aoibhe , Teich Trevor , Chan Owen , Liggins Richard , Riddell Michael C 
Published: September 2021

Abstract
Recent antecedent hypoglycemia is a known source of defective glucose counter-regulation in diabetes; the mechanisms perpetuating the cycle of progressive α-cell failure and recurrent hypoglycemia remain unknown. Somatostatin has been shown to suppress the glucagon response to acute hypoglycemia in rodent models of type 1 diabetes. We hypothesized that somatostatin receptor 2 antagonism (SSTR2a) would restore glucagon counterregulation and delay the onset of insulin-induced hypoglycemia in recurrently hypoglycemic, nondiabetic male rats. Healthy, male, Sprague–Dawley rats (n = 39) received bolus injections of insulin (10 U/kg, 8 U/kg, 5 U/kg) on 3 consecutive days to induce hypoglycemia. On day 4, animals were then treated with SSTR2a (10 mg/kg; n = 17) or vehicle (n = 12) 1 hour prior to the induction of hypoglycemia using insulin (5 U/kg). Plasma glucagon level during hypoglycemia was ~30% lower on day 3 (150 ± 75 pg/mL; P &lt; .01), and 68% lower on day 4 in the vehicle group (70 ± 52 pg/mL; P &lt; .001) compared with day 1 (219 ± 99 pg/mL). On day 4, SSTR2a prolonged euglycemia by 25 ± 5 minutes (P &lt; .05) and restored the plasma glucagon response to hypoglycemia. Hepatic glycogen content of SSTR2a-treated rats was 35% lower than vehicle controls after hypoglycemia induction on day 4 (vehicle: 20 ± 7.0 vs SSTR2a: 13 ± 4.4 µmol/g; P &lt; .01). SSTR2a treatment reverses the cumulative glucagon deficit resulting from 3 days of antecedent hypoglycemia in healthy rats. This reversal is associated with decreased hepatic glycogen content and delayed time to hypoglycemic onset. We conclude that recurrent hypoglycemia produces glucagon counterregulatory deficiency in healthy male rats, which can be improved by SSTR2a.