Deciphering the role of miRNA-134 in the pathophysiology of depression: A comprehensive review.

This study summarizes the significance of microRNA-134 (miRNA-134) in the pathophysiology, diagnosis, and treatment of depression, a disease still under investigation due to its complexity. miRNA-134 is an endogenous short non-coding RNA that can bind to the 3' untranslated region (3'UTR) of miRNA-134, inhibiting gene translation and showing great potential in the regulation of mood, synaptic plasticity, and neuronal function. This study included 15 articles retrieved from four English-language databases: PubMed, Embase, The Cochrane Library, and Web of Science, and three Chinese literature databases: CNKI, Wanfang, and Chinese Science and Technology Periodical Database (VIP).We evaluated each of the 15 articles using the Critical Appraisal Skills Program (CASP) tool.The standard integrates analyzes of genomic, transcriptomic, neuroimaging, and behavioral data analyses related to miRNA-134 and depression. A multidimensional framework based on standardized criteria was used for quality assessment. The main findings indicate that miRNA-134 significantly affects synaptic plasticity and neurotransmitter regulation, in particular the synthesis and release of serotonin and dopamine. miRNA-134 shows high sensitivity and specificity as a biomarker for the diagnosis of depression and has therapeutic potential for the targeted treatment of depression. miRNA-134 plays a crucial role in the pathogenesis of depression, providing valuable insights for early diagnosis and the development of targeted therapeutic strategies. This work highlights the potential of miRNA-134 as a focal point for advancing personalized medicine approaches for depression.

TCRcost: a deep learning model utilizing TCR 3D structure for enhanced of TCR-peptide binding.

Introduction: Predicting TCR-peptide binding is a complex and significant computational problem in systems immunology. During the past decade, a series of computational methods have been developed for better predicting TCR-peptide binding from amino acid sequences. However, the performance of sequence-based methods appears to have hit a bottleneck. Considering the 3D structures of TCR-peptide complexes, which provide much more information, could potentially lead to better prediction outcomes. Methods: In this study, we developed TCRcost, a deep learning method, to predict TCR-peptide binding by incorporating 3D structures. TCRcost overcomes two significant challenges: acquiring a sufficient number of high-quality TCR-peptide structures and effectively extracting information from these structures for binding prediction. TCRcost corrects TCR 3D structures generated by protein structure tools, significantly extending the available datasets. The main and side chains of a TCR structure are separately corrected using a long short-term memory (LSTM) model. This approach prevents interference between the chains and accurately extracts interactions among both adjacent and global atoms. A 3D convolutional neural network (CNN) is designed to extract the atomic features relevant to TCR-peptide binding. The spatial features extracted by the 3DCNN are then processed through a fully connected layer to estimate the probability of TCR-peptide binding. Results: Test results demonstrated that predicting TCR-peptide binding from 3D TCR structures is both efficient and highly accurate with an average accuracy of 0.974 on precise structures. Furthermore, the average accuracy on corrected structures was 0.762, significantly higher than the average accuracy of 0.375 on uncorrected original structures. Additionally, the average root mean square distance (RMSD) to precise structures was significantly reduced from 12.753 Å for predicted structures to 8.785 Å for corrected structures. Discussion: Thus, utilizing structural information of TCR-peptide complexes is a promising approach to improve the accuracy of binding predictions.

Epigenetic changes driven by environmental pollutants in lung carcinogenesis: a comprehensive review.

Lung cancer remains the leading cause of cancer-related mortality globally, with environmental pollutants identified as significant risk factors, especially for nonsmokers. The intersection of these pollutants with epigenetic mechanisms has emerged as a critical area of interest for understanding the etiology and progression of lung cancer. Epigenetic changes, including DNA methylation, histone modifications, and non-coding RNAs, can induce alterations in gene expression without affecting the DNA sequence and are influenced by environmental factors, contributing to the transformation of normal cells into malignant cells. This review assessed the literature on the influence of environmental pollutants on lung cancer epigenetics. A comprehensive search across databases such as PubMed, Web of Science, Cochrane Library, and Embase yielded 3,254 publications, with 22 high-quality papers included for in-depth analysis. These studies demonstrated the role of epigenetic markers, such as DNA methylation patterns of genes like F2RL3 and AHRR and alterations in the miRNA expression profiles, as potential biomarkers for lung cancer diagnosis and treatment. The review highlights the need to expand research beyond homogenous adult male groups typically found in high-risk occupational environments to broader population demographics. Such diversification can reduce biases and enhance the relevance of findings to various clinical contexts, fostering the development of personalized preventive and therapeutic measures. In conclusion, our findings underscore the potential of innovative epigenetic therapies, such as DNA demethylating drugs and histone modification agents, to counter environmental toxins' carcinogenic effects. The growing interest in miRNA therapies and studies aiming to correct aberrant methylation patterns indicate significant strides toward better lung cancer management and a healthier future for global communities.

Enhancement of extraction efficiency and functional properties of chickpea protein isolate using pulsed electric field combined with ultrasound treatment.

Chickpea protein isolate (CPI) is a promising dietary protein with the advantages of low allergenicity, easy digestion and balanced composition of essential amino acids. However, due to the thick skin of chickpeas, the extraction of CPI is challenging, resulting in lower efficiency of the alkaline extraction-isoelectric precipitation (AE-IEP) method. Therefore, the present study investigated the effect of pulsed electric field combined with ultrasound (PEF-US) treatment on the extraction efficiency of CPI and the functional properties was characterized. Parameter optimization was carried out using response surface methodology (RSM), with the following optimized conditions: pulse duration of 87 s, electric field intensity of 0.9 kV/cm, ultrasonic time of 15 min, and ultrasonic power of 325 W. Under the optimized conditions, the yield of CPI after combined (PEF-US) treatment was 13.52 ± 0.13 %, which was a 47.28 % improvement over the AE-IEP method. This yield was better than that obtained with either individual PEF or US treatment. Additionally, the functional properties (solubility, emulsification, and foaming) of CPI were significantly enhanced compared to AE-IEP. However, the stability of emulsification and foaming did not show significant differences among the four methods. The PEF-US method efficiently extracts CPI with excellent functional properties, enabling the production of proteins as desired functional additives in the food industry.

Incidence and Predictors of HBsAg Loss in Paediatric Patients With Chronic Hepatitis B Undergoing Antiviral Treatment.

BACKGROUND AND AIMS: Achieving HBsAg loss is a critical clinical milestone in the management of chronic hepatitis B (CHB) towards the eradication of hepatitis B. However, there are limited researches on the incidence and determinants of HBsAg loss in paediatric CHB patients undergoing antiviral treatment. Therefore, we aimed to analyse the incidence and potential determinants of HBsAg loss in children who suffered from CHB and received antiviral treatment. METHODS: This retrospective cohort study was performed on paediatric patients with progressive CHB who initiated either monotherapy or combination therapy using interferon/peg-interferon and entecavir. We utilised Cox regression models to evaluate the relationships between HBsAg loss and various determining factors. RESULTS: In total of 306 subjects with an average age of 4.99 years (range 1-15) were identified in this study, of whom 200 (65.4%) were male. After a median follow-up of 26 months, HBsAg loss occurred in 135 participants. The accumulated rate of HBsAg loss was 67.8% at the end of the follow-up evaluation. Multivariate Cox regression analysis revealed that older age (HR = 0.84, 95% CI: 0.79-0.90), female sex (HR = 1.61, 95% CI: 1.13-2.30), baseline HBsAg levels (HR = 0.72, 95% CI: 0.62-0.84), HBsAb positivity (HR = 1.77, 95% CI: 1.20-2.59) and serum bilirubin levels (HR = 0.96, 95% CI: 0.92-0.99) were statistically significant predictors of HBsAg loss. CONCLUSION: The incidence of HBsAg loss continues to increase in paediatric patients with CHB after antiviral treatment. Age, sex, baseline HBsAg and bilirubin levels and HBsAb positivity are found to be associated with sustained HBsAg loss.

Reliability of self-reported pubertal development scale for girls in early adolescent: a school population-based study.

OBJECTIVES: The study aimed to evaluate the correlation between self-reported pubertal developmental scale (PDS) and physically assessed Tanner staging by an experienced pediatrician among girls. METHODS: In a school population-based study in Zhongshan, China, we recruited 1,722 girls in grades 1-3 by a multistage stratified cluster random sampling method. Participants completed self-reported PDS questionnaire prior to physical examination. Breast development was evaluated by a female pediatrician combined with ultrasound examination for overweight/obese girls; pubic hair development was evaluated. Otherwise, we tested follicle-stimulating hormone (FSH) and luteinizing hormone (LH) for some participants. RESULTS: We observed a weak association between Tanner-derived composite stage (TDCS) and puberty category scores (PCS) (τ=0.288, p<0.001) among all girls. There was correlation (τ=0.314, p=0.001) between ultrasound-derived composite stage (UDCS) and PCS among overweight/obese girls. Moreover, among overweight/obese girls, PCS was positively correlated with LH (r=0.265, p=0.008), but not FSH (r=0.155, p=0.123), and when the basal LH value was greater than 0.3 mIU/mL, the proportion of PCS stage ≥2 (9/18) was higher than the proportion of TDCS ≥2 (5/18). As for the determination of pubertal onset, when UDCS was used as the gold standard, the specificity of PCS was 0.86 and positive predictive value was 90.00 %. CONCLUSIONS: There was a weak correlation between PCS and TDCS among girls early adolescence. Moreover, among overweight/obese girls, combining hormone values, ultrasonographic stage of breast, and the positive predictive value of PCS, we posit that self-reported PDS might be a more reliable method than TDCS to evaluate pubertal development among overweight/obese girls.

Sargassum pallidum reduces inflammation to exert antidepressant effect by regulating intestinal microbiome and ERK1/2/P38 signaling pathway.

Immune inflammation is one of the main factors in the pathogenesis of depression. It is an effective and active way to find more safe and effective anti-inflammatory depressant drugs from plant drugs. The purpose of this study is to explore the potential of marine plant Sargassum pallidum (Turn).C.Ag. (Haihaozi, HHZ) in the prevention and treatment of depression and to explain the related mechanism. Phytochemical analysis showed that alkaloids, terpenes, and organic acids are the main constituents. In vitro and in vivo activity studies showed the anti-neuroinflammatory and antidepressant effect of Sargassum pallidum, furthermore, confirmed that 7-Hydroxycoumarin, Scoparone, and Kaurenoic Acid are important plant metabolites in Sargasum pallidum for anti-neuroinflammation. Mechanism exploration showed that inhibition of ERK1/2/p38 inflammatory signaling pathway contributing to the antidepressant effect of Sargassum pallidum in reducing intestinal inflammatory levels. This study confirmed the value of Sargassum pallidum and its rich plant metabolites in anti-inflammatory depression, providing a new choice for the follow-up research and development of antidepressant drugs.

Identification and genomic analyses of a Streptococcus suis ST25 strain associated with the first human septicemia in mainland China.

Streptococcus suis (S. suis) is a Gram-positive bacterium and the main culprit behind zoonotic outbreaks, posing a serious threat to public health. The prevalent strains in China are mainly of sequence types (ST) 1 and 7, with few cases of human infections caused by other sequence type being reported. This study presents the first isolation of a ST25 strain from the blood of a septicemic patient. A 57-year-old febrile patient was admitted to a hospital in Hainan of China, diagnosed as septicemia and hepatic dysfunction. A strain of S. suis was isolated from blood culture and confirmed to be serotype 2 and ST25 through 16S rRNA sequencing and whole-genome sequencing, and its genome was further analyzed for gene functions and presence of drug resistance genes. The full-length genome of strain HN28 spans 2,280,124 bp and encodes a total of 2291 proteins. Genes annotated in COG, GO, KEGG, CAZy, and PHl databases accounted for 75.38 %, 69.14 %, 55.35 %, 4.58 %, and 11.87 % of the total predicted proteins, respectively. Virulence factor analysis revealed the presence of seven putative virulence genes in strain HN28. Analysis using the CARD database identified 51 resistance genes in HN28, alongside abundant exocytosis systems. These findings underscore the occurrence of S. suis infections in humans caused by less common ST, emphasizing the need for enhanced epidemiological investigations and monitoring of S. suis infections in the human population.

Pannonibacter tanglangensis sp. nov., a New Species Isolated from Pond Sediment.

Two bacterial strains (XCT-34T and XCT-53) isolated from sediment samples of an artificial freshwater reservoir were analyzed using a polyphasic approach. The two isolates are aerobic, Gram-stain-negative, oxidase-negative, catalase-positive, motile with polar flagella, rod-shaped, and approximately 1.4-3.4 × 0.4-0.9 µm in size. Phylogenetic analyses based on 16S rRNA gene and whole-genome sequences showed that the two strains formed a distinct branch within the evolutionary radiation of the genus Pannonibacter, closest to Pannonibacter carbonis Q4.6T (KCTC 52466). Furthermore, lower than threshold average nucleotide identity values (ANI, 85.7-86.4%) and digital DNA-DNA hybridization values (dDDH, 22.3-30.5%) of the two strains compared to the nearest type strains also confirmed that they represented a novel species. Genomic analyses, including annotation of the KEGG pathways, prediction of the secondary metabolism biosynthetic gene clusters and PHI phenotypes, supported functional inference and differentiation of the strains from the closely related taxa. Results of chemotaxonomic and physiological studies revealed that their distinct phenotypic characteristics distinguished them from existing Pannonibacter species. Thus, the two strains are considered to represent a novel species of Pannonibacter, for which the name of Pannonibacter tanglangensis sp. nov. is proposed, with XCT-34T (= KCTC 82332T = GDMCC 1.1947T) as the respective type strain.

Trajectories of serum HBsAg during treatment and association with HBsAg loss in children with HBeAg-positive chronic hepatitis B: a latent class trajectory analysis.

BACKGROUND: The change of serum hepatitis B surface antigen (HBsAg) during treatment are associated with HBsAg loss. However, little is known about the trajectory patterns of HBsAg in early treatment and their relationship with subsequent HBsAg loss. This study aimed to identify trajectories of HBsAg in children with HBeAg-positive chronic hepatitis B (CHB) and investigate the association between trajectory patterns and HBsAg loss. METHODS: A retrospective study was conducted on 166 treatment-naive children with HBeAg-positive CHB. Latent class trajectory analysis was used to identify trajectory groups of serum HBsAg. Cox proportional hazard model was used to assess the association between HBsAg trajectory groups and HBsAg loss. RESULTS: The median follow-up time was 20.70 (12.54, 34.17) months, and HBsAg loss occurred in 70(42.17%) of all study participants. Using latent class trajectory analysis, HBeAg-positive CHB patients were classified into three trajectory groups: trajectory 1 (sustained stability, 24.70%), trajectory 2 (slow decline, 38.55%), and trajectory 3 (rapid decline, 36.75%), respectively. The median decline levels of HBsAg at the 3-month and 6-month follow-ups were the highest in trajectory 3 (1.08 and 3.28 log10 IU/ml), followed by trajectory 2 (0.27 and 1.26 log10 IU/ml), and no change in trajectory 1. The risk of achieving HBsAg loss was higher in both trajectory 2 (HR, 3.65 [95% CI, 1.70-7.83]) and trajectory 3 (HR, 7.27 [95% CI, 3.01-17.61]), respectively. CONCLUSION: Serum HBsAg levels during early treatment can be classified into distinct trajectory groups, which may serve as an additional predictive indicator for HBsAg loss in HBeAg-positive CHB children.

Carbon emission assessment of lithium iron phosphate batteries throughout lifecycle under communication base station in China.

The demand for lithium-ion batteries has been rapidly increasing with the development of new energy vehicles. The cascaded utilization of lithium iron phosphate (LFP) batteries in communication base stations can help avoid the severe safety and environmental risks associated with battery retirement. This study conducts a comparative assessment of the environmental impact of new and cascaded LFP batteries applied in communication base stations using a life cycle assessment method. It analyzes the influence of battery costs and power structure on carbon emissions reduction. Results indicate: When consuming the same amount of electricity in a cascaded battery system (CBS), LFP batteries with a retirement state of health (SOH) range between 76.5 % and 90.0 % can reduce 30.3 % of the global warming potential (GWP) compared to new batteries. From the perspective of battery costs, when the price ratio of new to old batteries is greater than 31.0 %, the GWP of batteries retired at 70.0 % SOH is higher than that of new batteries. As the proportion of renewable energy sources in the power structure increases, the GWP of new batteries in 2035 is 15.0 % lower than in 2020. For batteries retired at 80.0 % SOH, their GWP decreases by 12.3 % compared to 2020. This study offers a new approach to determining the retirement point for LFP batteries from an environmental perspective, promoting carbon emission reduction throughout the entire battery life cycle and the sustainable development of the transportation sector.

Cell dehydration enables massive production of engineered membrane vesicles with therapeutic functions.

Extracellular vesicles (EVs) have emerged as promising biomaterials for the treatment of different disease. However, only handful types of EVs with clinical transformation potential have been reported to date, and their preparation on a large scale under biosafety-controlled conditions is limited. In this study, we characterize a novel type of EV with promising clinical application potential: dehydration-induced extracellular vesicles (DIMVs). DIMV is a type of micron-diameter cell vesicle that contains more bioactive molecules, such as proteins and RNA, but not DNA, than previously reported cell vesicles. The preparation of DIMV is extraordinarily straightforward, which possesses a high level of biosafety, and the protein utilization ratio is roughly 600 times greater than that of naturally secreted EVs. Additional experiments demonstrate the viability of pre- or post-isolation DIMV modification, including gene editing, nucleic acid encapsulation or surface anchoring, size adjustment. Finally, on animal models, we directly show the biosafety and immunogenicity of DIMV, and investigate its potential application as tumour vaccine or drug carrier in cancer treatment.

Clinical and virological characteristics of coexistent hepatitis B surface antigen and antibody in treatment-naive children with chronic hepatitis B virus infection.

Serological pattern of simultaneous positivity for hepatitis B surface antigen (HBsAg) and antibody against HBsAg (anti-HBs) is considered a specific and atypical phenomenon among patients with chronic hepatitis B virus (HBV) infection, especially in pediatric patients. Unfortunately, there is limited understanding of the clinical and virological characteristics among children having chronic HBV infection and the coexistence of HBsAg and anti-HBs. Hence, our objective was to determine the prevalence of coexistent HBsAg and anti-HBs and to explore the associated clinical and virological features in this patient population. The researchers conducted a retrospective cohort study on the 413 pediatric patients with chronic HBV infection from December 2011 to June 2022. The patients were stratified into two groups based on their anti-HBs status. Demographic, serum biochemical and virological parameters of two group were compared. Of the total 413 enrolled subjects, 94 (22.8%) were tested positive for both HBsAg and anti-HBs. Patients with anti-HBs were younger and demonstrated significantly higher ratio of albumin to globulin (A/G), elevated serum levels of alanine transaminase (ALT), lower ratio of aspartate transaminase (AST)/ALT (AST/ALT) and reduced serum levels of globulin, HBsAg and HBV DNA, Additionally, these patients were more likely to show coexistent HBeAg and anti-HBe when compared to patients without anti-HBs. The results of multivariate logistical analysis revealed that AST/ALT, serum levels of globulin and HBsAg were negatively associated with coexistence of HBsAg and anti-HBs. Our data demonstrated a considerable prevalence of coexisting HBsAg and anti-HBs in pediatric patients. Children with this specific serological pattern were commonly of a younger age, seemly predisposing them to early liver impairment and lower HBV replication activity.

Multi-file dynamic compression method based on classification algorithm in DNA storage.

The exponential growth in data volume has necessitated the adoption of alternative storage solutions, and DNA storage stands out as the most promising solution. However, the exorbitant costs associated with synthesis and sequencing impeded its development. Pre-compressing the data is recognized as one of the most effective approaches for reducing storage costs. However, different compression methods yield varying compression ratios for the same file, and compressing a large number of files with a single method may not achieve the maximum compression ratio. This study proposes a multi-file dynamic compression method based on machine learning classification algorithms that selects the appropriate compression method for each file to minimize the amount of data stored into DNA as much as possible. Firstly, four different compression methods are applied to the collected files. Subsequently, the optimal compression method is selected as a label, as well as the file type and size are used as features, which are put into seven machine learning classification algorithms for training. The results demonstrate that k-nearest neighbor outperforms other machine learning algorithms on the validation set and test set most of the time, achieving an accuracy rate of over 85% and showing less volatility. Additionally, the compression rate of 30.85% can be achieved according to k-nearest neighbor model, more than 4.5% compared to the traditional single compression method, resulting in significant cost savings for DNA storage in the range of $0.48 to 3 billion/TB. In comparison to the traditional compression method, the multi-file dynamic compression method demonstrates a more significant compression effect when compressing multiple files. Therefore, it can considerably decrease the cost of DNA storage and facilitate the widespread implementation of DNA storage technology.

Chemical-Free Recycling of Cathode Material and Aluminum Foil from Waste Lithium-Ion Batteries by Combining Plasma and Ultrasonic Technology.

With the rapid demand for lithium-ion batteries due to the widespread application of electric vehicles, a significant amount of battery electrode pieces requiring urgent treatment are generated during battery production and disposal. The strong bonding caused by the presence of binders makes it challenging to achieve thorough separation between the cathode active materials and Al foil, posing difficulties in efficient battery material recycling. To address this issue, a plasma-ultrasonically combined physical separation method is proposed in this study. This method utilizes plasma-generated excited-state radicals assisted by ultrasonic waves to separate active materials and current collectors. The results indicate that the binders are effectively decomposed under plasma treatment at 13.56 MHz, 100 W, and 10 min in an oxygen atmosphere, resulting in a separation efficiency of 96.8 wt % for the cathode materials. Characterization results demonstrate that the morphology, crystal structure, and chemical composition of the recycled cathode active materials remain unchanged, facilitating subsequent direct restoration and hydrometallurgical recycling. Simultaneously, the Al foil is also completely recycled for subsequent reuse. Compared with traditional methods of separating cathode active materials and aluminum foil, the method proposed in this study has significant economic and environmental potential. It can promote the recycling of battery materials and the development of sustainable transportation.

Low-Complexity 2D-DOD and 2D-DOA Estimation in Bistatic MIMO Radar Systems: A Reduced-Dimension MUSIC Algorithm Approach.

This paper presents a new technique for estimating the two-dimensional direction of departure (2D-DOD) and direction of arrival (2D-DOA) in bistatic uniform planar array Multiple-Input Multiple-Output (MIMO) radar systems. The method is based on the reduced-dimension (RD) MUSIC algorithm, aiming to achieve improved precision and computational efficiency. Primarily, this pioneering approach efficiently transforms the four-dimensional (4D) estimation problem into two-dimensional (2D) searches, thus reducing the computational complexity typically associated with conventional MUSIC algorithms. Then, exploits the spatial diversity of array response vectors to construct a 4D spatial spectrum function, which is crucial in resolving the complex angular parameters of multiple simultaneous targets. Finally, the objective is to simplify the spatial spectrum to a 2D search within a 4D measurement space to achieve an optimal balance between efficiency and accuracy. Simulation results validate the effectiveness of our proposed algorithm compared to several existing approaches, demonstrating its robustness in accurately estimating 2D-DOD and 2D-DOA across various scenarios. The proposed technique shows significant computational savings and high-resolution estimations and maintains high precision, setting a new benchmark for future explorations in the field.

Zinc deficiency deteriorates ovarian follicle development and function by inhibiting mitochondrial function.

Zinc (Zn) is a crucial trace element essential for human growth and development, particularly for reproductive health. Previous research has shown a decrease in serum zinc concentration with age and individuals with conditions such as polycystic ovary syndrome (PCOS) and diabetes mellitus. However, the specific effects of zinc deficiency on the female reproductive system, especially ovarian function, are not fully understood. In our study, we observed a significant reduction in the total number of follicles and mature follicles in the zinc deficiency group. This reduction correlated with decreased level of anti-Mullerian hormone (AMH) and abnormal gene expression affecting hormone secretion regulation. Furthermore, we found that zinc deficiency disrupted mitochondrial dynamics, leading to oxidative stress in the ovaries, which further inhibited autophagy and increased ovarian apoptosis. These changes ultimately resulted in the failure of germinal vesicle breakdown (GVBD) and reduced oocyte quality. Meanwhile, administration of zinc glycine effectively alleviated the oocyte meiotic arrest caused by dietary zinc deficiency. In conclusion, our findings demonstrated that dietary zinc deficiency can affect hormone secretion and follicle maturation by impairing mitochondrial function and autophagy.

Predictive role of early treatment dynamics of HBV RNA and HBcrAg for HBeAg seroconversion in children with chronic hepatitis B.

This study aimed to assess the predictive capacity of emerging serological markers, serum HBV RNA and HBcrAg, for HBeAg seroconversion in children with HBeAg-positive chronic hepatitis B (CHB). Treatment-naïve HBeAg-positive CHB children who admitted to the Liver Disease Center of Hunan Children's Hospital between April 2021 and September 2022 and received treatment with the combined entecavir and interferon-alpha treatment were recruited. Serum HBV RNA and HBcrAg were measured at baseline and Weeks 12, 24, and 48 of treatment. Our study showed that serum HBV RNA (HR = 0.71, 95% CI: 0.56-0.91, p = 0.006), HBcrAg (HR = 0.60, 95% CI: 0.43-0.84, p = 0.003), and HBsAg (HR = 0.49, 95%CI: 0.36-0.69, p < 0.001) at Week 12 were independent predictors of HBeAg seroconversion. ROC curve analysis presented that serum HBV RNA decline value (ΔHBV RNA) at Week 36 and HBcrAg decline value (ΔHBcrAg) at Week 12 (AUC = 0.871, p = 0.003 and AUC = 0.810, p = 0.003, respectively) could effectively predict HBeAg seroconversion. Furthermore, the optimal critical values were determined and the children with ΔHBV RNA > 3.759 log10 copies/mL at Week 36 or ΔHBcrAg >0.350 log10 U/mL at Week 12 more likely to achieve HBeAg seroconversion. The serum HBV RNA and HBcrAg provide new insights into the treatment of CHB in children. Early assessment of serum HBV RNA and HBcrAg during treatment can assist clinical decision-making and optimize individualized therapeutic approaches.

Transcription-related metabolic regulation in grafted lemon seedlings under magnesium deficiency stress.

Magnesium is one of the essential nutrients for plant growth, and plays a pivotal role in plant development and metabolism. Soil magnesium deficiency is evident in citrus production, which ultimately leads to failure of normal plant growth and development, as well as decreased productivity. Citrus is mainly propagated by grafting, so it is necessary to fully understand the different regulatory mechanisms of rootstock and scion response to magnesium deficiency. Here, we characterized the differences in morphological alterations, physiological metabolism and differential gene expression between trifoliate orange rootstocks and lemon scions under normal and magnesium-deficient conditions, revealing the different responses of rootstocks and scions to magnesium deficiency. The transcriptomic data showed that differentially expressed genes were enriched in 14 and 4 metabolic pathways in leaves and roots, respectively, after magnesium deficiency treatment. And the magnesium transport-related genes MHX and MRS2 may respond to magnesium deficiency stress. In addition, magnesium deficiency may affect plant growth by affecting POD, SOD, and CAT enzyme activity, as well as altering the levels of hormones such as IAA, ABA, GA3, JA, and SA, and the expression of related responsive genes. In conclusion, our research suggests that the leaves of lemon grafted onto trifoliate orange were more significantly affected than the roots under magnesium-deficient conditions, further indicating that the metabolic imbalance of scion lemon leaves was more severe.

MI-MZI based distributed optical fiber sensor for location and pattern recognition.

This research addressed the drawbacks of the conventional hybrid structure and processing technique by presenting a novel distributed fiber optic sensor based on a hybrid Michelson and Mach-Zehnder interferometer. The sensor can achieve blind spot free positioning and has a wide response frequency, additionally its structure is not complex. It can obtain two phase signals from each of the two interferometers by using a demodulation method that uses a 3 × 3 optical coupler. To determine the position of the disturbance, we computed cross-correlations on the two signals following basic mathematical techniques. Markov Transition Field was used to transform the phase signals-which had been filtered by a band pass filter-into two-dimensional images. Tagged photos built a dataset, which is then fed into a neural network to identify patterns. Experiments have shown that the frequency response capacity of the structure was verified, and it was able to achieve location within 0-30 km with location errors of ±85 m. In a six-category pattern recognition, the testing set accuracy was 98.74%.