Nitric Oxide Synthase in Male Urological and Andrologic Functions

Nitric oxide (NO), a crucial signaling molecule, is synthesized by the nitric oxide synthase (NOS) enzyme. The significant effects of NOS are under exploration, and the roles of potential therapy targets for diseases of NOS are widely accepted. In this chapter, we summarized the important roles of NOS mainly on pathogenesis of prostate diseases, male infertility, erectile dysfunction and, addition, the potential therapeutic efficacies of NOS for those diseases

Biomaterials research of China from 2013 to 2017 based on bibliometrics and visualization analysis

Objectives This study aims to evaluate the changes of development trends and research hotspots of biomaterials research from 2013 to 2017, which can identify the general information of papers and explore the changes of research content, thus providing perspectives for the development of biomaterials in China and other countries. Methods Data of the paper were retrieved from the Web of Science Core Collection, and then analyzed by the bibliometric and CiteSpace visualization analysis. Results It was found that a total of 3,839 related papers had been published from the year 2013 to 2017. The analysis of the articles showed that the annual quantity and quality of the articles in the biomaterials research have been increasing since 2013, and the Wang L / Chinese Academy of Sciences were the most productive author/institution. Meanwhile, the keywords “in vitro”, “scaffold”, “nanoparticle” , “mechanical property”, and “biocompatibility” have the relatively higher frequency, and the keywords “apatite”, “deposition”, and “surface modification” have the strongest burst citation. Conclusions After statistics and analysis, we found that biomaterials is a promising research field. The study may be helpful in understanding research trends in this field

Single-Cell Spatial Transcriptomics Unveils Platelet-Fueled Cycling Macrophages for Kidney Fibrosis.

With the increasing incidence of kidney diseases, there is an urgent need to develop therapeutic strategies to combat post-injury fibrosis. Immune cells, including platelets, play a pivotal role in this repair process, primarily through their released cytokines. However, the specific role of platelets in kidney injury and subsequent repair remains underexplored. Here, the detrimental role of platelets in renal recovery following ischemia/reperfusion injury and its contribution to acute kidney injury  to chronic kidney disease transition is aimed to investigated. In this study, it is shown that depleting platelets accelerates injury resolution and significantly reduces fibrosis. Employing advanced single-cell and spatial transcriptomic techniques, macrophages as the primary mediators modulated by platelet signals is identified. A novel subset of macrophages, termed cycling M2, which exhibit an M2 phenotype combined with enhanced proliferative activity is uncovered. This subset emerges in the injured kidney during the resolution phase and is modulated by platelet-derived thrombospondin 1 (THBS1) signaling, acquiring profibrotic characteristics. Conversely, targeted inhibition of THBS1 markedly downregulates the cycling M2 macrophage, thereby mitigating fibrotic progression. Overall, this findings highlight the adverse role of platelet THBS1-boosted cycling M2 macrophages in renal injury repair and suggest platelet THBS1 as a promising therapeutic target for alleviating inflammation and kidney fibrosis

Targeting DNA-PKcs and ATM with miR-101 Sensitizes Tumors to Radiation

Radiotherapy kills tumor-cells by inducing DNA double strand breaks (DSBs). However, the efficient repair of tumors frequently prevents successful treatment. Therefore, identifying new practical sensitizers is an essential step towards successful radiotherapy. In this study, we tested the new hypothesis: identifying the miRNAs to target DNA DSB repair genes could be a new way for sensitizing tumors to ionizing radiation.HERE, WE CHOSE TWO GENES: DNA-PKcs (an essential factor for non-homologous end-joining repair) and ATM (an important checkpoint regulator for promoting homologous recombination repair) as the targets to search their regulating miRNAs. By combining the database search and the bench work, we picked out miR-101. We identified that miR-101 could efficiently target DNA-PKcs and ATM via binding to the 3'- UTR of DNA-PKcs or ATM mRNA. Up-regulating miR-101 efficiently reduced the protein levels of DNA-PKcs and ATM in these tumor cells and most importantly, sensitized the tumor cells to radiation in vitro and in vivo.These data demonstrate for the first time that miRNAs could be used to target DNA repair genes and thus sensitize tumors to radiation. These results provide a new way for improving tumor radiotherapy

Alteration and clinical potential in gut microbiota in patients with cerebral small vessel disease

BackgroundCerebral small vessel disease (CSVD) is a cluster of microvascular disorders with unclear pathological mechanisms. The microbiota-gut-brain axis is an essential regulatory mechanism between gut microbes and their host. Therefore, the compositional and functional gut microbiota alterations lead to cerebrovascular disease pathogenesis. The current study aims to determine the alteration and clinical value of the gut microbiota in CSVD patients.MethodsSixty-four CSVD patients and 18 matched healthy controls (HCs) were included in our study. All the participants underwent neuropsychological tests, and the multi-modal magnetic resonance imaging depicted the changes in brain structure and function. Plasma samples were collected, and the fecal samples were analyzed with 16S rRNA gene sequencing.ResultsBased on the alpha diversity analysis, the CSVD group had significantly decreased Shannon and enhanced Simpson compared to the HC group. At the genus level, there was a significant increase in the relative abundances of Parasutterella, Anaeroglobus, Megasphaera, Akkermansia, Collinsella, and Veillonella in the CSVD group. Moreover, these genera with significant differences in CSVD patients revealed significant correlations with cognitive assessments, plasma levels of the blood-brain barrier-/inflammation-related indexes, and structural/functional magnetic resonance imaging changes. Functional prediction demonstrated that lipoic acid metabolism was significantly higher in CSVD patients than HCs. Additionally, a composite biomarker depending on six gut microbiota at the genus level displayed an area under the curve of 0.834 to distinguish CSVD patients from HCs using the least absolute shrinkage and selection operator (LASSO) algorithm.ConclusionThe evident changes in gut microbiota composition in CSVD patients were correlated with clinical features and pathological changes of CSVD. Combining these gut microbiota using the LASSO algorithm helped identify CSVD accurately

Mining document, concept, and term associations for effective biomedical retrieval - Introducing MeSH-enhanced retrieval models

Manually assigned subject terms, such as Medical Subject Headings (MeSH) in the health domain, describe the concepts or topics of a document. Existing information retrieval models do not take full advantage of such information. In this paper, we propose two MeSH-enhanced (ME) retrieval models that integrate the concept layer (i.e. MeSH) into the language modeling framework to improve retrieval performance. The new models quantify associations between documents and their assigned concepts to construct conceptual representations for the documents, and mine associations between concepts and terms to construct generative concept models. The two ME models reconstruct two essential estimation processes of the relevance model (Lavrenko and Croft 2001) by incorporating the document-concept and the concept-term associations. More specifically, in Model 1, language models of the pseudo-feedback documents are enriched by their assigned concepts. In Model 2, concepts that are related to users’ queries are first identified, and then used to reweight the pseudo-feedback documents according to the document-concept associations. Experiments carried out on two standard test collections show that the ME models outperformed the query likelihood model, the relevance model (RM3), and an earlier ME model. A detailed case analysis provides insight into how and why the new models improve/worsen retrieval performance. Implications and limitations of the study are discussed. This study provides new ways to formally incorporate semantic annotations, such as subject terms, into retrieval models. The findings of this study suggest that integrating the concept layer into retrieval models can further improve the performance over the current state-of-the-art models.Ye

Biophysical Effects of Land Cover Changes on Land Surface Temperature on the Sichuan Basin and Surrounding Regions

The biophysical effect of land cover changes (LCC) on local temperature is currently a hot topic. This work selects one of the nine agricultural divisions in China, the Sichuan Basin and surrounding regions, as the study area. By combining long-term series satellite remote sensing products with the space-and-time method, the spatial and temporal variations of the actual biophysical effects of LCC on land surface temperature (LST) are obtained. The results show that: (1) From 2001 to 2020, LCCs from Savannas to Cropland, from Cropland to Savannas, and from Savannas to Mixed Forest occurred frequently within the study area, and their area proportions of the total conversions are 21.7%, 18.5%, and 17.6%, respectively. (2) The biophysical feedback of LCC in the study area led to a LST increase of 0.01 ± 0.004 K at annual scale, which presents a seasonal pattern of “strong warming in summer and autumn yet weak cooling in winter”. It can exacerbate 14.3% or alleviate 8.3% of the background climate warming effect, illustrating the importance of biophysical effects on local climate change. The interaction between savannas and cropland or mixed forest and urbanizations formed the main driver for the above patterns. (3) Both the occurrence area of LCC and the warming effects at annual or seasonal scale show a trend of “first rising and then declining”, whereas the cooling effect in winter exhibits continuous enhancement over time. The monodirectional or mutual conversion between cropland and savannas is the dominant conversion responsible for these temporal patterns. The findings can provide realistic scientific guidance for informing rational policies on land management and targeted strategies for climate change response in the study area

Preoperative prediction for early recurrence of hepatocellular carcinoma using machine learning-based radiomics

ObjectiveTo develop a contrast-enhanced computed tomography (CECT) based radiomics model using machine learning method and assess its ability of preoperative prediction for the early recurrence of hepatocellular carcinoma (HCC).MethodsA total of 297 patients confirmed with HCC were assigned to the training dataset and test dataset based on the 8:2 ratio, and the follow-up period of the patients was from May 2012 to July 2017. The lesion sites were manually segmented using ITK-SNAP, and the pyradiomics platform was applied to extract radiomic features. We established the machine learning model to predict the early recurrence of HCC. The accuracy, AUC, standard deviation, specificity, and sensitivity were applied to evaluate the model performance.Results1,688 features were extracted from the arterial phase and venous phase images, respectively. When arterial phase and venous phase images were employed correlated with clinical factors to train a prediction model, it achieved the best performance (AUC with 95% CI 0.8300(0.7560-0.9040), sensitivity 89.45%, specificity 79.07%, accuracy 82.67%, p value 0.0064).ConclusionThe CECT-based radiomics may be helpful to non-invasively reveal the potential connection between CECT images and early recurrence of HCC. The combination of radiomics and clinical factors could boost model performance