Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved recovery from skeletal muscle damage is largely unexplained by myofibrillar protein synthesis or inflammatory and regenerative gene expression pathways.

The contribution of myofibrillar protein synthesis (MyoPS) to recovery from skeletal muscle damage in humans is unknown. Recreationally active males and females consumed a daily protein-polyphenol beverage targeted at increasing amino acid availability and reducing inflammation (PPB; n=9), both known to affect MyoPS, or an isocaloric placebo (PLA; n=9) during 168 h of recovery from 300 maximal unilateral eccentric contractions (EE). Muscle function was assessed daily. Muscle biopsies were collected 24, 27, 36, 72 and 168 h for MyoPS measurements using 2H2O and expression of 224 genes using RT-qPCR and pathway analysis. PPB improved recovery of muscle function, which was impaired for five days following EE in PLA (interaction; P<0.05). Acute postprandial MyoPS rates were unaffected by nutritional intervention (24-27 h). EE increased overnight (27-36 h) MyoPS versus control leg (PLA: 33±19%; PPB: 79±25%; leg P<0.01), and PPB tended to increase this further (interaction P=0.06). Daily MyoPS rates were greater with PPB between 72-168 h after EE, albeit after function had recovered. Inflammatory and regenerative signaling pathways were dramatically upregulated and clustered following EE but were unaffected by nutritional intervention. These results suggest that accelerated recovery from EE is not explained by elevated MyoPS or suppression of inflammation.
Investigation of carbamazepine-nicotinamide cocrystal solubility and dissolution by a UV imaging system

vi ABSTRACT In this study, the ability of pharmaceutical cocrystals on improving solubility and dissolution behaviour of poorly water soluble drug has been studied by a novel technique SDI300 UV imaging surface dissolution system. Pharmaceutical cocrystals of poorly water soluble drug carbamazepine (CBZ) were synthesized, which are 1: 1 carbamazepine nicotinamide (CBZ-NIC) cocrystal, and 2:1 carbamazepine succinic acid (CBZ-SUC) cocrystal. Firstly, dissolution and solution mediated phase transformation behaviour (SMPT) of CBZ-NIC cocrystal was studied by in situ techniques of UV imaging and Raman spectroscopy. This study has shown that in situ UV imaging and Raman spectroscopy with a complementary technique of SEM can provide an in depth understanding of cocrystal dissolution processes. It has been found that CBZ-NIC cocrystal including other polymorphs of CBZ III and I and mixture are converting to CBZ DH during dissolution. The influence of surfactants, SLS and Tween 80, on the solubility and dissolution behavior of the CBZ-NIC cocrystal has been studied. Results show that the SMPT of CBZ III and CBZ-NIC cocrystal can be altered by inclusion of a surfactant in dissolution medium. However, CBZ III and CBZ-NIC cocrystal have shown different transformation behavior with different surfactants. The solubility and dissolution behaviour of CBZ-NIC cocrystal, CBZ-SUC cocrystal in four biomedia (simulated gastric fluid, pH1.2 HCl buffer, simulated intestinal fluid, and pH 6.8 PBS buffer) were studied. Results have shown that equilibrium solubility of CBZ samples varied in different media. The two cocrystals dissolution rates show different trends as that of parent drug CBZ III. This can be explained by that the formation of cocrystal change the dissolution ability of CBZ III.
Reusability of Al-F Hydroxide Precipitates Generated in Adsorption and Coagulation Treatment of Fluoride for Adsorptive Removal of Arsenic

Abstract This study aims to investigate the feasibility of utilizing Al-F hydroxide precipitates generated in Al hydroxide [Al(OH)3] adsorption [Al(OH)3-Fads] and aluminum (Al) coagulation [Al(OH)3-Fcoag] for adsorptive removal of As(III) and As(V). Al(OH)3-Fads, Al(OH)3-Fcoag, and pristine Al(OH)3 were characterized by nitrogen sorption, X-ray photoelectron spectroscopy, and fourier transform infrared spectroscopy (FTIR) before and after arsenic adsorption. The kinetic study indicated that As(III) and As(V) adsorption on these Al-based solid wastes followed the pseudo-second-order model. The calculated adsorption capacity of Al(OH)3-Fads and Al(OH)3-Fcoag for As(III) was 48.0 and 31.0 mg/g, while it was 84.0 and 56.3 mg/g for As(V), respectively. These adsorption capacities were 25–50% lower compared with pristine Al(OH)3. Anion exchange of fluoride by H2AsO4− and HAsO42− dominated in As(V) removal by Al(OH)3-Fads, while formation of an As-O complex played a more important role in As(V) removal by Al(OH).
IMPACT OF REHABILITATION START TIME ON FUNCTIONAL OUTCOMES AFTER STROKE

Objective To investigate the optimum rehabilitation start timing for improved functional outcomes after stroke in Japan. Design A retrospective database study. Subjects A total of 140,655 patients with stroke from 1,161 acute hospitals in Japan. Only data for those patients who were discharged alive was included in the analysis. Methods Activities of daily living were assessed. Comparisons were made using the rehabilitation start day after hospital admission. Reference day 2 was compared with days 1, 3, 4, 5, and 6 or later. Modified Rankin Scale at time of discharge was used as the primary outcome. In addition, cases of ischaemic stroke and haemorrhagic stroke were analysed as separate subgroups. Results Univariate and multivariate logistic regression analyses showed that starting rehabilitation on day 2 resulted in a better outcome than starting on day 3 or later. There was no significant difference in outcome between starting rehabilitation on days 1 or 2 in all cases and subgroup of patient with infarction stroke. For a subgroup of patients with haemorrhagic stroke, starting rehabilitation on day 2 resulted in a better outcome than starting on day 1. Conclusion Starting post-stroke rehabilitation on the day of admission or second day of hospitalization may be the optimum timing for functional outcomes. However, for haemorrhagic stroke, starting rehabilitation on the second day of hospitalization may be more effective than on the day of admission. LAY ABSTRACT This study examined the effect on functional outcomes of the time after stroke of starting rehabilitation. A large national database was searched for eligible stroke patients, resulting in a total of 140,655 patients from 1,161 hospitals. Starting rehabilitation on the day of admission or second day of hospitalization after stroke was found to be associated with better functional outcomes at discharge than starting rehabilitation on the third day or later. For patients with haemorrhagic stroke, those who started rehabilitation on the second day of hospitalization had better functional outcome at discharge than those who started on the day of admission. Thus, starting rehabilitation on the day of admission or the second day of hospitalization after stroke may be the best timing for improved functional outcomes. However, among patients with haemorrhagic stroke, starting rehabilitation on the second day of hospitalization may result in better outcomes than starting on the day of admission.
Investigations of Chirality Effects on Undifferentiated State of Mesenchymal Stem Cells Using Soft Nanofibrous Oligopeptide Hydrogels

Soft nanofibrous oligopeptide hydrogels consisting of self-assembled l - and d -form Fmoc-Phe-Phe-Cys networks photo-cross-linked by poly(ethylene glycol)-dimethacrylate, which are referred to as l - and d -gel, respectively, were developed for investigation of chirality effects on the undifferentiated state of mesenchymal stem cells. Encapsulated mesenchymal stem cells in d -gel showed slower growth and less spreading, resulting in higher maintenance of the undifferentiated state, compared to in l -gel. This indicates that d -form peptide materials might be useful as scaffold materials for regenerative medicine using stem cells.
Sequence Labeling with Multiple Noisy Annotators

Sequence labelling task traditionally requires large-scale datasets with ground truth labels. As a cheaper and faster alternative approach, crowdsourcing provides sequence labels from multiple noisy annotators at the cost of label quality. In this paper, we propose a novel Teachers-Student framework to aggregate crowd annotations without actual ground truth or prior-knowledge about the annotators. Multiple teacher networks reach a consensus on encoding input instances and keep the annotator-speciﬁc information in the corresponding crowd components. The student network learns the comprehensive knowledge and aggregates annotator information from multiple teacher networks for better inference.
A Pilot Study for Investigation of Plasma Amino Acid Profile in Neurofibromatosis Type 1 Patients.

BACKGROUND Neurofibromatosis, also known as Von Recklinghausen disease, is a systemic and progressive genetic disease that primarily affects the skin, eyes, nervous system and bones. The disease can occur in a variety of ways and can vary from individuals. Metabolomic-based research using blood samples has enabled new diagnostic methods to be used in the diagnosis of various diseases, especially cancer. Among metabolites, profiling of plasma free amino acids (PFAA) is a promising approach because PFAAs bind all organ systems and play an important role in metabolism. OBJECTIVE This study aimed to determine the characteristics of PFAA profiles in neurofibromatosis patients and the possibility of using them for early detection and treatment of the disease. METHOD Patients with a diagnosis of Neurofibromatosis Type I confirmed by genetic analysis and healthy individuals of the same age group without any disease were included in the study. We analysed the nineteen plasma free amino acids (phenylalanine, proline, threonine, arginine, asparagine, cystine, valine, glutamate, tyrosine, serine, glutamine, glycine, tryptophane, leucine, lysine, methionine, isoleucine, aspartate and alanine) from neurofibromatosis Type I patients and control group by liquid chromatography tandem mass spectrometry (LC-MS/MS) in Metabolism Laboratory of Harran University Research and Application Hospital. The results of the plasma free amino acid levels were divided into 3 groups as essential, semi-essential and non-essential. The differences of amino acid levels between groups were determined. RESULTS Eight amino acid levels (methionine, arginine, cystine, glutamine, proline, asparagine, serine, aspartate) were significantly altered in patients with neurofibromatosis type 1. In essential amino acids, methionine levels were significantly higher in the patient group than the control group. While the levels of arginine and glutamine in semi-essential amino acids were statistically significantly higher in the patient group, a significant decrease was observed in cystine and proline levels compared to the control group's amino acid levels. In non-essential amino acids group, asparagine, serine and aspartate amino acid levels were significantly higher in the patient group compared to the control group. CONCLUSION The current research predicates that eight amino acids, nsmely methionine, arginine, cystine, glutamine, proline, asparagine, serine, aspartate can be considered to be valuable biomarkers for neurofibromatosis type I. This present study is the first to build models for neurofibromatosis Type I screening using plasma free amino acids and the amino acid profile will guide the predicting of the complications that may occur during the course of the disease.
Plant carbohydrate depletion impairs water relations and spreads via ectomycorrhizal networks

Carbon and water relations are fundamental to plant life and strongly interact. Under drought, the ability of plants to assimilate carbon is reduced, which increases their consumption of stored labile carbon in the form of non-structural carbohydrates (NSC). Stored NSC depletion may impair plant water relations, but mechanisms are not clear, and we do not know if its effects are independent of water deficit. If so, carbon costs of fungal symbionts could also indirectly influence plant drought tolerance through stored NSC depletion. We connected well-watered Pinus ponderosa seedling pairs via ectomycorrhizal (EM) networks where one seedling was shaded and the other experienced full light and compared responses to seedling pairs in the light. We measured plant water relations and traced carbon movements using 13CO2 to explore the mechanisms linking stored NSC to water relations, and to identify potential tradeoffs between the ability to endure low water potentials and maintaining EM fungi under carbon-limiting conditions. Even in the absence of drought, mild NSC depletion impaired osmoregulation capacity and turgor maintenance, a critical strategy to tolerate drought. This demonstrates that NSC storage influences plant water relations independently of plant water status. We also found that EM networks propagated NSC depletion and its negative effects on water relations from carbon stressed hosts to non-stressed hosts. These results highlight carbon allocation tradeoffs between supporting fungal symbionts and retaining water via stored NSC and have implications for biotic interactions and forest drought responses. Significance Statement The potential effects of future drought on global carbon cycles, vegetation-climate feedbacks, species distributions and their ecological impacts, urgently call for a clear understanding of factors influencing vegetation tolerance to drought. Key to this is the understanding of mechanisms and processes by which plants tolerate drought and how prevalent plant-fungal interactions may influence these processes. We demonstrate that even mild depletion of plant non-structural carbohydrate (NSC) storage readily decreases plant water retention capacity, therefore decreasing tolerance to drought. Because plant-fungal interactions depend on NSC exchange, plants face carbon-allocation tradeoffs between maintaining drought tolerance and feeding fungal symbionts. The impacts of these tradeoffs extend across plants connected via ectomycorrhizal networks as fungi propagate NSC depletion from NSC-limited plants to non-stressed individuals.
The targeted inhibition of prostate cancer by iron-based nanoparticles based on bioinformatics

Prostate cancer is an epithelial malignant tumor of the prostate, and it is one of the malignant tumors with a high incidence of urogenital system in men. The local treatment of prostate cancer is mainly radical resection and radical radiotherapy, but they are not applicable to advanced prostate cancer. Systemic therapy mainly includes targeted therapy and immunotherapy which could cause many complications, and will affect the prognosis and quality of life of patients. It is urgent to find new treatments for prostate cancer. Bioinformatics offers hope for us to find reliable therapeutic targets. Bioinformatics can use the tumor informations in database and analyze them to screen out the best differentially expressed genes. Using the selected differentially expressed genes as targets, a gene interference plasmid was designed, and the constructed plasmid was used for targeted gene therapy. There are some problems about gene therapy that need to be solved, such as how to transfer genes to target cells is also an important challenge. Due to their large molecular weight and hydrophilic nature, they cannot enter cells through passive diffusion mechanisms. Here we synthesized a DNA carrier used surface modified iron based nanoparticles, and used it to load plasmid including ShRNA which can inhibit the expression of oncogene SLC4A4 selected by bioinformatics’ method. After that we use this iron based nanoparticles/plasmid DNA nanocomposite to treat prostate cancer cells in vitro and in vivo. The target gene SLC4A4 we had selected using bioinformatics had a strong effect on the proliferation of prostate cells; Our nanocomposite could inhibit the expression of SLC4A4 effectively, it had strong inhibitory effects on prostate cancer cells both in vivo and in vitro, and can be used as a potential method for prostate cancer treatment.
Classification of drug use patterns

Characterizing long‐term prescription data is challenging due to the time‐varying nature of drug use. Conventional approaches summarize time‐varying data into categorical variables based on simple measures, such as cumulative dose, while ignoring patterns of use. The loss of information can lead to misclassification and biased estimates of the exposure‐outcome association. We introduce a classification method to characterize longitudinal prescription data with an unsupervised machine learning algorithm. We used administrative databases covering virtually all 1.3 million residents of Manitoba and explicitly designed features to describe the average dose, proportion of days covered (PDC), dose change, and dose variability, and clustered the resulting feature space using K‐means clustering. We applied this method to metformin use in diabetes patients. We identified 27,786 metformin users and showed that the feature distributions of their metformin use are stable for varying the lengths of follow‐up and that these distributions have clear interpretations. We found six distinct metformin user groups: patients with intermittent use, decreasing dose, increasing dose, high dose, and two medium dose groups (one with stable dose and one with highly variable use). Patients in the varying and decreasing dose groups had a higher chance of progression of diabetes than other patients. The method presented in this paper allows for characterization of drug use into distinct and clinically relevant groups in a way that cannot be obtained from merely classifying use by quantiles of overall use.
Donepezil and cognitive remediation therapy to augment treatment of alcohol use disorder related mild cognitive impairment (AUD-MCI): An open label pilot study with historical controls

Background Pharmacological and psychosocial interventions have only modest efficacy for Alcohol Use Disorder (AUD), and continued alcohol use has brain effects on neurocognition, which place heavy drinkers at increased risk of early onset dementia. The most common neurocognitive deficits are in the domains of executive function and memory, and these deficits may impact AUD treatment outcomes. AUD related Mild Cognitive Impairment (AUD-MCI) is a diagnosis in DSM-V and ICD-10. Donepezil, a cholinesterase inhibitor, is currently FDA approved for treatment of dementia, and recent preclinical research suggests anticholinesterase agents may treat alcoholism. Another approach to cognitive recovery is Cognitive Remediation Therapy (CRT). Recent research supports CRT efficacy in schizophrenia and related disorders, and some research suggests that CRT could improve neurocognition in substance abuse disorders (SUDs). This is the first report of an open-label clinical trial that combined donepezil with CRT to improve neurocognitive and clinical outcomes in the early phase of AUD recovery. Methods Eleven older male US Veterans with AUD-MCI as determined by Level II neurocognitive criteria and who had recently relapsed participated in an open-label trial of 13 weeks of donepezil combined with CRT. They were compared with matched historical control samples on neurocognitive and clinical outcomes. Results Participants had excellent adherence to donepezil and CRT. Neurocognitive improvements were highly significant on a composite score of learning and memory and executive function measures (p < .0001) and was significantly better than historical matched controls (p < .001). On a Clinical Global Impression scale, 90.9% of participants had a good clinical recovery compared with 59.5% of historical matched controls (p <.052). Conclusions AUD-MCI has not received much research attention but is of considerable public health importance. Findings in this open-label trial of donepezil + CRT should encourage further investigation into the clinical benefit of this combined treatment for AUD-MCI.
Xanthones as P-glycoprotein modulators and their impact on drug bioavailability

ABSTRACT Introduction: P-glycoprotein (P-gp) is an important efflux pump responsible for the extruding of many endogenous and exogenous substances out of the cells. P-gp can be modulated by different molecules – including xanthone derivatives – to surpass the multidrug resistance (MDR) phenomenon through P-gp inhibition, or to serve as an antidotal strategy in intoxication scenarios through P-gp induction/activation. Areas covered: This review provides a perspective on P-gp modulators, with particular focus on xanthonic derivatives, highlighting their ability to modulate P-gp expression and/or activity, and the potential impact of these effects on the pharmacokinetics, pharmacodynamics and toxicity of P-gp substrates. Expert opinion: Xanthones, of natural or synthetic origin, are able to modulate P-gp, interfering with its protein synthesis or with its mechanism of action, by decreasing or increasing its efflux capacity. These modulatory effects make the xanthonic scaffold a promising source of new derivatives with therapeutic potential. However, the mechanisms beyond the xanthones-mediated P-gp modulation and the chemical characteristics that make them more potent P-gp inhibitors or inducers/activators are still understudied. Furthermore, a new window of opportunity exists in the neuropathologies field, where xanthonic derivatives with potential to modulate P-gp should be further explored to optimize the prevention/treatment of brain pathologies. GRAPHICAL ABSTRACT
Identification of Dysregulated Genes for Late-Onset Alzheimer’s Disease Using Gene Expression Data in Brain

Background: Alzheimer’s Disease (AD) is a neurodegenerative complex brain disease that represents a public health concern. AD is considered the fifth leading cause of death in Americans who are older than 65 years which prioritizes the importance of understanding the etiology of AD in its early stages before the onset of symptoms. This study attempted to further understand Alzheimer’s disease (AD) etiology by investigating the dysregulated genes using gene expression data from multiple brain regions. Methods: A linear mixed-effects model for differential gene expression analysis was used in a sample of 15 AD and 30 control subjects, each with data from four different brain regions, in order to deal with the hierarchical multilevel data. Post-hoc Gene Ontology and pathway enrichment analyses provided insights on the biological implications in AD progression. Supervised machine learning algorithms were used to assess the discriminative power of the top 10 candidate genes in distinguishing between the two groups. Results: Enrichment analyses revealed biological processes and pathways that are related to structural constituents and organization of the axons and synapses. These biological processes and pathways imply dysfunctional axon and synaptic transmission between neuronal cells in AD. Random Forest classification algorithm gave the best accuracy on the test data with F1-score of 0.88. Conclusion: The differentially expressed genes were associated with axon and synaptic transmissions which affect the neuronal connectivity in cognitive systems involved in AD pathophysiology. These genes may open ways to explore new effective treatments and early diagnosis before the onset of clinical symptoms.