Genome-wide identification and expression pattern analysis of MIKC-Type MADS-box genes in Chionanthus retusus, an androdioecy plant.

BACKGROUND: The MADS-box gene family is widely distributed in the plant kingdom, and its members typically encoding transcription factors to regulate various aspects of plant growth and development. In particular, the MIKC-type MADS-box genes play a crucial role in the determination of floral organ development and identity recognition. As a type of androdioecy plant, Chionanthus retusus have unique gender differentiation. Manifested as male individuals with only male flowers and female individuals with only bisexual flowers. However, due to the lack of reference genome information, the characteristics of MIKC-type MADS-box genes in C. retusus and its role in gender differentiation of C. retusus remain largely unknown. Therefore, it is necessary to identify and characterize the MADS-box gene family within the genome of the C. retusus. RESULTS: In this study, we performed a genome-wide identification and analysis of MIKC-type MADS-box genes in C. retusus (2n = 2x = 46), utilizing the latest reference genome, and studied its expression pattern in individuals of different genders. As a result, we identified a total of 61 MIKC-type MADS-box genes in C. retusus. 61 MIKC-type MADS-box genes can be divided into 12 subfamilies and distributed on 18 chromosomes. Genome collinearity analysis revealed their conservation in evolution, while gene structure, domains and motif analysis indicated their conservation in structure. Finally, based on their expression patterns in floral organs of different sexes, we have identified that CrMADS45 and CrMADS60 may potentially be involved in the gender differentiation of C. retusus. CONCLUSIONS: Our studies have provided a general understanding of the conservation and characteristics of the MIKC-type MADS-box genes family in C. retusus. And it has been demonstrated that members of the AG subfamily, CrMADS45 and CrMADS60, may play important roles in the gender differentiation of C. retusus. This provides a reference for future breeding efforts to improve flower types in C. retusus and further investigate the role of MIKC-type MADS-box genes in gender differentiation.

The global burden of cataracts and its attributable risk factors in 204 countries and territories: a systematic analysis of the global burden of disease study.

Introduction: The global distribution and trends in the attributable burden of cataract risk have rarely been systematically explored. To guide the development of targeted and accurate cataract screening and treatment strategies, we analyzed the burden of cataract disease attributable to known risk factors. Method: This study utilized detailed cataract data from the Global Burden of Disease e 2019, and we analyzed disability-adjusted life years (DALYs) e each risk factor from 1990 to 2019. Additionally, we calculated estimated annual percentage changes (EAPCs) during the study period. Results: The results revealed that from 1990-2019, the global age-standardized DALYs of e attributable to particulate matter pollution, smoking, high fasting glucose plasma and high BMI showed steady downward trends (1990-2009: EAPC = -0.21 [-0.57 -0.14]); 2000-2009: EAPC = -0.95 [-1.01 -0.89]; 2010-2019: EAPC = -1.41 [-1.8 -1.02]). The age-standardized DALYs and mortality caused by each risk factor were highest in the low-middle sociodemographic index (SDI) region (EAPC = -1.77[(-2.19--1.34)]). The overall disease burden of cataracts is lower in males than in females. When analyzing the EAPCs of cataract disease burden for each risk factor individually, we found that the age-standardized disability-adjusted life years caused by particulate matter pollution and smoking decreased (PMP1990-2009: EAPC = -0.53 [-0.9--0.16]; 2000-2009: EAPC = -1.39 [-1.45--1.32]; 2010-2019: EAPC = -2.27 [-2.75--1.79]; smoking 2000 to 2009: EAPC = -1.51 [-1.6--1.43], 2009 to 2019: EAPC = -1.34 [-1.68--1])), while high fasting plasma glucose and high body mass index increased annually (HFPG1990 to 1999: EAPC = 1.27 [0.89-1.65], 2000 to 2009: EAPC = 1.02 [0.82-1.22], 2010-2019: EAPC = 0.44 [0.19-0.68]; HBMI 1990 to 1999: EAPC = 1.65 [1.37-1.94], 2000 to 2009: EAPC = 1.56 [1.43-1.68], 2010-2019: EAPC = 1.47 [1.18-1.77]). Disscussion: The burden of cataracts caused by ambient particulate matter and smoking is increasing in low, low-middle SDI areas, and specific and effective measures are urgently needed. The results of this study suggest that reducing particulate matter pollution, quitting smoking, controlling blood glucose, and lowering BMI could play important roles in reducing the occurrence of cataracts, especially in older people.

A retrospective study on the analysis of influencing factors of neutropenia in endometrial cancer with adjuvant chemoradiotherapy.

OBJECTIVE: This retrospective study aimed to investigate the factors influencing the occurrence of neutropenia in patients with endometrial cancer (EC) following adjuvant chemoradiotherapy (CRT). METHODS: Retrospective analysis of EC patients who underwent adjuvant CRT from January 2012 to June 2023 in the Department of Gynecology and Oncology of the First Affiliated Hospital of Shandong First Medical University. Neutropenia was defined as an Absolute Neutrophil Count (ANC) of peripheral blood neutrophils below 2 × 109/L. Factors affecting neutropenia in EC patients treated with CRT using Generalized Estimating Equation (GEE), and Logistic regression was used to further analyze the effect of adding radiotherapy to different chemotherapy cycles on neutropenia, so that patients receive optimal adjuvant CRT while the risk of neutropenia is appropriately controlled. RESULTS: A total of 144 patients met the inclusion criteria. They underwent 330 cycles of adjuvant chemotherapy, of whom 96 (66.7%) developed neutropenia, which occurred 140 times. The results of one-way GEE analysis showed that before CRT, White Blood Cell (WBC) (OR = 0.827; 95%CI, 0.701-0.976), ANC (OR = 0.749; 95%CI, 0.586-0.957), Absolute Monocyte Count (AMC) (OR = 0.047; 95%CI, 0.008-0.283), Blood Urea Nitrogen (BUN) (OR = 0.857; 95%CI, 0.741-0.991), platinum and docetaxel (platinum/docetaxel) dosing regimen (OR = 2.284; 95%CI, 1.130-4.618) were associated with neutropenia with adjuvant CRT for EC (p < 0.05), results of multifactorial GEE analysis showed that before adjuvant CRT ANC (OR = 0.552; 95%CI, 0.973-2.231), AMC (OR = 0.047; 95%CI, 0.004-0.052), platinum/docetaxel (OR = 2.437; 95%CI, 1.087-5.464) were an independent influence on neutropenia in adjuvant CRT for EC (p < 0.05). Multifactorial Logistic regression shows addition of radiotherapy to the first cycle of chemotherapy (OR = 4.413; 95%CI, 1.238-18.891) was an independent influence of neutropenia (p < 0.05). CONCLUSIONS: Patients with low pre-CRT ANC and AMC, platinum/docetaxel dosing regimens need to be closely monitored during each cycle of CRT. Also, the concurrent addition of radiotherapy should be avoided during the first cycle of chemotherapy.

Natural products for the treatment of age-related macular degeneration.

BACKGROUND: Age-related macular degeneration (AMD) is a chronic retinal disease that significantly influences the vision of the elderly. PURPOSE: There is no effective treatment and prevention method. The pathogenic process behind AMD is complex, including oxidative stress, inflammation, and neovascularization. It has been demonstrated that several natural products can be used to manage AMD, but systematic summaries are lacking. STUDY DESIGN AND METHODS: PubMed, Web of Science, and ClinicalTrials.gov were searched using the keywords "Biological Products" AND "Macular Degeneration" for studies published within the last decade until May 2023 to summarize the latest findings on the prevention and treatment of age-related macular degeneration through the herbal medicines and functional foods. RESULTS: The eligible studies were screened, and the relevant information about the therapeutic action and mechanism of natural products used to treat AMD was extracted. Our findings demonstrate that natural substances, including retinol, phenols, and other natural products, prevent the development of new blood vessels and protect the retina from oxidative stress in cells and animal models. However, they have barely been examined in clinical studies. CONCLUSION: Natural products could be highly prospective candidate drugs used to treat AMD, and further preclinical and clinical research is required to validate it to control the disease.

Upf2-Mediated Nonsense-Mediated Degradation Pathway Involved in Genetic Compensation of TrpA1 Knockout Mutant Silkworm (Bombyx mori).

Genetic mutations leading to premature termination codons are known to have detrimental effects. Using the Lepidoptera model insect, the silkworm (Bombyx mori), we explored the genetic compensatory response triggered by mutations with premature termination codons. Additionally, we delved into the molecular mechanisms associated with the nonsense-mediated mRNA degradation pathway. CRISPR/Cas9 technology was utilized to generate a homozygous bivoltine silkworm line BmTrpA1-/- with a premature termination. Transcript levels were assessed for the BmTrpA paralogs, BmPyrexia and BmPainless as well as for the essential factors Upf1, Upf2, and Upf3a involved in the nonsense-mediated mRNA degradation (NMD) pathway. Upf2 was specifically knocked down via RNA interference at the embryonic stage. The results comfirmed that the BmTrpA1 transcripts with a 2-base deletion generating a premature termination codon in the BmTrpA1-/- line. From day 6 of embryonic development, the mRNA levels of BmPyrexia, BmPainless, Upf1, and Upf2 were significantly elevated in the gene-edited line. Embryonic knockdown of Upf2 resulted in the suppression of the genetic compensation response in the mutant. As a result, the offspring silkworm eggs were able to hatch normally after 10 days of incubation, displaying a non-diapause phenotype. It was observed that a genetic compensation response does exist in BmTrpA1-/-B. mori. This study presents a novel discovery of the NMD-mediated genetic compensation response in B. mori. The findings offer new insights into understanding the genetic compensation response and exploring the gene functions in lepidopteran insects, such as silkworms.

Risk factors associated with false negative rate of sentinel lymph node biopsy in endometrial cancer: a systematic review and meta-analysis.

Objective: Currently, sentinel lymph node biopsy (SLNB) is increasingly used in endometrial cancer, but the rate of missed metastatic lymph nodes compared to systemic lymph node dissection has been a concern. We conducted a systematic review and meta-analysis to evaluate the false negative rate (FNR) of SLNB in patients with endometrial cancer and to explore the risk factors associated with this FNR. Data sources: Three databases (PubMed, Embase, Web of Science) were searched from initial database build to January 2023 by two independent reviewers. Research eligibility criteria: Studies were included if they included 10 or more women diagnosed with International Federation of Gynecology and Obstetrics (FIGO) stage I or higher endometrial cancer, the study technique used sentinel lymph node localization biopsy, and the reported outcome metrics included false negative and/or FNR. Study appraisal and synthesis methods: Two authors independently reviewed the abstracts and full articles. The FNR and factors associated with FNR were synthesized through random-effects meta-analyses and meta-regression. The results: We identified 62 eligible studies. The overall FNR for the 62 articles was 4% (95% CL 3-5).There was no significant difference in the FNR in patients with high-risk endometrial cancer compared to patients with low-risk endometrial cancer. There was no difference in the FNR for whether frozen sections were used intraoperatively. The type of dye used intraoperatively (indocyanine green/blue dye) were not significantly associated with the false negative rate. Cervical injection reduced the FNR compared with alternative injection techniques. Indocyanine green reduced the FNR compared with alternative Tc-99m. Postoperative pathologic ultrastaging reduced the FNR. Conclusions: Alternative injection techniques (other than the cervix), Tc-99m dye tracer, and the absence of postoperative pathologic ultrastaging are risk factors for a high FNR in endometrial cancer patients who undergo SLNB; therefore, we should be vigilant for missed diagnosis of metastatic lymph nodes after SLNB in such populations. Systematic review registration: http://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023433637.

Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.

OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions. METHODS: Totally 2272 multimodal ultrasound imaging was collected from 198 patients. The ResNet-18 network was employed to predict four molecular subtypes from B-US imaging, CDFI, and SE of patients with different ages. All the images were split into training and testing datasets by the ratio of 80%:20%. The predictive performance on testing dataset was evaluated through 5 metrics including mean accuracy, precision, recall, F1-scores, and confusion matrix. RESULTS: Based on B-US imaging, the test mean accuracy is 74.50%, the precision is 74.84%, the recall is 72.48%, and the F1-scores is 0.73. By combining B-US imaging with CDFI, the results were increased to 85.41%, 85.03%, 85.05%, and 0.84, respectively. With the integration of B-US imaging and SE, the results were changed to 75.64%, 74.69%, 73.86%, and 0.74, respectively. Using images from patients under 40 years old, the results were 90.48%, 90.88%, 88.47%, and 0.89. When images from patients who are above 40 years old, they were changed to 81.96%, 83.12%, 80.5%, and 0.81, respectively. CONCLUSION: Multimodal ultrasound imaging can be used to accurately predict the molecular subtypes of breast lesions. In addition to B-US imaging, CDFI rather than SE contribute further to improve predictive performance. The predictive performance is notably better for patients under 40 years old compared with those who are 40 years old and above.

Causal effect of gut microbiota of Defluviitaleaceae on the clinical pathway of "Influenza-Subacute Thyroiditis-Hypothyroidism".

Introduction: Hypothyroidism has been found to be influenced by gut microbiota. However, it remains unclear which a taxon of gut microbiota plays a key role in this function. Identifying the key bacteria affects hypothyroidism and through what mechanism will be helpful for the prevention of hypothyroidism through specific clinical pathways. Materials and methods: In Study A, 35 families and 130 genera of gut microbiota are used as exposures, with hypothyroidism as the outcome. The causal effect of the gut microbiota on hypothyroidism is estimated through two-sample Mendelian randomization. Combining the results of the two taxonomical levels, key taxa are selected, which in Study B are investigated for their causal association with multiple generally admitted causes of hypothyroidism and their more upstream factors. For validating and revealing the potential mechanism, enrichment analyses of the related genes and interacting transcription factors were performed. Results: In Study A, Defluviitaleaceae (OR: 0.043, 95% CI: 0.005-0.363, P = 0.018)/Defluviitaleaceae_UCG_011 (OR: 0.385, 95% CI: 0.172-0.865, P = 0.021) are significantly causally associated with hypothyroidism at both taxonomical levels. In Study B, Defluviitaleaceae family and Defluviitaleaceae_UCG_011 genus show the causal association with decreased thyroiditis (Family: OR: 0.174, 95% CI: 0.046-0.653, P = 0.029; Genus: OR: 0.139, 95% CI: 0.029-0.664, P = 0.043), decreased subacute thyroiditis (Family: OR: 0.028, 95% CI: 0.004-0.213, P = 0.007; Genus: OR: 0.018, 95% CI: 0.002-0.194, P = 0.013), decreased influenza (Family: OR: 0.818, 95% CI: 0.676-0.989, P = 0.038; Genus: OR: 0.792, 95% CI: 0.644-0.974, P = 0.027), and increased anti-influenza H3N2 IgG levels (Family: OR: 1.934, 95% CI: 1.123-3.332, P = 0.017; Genus: OR: 1.675, 95% CI: 0.953-2.943, P = 0.073). The results of the enrichment analysis are consistent with the findings and the suggested possible mechanisms. Conclusion: Defluviitaleaceae of the gut microbiota displays the probability of causally inhibiting the clinical pathway of "Influenza-Subacute Thyroiditis-Hypothyroidism" and acts as the potential probiotics to prevent influenza, subacute thyroiditis, and hypothyroidism.

RARPKB: a knowledge-guide decision support platform for personalized robot-assisted surgery in prostate cancer.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) has emerged as a pivotal surgical intervention for the treatment of prostate cancer (PCa). However, the complexity of clinical cases, heterogeneity of PCa, and limitations in physician expertise pose challenges to rational decision-making in RARP. To address these challenges, the authors aimed to organize the knowledge of previously complex cohorts and establish an online platform named the RARP knowledge base (RARPKB) to provide reference evidence for personalized treatment plans. MATERIALS AND METHODS: PubMed searches over the past two decades were conducted to identify publications describing RARP. The authors collected, classified, and structured surgical details, patient information, surgical data, and various statistical results from the literature. A knowledge-guided decision-support tool was established using MySQL, DataTable, ECharts, and JavaScript. ChatGPT-4 and two assessment scales were used to validate and compare the platform. RESULTS: The platform comprised 583 studies, 1589 cohorts, 1 911 968 patients, and 11 986 records, resulting in 54 834 data entries. The knowledge-guided decision support tool provide personalized surgical plan recommendations and potential complications on the basis of patients' baseline and surgical information. Compared with ChatGPT-4, RARPKB outperformed in authenticity (100% vs. 73%), matching (100% vs. 53%), personalized recommendations (100% vs. 20%), matching of patients (100% vs. 0%), and personalized recommendations for complications (100% vs. 20%). Postuse, the average System Usability Scale score was 88.88±15.03, and the Net Promoter Score of RARPKB was 85. The knowledge base is available at: http://rarpkb.bioinf.org.cn . CONCLUSIONS: The authors introduced the pioneering RARPKB, the first knowledge base for robot-assisted surgery, with an emphasis on PCa. RARPKB can assist in personalized and complex surgical planning for PCa to improve its efficacy. RARPKB provides a reference for the future applications of artificial intelligence in clinical practice.

Immune cell early activation, apoptotic kinetic, and T-cell functional impairment in domestic pigs after ASFV CADC_HN09 strain infection.

African swine fever (ASF) caused by the African swine fever virus (ASFV) is a fatal and highly contagious disease of domestic pigs characterized by rapid disease progression and death within 2 weeks. How the immune cells respond to acute ASFV infection and contribute to the immunopathogenesis of ASFV has not been completely understood. In this study, we examined the activation, apoptosis, and functional changes of distinct immune cells in domestic pigs following acute infection with the ASFV CADC_HN09 strain using multicolor flow cytometry. We found that ASFV infection induced broad apoptosis of DCs, monocytes, neutrophils, and lymphocytes in the peripheral blood of pigs over time. The expression of MHC class II molecule (SLA-DR/DQ) on monocytes and conventional DCs as well as CD21 expression on B cells were downregulated after ASFV infection, implying a potential impairment of antigen presentation and humoral response. Further examination of CD69 and ex vivo expression of IFN-γ on immune cells showed that T cells were transiently activated and expressed IFN-γ as early as 5 days post-infection. However, the capability of T cells to produce cytokines was significantly impaired in the infected pigs when stimulated with mitogen. These results suggest that the adaptive cellular immunity to ASFV might be initiated but later overridden by ASFV-induced immunosuppression. Our study clarified the cell types that were affected by ASFV infection and contributed to lymphopenia, improving our understanding of the immunopathogenesis of ASFV.

Effect of different interventions on the treatment of high-risk human papillomavirus infection: a systematic review and network meta-analysis.

Background: Persistent infection with high-risk human papillomavirus (HR-HPV) can lead to cervical intraepithelial neoplasia and cancer. At present, there is no medication that specifically targets HR-HPV infection. Objective: This study aimed to evaluate the effectiveness of different interventions in promoting HR-HPV regression using a MeSH meta-analysis method. Methods: A search for randomized controlled trials (RCTs) reporting different interventions for the treatment of HR-HPV infection included PubMed, Web of Science, Embase and Cochrane Library from the inception of the databases to March 8, 2023. Two researchers independently screened the articles, extracted data, and evaluated the quality. The literature that met the inclusion criteria was selected, the quality and risk of bias of the included studies were assessed according to the Cochrane 5.1 manual, and NMA was performed using Stata 16.0. The area under the cumulative ranking probability graph (SUCRA) represented the probability that each treatment would be the best intervention. Results: Nine studies involving 961 patients and 7 treatment options were included in the analysis. The results of the network meta-analysis indicated the following rank order in terms of promoting HR-HPV conversion: Anti-HPV biological dressing > vaginal gel > imiquimod > REBACIN® > interferon > probiotics > observation/placebo > Polyphenon E. Conclusion: Anti-HPV biological dressing treatment was found to be significantly effective in promoting HR-HPV conversion. However, further validation of the findings is necessary due to the limited number and quality of studies included in the analysis. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023413917.

An artificial intelligence method for predicting postoperative urinary incontinence based on multiple anatomic parameters of MRI.

Background: Deep learning methods are increasingly applied in the medical field; however, their lack of interpretability remains a challenge. Captum is a tool that can be used to interpret neural network models by computing feature importance weights. Although Captum is an interpretable model, it is rarely used to study medical problems, and there is a scarcity of data regarding MRI anatomical measurements for patients with prostate cancer after undergoing Robotic-Assisted Radical Prostatectomy (RARP). Consequently, predictive models for continence that use multiple types of anatomical MRI measurements are limited. Methods: We explored the energy efficiency of deep learning models for predicting continence by analyzing MRI measurements. We analyzed and compared various statistical models and provided reference examples for the clinical application of interpretable deep-learning models. Patients who underwent RARP at our institution between July 2019 and December 2020 were included in this study. A series of clinical MRI anatomical measurements from these patients was used to discover continence features, and their impact on continence was primarily evaluated using a series of statistical methods and computational models. Results: Age and six other anatomical measurements were identified as the top seven features of continence by the proposed model UINet7 with an accuracy of 0.97, and the first four of these features were also found by primary statistical analysis. Conclusions: This study fills the gaps in the in-depth investigation of continence features after RARP due to the limitations of clinical data and applicable models. We provide a pioneering example of the application of deep-learning models to clinical problems. The interpretability analysis of deep learning models has the potential for clinical applications.

Efficient Fabrication of TPU/MXene/Tungsten Disulfide Fibers with Ultra-Fast Response for Human Respiratory Pattern Recognition and Disease Diagnosis via Deep Learning.

Flexible wearable pressure sensors have received increasing attention as the potential application of flexible wearable devices in human health monitoring and artificial intelligence. However, the complex and expensive process of the conductive filler has limited its practical production and application on a large scale to a certain extent. This study presents a kind of piezoresistive sensor by sinking nonwoven fabrics (NWFs) into tungsten disulfide (WS2) and Ti3C2Tx MXene solutions. With the advantages of a simple production process and practicality, it is conducive to the realization of large-scale production. The assembled flexible pressure sensor exhibits high sensitivity (45.81 kPa-1), wide detection range (0-410 kPa), fast response/recovery time (18/36 ms), and excellent stability and long-term durability (up to 5000 test cycles). Because of the high elastic modulus of MXene and the synergistic effect between WS2 and MXene, the detection range and sensitivity of the piezoresistive pressure sensor are greatly improved, realizing the stable detection of human motion status in all directions. Meanwhile, its high sensitivity at low pressure allows the sensor to accurately detect weak signals such as weak airflow and wrist pulses. In addition, combining the sensor with deep-learning makes it easy to recognize human respiratory patterns with high accuracy, demonstrating its potential impact in the fields of ergonomics and low-cost flexible electronics.

Internet of things sports information collection and sports action simulation based on cloud computing data platform.

In recent years, cloud computing technology has shown exponential growth, and the upgrading of hardware and the improvement of computing performance have brought significant changes to the Internet of Things industry. With the changes of the times and the emergence of many new demands, data platforms under cloud computing platforms must make corresponding changes according to the new demands. Among them, the construction of cross regional data centers is particularly important, especially in commercial environments. How to reduce the cost of data centers on cloud computing platforms while ensuring business quality has become a crucial issue. Based on the above situation, this article has optimized the bandwidth cost of the data center and solved the problem of big data transmission based on delayed big data windows and multi delay windows. A mathematical model for optimizing bandwidth cost under multi delay windows is proposed. This article also studied sports action simulation, which plays an important role in sports research, film animation, and virtual reality. Simulation actions are usually implemented based on data capture methods. However, these methods typically do not have interactivity with the environment. To enhance the authenticity and interactive ability of simulation action information collection, this article adopts reinforcement learning method for training and design, and applies a system of functions such as collecting human sports data processing. This article applies cloud computing data platforms and sports information collection to sports action simulation, making progress in the development of sports action simulation.

Triboelectric Nanogenerators Based on Super-Stretchable Conductive Hydrogels with the Assistance of Deep-Learning for Handwriting Recognition.

Nowadays, wearable electronic devices are developing rapidly with the internet of things and human-computer interactions. However, there are problems such as low power, short power supply time, and difficulty in charging, leading to a limited range of practical applications. In this paper, a composite hydrogel composed of polyacrylamide, hydroxypropyl methylcellulose, and MXene (Ti3C2Tx) nanosheets was developed, which formed a stable double-chain structure by hydrogen bonding. The configuration endows the hydrogel with excellent properties, such as high strength, strong stretchability, excellent electrical conductivity, and high strain sensitivity. Based on these characteristics, a flexible multifunctional triboelectric nanogenerator (PHM-TENG) was prepared using the hydrogel as a functional electrode. The nanogenerator can collect biomechanical energy and convert it to 183 V with a maximum power density of 78.3 mW/m2. It is worth noting that PHM-TENG can be applied as a green power source for driving miniature electronics. Also, it can be used as an auto-powered strain sensor that distinguishes letters, enabling monitoring under small strain conditions. This work is anticipated to provide an avenue for the development of new intelligent systems for handwriting recognition.

Genome-wide identification and analysis of the SUPPRESSOR of MAX2 1-LIKE gene family and its interaction with DWARF14 in poplar.

BACKGROUND: Strigolactones (SLs) are important phytohormones that can regulate branch development in plants. Although SUPPRESSOR of MAX2 1-LIKE proteins (SMXLs) play a crucial role in SL signaling transduction, the SMXL gene family has not been well characterized in poplar. RESULTS: In this study, 12 members of the poplar SMXL gene family were identified and phylogenetically classified into four clades. Motif and 3D structural analyses revealed that PtSMXL proteins are structurally very conserved; however, the P-loop NTPase domain at the C-terminal was found to vary substantially among clades. A genomic collinearity analysis indicated that PtSMXL gene family members have expanded during recent genome doubling events in poplar, with all gene pairs subsequently undergoing purifying selection. According to a Cis-element analysis, PtSMXL promoters contain many light-responsive elements. In an expression pattern analysis, all 12 PtSMXL genes displayed tissue-specific expression, especially PtSMXL8a. PtSMXL7b expression was significantly downregulated after axillary bud growth begins. In addition, the expressions of PtSMXL7b and PtSMXL8a were highly induced by 2 µM GR24, a synthetic SL analog, thus suggesting that these genes are involved in SL-regulated axillary bud growth. In a yeast two-hybrid assay, only PtSMXL7b in clade II was able to interact with the SL receptor PtD14a in an SL dependent manner, which indicates that PtSMXL7b may be the functional homolog of D53/SMXL6/7/8 in poplar. Finally, we established its ability to affect axillary bud growth by constructing poplar overexpressing the PtSMXL7b gene. CONCLUSIONS: Our findings may inform future research on the functions of SMXLs in poplar, especially with respect to branch development.

In Situ Polymerized MXene/Polypyrrole/Hydroxyethyl Cellulose-Based Flexible Strain Sensor Enabled by Machine Learning for Handwriting Recognition.

Flexible strain sensors have significant progress in the fields of human-computer interaction, medical monitoring, and handwriting recognition, but they also face many challenges such as the capture of weak signals, comprehensive acquisition of the information, and accurate recognition. Flexible strain sensors can sense externally applied deformations, accurately measure human motion and physiological signals, and record signal characteristics of handwritten text. Herein, we prepare a sandwich-structured flexible strain sensor based on an MXene/polypyrrole/hydroxyethyl cellulose (MXene/PPy/HEC) conductive material and a PDMS flexible substrate. The sensor features a wide linear strain detection range (0-94%), high sensitivity (gauge factor 357.5), reliable repeatability (>1300 cycles), ultrafast response-recovery time (300 ms), and other excellent sensing properties. The MXene/PPy/HEC sensor can detect human physiological activities, exhibiting excellent performance in measuring external strain changes and real-time motion detection. In addition, the signals of English words, Arabic numerals, and Chinese characters handwritten by volunteers measured by the MXene/PPy/HEC sensor have unique characteristics. Through machine learning technology, different handwritten characters are successfully identified, and the recognition accuracy is higher than 96%. The results show that the MXene/PPy/HEC sensor has a significant impact in the fields of human motion detection, medical and health monitoring, and handwriting recognition.

Ultrastretchable, Self-Healing Conductive Hydrogel-Based Triboelectric Nanogenerators for Human-Computer Interaction.

The rapid development of wearable electronic devices and virtual reality technology has revived interest in flexible sensing and control devices. Here, we report an ionic hydrogel (PTSM) prepared from polypropylene amine (PAM), tannic acid (TA), sodium alginate (SA), and MXene. Based on the multiple weak H-bonds, this hydrogel exhibits excellent stretchability (strain >4600%), adhesion, and self-healing. The introduction of MXene nanosheets endows the hydrogel sensor with a high gauge factor (GF) of 6.6. Meanwhile, it also enables triboelectric nanogenerators (PTSM-TENGs) fabricated from silicone rubber-encapsulated hydrogels to have excellent energy harvesting efficiency, with an instantaneous output power density of 54.24 mW/m2. We build a glove-based human-computer interaction (HMI) system using PTSM-TENGs. The multidimensional signal features of PTSM-TENG are extracted and analyzed by the HMI system, and the functions of gesture visualization and robot hand control are realized. In addition, triboelectric signals can be used for object recognition with the help of machine learning techniques. The glove based on PTSM-TENG achieves the classification and recognition of five objects through contact, with an accuracy rate of 98.7%. Therefore, strain sensors and triboelectric nanogenerators based on hydrogels have broad application prospects in man-machine interface, intelligent recognition systems, auxiliary control systems, and other fields due to their excellent stretchable and high self-healing performance.

Controlling the morphology and wavelength of self-assembled coaxial GaAs/Ga(As)Sb/GaAs single quantum-well nanowires.

Antimonide-based ternary III-V nanowires (NWs) provide a tunable bandgap over a wide range, and the GaAsSb material system has prospective applications in the 1.3-1.55 µm spectral range of optical communications. In this paper, GaAs/Ga(As)Sb/GaAs single quantum well (SQW) NWs were grown on Si(111) substrates by molecular beam epitaxy (MBE). In addition, the morphologies and tunable wavelengths of the GaAs/Ga(As)Sb/GaAs SQWs were adjusted by interrupting the Ga droplets and changing the growth temperatures and V/III ratios. The four morphologies of the GaAs/Ga(As)Sb/GaAs SQW NWs were observed by scanning electron microscopy (SEM). The microscale lattice structure related to the incorporation of Sb in GaAs/Ga(As)Sb/GaAs SQWs was studied by Raman spectroscopy. The crystal quality of the GaAs/Ga(As)Sb/GaAs SQW NWs was researched by X-ray diffraction (XRD) and transmission electron microscopy (TEM). In addition, the optical properties of the GaAs/Ga(As)Sb/GaAs SQWs were investigated by photoluminescence (PL) spectroscopy. The PL spectra showed the peak emission wavelength range of ∼818 nm (GaAs) to ∼1628 nm (GaSb) at 10 K. This study provides an approach to enhance the effective control of the morphology, structure and wavelength of quantum well or core-shell NWs.

Self-Powered Nitrogen Dioxide Sensor Based on Pd-Decorated ZnO/MoSe2 Nanocomposite Driven by Triboelectric Nanogenerator.

This paper introduces a high-performance self-powered nitrogen dioxide gas sensor based on Pd-modified ZnO/MoSe2 nanocomposites. Poly(vinyl alcohol) (PVA) nanofibers were prepared by high-voltage electrospinning and tribological nanogenerators (TENGs) were designed. The output voltage of TENG and the performance of the generator at different frequencies were measured. The absolute value of the maximum positive and negative voltage exceeds 200 V. Then, the output voltage of a single ZnO thin-film sensor, Pd@ZnO thin-film sensor and Pd@ZnO/MoSe2 thin-film sensor was tested by using the energy generated by TENG at 5 Hz, when the thin-film sensor was exposed to 1-50 ppm NO2 gas. The experimental results showed that the sensing response of the Pd@ZnO/MoSe2 thin-film sensor was higher than that of the single ZnO film sensor and Pd@ZnO thin-film sensor. The TENG-driven response rate of the Pd@ZnO/MoSe2 sensor on exposure to 50 ppm NO2 gas was 13.8. At the same time, the sensor had good repeatability and selectivity. The synthetic Pd@ZnO/MoSe2 ternary nanocomposite was an ideal material for the NO2 sensor, with excellent structure and performance.