Classification of congenital cataracts based on multidimensional phenotypes and its association with visual outcomes.

AIM: To establish a classification for congenital cataracts that can facilitate individualized treatment and help identify individuals with a high likelihood of different visual outcomes. METHODS: Consecutive patients diagnosed with congenital cataracts and undergoing surgery between January 2005 and November 2021 were recruited. Data on visual outcomes and the phenotypic characteristics of ocular biometry and the anterior and posterior segments were extracted from the patients' medical records. A hierarchical cluster analysis was performed. The main outcome measure was the identification of distinct clusters of eyes with congenital cataracts. RESULTS: A total of 164 children (299 eyes) were divided into two clusters based on their ocular features. Cluster 1 (96 eyes) had a shorter axial length (mean±SD, 19.44±1.68 mm), a low prevalence of macular abnormalities (1.04%), and no retinal abnormalities or posterior cataracts. Cluster 2 (203 eyes) had a greater axial length (mean±SD, 20.42±2.10 mm) and a higher prevalence of macular abnormalities (8.37%), retinal abnormalities (98.52%), and posterior cataracts (4.93%). Compared with the eyes in Cluster 2 (57.14%), those in Cluster 1 (71.88%) had a 2.2 times higher chance of good best-corrected visual acuity [<0.7 logMAR; OR (95%CI), 2.20 (1.25-3.81); P=0.006]. CONCLUSION: This retrospective study categorizes congenital cataracts into two distinct clusters, each associated with a different likelihood of visual outcomes. This innovative classification may enable the personalization and prioritization of early interventions for patients who may gain the greatest benefit, thereby making strides toward precision medicine in the field of congenital cataracts.

Non-invasive screening and subtyping for breast cancer by serum SERS combined with LGB-DNN algorithms.

Early detection of breast cancer and its molecular subtyping is crucial for guiding clinical treatment and improving survival rate. Current diagnostic methods for breast cancer are invasive, time consuming and complicated. In this work, an optical detection method integrating surface-enhanced Raman spectroscopy (SERS) technology with feature selection and deep learning algorithm was developed for identifying serum components and building diagnostic model, with the aim of efficient and accurate noninvasive screening of breast cancer. First, the high quality of serum SERS spectra from breast cancer (BC), breast benign disease (BBD) patients and healthy controls (HC) were obtained. Chi-square tests were conducted to exclude confounding factors, enhancing the reliability of the study. Then, LightGBM (LGB) algorithm was used as the base model to retain useful features to significantly improve classification performance. The DNN algorithm was trained through backpropagation, adjusting the weights and biases between neurons to improve the network's predictive ability. In comparison to traditional machine learning algorithms, this method provided more accurate information for breast cancer classification, with classification accuracies of 91.38 % for BC and BBD, and 96.40 % for BC, BBD, and HC. Furthermore, the accuracies of 90.11 % for HR+/HR- and 88.89 % for HER2+/HER2- can be reached when evaluating BC patients' molecular subtypes. These results demonstrate that serum SERS combined with powerful LGB-DNN algorithm would provide a supplementary method for clinical breast cancer screening.

Optical Nanobiosensor Based on Surface-Enhanced Raman Spectroscopy and Catalytic Hairpin Assembly for Early-Stage Lung Cancer Detection via Blood Circular RNA.

Lung cancer has become the leading cause of cancer-related deaths globally. However, early detection of lung cancer remains challenging, resulting in poor outcomes for the patients. Herein, we developed an optical biosensor integrating surface-enhanced Raman spectroscopy (SERS) with a catalyzed hairpin assembly (CHA) to detect circular RNA (circRNA) associated with tumor formation and progression (circSATB2). The signals of the Raman reporter were considerably enhanced by generating abundant SERS "hot spots" with a core-shell nanoprobe and 2D SERS substrate with calibration capabilities. This approach enabled the sensitive (limit of detection: 0.766 fM) and reliable quantitative detection of the target circRNA. Further, we used the developed biosensor to detect the circRNA in human serum samples, revealing that patients with lung cancer had higher circRNA concentrations than healthy subjects. Moreover, we characterized the unique circRNA concentration profiles of the early stages (IA and IB) and subtypes (IA1, IA2, and IA3) of lung cancer. These results demonstrate the potential of the proposed optical sensing nanoplatform as a liquid biopsy and prognostic tool for the early screening of lung cancer.

Sex and race differences in the association of albumin with cognitive function in older adults.

BACKGROUND: With the increasing aging population, dementia has become a significant socioeconomic burden. However, the effects of albumin on delayed recall (DR) impairment remain unclear, and there are limited reports on sex and race differences in this relationship. This study aimed to investigate the association between albumin levels and DR impairment in older adults. METHODS: A total of 1507 normal cognitive function and 553 DR impairment from the National Health and Nutrition Examination Survey (NHANES) 2011-2014 were included in this cross-sectional analysis. Participants aged 60 years and above were assessed using the Consortium to Establish a Registry for Alzheimer's Disease DR (CERAD-DR) test to evaluate cognitive function. Participants were categorized into DR impairment and normal cognitive function groups according to their CERAD-DR scores. Logistic regression analyses, generalized additive models, and fitted smoothing curves were utilized for data analysis. RESULTS: After adjusting for potential confounders, a negative association was found between albumin levels and cognitive function (odds ratio [OR] = 0.60, 95% confidence interval [CI] 0.41-0.87). Subgroup analysis stratified by sex, race/ethnicity, and age revealed that the negative association remained significant in men (OR = 0.53, 95%CI 032-0.87), Blacks (OR = 0.35, 95%CI 0.17-0.74), and the age group of 60-70 years (OR = 0.48, 95%CI 0.28-0.81). However, no significant association was observed in women (OR = 0.72, 95%CI 0.41-1.28), whites (OR = 0.58, 95%CI 0.31-1.07), or Mexican Americans (OR = 1.11, 95%CI 0.35-3.46), as well as the age group of 71-80 years (OR = 0.62, 95%CI 0.37-1.03). CONCLUSIONS: Our study suggests that elevated albumin levels are associated with a decreased incidence of cognitive function impairment, particularly in older men and Blacks. This finding indicates that maintaining high levels of albumin may be beneficial for cognitive function in older adults.

Identification of novel molecular subtypes to improve the classification framework of nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) treatment is largely based on a 'one-drug-fits-all' strategy in patients with similar pathological characteristics. However, given its biological heterogeneity, patients at the same clinical stage or similar therapies exhibit significant clinical differences. Thus, novel molecular subgroups based on these characteristics may better therapeutic outcomes. METHODS: Herein, 192 treatment-naïve NPC samples with corresponding clinicopathological information were obtained from Fujian Cancer Hospital between January 2015 and January 2018. The gene expression profiles of the samples were obtained by RNA sequencing. Molecular subtypes were identified by consensus clustering. External NPC cohorts were used as the validation sets. RESULTS: Patients with NPC were classified into immune, metabolic, and proliferative molecular subtypes with distinct clinical features. Additionally, this classification was repeatable and predictable as validated by the external NPC cohorts. Metabolomics has shown that arachidonic acid metabolites were associated with NPC malignancy. We also identified several key genes in each subtype using a weighted correlation network analysis. Furthermore, a prognostic risk model based on these key genes was developed and was significantly associated with disease-free survival (hazard ratio, 1.11; 95% CI, 1.07-1.16; P < 0.0001), which was further validated by an external NPC cohort (hazard ratio, 7.71; 95% CI, 1.39-42.73; P < 0.0001). Moreover, the 1-, 3-, and 5-year areas under the curve were 0.84 (95% CI, 0.74-0.94), 0.81 (95% CI, 0.73-0.89), and 0.82 (95% CI, 0.73-0.90), respectively, demonstrating a high predictive value. CONCLUSIONS: Overall, we defined a novel classification of nasopharyngeal carcinoma (immune, metabolism, and proliferation subtypes). Among these subtypes, metabolism and proliferation subtypes were associated with advanced stage and poor prognosis of NPC patients, whereas the immune subtype was linked to early stage and favorable prognosis.

MYH1G-AS is a chromatin-associated lncRNA that regulates skeletal muscle development in chicken.

BACKGROUND: Skeletal muscle development is pivotal for animal growth and health. Recently, long noncoding RNAs (lncRNAs) were found to interact with chromatin through diverse roles. However, little is known about how lncRNAs act as chromatin-associated RNAs to regulate skeletal muscle development. Here, we aim to investigate the regulation of chromatin-associated RNA (MYH1G-AS) during skeletal muscle development. METHODS: We provided comprehensive insight into the RNA profile and chromatin accessibility of different myofibers, combining RNA sequencing (RNA-seq) with an assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). The dual-luciferase reporter assay and chromatin immunoprecipitation (ChIP) assay were used to analyze the transcriptional regulation mechanism of MYH1G-AS. ALKBH5-mediated MYH1G-AS N6-methyladenosine (m6A) demethylation was assessed by a single-base elongation and ligation-based qPCR amplification method (SELECT) assay. Functions of MYH1G-AS were investigated through a primary myoblast and lentivirus/cholesterol-modified antisense oligonucleotide (ASO)-mediated animal model. To validate the interaction of MYH1G-AS with fibroblast growth factor 18 (FGF18) protein, RNA pull down and an RNA immunoprecipitation (RIP) assay were performed. Specifically, the interaction between FGF18 and SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A member 5 (SMARCA5) protein was analyzed by coimmunoprecipitation (Co-IP) and a yeast two-hybrid assay. RESULTS: A total of 45 differentially expressed (DE) lncRNAs, with DE ATAC-seq peaks in their promoter region, were classified as open chromatin-associated lncRNAs. A skeletal muscle-specific lncRNA (MSTRG.15576.9; MYH1G-AS), which is one of the open chromatin-associated lncRNA, was identified. MYH1G-AS transcription is coordinately regulated by transcription factors (TF) SMAD3 and SP2. Moreover, SP2 represses ALKBH5 transcription to weaken ALKBH5-mediated m6A demethylation of MYH1G-AS, thus destroying MYH1G-AS RNA stability. MYH1G-AS accelerates myoblast proliferation but restrains myoblast differentiation. Moreover, MYH1G-AS drives a switch from slow-twitch to fast-twitch fibers and causes muscle atrophy. Mechanistically, MYH1G-AS inhibits FGF18 protein stabilization to reduce the interaction of FGF18 to SMARCA5, thus repressing chromatin accessibility of the SMAD4 promoter to activate the SMAD4-dependent pathway. CONCLUSIONS: Our results reveal a new pattern of the regulation of lncRNA expression at diverse levels and help expound the regulation of m6A methylation on chromatin status.

An outlier removal method based on PCA-DBSCAN for blood-SERS data analysis.

Surface-enhanced Raman spectroscopy (SERS) has shown promising potential in cancer screening. In practical applications, Raman spectra are often affected by deviations from the spectrometer, changes in measurement environments, and anomalies in spectrum characteristic peak intensities due to improper sample storage. Previous research has overlooked the presence of outliers in categorical data, leading to significant impacts on model learning outcomes. In this study, we propose a novel method, called Principal Component Analysis and Density Based Spatial Clustering of Applications with Noise (PCA-DBSCAN) to effectively remove outliers. This method employs dimensionality reduction and spectral data clustering to identify and remove outliers. The PCA-DBSCAN method introduces adjustable parameters (Eps and MinPts) to control the clustering effect. The effectiveness of the proposed PCA-DBSCAN method is verified through modeling on outlier-removed datasets. Further refinement of the machine learning model and PCA-DBSCAN parameters resulted in the best cancer screening model, achieving 97.41% macro-average recall and 97.74% macro-average F1-score. This paper introduces a new outlier removal method that significantly improves the performance of the SERS cancer screening model. Moreover, the proposed method serves as inspiration for outlier detection in other fields, such as biomedical research, environmental monitoring, manufacturing, quality control, and hazard prediction.

Supplementary White, UV-A, and Far-Red Radiation Differentially Regulates Growth and Nutritional Qualities of Greenhouse Lettuce.

Light is a crucial environmental signal and a form of photosynthetic energy for plant growth, development, and nutrient formation. To explore the effects of light quality on the growth and nutritional qualities of greenhouse-grown lettuce (Lactuca sativa L.), lettuce was cultivated under supplementary white (W) light-emitting diodes (LEDs); white plus ultraviolet A LEDs (W+UV); white plus far-red LEDs (W+FR); and the combination of white, far-red, and UV-A LEDs (W+FR+UV) for 25 days, with lettuce grown under natural sunlight used as the control. The results indicate that the leaf length and leaf width values for lettuce grown under the W+FR+UV treatment were significantly higher than those of lettuce grown under other supplementary light treatments. The highest values of shoot fresh weight, shoot dry weight, root fresh weight, and root dry weight were recorded under the W+FR treatment (4.0, 6.0, 8.0, and 12.4 times higher than those under the control treatment, respectively). Lettuce grown under the W+FR treatment exhibited the highest total chlorophyll content (39.1%, 24.6%, and 16.2% higher than that under the W, W+UV, and W+FR+UV treatments, respectively). The carotenoid content of lettuce grown under the W+FR treatment was the highest among all treatments. However, the root activity of greenhouse-grown lettuce was the highest under the W+FR+UV treatment. Soluble sugar content, cellulose content, and starch content in the lettuce responded differently to the light treatments and were highest under the W+UV treatment. In summary, supplementary light promoted growth and nutrient accumulation in lettuce. Specifically, white plus far-red light promoted lettuce growth, and white plus UV increased some specific compounds in greenhouse-grown lettuce. Our findings provide valuable references for the application of light-supplementation strategies to greenhouse lettuce production.

Adaptive divergence and genetic vulnerability of relict species under climate change: a case study of Pterocarya macroptera.

BACKGROUND AND AIMS: Understanding adaptive genetic variation and whether it can keep pace with predicted future climate change is critical in assessing the genetic vulnerability of species and developing conservation management strategies. The lack of information on adaptive genetic variation in relict species carrying abundant genetic resources hinders the assessment of genetic vulnerability. Using a landscape genomics approach, this study aimed to determine how adaptive genetic variation shapes population divergence and to predict the adaptive potential of Pterocarya macroptera (a vulnerable relict species in China) under future climate scenarios. METHODS: We applied restriction site-associated DNA sequencing (RAD-seq) to obtain 8244 single-nucleotide polymorphisms (SNPs) from 160 individuals across 28 populations. We examined the pattern of genetic diversity and divergence, and then identified outliers by genetic differentiation (FST) and genotype-environment association (GEA) methods. We further dissected the effect of geographical/environmental gradients on genetic variation. Finally, we predicted genetic vulnerability and adaptive risk under future climate scenarios. KEY RESULTS: We identified three genetic lineages within P. macroptera: the Qinling-Daba-Tianmu Mountains (QDT), Western Sichuan (WS) and Northwest Yunnan (NWY) lineages, which showed significant signals of isolation by distance (IBD) and isolation by environment (IBE). IBD and IBE explained 3.7-5.7 and 8.6-12.8 % of the genetic structure, respectively. The identified GEA SNP-related genes were involved in chemical defence and gene regulation and may exhibit higher genetic variation to adapt to the environment. Gradient forest analysis revealed that the genetic variation was mainly shaped by temperature-related variables, indicating its adaptation to local thermal environments. A limited adaptive potential was suggested by the high levels of genetic vulnerability in marginal populations. CONCLUSIONS: Environmental gradient mainly shaped the population differentiation of P. macroptera. Marginal populations may be at high risk of extinction, and thus proactive management measures, such as assisted gene flow, are required to ensure the survival of these populations.

Laser tweezer Raman spectroscopy combined with deep neural networks for identification of liver cancer cells.

Rapid identification of cancer cells is crucial for clinical treatment guidance. Laser tweezer Raman spectroscopy (LTRS) that provides biochemical characteristics of cells can be used to identify cell phenotypes through classification models in a non-invasive and label-free manner. However, traditional classification methods require extensive reference databases and clinical experience, which is challenging when sampling at inaccessible locations. Here, we describe a classification method combing LTRS with deep neural network (DNN) for differential and discriminative analysis of multiple liver cancer (LC) cells. By using LTRS, we obtained high-quality single-cell Raman spectra of normal hepatocytes (HL-7702) and liver cancer cell lines (SMMC-7721, Hep3B, HepG2, SK-Hep1 and Huh7). The tentative assignment of Raman peaks indicated that arginine content was elevated and phenylalanine, glutathione and glutamate content was decreased in liver cancer cells. Subsequently, we randomly selected 300 spectra from each cell line for DNN model analysis, achieving a mean accuracy of 99.2%, a mean sensitivity of 99.2% and a mean specificity of 99.8% for the identification and classification of multiple LC cells and hepatocyte cells. These results demonstrate the combination of LTRS and DNN is a promising method for rapid and accurate cancer cell identification at single cell level.

Ultrasensitive detection of SARS-CoV-2 antigen using surface-enhanced Raman spectroscopy-based lateral flow immunosensor.

The fast spread and transmission of the coronavirus 2019 (COVID-19) has become one of serious global public health problems. Herein, a surface enhanced Raman spectroscopy-based lateral flow immunoassay (LFA) was developed for the detection of SARS-CoV-2 antigen. Using uniquely designed core-shell nanoparticle with embedded Raman probe molecules as the indicator to reveal the concentration of target protein, excellent quantitative performance with a limit of detection (LOD) of 0.03 ng/mL and detection range of 10-1000 ng/mL can be achieved within 15 min. Besides, the detection of spiked virus protein in human saliva was also performed with a portable Raman spectrometer, proposing the feasibility of the method in practical applications. This easy-to-use, rapid and accurate method would provide a point-of-care testing way as the ideal alternative for current detection requirement of virus-related biomarkers.

Shifted-excitation Raman difference spectroscopy for improving in vivo detection of nasopharyngeal carcinoma.

A strong fluorescence background is one of the common interference factors of Raman spectroscopic analysis in biological tissue. This study developed an endoscopic shifted-excitation Raman difference spectroscopy (SERDS) system for real-time in vivo detection of nasopharyngeal carcinoma (NPC) for the first time. Owing to the use of the SERDS method, the high-quality Raman signals of nasopharyngeal tissue could be well extracted and characterized from the complex raw spectra by removing the fluorescence interference signals. Significant spectral differences relating to proteins, phospholipids, glucose, and DNA were found between 42 NPC and 42 normal tissue sites. Using linear discriminant analysis, the diagnostic accuracy of SERDS for NPC detection was 100%, which was much higher than that of raw Raman spectroscopy (75.0%), showing the great potential of SERDS for improving the accurate in vivo detection of NPC.

Integration of transcriptome sequencing and whole genome resequencing reveal candidate genes in egg production of upright and pendulous-comb chickens.

Egg production performance plays an important role in the poultry industry across the world. Previous studies have shown a great difference in egg production performance between pendulous-comb (PC) and upright-comb (UC) chickens. However, there are no reports to identify potential candidate genes for egg production in PC and UC chickens. In the present study, 1,606 laying chickens were raised, and the egg laid by individual chicken was collected for 100 d. Moreover, the expression level of estrogen and progesterone hormones was measured at the start-laying and peak-laying periods of hens. Besides, 4 PC and 4 UC chickens were selected at 217 d of age to perform transcriptome sequencing (RNA-seq) and whole genome resequencing (WGS) to screen the potential candidate genes of egg production. The results showed that PC chicken demonstrated better egg production performance (P < 0.05) and higher estrogen and progesterone hormone expression levels than UC chicken (P < 0.05). RNA-seq analysis showed that 341 upregulated and 1,036 downregulated differentially expressed genes (DEGs) were identified in the ovary tissues of PC and UC chickens. These DEGs were mainly enriched in protein-related, lipid-related, and nucleic acids-related biological processes including ribosome, peptide biosynthetic process, lipid transport terms, and catalytic activity acting on RNA which can significantly affect egg production in chicken. The enrichment results of WGS analysis were consistent with RNA-seq. Further, joint analysis of WGS and RNA-seq data was utilized to screen 30 genes and CAMK1D, CLSTN2, MAST2, PIK3C2G, TBC1D1, STK3, ADGRB3, and PPARGC1A were identified as potential candidate genes for egg production in PC and UC chickens. In summary, our study provides a wealth of information for a better understanding of the genetic and molecular mechanism for the future breeding of PC and UC chickens for egg production.

Highly Efficient Singlet Oxygen Generation by BODIPY-Ruthenium(II) Complexes for Promoting Neurite Outgrowth and Suppressing Tau Protein Aggregation.

Singlet oxygen (1O2) has been recently identified as a key molecule against toxic Aß aggregation, which is associated with the currently incurable Alzheimer's disease (AD). However, limited research has studied its efficiency against tau protein aggregation, the other major hallmark of AD. Herein, we designed and synthesized boron-dipyrromethene (BODIPY)-ruthenium conjugates and isolated three isomers. Under visible-light irradiation, the ε isomer can be photoactivated and efficiently generate singlet oxygen. Particularly, the complex demonstrated successful results in attenuating tauopathy─an appreciable decrease to 43 ± 2% at 100 nM. The photosensitizer was further found to remarkably promote neurite outgrowth and significantly increased the length and number of neurites in nerve cells. As a result of effective photoinduced singlet oxygen generation and proactive neurite outgrowth, the hybrid design has great potential for therapeutics for Alzheimer's disease.

Amelioration of Chilling Injury by Fucoidan in Cold-Stored Cucumber via Membrane Lipid Metabolism Regulation.

Cucumber fruit is very sensitive to chilling injury, which rapidly depreciates their commodity value. Herein, the effect of fucoidan treatment on cucumber under cold stress were investigated. Fucoidan treatment of cold-stored cucumber alleviated the occurrence of chilling injury, delayed weight loss, lowered electrolyte leakage and respiration rate, and retarded malondialdehyde accumulation. Different from the control fruit, fucoidan treated fruit showed a high level of fatty acid unsaturated content, fatty acid unsaturation, and unsaturation index and increased ω-FDAS activity, along with upregulated expression levels of CsSAD and CsFAD genes. Fucoidan reduced the phosphatidic acid content and membrane lipid peroxidation, lowered the phospholipase D (PLD) and lipoxygenase (LOX) activity, and downregulated the expression levels of CsPLD and CsLOX genes. Collectively, fucoidan treatment maintained the integrity of cell membrane in cold-stress cucumbers. The results provide a new prospect for the development of fucoidan as a preservative agent in the low-temperature postharvest storage of cucumbers.

Profiling of Tumor Cell-Delivered Exosome by Surface Enhanced Raman Spectroscopy-Based Biosensor for Evaluation of Nasopharyngeal Cancer Radioresistance.

Although the advancement of radiotherapy significantly improves the survival of nasopharyngeal cancer (NPC), radioresistance associated with recurrence and poor outcomes still remains a daunting challenge in the clinical scenario. Currently, effective biomarkers and convenient detection methods for predicting radioresistance have not been well established. Here, the surface-enhanced Raman spectroscopy combined with proteomics is used to firstly profile the characteristic spectral patterns of exosomes secreted from self-established NPC radioresistance cells, and reveals specific variations of proteins expression during radioresistance formation, including collagen alpha-2 (I) chain (COL1A2) that is associated with a favorable prognosis in NPC and is negatively associated with DNA repair scores and DNA repair-related genes via bioinformatic analysis. Furthermore, deep learning model-based diagnostic model is generated to accurately identify the exosomes from radioresistance group. This work demonstrates the promising potential of exosomes as a novel biomarker for predicting the radioresistance and develops a rapid and sensitive liquid biopsy method that will provide a personalized and precise strategy for clinical NPC treatment.

Transcriptomic analysis reveals the mechanism of the alleviation of salt stress by salicylic acid in pepper (Capsicum annuum L.).

BACKGROUND: The growth and yield of pepper (Capsicum annuum L.) is often affected by the critical salt stress. Salicylic acid (SA) can improve plants' stress tolerance by promoting growth and regulating ion absorption and transportation. METHODS AND RESULTS: To uncover the alleviated mechanism of salt stress by SA in pepper, we conducted morphological, physiological, cytological, and transcriptomic analyses under a single SA treatment and NaCl with and without SA pre-treatment for 9 days. Seedlings under NaCl treatment showed yellow shrunken leaves, this tatus were alleviated by NS treatment (NaCl with SA pre-treatment). Compared with plants under NaCl treatment, those in the NS treatment showed reduced lipid peroxidation, and significantly increased contents of chlorophyll and osmotic regulators (proline, soluble sugars). Treatment with SA balanced the Na+/K+ ratio. We conducted transcriptome sequencing and identified differentially expressed genes (DEGs) contributing to alleviation of salt stress by SA in pepper. Besides photosynthesis related genes, GO and KEGG analyses revealed that the DEGs were enriched in 'sequence-specific DNA binding', 'transcription regulator activity' and 'DNA binding transcription factor activity' by GO terms. And our results showed that TFs, such as MYB, bZIP, BBX, AP2/ERF, NAC, etc., probably make a great contribution in the alleviation of salt stress by SA. CONCLUSIONS: These results reveal that SA can improve plants' stress tolerance by balancing ion absorption, gene expression and transcriptional regulation, which provide new ideas and resources for subsequent research on the mechanism of salt tolerance in pepper.

Recent progress in surface-enhanced Raman spectroscopy-based biosensors for the detection of extracellular vesicles.

Extracellular vesicles (EVs) are a type of mediator that enables intercellular communication. Moreover, EVs carry critical molecular information from parental cells, making them ideal biomarkers for clinical screening and diagnosis. Currently, several sensing technologies have been established to sensitively detect EVs. Among them, surface-enhanced Raman spectroscopy (SERS) has become a powerful analytical tool with high sensitivity and low detection limits. In this review, we first cover the biological characteristics of EVs and the principle of SERS amplification. Then, we describe the recent progress in SERS technology applied to detect EVs, including direct label-free methods and indirect labeling strategies, in which substrate fabrication and nanoprobe assembly were emphasized. Furthermore, SERS technology could also be used to characterize or monitor the behavior of programmable EVs. Finally, we discuss the prospects and issues to be addressed for the development of SERS technology for EV analysis.