Miracle-dz/UniFAR-FTUs huggingface dataset:
FnCas12a/crRNA-Mediated Genome Editing in Eimeria tenella

Eimeria species are intracellular parasites residing inside the intestinal epithelial cell, which cause poultry coccidiosis and result in significant financial losses in the poultry industry. Genome editing of Eimeria is of immense importance for the development of vaccines and drugs. CRISPR/Cas9 has been utilized for manipulating the genome of Eimeria tenella (E. tenella). Ectopic expression of Cas9, i.e., via plasmids, would introduce transgene, which substantially limits its application, especially for vaccine development. In this study, we initially optimized the condition of the transfection protocol. We demonstrated that with the optimized condition, the transfection of FnCas12a (also known as “FnCpf1”) protein and crRNA targeting EtHistone H4 triggered DNA double-strand breaks in vivo. We then used this strategy to knock-in a coding cassette for an enhanced yellow fluorescent protein (EYFP) and dihydrofolate reductase–thymidylate synthase gene (DHFR) as a selection marker to tag endogenous EtActin. The engineered E. tenella parasite possesses EYFP expression in its entire life cycle. Our results demonstrated that FnCas12a could trigger genome editing in E. tenella, which augments the applicability of the dissection of gene function and the development of anticoccidial drugs and vaccines for Eimeria species.
Efficacy and Safety of Metformin Use in Rheumatoid Arthritis: A Randomized Controlled Study

Objective: To evaluate the efficacy and safety of metformin use in rheumatoid arthritis (RA) patients receiving conventional synthetic disease modifying anti-rheumatic drugs (csDMARDs). Methods: A prospective, randomized, controlled, single blinded, study was carried on 66 RA patients with moderate and high disease activity state, receiving csDMARDs. Patients were simply randomized to receive either metformin 850 mg twice daily (Metformin group, n = 33), or placebo twice daily (Control group, n = 33) in addition to their stable anti-rheumatic regimen and followed up for 6 months. Serum C-reactive protein (CRP), disease activity of 28 joints based on CRP (DAS-28-CRP), and quality of life (QOL) were evaluated at baseline and then every 3 months. Moreover, serum adiponectin was assessed at baseline and after 6 months. Results: Sixty patients completed the study. Drop out was due to intolerance to metformin side effects (n = 3) and non-compliance (n = 3). Metformin significantly decreased CRP levels and DAS-28-CRP after 6 months compared to the control group (p-value <0.001). A significant improvement in QOL of metformin group was observed as early as after 3 months (p-value = 0.006) with a continued improvement observed at 6 months (p-value <0.001) compared to the control group. Despite the significantly higher serum adiponectin in the metformin group at baseline, it was significantly reduced after 6 months in the metformin group with median percent change of −63.49% compared to the significant increase in the control group with median percent change of 92.40%. Conclusion: Metformin significantly improved inflammation, disease severity, and QOL in RA patients with high safety profile. Clinical Trial Registration: Clinical-Trials.gov, identifier [NCT08363405].
Detection of Cerebrospinal Fluid Neurofilament Light Chain as a Marker for Alpha-Synucleinopathies

Alpha-synucleinopathies, such as Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA), are a class of neurodegenerative diseases. A diagnosis may be challenging because clinical symptoms partially overlap, and there is currently no reliable diagnostic test available. Therefore, we aimed to identify a suitable marker protein in cerebrospinal fluid (CSF) to distinguish either between different types of alpha-synucleinopathies or between alpha-synucleinopathies and controls. In this study, the regulation of different marker protein candidates, such as alpha-synuclein (a-Syn), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and total tau (tau) in different types of alpha-synucleinopathies, had been analyzed by using an ultrasensitive test system called single-molecule array (SIMOA). Interestingly, we observed that CSF-NfL was significantly elevated in patients with DLB and MSA compared to patients with PD or control donors. To differentiate between groups, receiver operating characteristic (ROC) curve analysis resulted in a very good diagnostic accuracy as indicated by the area under the curve (AUC) values of 0.87–0.92 for CSF-NfL. Furthermore, we observed that GFAP and tau were slightly increased either in DLB or MSA, while a-Syn levels remained unregulated. Our study suggests NfL as a promising marker to discriminate between different types of alpha-synucleinopathies or between DLB/MSA and controls.
Pharmacokinetics of Pantoprazole and Pantoprazole Sulfone in Goats After Intravenous Administration: A Preliminary Report

Background: Ruminant species are at risk of developing abomasal ulceration, but there is a lack of pharmacokinetic data for anti-ulcer therapies, such as the proton pump inhibitor pantoprazole, in goats. Objective: The primary study objective was to estimate the plasma pharmacokinetic parameters for pantoprazole in adult goats after intravenous administration. A secondary objective was to describe the pharmacokinetic parameters for the metabolite, pantoprazole sulfone, in goats. Methods: Pantoprazole was administered intravenously to six adult goats at a dose of 1 mg/kg. Plasma samples were collected over 36h and analyzed via reverse phase high performance liquid chromatography for determination of pantoprazole and pantoprazole sulfone concentrations. Pharmacokinetic parameters were determined by non-compartmental analysis. Results: Plasma clearance, elimination half-life, and volume of distribution of pantoprazole were estimated at 0.345 mL/kg/min, 0.7 h, and 0.9 L/kg, respectively following IV administration. The maximum concentration, elimination half-life and area under the curve of pantoprazole sulfone were estimated at 0.1 μg/mL, 0.8 h, and 0.2 hr*μg/mL, respectively. The global extraction ratio was estimated 0.00795 ± 0.00138. All animals had normal physical examinations after conclusion of the study. Conclusion: The reported plasma clearance for pantoprazole is lower than reported for foals, calves, and alpacas. The elimination half-life appears to be < that reported for foals and calves. Future pharmacodynamic studies are necessary for determination of the efficacy of pantoprazole on acid suppression in goats.
Superiority Verification of Deep Learning in the Identification of Medicinal Plants: Taking Paris polyphylla var. yunnanensis as an Example

Medicinal plants have a variety of values and are an important source of new drugs and their lead compounds. They have played an important role in the treatment of cancer, AIDS, COVID-19 and other major and unconquered diseases. However, there are problems such as uneven quality and adulteration. Therefore, it is of great significance to find comprehensive, efficient and modern technology for its identification and evaluation to ensure quality and efficacy. In this study, deep learning, which is superior to conventional identification techniques, was extended to the identification of the part and region of the medicinal plant Paris polyphylla var. yunnanensis from the perspective of spectroscopy. Two pattern recognition models, partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM), were established, and the overall discrimination performance of the three types of models was compared. In addition, we also compared the effects of different sample sizes on the discriminant performance of the models for the first time to explore whether the three models had sample size dependence. The results showed that the deep learning model had absolute superiority in the identification of medicinal plant. It was almost unaffected by factors such as data type and sample size. The overall identification ability was significantly better than the PLS-DA and SVM models. This study verified the superiority of the deep learning from examples, and provided a practical reference for related research on other medicinal plants.
Gene Expression Profiling for Differential Diagnosis of Liver Metastases: A Multicenter, Retrospective Cohort Study

Background Liver metastases (LM) are the most common tumors encountered in the liver and continue to be a significant cause of morbidity and mortality. Identification of the primary tumor of any LM is crucial for the implementation of effective and tailored treatment approaches, which still represents a difficult problem in clinical practice. Methods The resection or biopsy specimens and associated clinicopathologic data were archived from seven independent centers between January 2017 and December 2020. The primary tumor sites of liver tumors were verified through evaluation of available medical records, pathological and imaging information. The performance of a 90-gene expression assay for the determination of the site of tumor origin was assessed. Result A total of 130 LM covering 15 tumor types and 16 primary liver tumor specimens that met all quality control criteria were analyzed by the 90-gene expression assay. Among 130 LM cases, tumors were most frequently located in the colorectum, ovary and breast. Overall, the analysis of the 90-gene signature showed 93.1% and 100% agreement rates with the reference diagnosis in LM and primary liver tumor, respectively. For the common primary tumor types, the concordance rate was 100%, 95.7%, 100%, 93.8%, 87.5% for classifying the LM from the ovary, colorectum, breast, neuroendocrine, and pancreas, respectively. Conclusion The overall accuracy of 93.8% demonstrates encouraging performance of the 90-gene expression assay in identifying the primary sites of liver tumors. Future incorporation of the 90-gene expression assay in clinical diagnosis will aid oncologists in applying precise treatments, leading to improved care and outcomes for LM patients.
Seismic and Aseismic Cycle of the Ecuador–Colombia Subduction Zone

The Colombia–Ecuador subduction zone is an exceptional natural laboratory to study the seismic cycle associated with large and great subduction earthquakes. Since the great 1906 Mw = 8.6 Colombia–Ecuador earthquake, four large Mw > 7.5 megathrust earthquakes occurred within the 1906 rupture area, releasing altogether a cumulative seismic moment of ∼35% of the 1906 seismic moment. We take advantage of newly released seismic catalogs and global positioning system (GPS) data at the scale of the Colombia–Ecuador subduction zone to balance the moment deficit that is building up on the megathrust interface during the interseismic period with the seismic and aseismic moments released by transient slip episodes. Assuming a steady-state interseismic loading, we found that the seismic moment released by the 2016 Mw = 7.8 Pedernales earthquake is about half of the moment deficit buildup since 1942, suggesting that the Pedernales segment was mature to host that seismic event and its postseismic afterslip. In the aftermath of the 2016 event, the asperities that broke in 1958 and 1979 both appears to be mature to host a large Mw > 7.5 earthquakes if they break in two individual seismic events, or an Mw∼7.8–8.0 earthquake if they break simultaneously. The analysis of our interseismic-coupling map suggests that the great 1906 Colombia–Ecuador earthquake could have ruptured a segment of 400 km-long bounded by two 80 km wide creeping segments that coincide with the entrance into the subduction of the Carnegie ridge in Ecuador and the Yaquina Graben in Colombia. These creeping segments share similar frictional properties and may both behave as strong seismic barriers able to stop ruptures associated with great events like in 1906. Smaller creeping segments are imaged within the 1906 rupture area and are located at the extremities of the large 1942, 1958, 1979, and 2016 seismic ruptures. Finally, assuming that the frequency–magnitude distribution of megathrust seismicity follows the Gutenberg–Richter law and considering that 50% of the transient slip on the megathrust is aseismic, we found that the maximum magnitude subduction earthquake that can affect this subduction zone has a moment magnitude equivalent to Mw ∼8.8 with a recurrence time of 1,400 years. No similar magnitude event has yet been observed in that region.
Response of Background Herbivory in Mature Birch Trees to Global Warming

Given the time scale based on the duration of exposure to global warming, natural climate-gradient studies and experimental manipulations have detected long-term (decades to centuries) and short-term (years to decades) ecological responses to global warming. Combination of these two complementary approaches within a single study may enable prediction of the likely responses of ecological processes to global warming. To understand how global warming affects plant–herbivore interactions within a canopy of Erman’s birch, we combined an elevational gradient study and a warming experiment involving mature birch trees in which the soil and tree branches were warmed separately. In the elevational gradient study, herbivory by chewing insects and plant growth increased as elevation decreased, and the concentrations of condensed tannins and total phenolics in the leaves decreased. In the warming experiment, soil warming alone increased herbivory, and the addition of branch warming amplified the effect on herbivory. Soil warming alone decreased the tannin concentration, and the addition of branch warming led to a further reduction. The variation in herbivory was best explained by the tannin content of leaves. Our experimental results demonstrate that the decreased tannin content of leaves due to a combination of soil and branch warming was an important driver of increased herbivory in the canopy of the mature birch trees. The similar tendencies in the short- and long-term responses imply that global warming is likely to increase background herbivory in mature birch trees by decreasing the tannin content of leaves in the canopy.
Microplastics in Florida, United States: A Case Study of Quantification and Characterization With Intertidal Snails

Concentrations of microplastics are increasing within the oceans, including waters surrounding Florida, United States. Miles of sandy beaches make the sunshine state a prime tourist destination leading to an increased amount of pollution along Florida coasts. Microplastics can cause damage to intertidal organisms, as well as causing issues up the food chain with biomagnification and seafood consumers, such as humans. Florida is also subject to hurricanes which often distribute sediments, filling the water column with previously settled microplastics. These factors make Florida a special case to review considering the state is affected heavily by hurricanes and tourism, which can contribute to microplastic concentrations in the Gulf of Mexico. The focus of this study was to quantify, characterize, and compare microplastics contamination in two predatory marine snail species from intertidal habitats in Florida, United States Ingestion results were also compared to microplastics contamination of water samples collected from the same locations. Red-mouth rock shell (Stramonita haemastoma, n = 30) and Crown conch (Melongena corona, n = 30) snails were collected from intertidal habitats in Florida and digested for microplastics quantification. Water samples were filtered and microplastics were quantified. 256 microplastics, of which 93% were microfibers and 7% were microfragments were isolated from snails (n = 60). Additionally, 67 microplastics were isolated from 8 L of seawater (8.375 microplastics/L), of which 97% were microfibers and 3% were microfragments. This is the first known study to demonstrate microplastics contamination of tissues in predatory marine intertidal snails. Marine intertidal snails may be good organisms for biomonitoring of microplastics in intertidal sandy habitats.
Artificial Intelligence Based Multimodality Imaging: A New Frontier in Coronary Artery Disease Management

Coronary artery disease (CAD) represents one of the most important causes of death around the world. Multimodality imaging plays a fundamental role in both diagnosis and risk stratification of acute and chronic CAD. For example, the role of Coronary Computed Tomography Angiography (CCTA) has become increasingly important to rule out CAD according to the latest guidelines. These changes and others will likely increase the request for appropriate imaging tests in the future. In this setting, artificial intelligence (AI) will play a pivotal role in echocardiography, CCTA, cardiac magnetic resonance and nuclear imaging, making multimodality imaging more efficient and reliable for clinicians, as well as more sustainable for healthcare systems. Furthermore, AI can assist clinicians in identifying early predictors of adverse outcome that human eyes cannot see in the fog of “big data. ” AI algorithms applied to multimodality imaging will play a fundamental role in the management of patients with suspected or established CAD. This study aims to provide a comprehensive overview of current and future AI applications to the field of multimodality imaging of ischemic heart disease.
Gait-Related Brain Activation During Motor Imagery of Complex and Simple Ambulation in Parkinson's Disease With Freezing of Gait

Background: Freezing of gait (FOG) in Parkinson's disease (PD) is a devastating clinical phenomenon that has a detrimental impact on patients. It tends to be triggered more often during turning (complex) than during forwarding straight (simple) walking. The neural mechanism underlying this phenomenon remains unclear and requires further elucidation. Objective: To investigate the differences in cerebral functional magnetic resonance imaging responses between PD patients with and without FOG during explicitly video-guided motor imagery (MI) of various complex (normal, freezing) and simple (normal, freezing) walking conditions. Methods: We recruited 34 PD patients, namely, 20 with FOG and 14 without FOG, and 15 normal controls. Participants underwent video-guided MI of turning and straight walking, with and without freezing, while their brain blood oxygen level-dependent (BOLD) activities were measured. Gait analysis was performed. Results: While comparing FOG turning with FOG straight walking, freezers showed higher activation of the superior occipital gyrus, left precentral gyrus, and right postcentral gyrus compared with non-freezers. Normal controls also manifest similar findings compared with non-freezers, except no difference was noted in occipital gyrus activity between the two groups. Freezers also displayed a higher effect size in the locomotor regions than non-freezers during imagery of normal turning. Conclusions: Our findings suggest that freezers require a higher drive of cortical and locomotion regions to overcome the overinhibition of the pathways in freezers than in non-freezers. Compared with simple walking, increased dorsal visual pathway and deep locomotion region activities might play pivotal roles in tackling FOG in freezers during complex walking.
Sirtuins as Potential Therapeutic Targets for Mitigating Neuroinflammation Associated With Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common neurodegenerative disorder, which is associated with memory deficit and global cognitive decline. Age is the greatest risk factor for AD and, in recent years, it is becoming increasingly appreciated that aging-related neuroinflammation plays a key role in the pathogenesis of AD. The presence of β-amyloid plaques and neurofibrillary tangles are the primary pathological hallmarks of AD; defects which can then activate a cascade of molecular inflammatory pathways in glial cells. Microglia, the resident macrophages in the central nervous system (CNS), are the major triggers of inflammation; a response which is typically intended to prevent further damage to the CNS. However, persistent microglial activation (i.e., neuroinflammation) is toxic to both neurons and glia, which then leads to neurodegeneration. Growing evidence supports a central role for sirtuins in the regulation of neuroinflammation. Sirtuins are NAD+-dependent protein deacetylases that modulate a number of cellular processes associated with inflammation. This review examines the latest findings regarding AD-associated neuroinflammation, mainly focusing on the connections among the microglial molecular pathways of inflammation. Furthermore, we highlight the biology of sirtuins, and their role in neuroinflammation. Suppression of microglial activity through modulation of the sirtuin activity has now become a key area of research, where progress in therapeutic interventions may slow the progression of Alzheimer’s disease.
What Drives Outpatient Care Costs in Kenya? An Analysis With Generalized Estimating Equations

Objective: This study aimed to identify the factors associated with outpatient expenses incurred by households in Kenya. Background: The problem of outpatient healthcare expenses incurred by citizens in countries with limited resources has received little attention. Thus, this study aimed to determine the predictors of household spending on outpatient expenses in Kenya. Method: We conducted a cross-sectional analysis on households in Kenya using data from the 2018 Kenya Household Health Expenditure and Utilization Survey. We applied the generalized estimating equations method to determine the best subset of predictors of outpatient care cost. Findings: The best predictors of outpatient care expenses in Kenya are age, wealth index, and education level of the household head. Conclusions: There were no differences regarding age in the mean spending on outpatient care. Moreover, we found that the cost of outpatient care changes with age in a sinusoidal manner. We observed that rich households spent more on outpatient care, mostly owing to their financial ability. Households whose heads reported primary or secondary school education level spent less on outpatient costs than households headed by those who never went to school.