Constructing Stiffness Tunable DNA Hydrogels Based on DNA Modules with Adjustable Rigidity.

DNA hydrogel represents a potent material for crafting biological scaffolds, but the toolbox to systematically regulate the mechanical property is still limited. Herein, we have provided a strategy to tune the stiffness of DNA hydrogel through manipulating the rigidity of DNA modules. By introducing building blocks with higher molecular rigidity and proper connecting fashion, DNA hydrogel stiffness could be systematically elevated. These hydrogels showed excellent dynamic properties and biocompatibility, thus exhibiting great potential in three-dimensional (3D) cell culture. This study has offered a systematic method to explore the structure-property relationship, which may contribute to the development of more intelligent and personalized biomedical platforms.

DNA-based nanostructures for RNA delivery.

RNA-based therapeutics have emerged as a promising approach for the treatment of various diseases, including cancer, genetic disorders, and infectious diseases. However, the delivery of RNA molecules into target cells has been a major challenge due to their susceptibility to degradation and inefficient cellular uptake. To overcome these hurdles, DNA-based nano technology offers an unprecedented opportunity as a potential delivery platform for RNA therapeutics. Due to its excellent characteristics such as programmability and biocompatibility, these DNA-based nanostructures, composed of DNA molecules assembled into precise and programmable structures, have garnered significant attention as ideal building materials for protecting and delivering RNA payloads to the desired cellular destinations. In this review, we highlight the current progress in the design and application of three DNA-based nanostructures: DNA origami, lipid-nanoparticle (LNP) technology related to frame guided assembly (FGA), and DNA hydrogel for the delivery of RNA molecules. Their biomedical applications are briefly discussed and the challenges and future perspectives in this field are also highlighted.

Angiopoietin-like protein 2 inhibits thrombus formation.

Acute myocardial infarction is mainly caused by a lack of blood flood in the coronary artery. Angiopoietin-like protein 2 (ANGPTL2) induces platelet activation and thrombus formation in vitro through binding with immunoglobulin-like receptor B, an immunoglobulin superfamily receptor. However, the mechanism by which it regulates platelet function in vivo remains unclear. In this study, we investigated the role of ANGPTL2 during thrombosis in relationship with ST-segment elevation myocardial infarction (STEMI) with spontaneous recanalization (SR). In a cohort of 276 male and female patients, we measured plasma ANGPTL2 protein levels. Using male Angptl2-knockout and wild-type mice, we examined the inhibitory effect of Angptl2 on thrombosis and platelet activation both in vivo and ex vivo. We found that plasma and platelet ANGPTL2 levels were elevated in patients with STEMI with SR compared to those in non-SR (NSR) patients, and was an independent predictor of SR. Angptl2 deficiency accelerated mesenteric artery thrombosis induced by FeCl3 in Angptl2-/- compared to WT animals, promoted platelet granule secretion and aggregation induced by thrombin and collogen while purified ANGPTL2 protein supplementation reversed collagen-induced platelet aggregation. Angptl2 deficiency also increased platelet spreading on immobilized fibrinogen and clot contraction. In collagen-stimulated Angptl2-/- platelets, Src homology region 2 domain-containing phosphatase (Shp)1-Y564 and Shp2-Y580 phosphorylation were attenuated while Src, Syk, and Phospholipase Cγ2 (PLCγ2) phosphorylation increased. Our results demonstrate that ANGPTL2 negatively regulated thrombus formation by activating ITIM which can suppress ITAM signaling pathway. This new knowledge provides a new perspective for designing future antiplatelet aggregation therapies.

Treatment failure is a key factor in the development of Helicobacter pylori resistance.

BACKGROUND: Helicobacter pylori eradication failure influences its antibiotic resistance. AIMS: This study aimed to evaluate the effect of previous treatment failures on it, including the changes in the antibiotic resistance rates, minimal inhibitory concentration (MIC) distributions, and resistance patterns. MATERIALS AND METHODS: This single-center retrospective study included 860 primary isolates and 247 secondary isolates. Antibiotic susceptibility testing was performed for amoxicillin, metronidazole, clarithromycin, levofloxacin, furazolidone, tetracycline, and rifampicin. The demographic data and detailed regimens were collected. RESULTS: The primary resistance rates to amoxicillin, metronidazole, clarithromycin, levofloxacin, tetracycline, rifampin, and furazolidone were 5.93%, 83.84%, 28.82%, 26.28%, 0.35%, 1.16%, and 0%, while secondary were 25.10%, 92.31%, 79.76%, 63.16%, 1.06%, 3.19%, and 0%, respectively. The resistance rates to amoxicillin, metronidazole, clarithromycin, and levofloxacin increased significantly with the number of treatment failures accumulated, and showed a linear trend. The proportion of primary and secondary multidrug-resistant (MDR) isolates were 17.79% and 63.16%, respectively. The MIC values of amoxicillin, clarithromycin, and levofloxacin were elevated significantly with medication courses increased. CONCLUSION: The prevalence of amoxicillin, clarithromycin, levofloxacin, and metronidazole resistance would increase rapidly following first-line treatment failure, as well as the MIC values of them. Clinicians should pay great attention to the first-line treatment to cure H. pylori infection successfully.

Identification of shared molecular mechanisms and diagnostic biomarkers between heart failure and idiopathic pulmonary fibrosis.

Background: Heart failure (HF) and idiopathic pulmonary fibrosis (IPF) are global public health concerns. The relationship between HF and IPF is widely acknowledged. However, the interaction mechanisms between these two diseases remain unclear, and early diagnosis is particularly difficult. Through the integration of bioinformatics and machine learning, our work aims to investigate common gene features, putative molecular causes, and prospective diagnostic indicators of IPF and HF. Methods: The Gene Expression Omnibus (GEO) database provided the RNA-seq datasets for HF and IPF. Utilizing a weighted gene co-expression network analysis (WGCNA), possible genes linked to HF and IPF were found. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were then employed to analyze the genes that were shared by HF and IPF. Using the cytoHubba and iRegulon algorithms, a competitive endogenous RNA (ceRNA) network was built based on seven basic diagnostic indicators. Additionally, hub genes were identified using machine learning approaches. External datasets were used to validate the findings. Lastly, the association between the number of immune cells in tissues and the discovered genes was estimated using the CIBERSORT method. Results: In total, 63 shared genes were identified between HF- and IPF-related modules using WGCNA. Extracellular matrix (ECM)/structure organization, ECM-receptor interactions, focal, and protein digestion and absorption, were shown to be the most enrichment categories in GO and KEGG enrichment analysis of common genes. Furthermore, a total of seven fundamental genes, including COL1A1, COL3A1, THBS2, CCND1, ASPN, FAP, and S100A12, were recognized as pivotal genes implicated in the shared pathophysiological pathways of HF and IPF, and TCF12 may be the most important regulatory transcription factor. Two characteristic molecules, CCND1 and NAP1L3, were selected as potential diagnostic markers for HF and IPF, respectively, using a support vector machine-recursive feature elimination (SVM-RFE) model. Furthermore, the development of diseases and diagnostic markers may be associated with immune cells at varying degrees. Conclusions: This study demonstrated that ECM/structure organisation, ECM-receptor interaction, focal adhesion, and protein digestion and absorption, are common pathogeneses of IPF and HF. Additionally, CCND1 and NAP1L3 were identified as potential diagnostic biomarkers for both HF and IPF. The results of our study contribute to the comprehension of the co-pathogenesis of HF and IPF at the genetic level and offer potential biological indicators for the early detection of both conditions.

Climate warming promotes collateral antibiotic resistance development in cyanobacteria.

Both cyanobacterial blooms and antibiotic resistance have aggravated worldwide and posed a great threat to public health in recent years. As a significant source and reservoir of water environmental resistome, cyanobacteria exhibit confusing discrepancy between their reduced susceptibility and their chronic exposure to antibiotic mixtures at sub-inhibitory concentrations. How the increasing temperature affects the adaptive evolution of cyanobacteria-associated antibiotic resistance in response to low-level antibiotic combinations under climate change remains unclear. Here we profiled the antibiotic interaction and collateral susceptibility networks among 33 commonly detected antibiotics in 600 cyanobacterial strains isolated from 50 sites across four eutrophicated lakes in China. Cyanobacteria-associated antibiotic resistance level was found positively correlated to antibiotic heterogeneity across all sites. Among 528 antibiotic combinations, antagonism was observed for 62 % interactions and highly conserved within cyanobacterial species. Collateral resistance was detected in 78.5 % of pairwise antibiotic interaction, leading to a widened or shifted upwards mutant selection window for increased opportunity of acquiring second-step mutations. We quantified the interactive promoting effect of collateral resistance and increasing temperature on the evolution of both phenotypic and genotypic cyanobacteria-associated resistance under chronic exposure to environmental level of antibiotic combinations. With temperature increasing from 16 °C to 36 °C, the evolvability index and genotypic resistance level increased by 1.25 - 2.5 folds and 3 - 295 folds in the collateral-resistance-informed lineages, respectively. Emergence of resistance mutation pioneered by tolerance, which was jointly driven by mutation rate and persister fraction, was found to be accelerated by increased temperature and antibiotic switching rate. Our findings provided mechanic insights into the boosting effect of climate warming on the emergence and development of cyanobacteria-associated resistance against collateral antibiotic phenotypes.

Gradually Self-Strengthen DNA Supramolecular Hydrogels.

The dynamic mechanical strength of the extracellular matrix (ECM) has been demonstrated to play important role in determining the cell behavior. Growing evidences suggest that the gradual stiffening process of the matrix is particularly decisive during tissue development and wound healing. Herein, a novel strategy to prepare hydrogels with gradually enhanced mechanical strength is provided. Such hydrogels could maintain the dynamic properties at their initial states, such as self-healing and shear-thinning properties. With subsequent slow covalent crosslinking, the stability and mechanical properties would be gradually improved. This method is useful for sequence programmability and oxidation strategies, which has provided an alternated tool to study cell behavior during dynamic increase in mechanical strength of ECM.

The Value of Nerve Ultrasound to Diagnose and Follow Up the Multifocal Neurolyphomatosis in the Upper Limb---- Case Report and Literature Review.

INTRODUCTION: Neurolymphomatosis (NL) is a rare disease. Ultrasound (US) plays a crucial role in diagnosing and following up the NL. CASE PRESENTATION: A 59-year-old man was hospitalized with acute pain in the left upper extremity. Ultrasound revealed segmental swelling of multiple nerves around his left elbow with abundant blood flow signals. Contrast-Enhanced Ultrasound (CEUS) showed a rapid, complete and homogenous enhancement in the nerve lesions in the early arterial phase. The NL was confirmed by imaging and flow cytometry, and he accepted chemotherapy. The posttherapeutic ultrasound showed that the nerves in the left upper limb were basically normal. Unfortunately, the patient died of cerebral metastasis in 5 months. CONCLUSION: The nerve US and CEUS can show specific manifestations and provide more diagnostic information about NL.

A tripartite evolutionary game study of low-carbon innovation system from the perspective of dynamic subsidies and taxes.

Traditional manufacturing industry is in the early stages of transition to low-carbon innovative production, and is in urgent need of a low-carbon innovation system to achieve the goal of carbon neutrality. In order to realize the effective supervision of enterprise carbon emissions, this paper constructs a tripartite evolutionary game model among the corporate, government and public from the perspective of dynamic subsidies and taxes. The main results are as follows. First, the increase in government subsidies to a certain extent will help encourage companies to choose low-carbon innovative production strategies, but more subsidies are not always better. Excessive subsidies will increase the cost of government regulation and reduce the probability of government regulation. Second, the tripartite evolutionary game system does not converge under the static subsidies and taxes mechanism. But the system could quickly converges to the stable condition under dynamic subsidies and taxes. The stable point is the situation of corporate low-carbon innovation, government regulation, and public supervision. Third, the public intervention and supervision can effectively prevent the phenomenon of government misconduct and enterprises over-emission production. And the influence of public reward and punishment is more effective for the government than for enterprises.

Fluorine-19 labeling of the tryptophan residues in the G protein-coupled receptor NK1R using the 5-fluoroindole precursor in Pichia pastoris expression.

In NMR spectroscopy of biomolecular systems, the use of fluorine-19 probes benefits from a clean background and high sensitivity. Therefore, 19F-labeling procedures are of wide-spread interest. Here, we use 5-fluoroindole as a precursor for cost-effective residue-specific introduction of 5-fluorotryptophan (5F-Trp) into G protein-coupled receptors (GPCRs) expressed in Pichia pastoris. The method was successfully implemented with the neurokinin 1 receptor (NK1R). The 19F-NMR spectra of 5F-Trp-labeled NK1R showed one well-separated high field-shifted resonance, which was assigned by mutational studies to the "toggle switch tryptophan". Residue-selective labeling thus enables site-specific investigations of this functionally important residue. The method described here is inexpensive, requires minimal genetic manipulation and can be expected to be applicable for yeast expression of GPCRs at large.

Reshaping the Landscape of the Genome: Toolkits for Precise DNA Methylation Manipulation and Beyond.

DNA methylation plays a pivotal role in various biological processes and is highly related to multiple diseases. The exact functions of DNA methylation are still puzzling due to its uneven distribution, dynamic conversion, and complex interactions with other substances. Current methods such as chemical- and enzyme-based sequencing techniques have enabled us to pinpoint DNA methylation at single-base resolution, which necessitated the manipulation of DNA methylation at comparable resolution to precisely illustrate the correlations and causal relationships between the functions of DNA methylation and its spatiotemporal patterns. Here a perspective on the past, recent process, and future of precise DNA methylation tools is provided. Specifically, genome-wide and site-specific manipulation of DNA methylation methods is discussed, with an emphasis on their principles, limitations, applications, and future developmental directions.

Impact of Helicobacter pylori colonization density and depth on gastritis severity.

BACKGROUND AND OBJECTIVES: Helicobacter pylori (H. pylori) infection is the most common etiology of chronic gastric. H. pylori gastritis would gradually evolve into gastric atrophy, intestinal metaplasia, dysplasia and malignant lesions. Herein, this study aimed to investigate the potential impact of H. pylori colonization density and depth on the severity of histological parameters of gastritis. METHODS: A prospective monocentric study was conducted from December 2019 to July 2022, enrolling patients with confirmed chronic H. pylori infection via histopathological evaluation. H. pylori colonization status was detected by immunohistochemical staining, pathological changes of gastric specimens were detected by hematoxylin eosin staining. Epidemiological, endoscopic and histopathological data were collected. RESULTS: A total of 1120 patients with a mean age of 45.8 years were included. Regardless of the previous history of H. pylori eradication treatment, significant correlations were observed between the density and depth of H. pylori colonization and the intensity of gastritis activity (all P < 0.05). Patients with the lowest level of H. pylori colonization density and depth exhibited the highest level of mild activity. In whole participants and anti-H. pylori treatment-naive participants, H. pylori colonization density and depth were markedly correlated with the severity of chronic gastritis and gastric atrophy (all P < 0.05). H. pylori colonization density (P = 0.001) and depth (P = 0.047) were significantly associated with ulcer formation in patients naive to any anti-H. pylori treatment. No significant associations were observed between the density and depth of H. pylori colonization and other histopathological findings including lymphadenia, lymphoid follicle formation and dysplasia. CONCLUSIONS: As the density and depth of H. pylori colonization increased, so did the activity and severity of gastritis, along with an elevated risk of ulcer formation.

Rational Design of DNA Hydrogels Based on Molecular Dynamics of Polymers.

In recent years, DNA has emerged as a fascinating building material to engineer hydrogel due to its excellent programmability, which has gained considerable attention in biomedical applications. Understanding the structure-property relationship and underlying molecular determinants of DNA hydrogel is essential to precisely tailor its macroscopic properties at molecular level. In this review, the rational design principles of DNA molecular networks based on molecular dynamics of polymers on the temporal scale, which can be engineered via the backbone rigidity and crosslinking kinetics, are highlighted. By elucidating the underlying molecular mechanisms and theories, it is aimed to provide a comprehensive overview of how the tunable DNA backbone rigidity and the crosslinking kinetics lead to desirable macroscopic properties of DNA hydrogels, including mechanical properties, diffusive permeability, swelling behaviors, and dynamic features. Furthermore, it is also discussed how the tunable macroscopic properties make DNA hydrogels promising candidates for biomedical applications, such as cell culture, tissue engineering, bio-sensing, and drug delivery.

Clinical neuromodulatory effects of deep brain stimulation in disorder of consciousness: A literature review.

BACKGROUND: The management of patients with disorders of consciousness (DOC) presents substantial challenges in clinical practice. Deep brain stimulation (DBS) has emerged as a potential therapeutic approach, but the lack of standardized regulatory parameters for DBS in DOC hinders definitive conclusions. OBJECTIVE: This comprehensive review aims to provide a detailed summary of the current issues concerning patient selection, target setting, and modulation parameters in clinical studies investigating the application of DBS for DOC patients. METHODS: A meticulous systematic analysis of the literatures was conducted, encompassing articles published from 1968 to April 2023, retrieved from reputable databases (PubMed, Embase, Medline, and Web of Science). RESULTS: The systematic analysis of 21 eligible articles, involving 146 patients with DOC resulting from acquired brain injury or other disorders, revealed significant insights. The most frequently targeted regions were the Centromedian-parafascicular complex (CM-pf) nuclei and central thalamus (CT), both recognized for their role in regulating consciousness. However, other targets have also been explored in different studies. The stimulation frequency was predominantly set at 25 or 100 Hz, with pulse width of 120 µs, and voltages ranged from 0 to 4 V. These parameters were customized based on individual patient responses and evaluations. The overall clinical efficacy rate in all included studies was 39.7%, indicating a positive effect of DBS in a subset of DOC patients. Nonetheless, the assessment methods, follow-up durations, and outcome measures varied across studies, potentially contributing to the variability in reported efficacy rates. CONCLUSION: Despite the challenges arising from the lack of standardized parameters, DBS shows promising potential as a therapeutic option for patients with DOC. However, there still remains the need for standardized protocols and assessment methods, which are crucial to deepen the understanding and optimizing the therapeutic potential of DBS in this specific patient population.

The impact of climate change and human activities on the change in the net primary productivity of vegetation-taking Sichuan Province as an example.

Vegetation is an essential component of terrestrial ecosystems, influenced by climate change and human activities. Quantifying the relative contributions of climate change and human activities to vegetation dynamics is crucial for addressing global climate change. Sichuan Province is one of the essential ecological functional areas in the upper reaches of the Yangtze River, and its vegetation change is of great significance to the environmental function and ecological security of the Yangtze River Basin and southwest China. In this paper, the modified Carnegie-Ames-Stanford Approach(CASA) model was used to estimate the monthly NPP (Net Primary Productivity) of vegetation in Sichuan Province from 2000 to 2018, and the univariate linear regression analysis was used to analyze the temporal and spatial variation of vegetation NPP in Sichuan Province from 2000 to 2018. In addition, taking vegetation NPP as an index, Pearson correlation analysis, partial correlation analysis, and second-order partial correlation analysis were carried out to quantitatively analyze the contribution of climate change and human activities to vegetation NPP. Finally, the Hurst index and nonparametric Man-Kendall significance test were used to predict the future change trend of vegetation NPP in Sichuan Province. The results show that (1) from 2000 to 2018, the NPP of vegetation in Sichuan Province has a significant increasing trend (Slope = 6.09gC·m-2·a-1), with a multi-year average of 438.72 gC·m-2·a-1, showing a trend of low in the east and high in the middle. The response of vegetation NPP to altitude is different at different elevations; (2) the contribution rates of climate change and human activities to vegetation NPP change are 4.12gC·m-2·a-1 and 1.97gC·m-2·a-1, respectively. In contrast, the impact of human activities on NPP is more significant than climate change. Human activities are the main factors affecting vegetation restoration and degradation in Sichuan Province. However, the positive contribution to NPP change is less than climate change; (3) the future vegetation NPP change trend in Sichuan Province is mainly rising, and the same direction change trend is much larger than the reverse change trend. The areas with an increasing trend in the future account for 89.187% of the total area. This research helps understand the impact of climate change and human activities on vegetation change in Sichuan Province. It offers scientific bases for vegetation restoration and ecosystem management in Sichuan and the surrounding areas.

Identification and visualization of environmental microplastics by Raman imaging based on hyperspectral unmixing coupled machine learning.

Microplastics (MPs) are ubiquitous contaminants that have become an emerging pollutant of concern, potentially threatening human health and ecosystem environments. Although current detection methods can accurately identify various types of MPs, it remains necessary to develop non-destructive and rapid methods to meet growing demands for detection. Herein, we combine a hyperspectral unmixing method and machine learning to analyse Raman imaging data of environmental MPs. Five MPs types including poly(butylene adipate-co-terephthalate) (PBAT), poly(butylene succinate) (PBS), p-polyethylene (PE), polystyrene (PS) and polypropylene (PP) were visualized and identified. Individual or mixed pure or aged MPs along with environmental samples were analysed by Raman imaging. Alternating volume maximization (AVmax) combined with unconstrained least squares (UCLS) method estimated end members and abundance maps of each of the MPs in the samples. Pearson correlation coefficients (r) were used as the evaluation index; the results showed that there is a high similarity between the raw spectra and the average spectra calculated by AVmax. This indicates that Raman imaging based on machine learning and hyperspectral unmixing is a novel imaging analysis method that can directly identify and visualize MPs in the environment.

Dissecting the intricacies of human antibody responses to SARS-CoV-1 and SARS-CoV-2 infection.

The 2003 severe acute respiratory syndrome coronavirus (SARS-CoV-1) causes more severe disease than SARS-CoV-2, which is responsible for COVID-19. However, our understanding of antibody response to SARS-CoV-1 infection remains incomplete. Herein, we studied the antibody responses in 25 SARS-CoV-1 convalescent patients. Plasma neutralization was higher and lasted longer in SARS-CoV-1 patients than in severe SARS-CoV-2 patients. Among 77 monoclonal antibodies (mAbs) isolated, 60 targeted the receptor-binding domain (RBD) and formed 7 groups (RBD-1 to RBD-7) based on their distinct binding and structural profiles. Notably, RBD-7 antibodies bound to a unique RBD region interfaced with the N-terminal domain of the neighboring protomer (NTD proximal) and were more prevalent in SARS-CoV-1 patients. Broadly neutralizing antibodies for SARS-CoV-1, SARS-CoV-2, and bat and pangolin coronaviruses were also identified. These results provide further insights into the antibody response to SARS-CoV-1 and inform the design of more effective strategies against diverse human and animal coronaviruses.

Epileptic Seizure Prediction Using Attention Augmented Convolutional Network.

Early seizure prediction is crucial for epilepsy patients to reduce accidental injuries and improve their quality of life. Identifying pre-ictal EEG from the inter-ictal state is particularly challenging due to their nonictal nature and remarkable similarities. In this study, a novel epileptic seizure prediction method is proposed based on multi-head attention (MHA) augmented convolutional neural network (CNN) to address the issue of CNN's limit of capturing global information of input signals. First, data enhancement is performed on original EEG recordings to balance the pre-ictal and inter-ictal EEG data, and the EEG recordings are sliced into 6-second-long EEG segments. Subsequently, EEG time-frequency distribution is obtained using Stockwell transform (ST), and the attention augmented convolutional network is employed for feature extraction and classification. Finally, post-processing is utilized to reduce the false prediction rate (FPR). The CHB-MIT EEG database was used to evaluate the system. The validation results showed a segment-based sensitivity of 98.24% and an event-based sensitivity of 94.78% with a FPR of 0.05/h were yielded, respectively. The satisfying results of the proposed method demonstrate its possible potential for clinical applications.

A novel magnetic Fe3O4/cellulose nanofiber/polyethyleneimine/thiol-modified montmorillonite aerogel for efficient removal of heavy metal ions: Adsorption behavior and mechanism study.

To efficiently remove heavy metals from wastewater, designing an adsorbent with high adsorption capacity and ease of recovery is necessary. This paper presents a novel magnetic hybridized aerogel, Fe3O4/cellulose nanofiber/polyethyleneimine/thiol-modified montmorillonite (Fe3O4/CNF/PEI/SHMMT), and explores its adsorption performance and mechanism for Pb2+, Cu2+, and Cd2+ in aqueous solutions. The hybrid aerogel has a slit-like porous structure and numerous exposed active sites, which facilitates the uptake of metal ions by adsorption. Pb2+, Cu2+, and Cd2+ adsorption by the hybridized aerogel followed the second-order kinetics and the Langmuir isotherm model, the maximum adsorption of Pb2+, Cu2+, and Cd2+ at 25 °C, pH = 6, 800 mg/L was 429.18, 381.68 and 299.40 mg/g, respectively. The adsorption process was primarily attributed to monolayer chemical adsorption, a spontaneous heat-absorption reaction. FTIR, XPS and DFT studies confirmed that the adsorption mechanisms of Fe3O4/CNF/PEI/SHMMT on Pb2+, Cu2+, and Cd2+ were mainly chelation, coordination, and ion exchange. The lowest adsorption energy of Pb2+ on the hybrid aerogel was calculated to be -2.37 Ha by DFT, which indicates that the sample has higher adsorption affinity and preferential selectivity for Pb2+. After 5 cycles, the adsorption efficiency of the aerogel was still >85 %. The incorporation of Fe3O4 improved the mechanical properties of the aerogel. The Fe3O4/CNF/PEI/SHMMT has fast magnetic responsiveness, and it is easy to be separated and recovered after adsorption, which is a promising potential for the treatment of heavy metal ions.

Helicobacter pylori infection reduces the efficacy of cancer immunotherapy: A systematic review and meta-analysis.

BACKGROUND: Cancer immunotherapy has shown promising results in several tumors, but its efficacy is influenced by the immune state of the body. Helicobacter pylori (H. pylori) infection can modulate the immune function of the body through various pathways, ultimately affecting the effectiveness of cancer immunotherapy. AIM: In this meta-analysis, we aimed to explore the association between H. pylori infection and the efficacy of cancer immunotherapy. METHODS: We conducted a comprehensive search of PubMed, Embase, Web of Science, and Cochrane Central Register of Controlled Trials to identify relevant articles. We extracted and pooled the hazard ratio (HR) of the overall survival (OS) and progression-free survival (PFS) by Review Manager 5.4. RESULTS: Our analysis included four studies with a total of 263 participants. Compared to the control group, patients receiving cancer immunotherapy with H. pylori infection had a shorter OS (HR = 2.68, 95% CI: 2.00-4.11, p < 0.00001) and PFS (HR = 2.25, 95% CI: 1.66-3.60, p < 0.00001). CONCLUSION: Our meta-analysis suggested that H. pylori infection has a detrimental effect on cancer immunotherapy.