Investigation and identification of let-7a related functional proteins in gastric carcinoma by proteomics

Abstract. MicroRNAs are small noncoding RNA molecules that control expression of target genes. Our previous studies show that let-7a decreased in gastric carcinoma and that up-regulation of let-7a by gene augmentation inhibited gastric carcinoma cell growth both in vitro and in vivo, whereas it remains largely unclear as to how let-7a affects tumor growth. In this study, proteins associated with the function of let-7a were detected by high throughout screening. The cell line of SGC-7901 stablely overexpressing let-7a was successfully established by gene cloning. Two-dimensional gel electrophoresis (2-DEy was used to separate the total proteins of SGC-7901/let-7a, SGC-7901/EV and SGC-7901, and PDQuest software was applied to analyze 2-DE images. Ten different protein spots were identified by MALDI-TOF-MS, and they may be the proteins associated with let-7a function. The overexpressed proteins included Antioxidant protein 2, Insulin-like growth factor binding protein 2, Protein disulfide isomerase A2, C-1-tetrahydrofolate synthase, Cyclin-dependent kinase inhibitor1 (CDKN1) and Rho-GTPase activating protein 4. The underexpressed proteins consisted of S-phase kinase-associated protein 2 (Spk2), Platelet membrane glycoprotein, Fibronectin and Cks1 protein. Furthermore, the different expression levels of the partial proteins (CDKN1, Spk2 and Fibronectin) were confirmed by western blot analysis. The data suggest that these differential proteins are involved in a novel let-7a signal pathway and these findings provide the basis to investigate the functional mechanisms of let-7a in gastric carcinoma

Control-free and efficient integrated photonic neural networks via hardware-aware training and pruning

Integrated photonic neural networks (PNNs) are at the forefront of AI computing, leveraging on light's unique properties, such as large bandwidth, low latency, and potentially low power consumption. Nevertheless, the integrated optical components within PNNs are inherently sensitive to external disturbances and thermal interference, which can detrimentally affect computing accuracy and reliability. Current solutions often use complicated control methods, resulting in high hardware complexity impractical for large-scale PNNs. In response, we propose a novel hardware-aware training and pruning approach. The core idea is to train the parameters of a physical neural network towards its noise-robust and energy-efficient region. This innovation enables control-free and energy-efficient photonic computing. Our method is validated across diverse integrated PNN architectures. Through experimental validation, our approach significantly enhances the computing precision of MRR-based PNN, achieving a notable 4-bit improvement without the need for complex device control mechanisms or energy-intensive temperature stabilization circuits. Specifically, it improves the accuracy of experimental handwritten digit classification from 67.0% to 95.0%, nearing theoretical limits and achieved without a thermoelectric controller. Additionally, this approach reduces the energy by tenfold. We further extend the validation to various architectures, such as PCM-based PNN, demonstrating the broad applicability of our approach across different platforms. This advancement represents a significant step towards the practical, energy-efficient, and noise-resilient implementation of large-scale integrated PNNs.Comment: 21 pages, 6 figure

Association of urban forest landscape characteristics with biomass and soil carbon stocks in Harbin City, Northeastern China

Background Urban forests help in mitigating carbon emissions; however, their associations with landscape patterns are unclear. Understanding the associations would help us to evaluate urban forest ecological services and favor urban forest management via landscape regulations. We used Harbin, capital city of the northernmost province in China, as an example and hypothesized that the urban forests had different landscape metrics among different forest types, administrative districts, and urban–rural gradients, and these differences were closely associated with forest carbon sequestration in the biomass and soils. Methods We extracted the urban forest tree coverage area on the basis of 2 GF-1 remote sensing images and object-oriented based classification method. The analysis of forest landscape patterns and estimation of carbon storage were based on tree coverage data and 199 plots. We also examined the relationships between forest landscape metrics and carbon storage on the basis of forest types, administrative districts, ring roads, and history of urban settlements by using statistical methods. Results The small patches covering an area of less than 0.5 ha accounted for 72.6% of all patches (average patch size, 0.31 ha). The mean patch size (AREA_MN) and largest patch index (LPI) were the highest in the landscape and relaxation forest and Songbei District. The landscape shape index (LSI) and number of patches linearly decreased along rural-urban gradients (p < 0.05). The tree biomass carbon storage varied from less than 10 thousand tons in the urban center (first ring road region and 100-year regions) to more than 100 thousand tons in the rural regions (fourth ring road and newly urbanized regions). In the same urban–rural gradients, soil carbon storage varied from less than five thousand tons in the urban centers to 73–103 thousand tons in the rural regions. The association analysis indicated that the total forest area was the key factor that regulates total carbon storage in trees and soils. However, in the case of carbon density (ton ha−1), AREA_MN was strongly associated with tree biomass carbon, and soil carbon density was negatively related to LSI (p < 0.01) and AREA_MN (p < 0.05), but positively related to LPI (p < 0.05). Discussion The urban forests were more fragmented in Harbin than in other provincial cities in Northeastern China, as shown by the smaller patch size, more complex patch shape, and larger patch density. The decrease in LSI along the rural-urban gradients may contribute to the forest carbon sequestrations in downtown regions, particularly underground soil carbon accumulation, and the increasing patch size may benefit tree carbon sequestration. Our findings help us to understand how forest landscape metrics are associated with carbon storage function. These findings related to urban forest design may maximize forest carbon sequestration services and facilitate in precisely estimating the forest carbon sink

Minimally Supervised Categorization of Text with Metadata

Document categorization, which aims to assign a topic label to each document, plays a fundamental role in a wide variety of applications. Despite the success of existing studies in conventional supervised document classification, they are less concerned with two real problems: (1) the presence of metadata: in many domains, text is accompanied by various additional information such as authors and tags. Such metadata serve as compelling topic indicators and should be leveraged into the categorization framework; (2) label scarcity: labeled training samples are expensive to obtain in some cases, where categorization needs to be performed using only a small set of annotated data. In recognition of these two challenges, we propose MetaCat, a minimally supervised framework to categorize text with metadata. Specifically, we develop a generative process describing the relationships between words, documents, labels, and metadata. Guided by the generative model, we embed text and metadata into the same semantic space to encode heterogeneous signals. Then, based on the same generative process, we synthesize training samples to address the bottleneck of label scarcity. We conduct a thorough evaluation on a wide range of datasets. Experimental results prove the effectiveness of MetaCat over many competitive baselines.Comment: 10 pages; Accepted to SIGIR 2020; Some typos fixe

Inhibition of TNF-α Improves the Bladder Dysfunction That Is Associated With Type 2 Diabetes

Diabetic bladder dysfunction (DBD) is common and affects 80% of diabetic patients. However, the molecular mechanisms underlying DBD remain elusive because of a lack of appropriate animal models. We demonstrate DBD in a mouse model that harbors hepatic-specific insulin receptor substrate 1 and 2 deletions (double knockout [DKO]), which develops type 2 diabetes. Bladders of DKO animals exhibited detrusor overactivity at an early stage: increased frequency of nonvoiding contractions during bladder filling, decreased voided volume, and dispersed urine spot patterns. In contrast, older animals with diabetes exhibited detrusor hypoactivity, findings consistent with clinical features of diabetes in humans. The tumor necrosis factor (TNF) superfamily genes were upregulated in DKO bladders. In particular, TNF-α was upregulated in serum and in bladder smooth muscle tissue. TNF-α augmented the contraction of primary cultured bladder smooth muscle cells through upregulating Rho kinase activity and phosphorylating myosin light chain. Systemic treatment of DKO animals with soluble TNF receptor 1 (TNFRI) prevented upregulation of Rho A signaling and reversed the bladder dysfunction, without affecting hyperglycemia. TNFRI combined with the antidiabetic agent, metformin, improved DBD beyond that achieved with metformin alone, suggesting that therapies targeting TNF-α may have utility in reversing the secondary urologic complications of type 2 diabetes

The rising death burden of atrial fibrillation and flutter in low-income regions and younger populations

ObjectiveThe aim of the study was to depict the global death burden of atrial fibrillation and/or flutter (AFF) between 1990 and 2019 and predict this burden in the next decade.MethodsWe retrieved annual death data on cases and rates of AFF between 1990 and 2019 from the Global Burden of Disease (GBD) Study 2019 and projected the trends for 2020–2029 by developing the Bayesian age-period-cohort model.ResultsThe global number of deaths from AFF increased from 117,038.00 in 1990 to 315,336.80 in 2019. This number is projected to reach 404,593.40 by 2029. The age-standardized mortality rates (ASMRs) of AFF have increased significantly in low- to middle-sociodemographic index (SDI) regions, which will surpass that in high SDI regions and reach above 4.60 per 100,000 by 2029. Globally, women have a higher ASMR than men, which is largely attributed to disproportionately higher mortality in women than men in lower SDI regions. Notably, AFF-related premature mortality continues to worsen worldwide. A pandemic of high systolic blood pressure and high body mass index (BMI) largely contributes to AFF-associated death. In particular, low- to middle-SDI regions and younger populations are increasingly affected by the rapidly growing current and future risk of high BMI.ConclusionThe global death burden of AFF in low-income countries and younger generations have not been sufficiently controlled in the past and will continue growing in the future, which is largely attributed to metabolic risks, particularly for high BMI. There is an urgent need to implement effective measures to control AFF-related mortality

Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach.

Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO2. We developed a 3D reaction-diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf-level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis

Cell transcriptomic atlas of the non-human primate Macaca fascicularis.

Studying tissue composition and function in non-human primates (NHPs) is crucial to understand the nature of our own species. Here we present a large-scale cell transcriptomic atlas that encompasses over 1 million cells from 45 tissues of the adult NHP Macaca fascicularis. This dataset provides a vast annotated resource to study a species phylogenetically close to humans. To demonstrate the utility of the atlas, we have reconstructed the cell-cell interaction networks that drive Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases, and intersected our data with human genetic disease orthologues to establish potential clinical associations. Our M. fascicularis cell atlas constitutes an essential reference for future studies in humans and NHPs.We thank W. Liu and L. Xu from the Huazhen Laboratory Animal Breeding Centre for helping in the collection of monkey tissues, D. Zhu and H. Li from the Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory) for technical help, G. Guo and H. Sun from Zhejiang University for providing HCL and MCA gene expression data matrices, G. Dong and C. Liu from BGI Research, and X. Zhang, P. Li and C. Qi from the Guangzhou Institutes of Biomedicine and Health for experimental advice or providing reagents. This work was supported by the Shenzhen Basic Research Project for Excellent Young Scholars (RCYX20200714114644191), Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), Shenzhen Bay Laboratory (SZBL2019062801012) and Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011). In addition, L.L. was supported by the National Natural Science Foundation of China (31900466), Y. Hou was supported by the Natural Science Foundation of Guangdong Province (2018A030313379) and M.A.E. was supported by a Changbai Mountain Scholar award (419020201252), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), a Chinese Academy of Sciences–Japan Society for the Promotion of Science joint research project (GJHZ2093), the National Natural Science Foundation of China (92068106, U20A2015) and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075). M.L. was supported by the National Key Research and Development Program of China (2021YFC2600200).S

Redefining Cardiac Biomarkers in Predicting Mortality of Inpatients With COVID-19

The prognostic power of circulating cardiac biomarkers, their utility, and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multicentered retrospective study, we enrolled 3219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effects Cox model, after adjusting for age, sex, and comorbidities, the adjusted hazard ratio of 28-day mortality for hs-cTnI (high-sensitivity cardiac troponin I) was 7.12 ([95% CI, 4.60-11.03] P\u3c0.001), (NT-pro)BNP (N-terminal pro-B-type natriuretic peptide or brain natriuretic peptide) was 5.11 ([95% CI, 3.50-7.47] P\u3c0.001), CK (creatine phosphokinase)-MB was 4.86 ([95% CI, 3.33-7.09] P\u3c0.001), MYO (myoglobin) was 4.50 ([95% CI, 3.18-6.36] P\u3c0.001), and CK was 3.56 ([95% CI, 2.53-5.02] P\u3c0.001). The cutoffs of those cardiac biomarkers for effective prognosis of 28-day mortality of COVID-19 were found to be much lower than for regular heart disease at about 19%-50% of the currently recommended thresholds. Patients with elevated cardiac injury markers above the newly established cutoffs were associated with significantly increased risk of COVID-19 death. In conclusion, cardiac biomarker elevations are significantly associated with 28-day death in patients with COVID-19. The prognostic cutoff values of these biomarkers might be much lower than the current reference standards. These findings can assist in better management of COVID-19 patients to improve outcomes. Importantly, the newly established cutoff levels of COVID-19-associated cardiac biomarkers may serve as useful criteria for the future prospective studies and clinical trials