Epicardial adipose tissue volume highly correlates with left ventricular diastolic dysfunction in endogenous Cushing's syndrome.

BACKGROUND: Cushing's syndrome (CS) is associated with increased risk for heart failure, which often initially manifests as left ventricular diastolic dysfunction (LVDD). In this study, we aimed to explore the potential risk factors of LVDD in CS by incorporating body composition parameters. METHODS: A retrospective study was conducted on patients diagnosed with endogenous CS no less than 18 years old. The control group consisted of healthy individuals who were matched to CS patients in terms of gender, age, and BMI. LIFEx software (version 7.3) was applied to measure epicardial adipose tissue volume (EATV) on non-contrast chest CT, as well as abdominal adipose tissue and skeletal muscle mass at the first lumbar vertebral level. Echocardiography was used to evaluate left ventricular (LV) diastolic function. Body compositions and clinical data were examined in relation to early LVDD. RESULTS: A total of 86 CS patients and 86 healthy controls were enrolled. EATV was significantly higher in CS patients compared to control subjects (150.33 cm3 [125.67, 189.41] vs 90.55 cm3 [66.80, 119.84], p < 0.001). CS patients had noticeably increased visceral fat but decreased skeletal muscle in comparison to their healthy counterparts. Higher prevalence of LVDD was found in CS patients based on LV diastolic function evaluated by E/A ratio (p < 0.001). EATV was proved to be an independent risk factor for LVDD in CS patients (OR = 1.015, 95%CI 1.003-1.026, p = 0.011). If the cut-point of EATV was set as 139.252 cm3 in CS patients, the diagnostic sensitivity and specificity of LVDD were 84.00% and 55.60%, respectively. CONCLUSION: CS was associated with marked accumulation of EAT and visceral fat, reduced skeletal muscle mass, and increased prevalence of LVDD. EATV was an independent risk factor for LVDD, suggesting the potential role of EAT in the development of LVDD in CS.

This study explored the potential risk factors of LVDD in endogenous CS by incorporating body composition parameters. EATV was identified as an independent risk factor for LVDD. Targeted therapeutic interventions to reduce excessive cortisol-induced EAT accumulation may be promising to mitigate the risk of LVDD development in patients with CS.

GBA-AAV mitigates sleep disruptions and motor deficits in mice with REM sleep behavior disorder.

Sleep disturbances, including rapid eye movement sleep behavior disorder (RBD), excessive daytime sleepiness, and insomnia, are common non-motor manifestations of Parkinson's disease (PD). Little is known about the underlying mechanisms, partly due to the inability of current rodent models to adequately mimic the human PD sleep phenotype. Clinically, increasing studies have reported that variants of the glucocerebrosidase gene (GBA) increase the risk of PD. Here, we developed a mouse model characterized by sleep-wakefulness by injecting α-synuclein preformed fibronectin (PFF) into the sublaterodorsal tegmental nucleus (SLD) of GBA L444P mutant mice and investigated the role of the GBA L444P variant in the transition from rapid eye movement sleep behavior disorder to PD. Initially, we analyzed spectral correlates of REM and NREM sleep in GBA L444P mutant mice. Importantly, EEG power spectral analysis revealed that GBA L444P mutation mice exhibited reduced delta power during non-rapid eye movement (NREM) sleep and increased theta power (8.2-10 Hz) in active rapid eye movement (REM) sleep phases. Our study revealed that GBA L444P-mutant mice, after receiving PFF injections, exhibited increased sleep fragmentation, significant motor and cognitive dysfunctions, and loss of dopaminergic neurons in the substantia nigra. Furthermore, the over-expression of GBA-AAV partially improved these sleep disturbances and motor and cognitive impairments. In conclusion, we present the initial evidence that the GBA L444P mutant mouse serves as an essential tool in understanding the complex sleep disturbances associated with PD. This model further provides insights into potential therapeutic approaches, particularly concerning α-synuclein accumulation and its subsequent pathological consequences.

Hemoglobin nanoclusters-mediated regulation of KPNA4 in hypoxic tumor microenvironment enhances photodynamic therapy in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly malignant tumor known for its hypoxic environment, which contributes to resistance against the anticancer drug Sorafenib (SF). Addressing SF resistance in HCC requires innovative strategies to improve tumor oxygenation and effectively deliver therapeutics. RESULTS: In our study, we explored the role of KPNA4 in mediating hypoxia-induced SF resistance in HCC. We developed hemoglobin nanoclusters (Hb-NCs) capable of carrying oxygen, loaded with indocyanine green (ICG) and SF, named HPRG@SF. In vitro, HPRG@SF targeted HCC cells, alleviated hypoxia, suppressed KPNA4 expression, and enhanced the cytotoxicity of PDT against hypoxic, SF-resistant HCC cells. In vivo experiments supported these findings, showing that HPRG@SF effectively improved the oxygenation within the tumor microenvironment and countered SF resistance through combined photodynamic therapy (PDT). CONCLUSION: The combination of Hb-NCs with ICG and SF, forming HPRG@SF, presents a potent strategy to overcome drug resistance in hepatocellular carcinoma by improving hypoxia and employing PDT. This approach not only targets the hypoxic conditions that underlie resistance but also provides a synergistic anticancer effect, highlighting its potential for clinical applications in treating resistant HCC.

Spectral-Sensing System for Distinguishing CH3OH and CD3OD.

Spectrally discriminating CH3OH and CD3OD, and even detecting CH3OH contents in the CD3OD solvent, are important yet have not been achieved so far, likely owing to their very similar chemical/physical properties. Herein, dynamic transesterification reactions, which can be achieved via two-step proton transfers, can be signaled via ultraviolet UV-visible (UV/vis) absorption and fluorescence spectroscopies under mild experimental conditions. Introduction of strong electron-withdrawing groups, such as -NO2, to the aromatic ring (benzoic acid moiety or phenol moiety) of carboxylate esters to activate the esters is important for transesterification reactions and is an intriguing method for modulating the selectivity of the spectral response. The rate constant of the transesterification reaction enhanced with increasing the total number of strong electron-withdrawing groups. Furthermore, the rate constants of esters in which substituent(s) are connected to the phenol moiety are higher than those of corresponding esters in which substituent(s) are connected to the benzoic acid moiety. In transesterification systems, added aliphatic amines mainly play two roles: (i) lowering the energy barrier of the first transesterification step via the formation of intermolecular hydrogen bonding in ternary systems and (ii) deprotonating the released 4-nitrophenol in UV/vis absorption spectral systems to generate an UV/vis absorption spectral signal reporter, i.e., nitrophenolate anions. As a result of the methanol-mediated transesterification reaction, spectral-sensing systems can be established for discriminating CH3OH and CD3OD and even detecting low CH3OH contents in the CD3OD solvent, owing to the kinetic isotope effect. This is the first example of spectral recognition between CD3OD and CH3OH.

Short-term skin reactions and changes in stratum corneum following different ways of facial sheet mask usage.

BACKGROUND: The global facial mask market grows steadily at 8.5 % annually. However, prolonged use may lead to skin inflammation. OBJECTIVE: To investigate how various mask types and wearing durations impact skin physiology and aquaporins3 (AQP3) expression in healthy subjects. METHODS: We used a randomized controlled design to investigate the effects of three types of facial masks (pure water, hyaluronan, and bifida ferment lysate) and four different duration(5, 15, 25, and 40 min) on various skin parameters in volunteers, assessing moisture content, transepidermal water loss (TEWL), sebum, corneocyte size, and AQP3 expression before and after mask application, while also evaluating adverse reactions, discomfort, and noncompliance. RESULT: Hydration and TEWL increased at first, then decreased. Sebum increased with all types of masks, particularly after 40 min. Vasodilation and AQP3 expression were linked to mask duration. Corneocyte sizes remained constant. The main adverse reactions were redness (10.71 %, n = 28) and dryness (57.14 %, n = 28), especially with pure water masks lasting over 25 min. CONCLUSION: Short-term use of facial sheet masks (<25 min) benefits skin with improved hydration, reduced redness, and AQP3 activation, while prolonged use can lead to increased dryness and redness.

Predicting the potentially exacerbation of severe viral pneumonia in hospital by MuLBSTA score joint CD4 + and CD8 +T cell counts: construction and verification of risk warning model.

PURPOSE: This study mainly focuses on the immune function and introduces CD4+, CD8+ T cells and their ratios based on the MuLBSTA score, a previous viral pneumonia mortality risk warning model, to construct an early warning model of severe viral pneumonia risk. METHODS: A retrospective single-center observational study was operated from January 2021 to December 2022 at the People's Hospital of Liangjiang New Area, Chongqing, China. A total of 138 patients who met the criteria for viral pneumonia in hospital were selected and their data, including demographic data, comorbidities, laboratory results, CT scans, immunologic and pathogenic tests, treatment regimens, and clinical outcomes, were collected and statistically analyzed. RESULTS: Forty-one patients (29.7%) developed severe or critical illness. A viral pneumonia severe risk warning model was successfully constructed, including eight parameters: age, bacterial coinfection, CD4+, CD4+/CD8+, multiple lung lobe infiltrations, smoking, hypertension, and hospital admission days. The risk score for severe illness in patients was set at 600 points. The model had good predictive performance (AUROC = 0.94397), better than the original MuLBSTA score (AUROC = 0.8241). CONCLUSION: A warning system constructed based on immune function has a good warning effect on the risk of severe conversion in patients with viral pneumonia.

Janus structure hydrogels: recent advances in synthetic strategies, biomedical microstructure and (bio)applications.

Janus structure hydrogels (JSHs) are novel materials. Their primary fabrication methods and various applications have been widely reported. JSHs are primarily composed of Janus particles (JNPs) and polysaccharide components. They exhibit two distinct physical or chemical properties, generating intriguing characteristics due to their asymmetric structure. Normally, one side (adhesive interface) is predominantly constituted of polysaccharide components, primarily serving excellent adhesion. On the other side (functional surface), they integrate diverse functionalities, concurrently performing a plethora of synergistic functions. In the biomedical field, JSHs are widely applied in anti-adhesion, drug delivery, wound healing, and other areas. It also exhibits functions in seawater desalination and motion sensing. Thus, JSHs hold broad prospects for applications, and they possess significant research value in nanotechnology, environmental science, healthcare, and other fields. Additionally, this article proposes the challenges and future work facing these fields.

Genome-wide identification of JAZ gene family in sugarcane and function analysis of ScJAZ1/2 in drought stress response and flowering regulation.

The JASMONATE ZIM DOMAIN (JAZ) proteins are a key inhibitors of the jasmonic acid (JA) signaling pathway that play an important role in the regulation of plant growth and development and environmental stress responses. However, there is no systematic identification and functional analysis of JAZ gene family members in sugarcane. In this study, a total of 49 SsJAZ genes were identified from the wild sugarcane species Saccharum spontaneum genome that were unevenly distributed on 13 chromosomes. Phylogenetic analysis showed that all SsJAZ members can be divided into six groups, and most of the SsJAZ genes contained photoreactive and ABA-responsive elements. RNA-seq analysis revealed that SsJAZ1-1/2/3/4 and SsJAZ7-1 were significantly upregulated under drought stress. The transcript level of ScJAZ1 which is the homologous gene of SsJAZ1 in modern sugarcane cultivars was upregulated by JA, PEG, and abscisic acid (ABA). Moreover, ScJAZ1 can interact with three other JAZ proteins to form heterodimers. The spatial and temporal expression analysis showed that SsJAZ2-1/2/3/4 were highly expressed in different tissues and growth stages and during the day-night rhythm between 10:00 and 18:00. Overexpression of ScJAZ2 in Arabidopsis accelerated flowering through activating the expression of AtSOC1, AtFT, and AtLFY. Moreover, the transcription level of ScJAZ2 was about 30-fold in the early-flowering sugarcane variety than that of the non-flowering variety, indicating ScJAZ2 positively regulated flowering. This first systematic analysis of the JAZ gene family and function analysis of ScJAZ1/2 in sugarcane provide key candidate genes and lay the foundation for sugarcane breeding.

A 2-order additive fuzzy measure identification method based on hesitant fuzzy linguistic interaction degree and its application in credit assessment.

To reflect both fuzziness and hesitation in the evaluation of interactivity between attributes in the identification process of 2-order additive fuzzy measure, this work uses the hesitant fuzzy linguistic term set (HFLTS) to describe and depict the interactivity between attributes. Firstly, the interactivity between attributes is defined by the supermodular game theory. According to this definition, a linguistic term set is established to characterize the interactivity between attributes. Under the linguistic term set, the experts employ linguistic expressions generated by context-free grammar to qualitatively describe the interactivity between attributes. Secondly, through the conversion function, the linguistic expressions are transformed into the hesitant fuzzy linguistic term sets (HFLTSs). The individual evaluation results of all experts were further aggregated with the defined hesitant fuzzy linguistic weighted power average operator (HFLWPA). Thirdly, based on the standard Euclidean distance formula of the hesitant fuzzy linguistic elements (HFLEs), the hesitant fuzzy linguistic interaction degree (HFLID) between attributes is defined and calculated by constructing a piecewise function. As a result, a 2-order additive fuzzy measure identification method based on HFLID is proposed. Based on the proposed method, using the Choquet fuzzy integral as nonlinear integration operator, a multi-attribute decision making (MADM) process is then presented. Taking the credit assessment of the big data listed companies in China as an application example, the analysis results of application example prove the feasibility and effectiveness of the proposed method. This work successfully reflects both the fuzziness and hesitation in evaluating the interactivity between attributes in the identification process of 2-order additive fuzzy measure, enriches the theoretical framework of 2-order additive fuzzy measure, and expands the applicability and methodology of 2-order additive fuzzy measure in multi-attribute decision making.

Comprehensive analysis of the miRNA-mRNA regulatory network involved in spontaneous recovery of an H2O2-induced zebrafish cataract model.

OBJECTIVE: To identify the hub miRNAs and mRNAs contributing to the spontaneous recovery of an H2O2-induced zebrafish cataract model. METHODS: Zebrafishes were divided into three groups, i.e., Group A, which included normal control fish (day 0), and Groups B and C, where fish were injected with 2.5% hydrogen peroxide into the anterior chamber and reared for 14 and 30 days, respectively. Fish eyes were examined by stereomicroscope photography and optical coherence tomography (OCT). RNA profiles of fish lenses were detected by RNA sequencing. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs) were identified among three groups. The DEGs and DEmiRs, which changed in opposite positions between "B vs. A" and "C vs. B" were defined as ODGs (opposite positions changed DEGs) and ODmiRs (opposite positions changed DEmiRs). Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) analysis were carried out by R language. The protein-protein interaction network (PPI) was constructed using STRING. Potential targets of miRNAs were obtained using miRanda. miRNA-mRNA networks were constructed by Cytoscape. RESULTS: The fish lens opacity formed on day 14 and recovered to transparent on day 30 after injection. Compared to group B, 1366 DEGs and 54 DEmiRs were identified in group C. "C vs. B" DEGs were enriched in gene clusters related to development and oxidative phosphorylation. Target genes of DEmiRs were enriched in clusters such as development and cysteine metabolism. Among three groups, 786 ODGs and 27 ODmiRs were identified, and 480 ODGs were predicted as targets of ODmiRs. Target ODGs were enriched in pathways related to methionine metabolism, ubiquitin, sensory system development, and structural constituents of the eye lens. In addition, we established an ODmiRs-ODGs regulation network. CONCLUSION: We identified several hub mRNAs and altered miRNAs in the formation and reversal of zebrafish cataracts. These hub miRNAs/mRNAs could be potential targets for the non-surgical treatment of ARC.

Biological signatures of the International Prognostic Index in diffuse large B-cell lymphoma.

ABSTRACT: Diffuse large B-cell lymphoma (DLBCL) is a highly aggressive subtype of lymphoma with clinical and biological heterogeneity. The International Prognostic Index (IPI) shows great prognostic capability in the era of rituximab, but the biological signatures of IPI remain to be discovered. In this study, we analyzed the clinical data in a large cohort of 2592 patients with newly diagnosed DLBCL. Among them, 1233 underwent DNA sequencing for oncogenic mutations, and 487 patients underwent RNA sequencing for lymphoma microenvironment (LME) alterations. Based on IPI scores, patients were categorized into 4 distinct groups, with 5-year overall survival of 41.6%, 55.3%, 71.7%, and 89.7%, respectively. MCD-like subtype was associated with age of >60 years, multiple extranodal involvement, elevated serum lactate dehydrogenase (LDH), and IPI scores ranging from 2 to 5, whereas ST2-like subtype showed an opposite trend. Patients with EZB-like MYC+ and TP53Mut subtypes exhibited poor clinical outcome independent of the IPI; integrating TP53Mut into IPI could better distinguish patients with dismal survival. The EZB-like MYC-, BN2-like, N1-like, and MCD-like subtypes had inferior prognosis in patients with IPI scores of ≥2, indicating necessity for enhanced treatment. Regarding LME categories, the germinal center-like LME was more prevalent in patients with normal LDH and IPI scores of 0 to 1. The mesenchymal LME served as an independent protective factor, whereas the germinal center-like, inflammatory, and depleted LME categories correlated with inferior prognosis for IPI scores of 2 to 5. In summary, our work explored the biological signatures of IPI, thus providing useful rationale for future optimization of the IPI-based treatment strategies with multi-omics information in DLBCL.

Toxicity of common biocides used in aquaculture to embryos and larvae of Brachymystax tsinlingensis Li.

Brachymystax tsinlingensis Li is a threatened fish species endemic to China. With the problems of environmental factors and seeding breeding diseases, it is important to further improve the efficiency of seeding breeding and the basis of resource protection. This study investigated the acute toxicity of copper, zinc and methylene blue (MB) on hatching, survival, morphology, heart rate (HR) and stress behaviour of B. tsinlingensis. Eggs (diameter: 3.86 ± 0.07 mm, weight: 0.032 ± 0.004 g) of B. tsinlingensis were selected randomly from artificial propagation and developed from eye-pigmentation-stage embryos to yolk-sac stage larvae (length: 12.40 ± 0.02 mm, weight: 0.03 ± 0.001 g) and exposed to different concentrations of Cu, Zn and MB for 144 h in a series of semi-static toxicity tests. The acute toxicity tests indicated that the 96-h median lethal concentration (LC50 ) values of the embryos and larvae were 1.71 and 0.22 mg l-1 for copper and 2.57 and 2.72 mg l-1 for zinc, respectively, whereas the MB LC50 after 144-h exposure for embryos and larvae were 67.88 and 17.81 mg l-1 , respectively. The safe concentrations of copper, zinc and MB were 0.17, 0.77 and 6.79 mg l-1 for embryos and 0.03, 0.03 and 1.78 mg l-1 for larvae, respectively. Copper, zinc and MB treatments with concentrations greater than 1.60, 2.00 and 60.00 mg l-1 , respectively, led to a significantly low hatching rate and significantly high embryo mortality (P < 0.05), and copper and MB treatments with concentrations greater than 0.2 and 20 mg l-1 led to significantly high larvae mortality (P < 0.05). Exposure to copper, zinc and MB resulted in developmental defects, including spinal curvature, tail deformity, vascular system anomalies and discolouration. Moreover, copper exposure significantly reduced the HR of larvae (P < 0.05). The embryos exhibited an obvious change in behaviour, converting from the normal behaviour of emerging from the membrane head first to emerging tail first, with probabilities of 34.82%, 14.81% and 49.07% under copper, zinc and MB treatments, respectively. The results demonstrated that the sensitivity of yolk-sac larvae to copper and MB was significantly higher than that of embryos (P < 0.05) and that B. tsinlingensis embryos or larvae might be more resistant to copper, zinc and MB than other members of the Salmonidae family, which benefits their resource protection and restoration.

Confined In-Situ Encapsulation of Co/C Composites with Increased Heterogeneous Interface Polarization for Enhanced Electromagnetic Performance.

It is an urgent problem to realize reliable microwave absorption materials (MAMs) with low density. To address this issue, a series of controlled experiments w ere carried out, which indicated that the tubular structure enables excellent microwave absorption properties with a lower powder filling rate. This performance is attributable to the combined dielectric and magnetic loss mechanisms provided by Co/C and the interface polarization facilitated by multiple heterogeneous interfaces. Particularly, Co@C nanotubes, benefiting from the enhanced heterointerface polarization due to their abundant specific surface area and the reduced electron migration barrier induced by their 1D stacked structure, effectively achieved a dual enhancement of dielectric loss and polarization loss at lower powder filling ratios. Furthermore, the magnetic coupling effect of magnetic nanoparticle arrays in tubular structures is demonstrated by micromagnetic simulation, which have been few reported elsewhere. These propertied enable Co@C nanotubes to achieve minimum reflection loss and maximum effective absorption broadband values of 61.0 dB and 5.5 GHz, respectively, with a powder filling ratio of 20 wt% and a thickness of 1.94 mm. This study reveals the significance of designing 1D structures in reducing powder filling ratio and matching thickness, providing valuable insights for developing MAMs with different microstructures.

A remaining useful life estimation method based on long short-term memory and federated learning for electric vehicles in smart cities.

In modern society, environmental sustainability is a top priority as one of the most promising entities in the new energy sector. Electric vehicles (EVs) are rapidly gaining popularity due to their promise of better performance and comfort. Above all, they can help address the problem of urban air pollution. Nonetheless, lithium batteries, one of the most essential and expensive components of EVs, have posed challenges, such as battery aging, personal safety, and recycling. Precisely estimating the remaining useful life (RUL) of lithium battery packs can effectively assist in enhancing the personal safety of EVs and facilitating secondary trading and recycling in other industries without compromising safety and reliability. However, the RUL estimation of batteries involves many variables, and the operating conditions of EV batteries are highly dynamic as they change with the environment and the driving style of the users. Many existing methods exist to estimate the RUL based on batteries' state of health (SOH), but only some are suitable for real-world data. There are several difficulties as follows. Firstly, obtaining data about battery usage in the real world takes work. Secondly, most of these estimation models must be more representative and generalized because they are trained on separate data for each battery. Lastly, collecting data for centralized training may lead to a breach of user privacy. In this article, we propose an RUL estimation method utilizing a deep learning (DL) approach based on long short-term memory (LSTM) and federated learning (FL) to predict the RUL of lithium batteries. We refrain from incorporating unmeasurable variables as inputs and instead develop an estimation model leveraging LSTM, capitalizing on its ability to predict time series data. In addition, we apply the FL framework to train the model to protect users' battery data privacy. We verified the results of the model on experimental data. Meanwhile, we analyzed the model on actual data by comparing its mean absolute and relative errors. The comparison of the training and prediction results of the three sets of experiments shows that the federated training method achieves higher accuracy in predicting battery RUL compared to the centralized training method and another DL method, with solid training stability.

A fusion of VGG-16 and ViT models for improving bone tumor classification in computed tomography.

Background and Objective: Bone tumors present significant challenges in orthopedic medicine due to variations in clinical treatment approaches for different tumor types, which includes benign, malignant, and intermediate cases. Convolutional Neural Networks (CNNs) have emerged as prominent models for tumor classification. However, their limited perception ability hinders the acquisition of global structural information, potentially affecting classification accuracy. To address this limitation, we propose an optimized deep learning algorithm for precise classification of diverse bone tumors. Materials and Methods: Our dataset comprises 786 computed tomography (CT) images of bone tumors, featuring sections from two distinct bone species, namely the tibia and femur. Sourced from The Second Affiliated Hospital of Fujian Medical University, the dataset was meticulously preprocessed with noise reduction techniques. We introduce a novel fusion model, VGG16-ViT, leveraging the advantages of the VGG-16 network and the Vision Transformer (ViT) model. Specifically, we select 27 features from the third layer of VGG-16 and input them into the Vision Transformer encoder for comprehensive training. Furthermore, we evaluate the impact of secondary migration using CT images from Xiangya Hospital for validation. Results: The proposed fusion model demonstrates notable improvements in classification performance. It effectively reduces the training time while achieving an impressive classification accuracy rate of 97.6%, marking a significant enhancement of 8% in sensitivity and specificity optimization. Furthermore, the investigation into secondary migration's effects on experimental outcomes across the three models reveals its potential to enhance system performance. Conclusion: Our novel VGG-16 and Vision Transformer joint network exhibits robust classification performance on bone tumor datasets. The integration of these models enables precise and efficient classification, accommodating the diverse characteristics of different bone tumor types. This advancement holds great significance for the early detection and prognosis of bone tumor patients in the future.

Genome-wide identification of GTE family proteins in sugarcane (Saccharum spontaneum) reveals that SsGTEL3a confers drought tolerance.

The bromodomain is a highly conserved protein domain that specifically binds to acetylated lysine residues in histones, thereby activating transcription of target genes. Although some progress in Global Transcription Factor Group E (GTE) has been achieved in numerous animals and a few plant species, no systematic analysis of GTE gene families has been reported yet in sugarcane. In our study, 37 GTE and GTE-Like (GTEL) genes were characterized in the Saccharum spontaneum. All SsGTE/SsGTEL members were heterogeneously located on all chromosomes of the sugarcane genome and divided into five groups. Transcriptome data showed that SsGTEL3a was expressed at significantly higher levels under drought stress in drought-resistant varieties than in drought-sensitive varieties. Moreover, the overexpression of SsGTEL3a significantly improved the drought tolerance in Arabidopsis through improving the scavenging ability of reactive oxygen species. Additionally, an interaction between ScFAR1 and SsGTEL3a was identified, with ScFAR1 showing a positive response to drought stress in bacterium. In summary, this systematic analysis of GTE gene family in sugarcane and functional research of SsGTEL3a broadened deeper insight into their evolutionary dynamics and functional properties and provided new candidate genes for drought-resistant molecular breeding of sugarcane.

Engineered exosomes for tissue regeneration: from biouptake, functionalization and biosafety to applications.

Exosomes are increasingly recognized as important effector molecules that regulate intercellular signaling pathways. Notably, certain types of exosomes can induce therapeutic responses, including cell proliferation, angiogenesis, and tissue repair. The use of exosomes in therapy is a hot spot in current research, especially in regenerative medicine. Despite the therapeutic potential, problems have hindered their success in clinical applications. These shortcomings include low concentration, poor targeting and limited loading capability. To fully realize their therapeutic potential, certain modifications are needed in native exosomes. In the present review, we summarize the exosome modification and functionalization strategies. In addition, we provide an overview of potential clinical applications and highlight the issues associated with the biosafety and biocompatibility of engineered exosomes in applications.

[Effects of Straw Returning with Lime on SOC and Carbon Pool Management in Acidic Paddy Soil].

Soil acidification and low SOC are the main limiting factors in acidic paddy soils. Straw returning with lime is an effective measure to alleviate soil acidification and improve soil fertility; however, its interaction effects on SOC and carbon pool management are still unclear. To investigate the impact of straw returning with lime on the organic carbon pool of acidic paddy soil, field experiments were conducted on acidic paddy soil in Baiyun District and Huiyang District of Guangdong Province. The changes in soil total organic carbon (TOC), water-soluble organic carbon (DOC), active organic carbon (LOC), particulate organic carbon (POC), microbial biomass carbon (MBC), carbon pool index (CPI), stable organic carbon (IOC), carbon pool activity (L), carbon pool activity index (CPAI), and carbon pool management index (CPMI) were analyzed under three treatments (CK, conventional fertilization; RS, straw returning+conventional fertilization; RS+L straw returning with lime+conventional fertilization). The results demonstrated that compared with that in CK, the TOC, LOC, POC, and MBC in the RS+L treatment were significantly increased by 10.24%-17.79%, 34.49%-44.37%, 19.27%-23.59%, and 33.36%-43.26%, respectively (P<0.05). Compared with that in CK, the RS+L treatment significantly increased the DOC content during the early growth stage (15-45 days after transplanting) of rice (P<0.05) but had no significant influence on the DOC content during the late growth stage of rice. Compared with that in RS, the TOC, LOC, POC, and MBC in the RS+L treatment were increased by 2.15%-6.95%, 1.17%-17.90%, 4.27%-8.65%, and 12.99%-14.53%, respectively. Compared with that in CK, the RS+L treatment significantly increased IOC and CPI by 8.32%-15.57% and 14.00%-20.00%, respectively (P<0.05). Compared with that in the CK treatment, the RS treatment significantly increased CPI by 14.00%-18.00% (P<0.05). No significant differences in L, CPAI, or CPMI were detected among the different treatments. The soil pH in the RS+L treatment was significantly higher than that in the CK treatment (P<0.05). No significant differences in rice yield were detected among the different treatments. Principal component analysis demonstrated that rice yield was primarily correlated with DOC, LOC, CPAI, and CPMI but its contribution to SOC and carbon pool management index was low. Principal component analysis also indicated that straw returning with lime could improve soil pH and nutrient contents of acidic paddy soil, driving the formation and accumulation of organic carbon fraction such as MBC and POC, thus boosting the increase in SOC. In conclusion, straw returning with lime is beneficial to the accumulation of MBC, POC, LOC, and IOC in acidic paddy soil to improve the content and stability of soil total organic carbon, which is an effective way to improve the carbon sequestration of acidic paddy soil.