Determinants of care partner burden in atypical Parkinsonian syndromes: A retrospective, multi-center analysis.

Introduction: Progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), and multiple system atrophy (MSA) are rare neurodegenerative diseases associated with rapid decline and require complex symptom management. Caregiving responsibilities significantly increase with progression of these atypical Parkinsonian syndromes, yet care burden in these syndromes has not been researched extensively to date. Methods: The Zarit Burden Interview (ZBI) was used to assess burden in care partners of patients clinically diagnosed with PSP, CBS, or MSA seen in specialty interdisciplinary clinics at two academic movement disorders centers. Univariable and multivariable regression analyses were performed to evaluate cross-sectional demographic and clinical determinants of care partner burden. Results: A total of 139 care partners completed the ZBI (59.0% PSP, 28.1% MSA, 12.9% CBS). Cohorts at both medical centers were similar across all variables. Female gender of both patients and care partners was independently associated with higher ZBI scores. Additionally, MSA-Parkinsonian type was significantly associated with lower total care partner burden compared to PSP and CBS. Conclusion: Several determinants of higher care partner burden in atypical Parkinsonian syndromes were identified, particularly female gender and diagnosis. Healthcare professionals can consider this information when assessing individualized needs of patients and care partners and referring to disease-specific resources. Additionally, this study's methods and results highlight the potential to further explore interdisciplinary care as a means of comprehensive evaluation and support for those with atypical Parkinsonism.

Will AMPK be a potential therapeutic target for hepatocellular carcinoma?

Cancer is the disease that poses the greatest threat to human health today. Among them, hepatocellular carcinoma (HCC) is particularly prominent due to its high recurrence rate and extremely low five-year postoperative survival rate. In addition to surgical treatment, radiotherapy, chemotherapy, and immunotherapy are the main methods for treating HCC. Due to the natural drug resistance of chemoradiotherapy and targeted drugs, satisfactory results have not been achieved in terms of therapeutic efficacy and cost. AMP-Activated Protein Kinase (AMPK) is a serine/threonine protein kinase. It mainly coordinates the metabolism and transformation of energy between cells, which maintaining a balance between energy supply and demand. The processes of cell growth, proliferation, autophagy, and survival all involve various reaction of cells to energy changes. The regulatory role of AMPK in cellular energy metabolism plays an important role in the occurrence, development, treatment, and prognosis of HCC. Here, we reviewed the latest progress on the regulatory role of AMPK in the occurrence and development of HCC. Firstly, the molecular structure and activation mechanism of AMPK were introduced. Secondly, the emerging regulator related to AMPK and tumors were elaborated. Next, the multitasking roles of AMPK in the occurrence and development mechanism of HCC were discussed separately. Finally, the translational implications and the challenges of AMPK-targeted therapies for HCC treatment were elaborated. In summary, these pieces of information suggest that AMPK can serve as a promising specific therapeutic target for the treatment of HCC.

Identification of immune- and oxidative stress-related signature genes as potential targets for mRNA vaccines for pancreatic cancer patients.

Adenocarcinoma of the pancreas (PAAD) is one of the deadliest malignant tumors, and messenger ribonucleic acid vaccines, which constitute the latest generation of vaccine technology, are expected to lead to new ideas for the treatment of pancreatic cancer. The Cancer Genome Atlas-PAAD and Genotype-Tissue Expression data were merged and analyzed. Weighted gene coexpression network analysis was used to identify gene modules associated with tumor mutational burden among the genes related to both immunity and oxidative stress. Differentially expressed immune-related oxidative stress genes were screened via univariate Cox regression analysis, and these genes were analyzed via nonnegative matrix factorization. After immune infiltration analysis, least absolute shrinkage and selection operator regression combined with Cox regression was used to construct the model, and the usefulness of the model was predicted based on the receiver operating characteristic curve and decision curve analysis curves after model construction. Finally, metabolic pathway enrichment was analyzed using gene set enrichment analysis combined with Kyoto Encyclopedia of Genes and Genomes and gene ontology biological process analyses. This model consisting of the ERAP2, mesenchymal-epithelial transition factor (MET), CXCL9, and angiotensinogen (AGT) genes can be used to help predict the prognosis of pancreatic cancer patients more accurately than existing models. ERAP2 is involved in immune activation and is important in cancer immune evasion. MET binds to hepatocyte growth factor, leading to the dimerization and phosphorylation of c-MET. This activates various signaling pathways, including MAPK and PI3K, to regulate the proliferation, invasion, and migration of cancer cells. CXCL9 overexpression is associated with a poor patient prognosis and reduces the number of CD8 + cytotoxic T lymphocytes in the PAAD tumor microenvironment. AGT is cleaved by the renin enzyme to produce angiotensin 1, and AGT-converting enzyme cleaves angiotensin 1 to produce angiotensin 2. Exposure to AGT-converting enzyme inhibitors after pancreatic cancer diagnosis is associated with improved survival. The 4 genes identified in the present study - ERAP2, MET, CXCL9, and AGT - are expected to serve as targets for messenger ribonucleic acid vaccine development and need to be further investigated in depth.

Preparation and characterization of agarose-sodium alginate hydrogel beads for the co-encapsulation of lycopene and resveratrol nanoemulsion.

In the study, lycopene and resveratrol nanoemulsion hydrogel beads were prepared by using agarose­sodium alginate as a carrier and the semi-interpenetrating polymer network technique, characteristics and morphologies were evaluated by scanning electron microscopy, fluorescence microscopy, rheological measurement. The synergistic antioxidant effect of lycopene and resveratrol was confirmed, the best synergistic antioxidant performance is achieved when the ratio of 1:1. To increase the solubility and improve the stability, the lycopene was prepared as solid dispersion added to the nanoemulsion. The encapsulation rate of lycopene and resveratrol reached 93.60 ± 2.94 % and 89.30 ± 1.75 %, respectively, and the cumulative release showed that the addition of agarose slowed down the release rate of the compound, which improves the applicability of lycopene and resveratrol and development of carriers for the delivery of different bioactive ingredients.

Magnetothermal-activated gene editing strategy for enhanced tumor cell apoptosis.

Precise and effective initiation of the apoptotic mechanism in tumor cells is one of the most promising approaches for the treatment of solid tumors. However, current techniques such as high-temperature ablation or gene editing suffer from the risk of damage to adjacent normal tissues. This study proposes a magnetothermal-induced CRISPR-Cas9 gene editing system for the targeted knockout of HSP70 and BCL2 genes, thereby enhancing tumor cell apoptosis. The magnetothermal nanoparticulate platform is composed of superparamagnetic ZnCoFe2O4@ZnMnFe2O4 nanoparticles and the modified polyethyleneimine (PEI) and hyaluronic acid (HA) on the surface, on which plasmid DNA can be effectively loaded. Under the induction of a controllable alternating magnetic field, the mild magnetothermal effect (42℃) not only triggers dual-genome editing to disrupt the apoptosis resistance mechanism of tumor cells but also sensitizes tumor cells to apoptosis through the heat effect itself, achieving a synergistic therapeutic effect. This strategy can precisely regulate the activation of the CRISPR-Cas9 system for tumor cell apoptosis without inducing significant damage to healthy tissues, thus providing a new avenue for cancer treatment.

Synergistic degradation of 2,4-dichlorophenoxyacetic acid in water by interfacial pre-reduction enhanced peroxymonosulfate activation derived from novel zero-valent iron/biochar.

Iron-based biochar exhibits great potential in degrading emerging pollutants and remediation of water environments. In this study, a highly efficient catalytic Fe0/biochar (MZB-800) was synthesized by the co-pyrolysis of poplar sawdust and K2FeO4 at 800 °C. A novel water purification technology of pre-reduction followed by PMS activation for MZB-800 was proposed to degrade the refractory 2,4-dichlorophenoxyacetic acid (2,4-D) pesticide. The corrosive effect of the strong oxidizing potassium salt endowed the MZB-800 surface with more Fe0 and porous structure, achieving greater 2,4-D adsorption binding energy. The removal efficiency of MZB-800 on 2,4-D was greater than that of biochar (BC) and conventional Fe0/biochar (Fe-BC) prepared by FeCl3·6 H2O as the precursor. The proposed novel water purification technology showed the synergistic effect between the interfacial pre-reduction and the PMS activation derived by MZB-800. Regarding 2,4-D degradation and dechlorination performance, the synergistic coefficient between pre-reduction and subsequent PMS activation for MZB-800 were 2 and 1.4 respectively. Based on the normalized kinetic analysis and the Langmuir-Hinshelwood model, we proposed the underlying mechanism of MZB-800 interfacial pre-reduction and subsequent PMS activation for synergistic removal of 2,4-D. The large amount of Fe2+ and hydroxyl density accumulated by the Fe0 and hydroquinone structures on the MZB-800 surface during the pre-reduction stage provided abundant active sites for the subsequent activation of PMS. The improved activation reaction rate generated more reactive oxygen species, further strengthening the removal efficiency of 2,4-D. This work manifested that the novel water purification technology of pre-reduction/PMS activation of iron-based biochar is feasible for removing emerging pollutants in the water environment. ENVIRONMENTAL IMPLICATION: Extensive abuse of 2,4-dichlorophenoxyacetic acid (2,4-D) herbicide with high solubility and refractory degradation has caused environmental pollution and ecological deterioration. This manuscript described a novel water purification technology, centered on high-efficiency Fe0/biochar and utilizing pre-reduction and PMS reactivation strategies to synergistically degrade 2,4-D, which had strong environmental relevance. By elucidating the synergistic removal mechanism, the research provided valuable insights into removing emerging pollutants, thus promoting environmental sustainability and safeguarding ecosystem health. Overall, it is of high importance to provide a feasible and efficient method for removing hazardous 2,4-D from water environments, which contributes to addressing pressing environmental problems.

TP-GCL: graph contrastive learning from the tensor perspective.

Graph Neural Networks (GNNs) have demonstrated significant potential as powerful tools for handling graph data in various fields. However, traditional GNNs often encounter limitations in information capture and generalization when dealing with complex and high-order graph structures. Concurrently, the sparse labeling phenomenon in graph data poses challenges in practical applications. To address these issues, we propose a novel graph contrastive learning method, TP-GCL, based on a tensor perspective. The objective is to overcome the limitations of traditional GNNs in modeling complex structures and addressing the issue of sparse labels. Firstly, we transform ordinary graphs into hypergraphs through clique expansion and employ high-order adjacency tensors to represent hypergraphs, aiming to comprehensively capture their complex structural information. Secondly, we introduce a contrastive learning framework, using the original graph as the anchor, to further explore the differences and similarities between the anchor graph and the tensorized hypergraph. This process effectively extracts crucial structural features from graph data. Experimental results demonstrate that TP-GCL achieves significant performance improvements compared to baseline methods across multiple public datasets, particularly showcasing enhanced generalization capabilities and effectiveness in handling complex graph structures and sparse labeled data.

Digital ray: enhancing cataractous fundus images using style transfer generative adversarial networks to improve retinopathy detection.

BACKGROUND/AIMS: The aim of this study was to develop and evaluate digital ray, based on preoperative and postoperative image pairs using style transfer generative adversarial networks (GANs), to enhance cataractous fundus images for improved retinopathy detection. METHODS: For eligible cataract patients, preoperative and postoperative colour fundus photographs (CFP) and ultra-wide field (UWF) images were captured. Then, both the original CycleGAN and a modified CycleGAN (C2ycleGAN) framework were adopted for image generation and quantitatively compared using Frechet Inception Distance (FID) and Kernel Inception Distance (KID). Additionally, CFP and UWF images from another cataract cohort were used to test model performances. Different panels of ophthalmologists evaluated the quality, authenticity and diagnostic efficacy of the generated images. RESULTS: A total of 959 CFP and 1009 UWF image pairs were included in model development. FID and KID indicated that images generated by C2ycleGAN presented significantly improved quality. Based on ophthalmologists' average ratings, the percentages of inadequate-quality images decreased from 32% to 18.8% for CFP, and from 18.7% to 14.7% for UWF. Only 24.8% and 13.8% of generated CFP and UWF images could be recognised as synthetic. The accuracy of retinopathy detection significantly increased from 78% to 91% for CFP and from 91% to 93% for UWF. For retinopathy subtype diagnosis, the accuracies also increased from 87%-94% to 91%-100% for CFP and from 87%-95% to 93%-97% for UWF. CONCLUSION: Digital ray could generate realistic postoperative CFP and UWF images with enhanced quality and accuracy for overall detection and subtype diagnosis of retinopathies, especially for CFP.\ TRIAL REGISTRATION NUMBER: This study was registered with ClinicalTrials.gov (NCT05491798).

Cell-type and dynamic state govern genetic regulation of gene expression in heterogeneous differentiating cultures.

Identifying the molecular effects of human genetic variation across cellular contexts is crucial for understanding the mechanisms underlying disease-associated loci, yet many cell-types and developmental stages remain underexplored. Here we harnessed the potential of heterogeneous differentiating cultures ( HDCs ), an in vitro system in which pluripotent cells asynchronously differentiate into a broad spectrum of cell-types. We generated HDCs for 53 human donors and collected single-cell RNA-sequencing data from over 900,000 cells. We identified expression quantitative trait loci in 29 cell-types and characterized regulatory dynamics across diverse differentiation trajectories. This revealed novel regulatory variants for genes involved in key developmental and disease-related processes while replicating known effects from primary tissues, and dynamic regulatory effects associated with a range of complex traits.

Evaluation of aroma characteristics of Penaeus vannamei with different drying methods using HS-SPME-GC-MS, MMSE-GC-MS, and sensory evaluation.

The effects of microwave drying (MD), hot air drying (HAD), vacuum hot air drying (VD), and vacuum freeze drying (VFD) on the volatile profiles of Penaeus vannamei were investigated. A total of 89 and 94 volatile compounds were identified by headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and monolithic material sorptive extraction gas chromatography-mass spectrometry (MMSE-GC-MS), respectively. Orthogonal partial least squares-discriminant analysis (OPLS-DA) and variable influence on projection (VIP) models were utilized to select characteristic volatiles and key marker compounds (e.g., octanal, 1-octen-3-ol, 2-methyl-butanal, 2-ethyl-furan, and trimethyl-pyrazine) to discriminate among four drying methods. Based on synthesis of odor descriptions and sensory evaluation, it was found that P. vannamei via MD, HAD, and VD greatly reduced the fishy and generated roasted, fatty, and smoked odors. This study systematically analyzed the aroma characteristics of four traditional dried P. vannamei products, which may provide theoretical guidance for industrial production.

Nanocatalytic Anti-Tumor Immune Regulation.

Immunotherapy has brought a new dawn for human being to defeat cancer. Although existing immunotherapy regimens (CAR-T, etc.) have made breakthroughs in the treatments of hematological cancer and few solid tumors such as melanoma, the therapeutic efficacy on most solid tumors is still far from being satisfactory. In recent years, the researches on tumor immunotherapy based on nanocatalytic materials are under rapid development, and significant progresses have been made. Nanocatalytic medicine has been demonstrated to be capable of overcoming the limitations of current clinicnal treatments by using toxic chemodrugs, and exhibits highly attractive advantages over traditional therapies, such as the enhanced and sustained therapeutic efficacy based on the durable catalytic activity, remarkably reduced harmful side-effects without using traditional toxic chemodrugs, and so on. Most recently, nanocatalytic medicine has been introduced in the immune-regulation for disease treatments, especially, in the immunoactivation for tumor therapies. This article presents the most recent progresses in immune-response activations by nanocatalytic medicine-initiated chemical reactions for tumor immunotherapy, and elucidates the mechanism of nanocatalytic medicines in regulating anti-tumor immunity. By reviewing the current research progress in the emerging field, this review will further highlight the great potential and broad prospects of nanocatalysis-based anti-tumor immune-therapeutics.

Transparent Self-Healing Anti-Freezing Ionogel for Monolayered Triboelectric Nanogenerator and Electromagnetic Energy-Based Touch Panel.

The advent of Internet of Things and artificial intelligence era necessitates the advancement of self-powered electronics. However, prevalent multifunctional electronics still face great challenges in rigid electrodes, stacked layers, and external power sources to restrict the development in flexible electronics. Here, a transparent, self-healing, anti-freezing (TSA) ionogel composed of fluorine-rich ionic liquid and fluorocarbon elastomer, which is engineered for monolayered triboelectric nanogenerators (M-TENG) and electromagnetic energy-based touch panels is developed. Notably, the TSA-ionogel exhibits remarkable features including outstanding transparency (90%), anti-freezing robustness (253 K), impressive stretchability (600%), and repetitive self-healing capacity. The resultant M-TENG achieves a significant output power density (200 mW m-2 ) and sustains operational stability beyond 1 year. Leveraging this remarkable performance, the M-TENG is adeptly harnessed for biomechanical energy harvesting, self-powered control interface, electroluminescent devices, and enabling wireless control over electrical appliances. Furthermore, harnessing Faraday's induction law and exploiting human body's intrinsic antenna properties, the TSA-ionogel seamlessly transforms into an autonomous multifunctional epidermal touch panel. This touch panel offers impeccable input capabilities through word inscription and participation in the Chinese game of Go. Consequently, the TSA-ionogel's innovation holds the potential to reshape the trajectory of next-generation electronics and profoundly revolutionize the paradigm of human-machine interaction.

Identification of a 2-phenylthiazole derivative acetylcholinesterase modulator with in vitro antitumor activity in breast cancer cells.

Acetylcholinesterase (AchE) is a serine hydrolase with classical function to degrade acetylcholine and terminate neurotransmission. While "nonclassical" functions of AchE were involved in cell growth, death, invasion, etc. The expression and activity of AchE is changed in tumors, suggesting AChE inhibitors (AchEIs) may serve as potential antitumor drugs. In this study, the antitumor activity of a series of 2-phenylthiazole derivatives originally designed and synthesized as AchEIs were investigated. One compound named A6, was screened out with superior antitumor efficacy, especially against breast cancer MCF-7 cells. A6 significantly disrupted the amino acid metabolism and inhibited migration of MCF-7. In addition, A6 induced apoptosis of MCF-7 cells. To clarify how A6 affected on MCF-7 cells, RNA-seq analysis was conducted to evaluate the whole genome effect of A6 on gene expression. A total of 153 genes were increased, and the expression of 81 genes was decreased. GO and KEGG enrichment analysis showed A6 treatment mainly disrupted sterol/cholesterol pathway, Ras signaling pathway, VEGF signaling pathway, etc. Moreover, bioinformatic analysis and cell viability test showed A6 plays anticancer role by regulating Best1 and HIST1H2BJ. These results indicate that AchEI A6 could be a potential antitumor agent for breast cancer patients and could help the development of novel therapies.

The role of body mass index on the association between the energy-adjusted dietary inflammatory index and hyperuricemia: a mediation analysis based on NHANES (2007-2016).

BACKGROUND: The Energy-Adjusted Dietary Inflammatory Index (E-DII) is related to both body mass index (BMI) and hyperuricemia. However, the association among BMI, hyperuricemia and DII is yet to be fully elucidated. The purpose of this study is to explore the role of BMI in the relationship between E-DII and hyperuricemia in the American population. METHODS: A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2007 to 2016, with a sample size of 10,571 participants. The study used a weighted logistic regression model and a generalized additive model (GAM) to explore the associations among BMI, hyperuricemia and E-DII. Furthermore, mediation analysis was utilized to illustrate the mediating relationships among these variables. RESULTS: The results of the study indicated that a higher E-DII was related to an increased risk of hyperuricemia. The association between E-DII and hyperuricemia was partially mediated by BMI. CONCLUSIONS: E-DII is associated with hyperuricemia. BMI mediates the relationship between E-DII and hyperuricemia among Americans, which provides crucial information for the prevention of hyperuricemia.

Multitask Image Clustering via Deep Information Bottleneck.

Multitask image clustering approaches intend to improve the model accuracy on each task by exploring the relationships of multiple related image clustering tasks. However, most existing multitask clustering (MTC) approaches isolate the representation abstraction from the downstream clustering procedure, which makes the MTC models unable to perform unified optimization. In addition, the existing MTC relies on exploring the relevant information of multiple related tasks to discover their latent correlations while ignoring the irrelevant information between partially related tasks, which may also degrade the clustering performance. To tackle these issues, a multitask image clustering method named deep multitask information bottleneck (DMTIB) is devised, which aims at conducting multiple related image clustering by maximizing the relevant information of multiple tasks while minimizing the irrelevant information among them. Specifically, DMTIB consists of a main-net and multiple subnets to characterize the relationships across tasks and the correlations hidden in a single clustering task. Then, an information maximin discriminator is devised to maximize the mutual information (MI) measurement of positive samples and minimize the MI of negative ones, in which the positive and negative sample pairs are constructed by a high-confidence pseudo-graph. Finally, a unified loss function is devised for the optimization of task relatedness discovery and MTC simultaneously. Empirical comparisons on several benchmark datasets, NUS-WIDE, Pascal VOC, Caltech-256, CIFAR-100, and COCO, show that our DMTIB approach outperforms more than 20 single-task clustering and MTC approaches.

Norbornene Copolymerization with Polar Monomers Catalyzed by Palladium Catalysts Containing Imidazolidin-2-imine/Guanidine Ligands.

The development of a palladium catalyst that has enhanced catalytic performance, such as low aluminum cocatalyst loading, good copolymerization ability, high molecular weight, and excellent solubility of the (co)polymers, is still a challenge in norbornene copolymerizations. Here, a series of PdCl2 and PdMeCl complexes containing differently substituted anilines and imidazolidin-2-imine/guanidine ligands was successfully synthesized and characterized. X-ray diffraction analysis results revealed that these Pd complexes adopted an almost square-planar geometry, and the six-membered chelate ring showed structural distinctions as compared to traditional N^N-based α-diimine and ß-diimine Pd complexes. These Pd complexes were activated by EtAlCl2 and then exhibited moderate activity (104-105 g mol-1 h-1) and good thermal stability (up to 90 °C) for norbornene polymerization to produce high-molecular-weight PNBs (Mn up to 96.4 kg mol-1) with narrow polydispersities (PDI as low as 1.39). These Pd complexes also exhibited good polar group tolerance in the copolymerization of norbornene with methyl 5-norbornene-2-carboxylate and methyl 10-undecenoate, in which the activity was achieved up to 7.04 × 104 g mol-1 h-1. It furnished polar functionalized norbornene-based copolymers with high molecular weight (Mn up to 63.1 kg mol-1), narrow PDI, reasonable polar monomer incorporation, and good solubility. These Pd catalysts exhibited an enhanced copolymerization ability to produce PNB or NB-based copolymers, representing significant progress in this field.

LGNN: a novel linear graph neural network algorithm.

The emergence of deep learning has not only brought great changes in the field of image recognition, but also achieved excellent node classification performance in graph neural networks. However, the existing graph neural network framework often uses methods based on spatial domain or spectral domain to capture network structure features. This process captures the local structural characteristics of graph data, and the convolution process has a large amount of calculation. It is necessary to use multi-channel or deep neural network structure to achieve the goal of modeling the high-order structural characteristics of the network. Therefore, this paper proposes a linear graph neural network framework [Linear Graph Neural Network (LGNN)] with superior performance. The model first preprocesses the input graph, and uses symmetric normalization and feature normalization to remove deviations in the structure and features. Then, by designing a high-order adjacency matrix propagation mechanism, LGNN enables nodes to iteratively aggregate and learn the feature information of high-order neighbors. After obtaining the node representation of the network structure, LGNN uses a simple linear mapping to maintain computational efficiency and obtain the final node representation. The experimental results show that the performance of the LGNN algorithm in some tasks is slightly worse than that of the existing mainstream graph neural network algorithms, but it shows or exceeds the machine learning performance of the existing algorithms in most graph neural network performance evaluation tasks, especially on sparse networks.

LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality.

Age is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical practice and self-monitoring is important but currently lacking. The human lens accumulates age-related changes that are amenable to rapid and objective assessment. Here, using lens photographs from 20 to 96-year-olds, we develop LensAge to reflect lens aging via deep learning. LensAge is closely correlated with chronological age of relatively healthy individuals (R2 > 0.80, mean absolute errors of 4.25 to 4.82 years). Among the general population, we calculate the LensAge index by contrasting LensAge and chronological age to reflect the aging rate relative to peers. The LensAge index effectively reveals the risks of age-related eye and systemic disease occurrence, as well as all-cause mortality. It outperforms chronological age in reflecting age-related disease risks (p < 0.001). More importantly, our models can conveniently work based on smartphone photographs, suggesting suitability for routine self-examination of aging status. Overall, our study demonstrates that the LensAge index may serve as an ideal quantitative indicator for clinically assessing and self-monitoring biological age in humans.

MdNup62 involved in salt and osmotic stress tolerance in apple.

Abiotic stress of plants has serious consequences on the development of the apple industry. Nuclear pore complexes (NPCs) control nucleoplasmic transport and play an important role in the regulation of plant abiotic stress response. However, the effects of NPCs on apple salt and osmotic stress responses have not been reported yet. In this study, we analyzed the expression and function of NUCLEOPORIN 62 (MdNup62), a component of apple NPC. MdNup62 expression was significantly increased by salt and mannitol (simulated osmotic stress) treatment. The MdNup62-overexpressing (OE) Arabidopsis and tomato lines exhibited significantly reduced salt stress tolerance, and MdNup62-OE Arabidopsis lines exhibited reduced osmotic stress tolerance. We further studied the function of HEAT SHOCK FACTOR A1d (MdHSFA1d), the interacting protein of MdNup62, in salt and osmotic stress tolerance. In contrast to MdNup62, MdHSFA1d-OE Arabidopsis lines showed significantly enhanced tolerance to salt and osmotic stress. Our findings suggest a possible interaction of MdNup62 with MdHSFA1d in the mediation of nuclear and cytoplasmic transport and the regulation of apple salt and osmotic stress tolerance. These results contribute to the understanding of the salt and osmotic stress response mechanism in apple.

Synthesis of cell penetrating peptide sterol coupler and its liposome study on S-mRNA.

In order to overcome the current LNP-mRNA delivery system's weakness of poor stability and rapid degradation by nuclease, a novel chol-CGYKK molecule and then the new phospholipid liposome were designed and prepared. A solid phase approach synthesized CGYKK and connected it to cholesterol via a disulfide linker to form the desired chol-CGYKK. Four formulated samples with different proportions of excipients were prepared by freeze-drying cationic liposomes and packaged S-mRNA. The stability test shows that after six months at 4 °C, the encapsulation rate of this novel phospholipid liposome was still approximately 90%, which would significantly improve the storage and transportation requirement. Transmission electron microscopy, atomic force microscopy, and scanning electron microscopy indicated that the liposomes were spherical and uniformly dispersed. On comparing the levels of mRNA protein expression of the four formulated samples, the S protein vaccine expression of formulated sample 1 was the highest. Uptake by vector cells for formulated sample 1 showed that compared to Lipo2000, and the transfection efficiency was 66.7%. Furthermore, the safety evaluation of the CGYKK and mRNA vaccine liposomes revealed no toxic effects. The in vivo study demonstrated that this novel mRNA vaccine had an immune response. However, it was still not as good as the LNP group right now, but its excellent physicochemical properties, stability, in vitro biological activity, and in vivo efficacy against SARS-CoV-2 provided new strategies for developing the next generation of mRNA delivery system.