Miracle-dz/UniFAR-FTUs huggingface dataset:
Solid State Photoreduction of Silver on Mesoporous Silica to Enhance Antifungal Activity

A solid-state Ultraviolet-photoreduction process of silver cations to produce Ag0 nanostructures on a mesoporous silica is presented as an innovative method for the preparation of efficient environmental anti-fouling agents. Mesoporous silica powder, contacted with AgNO3, is irradiated at 366 nm, where silica surface defects absorb. The detailed characterization of the materials enables us to document the silica assisted photo-reduction. The appearance of a Visible (Vis) band centered at 470 nm in the extinction spectra, due to the surface plasmon resonance of Ag0 nanostructures, and the morphology changes observed in transmission electron microscopy (TEM) images, associated with the increase of Ag/O ratio in energy dispersive X-ray (EDX) analysis, indicate the photo-induced formation of Ag0. The data demonstrate that the photo-induced reduction of silver cation occurs in the solid state and takes place through the activation of silica defects. The activation of the materials after UV-processing is then tested, evaluating their antimicrobial activity using an environmental filamentous fungus, Aspergillus niger. The treatment doubled inhibitory capacity in terms of minimal inhibitory concentration (MIC) and biofilm growth. The antimicrobial properties of silver–silica nanocomposites are investigated when dispersed in a commercial sealant; the nanocomposites show excellent dispersion in the silicon and improve its anti-fouling capacity.
Effect of Temperature on Catalytic Decomposition of Tar using Indonesian Iron Ore as Catalyst

In pyrolysis, tar is undesired byproduct because it causes operational problems such as the contamination in the inner wall of a reactor, blockages in pipes, corrosion and formation of tar aerosols and carcinogenic. Therefore, it is necessary to take steps for removing or decomposing tar into fuel gas (bio-syngas) and other compounds that are more useful. In this experiment, catalytic process was selected to decompose tar derived from wood waste pyrolysis. The study focused on the effect of temperature on catalytic tar decomposition using a fixed bed reactor which was equipped with preheater to convert tar into gas product. The variables studied were temperatures between 500 – 700 0 C and length of catalyst bed between 0.67 – 1.34 cm. Yields of gas, bio-oil, char and aqueous and also compositions of gas and liquid product were evaluated. The liquid product are represented in terms of acid compounds, hydrocarbon compounds, ketone compounds, oxygenate compounds, aromatic hydrocarbon - one cyclic (AH-1), poly aromatic hydrocarbon - two cyclic (PAH-2) and poly aromatic hydrocarbon - three cyclic (PAH-3). The results showed that the yields of gas and char increased by increasing temperature from 500 to 700 0 C, while bio-oil decreased. In addition, increasing temperature resulted new compounds of AH-1, PAH-2 and PAH-3. The yields of PAH-2 and PAH-3 on liquid product and H 2 and methane on gas product also increased, while yields of acid, ketone, AH-1 decreased.
3D Printed Punctal Plugs for Controlled Ocular Drug Delivery

Dry eye disease is a common ocular disorder that is characterised by tear deficiency or excessive tear evaporation. Current treatment involves the use of eye drops; however, therapeutic efficacy is limited because of poor ocular bioavailability of topically applied formulations. In this study, digital light processing (DLP) 3D printing was employed to develop dexamethasone-loaded punctal plugs. Punctal plugs with different drug loadings were fabricated using polyethylene glycol diacrylate (PEGDA) and polyethylene glycol 400 (PEG 400) to create a semi-interpenetrating network (semi-IPN). Drug-loaded punctal plugs were characterised in terms of physical characteristics (XRD and DSC), potential drug-photopolymer interactions (FTIR), drug release profile, and cytocompatibility. In vitro release kinetics of the punctal plugs were evaluated using an in-house flow rig model that mimics the subconjunctival space. The results showed sustained release of dexamethasone for up to 7 days from punctal plugs made with 20% w/w PEG 400 and 80% w/w PEGDA, while punctal plugs made with 100% PEGDA exhibited prolonged releases for more than 21 days. Herein, our study demonstrates that DLP 3D printing represents a potential manufacturing platform for fabricating personalised drug-loaded punctal plugs with extended release characteristics for ocular administration.
Potential Salivary Markers for Differential Diagnosis of Crohn’s Disease and Ulcerative Colitis

The properties of the saliva of patients with inflammatory bowel disease (IBD) are poorly recognized. Likewise, the diagnostic potential of saliva for differentiating various forms of IBD is largely unexplored. Therefore, we compared the concentrations of several parameters in unstimulated whole mixed saliva collected in a standardized manner from patients with active IBD unresponsive to conventional therapy. The samples were received from 27 patients with Crohn’s disease (CD), 24 patients with ulcerative colitis (UC), and 51 healthy individuals. Compared to the controls, the salivary concentrations of S100A8/calprotectin, myeloperoxidase, and IgA were significantly decreased in both CD and UC patients. In addition, patients with UC had decreased levels of TNF-R1 and decreased catalase activity. Interestingly, the concentrations of myeloperoxidase and TNF-R1 showed a high differentiation potential for CD and UC (AUC = 0.690 and 0.672, respectively). All these findings are discussed in the context of host defense in the oral cavity, patients’ prior treatment regimens, and smoking habits.
Atomistic Assessment of Solute-Solute Interactions during Grain Boundary Segregation

Grain boundary solute segregation is becoming increasingly common as a means of stabilizing nanocrystalline alloys. Thermodynamic models for grain boundary segregation have recently revealed the need for spectral information, i.e., the full distribution of environments available at the grain boundary during segregation, in order to capture the essential physics of the problem for complex systems like nanocrystalline materials. However, there has been only one proposed method of extending spectral segregation models beyond the dilute limit, and it is based on simple, fitted parameters that are not atomistically informed. In this work, we present a physically motived atomistic method to measure the full distribution of solute-solute interaction energies at the grain boundaries in a polycrystalline environment. We then cast the results into a simple thermodynamic model, analyze the Al(Mg) system as a case study, and demonstrate strong agreement with physically rigorous hybrid Monte Carlo/molecular statics simulations. This approach provides a means of rapidly measuring key interactions for non-dilute grain boundary segregation for any system with an interatomic potential.
Glycomacropeptide for Management of Insulin Resistance and Liver Metabolic Perturbations

Background and Aims: The increasing prevalence and absence of effective global treatment for metabolic syndrome (MetS) are alarming given the potential progression to severe non-communicable disorders such as type 2 diabetes and nonalcoholic fatty liver disease. The purpose of this study was to investigate the regulatory role of glycomacropeptide (GMP), a powerful milk peptide, in insulin resistance and liver dysmetabolism, two central MetS conditions. Materials and Methods: C57BL/6 male mice were fed a chow (Ctrl), high-fat, high-sucrose (HFHS) diet or HFHS diet along with GMP (200 mg/kg/day) administered by gavage for 12 weeks. Results: GMP lowered plasma insulin levels (in response to oral glucose tolerance test) and HOMA-IR index, indicating a more elevated systemic insulin sensitivity. GMP was also able to decrease oxidative stress and inflammation in the circulation as reflected by the decline of malondialdehyde, F2 isoprostanes and lipopolysaccharide. In the liver, GMP raised the protein expression of the endogenous anti-oxidative enzyme GPx involving the NRF2 signaling pathway. Moreover, the administration of GMP reduced the gene expression of hepatic pro-inflammatory COX-2, TNF-α and IL-6 via inactivation of the TLR4/NF-κB signaling pathway. Finally, GMP improved hepatic insulin sensitization given the modulation of AKT, p38 MAPK and SAPK/JNK activities, thereby restoring liver homeostasis as revealed by enhanced fatty acid β-oxidation, reduced lipogenesis and gluconeogenesis. Conclusions: Our study provides evidence that GMP represents a promising dietary nutraceutical in view of its beneficial regulation of systemic insulin resistance and hepatic insulin signaling pathway, likely via its powerful antioxidant and anti-inflammatory properties.
Novel Coagulation Factor VIII Gene Therapy in a Mouse Model of Hemophilia A by Lipid-Coated Fe3O4 Nanoparticles

Hemophilia A is a bleeding disease caused by loss of coagulation factor VIII (FVIII) function. Although prophylactic FVIII infusion prevents abnormal bleeding, disability and joint damage in hemophilia patients are common. The cost of treatment is among the highest for a single disease, and the adverse effects of repeated infusion are still an issue that has not been addressed. In this study, we established a nonviral gene therapy strategy to treat FVIII knockout (FVIII KO) mice. A novel gene therapy approach was developed using dipalmitoylphosphatidylcholine formulated with iron oxide (DPPC-Fe3O4) to carry the B-domain-deleted (BDD)-FVIII plasmid, which was delivered into the FVIII KO mice via tail vein injection. Here, a liver-specific albumin promoter-driven BDD-FVIII plasmid was constructed, and the binding ability of circular DNA was confirmed to be more stable than that of linear DNA when combined with DPPC-Fe3O4 nanoparticles. The FVIII KO mice that received the DPPC-Fe3O4 plasmid complex were assessed by staining the ferric ion of DPPC-Fe3O4 nanoparticles with Prussian blue in liver tissue. The bleeding of the FVIII KO mice was improved in a few weeks, as shown by assessing the activated partial thromboplastin time (aPTT). Furthermore, no liver toxicity, thromboses, deaths, or persistent changes after nonviral gene therapy were found, as shown by serum liver indices and histopathology. The results suggest that this novel gene therapy can successfully improve hemostasis disorder in FVIII KO mice and might be a promising approach to treating hemophilia A patients in clinical settings.
Composition of the Gut Microbiome Influences Production of Sulforaphane-Nitrile and Iberin-Nitrile from Glucosinolates in Broccoli Sprouts

Isothiocyanates, such as sulforaphane and iberin, derived from glucosinolates (GLS) in cruciferous vegetables, are known to prevent and suppress cancer development. GLS can also be converted by bacteria to biologically inert nitriles, such as sulforaphane-nitrile (SFN-NIT) and iberin-nitrile (IBN-NIT), but the role of the gut microbiome in this process is relatively undescribed and SFN-NIT excretion in humans is unknown. An ex vivo fecal incubation model with in vitro digested broccoli sprouts and 16S sequencing was utilized to explore the role of the gut microbiome in SFN- and IBN-NIT production. SFN-NIT excretion was measured among human subjects following broccoli sprout consumption. The fecal culture model showed high inter-individual variability in nitrile production and identified two sub-populations of microbial communities among the fecal cultures, which coincided with a differing abundance of nitriles. The Clostridiaceae family was associated with high levels, while individuals with a low abundance of nitriles were more enriched with taxa from the Enterobacteriaceae family. High levels of inter-individual variation in urine SFN-NIT levels were also observed, with peak excretion of SFN-NIT at 24 h post broccoli sprout consumption. These results suggest that nitrile production from broccoli, as opposed to isothiocyanates, could be influenced by gut microbiome composition, potentially lowering efficacy of cruciferous vegetable interventions.
Magnetic Resonance Simulation in Education: Quantitative Evaluation of an Actual Classroom Experience

Magnetic resonance is an imaging modality that implies a high complexity for radiographers. Despite some simulators having been developed for training purposes, we are not aware of any attempt to quantitatively measure their educational performance. The present study gives an answer to the question: Does an MRI simulator built on specific functional and non-functional requirements help radiographers learn MRI theoretical and practical concepts better than traditional educational method based on lectures? Our study was carried out in a single day by a total of 60 students of a main hospital in Madrid, Spain. The experiment followed a randomized pre-test post-test design with a control group that used a traditional educational method, and an experimental group that used our simulator. Knowledge level was assessed by means of an instrument with evidence of validity in its format and content, while its reliability was analyzed after the experiment. Statistical differences between both groups were measured. Significant statistical differences were found in favor of the participants who used the simulator for both the post-test score and the gain (difference between post-test and pre-test scores). The effect size turned out to be significant as well. In this work we evaluated a magnetic resonance simulation paradigm as a tool to help in the training of radiographers. The study shows that a simulator built on specific design requirements is a valuable complement to traditional education procedures, backed up with significant quantitative results.
Nintedanib Regulates GRK2 and CXCR2 to Reduce Neutrophil Recruitment in Endotoxin-Induced Lung Injury

The role of nintedanib, a multiple tyrosine kinase inhibitor, in the treatment of sepsis-induced acute lung injury (ALI) remains unclear. Lipopolysaccharide (LPS), also known as endotoxin, has been used to induce ALI. The goal of this study was to assess the effect of nintedanib in attenuating the histopathological changes of LPS-induced ALI. Nintedanib was administered via oral gavage to male C57BL/6 mice 24 h and 10 min before intratracheal endotoxin instillation. Lung histopathological characteristics, adhesion molecule expression, and the regulatory signaling pathways of neutrophil chemotaxis were analyzed after 24 h. We found that nintedanib significantly reduced histopathological changes and neutrophil recruitment in LPS-induced ALI. The number of neutrophils in bronchoalveolar lavage fluid (BALF) was reduced in nintedanib-treated relative to untreated mice with ALI. Nintedanib mediated the downregulation of the chemotactic response to LPS by reducing the expression of adhesion molecules and the phosphorylated p38:total p38 mitogen-activated protein kinase (MAPK) ratio in the lungs of mice with ALI. Nintedanib also reduced the expression of lymphocyte antigen 6 complex locus G6D (Ly6G) and very late antigen 4 (VLA-4) in BALF neutrophils and mediated the downregulation of chemokine (C-X-C motif) receptor 2 (CXCR2) and upregulation of G protein-coupled receptor kinase 2 (GRK2) activity in peripheral blood neutrophils in mice with LPS-induced ALI. Nintedanib improved the histopathological changes of LPS-induced ALI by reducing neutrophil chemotaxis. These effects were mediated by the inhibition of adhesion molecules via the activation of GRK2 and the inhibition of p38 MAPK and CXCR2.
Is It Possible to Create Antimicrobial Peptides Based on the Amyloidogenic Sequence of Ribosomal S1 Protein of P. aeruginosa?

The development and testing of new antimicrobial peptides (AMPs) represent an important milestone toward the development of new antimicrobial drugs that can inhibit the growth of pathogens and multidrug-resistant microorganisms such as Pseudomonas aeruginosa, Gram-negative bacteria. Most AMPs achieve these goals through mechanisms that disrupt the normal permeability of the cell membrane, which ultimately leads to the death of the pathogenic cell. Here, we developed a unique combination of a membrane penetrating peptide and peptides prone to amyloidogenesis to create hybrid peptide: “cell penetrating peptide + linker + amyloidogenic peptide”. We evaluated the antimicrobial effects of two peptides that were developed from sequences with different propensities for amyloid formation. Among the two hybrid peptides, one was found with antibacterial activity comparable to antibiotic gentamicin sulfate. Our peptides showed no toxicity to eukaryotic cells. In addition, we evaluated the effect on the antimicrobial properties of amino acid substitutions in the non-amyloidogenic region of peptides. We compared the results with data on the predicted secondary structure, hydrophobicity, and antimicrobial properties of the original and modified peptides. In conclusion, our study demonstrates the promise of hybrid peptides based on amyloidogenic regions of the ribosomal S1 protein for the development of new antimicrobial drugs against P. aeruginosa.
Magnetization Reversal Process and Magnetostatic Interactions in Fe56Co44/SiO2/Fe3O4 Core/Shell Ferromagnetic Nanowires with Non-Magnetic Interlayer

Nowadays, numerous works regarding nanowires or nanotubes are being published, studying different combinations of materials or geometries with single or multiple layers. However, works, where both nanotube and nanowires are forming complex structures, are scarcer due to the underlying difficulties that their fabrication and characterization entail. Among the specific applications for these nanostructures that can be used in sensing or high-density magnetic data storage devices, there are the fields of photonics or spintronics. To achieve further improvements in these research fields, a complete understanding of the magnetic properties exhibited by these nanostructures is needed, including their magnetization reversal processes and control of the magnetic domain walls. In order to gain a deeper insight into this topic, complex systems are being fabricated by altering their dimensions or composition. In this work, a successful process flow for the additive fabrication of core/shell nanowires arrays is developed. The core/shell nanostructures fabricated here consist of a magnetic nanowire nucleus (Fe56Co44), grown by electrodeposition and coated by a non-magnetic SiO2 layer coaxially surrounded by a magnetic Fe3O4 nanotubular coating both fabricated by means of the Atomic Layer Deposition (ALD) technique. Moreover, the magnetization reversal processes of these coaxial nanostructures and the magnetostatic interactions between the two magnetic components are investigated by means of standard magnetometry and First Order Reversal Curve methodology. From this study, a two-step magnetization reversal of the core/shell bimagnetic nanostructure is inferred, which is also corroborated by the hysteresis loops of individual core/shell nanostructures measured by Kerr effect-based magnetometer.
Attenuation of PITPNM1 Signaling Cascade Can Inhibit Breast Cancer Progression

Phosphatidylinositol transfer protein membrane-associated 1 (PITPNM1) contains a highly conserved phosphatidylinositol transfer domain which is involved in phosphoinositide trafficking and signaling transduction under physiological conditions. However, the functional role of PITPNM1 in cancer progression remains unknown. Here, by integrating datasets of The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer (METABRIC), we found that the expression of PITPNM1 is much higher in breast cancer tissues than in normal breast tissues, and a high expression of PITPNM1 predicts a poor prognosis for breast cancer patients. Through gene set variation analysis (GSEA) and gene ontology (GO) analysis, we found PITPNM1 is mainly associated with carcinogenesis and cell-to-cell signaling ontology. Silencing of PITPNM1, in vitro, significantly abrogates proliferation and colony formation of breast cancer cells. Collectively, PITPNM1 is an important prognostic indicator and a potential therapeutic target for breast cancer.
Dialectical Behaviour Therapy Improves Emotion Dysregulation Mainly in Binge Eating Disorder and Bulimia Nervosa: A Systematic Review and Meta-Analysis

Emotion dysregulation is a transdiagnostic phenomenon in Eating Disorders (ED), and Dialectical Behaviour Therapy (DBT) (which was developed for reducing dysregulated emotions in personality disorders) has been employed in patients with ED. This systematic review and meta-analysis investigated whether the effect of DBT was stronger on emotion dysregulation, general psychopathology, and Body Mass Index (BMI) in participants with ED, when compared to a control group (active therapy and waitlist). Eleven studies were identified in a systematic search in accordance with PRISMA guidelines. Most studies included participants with Binge Eating Disorder (BED) (n = 8), some with Bulimia Nervosa (BN) (n = 3), and only one with Anorexia Nervosa (AN). The pooled effect of DBT indicated a greater improvement in Emotion Regulation (ER) (g = −0.69, p = 0.01), depressive symptoms (g = −0.33, p < 0.00001), ED psychopathology (MD = −0.90, p = 0.005), Objective Binge Episodes (OBE) (MD = −0.27, p = 0.003), and BMI (MD = −1.93, p = 0.01) compared to the control group. No improvement was detected in eating ER following DBT (p = 0.41). DBT demonstrated greater efficacy compared with the control group in improving emotion dysregulation, ED psychopathology, and BMI in ED. The limitations included the small number of studies and high variability.
Subgroup Preference Neural Network

Subgroup label ranking aims to rank groups of labels using a single ranking model, is a new problem faced in preference learning. This paper introduces the Subgroup Preference Neural Network (SGPNN) that combines multiple networks have different activation function, learning rate, and output layer into one artificial neural network (ANN) to discover the hidden relation between the subgroups’ multi-labels. The SGPNN is a feedforward (FF), partially connected network that has a single middle layer and uses stairstep (SS) multi-valued activation function to enhance the prediction’s probability and accelerate the ranking convergence. The novel structure of the proposed SGPNN consists of a multi-activation function neuron (MAFN) in the middle layer to rank each subgroup independently. The SGPNN uses gradient ascent to maximize the Spearman ranking correlation between the groups of labels. Each label is represented by an output neuron that has a single SS function. The proposed SGPNN using conjoint dataset outperforms the other label ranking methods which uses each dataset individually. The proposed SGPNN achieves an average accuracy of 91.4% using the conjoint dataset compared to supervised clustering, decision tree, multilayer perceptron label ranking and label ranking forests that achieve an average accuracy of 60%, 84.8%, 69.2% and 73%, respectively, using the individual dataset.