Polyglycerol-Shelled Reduction-Sensitive Polymersome for DM1 Delivery to HER-2-Positive Breast Cancer.

Supramolecular delivery systems with the prolonged circulation, the potential for diverse functionalization, and few toxin-related limitations have been extensively studied. For the present study, we constructed a linear polyglycerol-shelled polymersome attached with the anti-HER-2-antibody trastuzumab. We then covalently loaded the anticancer drug DM1 in the polymersome via dynamic disulfide bonding. The resulted trastuzumab-polymersome-DM1 (Tra-PS-DM1) exhibits a mean size of 95.3 nm and remarkable drug loading efficiency % of 99.3%. In addition to its superior stability, we observed the rapid release of DM1 in a controlled manner under reductive conditions. Compared to the native polymersomes, Tra-PS-DM1 has shown greatly improved cellular uptake and significantly reduced IC50 up to 17-fold among HER-2-positive cancer cells. Moreover, Tra-PS-DM1 demonstrated superb growth inhibition of HER-2-positive tumoroids; specifically, BT474 tumoroids shrunk up to 62% after 12 h treatment. With exceptional stability and targetability, the PG-shelled Tra-PS-DM1 appears as an attractive approach for HER-2-positive tumor treatment.

SIRT1 mediates the excitability of spinal CaMKIIα-positive neurons and participates in neuropathic pain by controlling Nav1.3.

AIMS: Neuropathic pain is a common chronic pain disorder, which is largely attributed to spinal central sensitization. Calcium/calmodulin-dependent protein kinase II alpha (CaMKIIα) activation in the spinal dorsal horn (SDH) is a major contributor to spinal sensitization. However, the exact way that CaMKIIα-positive (CaMKIIα+) neurons in the SDH induce neuropathic pain is still unclear. This study aimed to explore the role of spinal CaMKIIα+ neurons in neuropathic pain caused by chronic constriction injury (CCI) and investigate the potential epigenetic mechanisms involved in CaMKIIα+ neuron activation. METHODS: CCI-induced neuropathic pain mice model, Sirt1loxP/loxP mice, and chemogenetic virus were used to investigate whether the activation of spinal CaMKIIα+ neurons is involved in neuropathic pain and its involved mechanism. Transcriptome sequence, western blotting, qRT-PCR, and immunofluorescence analysis were performed to assay the expression of related molecules and activation of neurons. Co-immunoprecipitation was used to observe the binding relationship of protein. Chromatin immunoprecipitation (ChIP)-PCR was applied to analyze the acetylation of histone H3 in the Scn3a promoter region. RESULTS: The expression of sodium channel Nav1.3 was increased and the expression of SIRT1 was decreased in the spinal CaMKIIα+ neurons of CCI mice. CaMKIIα neurons became overactive after CCI, and inhibiting their activation relieved CCI-induced pain. Overexpression of SIRT1 reversed the increase of Nav1.3 and alleviated pain, while knockdown of SIRT1 or overexpression of Nav1.3 promoted CaMKIIα+ neuron activation and induced pain. By knocking down spinal SIRT1, the acetylation of histone H3 in the Scn3a (encoding Nav1.3) promoter region was increased, leading to an increased expression of Nav1.3. CONCLUSION: The findings suggest that an aberrant reduction of spinal SIRT1 after nerve injury epigenetically increases Nav1.3, subsequently activating CaMKIIα+ neurons and causing neuropathic pain.

Preparation of novel sulfated polysaccharide-carboxymethyl-5-fluorouracil-folic acid conjugates for targeted anticancer drug delivery.

GFP1, a sulfated polysaccharide extracted from Grateloupia filicina, exhibits remarkable immunomodulatory activity. To reduce the side effects of 5-fluorouracil (5-FU), GFP1 was employed as a macromolecular carrier to synthesize of GFP1-C-5-FU by reacting with carboxymethyl-5-fluorouracil (C-5-FU). Subsequently, this new compound was reacted with folic acid (FA) through an ester bond, forming novel conjugates named GFP1-C-5-FU-FA. Nuclear magnetic resonance analysis confirmed the formation of GFP1-C-5-FU-FA. In vitro drug release studies revealed that the cumulative release rate of C-5-FU reached 46.9 % in phosphate buffer (pH 7.4) after 96 h, a rate significantly higher than that of the control groups, indicating the controlled drug release behavior of GFP1-C-5-FU-FA. Additionally, in vitro anticancer assays demonstrated the potent anticancer activity of GFP1-C-5-FU-FA conjugates, as evidenced by the reduced viability of HeLa and AGS cancer cells, along with increased levels of apoptosis and cellular uptake. Western blot analysis indicated that the GFP1-C-5-FU-FA conjugate effectively enhanced phosphorylation in cancer cells through the NF-kB and MAPK pathways, thereby promoting apoptosis. These findings highlight the potential of folate-targeted conjugates in efficiently treating HeLa and AGS cancer cells in vitro and lay a robust theoretical groundwork for future in vivo anti-cancer research involving these cells.

Continuous protein-density gradients: A new approach to correlate physical cues with cell response.

To assess cellular behavior within heterogeneous tissues, such as bone, skin, and nerves, scaffolds with biophysical gradients are required to adequately replicate the in vivo interaction between cells and their native microenvironment. In this study, we introduce a strategy for depositing ultrathin films comprised of laminin-111 with precisely controlled biophysical gradients onto planar substrates using the Langmuir-Blodgett (LB) technique. The gradient is created by controlled desynchronization of the barrier compression and substrate withdrawal speed during the LB deposition process. Characterization of the films was performed using techniques such as atomic force microscopy and confocal fluorescence microscopy, enabling the comprehensive analysis of biophysical parameters along the gradient direction. Furthermore, human adipose-derived stem cells were seeded onto the gradient films to investigate the influence of protein density on cell attachment, showing that the distribution of the cells can be modulated by the arrangement of the laminin at the air-water interface. The presented approach not only allowed us to gain insights into the intricate interplay between biophysical cues and cell behavior within complex tissue environments, but it is also suited as a screening approach to determine optimal protein concentrations to achieve a target cellular output.

Trajectories of squamous cell carcinoma antigen and outcomes of patients with advanced penile cancer after chemotherapy based on paclitaxel, ifosfamid, and cisplatin regimen.

INTRODUCTION: Penile cancer (PC) is a lethal malignancy with no effective prognostic biomarker. We aim to investigate associations between trajectories of squamous cell carcinoma antigen (SCC-A) and patient outcomes after chemotherapy based on paclitaxel, ifosfamid, and cisplatin (TIP) regimen. METHODS: Consecutive AJCC staging III/IV PC patients who received TIP chemotherapy and repeated SCC-A measurements in 2014-2022 were analyzed. Latent class growth mixed (LCGM) models were employed to characterize patients' serum SCC-A trajectories. Patient survival, and clinical and pathological tumor responses were compared. Inverse probability treatment weighting was used to adjust confounding factors. RESULTS: Eighty patients were included. LCGM models identified two distinct trajectories of SCC-A: low-stable (40%; n = 32) and high-decline (60%; n = 48). Overall survival (HR [95% CI]: 3.60 [1.23-10.53], p = 0.019), progression-free survival (HR [95% CI]: 11.33 [3.19-40.3], p < 0.001), objective response rate (37.5% vs. 62.5% p = 0.028), disease control rate (60.4% vs. 96.9% p < 0.00), and pathological complete response rate (21.2% vs. 51.9%, p = 0.014) were significantly worse in the high-decline arm. CONCLUSION: PC patients' SCC-A change rate was associated with tumor response and patient survival after TIP chemotherapy. SCC-A might assist tumor monitoring after systemic therapies.

Protein function annotation and virulence factor identification of Klebsiella pneumoniae genome by multiple machine learning models.

Klebsiella pneumoniae is a type of Gram-negative bacterium which can cause a range of infections in human. In recent years, an increasing number of strains of K. pneumoniae resistant to multiple antibiotics have emerged, posing a significant threat to public health. The protein function of this bacterium is not well known, thus a systematic investigation of K. pneumoniae proteome is in urgent need. In this study, the protein functions of this bacteria were re-annotated, and their function groups were analyzed. Moreover, three machine learning models were built to identify novel virulence factors. Results showed that the functions of 16 uncharacterized proteins were first annotated by sequence alignment. In addition, K. pneumoniae proteins share a high proportion of homology with Haemophilus influenzae and a low homology proportion with Chlamydia pneumoniae. By sequence analysis, 10 proteins were identified as potential drug targets for this bacterium. Our model achieved a high accuracy of 0.901 in the benchmark dataset. By applying our models to K. pneumoniae, we identified 39 virulence factors in this pathogen. Our findings could provide novel clues for the treatment of K. pneumoniae infection.

Study of the mechanism of non-covalent interactions between chlorogenic acid and soy protein isolate: Multi-spectroscopic, in vitro, and computational docking analyses.

This study investigated the interaction mechanism between chlorogenic acid (CA) and soy protein isolate (SPI) through multi-spectroscopic and computational docking and analyzed the changes in its functional properties. The results showed that the interaction of CA with SPI changed its UV and fluorescence absorption, and the fluorescence quenching mechanism was static quenching. At the same time, the secondary structure of the protein was altered, with a reduction in α-helix, ß-sheet and ß-turn. Computer docking analysis showed that CA binds to SPI through hydrophobic interactions, van der Waals forces, and hydrogen bonding to form a more compact complex. In addition, the dose-dependent enhancement of CA improved the functional properties of the complexes, including foaming, emulsification, and antioxidant properties. This study systematically investigated the mechanism of interaction between CA and SPI, which supports further research on food complex systems containing CA and SPI, as well as the application of the complex.

Ba2Ga2F6(IO3)(PO4): the first fluoride-containing iodate-phosphate with a 1D [Ga2F6(IO3)(PO4)]4- helix chain.

Herein, the first F-containing iodate-phosphate, namely Ba2Ga2F6(IO3)(PO4), was prepared via a hydrothermal reaction, in which HPF6 (70 wt% solution in water) was used as the source of both fluoride and phosphate anions for the first time. Ba2Ga2F6(IO3)(PO4) features an unprecedented 1D [Ga2F6(IO3)(PO4)]4- helix chain, composed of a 1D Ga(1)(IO3)O4F chain via the bridging of 0D Ga(2)(PO4)F5. The UV-Vis spectrum shows that Ba2Ga2F6(IO3)(PO4) has a wide bandgap with a short-UV absorption edge (4.35 eV; 253 nm). Birefringence measurement under a polarizing microscope shows that Ba2Ga2F6(IO3)(PO4) displays a moderate birefringence of 0.072@550 nm, which is consistent with the value (0.070@550 nm) obtained by DFT calculations, indicating that Ba2Ga2F6(IO3)(PO4) has potential applications as a short-UV birefringent material. This study highlights the crucial role played by the incorporation of specific functional groups into compounds, shedding light on their contribution to promising inorganic functional materials.

Intelligent control of self-driving vehicles based on adaptive sampling supervised actor-critic and human driving experience.

Due to the complexity of the driving environment and the dynamics of the behavior of traffic participants, self-driving in dense traffic flow is very challenging. Traditional methods usually rely on predefined rules, which are difficult to adapt to various driving scenarios. Deep reinforcement learning (DRL) shows advantages over rule-based methods in complex self-driving environments, demonstrating the great potential of intelligent decision-making. However, one of the problems of DRL is the inefficiency of exploration; typically, it requires a lot of trial and error to learn the optimal policy, which leads to its slow learning rate and makes it difficult for the agent to learn well-performing decision-making policies in self-driving scenarios. Inspired by the outstanding performance of supervised learning in classification tasks, we propose a self-driving intelligent control method that combines human driving experience and adaptive sampling supervised actor-critic algorithm. Unlike traditional DRL, we modified the learning process of the policy network by combining supervised learning and DRL and adding human driving experience to the learning samples to better guide the self-driving vehicle to learn the optimal policy through human driving experience and real-time human guidance. In addition, in order to make the agent learn more efficiently, we introduced real-time human guidance in its learning process, and an adaptive balanced sampling method was designed for improving the sampling performance. We also designed the reward function in detail for different evaluation indexes such as traffic efficiency, which further guides the agent to learn the self-driving intelligent control policy in a better way. The experimental results show that the method is able to control vehicles in complex traffic environments for self-driving tasks and exhibits better performance than other DRL methods.

Poly (adenosine diphosphate-ribose) polymerase inhibitors in the treatment of triple-negative breast cancer with homologous repair deficiency.

Breast cancer (BC) is a highly heterogeneous disease, and the presence of germline breast cancer gene mutation (gBRCAm) is associated with a poor prognosis. Triple-negative breast cancer (TNBC) is a BC subtype, characterized by the absence of hormone and growth factor receptor expression, making therapeutic decisions difficult. Defects in the DNA damage response pathway due to mutation in breast cancer genes (BRCA 1/2) lead to homologous recombination deficiency (HRD). However, in HRD conditions, poly (adenosine diphosphate-ribose) polymerase (PARP) proteins repair DNA damage and lead to tumor cell survival. Biological understanding of HRD leads to the development of PARP inhibitors (PARPi), which trap PARP proteins and cause genomic instability and tumor cell lysis. HRD assessment can be an important biomarker in identifying gBRCAm patients with BC who could benefit from PARPi therapy. HRD can be identified by homologous recombination repair (HRR) gene-based assays, genomic-scarring assays and mutational signatures, transcription and protein expression profiles, and functional assays. However, gold standard methodologies that are robust and reliable to assess HRD are not available currently. Hence, there is a pressing need to develop accurate biomarkers identifying HRD tumors to guide targeted therapies such as PARPi in patients with BC. HRD assessment has shown fruitful outcomes in chemotherapy studies and preliminary evidence on PARPi intervention as monotherapy and combination therapy in HRD-stratified patients. Furthermore, ongoing trials are exploring the potential of PARPi in BC and clinically complex TNBC settings, where HRD testing is used as an adjunct to stratify patients based on BRCA mutations.

Two-dimensional tetragonal AlOX (X = Cl, Br, or I) monolayers with promising photocatalytic performance: first-principles investigations.

It is of great significance to search for new two-dimensional materials with excellent photocatalytic water splitting properties. Here, the AlOX (X = Cl, Br, or I) monolayers were constructed to explore their electronic and optical properties as a potential photocatalyst and mechanism of high photocatalytic activity by first principles calculations, for the first time. The results show that the AlOX (X = Cl, Br, or I) monolayers are all dynamically and thermodynamically stable. It is found that the AlOI monolayer exhibits visible optical absorption with a 538 nm absorption band edge, due to its direct band gap of 2.22 eV. Moreover, an appropriate band edge potential ensures its excellent reduction-oxidation (redox) ability. The asymmetry of crystals along different directions results in a noncoplanar HOMO and LUMO as well as an anisotropy effective mass and favors the separation of photogenerated carriers. These findings present the potential of the AlOX (X = Cl, Br, or I) monolayers as photocatalysts.

Identification of novel single nucleotide variants in the drug resistance mechanism of Mycobacterium tuberculosis isolates by whole-genome analysis.

BACKGROUND: Tuberculosis (TB) represents a major global health challenge. Drug resistance in Mycobacterium tuberculosis (MTB) poses a substantial obstacle to effective TB treatment. Identifying genomic mutations in MTB isolates holds promise for unraveling the underlying mechanisms of drug resistance in this bacterium. METHODS: In this study, we investigated the roles of single nucleotide variants (SNVs) in MTB isolates resistant to four antibiotics (moxifloxacin, ofloxacin, amikacin, and capreomycin) through whole-genome analysis. We identified the drug-resistance-associated SNVs by comparing the genomes of MTB isolates with reference genomes using the MuMmer4 tool. RESULTS: We observed a strikingly high proportion (94.2%) of MTB isolates resistant to ofloxacin, underscoring the current prevalence of drug resistance in MTB. An average of 3529 SNVs were detected in a single ofloxacin-resistant isolate, indicating a mutation rate of approximately 0.08% under the selective pressure of ofloxacin exposure. We identified a set of 60 SNVs associated with extensively drug-resistant tuberculosis (XDR-TB), among which 42 SNVs were non-synonymous mutations located in the coding regions of nine key genes (ctpI, desA3, mce1R, moeB1, ndhA, PE_PGRS4, PPE18, rpsA, secF). Protein structure modeling revealed that SNVs of three genes (PE_PGRS4, desA3, secF) are close to the critical catalytic active sites in the three-dimensional structure of the coding proteins. CONCLUSION: This comprehensive study elucidates novel resistance mechanisms in MTB against antibiotics, paving the way for future design and development of anti-tuberculosis drugs.

Exploring secondary aerosol formation associated with elemental carbon in the lower free troposphere.

The variability of element carbon (EC) mixed with secondary species significantly complicates the assessment of its environmental impact, reflecting the complexity and diversity of EC-containing particles' composition and morphology during their ascent and regional transport. While the catalytic role of EC in secondary aerosol formation is recognized, the effects of heterogeneous chemistry on secondary species formation within diverse EC particle types are not thoroughly understood, particularly in the troposphere. Alpine sites offer a prime environment to explore EC properties post-transport from the ground to the free troposphere. Consequently, we conducted a comprehensive study on the genesis of secondary aerosols in EC-containing particles at Mt. Hua (altitude: 2069 m) from 1 May to 10 July, using a single particle aerosol mass spectrometer (SPAMS). Our analysis identified six major EC particle types, with EC-K, EC-SN, and EC-NaK particles accounting for 27.6 %, 27.0 %, and 19.6 % of the EC particle population, respectively. The concentration-weighted trajectory (CWT) indicated that the lower free troposphere over Mt. Hua is significantly affected by anthropogenic emissions at ground-level, predominantly from northwestern and eastern China. Atmospheric interactions are crucial in generating high sulfate levels in EC-SN and EC-OC particles (> 70 %) and notable nitrate levels in EC-K, EC-BB, and EC-Fe particles (> 80 %). The observed high chloride content in EC-OC particles (56 ± 32 %) might enhance chlorine's reactivity with organic compounds via heterogeneous reactions within the troposphere. Distinct diurnal cycles for sulfate and nitrate are mainly driven by varying transport dynamics and formation processes, showing minimal dependency on EC particle types. Enhanced nocturnal oxalate conversion in EC-Fe particles is likely due to the aqueous oxidation of precursors, with Fe-catalyzed Fenton reactions enhancing OH radical production. This investigation provides critical insights into EC's role in secondary aerosol development during its transport in the lower free troposphere.

Effects of seasonal precipitation regimes on microbial biomass and extracellular enzyme activity during shrub foliar litter decomposition in a subtropical forest.

Elucidating the mechanisms underlying microbial biomass and extracellular enzyme activity responses to the seasonal precipitation regime during foliar litter decomposition is highly important for understanding the material cycle of forest ecosystems in the context of global climate change; however, the specific underlying mechanisms remain unclear. Hence, a precipitation manipulation experiment involving a control (CK) and treatments with decreased precipitation in the dry season and extremely increased precipitation in the wet season (IE) and decreased precipitation in the dry season and proportionally increased precipitation in the wet season (IP) was conducted in a subtropical evergreen broad-leaved forest in China from October 2020 to October 2021. The moisture, microbial biomass, and extracellular enzyme activities of foliar litter from two dominant shrub species, Phyllostachys violascens and Alangium chinense, were measured at six stages during the dry and wet seasons. The results showed that (1) both IE and IP significantly decreased the microbial biomass carbon and microbial biomass nitrogen content and the activities of ß-1,4-glucosidase, ß-1,4-N-acetylglucosaminidase, acid phosphatase and cellulase in the dry season, while the opposite effects were observed in the wet season. (2) Compared with those of IE, the effects of IP on foliar litter microbial biomass and extracellular enzyme activity were more significant. (3) The results from the partial least squares model indicated that extracellular enzyme activity during foliar litter decomposition was strongly controlled by the foliar litter water content, microbial biomass nitrogen, the ratio of total carbon to total phosphorus, foliar litter total carbon, and foliar litter total nitrogen. These results provide an important theoretical basis for elucidating the microbial mechanisms driving litter decomposition in a subtropical forest under global climate change scenarios.

Multi-omics analyses provide insights into the genomic basis of differentiation among four sweet osmanthus groups.

Sweet osmanthus (Osmanthus fragrans) is famous in China for its flowers and contains four groups: Albus, Luteus, Aurantiacus, and Asiaticus. Understanding the relationships among these groups and the genetic mechanisms of flower color and aroma biosynthesis are of tremendous interest. In this study, we sequenced representative varieties from two of the four sweet osmanthus groups. Multi-omic and phylogenetic analyses of varieties from each of the four groups showed that Asiaticus split first within the species, followed by Aurantiacus and the sister groups Albus and Luteus. We show that the difference in flower color between Aurantiacus and the other three groups was caused by a 4-bp deletion in the promoter region of carotenoid cleavage dioxygenase 4 (OfCCD4) that leads to expression decrease. In addition, we identified 44 gene pairs exhibiting significant structural differences between the multi-seasonal flowering variety 'Rixianggui' in the Asiaticus group and other autumn flowering varieties. Through correlation analysis between intermediate products of aromatic components and gene expression, we identified eight genes associated with the linalool, α- and ß-ionone biosynthesis pathways. Overall, our study offers valuable genetic resources for sweet osmanthus, while also providing genetic clues for improving the flower color and multi-season flowering of osmanthus and other flowers.

Multi-omics analysis reveals key regulatory defense pathways and genes involved in salt tolerance of rose plants.

Salinity stress causes serious damage to crops worldwide, limiting plant production. However, the metabolic and molecular mechanisms underlying the response to salt stress in rose (Rosa spp.) remain poorly studied. We therefore performed a multi-omics investigation of Rosa hybrida cv. Jardin de Granville (JDG) and Rosa damascena Mill. (DMS) under salt stress to determine the mechanisms underlying rose adaptability to salinity stress. Salt treatment of both JDG and DMS led to the buildup of reactive oxygen species (H2O2). Palisade tissue was more severely damaged in DMS than in JDG, while the relative electrolyte permeability was lower and the soluble protein content was higher in JDG than in DMS. Metabolome profiling revealed significant alterations in phenolic acid, lipids, and flavonoid metabolite levels in JDG and DMS under salt stress. Proteome analysis identified enrichment of flavone and flavonol pathways in JDG under salt stress. RNA sequencing showed that salt stress influenced primary metabolism in DMS, whereas it substantially affected secondary metabolism in JDG. Integrating these datasets revealed that the phenylpropane pathway, especially the flavonoid pathway, is strongly enhanced in rose under salt stress. Consistent with this, weighted gene coexpression network analysis (WGCNA) identified the key regulatory gene chalcone synthase 1 (CHS1), which is important in the phenylpropane pathway. Moreover, luciferase assays indicated that the bHLH74 transcription factor binds to the CHS1 promoter to block its transcription. These results clarify the role of the phenylpropane pathway, especially flavonoid and flavonol metabolism, in the response to salt stress in rose.

Multi-View Time-Series Hypergraph Neural Network for Action Recognition.

Recently, action recognition has attracted considerable attention in the field of computer vision. In dynamic circumstances and complicated backgrounds, there are some problems, such as object occlusion, insufficient light, and weak correlation of human body joints, resulting in skeleton-based human action recognition accuracy being very low. To address this issue, we propose a Multi-View Time-Series Hypergraph Neural Network (MV-TSHGNN) method. The framework is composed of two main parts: the construction of a multi-view time-series hypergraph structure and the learning process of multi-view time-series hypergraph convolutions. Specifically, given the multi-view video sequence frames, we first extract the joint features of actions from different views. Then, limb components and adjacent joints spatial hypergraphs based on the joints of different views at the same time are constructed respectively, temporal hypergraphs are constructed joints of the same view at continuous times, which are established high-order semantic relationships and cooperatively generate complementary action features. After that, we design a multi-view time-series hypergraph neural network to efficiently learn the features of spatial and temporal hypergraphs, and effectively improve the accuracy of skeleton-based action recognition. To evaluate the effectiveness and efficiency of MV-TSHGNN, we conduct experiments on NTU RGB+D, NTU RGB+D 120 and imitating traffic police gestures datasets. The experimental results indicate that our proposed method model achieves the new state-of-the-art performance.

Comparison of trial lens and computer-aided fitting in orthokeratology: A multi-center, randomized, examiner-masked, controlled study.

PURPOSE: To compare the efficacy and safety between traditional lens fitting and computer-aided fitting methods for orthokeratology (OrthoK) in the Chinese population. METHODS: A multi-center, examiner-masked, randomized controlled study was conducted with a one-year follow-up period, enrolling 280 participants with spherical equivalent (SE) ranging from -0.5D to -4.0D. Participants were assigned to either the computer-aided orthokeratology fitting group (trial group) or the traditional lens fitting group (control group) using stratified randomization based on age (8 to 13 years, 13 to 18 years, and ≥ 18 years) to ensure a minimum of 30 cases in each sub-age group. Ocular examinations included visual acuity, objective and subjective refraction, corneal endothelial cell density, corneal topography, intraocular pressure, axial length, and ocular health assessment. Successful lens-correction was defined as the residual refraction with the OK lens, which should not exceed ± 0.5D, and/or an uncorrected visual acuity of no worse than 0.1 logMAR. Statistical analysis involves t-tests, analysis of variance, and Chi-squared tests. RESULTS: 215 subjects were included in the statistical analysis (109 in the trial group and 106 in the control group). In both groups, compared to baseline data, the uncorrected visual acuity (UCVA) improved significantly, with SE reduced and central corneal curvature flattened greatly after wearing OrthoK lens (P < 0.05 for all). Compared to the control group, the trial group exhibited a higher successful rate in correcting UCVA (93.6 % vs. 84.0 %, P = 0.03) and slightly better correction in refraction (77.1 % vs. 66.0 %, P = 0.07) at 1-month follow-up. However, no significant differences were observed in the axial length elongation, corneal changes, or the incidence of adverse events between the two groups. CONCLUSION: These findings indicate the higher efficiency and slightly better performance in correcting myopia and improving UCVA of computer-aided lens fitting approach compared to the traditional one, but similar outcomes in controlling axial elongation.

Identification and validation of stable reference genes for RT-qPCR analyses of Kobresia littledalei seedlings.

BACKGROUND: Kobreisa littledalei, belonging to the Cyperaceae family is the first Kobresia species with a reference genome and the most dominant species in Qinghai-Tibet Plateau alpine meadows. It has several resistance genes which could be used to breed improved crop varieties. Reverse Transcription Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR) is a popular and accurate gene expression analysis method. Its reliability depends on the expression levels of reference genes, which vary by species, tissues and environments. However, K.littledalei lacks a stable and normalized reference gene for RT-qPCR analysis. RESULTS: The stability of 13 potential reference genes was tested and the stable reference genes were selected for RT-qPCR normalization for the expression analysis in the different tissues of K. littledalei under two abiotic stresses (salt and drought) and two hormonal treatments (abscisic acid (ABA) and gibberellin (GA)). Five algorithms were used to assess the stability of putative reference genes. The results showed a variation amongst the methods, and the same reference genes showed tissue expression differences under the same conditions. The stability of combining two reference genes was better than a single one. The expression levels of ACTIN were stable in leaves and stems under normal conditions, in leaves under drought stress and in roots under ABA treatment. The expression of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression was stable in the roots under the control conditions and salt stress and in stems exposed to drought stress. Expression levels of superoxide dismutase (SOD) were stable in stems of ABA-treated plants and in the roots under drought stress. Moreover, RPL6 expression was stable in the leaves and stems under salt stress and in the stems of the GA-treated plants. EF1-alpha expression was stable in leaves under ABA and GA treatments. The expression levels of 28 S were stable in the roots under GA treatment. In general, ACTIN and GAPDH could be employed as housekeeping genes for K. littledalei under different treatments. CONCLUSION: This study identified the best RT-qPCR reference genes for different K. littledalei tissues under five experimental conditions. ACTIN and GAPDH genes can be employed as the ideal housekeeping genes for expression analysis under different conditions. This is the first study to investigate the stable reference genes for normalized gene expression analysis of K. littledalei under different conditions. The results could aid molecular biology and gene function research on Kobresia and other related species.