TransFOL: A Logical Query Model for Complex Relational Reasoning in Drug-Drug Interaction.

Predicting drug-drug interaction (DDI) plays a crucial role in drug recommendation and discovery. However, wet lab methods are prohibitively expensive and time-consuming due to drug interactions. In recent years, deep learning methods have gained widespread use in drug reasoning. Although these methods have demonstrated effectiveness, they can only predict the interaction between a drug pair and do not contain any other information. However, DDI is greatly affected by various other biomedical factors (such as the dose of the drug). As a result, it is challenging to apply them to more complex and meaningful reasoning tasks. Therefore, this study regards DDI as a link prediction problem on knowledge graphs and proposes a DDI prediction model based on Cross-Transformer and Graph Convolutional Networks (GCN) in first-order logical query form, TransFOL. In the model, a biomedical query graph is first built to learn the embedding representation. Subsequently, an enhancement module is designed to aggregate the semantics of entities and relations. Cross-Transformer is used for encoding to obtain semantic information between nodes, and GCN is used to gather neighbour information further and predict inference results. To evaluate the performance of TransFOL on common DDI tasks, we conduct experiments on two benchmark datasets. The experimental results indicate that our model outperforms state-of-the-art methods on traditional DDI tasks. Additionally, we introduce different biomedical information in the other two experiments to make the settings more realistic. Experimental results verify the strong drug reasoning ability and generalization of TransFOL in complex settings. Data and code are available at https://github.com/Cheng0829/TransFOL.

Pregnancy Outcomes in Women Who Developed Elevated Blood Pressure and Stage I Hypertension after 20 Weeks Gestation.

OBJECTIVE: The American College of Obstetrics threshold for hypertension (≥140/90 mm Hg) differs from those of the American College of Cardiology (ACC) and the American Heart Association (AHA). It is unknown if ACC/AHA hypertension levels are associated with adverse pregnancy outcomes (APOs) after 20 weeks gestation. The purpose of this study is to analyze APOs in women with blood pressure (BP) in the elevated or stage 1 range after 20 weeks gestation. STUDY DESIGN: This was a secondary analysis of the nuMoM2b prospective cohort study of 10,038 nulliparous, singleton pregnancies between 2010 and 2014. BP was measured at three visits during the pregnancy using a standard protocol. Women without medical comorbidities, with normal BP by ACC/AHA guidelines (systolic BP [SBP] < 120 and diastolic BP [DBP] < 80 mm Hg) up to 22 weeks, were included. Exposure was BP between 22 and 29 weeks gestation: normal (SBP < 120 and DBP < 80 mm Hg), elevated (SBP: 120-129 and DBP < 80 mm Hg), and stage 1 (SBP: 130-139 or DBP: 80-89 mm Hg). The primary outcome was hypertensive disorder of pregnancy (HDP) at delivery. Secondary outcomes included fetal growth restriction (FGR), placental abruption, preterm delivery, and cesarean delivery. Multivariable-adjusted odds ratio (aORs) and 95% confidence intervals (CIs) were estimated using logistic regression models. RESULTS: Of 4,460 patients that met inclusion criteria, 3,832 (85.9%) had BP in the normal range, 408 (9.1%) in elevated, and 220 (4.9%) in stage 1 range between 22 and 29 weeks. The likelihood of HDP was significantly higher in women with elevated BP (aOR 1.71, 95%CI: 1.18,2.48), and stage 1 BP (aOR: 2.79, 95%CI: 1.84,4.23) compared to normal BP (p < 0.001). Stage 1 BP had twice odds of FGR (aOR: 2.33, 95%CI: 1.22,4.47) and elevated BP had three times odds of placental abruption (aOR: 3.03; 95%CI: 1.24,7.39). CONCLUSION: Elevated or stage 1 BP >20 weeks of pregnancy are associated with HDP, FGR, and placental abruption. KEY POINTS: · Elevated and stage 1 BP increases risk for HDP.. · Elevated BP increases risk for placental abruption.. · Stage 1 BP increases risk for FGR..

Experimental Study on the Wind Erosion Resistance of Aeolian Sand Solidified by Microbially Induced Calcite Precipitation (MICP).

Microbially induced calcite precipitation (MICP) is an emerging solidification method characterized by high economic efficiency, environmental friendliness, and durability. This study validated the reliability of the MICP sand solidification method by conducting a small-scale wind tunnel model test using aeolian sand solidified by MICP and analyzing the effects of wind velocity (7 m/s, 10 m/s, and 13 m/s), deflation angle (0°, 15°, 30°, and 45°), wind erosion cycle (1, 3, and 5), and other related factors on the mass loss rate of solidified aeolian sand. The microstructure of aeolian sand was constructed by performing mesoscopic and microscopic testing based on X-ray diffraction analysis (XRD), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). According to the test results, the mass loss rate of solidified aeolian sand gradually increases with the increase in wind velocity, deflation angle, and wind erosion cycle. When the wind velocity was 13 m/s, the mass loss rate of the aeolian sand was only 63.6%, indicating that aeolian sand has excellent wind erosion resistance. CaCO3 crystals generated by MICP were mostly distributed on sand particle surfaces, in sand particle pores, and between sand particles to realize the covering, filling, and cementing effects.

Effects of Aripiprazole on Olanzapine Population Pharmacokinetics and Initial Dosage Optimization in Schizophrenia Patients.

Objective: Olanzapine has already been used to treat schizophrenia patients; however, the initial dosage recommendation when multiple drugs are used in combination, remains unclear. The purpose of this study was to explore the drug-drug interaction (DDI) of multiple drugs combined with olanzapine and to recommend the optimal administration of olanzapine in schizophrenia patients. Methods: In this study, we obtained olanzapine concentrations from therapeutic drug monitoring (TDM) database. In addition, related medical information, such as physiological, biochemical indexes, and concomitant drugs was acquired using medical log. Sixty-five schizophrenia patients were enrollmented for analysis using population pharmacokinetic model by means of nonlinear mixed effect (NONMEM). Results: Weight and combined use of aripiprazole significantly affected olanzapine clearance. Without aripiprazole, for once-daily olanzapine administration dosages, 0.6, 0.5 mg/kg/day were recommended for 40-70, and 70-100 kg schizophrenia patients, respectively; for twice-daily olanzapine administration dosages, 0.6, 0.5 mg/kg/day were recommended for 40-60, and 60-100 kg schizophrenia patients, respectively. With aripiprazole, for once-daily olanzapine administration dosages, 0.4, 0.3 mg/kg/day were recommended for 40-53, and 53-100 kg schizophrenia patients, respectively; for twice-daily olanzapine administration dosages, 0.4 mg/kg/day was recommended for 40-100 kg schizophrenia patients, respectively. Conclusion: Aripiprazole significantly affected olanzapine clearance, and when schizophrenia patients use aripiprazole, the olanzapine dosages need adjust. Meanwhile, we firstly recommended the optimal initial dosages of olanzapine in schizophrenia patients.

Radical cascade silylation/cyclization of 1,7-dienes to access silyl-substituted benzo[b]azepin-2-ones.

A novel silyl radical-induced cascade silylation/cyclization of 1,7-dienes has been realized employing readily available hydrosilanes as a silicon source and Cu(I) salt as a catalyst. This protocol introduces diverse silicon fragments into a challenging 7-membered ring structure and provides an efficient approach to a wide array of biologically important silyl-substituted benzo[b]azepin-2-ones. Several control experiments suggest that the reaction undergoes a free radical process. The gram-scale synthesis and late-stage transformations further demonstrate the scalability and applicability of the reaction in organic synthesis.

RNA-seq based transcriptomic map reveals multiple pathways of necroptosis in treating myocardial ischemia reperfusion injury.

Necroptosis has been shown to contribute to myocardial ischemia reperfusion injury (MIRI). This study aims to gain new insights into the signaling pathway of necroptosis in rat MIRI using RNA sequencing. MIRI was induced in male rats by ligating the left anterior descending coronary artery for 30 min, followed by reperfusion for 120 min. RNA sequencing was performed to obtain mRNA profiles of MIRI group and MIRI group treated with necrostatin-1 (Nec-1,an inhibitor of necroptosis). Differentially expressed genes (DEGs) were then identified. The DEGs were prominently enriched in the TNF-α signaling pathway, the MAPK signaling pathway and cytokine-cytokine receptor pathways. The majority of the results were associated with genes like Thumpd3,Egr2,Dot1l,Cyp1a1,Dbnl,which primarily regulate inflammatory response and apoptosis, particularly in myocardium. The above results suggested that Nec-1 might be involved in the regulation of necroptosis and the inflammatory response through the above-mentioned genes.

Repeated inoculation with rumen fluid accelerates the rumen bacterial transition with no benefit on production performance in postpartum Holstein dairy cows.

BACKGROUND: The dairy cow's postpartum period is characterized by dramatic physiological changes, therefore imposing severe challenges on the animal for maintaining health and milk output. The dynamics of the ruminal microbiota are also tremendous and may play a crucial role in lactation launch. We aim to investigate the potential benefits of early microbial intervention by fresh rumen microbiota transplantation (RMT) and sterile RMT in postpartum dairy cows. Twelve fistulated peak-lactation dairy cows were selected to be the donors for rumen fluid collection. Thirty postpartum cows were divided into 3 groups as the transplantation receptors respectively receiving 10 L fresh rumen fluid (FR), 10 L sterile rumen fluid (SR), or 10 L saline (CON) during 3 d after calving. RESULTS: Production performance, plasma indices, plasma lipidome, ruminal microbiome, and liver transcriptome were recorded. After fresh and sterile RMT, we found that the molar proportion of propionic acid was increased on d 7 in the FR and SR groups and the bacterial composition was also significantly changed when compared with the CON group. A similarity analysis showed that the similarities between the CON group and FR or SR group on d 7 were 48.40% or 47.85%, whereas the similarities between microbiota on d 7 and 21 in the FR and SR groups were 68.34% or 66.85%. Dry matter intake and feed efficiency were not affected by treatments. Plasma ß-hydroxybutyrate concentration in the FR group was decreased and significantly different lipids mainly included phosphatidylcholine and lysophosphatidylcholine containing polyunsaturated fatty acids. Hepatic transcriptomics analysis indicated acute-phase response pathways were upregulated in the SR group. CONCLUSIONS: Our study suggests that RMT can shorten the transition process of the ruminal microbiota of postpartum dairy cows with no benefit on dry matter intake or feed efficiency. Inoculation with rumen fluid may not be a useful approach to promote the recovery of postpartum dairy cows.

Optimizing the initial tacrolimus dosage in Chinese children with lung transplantation within normal hematocrit levels.

Background: The appropriate initial dosage of tacrolimus is undefined in Chinese pediatric lung transplant patients with normal hematocrit values. The purpose of this study is to optimize the initial dose of tacrolimus in Chinese children who are undergoing lung transplantation and have normal hematocrit levels. Methods: The present study is based on a published population pharmacokinetic model of tacrolimus in lung transplant patients and uses the Monte Carlo simulation to optimize the initial tacrolimus dosage in Chinese children with lung transplantation within normal hematocrit levels. Results: Within normal hematocrit levels, for children with lung transplantation who do not carry the CYP3A5*1 gene and have no coadministration with voriconazole, it is recommended to administer tacrolimus at a dosage of 0.02 mg/kg/day, divided into two doses, for children weighing 10-32 kg, and a dosage of 0.03 mg/kg/day, also divided into two doses, for children weighing 32-40 kg. For children with lung transplantation who carry the CYP3A5*1 gene and have no coadministration with voriconazole, tacrolimus dosages of 0.02, 0.03, and 0.04 mg/kg/day split into two doses are recommended for children weighing 10-15, 15-32, and 32-40 kg, respectively. For children with lung transplantation who do not carry the CYP3A5*1 gene and have coadministration with voriconazole, tacrolimus dosages of 0.01 and 0.02 mg/kg/day split into two doses are recommended for children weighing 10-17 and 17-40 kg, respectively. For children with lung transplantation who carry the CYP3A5*1 gene and have coadministration with voriconazole, a tacrolimus dosage of 0.02 mg/kg/day split into two doses is recommended for children weighing 10-40 kg. Conclusions: It is the first time to optimize the initial dosage of tacrolimus in Chinese children undergoing lung transplantation within normal hematocrit.

The association between lead exposure and dental caries ─ a systematic review.

INTRODUCTION: Dental caries has declined over the years, but it remains a major public health issue. This review aimed to investigate the association between lead and caries experience in either deciduous or permanent teeth. METHODS: A comprehensive search of PubMed, EMBASE, and Google Scholar was conducted to identify relevant studies published up until December 2022. Included were human observational studies that investigated the association between lead exposure and dental caries. The review adhered to the PRISMA guideline. RESULTS: Sixteen studies were included in this review, with nine focusing on deciduous teeth, thirteen on permanent teeth, and six examining both types of teeth. Most of the studies (5 of 6) found a positive association between blood lead (PbB) levels and caries in deciduous teeth, while the findings for permanent teeth were less conclusive, with only 3 of 10 studies finding an association. One of the two studies assessing salivary lead (PbSa) levels found a weak association for permanent teeth. All four studies that examined lead (Pb) concentration in teeth found a positive association for both deciduous and permanent teeth. CONCLUSION: Many published studies indicated a positive association between Pb exposure and caries experience in deciduous dentition. Children with elevated PbB level should be considered as having higher caries experience. Due to lack of consensus on measurement and examination technique, there remains insufficient evidence to make any definitive conclusions especially in permanent teeth, and so more studies are warranted.

SADR: Self-Supervised Graph Learning With Adaptive Denoising for Drug Repositioning.

Traditional drug development is often high-risk and time-consuming. A promising alternative is to reuse or relocate approved drugs. Recently, some methods based on graph representation learning have started to be used for drug repositioning. These models learn the low dimensional embeddings of drug and disease nodes from the drug-disease interaction network to predict the potential association between drugs and diseases. However, these methods have strict requirements for the dataset, and if the dataset is sparse, the performance of these methods will be severely affected. At the same time, these methods have poor robustness to noise in the dataset. In response to the above challenges, we propose a drug repositioning model based on self-supervised graph learning with adptive denoising, called SADR. SADR uses data augmentation and contrastive learning strategies to learn feature representations of nodes, which can effectively solve the problems caused by sparse datasets. SADR includes an adaptive denoising training (ADT) component that can effectively identify noisy data during the training process and remove the impact of noise on the model. We have conducted comprehensive experiments on three datasets and have achieved better prediction accuracy compared to multiple baseline models. At the same time, we propose the top 10 new predictive approved drugs for treating two diseases. This demonstrates the ability of our model to identify potential drug candidates for disease indications.

Temporal Protein Complex Identification Based on Dynamic Heterogeneous Protein Information Network Representation Learning.

Protein complexes, as the fundamental units of cellular function and regulation, play a crucial role in understanding the normal physiological functions of cells. Existing methods for protein complex identification attempt to introduce other biological information on top of the protein-protein interaction (PPI) network to assist in evaluating the degree of association between proteins. However, these methods usually treat protein interaction networks as flat homogeneous static networks. They cannot distinguish the roles and importance of different types of biological information, nor can they reflect the dynamic changes of protein complexes. In recent years, heterogeneous network representation learning has achieved great success in processing complex heterogeneous information and mining deep semantics. We thus propose a temporal protein complex identification method based on Dynamic Heterogeneous Protein information network Representation Learning, DHPRL. DHPRL naturally integrates multiple types of heterogeneous biological information in the cellular temporal dimension. It simultaneously models the temporal dynamic properties of proteins and the heterogeneity of biological information to improve the understanding of protein interactions and the accuracy of complex prediction. Firstly, we construct Dynamic Heterogeneous Protein Information Network (DHPIN) by integrating temporal gene expression information and GO attribute information. Then we design a dual-view collaborative contrast mechanism. Specifically, proposing to learn protein representations from two views of DHPIN (1-hop relation view and meta-path view) to model the consistency and specificity between nearest-neighbour bio information and deeper biological semantics. The dynamic PPI network is thereafter re-weighted based on the learned protein representations. Finally, we perform protein identification on the re-weighted dynamic PPI network. Extensive experimental results demonstrate that DHPRL can effectively model complicated biological information and achieve state-of-the-art performance in most cases. The source code and datasets for DHPR are available at https://github.com/LI-jasm/DHPRL.

Syk/BLNK/NF-κB signaling promotes pancreatic injury induced by tacrolimus and potential protective effect from rapamycin.

BACKGROUND: The treatment of tacrolimus-induced post-transplantation diabetes mellitus (PTDM) has become a hot topic to improve the long-term survival of organ transplant patients, however whose pathogenesis has not been fully elucidated. In pancreas, the up-regulation of NF-κB has been reported to stimulate cytokine IL-1ß/TNF-α secretion, inducing pancreatic injury, meanwhile other studies have reported the inhibitory effect of rapamycin on NF-κB. PURPOSE: The aim of this study was to clarify the mechanism of tacrolimus-induced pancreatic injury and to explore the potential effect from small dose of sirolimus. METHODS: Wistar rats were randomly divided normal control (NC) group, PTDM group, sirolimus intervention (SIR) group. Transcriptomic analysis was used to screen potential mechanism of PTDM. Biochemical index detections were used to test the indicators of pancreatic injury. Pathological staining, immumohistochemical staining, immunofluorescent staining, western blot were used to verify the underlying mechanism. RESULTS: Compared with NC group, the level of insulin was significant reduction (P < 0.01), inversely the level of glucagon was significantly increase (P < 0.01) in PTDM group. Transcriptomic analysis indicated Syk/BLNK/NF-κB signaling was significantly up-regulated in PTDM group. Pathological staining, immumohistochemical staining, immunofluorescent staining, western blot verified Syk/BLNK/NF-κB and TNF-α/IL-1ß were all significantly increased (P < 0.05 or P < 0.01), demonstrating the mechanism of tacrolimus-induced pancreatic injury via Syk/BLNK/NF-κB signaling. In addition, compared with PTDM group, the levels of weight, FPG, AMY, and GSP in SIR group were significant ameliorative (P < 0.05 or P < 0.01), and the expressions of p-NF-κB, TNF-α/IL-1ß in SIR group were significantly reduction (P < 0.05 or P < 0.01), showing Syk/BLNK/NF-κB signaling promoted pancreatic injury induced by tacrolimus and potential protective effect from rapamycin reducing NF-κB. CONCLUSION: Syk/BLNK/NF-κB signaling promotes pancreatic injury induced by tacrolimus and rapamycin has a potentially protective effect by down-regulating NF-κB. Further validation and clinical studies are needed in the future.

Serum zinc concentration and dietary zinc intake in relation to cognitive function: an analysis of the REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort.

PURPOSE: There are several pathways by which zinc may be a modifiable factor to slow age-related cognitive decline. We investigated the associations between serum and dietary zinc and cognitive impairment in a longitudinal cohort. METHODS: We used data from the REasons for Geographic and Racial Differences in Stroke (REGARDS) Cohort (n = 30,239) and the REGARDS Trace Element Study (n = 2666). Baseline serum zinc concentrations (2003-2007) were measured using inductively coupled plasma mass spectrometry. Baseline dietary zinc intake was measured via the Block food frequency questionnaire. Serum zinc concentrations and dietary zinc intake were categorized into quartiles. The outcome of interest was impairment on the Six-Item Screener (SIS), a measure of global cognitive functioning administered annually. The Enhanced Cognitive Battery (ECB), a more comprehensive series of tests assessing memory and fluency, was administered every two years and considered a secondary outcome. Associations between zinc and incident impairment were assessed using multivariable logistic regression. RESULTS: Among 2065 participants with serum zinc data, 184 individuals developed impairment over 10 years of follow-up. In adjusted models, there was no significant association between serum zinc and impairment as assessed by the SIS or the ECB. Among 18,103 participants who had dietary data, 1424 experienced incident impairment on the SIS. Dietary zinc intake was not significantly associated with impairment as assessed by the SIS or the ECB in adjusted models. CONCLUSION: Findings from this U.S. cohort did not support the hypothesis that serum zinc concentration or dietary zinc intake is associated with the risk of cognitive impairment.

MPTN: A message-passing transformer network for drug repurposing from knowledge graph.

Drug repurposing (DR) based on knowledge graphs (KGs) is challenging, which uses knowledge graph reasoning models to predict new therapeutic pathways for existing drugs. With the rapid development of computing technology and the growing availability of validated biomedical data, various knowledge graph-based methods have been widely used to analyze and process complex and novel data to discover new indications for given drugs. However, existing methods need to be improved in extracting semantic information from contextual triples of biomedical entities. In this study, we propose a message-passing transformer network named MPTN based on knowledge graph for drug repurposing. Firstly, CompGCN is used as precoder to jointly aggregate entity and relation embeddings. Then, to fully capture the semantic information of entity context triples, the message propagating transformer module is designed. The module integrates the transformer into the message passing mechanism and incorporates the attention weight information of computing entity context triples into the entity embedding to update the entity embedding. Next, the residual connection is introduced to retain information as much as possible and improve prediction accuracy. Finally, MPTN utilizes the InteractE module as the decoder to obtain heterogeneous feature interactions in entity and relation representations and predict new pathways for drug treatment. Experiments on two datasets show that the model is superior to the existing knowledge graph embedding (KGE) learning methods.

Tailoring the density of states of Ni(OH)2 with Ni0 towards solar urea wastewater splitting.

Solar urea wastewater splitting is capable of producing hydrogen and degrading the urea pollutant simultaneously. Nickel hydroxide (Ni(OH)2) has been recognized as an effective cocatalyst for the urea oxidation reaction (UOR). But the lack of an efficient preparation method and a suitable Ni(OH)2 based cocatalyst limits the performances of solar urea wastewater splitting. Herein, a potential-cycling method is developed with a high-purity nickel plate serving as the counter electrode and nickel source in a three-electrode configuration. Spherical Ni0-doped Ni(OH)2 nanoparticles are successfully synthesized on the surface of TiO2 nanorod arrays. The photocurrent density of TiO2/Ni0:Ni(OH)2 can reach 0.56 mA cm-2 at 1.23 VRHE in 1 M NaOH and 0.33 M CO(NH2)2 mixed electrolyte under AM1.5G illumination, which is 1.75 and 1.93 times those of TiO2/Ni(OH)2 deposited using a normal potentiostatic method with nickel salt solution and pristine TiO2, respectively. Ni0 doping can significantly decrease the charge transfer resistance and provide a more favorable distribution of density of states of Ni(OH)2 for the UOR. Furthermore, Ni0:Ni(OH)2 decorated TiO2 photoanodes exhibit good photocurrent retention during 12 h continuous testing. This work expands the preparation technique of urea catalysts and the strategy for developing highly efficient nickel-based catalysts.

Semantic-enhanced Graph Contrastive Learning with Adaptive Denoising for Drug Repositioning.

The traditional drug development process requires a significant investment in workforce and financial resources. Drug repositioning as an efficient alternative has attracted much attention during the last few years. Despite the wide application and success of the method, there are still many shortcomings in the existing model. For example, sparse datasets will seriously affect the existing methods' performance. Additionally, these methods do not pay attention to the noise in datasets. In response to the above defects, we propose a semantic-enriched augmented graph contrastive learning with an adaptive denoising method, called SGCD. This method enhances data from the perspective of the embedding layer, deeply mines potential neighborhood relation-ships in semantic space, and combines similar drugs in the semantic neighborhoods into prototype comparison targets, thus effectively mitigating the impact of data sparsity on the model. Moreover, to enhance the model's robustness to noisy data, we use the adaptive denoising method, which can effectively identify noisy data in the training process. Exhaustive experiments on multiple real datasets show the effectiveness of the proposed model. The code implementation is available at https://github.com/yuhuimin11/SGCD-master.

Inonotus obliquus sclerotia epidermis were different from internal tissues in compound composition, antioxidant activity, and associated fungi.

Inonotus obliquus is a medicinal fungus with potential for use in various health applications. To better utilize this fungus, this study focused on epidermis and internal tissues of five sclerotia from different regions in Jilin, Inner Mongolia, and Heilongjiang, examining their polyphenols, polysaccharides, flavonoids, and total triterpenes contents. And evaluated the extracts from sclerotia for their total antioxidant capacity and scavenging ability of DPPH free radicals. The study also isolated the associated fungi from the epidermis and internal tissues of three sclerotia. Results revealed that the polyphenol content was higher in the epidermis than in internal tissue of every sclerotium. However, flavonoid and total triterpenoid content was lower in the epidermis of every sclerotium. The polysaccharide content was no significant in different parts of three sclerotia, but the epidermal polysaccharide content in two sclerotia was significantly higher than in internal tissues. The internal tissue extracts from tested sclerotia exhibited better scavenging ability of DPPH free radicals than those from the epidermis. There was no significant difference in total antioxidant capacity among different parts of three sclerotia, and the internal tissues' total antioxidant capacity in two sclerotia was higher than the epidermis. The number and species of associated fungi in the internal tissues were far less than that in the epidermis. The study suggests separating the epidermis and internal tissue for medicinal use. The research provides insights into the bioactive components and associated fungi of I. obliquus to inform its practical application in medicine.

Smoking Modifies the Association Between Radon Exposure and Incident Ischemic Stroke: The REGARDS Study.

BACKGROUND: Exposure to radon has been linked to lung cancer and other lung diseases. Although biologically plausible, research of residential radon exposure in relation to stroke risk is scarce. METHODS: Study participants were from the REGARDS (Reasons for Geographic and Racial Differences in Stroke) cohort (n=30 239), which consisted of male and female non-Hispanic Black and White adults aged 45 and older. After excluding participants with baseline stroke and transient ischemic attack, and missing information on exposure and outcome of interest, the final sample size was 26 950. The primary outcome was time to the first ischemic stroke through September 30, 2020. County-level radon measures from Lawrence Berkeley National Laboratory were linked to each participant based on their geocoded residential history. We used Cox proportional hazards regression models with a time-dependent exposure to estimate hazard ratios and 95% CIs for the association. RESULTS: After controlling for potential confounding factors including demographic, lifestyle, clinical variables, and PM2.5, radon exposure was significantly associated with incident ischemic stroke among never-smokers (hazard ratio, 1.39 [95% CI, 1.01-1.90]) but not ever-smokers. The results were generally consistent in the sensitivity analysis when using radon measures from state/Environmental Protection Agency residential radon survey. CONCLUSIONS: Findings from this study suggest that the association between residential radon exposure and incidence of ischemic stroke varies by smoking status and may be prominent in never-smokers. Further studies incorporating indoor-radon measures are needed to confirm these findings.

Examining the potential impacts of intensive blood pressure treatment on the socioeconomic inequity in hypertension prevalence in China: a nationally representative cross-sectional study.

Few studies focused on the equity of hypertension prevalence before and after the diagnostic threshold change. The study aimed to analyze the 130/80 mmHg hypertension diagnostic threshold on the equity of hypertension prevalence in China. The baseline survey data from the China Health and Retirement Longitudinal Study (CHARLS) conducted from 2011 to 2012 were utilized to evaluate the impact of the 130/80 mmHg diagnostic threshold on the equity of hypertension prevalence in China using the concentration index and its decomposition which was an index reflecting the health inequality caused by social and economic factors. The prevalence of hypertension was 41.56% and 57.33% under the diagnostic thresholds of 140/90 mmHg and 130/80 mmHg, respectively. The concentration index for hypertension prevalence in China was -0.017 (95%CI: -0.028, -0.006) under the 140/90 mmHg threshold and -0.010 (95%CI: -0.018, -0.002) under the 130/80 mmHg threshold. Concentration index decomposition analysis of hypertension prevalence diagnosed at both diagnostic thresholds showed that age, BMI, and economic status contributed more to the inequitable situation of hypertension prevalence. Higher age, higher BMI, and poorer economic status increased the inequity of hypertension prevalence. No significant difference in the increase in hypertension among individuals of different economic status after implementing the blood pressure control standard (130/80 mmHg), and the prevalence of hypertension in the region did not show a significant bias towards the low economic status population. Therefore, implementing this standard will not increase the risk of hypertension prevalence biased toward people of low economic status. Implementing the 130/80 mmHg diagnostic threshold will not increase the risk of hypertension prevalence biased towards people of low economic status.

Cu2ZnSnS4 (CZTS) for Photoelectrochemical CO2 Reduction: Efficiency, Selectivity, and Stability.

Massive emissions of carbon dioxide (CO2) have caused environmental issues like global warming, which needs to be addressed. Researchers have developed numerous methods to reduce CO2 emissions. Among these, photoelectrochemical (PEC) CO2 reduction is a promising method for mitigating CO2 emissions. Recently, Cu2ZnSnS4 (CZTS) has been recognized as good photocathode candidate in PEC systems for CO2 reduction due to its earth abundance and non-toxicity, as well as its favourable optical/electrical properties. The performance of PEC CO2 reduction can be evaluated based on its efficiency, selectivity, and stability, which are significantly influenced by the photocathode materials. As a result, researchers have applied various strategies to improve the performance of CZTS photocathodes, including band structure engineering and surface catalytic site engineering. This review provides an overview of advanced methods to enhance the PEC systems for CO2 reduction, focusing on CZTS.