Prognostic value of growth differentiation factor-15 in Chinese patients with heart failure: A prospective observational study

  Background: Growth differentiation factor-15 (GDF-15), a biomarker associated with remodeling, oxidative stress and inflammation, has been used to stratify heart failure (HF) patients. However, its prognostic value in Chinese HF patients is still unknown. Methods: GDF-15 levels were examined on admission in 272 consecutive HF patients in Beijing Hospital (a Chinese tertiary medical center) by a commercial enzyme-linked immunosorbent assay. We recorded the incidence of all-cause mortality and/or readmission for HF during a median follow-up period of 558 days. Patients were stratified according to the tertiles of GDF-15. Results: Fifty-three (19.5%) patients died and 103 (37.9%) patients had major adverse cardiac events (MACE) which included the composite outcome of all-cause mortality or readmission for HF at the end of follow-up. Kaplan-Meier survival curves showed that the third tertile of GDF-15 was associated with increased rate of all-cause mortality (compared with the first and second tertiles, log rank p = 0.001 and 0.001, respectively) or MACE (compared with the first and second tertiles, log rank p = 0.002 and p < 0.001, respectively). In addition, multivariate Cox regression model showed that the highest tertile of GDF-15 was independently associated with increased risk of all-cause death (hazard ratio = 5.95, 95% confidence interval 1.88–18.78, p = 0.002) compared with the lowest tertile after adjustment for related clinical variables such as age, renal function or N-terminal pro-B-type natriuretic peptide.  Conclusions: Plasma GDF-15 is an independent predictor of all-cause mortality in Chinese patients with HF. It may potentially be used to stratify and prognosticate HF patients

DevNet: Self-supervised Monocular Depth Learning via Density Volume Construction

Self-supervised depth learning from monocular images normally relies on the 2D pixel-wise photometric relation between temporally adjacent image frames. However, they neither fully exploit the 3D point-wise geometric correspondences, nor effectively tackle the ambiguities in the photometric warping caused by occlusions or illumination inconsistency. To address these problems, this work proposes Density Volume Construction Network (DevNet), a novel self-supervised monocular depth learning framework, that can consider 3D spatial information, and exploit stronger geometric constraints among adjacent camera frustums. Instead of directly regressing the pixel value from a single image, our DevNet divides the camera frustum into multiple parallel planes and predicts the pointwise occlusion probability density on each plane. The final depth map is generated by integrating the density along corresponding rays. During the training process, novel regularization strategies and loss functions are introduced to mitigate photometric ambiguities and overfitting. Without obviously enlarging model parameters size or running time, DevNet outperforms several representative baselines on both the KITTI-2015 outdoor dataset and NYU-V2 indoor dataset. In particular, the root-mean-square-deviation is reduced by around 4% with DevNet on both KITTI-2015 and NYU-V2 in the task of depth estimation. Code is available at https://github.com/gitkaichenzhou/DevNet.Comment: Accepted by European Conference on Computer Vision 2022 (ECCV2022

Preparation, characterization and targeting of micronized 10-hydroxycamptothecin-loaded folate-conjugated human serum albumin nanoparticles to cancer cells

Qingyong Li, Chen Liu, Xiuhua Zhao, Yuangang Zu, Ying Wang, Baoyou Zhang, Dongmei Zhao, Qi Zhao, Lin Su, Yang Gao, Baihe SunKey Laboratory of Forest Plant Ecology, Ministry of Education, Northeast Forestry University, Harbin, Heilongjiang, People's Republic of ChinaBackground: The purpose of this study was to develop a method for targeted delivery of 10-hydroxycamptothecin (HCPT)-loaded nanoparticles (NPs) to cancer cells.Methods: We first used a supercritical antisolvent process to prepare micronized HCPT (nHCPT), and then folate-conjugated human serum albumin (HSA) nHCPT-loaded NPs (FA-HSA-nHCPT-NPs) were prepared using a NP-coated method combined with a desolvation technique. The amount of folate conjugation was 16 µg · mg-1 HSA.Results: The particle size of the spherical nHCPT microparticles obtained was 118.5 ± 6.6 nm. The particle size and zeta potential of the FA-HSA-nHCPT-NPs were 233.9 ± 1.2 nm and -25.23 ± 2.98 mV, respectively. The FA-HSA-nHCPT-NPs exhibited a smooth surface and a distinct spherical shape, and the results of differential scanning calorimetry and X-ray diffraction indicated that the FA-HSA-nHCPT-NPs presented in a nanostructured amorphous state. The FA-HSA-nHCPT-NPs showed sustained-release characteristics for 120 hours in vitro, with a drug-loading content of 7.3% and an encapsulating efficiency of 79.1%.Conclusion: The FA-NPs were effective delivery systems for uptake by SGC7901 cells compared with folate-free NPs. These results suggest that a NP-coated method combined with a desolvation technique is effective for preparing NPs with drugs having poor solubility in water and most organic solvents, using albumin as the wall material. FA-HSA-NPs are a stable delivery system and have the potential for targeted delivery of anticancer drugs.Keywords: nanoparticle-coated, desolvation technique, 10-hydroxycamptothecin, human serum albumin, folate, targeted delivery&nbsp

The novel role of LDHA/LDHB in the prognostic value and tumor-immune infiltration in clear cell renal cell carcinoma

Lactate dehydrogenase (LDH) is a crucial glycolytic enzyme which mediates the metabolic plasticity of cancer cells, however its clinical significance in renal cell carcinoma (RCC) is poorly understood. Herein, we examined the prognostic significance of the two primary components of LDH, i.e., LDHA and LDHB, in clear cell RCC (ccRCC) patients and further explored their association with immune infiltration in ccRCC. In this study, the expression levels of LDHA and LDHB were examined in ccRCC and adjacent normal tissues by Gene Expression Profiling Interactive Analysis 2 (GEPIA2), UALCAN, and western blotting (WB) analyses, and their prognostic values were estimated in 150 ccRCC and 30 adjacent normal tissues by immunohistochemistry (IHC) analysis. The relationship to immune infiltration of LDHA and LDHB genes was further investigated using tumor immune estimation resource 2 (TIMER2) and Tumor-Immune System Interactions and DrugBank (TISIDB) databases, respectively. Public databases and WB analyses demonstrated higher LDHA and lower LDHB in ccRCC than in non-tumor tissues. IHC analysis revealed that LDHA and LDHB expression profiles were significantly associated with tumor grade, stage, size, and overall survival (OS). Univariate survival analysis displayed that high grade, advanced stage, large tumor, metastasis, high LDHA, and low LDHB expression were significantly associated with a poorer OS, and multivariate analysis revealed tumor stage and LDHB were identified as independent predictors for OS in patients with ccRCC. Further TIMER2 and TISIDB analyses demonstrated that LDHA and LDHB expression was significantly related to multiple immune cells and immune inhibitors in over 500 ccRCC patients. These findings revealed that LDHB was an independent favorable predictor, and LDHA and LDHB correlated with tumor immune infiltrates in ccRCC patients, which indicated LDHA/LDHB could be implicated in the tumorigenesis of ccRCC and might be potential therapeutic targets for patients with ccRCC

GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing

Multimodal large language models (MLLMs) are designed to process and integrate information from multiple sources, such as text, speech, images, and videos. Despite its success in language understanding, it is critical to evaluate the performance of downstream tasks for better human-centric applications. This paper assesses the application of MLLMs with 5 crucial abilities for affective computing, spanning from visual affective tasks and reasoning tasks. The results show that \gpt has high accuracy in facial action unit recognition and micro-expression detection while its general facial expression recognition performance is not accurate. We also highlight the challenges of achieving fine-grained micro-expression recognition and the potential for further study and demonstrate the versatility and potential of \gpt for handling advanced tasks in emotion recognition and related fields by integrating with task-related agents for more complex tasks, such as heart rate estimation through signal processing. In conclusion, this paper provides valuable insights into the potential applications and challenges of MLLMs in human-centric computing. Our interesting examples are at https://github.com/EnVision-Research/GPT4Affectivity

Development of iFOX-hunting as a functional genomic tool and demonstration of its use to identify early senescence-related genes in the polyploid \u3ci\u3eBrassica napus\u3c/i\u3e

Functional genomic studies of many polyploid crops, including rapeseed (Brassica napus), are constrained by limited tool sets. Here we report development of a gain-of-function platform, termed ‘iFOX (inducible Full-length cDNA OvereXpressor gene)-Hunting’, for inducible expression of B. napus seed cDNAs in Arabidopsis. A Gateway-compatible plant gene expression vector containing a methoxyfenozide-inducible constitutive promoter for transgene expression was developed. This vector was used for cloning of random cDNAs from developing B. napus seeds and subsequent Agrobacterium-mediated transformation of Arabidopsis. The inducible promoter of this vector enabled identification of genes upon induction that are otherwise lethal when constitutively overexpressed and to control developmental timing of transgene expression. Evaluation of a subset of the resulting ~6000 Arabidopsis transformants revealed a high percentage of lines with full-length B. napus transgene insertions. Upon induction, numerous iFOX lines with visible phenotypes were identified, including one that displayed early leaf senescence. Phenotypic analysis of this line (rsl-1327) after methoxyfenozide induction indicated high degree of leaf chlorosis. The integrated B. napus cDNA was identified as a homolog of an Arabidopsis acyl-CoA binding protein (ACBP) gene designated BnACBP1-like. The early senescence phenotype conferred by BnACBP1-like was confirmed by constitutive expression of this gene in Arabidopsis and B. napus. Use of the inducible promoter in the iFOX line coupled with RNA-Seq analyses allowed mechanistic clues and a working model for the phenotype associated with BnACBP1-like expression. Our results demonstrate the utility of iFOX-Hunting as a tool for gene discovery and functional characterization of Brassica napus genome

Study of mercury transport and transformation in mangrove forests using stable mercury isotopes.

Mangrove forests are important wetland ecosystems that are a sink for mercury from tides, rivers and precipitation, and can also be sources of mercury production and export. Natural abundance mercury stable isotope ratios have been proven to be a useful tool to investigate mercury behavior in various ecosystems. In this study, mercury isotopic data were collected from seawater, sediments, air, and plant tissues in two mangrove forests in Guangxi and Fujian provinces, China, to study the transport and transformation of mercury in mangrove sediments. The mangroves were primarily subject to mercury inputs from external sources, such as anthropogenic activities, atmospheric deposition, and the surrounding seawater. An isotope mixing model based on mass independent fractionation (MIF) estimated that the mangrove wetland ecosystems accounted for <40% of the mercury in the surrounding seawater. The mercury in plant root tissues was derived mainly from sediments and enriched with light mercury isotopes. The exogenous mercury inputs from the fallen leaves were diluted by seawater, leading to a positive Δ199Hg offset between the fallen leaves and sediments. Unlike river and lake ecosystems, mangrove ecosystems are affected by tidal action, and the δ202Hg and Δ199Hg values of sediments were more negative than that of the surrounding seawater. The isotopic signature differences between these environmental samples were partially due to isotope fractionation driven by various physical and chemical processes (e.g., sorption, photoreduction, deposition, and absorption). These results contribute to a better understanding of the biogeochemical cycling of mercury in mangrove wetland ecosystems

Activation of Nrf2 by Sulforaphane Inhibits High Glucose-Induced Progression of Pancreatic Cancer via AMPK Dependent Signaling

Background/Aims: Sulforaphane (SFN) is known for its potent bioactive properties, such as anti-inflammatory and anti-tumor effects. However, its anti-tumor effect on pancreatic cancer is still poorly understood. In the present study, we explored the therapeutic potential of SFN for pancreatic cancer and disclosed the underlying mechanism. Methods: Panc-1 and MiaPaca-2 cell lines were used in vitro. The biological function of SFN in pancreatic cancer was measured using EdU staining, colony formation, apoptosis, migration and invasion assays. Reactive oxygen species (ROS) production was measured using 2’-7’-Dichlorofluorescein diacetate (DCF-DA) fluorometric analysis. Western blotting and immunofluorescence were used to measure the protein levels of p-AMPK and epithelial-mesenchymal transition (EMT) pathway-related proteins, and cellular translocation of nuclear factor erythroid 2-related factor 2 (Nrf2). Nude mice and transgenic pancreatic cancer mouse model were used to measure the therapeutic potential of SFN on pancreatic cancer. Results: SFN can inhibit pancreatic cancer cell growth， promote apoptosis, curb colony formation and temper the migratory and invasion ability of pancreatic cancer cells. Mechanistically, excessive ROS production induced by SFN activated AMPK signaling and promoted the translocation of Nrf2, resulting in cell viability inhibition of pancreatic cancer. Pretreatment with compound C, a small molecular inhibitor of AMPK signaling, reversed the subcellular translocation of Nrf2 and rescued cell invasion ability. With nude mice and pancreatic cancer transgenic mouse, we identified SFN could inhibit tumor progression, with smaller tumor size and slower tumor progression in SFN treatment group. Conclusion: Our study not only elucidates the mechanism of SFN-induced inhibition of pancreatic cancer in both normal and high glucose condition, but also testifies the dual-role of ROS in pancreatic cancer progression. Collectively, our research suggests that SFN may serve as a potential therapeutic choice for pancreatic cancer

Associations between blood systemic inflammatory markers and anxiety in Helicobacter pylori-infected patients

BackgroundChronic Helicobacter pylori (H. pylori) infection is associated with both gastrointestinal symptoms and systemic inflammation, which may contribute to the development of psychiatric disorders, particularly anxiety. Appropriate psychiatric interventions have been shown to significantly enhance treatment outcomes in patients undergoing clinical management for H. pylori infection. Early screening for anxiety in this population is therefore of critical clinical importance. This study aimed to identify potential biomarkers for anxiety detection and evaluate the relationship between these biomarkers and anxiety symptoms in H. pylori-positive individuals.MethodA total of 160 participants (81 H. pylori-positive and 79 H. pylori-negative patients) were enrolled in this study. All participants underwent standardized neuropsychological assessments and venous blood collection. Systemic inflammation indices were derived from routine hematological parameters.Results(1) H. pylori-positive patients showed significantly higher anxiety scores [Hamilton Anxiety Scale (HAMA) and Self-Rating Anxiety Scale (SAS)] and elevated inflammatory markers [systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)] as compared to H. pylori-negative ones. (2) AISI showed optimal diagnostic accuracy for infection status [area under the curve (AUC) =0.746)], followed by SIRI and SII (both AUC &gt; 0.7). (3) In H. pylori-positive patients, inflammatory markers correlated with both anxiety scores and glial fibrillary acidic protein (GFAP) levels. (4) Interactions between serum GFAP and blood SII and AISI were significantly associated with HAMA and SAS scores in H. pylori-positive patients. (5) The GFAP as the mediator, affected the relationship between the blood levels of systemic inflammatory markers and HAMA and SAS scores in H. pylori-positive patients.ConclusionOur findings suggest systemic inflammation indices contribute to anxiety development in H. pylori infection and may serve as practical biomarkers for anxiety screening

Reactive Oxygen Species and Targeted Therapy for Pancreatic Cancer

Pancreatic cancer is the fourth leading cause of cancer-related death in the United States. Reactive oxygen species (ROS) are generally increased in pancreatic cancer cells compared with normal cells. ROS plays a vital role in various cellular biological activities including proliferation, growth, apoptosis, and invasion. Besides, ROS participates in tumor microenvironment orchestration. The role of ROS is a doubled-edged sword in pancreatic cancer. The dual roles of ROS depend on the concentration. ROS facilitates carcinogenesis and cancer progression with mild-to-moderate elevated levels, while excessive ROS damages cancer cells dramatically and leads to cell death. Based on the recent knowledge, either promoting ROS generation to increase the concentration of ROS with extremely high levels or enhancing ROS scavenging ability to decrease ROS levels may benefit the treatment of pancreatic cancer. However, when faced with oxidative stress, the antioxidant programs of cancer cells have been activated to help cancer cells to survive in the adverse condition. Furthermore, ROS signaling and antioxidant programs play the vital roles in the progression of pancreatic cancer and in the response to cancer treatment. Eventually, it may be the novel target for various strategies and drugs to modulate ROS levels in pancreatic cancer therapy