Positions of the Mandibular Foramen and Canal in Different Skeletal Classes and Implications for Bilateral Sagittal Split Osteotomy.

Objectives: To evaluate the positions of the mandibular foramen (MF) and mandibular canal (MC) between different skeletal classes to highlight the implications for bilateral sagittal split osteotomy (BSSO). Methods: A cross-sectional study was performed using cone-beam computed tomography on 90 patients classified into classes I, II and III. Linear measurements were performed on multiplanar reconstructions as follows: from the MF to the edge of the mandibular ramus (1), to the mandibular notch (2), to the ramus width (3) and to the occlusal plane (4); and from the MC to the alveolar crest (A), to the lower border of the mandible (B) and to the mandibular buccal cortical bone (C). Mandibular thickness (D), width (E) and height (F) of the MC were measured. Intra-class correlation coefficient (ICC) checked the reliability. Two-way ANOVA and Tukey's test were used to compare measurements and classes. Results: Linear measurements 2 presented a statistically significant difference between classes I and II. There was no statistically significant difference between the classes and measurements B, C, D, E and F. Linear measurements A were shorter in class III than in class II. Conclusions: Although most measurements suggest that the BSSO technique does not need to be modified for each skeletal class, measurements from the MF to the mandibular notch in class II and from the MC to the alveolar crest on distal of the second molars in class III could help surgeons to recognize critical regions.

Structural basis for the rescue of hyperexcitable cells by the amyotrophic lateral sclerosis drug Riluzole.

Neuronal hyperexcitability is a key element of many neurodegenerative disorders including the motor neuron disease Amyotrophic Lateral Sclerosis (ALS), where it occurs associated with elevated late sodium current (INaL). INaL results from incomplete inactivation of voltage-gated sodium channels (VGSCs) after their opening and shapes physiological membrane excitability. However, dysfunctional increases can cause hyperexcitability-associated diseases. Here we reveal the atypical binding mechanism which explains how the neuroprotective ALS-treatment drug riluzole stabilises VGSCs in their inactivated state to cause the suppression of INaL that leads to reversed cellular overexcitability. Riluzole accumulates in the membrane and enters VGSCs through openings to their membrane-accessible fenestrations. Riluzole binds within these fenestrations to stabilise the inactivated channel state, allowing for the selective allosteric inhibition of INaL without the physical block of Na+ conduction associated with traditional channel pore binding VGSC drugs. We further demonstrate that riluzole can reproduce these effects on a disease variant of the non-neuronal VGSC isoform Nav1.4, where pathologically increased INaL is caused directly by mutation. Overall, we identify a model for VGSC inhibition that produces effects consistent with the inhibitory action of riluzole observed in models of ALS. Our findings will aid future drug design and supports research directed towards riluzole repurposing.

Lessons learned during the journey of data: from experiment to model for predicting kinase affinity, selectivity, polypharmacology, and resistance.

Recent advances in machine learning (ML) are reshaping drug discovery. Structure-based ML methods use physically-inspired models to predict binding affinities from protein:ligand complexes. These methods promise to enable the integration of data for many related targets, which addresses issues related to data scarcity for single targets and could enable generalizable predictions for a broad range of targets, including mutants. In this work, we report our experiences in building KinoML, a novel framework for ML in target-based small molecule drug discovery with an emphasis on structure-enabled methods. KinoML focuses currently on kinases as the relative structural conservation of this protein superfamily, particularly in the kinase domain, means it is possible to leverage data from the entire superfamily to make structure-informed predictions about binding affinities, selectivities, and drug resistance. Some key lessons learned in building KinoML include: the importance of reproducible data collection and deposition, the harmonization of molecular data and featurization, and the choice of the right data format to ensure reusability and reproducibility of ML models. As a result, KinoML allows users to easily achieve three tasks: accessing and curating molecular data; featurizing this data with representations suitable for ML applications; and running reproducible ML experiments that require access to ligand, protein, and assay information to predict ligand affinity. Despite KinoML focusing on kinases, this framework can be applied to other proteins. The lessons reported here can help guide the development of platforms for structure-enabled ML in other areas of drug discovery.

Therapeutic Peptides Are Preferentially Solubilized in Specific Microenvironments within PEG-PLGA Polymer Nanoparticles.

Polymeric nanoparticles are a highly promising drug delivery formulation. However, a lack of understanding of the molecular mechanisms that underlie their drug solubilization and controlled release capabilities has hindered the efficient clinical translation of such technologies. Polyethylene glycol-poly(lactic-co-glycolic) acid (PEG-PLGA) nanoparticles have been widely studied as cancer drug delivery vehicles. In this letter, we use unbiased coarse-grained molecular dynamics simulations to model the self-assembly of a PEG-PLGA nanoparticle and its solubulization of the anticancer peptide, EEK, with good agreement with previously reported experimental structural data. We applied unsupervised machine learning techniques to quantify the conformations that polymers adopt at various locations within the nanoparticle. We find that the local microenvironments formed by the various polymer conformations promote preferential EEK solubilization within specific regions of the NP. This demonstrates that these microenvironments are key in controlling drug storage locations within nanoparticles, supporting the rational design of nanoparticles for therapeutic applications.

Topology-controlled self-assembly of amphiphilic block copolymers.

Contemporary synthetic chemistry approaches can be used to yield a range of distinct polymer topologies with precise control. The topology of a polymer strongly influences its self-assembly into complex nanostructures however a clear mechanistic understanding of the relationship between polymer topology and self-assembly has not yet been developed. In this work, we use atomistic molecular dynamics simulations to provide a nanoscale picture of the self-assembly of three poly(ethylene oxide)-poly(methyl acrylate) block copolymers with different topologies into micelles. We find that the topology affects the ability of the micelle to form a compact hydrophobic core, which directly affects its stability. Also, we apply unsupervised machine learning techniques to show that the topology of a polymer affects its ability to take a conformation in response to the local environment within the micelles. This work provides foundations for the rational design of polymer nanostructures based on their underlying topology.

Fabrication of Chitosan/PEGDA Bionanocomposites for Enhanced Drug Encapsulation and Release Efficiency.

Drug delivery systems (DDS) have evolved in the last decades with the development of hydrogels and particles. However, challenges such as high systemic uptake, side effects, low bioavailability, and encapsulation efficiency continue to be significant hurdles faced by such DDSs. Particles and hydrogels can be specifically designed for targeted DDSs to mitigate some of these problems. This study developed chitosan (Cs) particles (Ps) and composite films using poly(ethylene glycol) diacrylate (PEGDA) as a copolymer to encapsulate gentamicin (GtS) for drug delivery. We demonstrated that lysozyme degrades the chitosan ß-1,4 glycosidic bonds to release GtS. PEGDA increased drug encapsulation efficiency by shielding the repelling forces of like charges between Cs and GtS. The data show that PEGDA does not hinder enzymatic degradation while increasing drug encapsulation efficiency and producing more homogeneous particles. Additionally, we utilized Michael's reaction to cross-link Cs, CsPs, and PEGDA to produce a film designed for drug delivery. The film is an anchor for CsPs to prevent premature drug release. The cross-linking of Cs and PEGDA does not affect lysozyme activity, and CsPs could successfully release GtS without affecting GtS activity.

Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES.

Using generative deep learning models and reinforcement learning together can effectively generate new molecules with desired properties. By employing a multi-objective scoring function, thousands of high-scoring molecules can be generated, making this approach useful for drug discovery and material science. However, the application of these methods can be hindered by computationally expensive or time-consuming scoring procedures, particularly when a large number of function calls are required as feedback in the reinforcement learning optimization. Here, we propose the use of double-loop reinforcement learning with simplified molecular line entry system (SMILES) augmentation to improve the efficiency and speed of the optimization. By adding an inner loop that augments the generated SMILES strings to non-canonical SMILES for use in additional reinforcement learning rounds, we can both reuse the scoring calculations on the molecular level, thereby speeding up the learning process, as well as offer additional protection against mode collapse. We find that employing between 5 and 10 augmentation repetitions is optimal for the scoring functions tested and is further associated with an increased diversity in the generated compounds, improved reproducibility of the sampling runs and the generation of molecules of higher similarity to known ligands.

Modular Software for Generating and Modeling Diverse Polymer Databases.

Machine learning methods offer the opportunity to design new functional materials on an unprecedented scale; however, building the large, diverse databases of molecules on which to train such methods remains a daunting task. Automated computational chemistry modeling workflows are therefore becoming essential tools in this data-driven hunt for new materials with novel properties, since they offer a means by which to create and curate molecular databases without requiring significant levels of user input. This ensures that well-founded concerns regarding data provenance, reproducibility, and replicability are mitigated. We have developed a versatile and flexible software package, PySoftK (Python Soft Matter at King's College London) that provides flexible, automated computational workflows to create, model, and curate libraries of polymers with minimal user intervention. PySoftK is available as an efficient, fully tested, and easily installable Python package. Key features of the software include the wide range of different polymer topologies that can be automatically generated and its fully parallelized library generation tools. It is anticipated that PySoftK will support the generation, modeling, and curation of large polymer libraries to support functional materials discovery in the nanotechnology and biotechnology arenas.

Directly imaging emergence of phase separation in peroxidized lipid membranes.

Lipid peroxidation is a process which is key in cell signaling and disease, it is exploited in cancer therapy in the form of photodynamic therapy. The appearance of hydrophilic moieties within the bilayer's hydrocarbon core will dramatically alter the structure and mechanical behavior of membranes. Here, we combine viscosity sensitive fluorophores, advanced microscopy, and X-ray diffraction and molecular simulations to directly and quantitatively measure the bilayer's structural and viscoelastic properties, and correlate these with atomistic molecular modelling. Our results indicate an increase in microviscosity and a decrease in the bending rigidity upon peroxidation of the membranes, contrary to the trend observed with non-oxidized lipids. Fluorescence lifetime imaging microscopy and MD simulations give evidence for the presence of membrane regions of different local order in the oxidized membranes. We hypothesize that oxidation promotes stronger lipid-lipid interactions, which lead to an increase in the lateral heterogeneity within the bilayer and the creation of lipid clusters of higher order.

Conformational Heterogeneity and Interchain Percolation Revealed in an Amorphous Conjugated Polymer.

Conjugated polymers are employed in a variety of application areas due to their bright fluorescence and strong biocompatibility. However, understanding the structure of amorphous conjugated polymers on the nanoscale is extremely challenging compared to their related crystalline phases. Using a bespoke classical force field, we study amorphous poly(9,9-di-n-octylfluorene-alt-benzothiadiazole) (F8BT) with molecular dynamics simulations to investigate the role that its nanoscale structure plays in controlling its emergent (and all-important) optical properties. Notably, we show that a giant percolating cluster exists within amorphous F8BT, which has ramifications in understanding the nature of interchain species that drive the quantum yield reduction and bathochromic shift observed in conjugated polymer-based devices and nanostructures. We also show that distinct conformations can be unravelled from within the disordered structure of amorphous F8BT using a two-stage machine learning protocol, highlighting a link between molecular conformation and ring stacking propensity. This work provides predictive understanding by which to enhance the optical properties of next-generation conjugated polymer-based devices and materials by rational, simulation-led design principles.

In vitro induced pluripotency from urine-derived cells in porcine.

BACKGROUND: The generation of induced pluripotent stem cells (iPSC) has been a game-changer in translational and regenerative medicine; however, their large-scale applicability is still hampered by the scarcity of accessible, safe, and reproducible protocols. The porcine model is a large biomedical model that enables translational applications, including gene editing, long term in vivo and offspring analysis; therefore, suitable for both medicine and animal production. AIM: To reprogramme in vitro into pluripotency, and herein urine-derived cells (UDCs) were isolated from porcine urine. METHODS: The UDCs were reprogrammed in vitro using human or murine octamer-binding transcription factor 4 (OCT4), SRY-box2 (SOX2), Kruppel-like factor 4 (KLF4), and C-MYC, and cultured with basic fibroblast growth factor (bFGF) supplementation. To characterize the putative porcine iPSCs three clonal lineages were submitted to immunocytochemistry for alkaline phosphatase (AP), OCT4, SOX2, NANOG, TRA1 81 and SSEA 1 detection. Endogenous transcripts related to the pluripotency (OCT4, SOX2 and NANOG) were analyzed via reverse transcription quantitative real-time polymerase chain reaction in different time points during the culture, and all three lineages formed embryoid bodies (EBs) when cultured in suspension without bFGF supplementation. RESULTS: The UDCs were isolated from swine urine samples and when at passage 2 submitted to in vitro reprogramming. Colonies of putative iPSCs were obtained only from UDCs transduced with the murine factors (mOSKM), but not from human factors (hOSKM). Three clonal lineages were isolated and further cultured for at least 28 passages, all the lineages were positive for AP detection, the OCT4, SOX2, NANOG markers, albeit the immunocytochemical analysis also revealed heterogeneous phenotypic profiles among lineages and passages for NANOG and SSEA1, similar results were observed in the abundance of the endogenous transcripts related to pluripotent state. All the clonal lineages when cultured in suspension without bFGF were able to form EBs expressing ectoderm and mesoderm layers transcripts. CONCLUSION: For the first time UDCs were isolated in the swine model and reprogrammed into a pluripotent-like state, enabling new numerous applications in both human or veterinary regenerative medicine.

Pentacyclic Triterpenoids Isolated from Celastraceae: A Focus in the 13C-NMR Data.

The Celastraceae family comprises about 96 genera and more than 1.350 species, occurring mainly in tropical and subtropical regions of the world. The species of this family stand out as important plant sources of triterpenes, both in terms of abundance and structural diversity. Triterpenoids found in Celastraceae species display mainly lupane, ursane, oleanane, and friedelane skeletons, exhibiting a wide range of biological activities such as antiviral, antimicrobial, analgesic, anti-inflammatory, and cytotoxic against various tumor cell lines. This review aimed to document all triterpenes isolated from different botanical parts of species of the Celastraceae family covering 2001 to 2021. Furthermore, a compilation of their 13C-NMR data was carried out to help characterize compounds in future investigations. A total of 504 pentacyclic triterpenes were compiled and distinguished as 29 aromatic, 50 dimers, 103 friedelanes, 89 lupanes, 102 oleananes, 22 quinonemethides, 88 ursanes and 21 classified as others.

Porcine Primordial Germ Cell-Like Cells Generated from Induced Pluripotent Stem Cells Under Different Culture Conditions.

Culture conditions regulate the process of pluripotency acquisition and self-renewal. This study aimed to analyse the influence of the in vitro environment on the induction of porcine induced pluripotent stem cell (piPSCs) differentiation into primordial germ cell-like cells (pPGCLCs). piPSC culture with different supplementation strategies (LIF, bFGF, or LIF plus bFGF) promoted heterogeneous phenotypic profiles. Continuous bFGF supplementation during piPSCs culture was beneficial to support a pluripotent state and the differentiation of piPSCs into pPGCLCs. The pPGCLCs were positive for the gene and protein expression of pluripotent and germinative markers. This study can provide a suitable in vitro model for use in translational studies and to help answer numerous remaining questions about germ cells.

Depression and suicide risk during the Covid-19 pandemic at a Brazilian public health psychosocial addiction care center: a preliminary report.

OBJECTIVE: To evaluate the impact of the Covid-19 pandemic on depressive symptoms and suicide risk among patients receiving treatment at a Public Health Psychosocial Addiction Care Center (CAPS AD III) in Porto Alegre, Brazil. METHODS: Questions from the Coronavirus Health Impact Survey (CRISIS) translated into Brazilian Portuguese were used to evaluate 70 patients' perceptions of and behaviors during the Covid-19 pandemic. Validated Brazilian versions of the Patient Health Questionnaire (PHQ-9) and the General Anxiety Disorder-7 (GAD-7) were used to evaluate the severity of depressive symptoms, suicide risk, and anxiety symptoms. A multiple logistic regression model was used to evaluate predictors of suicide risk in the sample. RESULTS: Around 70% of patients reported moderate depressive symptoms and 30% reported severe depressive symptoms, 17% of patients reported having thoughts of suicide or death on more than half of days and 10% reported having them daily. The logistic regression model identified history of alcohol use as the main predictor of suicide risk in (OR 13.0, p = 0.03). CONCLUSIONS: Individuals with a history of alcohol consumption had significantly higher suicide risk scores at a psychosocial public health care center in Brazil during the Covid-19 pandemic. This result may be important for devising better strategies and interventions to support this specific population profile.

Depression and suicide risk during the Covid-19 pandemic at a Brazilian public health psychosocial addiction care center: a preliminary report

Abstract Objective To evaluate the impact of the Covid-19 pandemic on depressive symptoms and suicide risk among patients receiving treatment at a Public Health Psychosocial Addiction Care Center (CAPS AD III) in Porto Alegre, Brazil. Methods Questions from the Coronavirus Health Impact Survey (CRISIS) translated into Brazilian Portuguese were used to evaluate 70 patients' perceptions of and behaviors during the Covid-19 pandemic. Validated Brazilian versions of the Patient Health Questionnaire (PHQ-9) and the General Anxiety Disorder-7 (GAD-7) were used to evaluate the severity of depressive symptoms, suicide risk, and anxiety symptoms. A multiple logistic regression model was used to evaluate predictors of suicide risk in the sample. Results Around 70% of patients reported moderate depressive symptoms and 30% reported severe depressive symptoms, 17% of patients reported having thoughts of suicide or death on more than half of days and 10% reported having them daily. The logistic regression model identified history of alcohol use as the main predictor of suicide risk in (OR 13.0, p = 0.03). Conclusions Individuals with a history of alcohol consumption had significantly higher suicide risk scores at a psychosocial public health care center in Brazil during the Covid-19 pandemic. This result may be important for devising better strategies and interventions to support this specific population profile.

Cattle In Vitro Induced Pluripotent Stem Cells Generated and Maintained in 5 or 20% Oxygen and Different Supplementation.

The event of cellular reprogramming into pluripotency is influenced by several factors, such as in vitro culture conditions (e.g., culture medium and oxygen concentration). Herein, bovine iPSCs (biPSCs) were generated in different levels of oxygen tension (5% or 20% of oxygen) and supplementation (bFGF or bFGF + LIF + 2i-bFL2i) to evaluate the efficiency of pluripotency induction and maintenance in vitro. Initial reprogramming was observed in all groups and bFL2i supplementation initially resulted in a superior number of colonies. However, bFL2i supplementation in low oxygen led to a loss of self-renewal and pluripotency maintenance. All clonal lines were positive for alkaline phosphatase; they expressed endogenous pluripotency-related genes SOX2, OCT4 and STELLA. However, expression was decreased throughout the passages without the influence of oxygen tension. GLUT1 and GLUT3 were upregulated by low oxygen. The biPSCs were immunofluorescence-positive stained for OCT4 and SOX2 and they formed embryoid bodies which differentiated in ectoderm and mesoderm (all groups), as well as endoderm (one line from bFL2i in high oxygen). Our study is the first to compare high and low oxygen environments during and after induced reprogramming in cattle. In our conditions, a low oxygen environment did not favor the pluripotency maintenance of biPSCs.

Altrenogest during early pregnancy modulates uterine glandular epithelium and endometrial growth factor expression at the time implantation in pigs.

This study evaluated the effects of supplying altrenogest from day 6-12 of pregnancy on the endometrial glandular epithelium, corpora lutea (CL) morphology, and endometrial and CL gene expression. A total of 12 crossbred females (Landrace × Large White) were used. The females were assigned to 4 treatments according to a random design with a 2 × 2 factorial arrangement, with two categories (sow or gilt) and two treatments (non-treated and treated with altrenogest). On day 6 of pregnancy, animals were allocated to one of the following groups: non-treated (NT, n = 6; 3 sows and 3 gilts), and (T, n = 6; 3 sows and 3 gilts) treated daily with 20 mg of altrenogest, from day 6-12 of pregnancy. All animals were euthanized on day 13 of pregnancy. All CLs were individually weighed, and their volume were determined. The endometrial glandular density (GD), mean glandular area (MGA), and vascular density (VD) were determined by histomorphometric and immunohistochemical analyses. Endometrium samples were collected and analyzed by qRT-PCR to evaluate the abundance of transcripts for VEGF and IGF-I. Females in the T group had higher MGA (P < 0.05) compared to the NT group. There was no effect of treatment on GD or VD for both experimental groups. Sows in the T group had augmented expression of IGF-I (P < 0.05). Progestagen had no detrimental effect on CL morphology. In conclusion, altrenogest improves the uterine environment during the peri-implantation period in pigs without compromising corpora lutea development.

Differentiation of Porcine Induced Pluripotent Stem Cells (piPSCs) into Neural Progenitor Cells (NPCs).

iPSC-derived neurons are attractive in vitro models to study neurogenesis and early phenotypic changes in mental illness, mainly when most animal models used in pre-clinical research, such as rodents, are not able to meet the criteria to translate the findings to the clinic. Non-human primates, canines, and porcine are considered more adequate models for biomedical research and drug development purposes, mainly due to their physiological, genetic, and anatomical similarities to humans. The swine model has gained particular interest in translational neuroscience, enabling safety and allotransplantation testing. Herein the generation of porcine iPSCs is described along with its further differentiation into neural progenitor cells (NPCs). The generated cells expressed NPC markers Nestin and GFAP, confirmed by RT-qPCR, and were positive for Nestin, b-Tubulin III, and Vimentin by immunofluorescence. These results show the evidence for the generation of NPC-like cells after in vitro induction with chemical inhibitors from a large animal model, an interesting and adequate model for regenerative and translational medicine research.

Generation of neural progenitor cells from porcine-induced pluripotent stem cells.

In this study, porcine embryonic fibroblasts (pEFs) were reprogrammed into porcine-induced pluripotent stem cells (piPSCs) using either human or mouse specific sequences for the OCT4, SOX2, c-Myc, and KLF4 transcription factors. In total, three pEFs lines were reprogrammed, cultured for at least 15 passages, and characterized regarding their pluripotency status (alkaline phosphatase expression, embryoid body formation, expression of exogenous and endogenous genes, and immunofluorescence). Two piPSC lines were further differentiated, using chemical inhibitors, into putative neural progenitor-like (NPC-like) cells with subsequent analyses of their morphology and expression of neural markers such as NESTIN and GFAP as well as immunofluorescent labeling of NESTIN, ß-TUBULIN III, and VIMENTIN. NPC-like cells were positive for all the neural markers tested. These results evidence of the generation of porcine NPC-like cells after in vitro induction with chemical inhibitors, representing an adequate model for future regenerative and translational medicine research.

Effect of the roasting levels of Coffea arabica L. extracts on their potential antioxidant capacity and antiproliferative activity in human prostate cancer cells.

Coffee, besides being one of the most consumed stimulating beverages in the world, has important bioactive activities, which have been attracting increasing attention from researchers. However, the standard process of roasting causes changes in its chemical composition. In the present study, extracts obtained from green and roasted beans (light, medium and dark) of Coffea arabica Linnaeus were submitted to high-power ultrasonic extraction and atomization by spray drying. Colorimetric analysis was used to classify the roasting levels of the dried extract samples. The effects of the roasting process on the bioactivity of the dried extracts were verified through the following assays: caffeine, chlorogenic acid and caffeic acid, by HPLC-PDA; total phenolics by Folin-Ciocalteu; antioxidant activity by DPPH, FRAP, ABTS and ORAC; antiproliferative activity, using the MTT assay; and cell cycle and apoptosis by flow cytometry in metastatic prostate cancer cell lines from bone (PC-3) and brain (DU-145). The results showed that the lowest levels of caffeine, chlorogenic and caffeic acids were observed in dark roasted coffee. In comparison to medium and dark extracts in PC-3 cells, the green and light coffee extracts had higher antioxidant activities and promoted cytotoxicity followed by cell cycle arrest in phase S and apoptosis induction. Thus, the roasting level of the coffee extracts may be related to the potential chemoprotective effects of Coffea arabica L. in prostate cancer cells.