Microporous Coordination Polymers for Efficient Recovery of Chloromethane from Organic Silicon Industrial Exhaust Gas.

Removal and recovery of methyl chloride (CH3Cl) from exhaust gas of organic silicon industry is highly important from the perspective of environment and economy. For the first time, a tailor-made microporous coordination polymer (Mn-BDC-TPA) was synthesized and applied to the efficient capture and recovery of CH3Cl from related gas mixtures. The high adsorption capacity of CH3Cl (163.4 cm3/g) and high adsorption selectivity of CH3Cl over other impurity gases (1965 for N2, 65 for CH4, and 16 for C2H6) were achieved at 298 K and 100 kPa due to the dual-cage pore system and larger polarizability of CH3Cl. Dynamic breakthrough experiments demonstrate the excellent CH3Cl recovery performance (capacity of >98 cm3/g and purity of >95%) in one adsorption-desorption cycle from the CH3Cl-involved binary, ternary, or quaternary gas mixture.

The association between the basal metabolic rate and cardiovascular disease: A two-sample Mendelian randomization study.

BACKGROUND: Mendelian randomization analysis was applied to elucidate the causal relationship between the basal metabolic rate (BMR) and common cardiovascular diseases. METHOD: We choose BMR as exposure. BMR is the metabolic rate of the body when the basic physiological activities (blood circulation, breathing and constant body temperature) are maintained. The normal BMR is 1507 kcal/day for men and 1276 kcal/day for women. The dataset was drawn from the public GWAS dataset (GWAS ID: ukb-a-268), collected and analysed by UK biobank, containing 331,307 European males and females. SNPs independently and strongly associated with BMR were used as instrumental variables in the inverse variance weighted analysis. MR-Egger, weighted median, MR pleiotropy residual sum, and outlier methods were also performed, and the sensitivity was evaluated using horizontal pleiotropy and heterogeneity analyses to ensure the stability of the results. RESULTS: An increased BMR is associated with a higher risk of cardiomyopathy (odds ratio [OR] = 2.00, 95% confidence interval [CI], 1.57-2.54, p = 1.87 × 10-8), heart failure (OR = 1.39, 95% CI, 1.27-2.51, p = 8.1 × 10-13), and valvular heart disease (OR = 1.18, 95% CI, 1.10-1.27, p = .00001). However, there was no clear association between BMR and the subtypes of other cardiovascular diseases, such as coronary disease (OR = .96, 95% CI, .85-1.08, p = .48651) and atrial fibrillation (AF) (OR = 1.85, 95% CI, 1.70-2.02, p = 6.28 × 10-44). CONCLUSION: Our study reveals a possible causal effect of BMR on the risk of cardiomyopathy, heart failure and valvular disease, but not for coronary disease and AF.

N and OH-Immobilized Cu3 Clusters In Situ Reconstructed from Single-Metal Sites for Efficient CO2 Electromethanation in Bicontinuous Mesochannels.

Cu-based catalysts hold promise for electrifying CO2 to produce methane, an extensively used fuel. However, the activity and selectivity remain insufficient due to the lack of catalyst design principles to steer complex CO2 reduction pathways. Herein, we develop a concept to design carbon-supported Cu catalysts by regulating Cu active sites' atomic-scale structures and engineering the carbon support's mesoscale architecture. This aims to provide a favorable local reaction microenvironment for a selective CO2 reduction pathway to methane. In situ X-ray absorption and Raman spectroscopy analyses reveal the dynamic reconstruction of nitrogen and hydroxyl-immobilized Cu3 (N,OH-Cu3) clusters derived from atomically dispersed Cu-N3 sites under realistic CO2 reduction conditions. The N,OH-Cu3 sites possess moderate *CO adsorption affinity and a low barrier for *CO hydrogenation, enabling intrinsically selective CO2-to-CH4 reduction compared to the C-C coupling with a high energy barrier. Importantly, a block copolymer-derived carbon fiber support with interconnected mesopores is constructed. The unique long-range mesochannels offer an H2O-deficient microenvironment and prolong the transport path for the CO intermediate, which could suppress the hydrogen evolution reaction and favor deep CO2 reduction toward methane formation. Thus, the newly developed catalyst consisting of in situ constructed N,OH-Cu3 active sites embedded into bicontinuous carbon mesochannels achieved an unprecedented Faradaic efficiency of 74.2% for the CO2 reduction to methane at an industry-level current density of 300 mA cm-2. This work explores effective concepts for steering desirable reaction pathways in complex interfacial catalytic systems via modulating active site structures at the atomic level and engineering pore architectures of supports on the mesoscale to create favorable microenvironments.

Hydrogen bond unlocking-driven pore structure control for shifting multi-component gas separation function.

Purification of ethylene (C2H4) as the most extensive and output chemical, from complex multi-components is of great significance but highly challenging. Herein we demonstrate that precise pore structure tuning by controlling the network hydrogen bonds in two highly-related porous coordination networks can shift the efficient C2H4 separation function from C2H2/C2H4/C2H6 ternary mixture to CO2/C2H2/C2H4/C2H6 quaternary mixture system. Single-crystal X-ray diffraction revealed that the different amino groups on the triazolate ligands resulted in the change of the hydrogen bonding in the host network, which led to changes in the pore shape and pore chemistry. Gas adsorption isotherms, adsorption kinetics and gas-loaded crystal structure analysis indicated that the coordination network Zn-fa-atz (2) weakened the affinity for three C2 hydrocarbons synchronously including C2H4 but enhanced the CO2 adsorption due to the optimized CO2-host interaction and the faster CO2 diffusion, leading to effective C2H4 production from the CO2/C2H2/C2H4/C2H6 mixture in one step based on the experimental and simulated breakthrough data. Moreover, it can be shaped into spherical pellets with maintained porosity and separation performance.

Does cleavage stage morphology increase the discriminatory power of prediction in blastocyst transfer outcome?

PURPOSE: To evaluate the contribution of the cleavage stage morphological parameters to the prediction of blastocyst transfer outcomes. METHODS: A retrospective study was conducted on 8383 single-blastocyst transfer cycles including 2246 fresh and 6137 vitrified-warmed cycles. XGboost, LASSO, and GLM algorithms were employed to establish models for assessing the predictive value of the cleavage stage morphological parameters in transfer outcomes. Four models were developed using each algorithm: all-in model with or without day 3 morphology and embryo quality-only model with or without day 3 morphology. RESULTS: The live birth rate was 48.04% in the overall cohort. The AUCs of the models with the algorithm of XGboost were 0.83, 0.82, 0.63, and 0.60; with LASSO were 0.66, 0.66, 0.61, and 0.60; and with GLM were 0.66, 0.66, 0.61, and 0.60 respectively. In models 1 and 2, female age, basal FSH, peak E2, endometrial thickness, and female BMI were the top five critical features for predicting live birth; In models 3 and 4, the most crucial factor was blastocyst formation on D5 rather than D6. In model 3, incorporating cleavage stage morphology, including early cleavage, D3 cell number, and fragmentation, was significantly associated with successful live birth. Additionally, the live birth rates for blastocysts derived from on-time, slow, and fast D3 embryos were 49.7%, 39.5%, and 52%, respectively. CONCLUSIONS: The value of cleavage stage morphological parameters in predicting the live birth outcome of single blastocyst transfer is limited.

Pretreatment prediction for IVF outcomes: generalized applicable model or centre-specific model?

STUDY QUESTION: What was the performance of different pretreatment prediction models for IVF, which were developed based on UK/US population (McLernon 2016 model, Luke model, Dhillon model, and McLernon 2022 model), in wider populations? SUMMARY ANSWER: For a patient in China, the published pretreatment prediction models based on the UK/US population provide similar discriminatory power with reasonable AUCs and underestimated predictions. WHAT IS KNOWN ALREADY: Several pretreatment prediction models for IVF allow patients and clinicians to estimate the cumulative probability of live birth in a cycle before the treatment, but they are mostly based on the population of Europe or the USA, and their performance and applicability in the countries and regions beyond these regions are largely unknown. STUDY DESIGN, SIZE, DURATION: A total of 26 382 Chinese patients underwent oocyte pick-up cycles between January 2013 and December 2020. PARTICIPANTS/MATERIALS, SETTING, METHODS: UK/US model performance was externally validated according to the coefficients and intercepts they provided. Centre-specific models were established with XGboost, Lasso, and generalized linear model algorithms. Discriminatory power and calibration of the models were compared as the forms of the AUC of the Receiver Operator Characteristic and calibration curves. MAIN RESULTS AND THE ROLE OF CHANCE: The AUCs for McLernon 2016 model, Luke model, Dhillon model, and McLernon 2022 model were 0.69 (95% CI 0.68-0.69), 0.67 (95% CI 0.67-0.68), 0.69 (95% CI 0.68-0.69), and 0.67 (95% CI 0.67-0.68), respectively. The centre-specific yielded an AUC of 0.71 (95% CI 0.71-0.72) with key predictors including age, duration of infertility, and endocrine parameters. All external models suggested underestimation. Among the external models, the rescaled McLernon 2022 model demonstrated the best calibration (Slope 1.12, intercept 0.06). LIMITATIONS, REASONS FOR CAUTION: The study is limited by its single-centre design and may not be representative elsewhere. Only per-complete cycle validation was carried out to provide a similar framework to compare different models in the sample population. Newer predictors, such as AMH, were not used. WIDER IMPLICATIONS OF THE FINDINGS: Existing pretreatment prediction models for IVF may be used to provide useful discriminatory power in populations different from those on which they were developed. However, models based on newer more relevant datasets may provide better calibrations. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Natural Science Foundation of China [grant number 22176159], the Xiamen Medical Advantage Subspecialty Construction Project [grant number 2018296], and the Special Fund for Clinical and Scientific Research of Chinese Medical Association [grant number 18010360765]. TRIAL REGISTRATION NUMBER: N/A.

Metal Selenide-Based Superstructure Nanoarrays with Ultrahigh Capacity for Alkaline Zn Batteries.

Transition metal selenides (TMSs) have great potential as cathode materials for alkaline Zn batteries (AZBs) owing to their high theoretical capacity and metallic conductivity. However, achieving a high specific capacity remains a formidable challenge due to the low structural stability and sluggish reaction kinetics of single-phase TMS. Herein, a facile method for fabricating a robust CoSe2 @Ni3 Se4 @Ni(OH)2 superstructure nanoarray (CNSNA) as an AZB cathode is presented. The sophisticated design enables structural stability and abundant active surface sites for efficient charge storage. Furthermore, the redox mediator K3 [Fe(CN)6 ] is employed to expedite the reaction kinetics and introduce supplementary redox reactions, further enhancing the charge storage capability. Consequently, the CNSNA electrode delivers an exceptional specific capacitance (609.08 mAh g-1 at 1 A g-1 ), surpassing all previously reported selenide-based materials. High-rate capability (239.37 mAh g-1 at 20 A g-1 ) and long cycling stability have also been achieved. The comprehensive charge storage mechanism studies confirmed the structural integrity, kinetic improvement, and high reactivity of the CNSNA superstructure. Moreover, the corresponding AZB based on CNSNA demonstrates an extraordinarily high energy density of 516.58 Wh kg-1 . The work offers guidance in the construction of superstructure-based TMS electrode materials, paving the way for the development of high-performance AZBs.

Assembly of an iron-based complex into a metal-organic framework: a space confinement strategy for isolation of mono-iron complexes to protect from dimerization.

Non-heme mononuclear iron complexes, especially when supported by tripodal tetradentate ligands, show promising C-H bond activation efficiency in catalytic reactions. Nevertheless, they intrinsically decay readily to their dinuclear form, and the dimerization process is inevitable in homogenous solution, which dramatically hinders their further application. Hence, we demonstrate that the mononuclear iron complex [(TPA)FeII-2L]2+ (L = labile ligands, mainly solvent molecules) was successfully encapsulated in a highly robust metal-organic framework UiO-66 via a two-step "ship-in-a-bottle" strategy. The nearly perfect size matching of the octahedral cages of the host UiO-66 provides ideal space confinement for the guest complex to protect from dimerization and dramatically increases the mono-nuclear complex stability compared to its un-confined state. The successful encapsulation of [(TPA)FeII-2L]2+ in UiO-66 was verified thoroughly by spectroscopy, microscopy, N2 adsorption, and electrochemistry characterization techniques. This work shows that encapsulating an unstable molecular complex in MOFs via a two-step "ship-in-a-bottle" strategy highlights opportunities for extending the heterogenization of homogeneous complexes.

The Role of Retinal Dopamine D1 Receptors in Ocular Growth and Myopia Development in Mice.

Dopamine is a key neurotransmitter in the signaling cascade controlling ocular refractive development, but the exact role and site of action of dopamine D1 receptors (D1Rs) involved in myopia remains unclear. Here, we determine whether retinal D1Rs exclusively mediate the effects of endogenous dopamine and systemically delivered D1R agonist or antagonist in the mouse form deprivation myopia (FDM) model. Male C57BL/6 mice subjected to unilateral FDM or unobstructed vision were divided into the following four groups: one noninjected and three groups that received intraperitoneal injections of a vehicle, D1R agonist SKF38393 (18 and 59 nmol/g), or D1R antagonist SCH39166 (0.1 and 1 nmol/g). The effects of these drugs on FDM were further assessed in Drd1-knock-out (Drd1-KO), retina-specific conditional Drd1-KO (Drd1-CKO) mice, and corresponding wild-type littermates. In the visually unobstructed group, neither SKF38393 nor SCH39166 affected normal refractive development, whereas myopia development was attenuated by SKF38393 and enhanced by SCH39166 injections. In Drd1-KO or Drd1-CKO mice, however, these drugs had no effect on FDM development, suggesting that activation of retinal D1Rs is pertinent to myopia suppression by the D1R agonist. Interestingly, the development of myopia was unchanged by either Drd1-KO or Drd1-CKO, and neither SKF38393 nor SCH39166 injections, nor Drd1-KO, affected the retinal or vitreal dopamine and the dopamine metabolite DOPAC levels. Effects on axial length were less marked than effects on refraction. Therefore, activation of D1Rs, specifically retinal D1Rs, inhibits myopia development in mice. These results also suggest that multiple dopamine D1R mechanisms play roles in emmetropization and myopia development.SIGNIFICANCE STATEMENT While dopamine is recognized as a "stop" signal that inhibits myopia development (myopization), the location of the dopamine D1 receptors (D1Rs) that mediate this action remains to be addressed. Answers to this key question are critical for understanding how dopaminergic systems regulate ocular growth and refraction. We report here the results of our study showing that D1Rs are essential for controlling ocular growth and myopia development in mice, and for identifying the retina as the site of action for dopaminergic control via D1Rs. These findings highlight the importance of intrinsic retinal dopaminergic mechanisms for the regulation of ocular growth and suggest specific avenues for exploring the retinal mechanisms involved in the dopaminergic control of emmetropization and myopization.

Inverse CO2/C2H2 separation assisted by coordinated water in a dysprosium(III) metal-organic framework.

An ultramicroporous metal-organic framework (MOF) constructed from dysprosium(III) and oxalate, termed Dy-F-oxa, is carefully studied for inverse separation of CO2 from C2H2. Adsorption experiments and modeling studies reveal that the high CO2 adsorption is attributed to the preferential sites for CO2 by coordinated water. After the equimolar gas mixture breakthrough experiment, C2H2 can be directly produced as a pure effluent.

Oocyte degeneration in a cohort adversely affects clinical outcomes in conventional IVF cycles: a propensity score matching study.

Background: Oocyte degeneration was mostly described in intracytoplasmic sperm injection (ICSI) cycles; there is no report showing the relationship between oocyte degeneration and clinical outcomes in conventional in vitro fertilization (IVF) cycles. This retrospective study using the propensity score (PS) matching method aimed to explore whether the presence of oocyte degeneration in conventional IVF cycles would affect the sibling embryo development potential and clinical outcomes. Methods: Patients with at least one oocyte degenerated after short-term insemination and stripping were defined as the degeneration (DEG) group, while patients with no oocyte degenerated were defined as the non-degeneration (NONDEG) group. The PS matching method was used to control for potential confounding factors, and a multivariate logistic regression analysis was made to evaluate whether the presence of oocyte degeneration would affect the cumulative live birth rate (CLBR). Results: After PS matching, basic characteristics were similar between the two groups, oocyte yield was significantly higher in the DEG group than the NON-DEG group (P < 0.05), mature oocyte number, 2 pronuclear (2PN) embryo number, 2PN embryo clearage rate, "slow" embryo number, "accelerated" embryo number, rate of cycles with total day 3 embryo extended culture, number of frozen embryo transfer (FET) cycles, transferred embryo stage, transferred embryo number, and live birth rate in fresh embryo transfer cycles were all similar between the two groups (P > 0.05), but the 2PN fertilization rate, available embryo number, high-quality embryo number, "normal" embryo number, frozen embryo number, blastocyst formation rate, and no available embryo cycle rate were all significantly lower in the DEG group than the NON-DEG group (P < 0.05). The cumulative live birth rate was also significantly lower in the DEG group than in the NON-DEG group (70.2% vs. 74.0%, P = 0.0019). Multivariate logistic regression analysis further demonstrated that the presence of oocyte degeneration in conventional IVF cycles adversely affects the CLBR both before (OR = 0.83, 95% CI: 0.75-0.92) and after (OR = 0.82, 95% CI: 0.72-0.93) PS matching. Conclusion: Our findings together revealed that the presence of oocyte degeneration in a cohort of oocytes may adversely affect subsequent embryo development potential and clinical outcomes in conventional IVF cycles.

Rocuronium bromide suppresses esophageal cancer via blocking the secretion of C-X-C motif chemokine ligand 12 from cancer associated fibroblasts.

BACKGROUND: Cancer associated fibroblasts (CAFs) communicate metabolically with tumor genesis and development. Rocuronium bromide (RB) is reported to exert certain inhibitory effect on tumor. Here, we investigate the role of RB in esophageal cancer (EC) malignant progression. METHODS: Tumor xenograft models with EC cells were locally and systemically administrated with RB to detect the influence of different administrations on tumor progression. Mouse CAFs PDGFRα+/F4/80- were sorted by Flow cytometry with specific antibodies. CAFs were treated with RB and co-cultured with EC cells. The proliferation, invasion and apoptosis assays of EC cells were performed to detect the influences of RB targeting CAFs on EC cell malignant progression. Human fibroblasts were employed to perform these detections to confirm RB indirect effect on EC cells. The gene expression changes of CAFs response to RB treatment were detected using RNA sequencing and verified by Western blot, immunohistochemistry and ELISA. RESULTS: Tumors in xenograft mice were observed significantly inhibited by local RB administration, but not by systemic administration. Moreover EC cells did not show obvious change in viability when direct stimulated with RB in vitro. However, when CAFs treated with RB were co-cultured with EC cells, obvious suppressions were observed in EC cell malignancy, including proliferation, invasion and apoptosis. Human fibroblasts were employed to perform these assays and similar results were obtained. RNA sequencing data of human fibroblast treated with RB, and Western blot, immunohistochemistry and ELISA results all showed that CXCL12 expression was significantly diminished in vivo and in vitro by RB. EC cells direct treated with CXCL12 showed much higher malignancy. Moreover cell autophagy and PI3K/AKT/mTOR signaling pathway in CAFs were both suppressed by RB which can be reversed by Rapamycin pretreatment. CONCLUSIONS: Our data suggest that RB could repress PI3K/AKT/mTOR signaling pathway and autophagy to block the CXCL12 expression in CAFs, thereby weakening the CXCL12-mediated EC tumor progression. Our data provide a novel insight into the underlying mechanism of RB inhibiting EC, and emphasize the importance of tumor microenvironment (cytokines from CAFs) in modulating cancer malignant progression.

Predicting the unexpected total fertilization failure in conventional in vitro fertilization cycles: What is the role of semen quality?

Background: Male and female gametes factors might contribute to the total fertilization failure (TFF). In first in vitro fertilization (IVF) cycles, decision-making of insemination protocol was mainly based on semen quality for the contribution of female clinical characteristics to TFF remained obscure. The purpose of the study was to evaluate the role of semen quality in predicting unexpected TFF. Methods: A single-center retrospective cohort analysis was performed on 19539 cycles between 2013 and 2021. Two algorithms, a Least Absolute Shrinkage and Selection Operator (LASSO) and an Extreme Gradient Boosting (Xgboost) were used to create models with cycle characteristics parameters. By including semen parameters or not, the contribution of semen parameters to the performance of the models was evaluated. The area under the curve (AUC), the calibration, and the net reclassification index (NRI) were used to evaluate the performance of the models. Results: The prevalence of TFF were .07 (95%CI:0.07-0.08), and .08 (95%CI:0.07-0.09) respectively in the development and validation group. Including all characteristics, with the models of LASSO and Xgboost, TFF was predicted with the AUCs of .74 (95%CI:0.72-0.77) and .75 (95%CI:0.72-0.77) in the validation group. The AUCs with models of LASSO and Xgboost without semen parameters were .72 (95%CI:0.69-0.74) and .73 (95%CI:0.7-0.75). The models of LASSO and Xgboost with semen parameters only gave the AUCs of .58 (95%CI:0.55-0.61) and .57 (95%CI:0.55-0.6). For the overall validation cohort, the event NRI values were -5.20 for the LASSO model and -.71 for the Xgboost while the non-event NRI values were 10.40 for LASSO model and 0.64 for Xgboost. In the subgroup of poor responders, the prevalence was .21 (95%CI:0.18-0.24). With refitted models of LASSO and Xgboost, the AUCs were .72 (95%CI:0.67-0.77) and .69 (95%CI:0.65-0.74) respectively. Conclusion: In unselected patients, semen parameters contribute to limited value in predicting TFF. However, oocyte yield is an important predictor for TFF and the prevalence of TFF in poor responders was high. Because reasonable predicting power for TFF could be achieved in poor responders, it may warrant further study to prevent TFF in these patients.

Metal-Organic Framework Composites and Their Derivatives as Efficient Electrodes for Energy Storage Applications: Recent Progress and Future Perspectives.

Metal-organic frameworks (MOFs) have been important electrochemical energy storage (EES) materials because of their rich species, large specific surface area, high porosity and rich active sites. Nevertheless, the poor conductivity, low mechanical and electrochemical stability of pristine MOFs have hindered their further applications. Although single component MOF derivatives have higher conductivity, self-aggregation often occurs during preparation. Composite design can overcome the shortcomings of MOFs and derivatives and create synergistic effects, resulting in improved electrochemical properties for EES. In this review, recent applications of MOF composites and derivatives as electrodes in different types of batteries and supercapacitors are critically discussed. The advantages, challenges, and future perspectives of MOF composites and derivatives have been given. This review may guide the development of high-performance MOF composites and derivatives in the field of EES.

The carbon footprint response to projected base stations of China's 5G mobile network.

While the rapid expansion of China's 5G mobile network helps to speed up the nation's economic and social development, it tends to release more CO2 due to the 5G's significant energy demand, hampering sustainable development of the 5G network. Previous assessments of CO2 emissions from China's 5G development were based on a projected 5G network ranging from six to fifteen million base stations with the absent of a convincing business model in 5G's application. Under the scenario of business-estimated six million base stations in 2030, the share of electricity consumed by China's 5G networks in 2030 could reach 8.4 % of the national total power generation, causing 0.44 GtCO2/yr CO2 emissions. We collected 5G base station numbers in 2020 and 2021 in 31 provinces and province-level municipalities (PLM), the period with the rapid growth of the 5G base stations in China. We linked these provincial base stations with provincial Gross Domestic Product (GDP), population (POP), and big data development level (BDDL) and established a statistical model to predict 5G base stations by 2030. The model predicted 2-5 million 5G base stations by 2030, considerably lower than the business-projected base station number. Under the model predicted 5G base stations, China's 5G network could yield 0.15-0.29 GtCO2/yr emissions subject to the nation's BDDL from 40 to 80 % by 2030. Both 5G base stations and CO2 emissions are significantly lower than the previous estimates. We decomposed the CO2 footprint of China's 5G networks and assessed the contribution of the number of 5G base stations and mobile data traffic to 5G-induced CO2 emissions. We find that increasing the application of clean energy and promoting energy efficiency can reduce CO2 emissions in the 5G network. To more accurately estimate 5G's climate effect, we propose that it urgently needs to improve vivid 5G business models.

Piezo1 (Piezo-Type Mechanosensitive Ion Channel Component 1)-Mediated Mechanosensation in Macrophages Impairs Perfusion Recovery After Hindlimb Ischemia in Mice.

BACKGROUND: Angiogenesis is a promising strategy for those with peripheral artery disease. Macrophage-centered inflammation is intended to govern the deficiency of the angiogenic response after hindlimb ischemia. However, little is known about the mechanism of macrophage activation beyond signals from cytokines and chemokines. We sought to identify a novel mechanical signal from the ischemic microenvironment that provokes macrophages and the subsequent inflammatory cascade and to investigate the potential role of Piezo-type mechanosensitive ion channels (Piezo) on macrophages during this process. METHODS: Myeloid cell-specific Piezo1 (Piezo-type mechanosensitive ion channel component 1) knockout (Piezo1ΔMΦ) mice were generated by crossing Piezo1fl/fl (LysM-Cre-/-; Piezo1 flox/flox) mice with LysM-Cre transgenic mice to assess the roles of Piezo1 in macrophages after hindlimb ischemia. Furthermore, in vitro studies were carried out in bone marrow-derived macrophages to decipher the underlying mechanism. RESULTS: We found that tissue stiffness gradually increased after hindlimb ischemia, as indicated by Young's modulus. Compared to Piezo2, Piezo1 expression and activation were markedly upregulated in macrophages from ischemic tissues in concurrence with increased tissue stiffness. Piezo1ΔMΦ mice exhibited improved perfusion recovery by enhancing angiogenesis. Matrigel tube formation assays revealed that Piezo1 deletion promoted angiogenesis by enhancing FGF2 (fibroblast growth factor-2) paracrine signaling in macrophages. Conversely, activation of Piezo1 by increased stiffness or the agonist Yoda1 led to reduced FGF2 production in bone marrow-derived macrophages, which could be blocked by Piezo1 silencing. Mechanistically, Piezo1 mediated extracellular Ca2+ influx and activated Ca2+-dependent CaMKII (calcium/calmodulin-dependent protein kinase II)/ETS1 (ETS proto-oncogene 1) signaling, leading to transcriptional inactivation of FGF2. CONCLUSIONS: This study uncovers a crucial role of microenvironmental stiffness in exacerbating the macrophage-dependent deficient angiogenic response. Deletion of macrophage Piezo1 promotes perfusion recovery after hindlimb ischemia through CaMKII/ETS1-mediated transcriptional activation of FGF2. This provides a promising therapeutic strategy to enhance angiogenesis in ischemic diseases.

New emission inventory reveals termination of global dioxin declining trend.

Accurate estimates of spatiotemporally resolved Polychlorinated dibenzo-p-dioxins (PCDD/Fs, or dioxins) emissions are critical for understanding their environmental fate and associated health risks. In this study, by utilizing an empirical regression model for PCDD/Fs emissions, we developed a global emission inventory for 17 toxic PCDD/Fs congeners from 8 source sectors with a spatial resolution of 1° × 1° from 2002 to 2018. The results show that PCDD/Fs emissions decreased by 25.7 % (12.5 kg TEQ) between 2002 and 2018, mostly occurring in upper- and lower-middle income countries. Globally, open-burning processes, waste incineration, ferrous and nonferrous metal production sectors and heat and power generation were the major source sectors of PCDD/Fs. Spatially, high PCDD/Fs emissions were mainly identified in East and South Asia, Southeast Asia, and part of Sub-Saharan Africa. We find that the declining trend of dioxin emissions over the past decades terminated from the early 2010s due to increasing significance of wildfire induced emissions in the total emission. The PCDD/Fs emission inventory developed in the present study was verified by inputting the inventory as initial conditions into an atmospheric transport model, the Canadian Model for Environmental Transport of Organochlorine Pesticides (CanMETOP), to simulate PCDD/Fs concentrations in air and soil. The predicted concentrations were compared to field sampling data. The good agreement between the modeled and measured concentrations demonstrates the reliability of the inventory.

Application analysis of digital neural network-based data mining method in maximizing the performance of sports training / Análise de aplicação do método de mineração de dados baseado em rede neural digital na maximização do desempenho do treinamento esportivo / Análisis de la aplicación del método de minería de datos basado en redes neuronales digitales para maximizar el rendimiento del entrenamiento deportivo

ABSTRACT Introduction: In today's rapid development of science and technology, digital network data mining technology is developing as fast as the expansion of the frontiers of science and technology allows, with a very broad application level, covering most of the civilized environment. However, there is still much to explore in the application of sports training. Objective: Analyze the feasibility of data mining based on the digital network of sports training, maximizing athletes' training. Methods: This paper uses the experimental analysis of human FFT, combined with BP artificial intelligence network and deep data mining technology, to design a new sports training environment. The controlled test of this model was designed to compare advanced athletic training modalities with traditional modalities, comparing the athletes' explosive power, endurance, and fitness. Results: After 30 days of physical training, the athletic strength of athletes with advanced fitness increased by 15.33%, endurance increased by 15.85%, and fitness increased by 14.23%. Conclusion: The algorithm designed in this paper positively impacts maximizing athletes' training. It may have a favorable impact on training outcomes, as well as increase the athlete's interest in the sport. Level of evidence II; Therapeutic studies - investigating treatment outcomes.

RESUMO Introdução: No rápido desenvolvimento atual de ciência e tecnologia, a tecnologia de mineração de dados de rede digital desenvolve-se tão rápido quanto a expansão das fronteiras da ciência e tecnologia permitem, com um nível de aplicação muito amplo, cobrindo a maior parte do ambiente civilizado. No entanto, ainda há muito para explorar da aplicação no treinamento esportivo. Objetivo: Análise de viabilidade da mineração de dados com base na rede digital da formação esportiva, maximizar o treinamento dos atletas. Métodos: Este trabalho utiliza a análise experimental da FFT humana, combinada com a rede de inteligência artificial da BP e tecnologia de mineração profunda de dados, para projetar um novo ambiente de treinamento esportivo. O teste controlado deste modelo foi projetado para comparar modalidades avançadas de treinamento atlético com as modalidades tradicionais, comparando o poder explosivo, resistência e condição física do atleta. Resultados: Após 30 dias de treinamento físico, a força atlética dos esportistas com aptidão física avançada aumentou 15,33%, a resistência aumentou 15,85%, e o condicionamento físico aumentou 14,23%. Conclusão: O algoritmo desenhado neste artigo tem um impacto positivo na maximização do treinamento dos atletas. Pode ter um impacto favorável nos resultados do treinamento, bem como aumentar o interesse do atleta pelo esporte. Nível de evidência II; Estudos terapêuticos - investigação dos resultados do tratamento.

RESUMEN Introducción: En el rápido desarrollo actual de la ciencia y la tecnología, la tecnología de extracción de datos de redes digitales se desarrolla tan rápido como lo permiten las fronteras en expansión de la ciencia y la tecnología, con un nivel de aplicación muy amplio que abarca la mayor parte del entorno civilizado. Sin embargo, aún queda mucho por explorar de la aplicación en el entrenamiento deportivo. Objetivo: Análisis de viabilidad de la minería de datos basada en la red digital de entrenamiento deportivo, maximizar la formación de los atletas. Métodos: Este trabajo utiliza el análisis experimental de la FFT humana, combinado con la red de inteligencia artificial BP y la tecnología de minería de datos profunda, para diseñar un nuevo entorno de entrenamiento deportivo. La prueba controlada de este modelo se diseñó para comparar las modalidades de entrenamiento atlético avanzado con las modalidades tradicionales, comparando la potencia explosiva, la resistencia y la forma física del atleta. Resultados: Después de 30 días de entrenamiento físico, la fuerza atlética de los atletas con un estado físico avanzado aumentó en un 15,33%, la resistencia aumentó en un 15,85% y el estado físico aumentó en un 14,23%. Conclusión: El algoritmo diseñado en este trabajo tiene un impacto positivo en la maximización del entrenamiento de los atletas. Puede tener un impacto favorable en los resultados del entrenamiento, así como aumentar el interés del atleta por el deporte. Nivel de evidencia II; Estudios terapéuticos - investigación de los resultados del tratamiento.

A prognostic and therapeutic hallmark developed by the integrated profile of basement membrane and immune infiltrative landscape in lung adenocarcinoma.

Basement membranes (BMs) are specialised extracellular matrices that maintain cellular integrity and resist the breaching of carcinoma cells for metastases while regulating tumour immunity. The tumour immune microenvironment (TME) is essential for tumour growth and the response to and benefits from immunotherapy. In this study, the BM score and TME score were constructed based on the expression signatures of BM-related genes and the presence of immune cells in lung adenocarcinoma (LUAD), respectively. Subsequently, the BM-TME classifier was developed with the combination of BM score and TME score for accurate prognostic prediction. Further, Kaplan-Meier survival estimation, univariate Cox regression analysis and receiver operating characteristic curves were used to cross-validate and elucidate the prognostic prediction value of the BM-TME classifier in several cohorts. Findings from functional annotation analysis suggested that the potential molecular regulatory mechanisms of the BM-TME classifier were closely related to the cell cycle, mitosis and DNA replication pathways. Additionally, the guiding value of the treatment strategy of the BM-TME classifier for LUAD was determined. Future clinical disease management may benefit from the findings of our research.