Miracle-dz/UniFAR-FTUs huggingface dataset:
Surgical management of pancreatic neuroendocrine tumors: an introduction

ABSTRACT Introduction: Neuroendocrine tumors of the pancreas (pNETs) represent only 1% to 2% of all pancreatic neoplasms. These tumors can be classified as functional or nonfunctional tumors; as sporadic or from a genetic origin; as neuroendocrine neoplasms or carcinoma. Over the last decade, diagnosis of pNETs has increased significantly mainly due to the widespread use of cross-sectional imaging. Those tumors are usually associated with a good prognosis. Surgery, the only curative option for those patients, should always be discussed, ideally in a multidisciplinary team setting. Areas covered: We discuss i), the preoperative management of pNETs and the importance of accurate diagnosis, localization, grading and staging with computed tomography, magnetic resonance imaging, endoscopic ultrasound, and nuclear medicine imaging; ii), surgical indications and iii), the surgical approach (standard pancreatectomy vs pancreatic-sparing surgery). Expert opinion: The treatment option of all patients presenting with pNETs should be discussed in a multidisciplinary team setting with surgeon’s experienced in both pancreatic surgery and neuroendocrine tumor management. A complete preoperative imaging assessment – morphological and functional – must be performed. Surgery is usually recommended for functional pNETs, nonfunctional pNETs >2 cm (nf-pNETs) or for symptomatic nf-pNETs.
Diagnostic Yield Variation with Colonoscopy among Pediatric Endoscopists

Background: The primary aim of our study was to determine provider variation in diagnostic yield in a pediatric endoscopy center. Secondary aims were to examine ileal intubation rates as well as procedural complications at the provider level. Methods: A retrospective review of sequential pediatric patients who underwent a colonoscopy, completed by June 2018, determined the rates of endoscopically abnormal (EA) and isolated histologically abnormal (IHA) colonoscopies; the overall diagnostic yield was the combination of EA and IHA. Results: In total, 374 charts were reviewed. This study found high variability in diagnostic yield among the 16 clinicians ranging from as low as 22% to as high as 86% (p = 0.11) with an overall diagnostic yield of 48% for colonoscopy; excluding follow-up colonoscopies, the diagnostic yield was 42%. Abnormal calprotectin and abnormal blood tests were associated with higher diagnostic yields of 83 and 65%, respectively, compared with symptoms such as abdominal pain, diarrhea, and rectal bleeding which had yields of 39, 43, and 61%. Ileal intubation rates averaged 90% (range 63–100%, p = 0.06). In patients with a normal colon, there were 21 (6%) patients with an EA ileum and an additional 16 (4%) with an IHA ileum. Prep quality was rated excellent, good, or average in 97%. In addition, there was a low rate of serious complications (1 of 374). Conclusions: This study highlights the individual variability in diagnostic yield and ileal intubation rates in a pediatric gastroenterology practice. Goals for pediatric endoscopy could include ileal intubation rates of >90% and provider diagnostic yields of >40%.
Insulin-Like Growth Factor Dysregulation Both Preceding and Following Type 1 Diabetes Diagnosis

Insulin-like growth factors (IGFs), specifically IGF1 and IGF2, promote glucose metabolism, with their availability regulated by IGF-binding proteins (IGFBPs). We hypothesized that IGF1 and IGF2 levels, or their bioavailability, are reduced during type 1 diabetes development. Total serum IGF1, IGF2, and IGFBP1–7 levels were measured in an age-matched, cross-sectional cohort at varying stages of progression to type 1 diabetes. IGF1 and IGF2 levels were significantly lower in autoantibody (AAb)+ compared with AAb− relatives of subjects with type 1 diabetes. Most high-affinity IGFBPs were unchanged in individuals with pre–type 1 diabetes, suggesting that total IGF levels may reflect bioactivity. We also measured serum IGFs from a cohort of fasted subjects with type 1 diabetes. IGF1 levels significantly decreased with disease duration, in parallel with declining β-cell function. Additionally, plasma IGF levels were assessed in an AAb+ cohort monthly for a year. IGF1 and IGF2 showed longitudinal stability in single AAb+ subjects, but IGF1 levels decreased over time in subjects with multiple AAb and those who progressed to type 1 diabetes, particularly postdiagnosis. In sum, IGFs are dysregulated both before and after the clinical diagnosis of type 1 diabetes and may serve as novel biomarkers to improve disease prediction.
Adaptive Control of Noncanonical Neural-Network Nonlinear Systems With Unknown Input Dead-Zone Characteristics

Most of the available results on adaptive control of uncertain nonlinear systems with input dead-zone characteristics are for canonical nonlinear systems whose relative degrees are explicit and for which a Lyapunov-based backstepping design is directly applicable. However, those results cannot be applied to noncanonical form nonlinear systems whose relative degrees are implicit and for which a Lyapunov-based backstepping design may not be applicable. This article solves the adaptive control problem of a class of noncanonical neural-network nonlinear systems with unknown input dead-zones. A complete solution framework is developed, using a new gradient-based design which is applicable to noncanonical nonlinear systems with input dead-zones. Signal boundedness of the closed-loop system and the desired tracking performance are ensured with the developed control schemes. Their effectiveness is illustrated by an application example of speed control of dc motors. This article can be readily extended to handle general parametrizable noncanonical nonlinear systems with unknown dynamics and input dead-zones, to solve such an open problem.
Adverse pharmacokinetic interactions between illicit substances and clinical drugs

Abstract Adverse pharmacokinetic interactions between illicit substances and clinical drugs are of a significant health concern. Illicit substances are taken by healthy individuals as well as by patients with medical conditions such as mental illnesses, acquired immunodeficiency syndrome, diabetes mellitus and cancer. Many individuals that use illicit substances simultaneously take clinical drugs meant for targeted treatment. This concomitant usage can lead to life-threatening pharmacokinetic interactions between illicit substances and clinical drugs. Optimal levels and activity of drug-metabolizing enzymes and drug-transporters are crucial for metabolism and disposition of illicit substances as well as clinical drugs. However, both illicit substances and clinical drugs can induce changes in the expression and/or activity of drug-metabolizing enzymes and drug-transporters. Consequently, with concomitant usage, illicit substances can adversely influence the therapeutic outcome of coadministered clinical drugs. Likewise, clinical drugs can adversely affect the response of coadministered illicit substances. While the interactions between illicit substances and clinical drugs pose a tremendous health and financial burden, they lack a similar level of attention as drug-drug, food-drug, supplement-drug, herb-drug, disease-drug, or other substance-drug interactions such as alcohol-drug and tobacco-drug interactions. This review highlights the clinical pharmacokinetic interactions between clinical drugs and commonly used illicit substances such as cannabis, cocaine and 3, 4-Methylenedioxymethamphetamine (MDMA). Rigorous efforts are warranted to further understand the underlying mechanisms responsible for these clinical pharmacokinetic interactions. It is also critical to extend the awareness of the life-threatening adverse interactions to both health care professionals and patients.
Correcting for selective participation in cohort studies using auxiliary register data without identification of non-participants

Aims: Selective participation may hamper the validity of population-based cohort studies. The resulting bias can be alleviated by linking auxiliary register data to both the participants and the non-participants of the study, estimating propensity scores for participation and correcting for participation based on these. However, registry holders may not be allowed to disclose sensitive data on (invited) non-participants. Our aim is to provide guidance on how adequate bias correction can be achieved by using auxiliary register data but without disclosing information that could be linked to the subset of non-participants. Methods: We show how existing methods can be used to estimate generalisation weights under various data disclosure scenarios where invited non-participants are indistinguishable from uninvited ones. We also demonstrate how the methods can be implemented using Nordic register data. Results: Inverse-probability-of-sampling weights estimated within a random sample of the target population in which the non-respondents are disclosed are equivalent in expectation to analogous weights in a scenario where the non-participants and uninvited individuals from the population are indistinguishable. To minimise the risk of disclosure when the entire population is invited to participate, investigators should instead consider inverse-odds-of-sampling weights, a method that has previously been suggested for transporting study results to external populations. Conclusions: Generalisation weights can be estimated from auxiliary register data without disclosing information on invited non-participants.
Falls in persons with Parkinson's disease: Do non-motor symptoms matter as much as motor symptoms?

INTRODUCTION Falls are common among persons with Parkinson's disease (PD). On the other hand, predicting falls is complex as there are both generic and PD-specific contributors. In particular, the role of non-motor symptoms has been less studied. OBJECTIVE The objective of this study was to identify the role of non-motor predictors of falling in persons with PD (PwP). METHODS A cross-sectional study was carried out in PwP recruited from a movement disorders clinic. Clinical and demographical data were collected. All PwP were assessed using the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and the Non-Motor Symptoms Scale (NMSS). Variables were assessed at the bivariate level. Significant variables were put into a logistic regression model. RESULTS A total of 179 PwP were included. Overall, 16.8% of PwP had fallen in the past 12 months, with 53.3% of them being recurrent fallers. The mean number of monthly falls was 2.5 ± 3.3. Factors associated with falling in the bivariate analysis included the disease duration, Hoehn and Yahr stage, MDS-UPDRS part I and II, postural instability/gait disturbance (PIGD) subtype, NMSS urinary domain, NMSS miscellaneous domain, and non-motor severity burden (all p-values < 0.05). After multivariate analysis, only the disease duration (p = 0.03) and PIGD (p = 0.03) remained as independent risk factors. CONCLUSION Disease duration and the PIGD subtype were identified as relevant risk factors for falls in PwP Non-motor symptoms appear to have a less important role as risk factors for falls.
Phylogenetic analysis of ABCG subfamily proteins in plants: functional clustering and coevolution with ABCGs of pathogens

ABCG subfamily proteins are highly enriched in terrestrial plants. Many of these proteins secrete secondary metabolites that repel or inhibit pathogens. To establish why the ABCG subfamily proteins proliferated extensively during evolution, we constructed phylogenetic trees from a broad range of eukaryotic organisms. ABCG proteins were massively duplicated in land plants and in oomycetes, a group of agronomically important plant pathogens, which prompted us to hypothesize that plant and pathogen ABCGs coevolved. Supporting this hypothesis, full‐size ABCGs in host plants (Arabidopsis thaliana and Glycine max) and their pathogens (Hyaloperonospora arabidopsidis and Phytophthora sojae, respectively) had similar divergence times and patterns. Furthermore, generalist pathogens with broad ranges of host plants have diversified more ABCGs than their specialist counterparts. The hypothesis was further tested using an example pair of ABCGs that first diverged during multiplication in a host plant and its pathogen: AtABCG31 of A. thaliana and HpaP802307 of H. arabidopsidis. AtABCG31 expression was activated following infection with H. arabidopsidis, and disrupting AtABCG31 led to increased susceptibility to H. arabidopsidis. Together, our results suggest that ABCG genes in plants and their oomycete pathogens coevolved in an arms race, to extrude secondary metabolites involved in the plant's defense response against pathogens.
On the Causal Relationship between Household Consumption and Economic Growth in Saudi Arabia

This research paper explores the causal relationship between household consumption and economic growth over the period of 1980-2017. Hence, it applies the popular cointegration tests alongside the most common causality test. The empirical analysis shows the presence of a positive long run relationship between household consumption and economic growth. In specific, we find evidence revealing that a one percent increase in household expenditures on consumption would boost economic growth by 0.7 percent. Furthermore, causality analysis, based on Granger (1969) test, suggests that variation in household consumptions could explain changes in economic growth. Business and Economic Research ISSN 2162-486
Bat IFITM3 restriction depends on S-palmitoylation and a polymorphic site within the CD225 domain

Comparative analysis reveals adaptive evolution of bat IFITMs and a naturally polymorphic site within the conserved CD225 domain that affects S-palmitoylation and antiviral function of bat IFITM3. Host interferon-induced transmembrane proteins (IFITMs) are broad-spectrum antiviral restriction factors. Of these, IFITM3 potently inhibits viruses that enter cells through acidic endosomes, many of which are zoonotic and emerging viruses with bats (order Chiroptera) as their natural hosts. We previously demonstrated that microbat IFITM3 is antiviral. Here, we show that bat IFITMs are characterized by strong adaptive evolution and identify a highly variable and functionally important site—codon 70—within the conserved CD225 domain of IFITMs. Mutation of this residue in microbat IFITM3 impairs restriction of representatives of four different virus families that enter cells via endosomes. This mutant shows altered subcellular localization and reduced S-palmitoylation, a phenotype copied by mutation of conserved cysteine residues in microbat IFITM3. Furthermore, we show that microbat IFITM3 is S-palmitoylated on cysteine residues C71, C72, and C105, mutation of each cysteine individually impairs virus restriction, and a triple C71A-C72A-C105A mutant loses all restriction activity, concomitant with subcellular re-localization of microbat IFITM3 to Golgi-associated sites. Thus, we propose that S-palmitoylation is critical for Chiropteran IFITM3 function and identify a key molecular determinant of IFITM3 S-palmitoylation.
The role of plant expression platforms in biopharmaceutical development: possibilities for the future

ABSTRACT Introduction: Plant-made vaccines have been in the pipeline for nearly thirty years. Generated stably in transgenic plants or transiently using virus expression systems, pharmaceuticals have been developed to address global pandemics as well as several emerging One Health Diseases. Areas covered: This review describes the generation of plant-made vaccines to address some of the world’s most growing health concerns, including both infectious and non-communicable diseases, such as cancer. The review provides an overview of the research taking place in this field over the past three to five years. The PubMed database was searched under the topic of plant-made vaccine between the periods of 2014 and 2019. Expert opinion: While vaccines and other biologics have been shown to be cheap safe and efficacious, they have not yet entered the marketplace largely due to regulatory constraints. The lack of an appropriate regulatory structure to guide plant-made vaccines through to commercial development has stalled efforts to provide life-saving medicines to low- and middle-income families. In my opinion, it is paramount that regulatory hurdles are mitigated to address emerging infectious diseases such as Ebola and Zika in a timely manner.
A versatile cis-acting element reporter system to study the function, maturation and stability of ribosomal RNA mutants in archaea

Abstract General molecular principles of ribosome biogenesis have been well explored in bacteria and eukaryotes. Collectively, these studies have revealed important functional differences and few similarities between these processes. Phylogenetic studies suggest that the information processing machineries from archaea and eukaryotes are evolutionary more closely related than their bacterial counterparts. These observations raise the question of how ribosome synthesis in archaea may proceed in vivo. In this study, we describe a versatile plasmid-based cis-acting reporter system allowing to analyze in vivo the consequences of ribosomal RNA mutations in the model archaeon Haloferax volcanii. Applying this system, we provide evidence that the bulge-helix-bulge motif enclosed within the ribosomal RNA processing stems is required for the formation of archaeal-specific circular-pre-rRNA intermediates and mature rRNAs. In addition, we have collected evidences suggesting functional coordination of the early steps of ribosome synthesis in H. volcanii. Together our investigation describes a versatile platform allowing to generate and functionally analyze the fate of diverse rRNA variants, thereby paving the way to better understand the cis-acting molecular determinants necessary for archaeal ribosome synthesis, maturation, stability and function.
ABA INSENSITIVE4 promotes rather than represses PHYA‐dependent seed germination in Arabidopsis thaliana

Light quality plays vital roles in the life cycle of plants. For example, in seeds of many species, light quality determines the levels of the gibberelins (GA) and abscisic acid (ABA) phytohormones, which promote and repress seed germination respectively (Seo et al., 2006). In Arabidopsis thaliana, the photoreceptors phytochrome A (PHYA) and PHYB distinguish between full light (rich in red wavelength; R) and shade light (rich in far-red wavelength; FR) to regulate seed germination (Lymperopoulos et al., 2018).
Association Between Cerebral Small Vessel Disease With Antidepressant Use and Depression

Supplemental Digital Content is available in the text. Background and Purpose— Evidence links antidepressant use with cerebral small vessel disease; however, it remains unclear whether people with depression face comparable risk. This study aims to determine the association between antidepressant drug use and depression with markers of cerebral small vessel disease. Methods— One thousand nine hundred five participants (mean age, 72.5 years; 60% women) without stroke or dementia history underwent brain magnetic resonance imaging at baseline, and 1402 individuals underwent a second magnetic resonance imaging at 4 years. Outcomes were lacunes 3 to 15 mm and white matter hyperintensity volume (cm3) at baseline and follow-up. Exposure to antidepressants was grouped as (1) selective serotonin reuptake inhibitors (n=68), (2) tricyclics (n=40), (3) atypicals (n=24), (4) depressed nonusers (n=303), and (5) nondepressed/nonuser group (reference group, n=1470). Statistical analyses adjusted for propensity scores due to the nonrandomized exposure to antidepressant drugs. Results— There was an association between use of atypical antidepressants with lacunes at baseline (adjusted rate ratio, 2.59 [95% CI, 1.14–5.88]; P=0.023) and follow-up (adjusted rate ratio, 3.05 [95% CI, 1.25–7.43]; P=0.014). Lacunes at baseline were also associated with depressed nonusers (adjusted rate ratio, 1.53 [95% CI, 1.06–2.21]; P=0.023). Selective serotonin reuptake inhibitor users and depressed nonusers displayed higher total, periventricular, and deep white matter hyperintensity volumes at baseline. Selective serotonin reuptake inhibitor users had higher deep white matter hyperintensity volumes at follow-up. Conclusions— Users of atypical antidepressants, selective serotonin reuptake inhibitors, and depressed people without any antidepressant exposure all displayed markers of cerebral small vessel disease higher than the nondepressed/nonuser group. The findings suggest that cerebral small vessel disease is associated with depression and exposure to antidepressants.
Spatial-Temporal Dependency Modeling and Network Hub Detection for Functional MRI Analysis via Convolutional-Recurrent Network

Early identification of dementia at the stage of mild cognitive impairment (MCI) is crucial for timely diagnosis and intervention of Alzheimer's disease (AD). Although several pioneering studies have been devoted to automated AD diagnosis based on resting-state functional magnetic resonance imaging (rs-fMRI), their performance is somewhat limited due to non-effective mining of spatial-temporal dependency. Besides, few of these existing approaches consider the explicit detection and modeling of discriminative brain regions (i.e., network hubs) that are sensitive to AD progression. In this paper, we propose a unique Spatial-Temporal convolutional-recurrent neural Network (STNet) for automated prediction of AD progression and network hub detection from rs-fMRI time series. Our STNet incorporates the spatial-temporal information mining and AD-related hub detection into an end-to-end deep learning model. Specifically, we first partition rs-fMRI time series into a sequence of overlapping sliding windows. A sequence of convolutional components are then designed to capture the local-to-global spatially-dependent patterns within each sliding window, based on which we are able to identify discriminative hubs and characterize their unique contributions to disease diagnosis. A recurrent component with long short-term memory (LSTM) units is further employed to model the whole-brain temporal dependency from the spatially-dependent pattern sequences, thus capturing the temporal dynamics along time. We evaluate the proposed method on 174 subjects with 563 rs-fMRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, with results suggesting the effectiveness of our method in both tasks of disease progression prediction and AD-related hub detection.