System-based integrated metabolomics and microRNA analysis identifies potential molecular alterations in human X-linked cerebral adrenoleukodystrophy brain.

X-linked adrenoleukodystrophy is a severe demyelinating neurodegenerative disease mainly affecting males. The severe cerebral adrenoleukodystrophy (cALD) phenotype has a poor prognosis and underlying mechanism of onset and progression of neuropathology remains poorly understood. In this study we aim to integrate metabolomic and microRNA (miRNA) datasets to identify variances associated with cALD. Postmortem brain tissue samples from five healthy controls (CTL) and five cALD patients were utilized in this study. White matter from ALD patients was obtained from normal-appearing areas, away from lesions (NLA) and from the periphery of lesions- plaque shadow (PLS). Metabolomics was performed by gas chromatography coupled with time-of-flight mass spectrometry and miRNA expression analysis was performed by next generation sequencing (RNAseq). Principal component analysis revealed that among the three sample groups (CTL, NLA and PLS) there were 19 miRNA, including several novel miRNA, of which 17 were increased with disease severity and 2 were decreased. Untargeted metabolomics revealed 13 metabolites with disease severity-related patterns with 7 increased and 6 decreased with disease severity. Ingenuity pathway analysis of differentially altered metabolites and miRNA comparing CTL with NLA and NLA with PLS, identified several hubs of metabolite and signaling molecules and their upstream regulation by miRNA. The transomic approach to map the crosstalk between miRNA and metabolomics suggests involvement of specific molecular and metabolic pathways in cALD and offers opportunity to understand the complex underlying mechanism of disease severity in cALD.

Blood-based untargeted metabolomics in relapsing-remitting multiple sclerosis revealed the testable therapeutic target.

Metabolic aberrations impact the pathogenesis of multiple sclerosis (MS) and possibly can provide clues for new treatment strategies. Using untargeted metabolomics, we measured serum metabolites from 35 patients with relapsing-remitting multiple sclerosis (RRMS) and 14 healthy age-matched controls. Of 632 known metabolites detected, 60 were significantly altered in RRMS. Bioinformatics analysis identified an altered metabotype in patients with RRMS, represented by four changed metabolic pathways of glycerophospholipid, citrate cycle, sphingolipid, and pyruvate metabolism. Interestingly, the common upstream metabolic pathway feeding these four pathways is the glycolysis pathway. Real-time bioenergetic analysis of the patient-derived peripheral blood mononuclear cells showed enhanced glycolysis, supporting the altered metabolic state of immune cells. Experimental autoimmune encephalomyelitis mice treated with the glycolytic inhibitor 2-deoxy-D-glucose ameliorated the disease progression and inhibited the disease pathology significantly by promoting the antiinflammatory phenotype of monocytes/macrophage in the central nervous system. Our study provided a proof of principle for how a blood-based metabolomic approach using patient samples could lead to the identification of a therapeutic target for developing potential therapy.

Nanopatterning Induced Si Doping in Amorphous Ga2O3 for Enhanced Electrical Properties and Ultra-Fast Photodetection.

Ga2O3 has emerged as a promising material for the wide-bandgap industry aiming at devices beyond the limits of conventional silicon. Amorphous Ga2O3 is widely being used for flexible electronics, but suffers from very high resistivity. Conventional methods of doping like ion implantation require high temperatures post-processing, thereby limiting their use. Herein, an unconventional method of doping Ga2O3 films with Si, thereby enhancing its electrical properties, is reported. Ion-beam sputtering (500 eV Ar+) is utilized to nanopattern SiO2-coated Si substrate leaving the topmost part rich in elemental Si. This helps in enhancing the carrier conduction by increasing n-type doping of the subsequently coated 5 nm amorphous Ga2O3 films, corroborated by room-temperature resistivity measurement and valence band spectra, respectively, while the nanopatterns formed help in better light management. Finally, as proof of concept, metal-semiconductor-metal (MSM) photoconductor devices fabricated on doped, rippled films show superior properties with responsivity increasing from 6 to 433 mA W-1 while having fast detection speeds of 861 µs/710 µs (rise/fall time) as opposed to non-rippled devices (377 ms/392 ms). The results demonstrate a facile, cost-effective, and large-area method to dope amorphous Ga2O3 films in a bottom-up approach which may be employed for increasing the electrical conductivity of other amorphous oxide semiconductors as well.

Deep Earth Chronicles: High-Pressure Investigation of Phenakite Mineral Be2SiO4.

Beryllium silicate, recognized as the mineral phenakite (Be2SiO4), is a prevalent constituent in Earth's upper mantle. This study employs density-functional theory (DFT) calculations to explore the structural, mechanical, dynamical, thermodynamic, and electronic characteristics of this compound under both ambient and high-pressure conditions. Under ideal conditions, the DFT calculations align closely with experimental findings, confirming the mechanical and dynamical stability of the crystalline structure. Phenakite is characterized as an indirect band gap insulator, possessing an estimated band gap of 7.83 eV. Remarkably, oxygen states make a substantial contribution to both the upper limit of the valence band and the lower limit of the conduction band. We delved into the thermodynamic properties of the compound, including coefficients of thermal expansion, free energy, entropy, heat capacity, and the Gruneisen parameter across different temperatures. Our findings suggest that Be2SiO4 displays an isotropic behavior based on estimated anisotropic factors. Interestingly, our investigation revealed that, under pressure, the compression of phenakite is not significantly affected by bond angle bending.

A hybrid effective medium description for nanoporous gold films and thickness-mediated control of optical absorption.

With the increasing demand for sensing platforms operating across UV, visible, and near-infrared wavelengths, nanoporous gold has emerged as an ideal substrate for rapid, quantitative detection of analytes with excellent specificity and high sensitivity. This study investigates thickness-mediated compositional changes and their impact on scattering characteristics of thin nanoporous gold films fabricated using selective chemical etching. Specifically, we observe thickness-induced morphological and structural changes across different fabricated samples from 25-100nm in thickness. Upon their optical characterization across UV-VIS-NIR spectral regime, we notice that the constitutional differences among samples manifest distinctively \& deterministically in their total optical scattering response. In order to gain insights into these observed scattering responses and to fathom the subtle connections between structural properties of NPG films and their optical response, a hybrid theoretical model comprising Maxwell-Garnett \& Bruggeman effective medium approximations has been adopted. Our approach not only allows to appropriately account for the inhomogeneous nature of these films, but also corroborates well with the atomic force microscopy characterizations of the fabricated samples. Furthermore, tracing such a theoretical model is important as it helps in systematically ascertaining additional loss terms emerging in the complex dielectric function of films due to their nanoscale porosity \& roughness, permitting a good reproduction of measured optical spectra. We believe, our approach will not only facilitate accurate regulation of losses in NPG thin films but will also aid in deriving customized optical performance from them, thereby advancing their potential applications in sensing and beyond.

Monocular Painless Vision Loss in the Emergency Department: Multipurpose Utility of Point-of-Care Ultrasound.

BACKGROUND: Eye-related symptoms are a common presentation in the emergency department (ED). The cases range from simple viral conjunctivitis to trauma-related eye injuries. One pathological condition that could lead to vision loss is retinal artery occlusion (RAO). Evaluating a patient with an eye symptom requires thorough eye examination and advanced imaging in certain instances. Consultation with an ophthalmologist is also necessary for cases that require treatment recommendations and further testing. In the ED, point-of-care ultrasound (POCUS) is a commonly used diagnostic tool that can be used for ocular examination. CASE REPORT: We reported a case of a 60-year-old man who presented with painless partial right-eye vision loss. POCUS showed decreased flow in the right central retinal artery with an area of the pale retina seen on the image from the retinal camera, suggesting a possible branch RAO. Further examination with POCUS showed plaque formation at the carotid bifurcation, a potential cause of the patient's symptoms. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Emergency physicians and other providers should be encouraged to use POCUS to diagnose eye symptoms accurately and promptly. Abnormal findings will prompt immediate specialty consult and early appropriate management. Our case and other reported cases highlight POCUS's reliability and rapid diagnostic ability.

Predicting RNA distance-based contact maps by integrated deep learning on physics-inferred secondary structure and evolutionary-derived mutational coupling.

MOTIVATION: Recently, AlphaFold2 achieved high experimental accuracy for the majority of proteins in Critical Assessment of Structure Prediction (CASP 14). This raises the hope that one day, we may achieve the same feat for RNA structure prediction for those structured RNAs, which is as fundamentally and practically important similar to protein structure prediction. One major factor in the recent advancement of protein structure prediction is the highly accurate prediction of distance-based contact maps of proteins. RESULTS: Here, we showed that by integrated deep learning with physics-inferred secondary structures, co-evolutionary information and multiple sequence-alignment sampling, we can achieve RNA contact-map prediction at a level of accuracy similar to that in protein contact-map prediction. More importantly, highly accurate prediction for top L long-range contacts can be assured for those RNAs with a high effective number of homologous sequences (Neff > 50). The initial use of the predicted contact map as distance-based restraints confirmed its usefulness in 3D structure prediction. AVAILABILITY AND IMPLEMENTATION: SPOT-RNA-2D is available as a web server at https://sparks-lab.org/server/spot-rna-2d/ and as a standalone program at https://github.com/jaswindersingh2/SPOT-RNA-2D. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SPOT-Contact-LM: improving single-sequence-based prediction of protein contact map using a transformer language model.

MOTIVATION: Accurate prediction of protein contact-map is essential for accurate protein structure and function prediction. As a result, many methods have been developed for protein contact map prediction. However, most methods rely on protein-sequence-evolutionary information, which may not exist for many proteins due to lack of naturally occurring homologous sequences. Moreover, generating evolutionary profiles is computationally intensive. Here, we developed a contact-map predictor utilizing the output of a pre-trained language model ESM-1b as an input along with a large training set and an ensemble of residual neural networks. RESULTS: We showed that the proposed method makes a significant improvement over a single-sequence-based predictor SSCpred with 15% improvement in the F1-score for the independent CASP14-FM test set. It also outperforms evolutionary-profile-based methods trRosetta and SPOT-Contact with 48.7% and 48.5% respective improvement in the F1-score on the proteins without homologs (Neff = 1) in the independent SPOT-2018 set. The new method provides a much faster and reasonably accurate alternative to evolution-based methods, useful for large-scale prediction. AVAILABILITY AND IMPLEMENTATION: Stand-alone-version of SPOT-Contact-LM is available at https://github.com/jas-preet/SPOT-Contact-Single. Direct prediction can also be made at https://sparks-lab.org/server/spot-contact-single. The datasets used in this research can also be downloaded from the GitHub. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Emergency department burr hole simulation using 3D-printed model.

BACKGROUND: Traumatic epidural hematoma (EDH) with the potential to displace the brain tissue and increase intracranial pressure (ICP), is a life-threatening condition that requires emergent intervention. In rare circumstances, Emergency Physician (EP) may have to do skull trephination to reduce the ICP as a temporary measure. SPECIFIC AIMS: To evaluate emergency medicine (EM) residents' comfort in performing emergency department (ED) burr holes and to assess their difficulties and evaluate comfort level before and after simulated EDH cases. MATERIALS AND METHODS: A 3D-printed skull, electrical and manual drills were used for the simulation. Subjective comfort level pre and post-procedure, as well as objective procedural skills and time to complete the drill, were recorded. RESULTS: Twenty EM residents participated in the simulation study. The median time to perforate through the skull was 4 s for the electric drill and 10 s for the manual drill. A comfort level of 5 and above was reported by 12 participants for the manual drill and by 17 participants for the electric drill. Six participants had mild and 2 participants had moderate observed difficulty in handling the manual and electric drill. Most participants performed both procedures successfully with one attempt only. Three participants have an overall comfort level above 5 before the simulation and 13 participants had overall comfort level above 5 post-simulation. CONCLUSION: The 3D-printed model assisted the ED burr hole simulation and the residents could perform the procedure with minimum difficulties.

High-Precision Trace Hydrogen Sensing by Multipass Raman Scattering.

Despite its growing importance in the energy generation and storage industry, the detection of hydrogen in trace concentrations remains challenging, as established optical absorption methods are ineffective in probing homonuclear diatomics. Besides indirect detection approaches using, e.g., chemically sensitized microdevices, Raman scattering has shown promise as an alternative direct method of unambiguous hydrogen chemical fingerprinting. We investigated the suitability of feedback-assisted multipass spontaneous Raman scattering for this task and examined the precision with which hydrogen can be sensed at concentrations below 2 parts per million. A limit of detection of 60, 30, and 20 parts per billion was obtained at a pressure of 0.2 MPa in a 10-min-long, 120-min-long, and 720-min-long measurement, respectively, with the lowest concentration probed being 75 parts per billion. Various methods of signal extraction were compared, including asymmetric multi-peak fitting, which allowed the resolution of concentration steps of 50 parts per billion, determining the ambient air hydrogen concentration with an uncertainty level of 20 parts per billion.

Physico-chemical and Textural Properties of 3D Printed Plant-based and Hybrid Soft Meat Analogs.

This study investigated the physico-chemical and textural properties of 3D-printed pea protein-only and pea protein-chicken-based hybrid meat analogs. Both pea protein isolate (PPI)-only and hybrid cooked meat analogs had a similar moisture content of approximately 70%, which was similar to that of chicken mince. However, the protein content increased significantly with the amount of chicken in the hybrid paste undergoing 3D printing and cooking. Significant differences were observed in the hardness values of the non-printed cooked pastes and the 3D printed cooked counterparts, suggesting that the 3D printing process reduces the hardness of the samples and is a suitable method to produce a soft meal, and has significant potential in elderly health care. Scanning electron microscopy (SEM) revealed that adding chicken to the plant protein matrix led to better fiber formation. PPI itself was not able to form any fibers merely by 3D printing and cooking in boiling water. Protein-protein interactions were also studied through the protein solubility test, which indicated that hydrogen bonding was the major bonding that contributed to the structure formation in cooked printed meat analogs. In addition, disulfide bonding was correlated with improved fibrous structures, as observed through SEM.

Potato Processing Industry in China: Current Scenario, Future Trends and Global Impact.

Potatoes play an important role in ensuring food security. During the COVID-19 epidemic, consumption of processed potato products decreased, and consumption of fresh potatoes increased. China is the world's largest potato producer with more than 4.81 million hectares of area under potato production and 90.32 million metric tonnes of potatoes produced in 2018. This accounts for 27.36% of the world's planting area and 24.53% of the world's potato production. The proportion of potatoes processed in China was about 12% in 2017, mostly dominated by starch production. However, the recent policy of the Chinese government to popularise potato as a staple food has created new markets for processed potato products other than starch. A very few reports have analysed these future trends of the rapidly growing Chinese potato processing industry and its impact within and outside China. This paper provides an overview of the latest developments with a focus on processed potato products such as potato chips, French fries and dehydrated potatoes, and also, due to the unique Chinese diet culture, it highlights the need for more scientific research dedicated towards the development of novel potato-based healthy foods.

Mechanics of stabilized intercellular bridges.

Numerous engineered and natural systems form through reinforcement and stabilization of a deformed configuration that was generated by a transient force. An important class of such structures arises during gametogenesis, when a dividing cell undergoes incomplete cytokinesis, giving rise to daughter cells that remain connected through a stabilized intercellular bridge (ICB). ICBs can form through arrest of the contractile cytokinetic furrow and its subsequent stabilization. Despite knowledge of the molecular components, the mechanics underlying robust ICB assembly and the interplay between ring contractility and stiffening are poorly understood. Here, we report joint experimental and theoretical work that explores the physics underlying robust ICB assembly. We develop a continuum mechanics model that reveals the minimal requirements for the formation of stable ICBs, and validate the model's equilibrium predictions through a tabletop experimental analog. With insight into the equilibrium states, we turn to the dynamics: we demonstrate that contractility and stiffening are in dynamic competition and that the time intervals of their action must overlap to ensure assembly of ICBs of biologically observed proportions. Our results highlight a mechanism in which deformation and remodeling are tightly coordinated-one that is applicable to several mechanics-based applications and is a common theme in biological systems spanning several length scales.

Beneficial Effects of the Direct AMP-Kinase Activator PXL770 in In Vitro and In Vivo Models of X-Linked Adrenoleukodystrophy.

X-linked adrenoleukodystrophy (ALD) is a severe orphan disease caused by mutations in the peroxisomal ABCD1 transporter gene, leading to toxic accumulation of Very Long-Chain Fatty Acids (VLCFA - in particular C26:0) resulting in inflammation, mitochondrial dysfunction and demyelination. AMP-activated protein kinase (AMPK) is downregulated in ALD, and its activation is implicated as a therapeutic target. PXL770 is the first direct allosteric AMPK activator with established clinical efficacy and tolerability. Methods: We investigated its effects in ALD patient-derived fibroblasts/lymphocytes and Abcd1 KO mouse glial cells. Readouts included VLCFA levels, mitochondrial function and mRNA levels of proinflammatory genes and compensatory transporters (ABCD2-3). After PXL770 treatment in Abcd1 KO mice, we assessed VLCFA levels in tissues, sciatic nerve axonal morphology by electronic microscopy and locomotor function by open-field/balance-beam tests. Results: In patients' cells and Abcd1 KO glial cells, PXL770 substantially decreased C26:0 levels (by ∼90%), improved mitochondrial respiration, reduced expression of multiple inflammatory genes and induced expression of ABCD2-3 In Abcd1 KO mice, PXL770 treatment normalized VLCFA in plasma and significantly reduced elevated levels in brain (-25%) and spinal cord (-32%) versus untreated (P < 0.001). Abnormal sciatic nerve axonal morphology was also improved along with amelioration of locomotor function. Conclusion: Direct AMPK activation exerts beneficial effects on several hallmarks of pathology in multiple ALD models in vitro and in vivo, supporting clinical development of PXL770 for this disease. Further studies would be needed to overcome limitations including small sample size for some parameters, lack of additional in vivo biomarkers and incomplete pharmacokinetic characterization. SIGNIFICANCE STATEMENT: Adrenoleukodystrophy is a rare and debilitating condition with no approved therapies, caused by accumulation of very long-chain fatty acids. AMPK is downregulated in the disease and has been implicated as a potential therapeutic target. PXL770 is a novel clinical stage direct AMPK activator. In these studies, we used PXL770 to achieve preclinical validation of direct AMPK activation for this disease - based on correction of key biochemical and functional readouts in vitro and in vivo, thus supporting clinical development.

SPOT-1D-Single: improving the single-sequence-based prediction of protein secondary structure, backbone angles, solvent accessibility and half-sphere exposures using a large training set and ensembled deep learning.

MOTIVATION: Knowing protein secondary and other one-dimensional structural properties are essential for accurate protein structure and function prediction. As a result, many methods have been developed for predicting these one-dimensional structural properties. However, most methods relied on evolutionary information that may not exist for many proteins due to a lack of sequence homologs. Moreover, it is computationally intensive for obtaining evolutionary information as the library of protein sequences continues to expand exponentially. Here, we developed a new single-sequence method called SPOT-1D-Single based on a large training dataset of 39 120 proteins deposited prior to 2016 and an ensemble of hybrid long-short-term-memory bidirectional neural network and convolutional neural network. RESULTS: We showed that SPOT-1D-Single consistently improves over SPIDER3-Single and ProteinUnet for secondary structure, solvent accessibility, contact number and backbone angles prediction for all seven independent test sets (TEST2018, SPOT-2016, SPOT-2016-HQ, SPOT-2018, SPOT-2018-HQ, CASP12 and CASP13 free-modeling targets). For example, the predicted three-state secondary structure's accuracy ranges from 72.12% to 74.28% by SPOT-1D-Single, compared to 69.1-72.6% by SPIDER3-Single and 70.6-73% by ProteinUnet. SPOT-1D-Single also predicts SS3 and SS8 with 6.24% and 6.98% better accuracy than SPOT-1D on SPOT-2018 proteins with no homologs (Neff = 1), respectively. The new method's improvement over existing techniques is due to a larger training set combined with ensembled learning. AVAILABILITY AND IMPLEMENTATION: Standalone-version of SPOT-1D-Single is available at https://github.com/jas-preet/SPOT-1D-Single. Direct prediction can also be made at https://sparks-lab.org/server/spot-1d-single. The datasets used in this research can also be downloaded from GitHub. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Improved RNA secondary structure and tertiary base-pairing prediction using evolutionary profile, mutational coupling and two-dimensional transfer learning.

MOTIVATION: The recent discovery of numerous non-coding RNAs (long non-coding RNAs, in particular) has transformed our perception about the roles of RNAs in living organisms. Our ability to understand them, however, is hampered by our inability to solve their secondary and tertiary structures in high resolution efficiently by existing experimental techniques. Computational prediction of RNA secondary structure, on the other hand, has received much-needed improvement, recently, through deep learning of a large approximate data, followed by transfer learning with gold-standard base-pairing structures from high-resolution 3-D structures. Here, we expand this single-sequence-based learning to the use of evolutionary profiles and mutational coupling. RESULTS: The new method allows large improvement not only in canonical base-pairs (RNA secondary structures) but more so in base-pairing associated with tertiary interactions such as pseudoknots, non-canonical and lone base-pairs. In particular, it is highly accurate for those RNAs of more than 1000 homologous sequences by achieving >0.8 F1-score (harmonic mean of sensitivity and precision) for 14/16 RNAs tested. The method can also significantly improve base-pairing prediction by incorporating artificial but functional homologous sequences generated from deep mutational scanning without any modification. The fully automatic method (publicly available as server and standalone software) should provide the scientific community a new powerful tool to capture not only the secondary structure but also tertiary base-pairing information for building three-dimensional models. It also highlights the future of accurately solving the base-pairing structure by using a large number of natural and/or artificial homologous sequences. AVAILABILITY AND IMPLEMENTATION: Standalone-version of SPOT-RNA2 is available at https://github.com/jaswindersingh2/SPOT-RNA2. Direct prediction can also be made at https://sparks-lab.org/server/spot-rna2/. The datasets used in this research can also be downloaded from the GITHUB and the webserver mentioned above. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Single-sequence and profile-based prediction of RNA solvent accessibility using dilated convolutional neural network.

MOTIVATION: RNA solvent accessibility, similar to protein solvent accessibility, reflects the structural regions that are accessible to solvents or other functional biomolecules, and plays an important role for structural and functional characterization. Unlike protein solvent accessibility, only a few tools are available for predicting RNA solvent accessibility despite the fact that millions of RNA transcripts have unknown structures and functions. Also, these tools have limited accuracy. Here, we have developed RNAsnap2 that uses a dilated convolutional neural network with a new feature, based on predicted base-pairing probabilities from LinearPartition. RESULTS: Using the same training set from the recent predictor RNAsol, RNAsnap2 provides an 11% improvement in median Pearson Correlation Coefficient (PCC) and 9% improvement in mean absolute errors for the same test set of 45 RNA chains. A larger improvement (22% in median PCC) is observed for 31 newly deposited RNA chains that are non-redundant and independent from the training and the test sets. A single-sequence version of RNAsnap2 (i.e. without using sequence profiles generated from homology search by Infernal) has achieved comparable performance to the profile-based RNAsol. In addition, RNAsnap2 has achieved comparable performance for protein-bound and protein-free RNAs. Both RNAsnap2 and RNAsnap2 (SingleSeq) are expected to be useful for searching structural signatures and locating functional regions of non-coding RNAs. AVAILABILITY AND IMPLEMENTATION: Standalone-versions of RNAsnap2 and RNAsnap2 (SingleSeq) are available at https://github.com/jaswindersingh2/RNAsnap2. Direct prediction can also be made at https://sparks-lab.org/server/rnasnap2. The datasets used in this research can also be downloaded from the GITHUB and the webserver mentioned above. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Therapeutic potential of deuterium-stabilized (R)-pioglitazone-PXL065-for X-linked adrenoleukodystrophy.

X-linked adrenoleukodystrophy (ALD) results from ABCD1 gene mutations which impair Very Long Chain Fatty Acids (VLCFA; C26:0 and C24:0) peroxisomal import and ß-oxidation, leading to accumulation in plasma and tissues. Excess VLCFA drives impaired cellular functions (e.g. disrupted mitochondrial function), inflammation, and neurodegeneration. Major disease phenotypes include: adrenomyeloneuropathy (AMN), progressive spinal cord axonal degeneration, and cerebral ALD (C-ALD), inflammatory white matter demyelination and degeneration. No pharmacological treatment is available to-date for ALD. Pioglitazone, an anti-diabetic thiazolidinedione, exerts potential benefits in ALD models. Its mechanisms are genomic (PPARγ agonism) and nongenomic (mitochondrial pyruvate carrier-MPC, long-chain acyl-CoA synthetase 4-ACSL4, inhibition). However, its use is limited by PPARγ-driven side effects (e.g. weight gain, edema). PXL065 is a clinical-stage deuterium-stabilized (R)-enantiomer of pioglitazone which lacks PPARγ agonism but retains MPC activity. Here, we show that incubation of ALD patient-derived cells (both AMN and C-ALD) and glial cells from Abcd1-null mice with PXL065 resulted in: normalization of elevated VLCFA, improved mitochondrial function, and attenuated indices of inflammation. Compensatory peroxisomal transporter gene expression was also induced. Additionally, chronic treatment of Abcd1-null mice lowered VLCFA in plasma, brain and spinal cord and improved both neural histology (sciatic nerve) and neurobehavioral test performance. Several in vivo effects of PXL065 exceeded those achieved with pioglitazone. PXL065 was confirmed to lack PPARγ agonism but retained ACSL4 activity of pioglitazone. PXL065 has novel actions and mechanisms and exhibits a range of potential benefits in ALD models; further testing of this molecule in ALD patients is warranted.

Stability, optoelectronic and thermal properties of two-dimensional Janusα-Te2S.

Motivated by recent progress in the two-dimensional (2D) materials of group VI elements and their experimental fabrication, we have investigated the stability, optoelectronic and thermal properties of Janusα-Te2S monolayer using first-principles calculations. The phonon dispersion and MD simulations confirm its dynamical and thermal stability. The moderate band gap (∼1.5 eV), ultrahigh carrier mobility (∼103cm2V-1s-1), small exciton binding energy (0.26 eV), broad optical absorption range and charge carrier separation ability due to potential difference (ΔV = 1.07 eV) on two surfaces of Janusα-Te2S monolayer makes it a promising candidate for solar energy conversion. We propose various type-II heterostructures consisting of Janusα-Te2S and other transition metal dichalcogenides for solar cell applications. The calculated power conversion efficiencies of the proposed heterostructures, i.e.α-Te2S/T-PdS2,α-Te2S/BP andα-Te2S/H-MoS2are ∼21%, ∼19% and 18%, respectively. Also, the ultralow value of lattice thermal conductivity (1.16 W m-1K-1) of Janusα-Te2S makes it a promising material for the fabrication of next-generation thermal energy conversion devices.

Soft Tissue Filler Therapy and Informed Consent: A Canadian Review.

Soft Tissue Filler (STF) Therapy for cosmetic facial rejuvenation is associated with known complications. The manifestation of these known complications can lead to patients commencing civil litigation actions or making complaints to provincial regulatory authorities and alleging that the practitioner failed to obtain the patient's informed consent to the therapy. Data provided by the Canadian Medical Protective Association (CMPA) on medical-legal cases arising from the provision of STF therapy between 2005 and 2019 are presented. Select reported case law decisions from Canadian courts and regulatory bodies addressing the concept of informed consent are reviewed. Insights about the risk factors pertaining to the process of obtaining informed consent for STF therapy are presented to increase an understanding of the elements of communication and documentation needed to ensure patients are aware of the consequences of this treatment.