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Rosa davurica is widely used to treat various kinds of diseases because of its high antioxidant, antiviral and anti-inflammatory activities. This use of plant-based materials as medicine is called phytomedicine and has been widely practiced since time immemorial. However, the pharmacological mechanism of R. davurica in skin photoaging is not yet fully understood. Therefore, this study was carried out to evaluate the recovery effects of R. davurica leaf extracts (RDE) in UVB-irradiated human skin keratinocytes (HaCaTs) and investigate whether RDE is a potential therapeutic agent against skin photoaging. The expression of aging-related markers including mitogen-activated protein kinases/activator protein 1 (MAPK/AP-1), nuclear factor-κB (NF-κB), and nuclear factor E2-related factor 2/heme oxygenase-1 (Nrf2/HO-1) was evaluated using Western blot analysis. The reactive oxygen species (ROS) was also used by FACS in HaCaTs. Findings indicated that RDE is efficient in scavenging free radicals and dose-dependently reducing ROS generation. Furthermore, RDE notably decreased UVB-induced matrix metalloproteinase-1 (MMP-1) expression through inhibition of MAPK/AP-1 and NF-κB signaling pathways as well as induced blocking of extracellular matrix (ECM) degradation in UVB-irradiated HaCaTs. In addition, RDE improved Nrf2/HO-1 signaling that increases oxidative defense capacity and enhances transforming growth factor-beta (TGF-β) signaling activation to promote procollagen type I synthesis, relieving UVB-induced skin cell damage. In conclusion, the protective effects of RDE on skin cellular components suggest that it has a high biological potential for skin protection from UVB-induced skin photoaging and is a good candidate for drug and cosmetic application. Graphical abstract

Objectives: To provide empirical evidence that can be applied in medical settings, this study aimed to examine the effects of AAC display types on message production ability in patients with cognitive-communication disorders who are hospitalized and the correlation with the patients’ reading abilities.Methods: Twenty patients with cerebral vascular accidents who were diagnosed with cognitive-communication disorders participated in this study. Message production abilities were examined by measuring accuracy scores and response times under three AAC display conditions: (1) text-based visual scene display (VSD), (2) mixed type (text and graphic symbol-based) of VSD, and (3) graphic symbol-based GRID.Results: The graphic symbol-based GRID showed significantly high accuracy scores and short response time compared to the text-based VSD. There was no significant difference between the graphic symbol-based GRID and the mixed type of VSD in terms of accuracy scores and response time. In addition, significant correlations between the VSD type of display and the reading task scores were found.Conclusion: This study showed that the VSD types of AAC display do not enhance the communication efficacy more than the graphic symbol-based GRID in medical settings. It is at odds with a previous study that claims the effectiveness of text-based VSD without considering patients’ reading ability. These results suggest that rather than perceiving VSD itself to be more effective than other display types, it is important to provide individual graphic symbols so that reading impaired patients can understand the meaning of each message.

Cytokine imbalance is one of the causes of inflammation. Inflammation has yet to be adequately treated without side effects. Therefore, we tried to develop a peptide drug with minimal side effects. Peptide drugs have the advantage of being bio-friendly and bio-specific. In a previous study, three peptides with anti-inflammatory activity were derived based on a truncated IK (tIK) protein, which was a fragment of the IK protein with anti-inflammatory effects. The objective of this study was to optimize the process of expressing, isolating, and purifying the three peptides using bacterial strains and describe the process. Circular dichroism and solution state nuclear magnetic resonance spectroscopy were performed on the final purified high-purity peptide and its secondary structure was also identified.

We assessed sex differences in amyloid- and tau-PET retention in 119 amyloid positive patients with mild cognitive impairment or Alzheimer’s disease (AD) dementia. Patients underwent 3T-MRI, (11)C-PIB amyloid-PET and (18)F-Flortaucipir tau-PET. Linear ordinary least squares regression models tested sex differences in Flortaucipir-PET SUVR in a summary temporal region of interest as well as global PIB-PET. No sex differences were observed in demographics, Clinical Dementia Rating Sum of Boxes (CDR-SoB), Mini-Mental State Exam (MMSE), raw episodic memory scores, or cortical thickness. Females had higher global PIB SUVR (η(p)(2)=.043, p=.025) and temporal Flortaucipir SUVR (η(p)(2)=.070, p=.004), adjusting for age and CDR-SoB. Sex differences in temporal Flortaucipir-PET remained significant when controlling additionally for PIB SUVR and APOE4 status (η(p)(2)=.055, p=.013), or when using partial volume-corrected data. No sex differences were present in areas of known Flortaucipir off-target binding. Overall, females demonstrated greater AD regional tau-PET burden than males despite clinical comparability. Further characterization of sex differences will provide insight into AD pathogenesis and support development of personalized therapeutic strategies.

Development of colloidal quantum dot (CQD) inks enables single-step spin-coating of compact CQD films of appropriate thickness, enabling the promising performance of CQD photovoltaics (CQDPVs). Today's highest-performing CQD inks rely on volatile n-butylamine (BTA), but it is incompatible with scalable deposition methods since a rapid solvent evaporation results in irregular film thickness with an uneven surface. Here, we present a hybrid solvent system, consisting of BTA and N,N-dimethylformamide, which has a favorable acidity for colloidal stability as well as an appropriate vapor pressure, enabling a stable CQD ink that can be used to fabricate homogeneous, large-area CQD films via spray-coating. CQDPVs fabricated with the CQD ink exhibit suppressed charge recombination as well as fast charge extraction compared with conventional CQD ink-based PVs, achieving an improved power conversion efficiency (PCE) of 12.22% in spin-coated devices and the highest ever reported PCE of 8.84% among spray-coated CQDPVs.

Hyperthermia is used to combat and reduce the effects of tumors. This study relates to Co1−xMnxFe2O4 magnetic nanoparticles and their potential in hyperthermia treatment applications. Co1−xMnxFe2O4 nanoparticles were prepared using the high-temperature thermal decomposition method, and the cubic spinel structure with the Fd-3m space group was confirmed through X-ray diffraction analysis. The self-heating temperature was measured using a magneTherm device, and the Mossbauer spectrum covers six lines of sites A and B. Consequently, the composition, particle size, and frequency conditions of magnetic nanoparticles capable of generating self-heating temperatures near the cancer cell death temperature of 42–43 °C were established.

A significant increase in genome instability is associated with the conformational shift of a guanine-run-containing DNA strand into the four-stranded G-quadruplex (G4) DNA. The mechanism underlying the recombination and genome rearrangements following the formation of G4 DNA in vivo has been difficult to elucidate but has become better clarified by the identification and functional characterization of several key G4 DNA-binding proteins. Mammalian nucleolin (NCL) is a highly specific G4 DNA-binding protein with a well-defined role in the transcriptional regulation of genes with associated G4 DNA-forming sequence motifs at their promoters. The consequence of the in vivo interaction between G4 DNA and nucleolin in respect to the genome instability has not been previously investigated. We show here that the yeast nucleolin Nsr1 is enriched at a G4 DNA-forming sequence in vivo and is a major factor in inducing the genome instability associated with the cotranscriptionally formed G4 DNA in the yeast genome. We also show that Nsr1 results in impeding replication past such a G4 DNA-forming sequence. The G4-associated genome instability and the G4 DNA-binding in vivo require the arginine-glycine-glycine (RGG) repeats located at the C-terminus of the Nsr1 protein. Nsr1 with the deletion of RGG domain supports normal cell growth and is sufficient for its pre-rRNA processing function. However, the truncation of the RGG domain of Nsr1 significantly weakens its interaction with G4 DNA in vivo and restores unhindered replication, overall resulting in a sharp reduction in the genome instability associated with a guanine-rich G4 DNA-forming sequence. Our data suggest that the interaction between Nsr1 with the intact RGG repeats and G4 DNA impairs genome stability by precluding the access of G4-resolving proteins and impeding replication.

Faithful degradation of mRNAs is a critical step in gene expression, and eukaryotes share a major conserved mRNA decay pathway. In this major pathway, the two rate-determining steps in mRNA degradation are the initial gradual removal of the poly(A) tail, followed by removal of the cap structure. Removal of the cap structure is carried out by the decapping enzyme, containing the Dcp2 catalytic subunit. Although the mechanism and regulation of mRNA decay is well understood, the consequences of defects in mRNA degradation are less clear. Dcp2 has been reported as either essential or nonessential. Here, we clarify that Dcp2 is not absolutely required for spore germination and extremely slow growth, but in practical terms it is impossible to continuously culture dcp2∆ under laboratory conditions without suppressors arising. We show that null mutations in at least three different genes are each sufficient to restore growth to a dcp2∆, of which kap123∆ and tl(gag)g∆ appear the most specific. We show that kap123∆ and tl(gag)g∆ suppress dcp2 by mechanisms that are different from each other and from previously isolated dcp2 suppressors. The suppression mechanism for tL(GAG)G is determined by the unique GAG anticodon of this tRNA, and thus likely by translation of some CUC or CUU codons. Unlike previously reported suppressors of decapping defects, these suppressors do not detectably restore decapping or mRNA decay to normal rates, but instead allow survival while only modestly affecting RNA homeostasis. These results provide important new insight into the importance of decapping, resolve previously conflicting publications about the essentiality of DCP2, provide the first phenotype for a tl(gag)g mutant, and show that multiple distinct mechanisms can bypass Dcp2 requirement.

Introduction/PurposeSystemic lupus erythematosus (SLE) is a chronic auto-immune disease with a broad spectrum of clinical presentations, including heterogeneous and uncommon neuropsychiatric (NP) syndromes. Accurate diagnosis of neuropsychiatric SLE (NPSLE) is challenging due to lack of clinically useful biomarkers. Despite structural brain abnormalities on MRI in NPSLE being a common finding, a robust link between structural abnormalities and NPSLE has not been established, thus their contribution to the distinction between NPSLE patients and patients in which the NP symptoms are not primarily attributed to SLE is limited. Self-supervised contrastive learning algorithms do not require labels, and have been shown to be useful in classification tasks in rare diseases with limited number of datasets. The aim of our study was to apply self-supervised contrastive learning on T1-weighted images acquired from a well-defined cohort of SLE patients to distinguish between SLE patients with NP symptoms due to the disease (NPSLE) or and SLE patients with similar symptoms due to other causes (non-NPSLE).Subjects and Methods163 patients were included. We used 3T MRI T1-weighted images registered to the MNI152 template. The training set comprised 68 non-NPSLE and 34 NPSLE patients. During the training procedure, we applied random geometric transformations (cropping, left-right flipping and rotations) between iterations to enrich our data sets. Our ML pipeline consisted of convolutional base encoder and linear projector. To test the classification task, the projector was removed and one linear layer was measured. We trained the encoder and projector with the Normalized Temperature-scaled Cross Entropy Loss (NT-xent) loss function. We performed a Monte Carlo validation that consisted of 6 repeated random sub-samplings each using a random selection of a small group of samples from each group.ResultsIn the 6 trials described above, between 79% and 83% of the patients were correctly classified as NPSLE or non-NPSLE. For a qualitative evaluation of spatial distribution of the common features found in the NPSLE population, Gradient-weighted Class Activation Maps (Grad-CAM) were examined voxel-wise. Thresholded Grad-CAM maps show areas of common features identified for the NPSLE cohort, with no such communality found for the non-NPSLE group.Discussion/conclusionThe self-supervised contrastive learning model was effective in capturing diagnostic brain MRI features from a limited but well-defined cohort of SLE patients with NP symptoms. The interpretation of the Grad-CAM results is not straightforward, but points to involvement of the lateral and third ventricles, periventricular white matter and basal cisterns. We believe that the common features found in the NPSLE population in this study indicate a combination of tissue loss, local atrophy and to some extent that of periventricular white matter lesions, which are commonly found in NPSLE patients and appear hypointense on T1-weighted images.

Long-term exposure of the skin to solar radiation causes chronic inflammation and oxidative stress, which accelerates collagen degradation. This contributes to the formation of wrinkles and dark spots, skin fragility, and even skin cancer. In this study, Anemopsis californica (AC), a herb from North America that is well known for treating microorganism infection and promoting wound healing, was investigated for its photoprotective effects. The biological effects of AC were studied on two in vitro models, namely, lipopolysaccharide (LPS)-induced macrophages and ultraviolet B (UVB)-irradiated dermal fibroblasts, to characterize its underlying molecular mechanisms. The results showed that AC decreased the mRNA levels of inflammatory mediators in sensitized macrophages, including cytokines, inducible nitric oxide synthase (iNOS), and cyclooxygenase (COX-2). Moreover, AC alleviated UVB-induced photoaging in dermal fibroblasts by restoring procollagen synthesis. This resulted from the regulation of excessive reactive oxygen species (ROS) by AC, which was mediated by the activation of the antioxidative system nuclear factor erythroid 2-related factor 2 (NRF2). AC also alleviated oxidative stress and inflammatory responses by inhibiting the phosphorylation of mitogen-activated protein kinase (MAPK) and interfering with the nuclear translocation of the immune regulator nuclear factor of activated T-cells 1 (NFATc1). In conclusion, the protective effects of AC on skin cellular components suggested that it has the potential for use in the development of drugs and cosmetics that protect the skin from UVB-induced chronic inflammation and aging.

BackgroundMyasthenia gravis (MG) is an autoimmune, neuromuscular condition and patients with MG are vulnerable due to immunosuppressant use and disease manifestations of dyspnea and dysphagia during the coronavirus disease 2019 (COVID-19) pandemic.MethodsWe conducted a retrospective cohort study using the Optum® de-identified COVID-19 Electronic Health Record (EHR) dataset. Primary outcomes, such as hospitalization, ventilator use, intensive care unit (ICU) admission, and death in COVID-19 patients with MG, were compared with those of COVID-19 patients without MG: the subgroups of non-MG included those with rheumatoid arthritis (RA), systemic lupus (SLE), and multiple sclerosis (MS). We further analyzed factors affecting mortality, such as age, race/ethnicity, comorbidities, and MG treatments.ResultsAmong 421,086 individuals with COVID-19, there were 377 patients with MG, 7,362 patients with RA, 1,323 patients with SLE, 1,518 patients with MS, and 410,506 patients without MG. Patients with MG were older and had more comorbidities compared with non-MG patients and had the highest rates of hospitalization (38.5%), ICU admission (12.7%), ventilator use (3.7%), and mortality (10.6%) compared with all other groups. After adjusting for risk factors, patients with MG had increased risks for hospitalization and ICU compared with patients with non-MG and with RA but had risks similar to patients with SLE and with MS. The adjusted risk for ventilator use was similar across all groups, but the risk for mortality in patients with MG was lower compared with the SLE and MS groups. Among patients with MG, age over 75 years and dysphagia were predictors for increased COVID-19 mortality, but the recent MG treatment was not associated with COVID-19 mortality.ConclusionsCOVID-19 patients with MG are more likely to be admitted to the hospital and require ICU care. Older age and patients with dysphagia had an increased risk of mortality.

In this study, we propose dynamic model update methods for the adaptive classification model of text streams in a distributed learning environment. In particular, we present two model update strategies: (1) the entire model update and (2) the partial model update. The former aims to maximize the model accuracy by periodically rebuilding the model based on the accumulated datasets including recent datasets. Its learning time incrementally increases as the datasets increase, but we alleviate the learning overhead by the distributed learning of the model. The latter fine-tunes the model only with a limited number of recent datasets, noting that the data streams are dependent on a recent event. Therefore, it accelerates the learning speed while maintaining a certain level of accuracy. To verify the proposed update strategies, we extensively apply them to not only fully trainable language models based on CNN, RNN, and Bi-LSTM, but also a pre-trained embedding model based on BERT. Through extensive experiments using two real tweet streaming datasets, we show that the entire model update improves the classification accuracy of the pre-trained offline model; the partial model update also improves it, which shows comparable accuracy with the entire model update, while significantly increasing the learning speed. We also validate the scalability of the proposed distributed learning architecture by showing that the model learning and inference time decrease as the number of worker nodes increases.

Introduction: Cognitive impairment after concussion has been widely reported, but there is no reliable imaging biomarker that predicts the severity of cognitive decline post-concussion. This study tests the hypothesis that patients with a history of concussion and persistent cognitive impairment have fractional anisotropy (FA) and mean diffusivity (MD) values from diffusion tensor imaging (DTI) that are specifically associated with poor performance on the Montreal Cognitive Assessment (MoCA).Methods: Fifty-three subjects (19 females) with concussions and persistent cognitive symptoms had MR imaging and the MoCA. Imaging was analyzed by atlas-based, whole-brain DTI segmentation and FLAIR lesion segmentation. Then, we conducted a random forest-based recursive feature elimination (RFE) with 10-fold cross-validation on the entire dataset, and with partial correlation adjustment for age and lesion load.Results: RFE showed that 11 DTI variables were found to be important predictors of MoCA scores. Partial correlation analyses, corrected for age and lesion load, showed significant correlations between MoCA scores and right fronto-temporal regions: inferior temporal gyrus MD (r = −0.62, p = 0.00001), middle temporal gyrus MD (r = −0.54, p = 0.0001), angular gyrus MD (r = −0.48, p = 0.0008), and inferior frontal gyrus FA (r = 0.44, p = 0.002).Discussion: This is the first study to demonstrate a correlation between MoCA scores and DTI variables in patients with a history of concussion and persistent cognitive impairment. This kind of research will significantly increase our understanding of why certain persons have persistent cognitive changes after concussion which, in turn, may allow us to predict persistent impairment after concussion and suggest new interventions.

Myrciaria dubia (HBK) McVaugh (camu-camu) belongs to the family Myrtaceae. Although camu-camu has received a great deal of attention for its potential pharmacological activities, there is little information on the anti-oxidative stress and anti-inflammatory effects of camu-camu fruit in skin diseases. In the present study, we investigated the preventative effect of 70% ethanol camu-camu fruit extract against high glucose-induced human keratinocytes. High glucose-induced overproduction of reactive oxygen species (ROS) was inhibited by camu-camu fruit treatment. In response to ROS reduction, camu-camu fruit modulated the mitogen-activated protein kinases (MAPK)/activator protein-1 (AP-1), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), and nuclear factor of activated T cells (NFAT) signaling pathways related to inflammation by downregulating the expression of proinflammatory cytokines and chemokines. Furthermore, camu-camu fruit treatment activated the expression of nuclear factor E2-related factor 2 (Nrf2) and subsequently increased the NAD(P)H:quinone oxidoreductase1 (NQO1) expression to protect keratinocytes against high-glucose-induced oxidative stress. These results indicate that camu-camu fruit is a promising material for preventing oxidative stress and skin inflammation induced by high glucose level.

Na-ion solid-state electrolytes (Na-SSE) exhibit high potential for electrical energy storage owing to their high energy densities and low manufacturing cost. However, their mechanical properties critical to maintain structural stability at the interface are still insufficiently understood. In this study, a machine learning based regression model was developed for predicting the mechanical properties of Na-SSEs. As a training set, 12,361 materials were obtained from a well-known materials database (Materials Project) and were represented with their respective chemical and structural descriptors. The developed surrogate model exhibited a remarkable accuracy (R2 score) of 0.72 and 0.87, with a mean absolute error of 11.8 GPa and 15.3 GPa for the shear and bulk modulus, respectively. This model was then applied to predict the mechanical properties of 2,432 Na-SSEs, the properties of which have been validated with first principles calculations. Finally, the optimization process was performed to develop an ideal materials screening platform by adding the new minimized dataset, wherein the prediction uncertainty is reduced. We believe that the platform proposed in this study can accelerate the search for Na-SSEs with ideal mechanical properties at minimum cost., Comment: Submitted and Under Review

Many eukaryotes use RNA processing, including alternative splicing, to express multiple gene products from the same gene. The budding yeast Saccharomyces cerevisiae has been successfully used to study the mechanism of splicing and the splicing machinery, but alternative splicing in yeast is relatively rare and has not been extensively studied. Alternative splicing of SKI7/HBS1 is widely conserved, but yeast and a few other eukaryotes have replaced this one alternatively spliced gene with a pair of duplicated, unspliced genes as part of a whole genome doubling (WGD). We show that other examples of alternative splicing known to have functional consequences are widely conserved within Saccharomycotina. A common mechanism by which alternative splicing has disappeared is by replacement of an alternatively spliced gene with duplicate unspliced genes. This loss of alternative splicing does not always take place soon after duplication, but can take place after sufficient time has elapsed for speciation. Saccharomycetaceae that diverged before WGD use alternative splicing more frequently than S. cerevisiae, suggesting that WGD is a major reason for infrequent alternative splicing in yeast. We anticipate that WGDs in other lineages may have had the same effect. Having observed that two functionally distinct splice-isoforms are often replaced by duplicated genes allowed us to reverse the reasoning. We thereby identify several splice isoforms that are likely to produce two functionally distinct proteins because we find them replaced by duplicated genes in related species. We also identify some alternative splicing events that are not conserved in closely related species and unlikely to produce functionally distinct proteins.

Efficient charge collection in photovoltaics is a key issue toward their high performance. Despite the promising performance of colloidal quantum dot (CQD)-based photovoltaics (CQDPVs), they suffer significant dissipation of photocurrent due to imperfect surface passivation of the CQD hole transport layer (HTL) by a single 1,2-ethaneditihol (EDT) ligand. To address the critical drawback of existing CQDPVs, we offer a hybrid passivation strategy, including both EDT and thiocyanate (SCN). The hybrid passivation leads to seamless surface passivation of CQDs, remarkably suppressing charge recombination. This strategy also augments the p-doping density of the CQD, resulting in a pronounced energy level bending at the active layer/HTL interface and facilitating efficient charge separation. Moreover, enhanced electronic coupling across the CQDs (originating from reduced inter-dot spacing) promotes rapid charge extraction. Consequently, the flawless charge collection by a hybrid-passivated HTL successfully retrieves the photocurrent, achieving an enhanced CQDPV power conversion efficiency of 12.70% compared with 11.49% for the control device.

Faithful degradation of mRNAs is a critical step in gene expression, and eukaryotes share a major conserved mRNA decay pathway. In this major pathway, the two rate determining steps in mRNA degradation are the initial gradual removal of the poly(A) tail, followed by removal of the cap structure. Removal of the cap structure is carried out by the decapping enzyme, containing the Dcp2 catalytic subunit. While the mechanism and regulation of mRNA decay is well-understood, the consequences of defects in mRNA degradation are less clear. Dcp2 has been reported as either essential or nonessential. Here we clarify that Dcp2 is essential for continuous growth and use experimental evolution to identify suppressors of this essentiality. We show that null mutations in at least three different are each sufficient to restore viability to adcp2Δ, of whichkap123Δ andtl(gag)gΔ appear the most specific. Unlike previously reported suppressors of decapping defects, these suppressor do not restore decapping or mRNA decay to normal rates, but instead allow survival while only modestly affecting transcriptome homeostasis. These effects are not limited to mRNAs, but extend to ncRNAs including snoRNAs and XUTs. These results provide important new insight into the importance of decapping and resolves previously conflicting publications about the essentiality ofDCP2.