A study on the monitoring of heatwaves and bivariate frequency analysis based on mortality risk assessment in Wuhan, China.

The increasingly frequent occurrence of urban heatwaves has become a significant threat to human health. To quantitatively analyze changes in heatwave characteristics and to investigate the return periods of future heatwaves in Wuhan City, China, this study extracted 9 heatwave definitions and divided them into 3 mortality risk levels to identify and analyze historical observations and future projections of heatwaves. The copula functions were employed to derive the joint distribution of heatwave severity and duration and to analyze the co-occurrence return periods. The results demonstrate the following. (1) As the concentration of greenhouse gas emissions increases, the severity of heatwaves intensifies, and the occurrence of heatwaves increases significantly; moreover, a longer duration of heatwaves correlated with higher risk levels in each emission scenario. (2) Increasing concentrations of greenhouse gas emissions result in significantly shorter heatwave co-occurrence return periods at each level of risk. (3) In the 3 risk levels under each emission scenario, the co-occurrence return periods for heatwaves become longer as heatwave severity intensifies and duration increases. Under the influence of climate change, regional-specific early warning systems for heatwaves are necessary and crucial for policymakers to reduce heat-related mortality risks in the population, especially among vulnerable groups.

Transition and trend analysis of the burden of depression in China and different income countries: Based on GBD database and joinpoint regression model.

BACKGROUND: Depression is a leading cause of disability and poor health worldwide and is expected to rank first worldwide by 2030. The aim of this study is to analyze the transition and trend of depression burden in China and various income-level countries by utilizing the Global Burden of Disease (GBD) database and the Joinpoint regression model. This analysis seeks to comprehend the variations in the burden of depression across different income regions and evaluate their developmental patterns. METHODS: Based on the GBD 2019 open dataset, this study extracted data on YLD (Years Lived with Disability), DALY (Disability-Adjusted Life Years), and incidence related to depression. The analysis focused on the period between 1990 and 2019, covering global data and distinguishing between high-income, upper-middle-income, lower-middle-income, low-income countries, and China. We utilized the Joinpoint regression model to fit the spatiotemporal trend changes among different income-level countries. Pairwise comparisons were conducted to examine the parallelism and to determine if the differences in trend changes among various regions were statistically significant. RESULTS: From 1990 to 2019, the age-standardized YLD and DALY for depression female were higher than that in male. The YLD total change rate of depression men was higher than that of women. China exhibited the largest disparity in total YLD change rates between genders, reaching 0.08. During 1990 to 2019, the incidence of depression in 2005-2019 increased among females in middle to high-income countries, low-income countries, and China as compare to that of 1990-2005. Notably, China shown the most increase the incidence rate of females (from -0.4 % to 0.84 %). China experienced the most significant change in the YLD of depression during this period (AAPC = 0.45, 95 % CI = 0.41, 0.48, P < 0.01). China's YLD/Incidence rate was higher compared to the global, HICs, UMCs, LMCs, and LICs. In China, the YLD/incidence rate of depression began to rise in 1994, peaking around 2010, and then gradually declining. Since 2010, the growth rate of depression DALYs in China has been higher than the global average, high-income countries, upper-middle-income countries, lower-middle-income countries, and low-income countries. The DALY's AAPC value for the HLCs was the highest (AAPC = 0.24, 95 % CI = 0.22, 0.25, P < 0.01). The UMCs, in comparison to other regions, incidence rate had the highest AAPC value (AAPC = 0.48, 95 % CI = 0.46, 0.50, P < 0.01). CONCLUSIONS: Given the significant variations in the burden of depression across countries with different income levels, future strategies aimed at reducing the burden of depression should adopt tailored and differentiated approaches according to each country's specific needs and developmental stages.

Role of acupuncture in improving the outcome of sepsis-induced lung injury.

OBJECTIVE: The purpose of this study was to investigate the effect of serum exosomes of mice after acupuncture (acu-exo) on acute lung injury (ALI) in sepsis in vitro and in vivo. METHODS: Serum exosomes (acu-exo) of normal mice were prepared after acupuncture. Lipopolysaccharide (LPS) was used to establish the model of ALI in vivo and in vitro. Immunohistochemistry, western blot, and immunofluorescence were used to evaluate the mechanism of acu-exo on ALI. P2X7 knockout mice and P2X7 siRNA were used to verify the mechanism. RESULTS: Compared with normal mice, serum exosomes were significantly increased in normal mice after acupuncture. The results showed that P2X7 was increased in the lung of septic mice as compared with the WT group. It was also found that the increase in NLRP3 and NF-κB was accompanied by the activation of P2X7. Increased P2X7 led to activation of the P2X7 receptor causing mitochondrial dysfunctions in lung tissue of septic mice. Knockout of P2X7 or silenced P2X7 markedly decreased NLRP3 and NF-κB and led to mitochondrial function recovery in lung tissue of sepsis. At the same time, acu-exo significantly restored the above changes in the lung tissue of septic mice. CONCLUSIONS: Inhibition of P2X7 led to mitochondrial function recovery of lung tissue by inhibiting NLRP3 and NF-κB. At the same time, acu-exo could improve ALI by decreasing NLRP3 and NF-κB activation.

Quantitative measurements of dual-energy CT parameters in the diagnosis of osteoporosis - a highly sensitive and specific technique: An observational study.

With the aging of the population in our society, osteoporosis (OP) has become one of the chronic diseases that seriously threaten the physical health of the elderly, leading to a heavy burden on healthcare. In recent years, with the continuous development of dual-energy CT (DECT) technology, quantitative measurements of DECT parameters, which is highly sensitive to OP, provides accurate results, is convenient and cost-effective, and is expected to be widely used in bone density testing. This study was aimed to explore the value of quantitative measurements of DECT parameters in diagnosing OP, in order to better guide clinical judgments and treatment. A total of 187 patients who underwent dual-energy X-ray and DECT examinations at Tianjin hospital between January 2022 and June 2023 were included as participants in this study. The bone mineral density (BMD) values of the lumbar spine (L1-L4) were determined using dual-energy X-ray absorptiometry. Simultaneously, CT scans of the lumbar spine (L1-L4) were conducted to measure the CT values of contrast media (CM), mixed-energy image CT values (regular CT value [rCT]), calcium concentration (CaD), as well as fat fraction (FF). Pearson correlation analysis was used to examine the relationship between the quantitative measurements of L1 to L4 vertebral bodies obtained from DECT and BMD. The values of CM, rCT, and CaD in the OP group were all lower than those in the non-OP group with statistical significance (P < .001). Conversely, the fat fraction parameter value in the OP group was significantly higher in contrast with the non-OP group (P = .004); there was a positive correlation between CM, rCT, CaD, and BMD values (R = 0.579, P < .001; R = 0.604, P < .001; R = 0.563, P < .001); CM, rCT, and CaD had high diagnostic value for OP, as evidenced by AUCs of 0.935 (95% CI: 0.900-0.971), 0.956 (95% CI: 0.925-0.987), and 0.926 (95% CI: 0.858-0.954), respectively, all with P values < .001. Quantitative measurement of DECT parameters showed a high sensitivity as well as a high specificity in the diagnosis of OP. It is also highly feasible and holds significant clinical diagnostic value, making it a suitable candidate for widespread application.

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper we first introduced an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), which learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, we selected interpolating data points in the learned latent space that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-ß 1-42 (Aß42) monomer, our deep learning model provided a comprehensive sampling of Aß42's conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. This approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.

Applications of Biosensors in Bladder Cancer.

Bladder cancer (BC) is the tenth most common cancer globally, predominantly affecting men. Early detection and treatment are crucial due to high recurrence rates and poor prognosis for advanced stages. Traditional diagnostic methods like cystoscopy and imaging have limitations, leading to the exploration of noninvasive methods such as liquid biopsy. This review highlights the application of biosensors in BC, including electrochemical and optical sensors for detecting tumor markers like proteins, nucleic acids, and other biomolecules, noting their clinical relevance. Emerging therapeutic approaches, such as antibody-drug conjugates, targeted therapy, immunotherapy, and gene therapy, are also explored, the role of biosensors in detecting corresponding biomarkers to guide these treatments is examined. Finally, the review addresses the current challenges and future directions for biosensor applications in BC, highlighting the need for large-scale clinical trials and the integration of advanced technologies like deep learning to enhance diagnostic accuracy and treatment efficacy.

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper first an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), is developed that learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, interpolating data points in the learned latent space are selected that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-ß1-42 (Aß42) monomer, our deep learning model provided a comprehensive sampling of Aß42's conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. The proposed approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.

Histamine promotes mouse decidualization through stimulating epithelial amphiregulin release.

Accumulating evidence shows that inflammation is essential for embryo implantation and decidualization. Histamine, a proinflammatory factor that is present in almost all mammalian tissues, is synthesized through decarboxylating histidine by histidine decarboxylase (HDC). Although histamine is known to be essential for decidualization, the underlying mechanism remains undefined. In the present study, histamine had no obvious direct effects on in vitro decidualization in mice. However, the obvious differences in HDC protein levels between day 4 of pregnancy and day 4 of pseudopregnancy, as well as between delayed and activated implantation, suggested that the blastocyst may be involved in regulating HDC expression. Furthermore, blastocyst-derived tumor necrosis factor α (TNFα) significantly increased HDC levels in the luminal epithelium. Histamine increased the levels of amphiregulin (AREG) and disintegrin and metalloproteinase domain-containing protein 17 (ADAM17) proteins, which was abrogated by treatment with famotidine, a specific histamine type 2 receptor (H2R) inhibitor, or by TPAI-1 (a specific inhibitor of ADAM17). Intraluminal injection of urocanic acid (HDC inhibitor) on day 4 of pregnancy significantly reduced the number of implantation sites on day 5 of pregnancy. TNFα-stimulated increases in HDC, AREG and ADAM17 protein levels was abrogated by urocanic acid, a specific inhibitor of HDC. Additionally, AREG treatment significantly promoted in vitro decidualization. Collectively, our data suggests that blastocyst-derived TNFα induces luminal epithelial histamine secretion, and histamine increases mouse decidualization through ADAM17-mediated AREG release.

The first specific probe for pyrrolidine with multifunction by the interaction mechanism of atomic economic reaction.

Pyrrolidine (PyD) has an important impact on the environment and human health. However, there is currently no method for trace detection of PyD. Here, we successfully designed diaminomethylene-4H-pyran (1) as the first specific fluorescent probe for PyD. Only by adding PyD to probe 1, there is blue fluorescence at 455 nm, and the color of the solution changes from colorless to yellow. The detection limit is 1.12 × 10-6 M, and the response time is less than 5 min. Meanwhile, probe 1 can also sense the gaseous PyD and detect PyD in actual water samples. Moreover, due to the low biological toxicity, probe 1 can detect the exogenous PyD in zebrafish. The preliminary mechanism shows that probe 1 and PyD undergo a combination-type chemical reaction to generate a new substance 1-PyD. Therefore, the 100% atom utilization reaction enables probe 1 to exhibit specific adsorption and removal of PyD.

Helicobacter pylori East Asian type CagA hijacks more SHIP2 by its EPIYA-D motif to potentiate the oncogenicity.

CagA is a significant oncogenic factor injected into host cells by Helicobacter pylori, which is divided into two subtypes: East Asian type (CagAE), characterized by the EPIYA-D motif, and western type (CagAW), harboring the EPIYA-C motif. CagAE has been reported to have higher carcinogenicity than CagAW, although the underlying reason is not fully understood. SHIP2 is an intracellular phosphatase that can be recruited by CagA to perturb the homeostasis of intracellular signaling pathways. In this study, we found that SHIP2 contributes to the higher oncogenicity of CagAE. Co-Immunoprecipitation and Pull-down assays showed that CagAE bind more SHIP2 than CagAW. Immunofluorescence staining showed that a higher amount of SHIP2 recruited by CagAE to the plasma membrane catalyzes the conversion of PI(3,4,5)P3 into PI(3,4)P2. This alteration causes higher activation of Akt signaling, which results in enhanced IL-8 secretion, migration, and invasion of the infected cells. SPR analysis showed that this stronger interaction between CagAE and SHIP2 stems from the higher affinity between the EPIYA-D motif of CagAE and the SH2 domain of SHIP2. Structural analysis revealed the crucial role of the Phe residue at the Y + 5 position in EPIYA-D. After mutating Phe of CagAE into Asp (the corresponding residue in the EPIYA-C motif) or Ala, the activation of downstream Akt signaling was reduced and the malignant transformation of infected cells was alleviated. These findings revealed that CagAE hijacks SHIP2 through its EPIYA-D motif to enhance its carcinogenicity, which provides a better understanding of the higher oncogenic risk of H. pylori CagAE.

Associations between accelerometer-measured physical activity and sedentary behaviour with physical function among older women: a cross-sectional study.

BACKGROUND: This study aimed to investigate the relationships between accelerometer-measured physical activity (PA) and sedentary behaviour (SB) with physical function (PF) among older Chinese women in the community. METHODS: The present study comprised 1,113 community-dwelling older females, with an average age of 65 ± 2 years. We employed a linear regression analysis to investigate the relationship between patterns of PA and SB with PF. PA variables consisted of total PA time, bouted PA time (a continuous PA that lasts equal to or more than 10 min), and sporadic PA time (a continuous PA that lasts less than 10 min). SB variables included total SB time, 30-min bout of SB (a continuous SB that lasts equal to or more than 30 min), and 60-min bout of SB (a continuous SB that lasts equal to or more than 60 min). PF variables comprised handgrip strength (HGS), one-legged stance test with eyes closed (OLSTEC), usual walking speed (UWS), maximum walking speed (MWS) and chair-stand time (CT). To explore the joint effects of moderate-to-vigorous-intensity PA (MVPA) and SB on PF, we divided the duration of SB and MVPA participation in older women into different combinations: low MVPA & high SB, low MVPA & low SB, high MVPA & high SB, high MVPA & low SB. RESULTS: The study revealed a significant association between 30-min bout of SB and CT, which remained after adjusting for total MVPA time (P = 0.021). Both total MVPA and bouted MVPA were found to be positively associated with better UWS, MWS, CT, and PF Z-score. When the combination of low MVPA & high SB was used as a reference, the regression coefficients for PF ascended by 1.32 (P < 0.001) in the high MVPA & high SB group and by 1.13 (P < 0.001) in the high MVPA & low SB group. CONCLUSIONS: A significant association was observed between poorer lower limb function and prolonged, uninterrupted SB in older women, rather than with the total SB time. Concurrently, the insufficient engagement in MVPA may also be a crucial factor contributing to poorer PF in older women. Engaging in longer durations and higher intensity of PA, such as bouts of MVPA lasting a minimum of 10 min or longer, may contribute to better PF.

Antiferromagnetic phase transition in a 3D fermionic Hubbard model.

The fermionic Hubbard model (FHM)1 describes a wide range of physical phenomena resulting from strong electron-electron correlations, including conjectured mechanisms for unconventional superconductivity. Resolving its low-temperature physics is, however, challenging theoretically or numerically. Ultracold fermions in optical lattices2,3 provide a clean and well-controlled platform offering a path to simulate the FHM. Doping the antiferromagnetic ground state of a FHM simulator at half-filling is expected to yield various exotic phases, including stripe order4, pseudogap5, and d-wave superfluid6, offering valuable insights into high-temperature superconductivity7-9. Although the observation of antiferromagnetic correlations over short10 and extended distances11 has been obtained, the antiferromagnetic phase has yet to be realized as it requires sufficiently low temperatures in a large and uniform quantum simulator. Here we report the observation of the antiferromagnetic phase transition in a three-dimensional fermionic Hubbard system comprising lithium-6 atoms in a uniform optical lattice with approximately 800,000 sites. When the interaction strength, temperature and doping concentration are finely tuned to approach their respective critical values, a sharp increase in the spin structure factor is observed. These observations can be well described by a power-law divergence, with a critical exponent of 1.396 from the Heisenberg universality class12. At half-filling and with optimal interaction strength, the measured spin structure factor reaches 123(8), signifying the establishment of an antiferromagnetic phase. Our results provide opportunities for exploring the low-temperature phase diagram of the FHM.

Chemoprophylaxis Effect of EGCG on the Recurrence of Colorectal Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND AND AIMS: The recurrence rate of Colorectal Cancer (CRC) after cure is always high. The purpose of this study was to investigate whether green tea extract (-)-Epigallocatechin gallate (EGCG) has an effective preventive effect on the recurrence of CRC. METHODS: We conducted a systematic literature review and meta-analysis of the effects of taking EGCG or placebo on disease recurrence in patients after colon polyp removal. RESULTS: Five Randomized Controlled Trials (RCTs) were included in this review. A double-blind drug trial involving 1389 participants involved EGCG and placebo. The results showed no significant publication bias or heterogeneity in the five studies (I2 = 38%; p = 0.17). Patients taking EGCG had a lower recurrence rate of CRC than those in the placebo group. The results were statistically significant (Z=2.83, p < 0.05). CONCLUSION: This study demonstrated that long-term EGCG can prevent CRC recurrence to a certain extent.

Correlation between serum trimethylamine-N-oxide and body fat distribution in middle-aged and older adults: a prospective cohort study.

BACKGROUND: Trimethylamine-N-oxide (TMAO) is linked with obesity, while limited evidence on its relationship with body fat distribution. Herein, we investigated the associations between serum TMAO and longitudinal change of fat distribution in this prospective cohort study. METHODS: Data of 1964 participants (40-75y old) from Guangzhou Nutrition and Health Study (GNHS) during 2008-2014 was analyzed. Serum TMAO concentration was quantified by HPLC-MS/MS at baseline. The body composition was assessed by dual-energy X-ray absorptiometry at each 3-y follow-up. Fat distribution parameters were fat-to-lean mass ratio (FLR) and trunk-to-leg fat ratio (TLR). Fat distribution changes were derived from the coefficient of linear regression between their parameters and follow-up duration. RESULTS: After an average of 6.2-y follow-up, analysis of covariance (ANCOVA) and linear regression displayed women with higher serum TMAO level had greater increments in trunk FLR (mean ± SD: 1.47 ± 4.39, P-trend = 0.006) and TLR (mean ± SD: 0.06 ± 0.24, P-trend = 0.011). Meanwhile, for women in the highest TMAO tertile, linear mixed-effects model (LMEM) analysis demonstrated the annual estimated increments (95% CI) were 0.03 (95% CI: 0.003 - 0.06, P = 0.032) in trunk FLR and 1.28 (95% CI: -0.17 - 2.73, P = 0.083) in TLR, respectively. In men, there were no similar significant observations. Sensitivity analysis yielded consistent results. CONCLUSION: Serum TMAO displayed a more profound correlation with increment of FLR and TLR in middle-aged and older community-dwelling women in current study. More and further studies are still warranted in the future. TRIAL REGISTRATION: NCT03179657.

Research on the mechanism of sea buckthorn leaf Fu tea in the treatment of hyperlipidemia.

Background: Hyperlipidemia (HLP) presents a significant challenge to global public health. Mounting evidence suggests that statins, the recommended first-line lipid-lowering agents, have significant adverse effects. Consequently, the quest for natural and efficacious alternative therapies is steadily emerging as a research priority for HLP prevention and treatment. Consumption of tea, which is rich in diverse biologically active compounds with the capacity to regulate lipid metabolism and combat obesity, has emerged as a promising alternative therapy. Sea buckthorn leaves are rich in a multitude of biologically active substances, have a hypolipidemic effect, and can be used as a raw material for tea because of their unique flavor. There is a suggestion that combining Aspergillus cristatus with tea could modify or boost the lipid-lowering active compounds present in tea, thereby increasing its efficacy in regulating lipid metabolism. Results: Sea Buckthorn Leaf Fu Tea (SBLFT) was obtained by fermentation when sea buckthorn leaves contained 42 % moisture, inoculated with Aspergillus cristatus 0.2 mL/g, and incubated for 8 d at constant temperature. Animal experiments demonstrated that SBLFT significantly inhibited body weight gain in HLP rats and reduced lipid content and serum oxidative stress. In addition, liver tissue sections and functional indices showed that SBLFT can improve liver morphology and function abnormalities. Reverse transcription-polymerase chain reaction results indicated that the expression of Liver kinase B1 (LKB1), adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK), acetyl CoA carboxylase 1 (ACC1), and sterol-regulatory element binding protein-1 (SREBP1c) gene related to lipid metabolism was altered. Conclusion: SBLFT improved HLP, specifically via promoting the expression of LKB1 in the liver of HLP rats, activating AMPK, and inhibiting ACC1 and SREBP1c expression, resulting in the inhibition of fatty acid and triglyceride synthesis-related enzymes at the transcriptional level.

Highly Regular Layered Structure via Dual-Spatially-Confined Alignment of Nanosheets Enables High-Performance Nanocomposites.

Assembling ultrathin nanosheets into layered structure represents one promising way to fabricate high-performance nanocomposites. However, how to minimize the internal defects of the layered assemblies to fully exploit the intrinsic mechanical superiority of nanosheets remains challenging. Here, a dual-scale spatially confined strategy for the co-assembly of ultrathin nanosheets with different aspect ratios into a near-perfect layered structure is developed. Large-aspect-ratio (LAR) nanosheets are aligned due to the microscale confined space of a flat microfluidic channel, small-aspect-ratio (SAR) nanosheets are aligned due to the nanoscale confined space between adjacent LAR nanosheets. During this co-assembly process, SAR nanosheets can flatten LAR nanosheets, thus reducing wrinkles and pores of the assemblies. Benefiting from the precise alignment (orientation degree of 90.74%) of different-sized nanosheets, efficient stress transfer between nanosheets and interlayer matrix is achieved, resulting in layered nanocomposites with multiscale mechanical enhancement and superior fatigue durability (100 000 bending cycles). The proposed co-assembly strategy can be used to orderly integrate high-quality nanosheets with different sizes or diverse functions toward high-performance or multifunctional nanocomposites.

Single-cell RNA-sequencing provides new insights into the cell-specific expression patterns and transcriptional regulation of photosynthetic genes in bermudagrass leaf blades.

As an important warm-season turfgrass species, bermudagrass (Cynodon dactylon L.) flourishes in warm areas around the world due to the existence of the C4 photosynthetic pathway. However, how C4 photosynthesis operates in bermudagrass leaves is still poorly understood. In this study, we performed single-cell RNA-sequencing on 5296 cells from bermudagrass leaf blades. Eight cell clusters corresponding to mesophyll, bundle sheath, epidermis and vascular bundle cells were successfully identified using known cell marker genes. Expression profiling indicated that genes encoding NADP-dependent malic enzymes (NADP-MEs) were highly expressed in bundle sheath cells, whereas NAD-ME genes were weakly expressed in all cell types, suggesting C4 photosynthesis of bermudagrass leaf blades might be NADP-ME type rather than NAD-ME type. The results also indicated that starch synthesis-related genes showed preferential expression in bundle sheath cells, whereas starch degradation-related genes were highly expressed in mesophyll cells, which agrees with the observed accumulation of starch-filled chloroplasts in bundle sheath cells. Gene co-expression analysis further revealed that different families of transcription factors were co-expressed with multiple C4 photosynthesis-related genes, suggesting a complex transcription regulatory network of C4 photosynthesis might exist in bermudagrass leaf blades. These findings collectively provided new insights into the cell-specific expression patterns and transcriptional regulation of photosynthetic genes in bermudagrass.

The Bioactive Compounds of Epimedium and Their Potential Mechanism of Action in Treating Osteoporosis: A Network Pharmacology and Experimental Validation Study.

Osteoporosis is a global health challenge characterized by bone loss and microstructure deterioration, which urgently requires the development of safer and more effective treatments due to the significant adverse effects and limitations of existing drugs for long-term treatment. Traditional Chinese medicine, like Epimedium, offers fewer side effects and has been used to treat osteoporosis, yet its active compounds and pharmacological mechanisms remain unclear. In this study, 65 potential active compounds, 258 potential target proteins, and 488 pathways of Epimedium were identified through network pharmacology analysis. Further network analysis and review of the literature identified six potential active compounds and HIF-1α for subsequent experimental validation. In vitro experiments confirmed that 2″-O-RhamnosylIcariside II is the most effective compound among the six potential active compounds. It can promote osteoblast differentiation, bind with HIF-1α, and inhibit both HIF-1α gene and protein expression, as well as enhance COL1A1 protein expression under hypoxic conditions. In vivo experiments demonstrated its ability to improve bone microstructures and reduce bone loss by decreasing bone marrow adipose tissue, enhancing bone formation, and suppressing HIF-1α protein expression. This study is the first to describe the therapeutic effects of 2-O-RhamnosylIcariside II on osteoporosis, which was done, specifically, through a mechanism that targets and inhibits HIF-1α. This study provides a scientific basis for the clinical application of Epimedium and offers a new candidate drug for the treatment of osteoporosis. Additionally, it provides new evidence supporting HIF-1α as a therapeutic target for osteoporosis.

Impact of National Lockdown Measures on the Association Between Social Media Use and Sleep Disturbance During COVID-19: A Meta-Analysis of 21 Nations.

During the COVID-19 pandemic, the extensive lockdown measures implemented for disease mitigation triggered a surge in round-the-clock social media use, giving rise to widespread concerns regarding its impact on sleep health. This meta-analysis examined the association between social media use and sleep disturbance during the pandemic, along with potential moderators. The dataset included 43 independent samples comprising 68,247 residents of 21 countries across 7 world regions. The three-level mixed-effects meta-analysis revealed a weak, positive overall effect size (r = 0.1296, 95% confidence interval: 0.0764-0.1828, k = 90). The magnitude of the effect size varied by the type of social media use: compulsive use exhibited a moderately strong effect size, whereas information-focused use showed marginal significance. The effect size was more pronounced in countries imposing stricter (vs. less strict) lockdown measures. Lockdown status also moderated this association, with a marginally significant effect size observed during lockdowns but a significant effect size after lockdowns. For demographics, samples involving emerging adults demonstrated moderately strong effect sizes, whereas those involving the general population had modest effect sizes. Notably, the interaction between the type of social media use and lockdown status was significant. Specifically, the positive association with information-focused use was significant only during lockdowns, whereas that with general use was significant after, but not during, lockdowns. However, compulsive use showed a moderately strong effect size both during and after lockdowns. These findings underscored the importance of considering multiple factors-such as the type of social media use, context, and demographics-when studying social media use and sleep health.

Hotspots and trends of artificial intelligence in the field of cataracts: a bibliometric analysis.

PURPOSE: To analyze the hotspots and trends in artificial intelligence (AI) research in the field of cataracts. METHODS: The Science Citation Index Expanded of the Web of Science Core Collection was used to collect the research literature related to AI in the field of cataracts, which was analyzed for valuable information such as years, countries/regions, journals, institutions, citations, and keywords. Visualized co-occurrence network graphs were generated through the library online analysis platform, VOSviewer, and CiteSpace tools. RESULTS: A total of 222 relevant research articles from 41 countries were selected. Since 2019, the number of related articles has increased significantly every year. China (n = 82, 24.92%), the United States (n = 55, 16.72%) and India (n = 26, 7.90%) were the three countries with the most publications, accounting for 49.54% of the total. The Journal of Cataract and Refractive Surgery (n = 13, 5.86%) and Translational Vision Science & Technology (n = 10, 4.50%) had the most publications. Sun Yat-sen University (n = 25, 11.26%), the Chinese Academy of Sciences (n = 17, 7.66%), and Capital Medical University (n = 16, 7.21%) are the three institutions with the highest number of publications. We discovered through keyword analysis that cataract, diagnosis, imaging, classification, intraocular lens, and formula are the main topics of current study. CONCLUSIONS: This study revealed the hot spots and potential trends of AI in terms of cataract diagnosis and intraocular lens power calculation. AI will become more prevalent in the field of ophthalmology in the future.