Miracle-dz/UniFAR-FTUs huggingface dataset:
A Hydrophobic Derivative of Ciprofloxacin as a New Photoinitiator of Two-Photon Polymerization: Synthesis and Usage for the Formation of Biocompatible Polylactide-Based 3D Scaffolds

A hydrophobic derivative of ciprofloxacin, hexanoylated ciprofloxacin (CPF-hex), has been used as a photoinitiator (PI) for two-photon polymerization (2PP) for the first time. We present, here, the synthesis of CPF-hex and its application for 2PP of methacrylate-terminated star-shaped poly (D,L-lactide), as well a systematic study on the optical, physicochemical and mechanical properties of the photocurable resin and prepared three-dimensional scaffolds. CPF-hex exhibited good solubility in the photocurable resin, high absorption at the two-photon wavelength and a low fluorescence quantum yield = 0.079. Structuring tests showed a relatively broad processing window and revealed the efficiency of CPF-hex as a 2PP PI. The prepared three-dimensional scaffolds showed good thermal stability; thermal decomposition was observed only at 314 °C. In addition, they demonstrated an increase in Young’s modulus after the UV post-curing (from 336 ± 79 MPa to 564 ± 183 MPa, which is close to those of a cancellous (trabecular) bone). Moreover, using CPF-hex as a 2PP PI did not compromise the scaffolds’ low cytotoxicity, thus they are suitable for potential application in bone tissue regeneration.
A cell-based drug discovery assay identifies inhibition of cell stress responses as a new approach to treatment of epidermolysis bullosa simplex

ABSTRACT In the skin fragility disorder epidermolysis bullosa simplex (EBS), mutations in keratin 14 (K14, also known as KRT14) or keratin 5 (K5, also known as KRT5) lead to keratinocyte rupture and skin blistering. Severe forms of EBS are associated with cytoplasmic protein aggregates, with elevated kinase activation of ERK1 and ERK2 (ERK1/2; also known as MAPK3 and MAPK1, respectively), suggesting intrinsic stress caused by misfolded keratin protein. Human keratinocyte EBS reporter cells stably expressing GFP-tagged EBS-mimetic mutant K14 were used to optimize a semi-automated system to quantify the effects of test compounds on keratin aggregates. Screening of a protein kinase inhibitor library identified several candidates that reduced aggregates and impacted on epidermal growth factor receptor (EGFR) signalling. EGF ligand exposure induced keratin aggregates in EBS reporter keratinocytes, which was reversible by EGFR inhibition. EBS keratinocytes treated with a known EGFR inhibitor, afatinib, were driven out of activation and towards quiescence with minimal cell death. Aggregate reduction was accompanied by denser keratin filament networks with enhanced intercellular cohesion and resilience, which when extrapolated to a whole tissue context would predict reduced epidermal fragility in EBS patients. This assay system provides a powerful tool for discovery and development of new pathway intervention therapeutic avenues for EBS.
Ethyl Lauroyl Arginate, an Inherently Multicomponent Surfactant System

Ethyl lauroyl arginate (LAE) is an amino acid-based cationic surfactant with low toxicity and antimicrobial activity. It is widely used as a food preservative and component for food packaging. When stored, LAE decomposes by hydrolysis into surface-active components Nα-lauroyl–l-arginine (LAS) or dodecanoic (lauric) acid. There are only a limited number of reports considering the mechanism of surface activity of LAE. Thus, we analysed the surface tension isotherm of LAE with analytical standard purity in relation to LAE after prolonged storage. We used quantum mechanical density functional theory (DFT) computations to determine the preferred hydrolysis path and discuss the possibility of forming highly surface-active heterodimers, LAE-dodecanoate anion, or LAE-LAS. Applying molecular dynamics simulations, we determined the stability of those dimers linked by electrostatic interactions and hydrogen bonds. We used the adsorption model of surfactant mixtures to successfully describe the experimental surface tension isotherms. The real part surface dilational modulus determined by the oscillation drop method follows a diffusional transport mechanism. However, the nonlinear response of the surface tension could be observed for LAE concentration close to and above Critical Micelle Concentration (CMC). Nonlinearity originates from the presence of micelles and the reorganisation of the interfacial layer.
A Galactosidase-Activatable Fluorescent Probe for Detection of Bacteria Based on BODIPY

Pathogenic E. coli infection is one of the most widespread foodborne diseases, so the development of sensitive, reliable and easy operating detection tests is a key issue for food safety. Identifying bacteria with a fluorescent medium is more sensitive and faster than using chromogenic media. This study designed and synthesized a β-galactosidase-activatable fluorescent probe BOD-Gal for the sensitive detection of E. coli. It employed a biocompatible and photostable 4,4-difluoro-3a,4a-diaza-s-indancene (BODIPY) as the fluorophore to form a β-O-glycosidic bond with galactose, allowing the BOD-Gal to show significant on-off fluorescent signals for in vitro and in vivo bacterial detection. This work shows the potential for the use of a BODIPY based enzyme substrate for pathogen detection.
Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms

The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environmental threat but also as an exceptional material for sustainable development. The application of supervised machine learning (ML) algorithms to forecast the mechanical properties of concrete also has a significant role in developing the innovative environment in the field of civil engineering. This study was based on the use of the artificial neural network (ANN), boosting, and AdaBoost ML approaches, based on the python coding to predict the compressive strength (CS) of high calcium fly-ash-based GPC. The performance comparison of both the employed techniques in terms of prediction reveals that the ensemble ML approaches, AdaBoost, and boosting were more effective than the individual ML technique (ANN). The boosting indicates the highest value of R2 equals 0.96, and AdaBoost gives 0.93, while the ANN model was less accurate, indicating the coefficient of determination value equals 0.87. The lesser values of the errors, MAE, MSE, and RMSE of the boosting technique give 1.69 MPa, 4.16 MPa, and 2.04 MPa, respectively, indicating the high accuracy of the boosting algorithm. However, the statistical check of the errors (MAE, MSE, RMSE) and k-fold cross-validation method confirms the high precision of the boosting technique. In addition, the sensitivity analysis was also introduced to evaluate the contribution level of the input parameters towards the prediction of CS of GPC. The better accuracy can be achieved by incorporating other ensemble ML techniques such as AdaBoost, bagging, and gradient boosting.
Domain Analysis and Motif Matcher (DAMM): A Program to Predict Selectivity Determinants in Monosiga brevicollis PDZ Domains Using Human PDZ Data

Choanoflagellates are single-celled eukaryotes with complex signaling pathways. They are considered the closest non-metazoan ancestors to mammals and other metazoans and form multicellular-like states called rosettes. The choanoflagellate Monosiga brevicollis contains over 150 PDZ domains, an important peptide-binding domain in all three domains of life (Archaea, Bacteria, and Eukarya). Therefore, an understanding of PDZ domain signaling pathways in choanoflagellates may provide insight into the origins of multicellularity. PDZ domains recognize the C-terminus of target proteins and regulate signaling and trafficking pathways, as well as cellular adhesion. Here, we developed a computational software suite, Domain Analysis and Motif Matcher (DAMM), that analyzes peptide-binding cleft sequence identity as compared with human PDZ domains and that can be used in combination with literature searches of known human PDZ-interacting sequences to predict target specificity in choanoflagellate PDZ domains. We used this program, protein biochemistry, fluorescence polarization, and structural analyses to characterize the specificity of A9UPE9_MONBE, a M. brevicollis PDZ domain-containing protein with no homology to any metazoan protein, finding that its PDZ domain is most similar to those of the DLG family. We then identified two endogenous sequences that bind A9UPE9 PDZ with <100 μM affinity, a value commonly considered the threshold for cellular PDZ–peptide interactions. Taken together, this approach can be used to predict cellular targets of previously uncharacterized PDZ domains in choanoflagellates and other organisms. Our data contribute to investigations into choanoflagellate signaling and how it informs metazoan evolution.
Experimental Study of Bentonite-Free Water Based Mud Reinforced with Carboxymethylated Tapioca Starch: Rheological Modeling and Optimization Using Response Surface Methodology (RSM)

Drilling mud’s rheological characteristics, such as plastic viscosity and yield point, are adversely affected with an inappropriate mud formulation. Native starch is one of the most important components in water-based mud because it improves the rheological and filtration characteristics of the mud. The native starch stability under various temperature and exposure time regimes is an important concern for utilizing starch in oil and gas drilling operations. In this work, tapioca starch was modified using carboxymethylation for the first time in order to improve its performance in non-damaging water-based muds. The modified starch was characterized by Fourier-transform infrared spectroscopy and X-ray diffraction. The thermal stability was tested using thermal gravimetric analysis. Various mud blends were formulated based on the experimental design using response surface methodology (RSM) to investigate their performance at various temperature conditions. Thirty experimental runs were carried out based on the selected factors and responses considering the optimal (custom) design, and the results were analyzed through ANOVA. The Fourier-transform infrared spectroscopy and X-ray diffraction results confirmed the carboxymethylation of starch. The TGA analysis revealed strong thermal stability after modification. Additionally, the Power law model (PLM) described the obtained rheological data for the selected formulations, resulting in determination coefficients of more than 0.95. Furthermore, the examined samples showed a reduction in the flow behavior index from 0.30 to 0.21 and an increase in the consistency index from 5.6 to 15.1. Optimization and confirmation results revealed the adequacy of the generated empirical models for both plastic viscosity and yield point. The obtained consistency index values provided a direct relationship with the modified starch concentration, indicating an improvement in the cutting carrying capacity of mud. Based on the current literature survey, the studied formulation has not been reported in the literature.
Applications of Polymeric Composites in Bone Tissue Engineering and Jawbone Regeneration

Polymer-based composites are a group of biomaterials that exert synergic and combined activity. There are multiple reported uses of these composites in multiple biomedical areas, such as drug carriers, in wound dressings, and, more prominently, in tissue engineering and regenerative medicine. Bone grafting is a promising field in the use of polymeric composites, as this is the second most frequently transplanted organ in the United States. Advances in novel biomaterials, such as polymeric composites, will undoubtedly be of great aid in bone tissue engineering and regeneration. In this paper, a general view of bone structure and polymeric composites will be given, discussing the potential role of these components in bone tissue. Moreover, the most relevant jawbone and maxillofacial applications of polymeric composites will be revised in this article, collecting the main knowledge about this topic and emphasizing the need of further clinical studies in humans.
Immunohistochemical expression of programmed death-ligand 1 and CD8 in glioblastomas

Background Glioblastoma is the most aggressive primary malignant brain tumor in adults and is characterized by poor prognosis. Immune evasion occurs via programmed death-ligand 1 (PD-L1)/programmed death receptor 1 (PD-1) interaction. Some malignant tumors have responded to PD-L1/PD-1 blockade treatment strategies, and PD-L1 has been described as a potential predictive biomarker. This study discussed the expression of PD-L1 and CD8 in glioblastomas. Methods Thirty cases of glioblastoma were stained immunohistochemically for PD-L1 and CD8, where PD-L1 expression in glioblastoma tumor tissue above 1% is considered positive and CD-8 is expressed in tumor infiltrating lymphocytes. The expression of each marker was correlated with clinicopathologic parameters. Survival analysis was conducted to correlate progression-free survival (PFS) and overall survival (OS) with PD-L1 and CD8 expression. Results Diffuse/fibrillary PD-L1 was expressed in all cases (mean expression, 57.6%), whereas membranous PD-L1 was expressed in six of 30 cases. CD8-positive tumor-infiltrating lymphocytes (CD8+ TILs) had a median expression of 10%. PD-L1 and CD8 were positively correlated (p = .001). High PD-L1 expression was associated with worse PFS and OS (p = .026 and p = .001, respectively). Correlation of CD8+ TILs percentage with age, sex, tumor site, laterality, and outcomes were statistically insignificant. Multivariate analysis revealed that PD-L1 was the only independent factor that affected prognosis. Conclusions PD-L1 expression in patients with glioblastoma is robust; higher PD-L1 expression is associated with lower CD8+ TIL expression and worse prognosis.
A pleiotropic ATM variant (rs1800057 C>G) is associated with risk of multiple cancers.

ATM (ataxia-telangiectasia mutated) is an important cell-cycle checkpoint kinase required for cellular response to DNA damage. Activated by DNA double strand breaks, ATM regulates the activities of many downstream proteins involved in various carcinogenic events. Therefore, ATM or its genetic variants may have a pleiotropic effect in cancer development. We conducted a pleiotropic analysis to evaluate associations between genetic variants of ATM and risk of multiple cancers. With genotyping data extracted from previously published genome-wide association studies of various cancers, we performed multivariate logistic regression analysis, followed by a meta-analysis for each cancer site, to identify cancer risk-associated single-nucleotide polymorphisms (SNPs). In the ASSET two-sided analysis, we found that two ATM SNPs were significantly associated with risk of multiple cancers. One tagging SNP (rs1800057 C>G) was associated with risk of multiple cancers (two-sided P=5.27×10 -7). Because ATM rs1800057 is a missense variant, we also explored the intermediate phenotypes through which this variant may confer risk of multiple cancers and identified a possible immune-mediated effect of this variant. Our findings indicate that genetic variants of ATM may have a pleiotropic effect on cancer risk and thus provide an important insight into common mechanisms of carcinogenesis.
Improving cancer driver gene identification using multi-task learning on graph convolutional network

Cancer is thought to be caused by the accumulation of driver genetic mutations. Therefore, identifying cancer driver genes plays a crucial role in understanding the molecular mechanism of cancer and developing precision therapies and biomarkers. In this work, we propose a Multi-Task learning method, called MTGCN, based on the Graph Convolutional Network to identify cancer driver genes. First, we augment gene features by introducing their features on the protein-protein interaction (PPI) network. After that, the multi-task learning framework propagates and aggregates nodes and graph features from input to next layer to learn node embedding features, simultaneously optimizing the node prediction task and the link prediction task. Finally, we use a Bayesian task weight learner to balance the two tasks automatically. The outputs of MTGCN assign each gene a probability of being a cancer driver gene. Our method and the other four existing methods are applied to predict cancer drivers for pan-cancer and some single cancer types. The experimental results show that our model shows outstanding performance compared with the state-of-the-art methods in terms of the area under the Receiver Operating Characteristic (ROC) curves and the area under the precision-recall curves. The MTGCN is freely available via https://github.com/weiba/MTGCN.
Effects of Concurrent Training on 1RM and VO2 in Adults: Systematic Review with Meta-analysis

Abstract The purpose of this systematic review was to analyze the effects of concurrent training on one repetition maximum (1RM), maximum oxygen consumption (VO2max), and peak oxygen consumption (VO2peak) in healthy adults. The review followed PRISMA recommendations using randomized controlled trials in nine databases. Twenty-one studies met the inclusion criteria, totaling a sample of 796 subjects to perform the meta-analysis. As result, concurrent training provides similar increases in 1RM as strength training for upper limbs (standardized mean difference [SMD]: 0.12; 95% IC: [−0.18; 0.41]; p=0.43) and for the lower limbs (SMD: −0.32; 95% IC: [−0.79; 0.15]; p=0.19). Similarly, no difference was found in the aerobic capacity between the concurrent training vs. aerobic training groups ([SMD – VO2max]: −0.19; 95% IC: [−0.71; 0.33]; p=0.48 and [SMD – VO2peak]: −0.24; 95% IC: [−0.57; 0.08]; p=0.14). Based on the results found, we can affirm that a) similar to strength training, concurrent training provides maximum strength development for upper and lower limbs; and b) cardiorespiratory capacity is not impaired by concurrent training in relation to aerobic training, demonstrating the compatibility of the two training sessions.
Critical discussion on drug efflux in Mycobacterium tuberculosis

Abstract Mycobacterium tuberculosis (Mtb) can withstand months of antibiotic treatment. An important goal of tuberculosis research is to shorten the treatment to reduce the burden on patients, increase adherence to the drug regimen and thereby slow down the spread of drug resistance. Inhibition of drug efflux pumps by small molecules has been advocated as a promising strategy to attack persistent Mtb and shorten therapy. Although mycobacterial drug efflux pumps have been broadly investigated, mechanistic studies are scarce. In this critical review, we shed light on drug efflux in its larger mechanistic context by considering the intricate interplay between membrane transporters annotated as drug efflux pumps, membrane energetics, efflux inhibitors and cell wall biosynthesis processes. We conclude that a great wealth of data on mycobacterial transporters is insufficient to distinguish by what mechanism they contribute to drug resistance. Recent studies suggest that some drug efflux pumps transport structural lipids of the mycobacterial cell wall and that the action of certain drug efflux inhibitors involves dissipation of the proton motive force, thereby draining the energy source of all active membrane transporters. We propose recommendations on the generation and interpretation of drug efflux data to reduce ambiguities and promote assigning novel roles to mycobacterial membrane transporters.
A bacterial membrane sculpting protein with BAR domain-like activity

Bin/Amphiphysin/RVS (BAR) domain proteins belong to a superfamily of coiled-coil proteins influencing membrane curvature in eukaryotes and are associated with vesicle biogenesis, vesicle-mediated protein trafficking, and intracellular signaling. Here, we report a bacterial protein with BAR domain-like activity, BdpA, from Shewanella oneidensis MR-1, known to produce redox-active membrane vesicles and micrometer-scale outer membrane extensions (OMEs). BdpA is required for uniform size distribution of membrane vesicles and influences scaffolding of OMEs into a consistent diameter and curvature. Cryo-TEM reveals that a strain lacking BdpA produces lobed, disordered OMEs rather than membrane tubules or narrow chains produced by the wild-type strain. Overexpression of BdpA promotes OME formation during planktonic growth of S. oneidensis where they are not typically observed. Heterologous expression results in OME production in Marinobacter atlanticus and Escherichia coli. Based on the ability of BdpA to alter membrane architecture in vivo, we propose that BdpA and its homologs comprise a newly identified class of bacterial BAR domain-like proteins.
Crystallization, Structure and Significantly Improved Mechanical Properties of PLA/PPC Blends Compatibilized with PLA-PPC Copolymers Produced by Reactions Initiated with TBT or TDI

Poly (lactic acid) (PLA)-Poly (propylene carbonate) (PPC) block copolymer compatibilizers are produced in incompatible 70wt%PLA/PPC blend by initiating transesterification with addition of 1% of tetra butyl titanate (TBT) or by chain extension with addition of 2% of 2,4-toluene diisocyanate (TDI). The above blends can have much better mechanical properties than the blend without TBT and TDI. The elongation at break is dramatically larger (114% with 2% of TDI and 60% with 1% of TBT) than the blend without TDI and TBT, with a slightly lower mechanical strength. A small fraction of the copolymer is likely formed in the PLA/PPC blend with addition of TBT, and a significant amount of the copolymer can be made with addition of TDI. The copolymer produced with TDI has PPC as a major content (~70 wt%) and forms a miscible interphase with its own Tg. The crystallinity of the blend with TDI is significantly lower than the blend without TDI, as the PLA blocks of the copolymer in the interphase is hardly to crystallize. The average molecular weight increases significantly with addition of TDI, likely compensating the lower mechanical strength due to lower crystallinity. Material degradation can occur with addition of TBT, but it is very limited with 1% of TBT. However, compared with the blends without TBT, the PLA crystallinity of the blend with 1%TBT increases sharply during the cooling process, which likely compensates the loss of mechanical strength due to the slightly material degradation. The added TDI does not have any significant impact on PLA lamellar packing, but the addition of TBT can make PLA lamellar packing much less ordered, presumably resulted from much smaller PPC domains formed in the blend due to better compatibility.
Building an IoT Platform Based on Service Containerisation

IoT platforms have become quite complex from a technical viewpoint, becoming the cornerstone for information sharing, storing, and indexing given the unprecedented scale of smart services being available by massive deployments of a large set of data-enabled devices. These platforms rely on structured formats that exploit standard technologies to deal with the gathered data, thus creating the need for carefully designed customised systems that can handle thousands of heterogeneous data sensors/actuators, multiple processing frameworks, and storage solutions. We present the SCoT2.0 platform, a generic-purpose IoT Platform that can acquire, process, and visualise data using methods adequate for both real-time processing and long-term Machine Learning (ML)-based analysis. Our goal is to develop a large-scale system that can be applied to multiple real-world scenarios and is potentially deployable on private clouds for multiple verticals. Our approach relies on extensive service containerisation, and we present the different design choices, technical challenges, and solutions found while building our own IoT platform. We validate this platform supporting two very distinct IoT projects (750 physical devices), and we analyse scaling issues within the platform components.