Causal relationship between antihypertensive drugs and Hashimoto's thyroiditis: a drug-target Mendelian randomization study.

Introduction and objectives: Recent studies have indicated a potential association of hypertension with Hashimoto's thyroiditis (HT) and other autoimmune diseases, yet the impact of antihypertensive drugs on HT risk is not well understood. Methods: We employed a drug-target Mendelian randomization approach to investigate the prolonged impact of 9 classes of antihypertensive medications on HT susceptibility in European and Asian populations. Genetic variants close to or within genes associated with the drug targets and systolic blood pressure (SBP) were utilized to mimic the effects of antihypertensive medications. We focused on drugs linked to a lower risk of coronary artery disease for our main analysis. We gathered genetic data on SBP and HT risk from comprehensive genome-wide association studies available for European and Asian groups. For a supplementary analysis, we used expression quantitative trait loci (eQTLs) related to drug target genes as proxies. Results: Our analysis revealed that the use of calcium channel blockers (CCBs) is linked to a reduced risk of HT in both European (OR [95% CI]: 0.96 [0.95 to 0.98] per 1 mmHg decrease in SBP; p = 3.51×10-5) and Asian populations (OR [95% CI]: 0.28 [0.12, 0.66]; p = 3.54×10-3). Moreover, genetically mimicking the use of loop diuretics (OR [95% CI]: 0.94 [0.91, 0.97]; p = 3.57×10-5) and thiazide diuretics (0.98 [0.96, 0.99]; p = 3.83×10-3) showed a significant association with a decreased risk of HT only in European population. These outcomes were confirmed when eQTLs were employed to represent the effects of antihypertensive medications. Conclusion: The study suggests that CCBs and diuretics could potentially reduce the risk of HT in different populations. Additional research is needed to assess the feasibility of repurposing antihypertensive medications for the prevention of HT.

A clinical prediction model for distant metastases of pediatric neuroblastoma: an analysis based on the SEER database.

Background: Patients with distant metastases from neuroblastoma (NB) usually have a poorer prognosis, and early diagnosis is essential to prevent distant metastases. The aim was to develop a machine-learning model for predicting the risk of distant metastasis in patients with neuroblastoma to aid clinical diagnosis and treatment decisions. Methods: We built a predictive model using data from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2018 on 1,542 patients with neuroblastoma. Seven machine-learning methods were employed to forecast the likelihood of neuroblastoma distant metastases. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for building machine learning models. Secondly, the subject operating characteristic area under the curve (AUC), Precision-Recall (PR) curves, decision curve analysis (DCA), and calibration curves were used to assess model performance. To further explain the optimal model, the Shapley summation interpretation method (SHAP) was applied. Ultimately, the best model was used to create an online calculator that estimates the likelihood of neuroblastoma distant metastases. Results: The study included 1,542 patients with neuroblastoma, multifactorial logistic regression analysis showed that age, histology, tumor size, tumor grade, primary site, surgery, chemotherapy, and radiotherapy were independent risk factors for distant metastasis of neuroblastoma (P < 0.05). Logistic regression (LR) was found to be the optimal algorithm among the seven constructed, with the highest AUC values of 0.835 and 0.850 in the training and validation sets, respectively. Finally, we used the logistic regression model to build a network calculator for distant metastasis of neuroblastoma. Conclusion: The study developed and validated a machine learning model based on clinical and pathological information for predicting the risk of distant metastasis in patients with neuroblastoma, which may help physicians make clinical decisions.

Factors influencing HPV vaccine hesitancy among university students in China: A cross-sectional survey utilizing the 3Cs model.

The HPV vaccine, which has been demonstrated to be an effective method of reducing the risk of developing cervical cancer, is still being underutilized among college students in China. To assess the current status of HPV vaccine hesitancy among college students in Guangdong Province after the COVID-19 outbreak, and to systematically analyze the influencing factors of HPV vaccine hesitancy and construct a prediction model based on the WHO 3Cs model. A cross-sectional web-based survey was conducted in June 2023 among female college students in four cities in Guangdong Province. The data were analyzed using binary logistic regression with a focus on the 3Cs model: Complacency, Convenience, and Confidence. LASSO regression was employed to analyze the variables deemed to be of significance and to construct predictive models. Out of 1399 participants, 86.5% expressed no hesitancy toward HPV vaccination. However, 11.9% exhibited hesitancy, and 1.6% refused vaccination altogether. Factors such as trust in vaccine efficacy, perception of HPV infection risk, price considerations, and constraints like distance or time were significant contributors to hesitancy. Knowledge of the HPV vaccine, socio-demographic characteristics, and the educational level of participants' mothers also played a role in vaccine hesitancy. It is recommended that targeted interventions be implemented within educational institutions with the aim of raising awareness of cervical cancer and HPV vaccines, simplifying the scheduling of vaccination appointments, and increasing affordability through the implementation of strategic purchasing measures or subsidy schemes.

Construction of a machine learning-based prediction model for unfavorable discharge outcomes in patients with ischemic stroke.

Background: Ischemic stroke is a common and serious disease with economic and healthcare burdens. Predicting the unfavorable discharge outcome of patients is essential for formulating appropriate treatment strategies and providing personalized care. Therefore, this study aims to establish and validate a prediction model based on machine learning methods to accurately predict the discharge outcome of ischemic stroke patients, providing valuable information for clinical decision making. Methods: The derivation data consisted of 964 patients from Guangdong Provincial People's Hospital and was used for training and internal validation. A favourable discharge outcome was defined as a National Institutes of Health Stroke Scale score of ≤1 or a decrease of ≥8 points compared to the admission score. A predictive model was created based on 88 medical characteristics gathered during the patient's initial admission, using nine machine learning algorithms. The model's predictive performance was compared using various evaluation metrics. The final model's feature importance was ranked and explained using the Shapley additive explanation method. Findings: The random forest model demonstrated the greatest discriminative ability among the nine machine learning models. We created an interpretable random forest model by ranking and reducing the features based on their importance, which included eight features. In internal validations, the final model accurately predicted the discharge outcomes of ischemic stroke with AUC values of 0.903 and has been translated into a convenient tool to facilitate its utility in clinical settings. Conclusions: Our explainable ML model was not only successfully developed to accurately predict discharge outcomes in patients with ischemic stroke and it mitigated the concern of the "black-box" issue with an undirect interpretation of the ML technique.

Value of altered methylation patterns of genes RANBP3, LCP2 and GRAP2 in cfDNA in breast cancer diagnosis.

Background: The purpose of this study was to investigate the potential of plasma cfDNA methylation patterns in reflecting tumour methylation changes, focusing on three candidate sites, cg02469161, cg11528914, and cg20131654. These sites were selected for verification, with a particular emphasis on their association with breast cancer. Methods: We conducted a comprehensive analysis of 850k whole-methylation sequencing data to identify potential markers for breast cancer detection. Subsequently, we investigated the methylation status of the genes Ran-binding protein 3 (RANBP3), Lymphocyte cytoplasmic protein 2 (LCP2), and GRB2 related adaptor protein 2 (GRAP2), situated at the specified sites, using cancer and canceradjacent tissues from 17 breast cancer patients. We also examined the methylation patterns in different molecular subtypes and pathological grades of breast cancer. Additionally, we compared the methylation levels of these genes in plasma cfDNA to their performance in tissues. Results: Our analysis revealed that RANBP3, LCP2, and GRAP2 genes exhibited significant methylation differences between cancer and cancer-adjacent tissues. In breast cancer, these genes displayed diagnostic efficiencies of 91.0%, 90.6%, and 92.2%, respectively. Notably, RANBP3 showed a tendency towards lower methylation in HR+ breast cancer, and LCP2 methylation was correlated with tumour malignancy. Importantly, the methylation levels of these three genes in plasma cfDNA closely mirrored their tissue counterparts, with diagnostic efficiencies of 83.3%, 83.9%, and 77.6% for RANBP3, LCP2, and GRAP2, respectively. Conclusions: Our findings propose that the genes RANBP3, LCP2, and GRAP2, located at the identified methylation sites, hold significant potential as molecular markers in blood for the supplementary diagnosis of breast cancer. This study lays the groundwork for a more in-depth investigation into the changes in gene methylation patterns in circulating free DNA (cfDNA) for the early detection not only of breast cancer but also for various other types of cancer.

Comprehensive exploration of a traditional Chinese medicinal plant of Magnolia officinalis based on high-coverage mass spectrometry and multidimensional chemical-biological analysis.

Magnolia bark is a traditional Chinese medicine used for hypoglycaemia. With the widespread use of Magnolia bark, its resources are facing a serious shortage. To address this issue, a strategy based on high-coverage mass spectrometry (HCMS) and multidimensional chemical-biological analysis (MCBA) was proposed for the comprehensive exploration of Magnolia officinalis which is the main source of Magnolia bark. The strategy is divided into three main steps. In the first step, the stem bark, stem xylem, root bark, root xylem, leaf and rootlet of Magnolia officinalis were comprehensively analyzed using high-coverage mass spectrometry. In the second step, multivariate statistical analysis was used to explore the heterogeneity of the six parts and detect differential chemical components. In the third step, a combination of experimental screening and molecular docking was used to explore α-glucosidase inhibitors from Magnolia officinalis. Multidimensional chemical-biological analysis (MCBA) of Magnolia officinalis was achieved by combining the last two steps. Finally, a total of 103 compounds were identified from the whole plant of Magnolia officinalis. Differential components of stem bark, stem xylem, leaf, root bark, root xylem and rootlet were systematically revealed. A pair of positional isomers, namely magnolol and honokiol, were found to be α-glucosidase inhibitors. The activity of their combination is superior to that of each single compound, indicating that magnolol and honokiol are in a synergistic relationship. This strategy contributes to comprehensive exploitation of functional plants and effective alleviation of resource shortage. This study also provides a research paradigm for other similar traditional Chinese medicinal plants.

A strategy to distinguish similar traditional Chinese medicines by liquid chromatography-mass spectrometry, electronic senses, and gas chromatography-ion mobility spectrometry: Marsdeniae tenacissimae Caulis and Paederiae scandens Caulis as examples.

INTRODUCTION: Marsdeniae tenacissimae Caulis (MTC), a popular traditional Chinese medicine, has been widely used in the treatment of tumor diseases. Paederiae scandens Caulis (PSC), which is similar in appearance to MTC, is a common counterfeit product. It is difficult for traditional methods to effectively distinguish between MTC and PSC. Therefore, there is an urgent need for a rapid and accurate method to identify MTC and PSC. OBJECTIVES: The aim is to distinguish between MTC and PSC by analyzing the differences in nonvolatile organic compounds (NVOCs), taste, odor, and volatile organic compounds (VOCs). METHODS: Liquid chromatography-mass spectrometry (LC-MS) was utilized to analyze the NVOCs of MTC and PSC. Electronic tongue (E-tongue) and electronic nose (E-nose) were used to analyze their taste and odor respectively. Gas chromatography-ion mobility spectrometry (GC-IMS) was applied to analyze VOCs. Finally, multivariate statistical analyses were conducted to further investigate the differences between MTC and PSC, including principal component analysis, orthogonal partial least squares discriminant analysis, discriminant factor analysis, and soft independent modeling of class analysis. RESULTS: The results of this study indicate that the integrated strategy of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis can be effectively applied to distinguish between MTC and PSC. Using LC-MS, 25 NVOCs were identified in MTC, while 18 NVOCs were identified in PSC. The major compounds in MTC are steroids, while the major compounds in PSC are iridoid glycosides. Similarly, the distinct taste difference between MTC and PSC was precisely revealed by the E-tongue. Specifically, the pronounced bitterness in PSC was proven to stem from iridoid glycosides, whereas the bitterness evident in MTC was intimately tied to steroids. The E-nose detected eight odor components in MTC and six in PSC, respectively. The subsequent statistical analysis uncovered notable differences in their odor profiles. GC-IMS provided a visual representation of the differences in VOCs between MTC and PSC. The results indicated a relatively high relative content of 82 VOCs in MTC, contrasted with 32 VOCs exhibiting a similarly high relative content in PSC. CONCLUSION: In this study, for the first time, the combined use of LC-MS, E-tongue, E-nose, GC-IMS, and multivariate statistical analysis has proven to be an effective method for distinguishing between MTC and PSC from multiple perspectives. This approach provides a valuable reference for the identification of other visually similar traditional Chinese medicines.

Integration of High-Resolution LC-Q-TOF Mass Spectrometry and Multidimensional Chemical-Biological Analysis to Detect Nanomolar-Level Acetylcholinesterase Inhibitors from Different Parts of Zanthoxylum nitidum.

Zanthoxyli radix is a popular tea among the elderly, and it is believed to have a positive effect on Alzheimer's disease. In this study, a highly effective three-step strategy was proposed for comprehensive analysis of the active components and biological functions of Zanthoxylum nitidum (ZN), including high-resolution LC-Q-TOF mass spectrometry (HRMS), multivariate statistical analysis for heterogeneity (MSAH), and experimental and virtual screening for bioactivity analysis (EVBA). A total of 117 compounds were identified from the root, stem, and leaf of ZN through HRMS. Bioactivity assays showed that the order of acetylcholinesterase (AChE) inhibitory activity from strong to weak was root > stem > leaf. Nitidine, chelerythrine, and sanguinarine were found to be the main differential components of root, stem, and leaf by OPLS-DA. The IC50 values of the three compounds are 0.81 ± 0.02, 0.14 ± 0.01, and 0.48 ± 0.01 µM respectively, indicating that they are potent and high-quality AChE inhibitors. Molecular docking showed that pi-pi T-shaped interactions and pi-lone pairs played important roles in AChE inhibition. This study not only explains the biological function of Zanthoxyli radix in alleviating Alzheimer's disease to some extent, but also lays the foundation for the development of stem and leaf of ZN.

Highly Stable Silver Nanowire Plasmonic Electrodes for Flexible Polymer Light-Emitting Devices.

Silver nanowire (AgNW) transparent electrodes are considered as a promising candidate for applications in flexible optoelectronic devices. However, it remains a great challenge to obtain flexible AgNW electrodes with excellent optoelectrical properties and mechanical flexibility. Here, highly stable Ag nanoparticle (AgNP)-enhanced plasmonic AgNW electrodes are demonstrated via the controllable in situ growth of AgNPs at the AgNW junctions and introduction of an l-histidine (l-His) wrapping layer. The flexible transparent electrodes of AgNW-AgNP/l-His possess a low sheet resistance (Rsh) of ∼17.5 Ω sq-1, a high transmittance of ∼92.5% (550 nm), and a robust mechanical stability (100,000 bending cycles). Benefiting from plasmon-coupling effects, flexible polymer light-emitting devices (FPLEDs) with AgNW-AgNP/l-His electrodes present a current efficiency (CE) of ∼14.8 cd A-1 and an external quantum efficiency (EQE) of ∼5.6%, constituting ∼80% and ∼75% increases compared to those of the reference devices with AgNW electrodes, respectively. Additionally, the laminated flexible transparent PLEDs (FT-PLEDs) are demonstrated by integrating polydimethylsiloxane/AgNW-AgNP anodes by a soft lamination process. The FT-PLEDs present a CE of ∼7.1 cd A-1 (cathode side: ∼3.9 cd A-1; anode side: ∼3.2 cd A-1) and an EQE of ∼2.7% (cathode side: ∼1.5%; anode side: ∼1.2%). Furthermore, the FPLEDs and FT-PLEDs exhibit robust mechanical durability, maintaining ∼89% and ∼86% of their initial luminance after 1000 bending cycles at a bending radius of 2 mm, respectively. This work opens up a new avenue for the development of high performance and stable flexible optoelectronic devices.

Improving Granulosa Cell Function in Premature Ovarian Failure with Umbilical Cord Mesenchymal Stromal Cell Exosome-Derived hsa_circ_0002021.

BACKGROUND: The therapeutic potential of exosomes from human umbilical cord mesenchymal stem cells (HUMSCs-Exo) for delivering specific circular RNAs (circRNAs) in treating premature ovarian failure (POF) is not well understood. This study aimed to explore the efficacy of HUMSCs-Exo in delivering hsa_circ_0002021 for POF treatment, focusing on its effects on granulosa cell (GC) senescence and ovarian function. METHODS: Bioinformatic analysis was conducted on circRNA profiles using the GSE97193 dataset from GEO, targeting granulosa cells from varied age groups. To simulate granulosa cell senescence, KGN cells were treated with cyclophosphamide (CTX). HUMSCs were transfected with pcDNA 3.1 vectors to overexpress hsa_circ_0002021, and the HUMSCs-Exo secreted were isolated. These exosomes were characterized by transmission electron microscopy (TEM) and Western blotting to confirm exosomal markers CD9 and CD63. Co-culture of these exosomes with CTX-treated KGN cells was performed to assess ß-galactosidase activity, oxidative stress markers, ROS levels, and apoptosis via flow cytometry. Interaction between hsa_circ_0002021, microRNA-125a-5p (miR-125a-5p), and cyclin-dependent kinase 6 (CDK6) was investigated using dual-luciferase assays and RNA immunoprecipitation (RIP). A POF mouse model was induced with CTX, treated with HUMSCs-Exo, and analyzed histologically and via immunofluorescence staining. Gene expression was quantified using RT-qPCR and Western blot. RESULTS: hsa_circ_0002021 was under expressed in both in vivo and in vitro POF models and was effectively delivered by HUMSCs-Exo to KGN cells, showing a capability to reduce GC senescence. Overexpression of hsa_circ_0002021 in HUMSCs-Exo significantly enhanced these anti-senescence effects. This circRNA acts as a competitive adsorbent of miR-125a-5p, regulating CDK6 expression, which is crucial in modulating cell cycle and apoptosis. Enhanced expression of hsa_circ_0002021 in HUMSCs-Exo ameliorated GC senescence in vitro and improved ovarian function in POF models by modulating oxidative stress and cellular senescence markers. CONCLUSION: This study confirms that hsa_circ_0002021, when delivered through HUMSCs-Exo, can significantly mitigate GC senescence and restore ovarian function in POF models. These findings provide new insights into the molecular mechanisms of POF and highlight the therapeutic potential of circRNA-enriched exosomes in treating ovarian aging and dysfunction.

Research and application of hydrogel-encapsulated mesenchymal stem cells in the treatment of myocardial infarction.

Myocardial infarction (MI) stands out as a highly lethal disease that poses a significant threat to global health. Worldwide, heart failure resulting from MI remains a leading cause of human mortality. Mesenchymal stem cell (MSC) therapy has emerged as a promising therapeutic approach, leveraging its intrinsic healing properties. Nevertheless, pervasive issues, including a low cell retention rate, suboptimal survival rate, and incomplete differentiation of MSCs, present formidable challenges for further research. The introduction and advancement of biomaterials have offered a novel avenue for the exploration of MSC therapy in MI, marking considerable progress thus far. Notably, hydrogels, among the representative biomaterials, have garnered extensive attention within the biomedical field. This review delves into recent advancements, specifically focusing on the application of hydrogels to augment MSC therapy for cardiac tissue regeneration in MI.

Small animal PET imaging with the 68Ga-labeled pH (low) insertion peptide-like peptide YJL-4 in a triple-negative breast cancer mouse model.

BACKGROUND: The aim of this study was to prepare a novel 68Ga-labeled pH (low) insertion peptide (pHLIP)-like peptide, YJL-4, and determine its value for the early diagnosis of triple-negative breast cancer (TNBC) via in vivo imaging of tumor-bearing nude mice. The novel peptide YJL-4 was designed using a template-assisted method and synthesized by solid-phase peptide synthesis. After modification with the chelator 1,4,7­triazacyclononane-N,N',N″-triacetic acid (NOTA), the peptide was labeled with 68Ga. Then, the biodistribution of 68Ga-YJL-4 in tumor-bearing nude mice was investigated, and the mice were imaged by small animal positron emission tomography (PET). RESULTS: The radiochemical yield and radiochemical purity of 68Ga-YJL-4 were 89.5 ± 0.16% and 97.95 ± 0.06%, respectively. The biodistribution of 68Ga-YJL-4 in tumors (5.94 ± 1.27% ID/g, 6.72 ± 1.69% ID/g and 4.54 ± 0.58% ID/g at 1, 2 and 4 h after injection, respectively) was significantly greater than that of the control peptide in tumors at the corresponding time points (P < 0.01). Of the measured off-target organs, 68Ga-YJL-4 was highly distributed in the liver and blood. The small animal PET imaging results were consistent with the biodistribution results. The tumors were visualized by PET at 2 and 4 h after the injection of 68Ga-YJL-4. No tumors were observed in the control group. CONCLUSIONS: The novel pHLIP family peptide YJL-4 can adopt an α-helical structure for easy insertion into the cell membrane in an acidic environment. 68Ga-YJL-4 was produced in high radiochemical yield with good stability and can target TNBC tissue. Moreover, the strong concentration of radioactive 68Ga-YJL-4 in the abdomen does not hinder the imaging of early TNBC.

Construction and analysis of a joint diagnostic model of machine learning for cryptorchidism based on single-cell sequencing.

BACKGROUND: Cryptorchidism is a condition in which one or both of a baby's testicles do not fully descend into the bottom of the scrotum. Newborns with cryptorchidism are at increased risk of developing infertility later in life. The aim of this study was to develop a novel diagnostic model for cryptorchidism and to identify new biomarkers associated with cryptorchidism. METHODS: The study data were obtained from RNA sequencing data of cryptorchid patients from Nantong University Hospital and the Gene Expression Omnibus (GEO) database. Differential expression analysis was used to obtain differentially expressed genes (DEGs) between the control and cryptorchid groups. These DEGs were analyzed for their functions by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment using GSEA software. Random Forest algorithm was used to screen central genes based on these DEGs. Neuralnet software package was used to develop artificial neural network models. Based on clinical data, receiver operating characteristic (ROC) was used to validate the models. Single-cell sequencing analysis was used for the pathogenesis of cryptorchidism. RESULTS: We obtained a total of 525 important DEGs related to cryptorchidism, which are mainly associated with biological functions such as supramolecular complexes and microtubule cytoskeleton. Random forest approach screening obtained eight hub genes. A neural network based on the hub genes showed a 100% success rate of the model. Finally, single-cell sequencing analysis validated the hub genes. CONCLUSION: We developed a novel diagnostic model for cryptorchidism using artificial neural networks and validated its utility as an effective diagnostic tool.

Correction: Chen et al. Multifunctional Injectable Hydrogel Loaded with Cerium-Containing Bioactive Glass Nanoparticles for Diabetic Wound Healing. Biomolecules 2021, 11, 702.

The authors would like to replace Figure 4A of the following published paper [...].

Intelligent Biosensors Promise Smarter Solutions in Food Safety 4.0.

Food safety is closely related to human health. However, the regulation and testing processes for food safety are intricate and resource-intensive. Therefore, it is necessary to address food safety risks using a combination of deep learning, the Internet of Things, smartphones, quick response codes, smart packaging, and other smart technologies. Intelligent designs that combine digital systems and advanced functionalities with biosensors hold great promise for revolutionizing current food safety practices. This review introduces the concept of Food Safety 4.0, and discusses the impact of intelligent biosensors, which offer attractive smarter solutions, including real-time monitoring, predictive analytics, enhanced traceability, and consumer empowerment, helping improve risk management and ensure the highest standards of food safety.

Efficient Flexible Fabric-Based Top-Emitting Polymer Light-Emitting Devices for Wearable Electronics.

Low-cost fabric-based top-emitting polymer light-emitting devices (Fa-TPLEDs) have aroused increasing attention due to their remarkable potential applications in wearable displays. However, it is still challenging to realize efficient all-solution-processed devices from bottom electrodes to top electrodes with large-scale fabrication. Here, a smooth reflective Ag cathode integrated on fabric by one-step silver mirror reaction and a composite transparent anode of polydimethylsiloxane/silver nanowires/poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) via a water-assisted peeling method are presented, both of which possess excellent optoelectrical properties and robust mechanical flexibility. The Fa-TPLEDs are constructed by spin-coating functional layers on the bottom reflective cathodes and laminating the top transparent anodes. The Fa-TPLEDs show a current efficiency of 16.3 cd A-1 , an external quantum efficiency of 4.9% and angle-independent electroluminescence spectra. In addition, the Fa-TPLEDs possess excellent mechanical stability, maintaining a current efficiency of 14.3 cd A-1 after 200 bending cycles at a radius of 4 mm. The results demonstrate that the integration of solution-processed reflective cathodes and transparent anodes sheds light on a new avenue to construct low-cost and efficient fabric-based devices, showing great potential applications in emerging smart flexible/wearable electronics.

ß-Galactosidase: a traditional enzyme given multiple roles through protein engineering.

ß-Galactosidases are crucial carbohydrate-active enzymes that naturally catalyze the hydrolysis of galactoside bonds in oligo- and disaccharides. These enzymes are commonly used to degrade lactose and produce low-lactose and lactose-free dairy products that are beneficial for lactose-intolerant people. ß-galactosidases exhibit transgalactosylation activity, and they have been employed in the synthesis of galactose-containing compounds such as galactooligosaccharides. However, most ß-galactosidases have intrinsic limitations, such as low transglycosylation efficiency, significant product inhibition effects, weak thermal stability, and a narrow substrate spectrum, which greatly hinder their applications. Enzyme engineering offers a solution for optimizing their catalytic performance. The study of the enzyme's structure paves the way toward explaining catalytic mechanisms and increasing the efficiency of enzyme engineering. In this review, the structure features of ß-galactosidases from different glycosyl hydrolase families and the catalytic mechanisms are summarized in detail to offer guidance for protein engineering. The properties and applications of ß-galactosidases are discussed. Additionally, the latest progress in ß-galactosidase engineering and the strategies employed are highlighted. Based on the combined analysis of structure information and catalytic mechanisms, the ultimate goal of this review is to furnish a thorough direction for ß-galactosidases engineering and promote their application in the food and dairy industries.

Malaria epidemiological characteristics and control in Guangzhou, China, 1950-2022.

BACKGROUND: Malaria was once widespread in Guangzhou, China. However, a series of control measures have succeeded in eliminating local malaria infections. Based on the analysis of the characteristics of malaria epidemics in Guangzhou, China, from 1950 to 2022, the changes and effectiveness of malaria control strategies and surveillance management in Guangzhou from 1950 to 2022 are described. METHODS: Data on malaria prevention and treatment in Guangzhou from 1950 to 2022 were collected, and descriptive epidemiological methods were used to analyse the prevalence of malaria, preventive and control measures taken, and the effectiveness of prevention and treatment in different periods. Data on malaria cases were obtained from the Guangzhou Centre for Disease Control and Prevention (CDC) and the China Communicable Disease Reporting System. RESULTS: The development of the malaria control system in Guangzhou has gone through four periods: 1. High malaria prevalence (1950-1979), 2. Intensive prevention and control stage (1980-2000), 3. Consolidating gains in malaria control (2001-2008), and 4. Preventing reestablishment of transmission (2009-2022). During Period 1, only medical institutions at all levels and the local CDCs, the Guangzhou CDC participated in the malaria prevention and control system, establishing a three-tier health system on malaria prevention and control. During Period 2, other types of organizations, including the agricultural sector, schools and village committees, the construction department and street committee, are involved in the malaria control system. During Period 3, more and more organizations are joining forces to prevent and control malaria. A well-established multisectoral malaria control mechanism and an improved post-elimination surveillance management system are in place. Between 1950 and 2022, a total of 420,670 cases of malaria were reported. During Period 1, there was an epidemic of malaria in the early 1950s, with an annual incidence rate of more than 10,000/100,000, including a high rate of 2887.98/100,000 in 1954. In Period 2 malaria was gradually brought under control, with the average annual malaria incidence rate dropping to 3.14/100,000. During Period 3, the incidence rate was kept below 1/100,000, and by 2009 local malaria infections were eliminated. CONCLUSION: For decades, Guangzhou has adopted different malaria control strategies and measures at different epidemic stages. Increased collaboration among civil organizations in Guangzhou in malaria control has led to a significant decline in the number of malaria cases and the elimination of indigenous malaria infections by 2009.The experience of Guangzhou can guide the development of malaria control strategies in other cities experiencing similar malaria epidemics.

Combinatorics-based chemical characterization and bioactivity comparison of different parts of traditional Chinese medicinal plants through LC-Q-TOF-MS/MS, multivariate statistical analysis and bioassay: Marsdenia tenacissima as an example.

Marsdenia tenacissima is a traditional Chinese medicinal plant used for treating cancer, and its main medicinal part is the stem. Considering the resource shortage of M. tenacissima, it is of great significance to improve its utilization efficiency. Steroids and caffeoylquinic acids, the two main components of M. tenacissima, are composed of several basic structures. Based on this rule, a novel strategy of combinatorics-based chemical characterization was proposed to analyze the constituents of roots, stems and leaves of M. tenacissima. Combinatorics was used to generate a compound library for structure alignment, which has the advantages of wide coverage and high specificity. Steroids are composed of four basic parts: core skeleton (C), substituent at position 11 (A), substituent at position 12 (B) and sugar moiety (S). Based on combinatorics, a compound library consisting of 1080 steroids was generated. Diagnostic neutral loss has been used to effectively predict the substituents at position 11 and 12 of steroids, including acetyl, 2-methylpropionyl, tigloyl, 2-methylbutyryl and benzoyl. As a result, 131, 131 and 99 components were detected from the roots, stems and leaves of M. tenacissima, respectively. Principal component analysis (PCA) was used to analyze the differences of roots, stems and leaves, and orthogonal partial least squares-discriminant analysis (OPLS-DA) was further applied to find differential components. Tenacissoside H, a critical indicator component for quality evaluation of the stem, has been proved to be a differential component between roots and stems. Notably, the relative content of tenacissoside H in the roots was significantly higher than that in the stems. The bioactivity comparison showed that roots, stems and leaves of M. tenacissima had similar scavenging activity on 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical. However, their α-glucosidase inhibitory activity was ranked as leaves > stems > roots. Therefore, besides stems, the other parts of M. tenacissima have potential medicinal value. This study not only helps to develop the resource of M. tenacissima, but also provides a paradigm for the research of other similar medicinal plants.

Impact of perceived ease of use, organizational support mechanism, and industry competitive pressure on physicians' use of liver cancer screening technology in medical alliances.

Background: Liver cancer is one of the malignant tumors worldwide, while the prevention and control situation is grim at present, and the diffusion of its early screening technology still faces some challenges. This study aims to investigate the influencing mechanism of perceived ease of use, organizational support mechanism, and industry competitive pressure on hepatic early screening technologies use by physicians, so as to promote the wider use of corresponding technologies. Methods: Under the theoretical guidance of technology-organization-environment framework and mindsponge theory, this study took hepatic contrast-enhanced ultrasound as an example, and conducted a cross-sectional questionnaire by randomly selecting physicians from Fujian and Jiangxi provinces in China with a high and low incidence of liver cancer, respectively. Structural equation modeling was used to determine the correlation among perceived ease of use, organizational support mechanism, and industry competitive pressure, as well as their impact on the physicians' behavior toward contrast-enhanced ultrasound use. Results: The hypothesis model fits well with the data (χ2/df = 1.863, GFI = 0.937, AGFI = 0.908, RMSEA = 0.054, NFI = 0.959, IFI = 0.980, CFI = 0.980). Under technology-organization-environment framework, the perceived ease of use (ß = 0.171, p < 0.05), organizational support mechanism (ß = 0.423, p < 0.01), industry competitive pressure (ß = 0.159, p < 0.05) significantly influenced physicians' use of hepatic contrast-enhanced ultrasound. Besides, perceived ease of use and organizational support mechanism (ß = 0.216, p < 0.01), perceived ease of use and industry competitive pressure (ß = 0.671, p < 0.01), organizational support mechanism and industry competitive pressure (ß = 0.330, p < 0.01) were all associated significantly. Conclusion: From the lens of information processing (mindsponge theory) and technology-organization-environment framework, this study clarified the social and psychological influencing mechanism of perceived ease of use, organizational support mechanism, and industry competitive pressure on physicians' use of hepatic contrast-enhanced ultrasound. The results will directly propose recommendations for expanding hepatic contrast-enhanced ultrasound utilization and indirectly promoting other appropriate and effective health technologies diffusion within the integrated health system.