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Using α-cyano-4-hydroxy-cinnamic acid, a small molecule inhibitor of monocarboxylic acid transporters(MCTs), as the lead compound, a novel 18F-labeled α-cyano-4-hydroxy-cinnamic acid probe was designed and synthesized. The preliminary evaluation of stability and tumor PET/CT imaging were performed in this study. Taking α-cyano-4-(2-p-toluenesulfonyl-ethoxy)-methyl cinnamate as the precursor compound, the intermediate compound α-cyano-4-(2-［18F］-fluoroethoxy)-methyl cinnamate(［18F］4) was obtained by nucleophilic reaction with 18F-, which was separated and purified by high performance liquid chromatography(HPLC). α-cyano-4-(2-［18F］-fluoroethoxy)-cinnamic acid(［18F］FEtO-CHC, ［18F］5) can be obtained from the hydrolysis of ［18F］4 with 2 mol/L NaOH solution and the neutralization with 1 mol/L HCl solution. The results of cell proliferation inhibition assay show that compound ［19F］5 has better inhibitory activity than that of CHC. ［18F］FEtO-CHC shows good stability and biosafety from the in vitro and in vivo studies, and micro-PET/CT imaging in DU145 prostate cancer tumor-bearing mice shows that ［18F］5 has obvious radioactive accumulation at the tumor site. ［18F］FEtO-CHC has the advantages of simple synthesis process, good stability, high biological safety, and ability for tumor PET imaging. It is a potential PET agent for specific MCTs imaging.

CD8+ T cell responses restricted by MHC-E, a nonclassical MHC molecule, have been associated with protection in an SIV/rhesus macaque model. The biological relevance of HLA-E-restricted CD8+ T cell responses in HIV infection, however, remains unknown. In this study, CD8+ T cells responding to HIV-1 Gag peptides presented by HLA-E were analyzed. Using in vitro assays, we observed HLA-E-restricted T cell responses to what we believe to be a newly identified subdominant Gag-KL9 as well as a well-described immunodominant Gag-KF11 epitope in T cell lines derived from chronically HIV-infected patients and also primed from healthy donors. Blocking of the HLA-E/KF11 binding by the B7 signal peptide resulted in decreased CD8+ T cell responses. KF11 presented via HLA-E in HIV-infected cells was recognized by antigen-specific CD8+ T cells. Importantly, bulk CD8+ T cells obtained from HIV-infected individuals recognized infected cells via HLA-E presentation. Ex vivo analyses at the epitope level showed a higher responder frequency of HLA-E-restricted responses to KF11 compared with KL9. Taken together, our findings of HLA-E-restricted HIV-specific immune responses offer intriguing and possibly paradigm-shifting insights into factors that contribute to the immunodominance of CD8+ T cell responses in HIV infection.

The mining disturbance between multiple working faces will induce rock burst disaster, and regional harmonic mining is one of the key means to prevent this kind of rock burst. In order to verify the rationality and effectiveness of regional harmonic mining to prevent rock burst, taking Yima Mining Area where rock burst occurs frequently as an example, based on the harmonic mining principles and parameter values obtained from simulation, the harmonic mining scheme in the area between Yuejin and Changcun coal mines is formulated, and the effect of harmonic mining is evaluated by comparing the stress transfer characteristics and rock burst characteristics in the area with different harmonic degrees. The results show that the thickness of coal seam and huge thick conglomerate of Yuejin 23092 face and Changcun 21162 face are smaller in the area between Yuejin and Changcun coal mines. The width of coal pillar between 23092-21162 and 21170-21162 working faces are larger, and the horizontal distance and vertical offset between the two faces are further, so the 23092 and 21162 working faces between the two coal mines are the optimal continuous working faces. The degree of harmonic mining in the area between Yuejin and Changcun coal mines is higher than that of Gengcun and Qianqiu coal mines. The frequency and intensity of stress transfer caused by rock burst and mining among working faces are all significantly reduced with harmonic mining, and the range of stress transfer significantly is reduced, so the effect of harmonic mining is obvious.

This study presents the first column-averaged dry-air mole fractions of carbon dioxide (XCO2), methane (XCH4) and carbon monoxide (XCO) in the coal mine aggregation area in Shanxi, China, using two portable Fourier transform infrared spectrometers (EM27/SUNs), in the framework of the Collaborative Carbon Column Observing Network (COCCON). The measurements, collected over two months, were analyzed. Significant daily variations were observed, particularly in XCH4, which highlight the impact of coal mining emissions as a major CH4 source in the region. This study also compares COCCON XCO with measurements from the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5P satellite, revealing good agreement, with a mean bias of 7.15 ± 9.49 ppb. Additionally, comparisons were made between COCCON XCO2 and XCH4 data and analytical data from the Copernicus Atmosphere Monitoring Service (CAMS). The mean biases between COCCON and CAMS were −6.43 ± 1.75 ppm for XCO2 and 15.40 ± 31.60 ppb for XCH4. The findings affirm the stability and accuracy of the COCCON instruments for validating satellite observations and detecting local greenhouse gas sources. Operating COCCON spectrometers in coal mining areas offers valuable insights into emissions from these high-impact sources. [ABSTRACT FROM AUTHOR]

Accurate estimation of nitrogen dioxide (NO2) levels at high spatio‐temporal resolution is crucial for atmospheric research and public health assessments. This study introduces a novel machine learning (ML) framework enhanced with uncertainty quantification (UQ) to predict hourly NO2 concentrations over East Asia. Benefiting from tropospheric NO2 columns from the Geostationary Environment Monitoring Spectrometer (GEMS), along with land use, meteorological, and topographic data, our model demonstrates robust and reliable performance, evidenced by an R2 of 0.84 and RMSE of 2.93 ppb through cross‐validation. Unlike traditional ML regressions tasks, our framework not only provides a single NO2 estimate but also diagnoses data and model uncertainties for each pixel. Higher uncertainties are observed in regions with complex terrain and sparse monitoring. Hourly and Intra‐annual variations in concentration predictions and associated uncertainties are both significant. The explicit UQ informs decision‐making and highlights the need for cautious interpretation in atmospheric data‐driven predictions. Plain Language Summary: Our study aims to improve understanding of near‐surface nitrogen dioxide (NO2) levels, crucial for accessing health risks. Machine learning (ML) has emerged as a powerful tool in converting satellite‐derived NO2 columns to near‐surface concentrations. However, previous estimates were based on polar‐orbiting satellites, which yield only a single daily result. In contrast, we use data products from the Geostationary Environment Monitoring Spectrometer (GEMS), the first sensor providing continuous monitoring over Asia with hourly updates on NO2 columns during daylight. Importantly, while these ML models proficiently predict NO2 levels at the stations, they tend to lack a comprehensive uncertainty assessment, leading to potential overreliance on their spatial performance. Our work developed a way to not only capture hourly variations of near‐surface NO2 concentrations but also to quantify the certainty about these estimates across the entire space. This enhances air quality decision‐making and underscores the need for careful environmental prediction analysis. Key Points: Quantify data and model uncertainties in machine learning, revealing data surpasses model—critical for accurate assessmentsDerive hourly NO2 concentrations from GEMS NO2 columns, refining spatial‐temporal resolutionInform site construction decisions, cautioning against overestimating machine learning's spatial generalization capabilities [ABSTRACT FROM AUTHOR]

Background Patients with chronic lymphocytic leukemia (CLL) have reduced seroconversion rates and lower binding antibody (Ab) and neutralizing antibody (NAb) titers than healthy individuals following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) mRNA vaccination. Here, we dissected vaccine-mediated humoral and cellular responses to understand the mechanisms underlying CLL-induced immune dysfunction. Methods and findings We performed a prospective observational study in SARS-CoV-2 infection-naïve CLL patients (n = 95) and healthy controls (n = 30) who were vaccinated between December 2020 and June 2021. Sixty-one CLL patients and 27 healthy controls received 2 doses of the Pfizer-BioNTech BNT162b2 vaccine, while 34 CLL patients and 3 healthy controls received 2 doses of the Moderna mRNA-1273 vaccine. The median time to analysis was 38 days (IQR, 27 to 83) for CLL patients and 36 days (IQR, 28 to 57) for healthy controls. Testing plasma samples for SARS-CoV-2 anti-spike and receptor-binding domain Abs by enzyme-linked immunosorbent assay (ELISA), we found that all healthy controls seroconverted to both antigens, while CLL patients had lower response rates (68% and 54%) as well as lower median titers (23-fold and 30-fold; both p 23-fold and >17-fold lower median NAb titers (both p 2.4 mg/L), prior therapy, anti-CD20 immunotherapy ( Conclusions CLL pathogenesis is characterized by a progressive loss of adaptive immune functions, including in most treatment-naïve patients, with preexisting memory being preserved longer than the capacity to mount responses to new antigens. In addition, higher NAb titers and response rates identify mRNA-1273 as a superior vaccine for CLL patients., Author(s): Kai Qin 1, Kazuhito Honjo 1, Scott Sherrill-Mix 2, Weimin Liu 2, Regina M. Stoltz 2, Allisa K. Oman 1, Lucinda A. Hall 3, Ran Li 1, Sarah Sterrett [...]

Introduction: Previous studies suggested that sevelamer carbonate is well tolerated with a favorable efficacy and safety profile in both dialysis and nondialysis patients in Europe; however, the efficacy remains controversial, and few studies have examined sevelamer carbonate therapy in other ethnic nondialysis CKD patients. This study assessed the efficacy and safety of sevelamer carbonate in Chinese nondialysis CKD patients with hyperphosphatemia. Methods: The multicenter, randomized, double-blind, parallel group, placebo-controlled, and phase 3 clinical trial enrolled 202 Chinese nondialysis CKD patients with serum phosphorus ≥1.78 mmol/L. Patients were randomly assigned 1:1 to receive sevelamer carbonate (2.4-12 g per day) or placebo for 8 weeks. The primary outcome was the change in serum phosphorous between baseline and week 8. Results: Totally 482 Chinese patients were screened and 202 were randomized (sevelamer carbonate, n=101; placebo, n=101). The mean serum phosphorous decreased significantly in patients treated with sevelamer carbonate compared with placebo (-0.22±0.47 vs. 0.05±0.44 mmol/L, p

In the case of low content of heavy metals in soil, the hyperspectral characteristic response of heavy metals is very weak, so it is difficult to construct an accurate direct hyperspectral inversion model. In order to solve the above problems, according to the physical and chemical properties of soil chemical variables, the enrichment characteristics of heavy metals are transferred to the related major chemical elements, so that the weak information of heavy metals can be indirectly quantitatively inverted. In this paper, the black soil in Hailun was taken as the research object. Through principal component analysis and cluster analysis, it was confirmed that there was an obvious adsorption occurrence relationship between the major element iron oxide (Fe2O3) and trace heavy metals As, Zn, Cd. The best inversion model of iron oxide content in the study area was established by partial least square method (the determination coefficient is 0.704, the root mean square difference is 0.148, and the F-test is 12.732). Based on the occurrence relationship between iron oxide and As, Zn, CD, a nonlinear fitting model between the predicted value of iron oxide and the real value of heavy metals was constructed by neural network. The fitting results show that the fitting degree of As, Zn and Cd is As>Zn>Cd. The overall correlations are 0.796, 0.732, 0.530 respectively. The study results show that the indirect prediction model based on iron oxide content can better quantitatively predict As, Zn and Cd, which provides a new method for the quantitative analysis of trace heavy metal content. This model provides a basis for hyperspectral remote sensing technology to predict soil heavy metal content, enhances the feasibility of soil trace heavy metal inversion, and is helpful to refine the quality monitoring of natural resource. It is of great significance to deepen the comprehensive analysis and evaluation of geoscience system.