Association between early exposure to famine and risk of renal impairment in adulthood: a systematic review and meta-analysis.

Malnutrition early in life increases the later-life risk of noncommunicable diseases, and previous epidemiologic studies have found a link between famine and renal impairment, but no consensus has been reached. This meta-analysis and systematic review were conducted to assess the correlation between early-life famine exposure and the risk of developing renal impairment. Search in Embase, Scopus, Web of Science, PubMed, and Cochrane using keywords that report the correlation between early famine exposure and renal function indicators. RevMan and Stata software were used for data analysis. This meta-analysis contained twelve observational studies. The findings demonstrated a link between prenatal famine exposure and a higher risk of developing chronic kidney disease (CKD) (odds ratio (OR) = 1.73, 95% confidence interval (CI): 1.25, 2.39), a decreased estimated glomerular filtration rate (eGFR) (mean difference (MD) = -10.05, 95% CI: -11.64, -8.46), and increased serum creatinine (Scr) (MD = 0.02, 95% CI: 0.01, 0.03) compared to unexposed individuals. Famine exposure in childhood was associated with decreased eGFR (MD = -9.43, 95% CI: -12.01, -6.84) and increased Scr (MD = 0.03, 95% CI: 0.01, 0.04), but not with CKD (OR = 0.980, 95% CI: 0.53, 1.81). Famine exposure in adolescence and adulthood was associated with decreased eGFR (MD = -20.73, 95% CI: -22.40, -19.06). Evidence certainty was deemed to be of low or extremely low quality. Famine exposure early in life could pose a greater risk of developing renal impairment in adulthood, but this outcome may be driven by uncontrolled age differences between famine-births and post-famine-births (unexposed).

The association of changes in the Chinese visceral adiposity index and cardiometabolic diseases: a cohort study.

OBJECTIVE: The relationship between changes in Chinese visceral adiposity index (CVAI) and cardiometabolic diseases (CMD) in middle-aged and elderly individuals remains unclear. This study aimed to explore whether changes in the CVAI were associated with CMD incidence. METHODS: This study included 3,243 individuals aged over 45 years from the China Health and Retirement Longitudinal Study. The exposures were changes in the CVAI and cumulative CVAI from 2012 to 2015. Changes in the CVAI were classified using K-means clustering analysis, and the cumulative CVAI was calculated as follows: (CVAI2012 + CVAI2015)/2 × time (2015-2012). Multivariable logistic regression models were used to assess the relationship between different CVAI change classes and CMD incidence. Restricted cubic splines regression was used to assess the dose-response relationship between cumulative CVAI and CMD incidence. To investigate the relationship between combined exposure to each component of CAVI and CMD incidence, a weighted quantile sum regression analysis was employed. RESULTS: During the 5 years of follow-up, 776 (24%) incident CMD cases were identified. Changes in CVAI and cumulative CVAI were independently and positively associated with CMD. After adjusting for potential confounders, compared with Class 1, the adjusted ORs (95% CIs) for incident CMD were 1.18 (0.90-1.57) for Class 2, 1.40 (1.03-1.92) for Class 3, and 1.56 (1.04-2.34) for Class 4. When cumulative CVAI was categorized into quartiles, compared with Q1, the adjusted ORs (95% CIs) for incident CMD were 1.30 (1.00-1.70) for Q2, 1.34 (1.01-1.79) for Q3, and 1.63 (1.15-2.31) for Q4. In addition, cumulative CVAI in the overall population exhibited a linear association with CMD (Poverall = 0.012, Pnon-linearity = 0.287), diabetes (Poverall = 0.022, Pnon-linearity = 0.188), and stroke (Poverall = 0.002, Pnon-linearity = 0.978), but showed no significant association with heart disease (Poverall = 0.619, Pnon-linearity = 0.442). CONCLUSION: Participants with higher baseline CVAI level and a change of elevating CVAI level may suffer an increased incidence of CMD. Furthermore, our findings elucidate the underlying mechanisms of the CVAI by highlighting TG as the primary contributor to the observed associations. Long-term CVAI monitoring is of significant importance for early identification and prevention of CMD, with significant implications for clinical practice.

Robust 1D selective correlation NMR spectroscopy for rapid chemical and biological applications.

Selective homonuclear proton correlation NMR spectroscopy (COSY) provides a useful detection tool for elucidating molecular structures and identifying chemical compositions in 1D spectroscopic patterns. However, conventional 1D selective COSY experiments highly rely on the performance of selective excitation on targeted signals and their applications generally suffer from spectral congestion in complex chemical and biological samples. Herein, based on the concept of targeted excitation on coupled proton pairs and spectroscopic separation on their respective COSY responses, we propose a 1D selective NMR approach that is capable of individually recording direct coupling correlation information of targeted proton groups for analyses on complex samples, free of spectral congestion. The performance of the proposed approach is demonstrated on a medicine sample, a biological molecule, and a real metabonomics sample of human serum. This approach shows a promising analytical technique for structural studies and component analyses in chemical and biological applications. Keywords: NMR spectroscopy, Correlation spectroscopy, Targeted signal excitation, Spectral congestion, Molecular structure analysis.

The Non-Targeted Lipidomic-Based Classifier Reveals Two Candidate Biomarkers for Ischemic Stroke in Hypertensive Individuals.

Introduction: Traditional clinical risk factors are insufficient to estimate the residual risk of large-vessel ischemic stroke. Non-targeted lipidomic techniques provide an opportunity to evaluate these risks. Methods: Plasma samples were collected from 113 hypertensive individuals, including 55 individuals at high risk of ischemic stroke and 58 matched individuals, in a prospective nested case-control cohort. To identify dysregulated lipid metabolites, we conducted multivariate and univariate analyses. A classifier based on a cross-validated procedure was employed to select the optimal combination of lipid species and their ratios. Results: We identified 23 dysregulated lipid species in patients with and without ischemic stroke, including 16 (69.6%) up-regulated and 7 (30.4%) down-regulated lipid species. Through internal cross-validation, the optimal combination of two lipid features (phosphatidylcholine 34:2 and triglyceride 18:1/18:1/22:1 / phosphatidylcholine 34:2, referred to as ischemic stroke-related 2 lipid features - IS2LP) was selected, leading to a more precise prediction probability for ischemic stroke within 3.9 years. In the comparison of different risk factors, the traditional risk score, the IS2LP risk score, and the combination of the traditional risk score with IS2LP yield AUC values of 0.613(95% CI:0.509-0.717), 0.833(95% CI:0.755-0.911), and 0.843(95% CI:0.777-0.916), respectively. The combination of the traditional risk score and IS2LP exhibited significantly improved discriminative performance, with an integrated discrimination improvement (IDI) of 0.31 (p<0.001) and a continuous net reclassification improvement (NRI) of 1.06 (p < 0.001) compared to the traditional risk score. Conclusion: We identified new lipidomic biomarkers associated with the futural event of large-vessel ischemic stroke. These lipid species could serve as potential blood biomarkers for assessing the residual risk of ischemic stroke in hypertensive individuals.

Efficacy and safety of laser ablation and microwave ablation to treat papillary thyroid microcarcinoma: A retrospective study.

OBJECTIVE: To retrospectively analyze the efficacy and safety of laser ablation (LA) and microwave ablation (MWA) in the treatment of papillary thyroid microcarcinoma (PTMC). METHODS: This was a retrospective study of 103 patients (109 nodules) who underwent thermal ablation for PTMC between October 2019 and March 2023; 61 underwent LA and 48 underwent MWA. The mean patients' age was 43.50 ± 12.42 years. After ablation, changes in tumor size at different time points, local recurrence, new lesions, lymph node metastasis, and complications were evaluated and recorded. The feasibility, success rate, and safety of LA and MWA were analyzed. RESULTS: Complete absence of enhancement on contrast-enhanced ultrasonography was observed in all target tumors after ablation. At the last follow-up, the mean volume of the PTMC nodules decreased from 0.09 ± 0.09 to 0.03 ± 0.03 ml (LA group) and from 0.11 ± 0.10 to 0.06 ± 0.08 ml (MWA group) (both, P < 0.05). There was no significant difference in volume change between the groups (P (groups): 0.520; P (groups over time): 0.423), indicating similar efficacy between the groups. There was also no significant difference in the volume reduction rate between the groups during follow-up, except for at 3 months (P = 0.023). The complication rates did not differ between the LA group (8.2 %) and MWA group (6.3 %) (P > 0.05). CONCLUSION: During the short-term follow-up, ultrasound-guided LA and MWA were effective and safe for PTMC, and there were no significant differences in treatment outcomes between the methods.

[Research progress of type 2 inflammation-related tissue remodeling in nasal polyps].

Chronic rhinosinusitis with nasal polyps is a common chronic inflammatory disease with significant tissue remodeling, but the mechanism of remodeling remains unclear. Studies have shown that Type（T） 2 inflammatory network plays a crucial role in tissue remodeling and nasal polyp formation. Clinical trials have been carried out for several biological targets, and a number of potential therapeutic targets have received increasing attention. This paper will summarize the research progress of T2 inflammatory response involved in nasal polyp tissue remodeling to provide ideas for further exploring the mechanism of nasal polyp tissue remodeling.

Combining Fast Pure Shift NMR and GEMSTONE-Based Selective TOCSY for Efficient NMR Analysis of Complex Systems.

As one of the commonly used intact detection techniques, liquid NMR spectroscopy offers unparalleled insights into the chemical environments, structures, and dynamics of molecules. However, it generally encounters the challenges of crowded or even overlapped spectra, especially when probing complex sample systems containing numerous components and complicated molecular structures. Herein, we exploit a general NMR protocol for efficient NMR analysis of complex systems by combining fast pure shift NMR and GEMSTONE-based selective TOCSY. First, this protocol enables ultrahigh-selective observation on the coupling networks that are totally correlated with targeted resonances or components, even where they are situated in severely overlapped spectral regions. Second, pure shift simplification is introduced to enhance the spectral resolution and further resolve the subspectra containing spectral congestion, thus facilitating the dissection of overlapped spectra. Additionally, sparse sampling accompanied by spectral reconstruction is adopted to significantly accelerate acquisition and improve spectral quality. The advantages of this protocol were demonstrated on different complex sample systems, including a challenging compound of estradiol, a mixture of sucrose and d-glucose, and natural grape juice, verifying its feasibility and power, and boosting the potential application landscapes in various chemical fields.

Relationship between weight-adjusted-waist index and blood pressure as well as incident hypertension among middle-aged and elderly Chinese: A longitudinal study.

BACKGROUND AND AIM: The Weight-Adjusted Waist Index (WWI) is a novel obesity metric linked to metabolic disorders. Its relationship with blood pressure and hypertension prevalence in middle-aged and elderly Chinese is unclear. This study examined the association between WWI, blood pressure, and hypertension incidence. METHODS AND RESULTS: This cross-sectional study included 9298 participants from the China Health and Retirement Longitudinal Study, with 4120 non-hypertensive individuals enrolled in the cohort study. In the cross-sectional analysis, WWI was positively associated with systolic blood pressure (SBP) (Beta 0.88, 95% CI: 0.57-1.21, p < 0.001), showing stronger correlations than waist circumference (WC) (Beta 0.20, 95% CI: 0.16-0.23, p < 0.001) and body mass index (BMI) (Beta 0.63, 95% CI: 0.52-0.74, p < 0.001). WWI also showed a positive association with diastolic blood pressure (DBP) (Beta 0.51, 95% CI: 0.32-0.69, p < 0.001), stronger than those with WC (Beta 0.13, 95% CI: 0.11-0.15, p < 0.001) and BMI (Beta 0.43, 95% CI: 0.37-0.50, p < 0.001). In the longitudinal cohort study, there were 1325 (32%) incident cases of hypertension by the end of follow-up. WWI was positively associated with incident hypertension (OR 1.11, 95% CI: 1.04-1.18, p = 0.001), with a stronger predictive value than WC (OR 1.02, 95% CI: 1.01-1.03, p < 0.001) and BMI (OR 1.04, 95% CI: 1.02-1.06, p < 0.001). CONCLUSION: Elevated WWI may serve as an independent risk factor for incident hypertension in the middle-aged and elderly Chinese population.

Bibliometric analysis of global research on air pollution and cardiovascular diseases: 2012-2022.

Background: The relationship between air pollution and cardiovascular diseases (CVDs) has garnered significant interest among researchers globally. This study employed bibliometric analysis to provide an overview of current research on the association between air pollution and CVDs, offering a comprehensive analysis of global research trends in this area. Methods: An exhaustive scrutiny of literature pertaining to the nexus between air pollution and CVDs from 2012 to 2022 was conducted through rigorous screening of the Web of Science Core Collection (WoSCC). Publications were exclusively considered in English. Subsequently, sophisticated analytical tools including CiteSpace 6.2.4R, Vosviewer 1.6.19, HistCite 2.1, Python 3.7.5, Microsoft Charticulator, and Bibliometrix Online Analysis Platform were deployed to delineate research trends in this domain. Results: The analysis of the dataset, comprising 1710 documents, unveiled a consistent escalation in scientific publications, peaking in 2022 with a total of 248 publications. Moreover, Environmental Science and Toxicology stood out as the predominant categories. Examination of keyword frequency highlighted the terms 'air pollution', 'cardiovascular disease', and 'particulate matter' as the most prevalent. Notably, the most prolific entities, in terms of authors, journals, organizations, and countries, were identified as Robert D. Brook, Environmental Health Perspectives, Harvard University, and the United States, respectively. Conclusion: The findings presented a notable increase in high-quality publications on this topic over the past 11 years, suggesting a positive outlook for future research. The study concluded with an examination of three key themes in research trends related to air pollution and CVDs: the initial physiological response to pollutant exposure, the pathways through which pollutants are transmitted, and the subsequent effects on target organs. Additionally, various air pollutants, such as particulate matter, nitric dioxide, and ozone, could contribute to multiple CVDs, including coronary heart disease, hypertension, and heart failure. Although some hypotheses have been put forward, the mechanisms of air pollution-related CVDs still need to be explored in the future.

Two-Dimensional Laplace NMR Reconstruction through Deep Learning Enhancement.

Laplace NMR is a powerful tool for studying molecular dynamics and spin interactions, providing diffusion and relaxation information that complements Fourier NMR used for composition determination and structure elucidation. However, Laplace NMR demands sophisticated signal processing algorithms such as inverse Laplace transform (ILT). Due to the inherently ill-posed nature of ILT problems, it is generally challenging to perform satisfactory Laplace NMR processing and reconstruction, particularly for two-dimensional Laplace NMR. Herein, we propose a proof-of-concept approach that blends a physics-informed strategy with data-driven deep learning for two-dimensional Laplace NMR reconstruction. This approach integrates prior knowledge of mathematical and physical laws governing multidimensional decay signals by constructing a forward process model to simulate relationships among different decay factors. Benefiting from a noniterative neural network algorithm that automatically acquires prior information from synthetic data during training, this approach avoids tedious parameter tuning and enhances user friendliness. Experimental results demonstrate the practical effectiveness of this approach. As an advanced and impactful technique, this approach brings a fresh perspective to multidimensional Laplace NMR inversion.

Quantitative susceptibility mapping based basal ganglia segmentation via AGSeg: leveraging active gradient guiding mechanism in deep learning.

Background: With better visual contrast and the ability for magnetic susceptibility quantification analysis, quantitative susceptibility mapping (QSM) has emerged as an important magnetic resonance imaging (MRI) method for basal ganglia studies. Precise segmentation of basal ganglia is a prerequisite for quantification analysis of tissue magnetic susceptibility, which is crucial for subsequent disease diagnosis and surgical planning. The conventional method of localizing and segmenting basal ganglia heavily relies on layer-by-layer manual annotation by experts, resulting in a tedious amount of workload. Although several morphology registration and deep learning based methods have been developed to automate segmentation, the voxels around the nuclei boundary remain a challenge to distinguish due to insufficient tissue contrast. This paper proposes AGSeg, an active gradient guidance-based susceptibility and magnitude information complete (MIC) network for real-time and accurate basal ganglia segmentation. Methods: Various datasets, including clinical scans and data from healthy volunteers, were collected across multiple centers with different magnetic field strengths (3T/5T/7T), with a total of 210 three-dimensional (3D) susceptibility measurements. Manual segmentations following fixed rules for anatomical borders annotated by experts were used as ground truth labels. The proposed network took QSM maps and Magnitude images as two individual inputs, of which the features are selectively enhanced in the proposed magnitude information complete (MIC) module. AGSeg utilized a dual-branch architecture, with Seg-branch aiming to generate a proper segmentation map and Grad-branch to reconstruct the gradient map of regions of interest (ROIs). With the support of the newly designed active gradient module (AGM) and gradient guiding module (GGM), the Grad-branch provided attention guidance for the Seg-branch, facilitating it to focus on the boundary of target nuclei. Results: Ablation studies were conducted to assess the functionality of the proposed modules. Significant performance decrement was observed after ablating relative modules. AGSeg was evaluated against several existing methods on both healthy and clinical data, achieving an average Dice similarity coefficient (DSC) =0.874 and average 95% Hausdorff distance (HD95) =2.009. Comparison experiments indicated that our model had superior performance on basal ganglia segmentation and better generalization ability over existing methods. The AGSeg outperformed all implemented comparison deep learning algorithms with average DSC enhancement ranging from 0.036 to 0.074. Conclusions: The current work integrates a deep learning-based method into automated basal ganglia segmentation. The high processing speed and segmentation robustness of AGSeg contribute to the feasibility of future surgery planning and intraoperative navigation. Experiments show that leveraging active gradient guidance mechanisms and magnitude information completion can facilitate the segmentation process. Moreover, this approach also offers a portable solution for other multi-modality medical image segmentation tasks.

Multidrug-resistant aeromonas caviae causing cystitis in a renal failure patient.

A 49-year-old female with multiple myeloma complicated by renal failure had dysuria. The urine culture revealed multidrug-resistant aeromonas caviae during her hospital stay. Her symptoms and signs significantly improved after receiving a seven-day course of piperacillin-tazobactam treatment. She had no history of urinary tract infections(UTIs). On follow-up, she felt clinically well. Aeromonas caviae is a rare cause of UTI. We review previous cases of aeromonas caviae UTIs. The purpose of this case report is to assist in the diagnosis and management of aeromonas caviae cystitis.

Association between hypertension and osteoporosis: a population-based cross-sectional study.

BACKGROUND: Current evidence suggests that metabolic dysregulation is inextricably linked to both hypertension and osteoporosis, but the correlation between hypertension and osteoporosis is still unclear. Therefore, in this study, we explored the correlation between hypertension and osteoporosis. METHODS: A total of 37,807 participants from the National Health and Nutrition Examination Survey (1999-2010, 2013-2014, 2017-2018) were enrolled in this population-based cross-sectional study. Hypertension was considered an exposure factor and osteoporosis was considered an outcome factor. Logistic regression and subgroup analysis were used to assess the association between hypertension and osteoporosis. RESULTS: A total of 2,523 participants, with a mean age of 68.65 ± 12.21 years, suffered from osteoporosis, and 86.2% were female. Participants with osteoporosis had a greater prevalence of hypertension than participants without osteoporosis (p < 0.001). Participants with hypertension also had a greater prevalence of osteoporosis than participants without hypertension (p < 0.001). Univariate logistic regression analysis indicated that hypertension was associated with osteoporosis (OR: 2.693, 95% CI: 2.480-2.924, p < 0.001). Multivariate logistic regression analysis with a fully adjusted model indicated that hypertension was strongly associated with osteoporosis (OR: 1.183, 95% CI: 1.055-1.327, p = 0.004). Subgroup analysis revealed that the associations between hypertension and osteoporosis were significant in the younger than 60 years, male sex, diabetes subgroup and hypercholesterolemia subgroup (p < 0.05). CONCLUSION: Hypertension was independently associated with osteoporosis in the general population.

A Comprehensive Prognostic Model for Colon Adenocarcinoma Depending on Nuclear-Mitochondrial-Related Genes.

Background: Colon adenocarcinoma (COAD) has increasing incidence and is one of the most common malignant tumors. The mitochondria involved in cell energy metabolism, oxygen free radical generation, and cell apoptosis play important roles in tumorigenesis and progression. The relationship between mitochondrial genes and COAD remains largely unknown. Methods: COAD data including 512 samples were set out from the UCSC Xena database. The nuclear mitochondrial-related genes (NMRGs)-related risk prognostic model and prognostic nomogram were constructed, and NMRGs-related gene mutation and the immune environment were analyzed using bioinformatics methods. Then, a liver metastasis model of colorectal cancer was constructed and protein expression was detected using Western blot assay. Results: A prognostic model for COAD was constructed. Comparing the prognostic model dataset and the validation dataset showed considerable correlation in both risk grouping and prognosis. Based on the risk score (RS) model, the samples of the prognostic dataset were divided into high risk group and low risk group. Moreover, pathologic N and T stage and tumor recurrence in the two risk groups were significantly different. The four prognostic factors, including age and pathologic T stage in the nomogram survival model also showed excellent predictive performance. An optimal combination of nine differentially expressed NMRGs was finally obtained, including LARS2, PARS2, ETHE1, LRPPRC, TMEM70, AARS2, ACAD9, VARS2, and ATP8A2. The high-RS group had more inflamed immune features, including T and CD4+ memory cell activation. Besides, mitochondria-associated LRPPRC and LARS2 expression levels were increased in vivo xenograft construction and liver metastases assays. Conclusion: This study established a comprehensive prognostic model for COAD, incorporating nine genes associated with nuclear-mitochondrial functions. This model demonstrates superior predictive performance across four prognostic factors: age, pathological T stage, tumor recurrence, and overall prognosis. It is anticipated to be an effective model for enhancing the prognosis and treatment of COAD.

Lung tumor discrimination by deep neural network model CanDo via DNA methylation in bronchial lavage.

Bronchoscopic-assisted discrimination of lung tumors presents challenges, especially in cases with contraindications or inaccessible lesions. Through meta-analysis and validation using the HumanMethylation450 database, this study identified methylation markers for molecular discrimination in lung tumors and designed a sequencing panel. DNA samples from 118 bronchial washing fluid (BWF) specimens underwent enrichment via multiplex PCR before targeted methylation sequencing. The Recursive Feature Elimination Cross-Validation and deep neural network algorithm established the CanDo classification model, which incorporated 11 methylation features (including 8 specific to the TBR1 gene), demonstrating a sensitivity of 98.6% and specificity of 97.8%. In contrast, bronchoscopic rapid on-site evaluation (bronchoscopic-ROSE) had lower sensitivity (87.7%) and specificity (80%). Further validation in 33 individuals confirmed CanDo's discriminatory potential, particularly in challenging cases for bronchoscopic-ROSE due to pathological complexity. CanDo serves as a valuable complement to bronchoscopy for the discriminatory diagnosis and stratified management of lung tumors utilizing BWF specimens.

Differential Mechanisms of Microbial As(III) and Sb(III) Oxidation and Their Contribution to Tailings Reclamation.

Mine tailings are extremely oligotrophic environments frequently contaminated with elevated As and Sb, making As(III) and Sb(III) oxidation potentially important energy sources for the tailing microbiome. Although they have been proposed to share similar metabolic pathways, a systemic comparison of the As(III) and Sb(III) oxidation mechanisms and energy utilization efficiencies requires further elucidation. In this study, we employed a combination of physicochemical, molecular, and bioinformatic analyses to compare the kinetic and genetic mechanisms of As(III) and Sb(III) oxidation as well as their respective energy efficiencies for fueling the key nutrient acquisition metabolisms. Thiobacillus and Rhizobium spp. were identified as functional populations for both As(III) and Sb(III) oxidation in mine tailings by DNA-stable isotope probing. However, these microorganisms mediated As(III) and Sb(III) oxidation via different metabolic pathways, resulting in preferential oxidation of Sb(III) over As(III). Notably, both As(III) and Sb(III) oxidation can facilitate nitrogen fixation and phosphate solubilization in mine tailings, with Sb(III) oxidation being more efficient in powering these processes. Thus, this study provided novel insights into the microbial As(III) and Sb(III) oxidation mechanisms and their respective nutrient acquisition efficiencies, which may be critical for the reclamation of mine tailings.

Discovery of a novel BTK inhibitor S-016 and identification of a new strategy for the treatment of lymphomas including BTK inhibitor-resistant lymphomas.

Bruton's tyrosine kinase (BTK) has emerged as a therapeutic target for B-cell malignancies, which is substantiated by the efficacy of various irreversible or reversible BTK inhibitors. However, on-target BTK mutations facilitating evasion from BTK inhibition lead to resistance that limits the therapeutic efficacy of BTK inhibitors. In this study we employed structure-based drug design strategies based on established BTK inhibitors and yielded a series of BTK targeting compounds. Among them, compound S-016 bearing a unique tricyclic structure exhibited potent BTK kinase inhibitory activity with an IC50 value of 0.5 nM, comparable to a commercially available BTK inhibitor ibrutinib (IC50 = 0.4 nM). S-016, as a novel irreversible BTK inhibitor, displayed superior kinase selectivity compared to ibrutinib and significant therapeutic effects against B-cell lymphoma both in vitro and in vivo. Furthermore, we generated BTK inhibitor-resistant lymphoma cells harboring BTK C481F or A428D to explore strategies for overcoming resistance. Co-culture of these DLBCL cells with M0 macrophages led to the polarization of M0 macrophages toward the M2 phenotype, a process known to support tumor progression. Intriguingly, we demonstrated that SYHA1813, a compound targeting both VEGFR and CSF1R, effectively reshaped the tumor microenvironment (TME) and significantly overcame the acquired resistance to BTK inhibitors in both BTK-mutated and wild-type BTK DLBCL models by inhibiting angiogenesis and modulating macrophage polarization. Overall, this study not only promotes the development of new BTK inhibitors but also offers innovative treatment strategies for B-cell lymphomas, including those with BTK mutations.

Compact In Situ Electrochemical NMR with Wireless and Anti-interference Strategy in Multiscenario Applications.

The integration of electrochemistry with nuclear magnetic resonance (NMR) spectroscopy recently offers a powerful approach to understanding oxidative metabolism, detecting reactive intermediates, and predicting biological activities. This combination is particularly effective as electrochemical methods provide excellent mimics of metabolic processes, while NMR spectroscopy offers precise chemical analysis. NMR is already widely utilized in the quality control of pharmaceuticals, foods, and additives and in metabolomic studies. However, the introduction of additional and external connections into the magnet has posed challenges, leading to signal deterioration and limitations in routine measurements. Herein, we report an anti-interference compact in situ electrochemical NMR system (AICISENS). Through a wireless strategy, the compact design allows for the independent and stable operation of electrochemical NMR components with effective interference isolation. Thus, it opens an avenue toward easy integration into in situ platforms, applicable not only to laboratory settings but also to fieldwork. The operability, reliability, and versatility were validated with a series of biomimetic assessments, including measurements of microbial electrochemical systems, functional foods, and simulated drug metabolisms. The robust performance of AICISENS demonstrates its high potential as a powerful analytical tool across diverse applications.

Treatment of phenolic wastewater in an anaerobic fluidized bed microbial fuel cell filled with graphene oxide-macroporous adsorption resin as multifunctional carrier.

A novel graphene oxide-modified resin (graphene oxide-macroporous adsorption resin) was prepared and used as a multifunctional carrier in an anaerobic fluidized bed microbial fuel cell (AFB-MFC) to treat phenolic wastewater (PW). The macroporous adsorption resin (MAR) was used as the carrier, graphene oxide was used as the modified material, the conductive modified resin was prepared by loading graphene oxide (GO) on the resin through chemical reduction. The modified resin particles were characterized by scanning electron microscopy (SEM), Raman spectroscopy (RS), specific surface area and pore structure analysis. Graphene oxide-macroporous adsorption resin special model was established using the Amorphous Cell module in Materials Studio (MS), and the formation mechanism of graphene oxide-macroporous adsorption resin was studied using mean square displacement (MSD) of the force module. Molecular dynamics simulation was used to study the motion law of molecular and atomic dynamics at the interface of graphene oxide-macroporous adsorption resin composites. The strong covalent bond between GO and MAR ensures the stability of GO/MAR. When the modified resin prepared in 3.0 mg/mL GO mixture was used in the AFB-MFC, the COD removal of wastewater was increased by 9.1% to 72.44%, the voltage was increased by 84.04% to 405.8 mV, and power density was increased by 765.44% to 242.67 mW/m2.

Pure-Shift-Based Proton Magnetic Resonance Spectroscopy for High-Resolution Studies of Biological Samples.

Proton magnetic resonance spectroscopy (1H MRS) presents a powerful tool for revealing molecular-level metabolite information, complementary to the anatomical insight delivered by magnetic resonance imaging (MRI), thus playing a significant role in in vivo/in vitro biological studies. However, its further applications are generally confined by spectral congestion caused by numerous biological metabolites contained within the limited proton frequency range. Herein, we propose a pure-shift-based 1H localized MRS method as a proof of concept for high-resolution studies of biological samples. Benefitting from the spectral simplification from multiplets to singlet peaks, this method addresses the challenge of spectral congestion encountered in conventional MRS experiments and facilitates metabolite analysis from crowded NMR resonances. The performance of the proposed pure-shift 1H MRS method is demonstrated on different kinds of samples, including brain metabolite phantom and in vitro biological samples of intact pig brain tissue and grape tissue, using a 7.0 T animal MRI scanner. This proposed MRS method is readily implemented in common commercial NMR/MRI instruments because of its generally adopted pulse-sequence modules. Therefore, this study takes a meaningful step for MRS studies toward potential applications in metabolite analysis and disease diagnosis.