Evaluation of choroid vascular layer thickness in wet age-related macular degeneration using artificial intelligence.

PURPOSE: To facilitate the assessment of choroid vascular layer thickness in patients with wet age-related macular degeneration (AMD) using artificial intelligence (AI). METHODS: We included 194 patients with wet AMD and 225 healthy participants. Choroid images were obtained using swept-source optical coherence tomography. The average Sattler layer-choriocapillaris complex thickness (SLCCT), Haller layer thickness (HLT), and choroidal thickness (CT) were auto-measured at 7 regions centered around the foveola using AI and subsequently compared between the 2 groups. RESULTS: The SLCCT was lower in the AMD group than in the control group (P<0.05). The HLT was significantly higher in the AMD group than in the control group at the Tparafovea and T-perifovea in the total population (P<0.05) and in the ≤70-year subgroup (P<0.05). The CT was higher in the AMD group than in the control group, particularly at the N-perifovea, T-perifovea, and T-parafovea in the ≤70-year subgroup; Interestingly, it was lower in the AMD group than in the control group at the Nparafovea, N-fovea, foveola, and T-fovea in the >70-year subgroup (P<0.05). CONCLUSION: This novel AI-based auto-measurement was more accurate, efficient, and detailed than manual measurements. SLCCT thinning was observed in wet AMD; however, CT changes depended on the interaction between HLT compensatory thickening and SLCCT thinning.

Identification and classification of the genomes of novel microviruses in poultry slaughterhouse.

Microviridae is a family of phages with circular ssDNA genomes and they are widely found in various environments and organisms. In this study, virome techniques were employed to explore potential members of Microviridae in a poultry slaughterhouse, leading to the identification of 98 novel and complete microvirus genomes. Using a similarity clustering network classification approach, these viruses were found to belong to at least 6 new subfamilies within Microviridae and 3 higher-level taxonomic units. Genome size, GC content and genome structure of these new taxa showed evident regularities, validating the rationality of our classification method. Our method can divide microviruses into about 45 additional detailed clusters, which may serve as a new standard for classifying Microviridae members. Furthermore, by addressing the scarcity of host information for microviruses, the current study significantly broadened their host range and discovered over 20 possible new hosts, including important pathogenic bacteria such as Helicobacter pylori and Vibrio cholerae, as well as different taxa demonstrated different host specificities. The findings of this study effectively expand the diversity of the Microviridae family, providing new insights for their classification and identification. Additionally, it offers a novel perspective for monitoring and controlling pathogenic microorganisms in poultry slaughterhouse environments.

Comparison of Changes in Retinal Vascular Parameters and Density in Patients with Moyamoya Disease: A Retrospective Study.

INTRODUCTION: This study aimed to compare retinal vascular parameters and density in patients with moyamoya disease using the optical coherence tomography angiography. METHODS: This clinical trial totally enrolls 78 eyes from 39 participants, and all these patients with moyamoya disease (N = 13) are set as experimental group and participants with health who matched with age and gender are considered as the control group (N = 26). Then all these participants receive optical coherence tomography angiography detection. Participants' general data are collected and analyzed. Skeleton density (SD) value, vessel density (VD) value, fractal dimension (FD) value, vessel diameter index (VDI) value, foveal avascular zone (FAZ) value are analyzed. RESULTS: A total of 39 participants are included in this study. The SD value in the experimental group was significantly lower than that in control group (0.175 [0.166, 0.181] vs. 0.184 [0.175, 0.188], p = 0.017). Similarly, the VD value in the experimental group was significantly lower than that in the control group (0.333 [0.320, 0.350] vs. 0.354 [0.337, 0.364], p = 0.024). Additionally, the FD value in the experimental group was significantly lower than that in the control group (2.088 [2.083, 2.094] vs. 2.096 [2.090, 2.101], p = 0.022). As for the VDI and FAZ, VDI and FAZ values in the experimental group were lower than those in the control group, there was no significant difference in VDI and FAZ values between the two groups. CONCLUSIONS: Our study, using non-invasive and rapid OCTA imaging, confirmed decreased retinal vascular parameters and density in patients with moyamoya disease.

Unveiling CRESS DNA Virus Diversity in Oysters by Virome.

Oysters that filter feed can accumulate numerous pathogens, including viruses, which can serve as a valuable viral repository. As oyster farming becomes more prevalent, concerns are mounting about diseases that can harm both cultivated and wild oysters. Unfortunately, there is a lack of research on the viruses and other factors that can cause illness in shellfish. This means that it is harder to find ways to prevent these diseases and protect the oysters. This is part of a previously started project, the Dataset of Oyster Virome, in which we further study 30 almost complete genomes of oyster-associated CRESS DNA viruses. The replication-associated proteins and capsid proteins found in CRESS DNA viruses display varying evolutionary rates and frequently undergo recombination. Additionally, some CRESS DNA viruses have the capability for cross-species transmission. A plethora of unclassified CRESS DNA viruses are detectable in transcriptome libraries, exhibiting higher levels of transcriptional activity than those found in metagenome libraries. The study significantly enhances our understanding of the diversity of oyster-associated CRESS DNA viruses, emphasizing the widespread presence of CRESS DNA viruses in the natural environment and the substantial portion of CRESS DNA viruses that remain unidentified. This study's findings provide a basis for further research on the biological and ecological roles of viruses in oysters and their environment.

Synthesis of tetraphenylethylene-based small molecular sensor for the selective "turn-on" detection of pyrophosphoric acid in the aqueous solution.

Pyrophosphoric acid (PPi) is a crucial indicator for monitoring adenosine triphosphate hydrolysis processes, and abnormal PPi levels in the human body seriously threaten human health. Thus the efficient detection of the concentration of PPi in the aqueous solution is important and urgent. This paper described the successful synthesis of a tetraphenylethylene (TPE) derivative, named as TPE-4B, which contained four chelate pyridinium groups exhibiting aggregation-induced emission characteristics. TPE-4B was explicitly developed for the selective and sensitive fluorescence detection of PPi in aqueous solutions, showing a fluorescence "turn-on" response, and the detection limit was 65 nM. The four chelate pyridinium moieties of TPE-4B exhibited robust electrostatic interactions and binding capacity towards PPi, leading to the formation of aggregations, which was confirmed by zeta potential, dynamic light scattering, and scanning electron microscopy. Compared with free TPE-4B in the aqueous solution, the zeta potential of aggregations decreased from 20.7 to 4.2 mV, the average diameter increased from 155 to 403 nm, and the morphology transformed from porous nanostructures into a block-like format. Leveraging these properties, TPE-4B is a promising candidate for a "turn-on" fluorescence sensor designed to detect PPi in the aqueous solution.

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation.

BACKGROUND: The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impairment (CI) recognition. METHODS: We included 908 participants from a community-based cohort followed for over 15 years (the prospective KaiLuan Study) who underwent brain magnetic resonance imaging (MRI) and fundus photography between 2021 and 2022. The cohort consisted of both cognitively healthy individuals (N = 417) and those with cognitive impairment (N = 491). We employed the NFN+ deep learning framework for retinal vessel segmentation and measurement. Associations between Retinal microvascular parameters (RMPs: central retinal arteriolar / venular equivalents, arteriole to venular ratio, fractal dimension) and CI were assessed by Pearson correlation. P < 0.05 was considered statistically significant. The correlation between the CI and RMPs were explored, then the correlation coefficients between CI and RMPs were analyzed. Random Forest nonlinear classification model was used to predict whether one having cognitive decline or not. The assessment criterion was the AUC value derived from the working characteristic curve. RESULTS: The fractal dimension (FD) and global vein width were significantly correlated with the CI (P < 0.05). Age (0.193), BMI (0.154), global vein width (0.106), retinal vessel FD (0.099), and CRAE (0.098) were the variables in this model that were ranked in order of feature importance. The AUC values of the model were 0.799. CONCLUSIONS: Establishment of a predictive model based on the extraction of vascular features from fundus images has a high recognizability and predictive power for cognitive function and can be used as a screening method for CI.

The association of global vessel width with cognitive decline and cerebral small vessel disease burden in the KaiLuan study.

Background: As the retinal microvasculature shares similarities with the cerebral microvasculature, numerous studies have shown that retinal vascular is associated with cognitive decline. In addition, several population-based studies have confirmed the association between retinal vascular and cerebral small vessel disease (CSVD) burden. However, the association of retinal vascular with CSVD burden as well as cognitive function has not been explored simultaneously. This study investigated the relations of retinal microvascular parameters (RMPs) with CSVD burden and cognitive function. Methods: We conducted a cross-sectional study of participants in the KaiLuan study. Data were collected from subjects aged ≥18 years old who could complete retinal photography and brain magnetic resonance imaging (MRI) between December 2020 to October 2021 in the Kailuan community of Tangshan. RMPs were evaluated using a deep learning system. The cognitive function was measured using the Montreal Cognitive Assessment (MoCA). We conducted logistic regression models, and mediation analysis to evaluate the associations of RMPs with CSVD burden and cognitive decline. Results: Of the 905 subjects (mean age: 55.42±12.02 years, 54.5% female), 488 (53.9%) were classified with cognitive decline. The fractal dimension (FD) [odds ratio (OR), 0.098, 95% confidence interval (CI): 0.015-0.639, P=0.015] and global vein width (OR: 1.010, 95% CI: 1.005-1.015, P<0.001) were independent risk factors for cognitive decline after adjustment for potential confounding factors. The global artery width was significantly associated with severe CSVD burden (OR: 0.985, 95% CI: 0.974-0.997, P=0.013). The global vein width was sightly associated with severe CSVD burden (OR: 1.005, 95% CI: 1.000-1.010, P=0.050) after adjusting for potential confounders. The multivariable-adjusted odds ratios (95% CI) in highest tertile versus lowest tertile of global vein width were 1.290 (0.901-1.847) for cognitive decline and 1.546 (1.004-2.290) for severe CSVD burden, respectively. Moreover, CSVD burden played a partial mediating role in the association between global vein width and cognitive function (mediating effect 6.59%). Conclusions: RMPs are associated with cognitive decline and the development of CSVD. A proportion of the association between global vein width and cognitive decline may be attributed to the presence of CSVD burden.

Machine learning and deep learning enabled age estimation on medial clavicle CT images.

The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine learning (ML) and deep learning (DL) models for BAE based on medial clavicle CT images and evaluate the performance on normal and variant clavicles. This study retrospectively collected 1049 patients (mean± SD: 22.50±4.34 years) and split them into normal training and test sets, and variant training and test sets. An additional 53 variant clavicles were incorporated into the variant test set. The development stages of normal MCE were used to build a linear model and support vector machine (SVM) for BAE. The CT slices of MCE were automatically segmented and used to train DL models for automated BAE. Comparisons were performed by linear versus ML versus DL, and normal versus variant clavicles. Mean absolute error (MAE) and classification accuracy was the primary parameter of comparison. For BAE, the SVM had the best MAE of 1.73 years, followed by the commonly-used CNNs (1.77-1.93 years), the linear model (1.94 years), and the hybrid neural network CoAt Net (2.01 years). In DL models, SE Net 18 was the best-performing DL model with similar results to SVM in the normal test set and achieved an MAE of 2.08 years in the external variant test. For age classification, all the models exhibit superior performance in the classification of 18-, 20-, 21-, and 22-year thresholds with limited value in the 16-year threshold. Both ML and DL models produce desirable performance in BAE based on medial clavicle CT.

Automated bone age assessment from knee joint by integrating deep learning and MRI-based radiomics.

Bone age assessment (BAA) is a crucial task in clinical, forensic, and athletic fields. Since traditional age estimation methods are suffered from potential radiation damage, this study aimed to develop and evaluate a deep learning radiomics method based on multiparametric knee MRI for noninvasive and automatic BAA. This retrospective study enrolled 598 patients (age range,10.00-29.99 years) who underwent MR examinations of the knee joint (T1/T2*/PD-weighted imaging). Three-dimensional convolutional neural networks (3D CNNs) were trained to extract and fuse multimodal and multiscale MRI radiomic features for age estimation and compared to traditional machine learning models based on hand-crafted features. The age estimation error was greater in individuals aged 25-30 years; thus, this method may not be suitable for individuals over 25 years old. In the test set aged 10-25 years (n = 95), the 3D CNN (a fusion of T1WI, T2*WI, and PDWI) demonstrated the lowest mean absolute error of 1.32 ± 1.01 years, which is higher than that of other MRI modalities and the hand-crafted models. In the classification for 12-, 14-, 16-, and 18- year thresholds, accuracies and the areas under the ROC curves were all over 0.91 and 0.96, which is similar to the manual methods. Visualization of important features showed that 3D CNN estimated age by focusing on the epiphyseal plates. The deep learning radiomics method enables non-invasive and automated BAA from multimodal knee MR images. The use of 3D CNN and MRI-based radiomics has the potential to assist radiologists or medicolegists in age estimation.

Analysis of macula structural changes in Moyamoya disease using AI-assisted OCT.

OBJECTIVE: To investigate macula structure thickness and volume changes in patients with moyamoya disease (MMD). METHOD: In this cross-sectional study, we used artificial intelligence (AI) -assisted optical coherence tomography (OCT) to analyze the thickness and volume of macula in Moyamoya patients. ETDRS zoning divides the macula into nine different regions. In 15 patients with radial scanning OCT, the average thickness and volume of retina, RNFL, GCL, and choroid in these regions were measured. In 30 patients with radial or horizontal scanning OCT, based on the anatomical structure, the macula is divided into seven segments. Mean Sattler layer-choriocapillaris complex thickness (SLCCT), Haller layer thickness, and total choroidal thickness were measured for each segment using AI-assisted OCT. RESULTS: We recruited 30 patients (59 eyes) with MMD. In the 15 patients (29 eyes) who underwent radial scanning OCT, no significant change in retina, RNFL, GCL, and choroidal thickness was identified between the two groups (p > 0.05). There was no significant change in retina, RNFL, or choroidal volume between the two groups in different ETDRS macula regions (p > 0.05). The GCL volume in the macula's inner ring nasal portion (IN) was significantly lower. SLCCTs were considerably reduced in six macula regions in moyamoya groups (p < 0.05). There was no statistically significant change in Haller layer thickness. Only the nasal perifovea (PE_N) exhibited a significant variation in choroidal thickness. The Moyamoya group showed reduced choroidal thickness in PE_N segment. CONCLUSION: In patients with MMD, there is thinning of the Sattler layer-choriocapillaris complex in the choroid.

Post-cationic modification of a porphyrin-based conjugated microporous polymer for enhanced removal performance of bisphenol A.

A porphyrin-based conjugated microporous polymer photocatalyst named LDPO-2 was synthesized by a post-modification approach, which improved its hydrophilicity and visible light absorption ability. LDPO-2 achieved >99.5% removal efficiency for bisphenol A (BPA, 10 ppm) within 12 min of exposure to visible light, and the photocatalytic mechanism and potential degradation pathways were well investigated. LDPO-2 also exhibited impressive removal efficiency against BPA analogues, proving its practical applications in real-water treatment scenarios.

Small-Angle X-ray Scattering for PEGylated Liposomal Doxorubicin Drugs: An Analytical Model Comparison Study.

Liposomal delivery systems are recognized as efficient and safe platforms for chemotherapeutic agents, with doxorubicin-loaded liposomes being the most representative nanopharmaceuticals. Characterizing the structure of liposomal nanomedicines in high spatial and temporal resolution is critical to analyze and evaluate their stability and efficacy. Small-angle X-ray scattering (SAXS) is a powerful tool increasingly used to investigate liposomal delivery systems. In this study, we chose a Doxil-like PEGylated liposomal doxorubicin (PLD) as an example and characterized the liposomal drug structure using synchrotron SAXS. Classical analytical models, including the spherical-shell or flat-slab geometries with Gaussian or uniform electron density profiles, were used to model the internal structure of the liposomal membrane. A cylinder model was applied to fit the scattering from the drug crystal loaded in the liposomes. The high-resolution structures of the original drug, Caelyx, and a similar research drug prepared in our laboratory were characterized using these analytical models. The structural parameters of PLDs, including the thickness of the liposomal membrane and morphology of the drug crystal, were further compared. The results demonstrated that both spherical-shell and flat-slab geometries with Gaussian electron density distribution were suitable to elucidate the structural features of the liposomal membrane under a certain range of scattering vectors, while models with uniform electron density distribution exhibited poor fitting performance. This study highlights the technical features of SAXS, which provides structural information at the nanoscale for liposomal drugs. The demonstrated methods are reliable and easy-to-use for the structural analysis of liposomal drugs, which are helpful for a broader application of SAXS in the production and regulation of nanopharmaceuticals.

Enantiopure Dinaphtho[2,3-b:2,3-f]thieno[3,2-b]thiophenes: Reaching High Magnetoresistance Effect in OFETs.

Chiral molecules are known to behave as spin filters due to the chiral induced spin selectivity (CISS) effect. Chirality can be implemented in molecular semiconductors in order to study the role of the CISS effect in charge transport and to find new materials for spintronic applications. In this study, the design and synthesis of a new class of enantiopure chiral organic semiconductors based on the well-known dinaphtho[2,3-b:2,3-f]thieno[3,2-b]thiophene (DNTT) core functionalized with chiral alkyl side chains is presented. When introduced in an organic field-effect transistor (OFET) with magnetic contacts, the two enantiomers, (R)-DNTT and (S)-DNTT, show an opposite behavior with respect to the relative direction of the magnetization of the contacts, oriented by an external magnetic field. Each enantiomer displays an unexpectedly high magnetoresistance over one preferred orientation of the spin current injected from the magnetic contacts. The result is the first reported OFET in which the current can be switched on and off upon inversion of the direction of the applied external magnetic field. This work contributes to the general understanding of the CISS effect and opens new avenues for the introduction of organic materials in spintronic devices.

The novel amylase function of the carboxyl terminal domain of Amy63.

α-amylase plays a crucial role in regulating metabolism and health by hydrolyzing of starch and glycogen. Despite comprehensive studies of this classic enzyme spanning over a century, the function of its carboxyl terminal domain (CTD) with a conserved eight ß-strands is still not fully understood. Amy63, identified from a marine bacterium, was reported as a novel multifunctional enzyme with amylase, agarase and carrageenase activities. In this study, the crystal structure of Amy63 was determined at 1.8 Å resolution, revealing high conservation with some other amylases. Interestingly, the independent amylase activity of the carboxyl terminal domain of Amy63 (Amy63_CTD) was newly discovered by the plate-based assay and mass spectrometry. To date, the Amy63_CTD alone could be regarded as the smallest amylase subunit. Moreover, the significant amylase activity of Amy63_CTD was measured over a wide range of temperature and pH, with optimal activity at 60 °C and pH 7.5. The Small-angle X-ray scattering (SAXS) data showed that the high-order oligomeric assembly gradually formed with increasing concentration of Amy63_CTD, implying the novel catalytic mechanism as revealed by the assembly structure. Therefore, the discovery of the novel independent amylase activity of Amy63_CTD suggests a possible missing step or a new perspective in the complex catalytic process of Amy63 and other related α-amylases. This work may shed light on the design of nanozymes to process marine polysaccharides efficiently.

Deep learning enables automatic adult age estimation based on CT reconstruction images of the costal cartilage.

OBJECTIVE: Adult age estimation (AAE) is a challenging task. Deep learning (DL) could be a supportive tool. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. METHODS: Chest CT were reconstructed using volume rendering (VR) and maximum intensity projection (MIP) separately. Retrospective data of 2500 patients aged 20.00-69.99 years were obtained. The cohort was split into training (80%) and validation (20%) sets. Additional independent data from 200 patients were used as the test set and external validation set. Different modality DL models were developed accordingly. Comparisons were hierarchically performed by VR versus MIP, single-modality versus multi-modality, and DL versus manual method. Mean absolute error (MAE) was the primary parameter of comparison. RESULTS: A total of 2700 patients (mean age = 45.24 years ± 14.03 [SD]) were evaluated. Of single-modality models, MAEs yielded by VR were lower than MIP. Multi-modality models generally yielded lower MAEs than the optimal single-modality model. The best-performing multi-modality model obtained the lowest MAEs of 3.78 in males and 3.40 in females. On the test set, DL achieved MAEs of 3.78 in males and 3.92 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. For the external validation, MAEs were 6.05 in males and 6.68 in females for DL, and 6.93 and 8.28 for the manual method. CONCLUSIONS: DL demonstrated better performance than the manual method in AAE based on CT reconstruction of the costal cartilage. CLINICAL RELEVANCE STATEMENT: Aging leads to diseases, functional performance deterioration, and both physical and physiological damage over time. Accurate AAE may aid in diagnosing the personalization of aging processes. KEY POINTS: • VR-based DL models outperformed MIP-based models with lower MAEs and higher R2 values. • All multi-modality DL models showed better performance than single-modality models in adult age estimation. • DL models achieved a better performance than expert assessments.

A discussion of RNA virus taxonomy based on the 2020 International Committee on Taxonomy of Viruses report.

RNA viruses have a higher mutation rate than DNA viruses; however, RNA viruses are insufficiently studied outside disease settings. The International Committee on Taxonomy of Viruses (ICTV) is an organization set up by virologists to standardize virus classification. To better understand ICTV taxonomy and the characteristics and rules of different RNA virus families, we analyzed the 3,529 RNA viruses included in the 2020 ICTV report using five widely used metrics: length, host, GC content, number of predicted ORFs, and sequence similarity. The results show that host type has a significant influence on viral genome length and GC content. The genome lengths of virus members within the same genus are quite similar: 98.28% of the genome length differences within any particular genus are less than 20%. The species within those genera containing segmented viruses also have a similar length and number of segments. The number of predicted ORFs in the RNA viral genomes also shows a strong, statistically significant correlation with genome length. We suggest that due to the high mutation rate of RNA virus genomes, current RNA virus classification should mainly rely on protein similarities rather than nucleic acid similarities.

Metagenomic next-generation sequencing-guided antimicrobial treatment versus conventional antimicrobial treatment in early severe community-acquired pneumonia among immunocompromised patients (MATESHIP): A study protocol.

Background: Severe community-acquired pneumonia (SCAP) is the main cause of mortality in immunocompromised patients. Compared with conventional microbiological tests (CMT), metagenomic next-generation sequencing (mNGS) can quickly and simultaneously detect a wide array of bacteria, viruses, and fungi in an unbiased manner. It is increasingly used for severe respiratory infectious diseases, especially for immunocompromised patients. However, the effects of mNGS-based antimicrobial treatment procedures on clinical outcomes in immunocompromised patients with SCAP have not been evaluated. Methods/Design: The MATESHIP study is a prospective, multicenter, parallel-group, open-label, randomized controlled trial from 20 ICUs in university hospitals and academic teaching hospitals across Shandong Province, China. We will enroll 342 immunocompromised patients with early onset SCAP who are admitted to an intensive care unit (ICU). Participants will be randomly allocated to an mNGS-guided treatment group or a conventional treatment group (guided by CMT), according to centrally computer-based block randomization stratified by participating centers. Participants will undergo CMT tests using appropriate lower respiratory tract (LRT) and other necessary specimens, with or without mNGS tests using LRT specimens. The primary outcomes will be: (1) The relative change in Sequential Organ Failure Assessment (SOFA) score from randomization to day 5, day 7, day 10, or the day of ICU discharge/death; and (2) the consumption of antimicrobial agents during ICU stay (expressed as defined daily doses). The secondary outcome measures will be: days from randomization to initiation of definitive antimicrobial treatment; overall antimicrobial agent use and cost; total cost of hospitalization; length of ICU stay; 28- and 90-day mortality; and clinical cure rate. This study hypothesizes that mNGS-guided treatment will decrease the degree of organ dysfunction/failure, the consumption of antimicrobial agents, and mortality, while the cure rate will be increased, and the time to initiation of appropriate therapy will be advanced. Discussion: The MATESHIP study will evaluate for the first time whether mNGS-guided antimicrobial therapy improves the outcomes of SCAP in an immunocompromised population, and provide high-level evidence on the application of mNGS in the management of this population. Clinical Trial Registration: [ClinicalTrials.gov], identifier [NCT05290454].

Scalable Manufacturing of Solid Polymer Electrolytes with Superior Room-Temperature Ionic Conductivity.

A scalable manufacturing protocol is developed to prepare polymer-based solvent-free all-solid flexible energy storage devices based on a two-roll mill and adapted rubber mixing technology. The as-prepared solid polymer electrolytes (SPEs) consisting of commercial poly(methyl methacrylate)-grafted natural rubber (MG30) and lithium bis(trifluoromethanesulfonyl)imide achieve a superior ionic conductivity of 2.7 × 10-3 S cm-1 at 30 °C. The superior ionic conductivity is attributed to the formation of an ionic cluster network in the composite as proved by small-angle X-ray scattering and infrared spectroscopy measurements. Moreover, the as-prepared SPEs show good mechanical stability over a broad temperature range, that is , a storage modulus above 1 × 104 Pa from 30 to 120 °C as indicated by the rheology data. Furthermore, the SPEs were assembled with the carbon black-filled MG30 (i.e., MG30C) electrode into a flexible supercapacitor cell, which had a wide voltage window of 3.5 V, good energy density of 28.4 µW h·cm-2 at 160 °C, and good temperature tolerance up to 160 °C. This scaling-up manufacture strategy shows tremendous potential to the advancing of SPEs in applications of flexible energy storage device.

The Second Class of Tetrahydrofolate (THF-II) Riboswitches Recognizes the Tetrahydrofolic Acid Ligand via Local Conformation Changes.

Riboswitches are regulatory noncoding RNAs found in bacteria, fungi and plants, that modulate gene expressions through structural changes in response to ligand binding. Understanding how ligands interact with riboswitches in solution can shed light on the molecular mechanisms of this ancient regulators. Previous studies showed that riboswitches undergo global conformation changes in response to ligand binding to relay information. Here, we report conformation switching models of the recently discovered tetrahydrofolic acid-responsive second class of tetrahydrofolate (THF-II) riboswitches in response to ligand binding. Using a combination of selective 2'-hydroxyl acylation, analyzed by primer extension (SHAPE) assay, 3D modeling and small-angle X-ray scattering (SAXS), we found that the ligand specifically recognizes and reshapes the THF-II riboswitch loop regions, but does not affect the stability of the P3 helix. Our results show that the THF-II riboswitch undergoes only local conformation changes in response to ligand binding, rearranging the Loop1-P3-Loop2 region and rotating Loop1 from a ~120° angle to a ~75° angle. This distinct conformation changes suggest a unique regulatory mechanism of the THF-II riboswitch, previously unseen in other riboswitches. Our findings may contribute to the fields of RNA sensors and drug design.