P-Selectin Glycoprotein Ligand-1 Deficiency Protects Against Aortic Aneurysm Formation Induced by DOCA Plus Salt.

PURPOSE: P-selectin glycoprotein ligand-1 (PSGL-1) acts as a crucial regulator for the inflammatory cells infiltration by mediating the adhesion of leukocytes. However, the role of PSGL-1 in aortic aneurysm remains elusive. Here, we investigated the role of PSGL-1 in aortic aneurysm (AA) development. METHODS: We first detected PSGL-1 expression in samples from aortic aneurysm patients and mouse AA models via western blotting, immunofluorescence, and flow cytometry, and then we used global PSGL-1 knockout mice and their wild type controls to establish an aortic aneurysm model induced by deoxycorticosterone acetate (DOCA) plus high salt (HS). The incidence, fatality rates, and the pathological changes of aortic aneurysm were analyzed in each group. The inflammation, adhesion molecules expression, and PSGL-1 mediated leukocyte-endothelial adhesion and their underlying mechanisms were explored further. RESULTS: Increased PSGL-1 levels were observed in human and mouse aortic aneurysm, and on leukocytes of mice treated with DOCA+HS. PSGL-1 deficiency reduced the incidence and severity of aortic aneurysm significantly, as well as decreased elastin fragmentation, collagen accumulation, and smooth muscle cells degeneration. Mechanistically, the protective effect of PSGL-1 inhibition was mediated by the reduced adhesion molecules, and the subsequently reduced leukocyte-endothelial adhesion through the NF-κB pathway, which finally led to reduced inflammatory cells infiltration and decreased inflammatory factors expression. CONCLUSION: PSGL-1 deficiency is protective against inflammatory cells migration and recruitment in the condition of AA through attenuation of leukocyte-endothelial adhesion. Inhibition of PSGL-1 may be a potential therapeutic target for the prevention and treatment of human AA.

Comparison of ureteroscopy (URS) complementary treatment after extracorporeal shock wave lithotripsy failure with primary URS lithotripsy with holmium laser treatment for proximal ureteral stones larger than10mm.

BACKGROUND: To compare ureteroscopy (URS) complementary treatment following extracorporeal shock wave lithotripsy (SWL) failure with primary URS lithotripsy for proximal ureteral stones > 10 mm, and try to find out acceptable number of SWL sessions followed by safe URS. METHODS: This was a retrospective study following approval from Medical Ethics Committee of People's Hospital of Chongqing Banan District. Patients (n = 340) who received URS in our hospital for stones > 10 mm from Jan 2015 to June 2020 were divided into two groups according to their previous SWL history. Group 1 consisted of 160 patients that underwent unsuccessful SWL before URS. Group 2 encompassed 180 patients without SWL before URS. Patient's operative outcomes were compared. A logistic regression and receiver operator characteristics (ROC) were used to identify the acceptable number of SWL sessions prior to URS, regarding the intra-operative complications of URS. RESULTS: The group 1 required more surgery time (41.38 ± 11.39 min vs. 36.43 ± 13.36 min, p = 0.01). At the same time, more intra-operative (68.1% VS 22.8%, p < 0.05) and post-operative (35% VS 18.0%, p = 0.001) complications occurred in group 1. Need more hospital stay in group 1 (2.7 ± 1.2 days vs 1.6 ± 1.1 days, p < 0.05). More patients in group 1 need further URS (16.3% VS 8.9%, p = 0.029). After second URS, the SFR of URS in two groups was insignificant differences (82.5% VS 88.9%, p > 0.05). The median (25-75%) of SWL sessions before URS was 2 (1-3) in group 1. According to the results of logistic regression analysis, patients suffered more SWL failure have an increased risk of complications during URS (OR = 1.995, 95% CI: 1.636-2.434). ROC showed that the optimal number of SWL session followed by URS were 0.5, with a sensitivity of 67.7% and specificity of 71.5%. Intra-operative complication rates of URS treatment were higher in patients who suffered > 1 SWL failure (72.6% vs 57.4%, p = 0.047). CONCLUSION: There was no acceptable number of SWL sessions that could be followed by URS with fewer intra-operative complications. Patients who underwent previous SWL were likely to suffer more intra-operative complications, the average operating time, hospitalization time, and needing further treatment, during URS treatment for proximal ureteral stones larger than 10 mm.

Environmental Factors and Microbial Diversity and Abundance Jointly Regulate Soil Nitrogen and Carbon Biogeochemical Processes in Tibetan Wetlands.

Wetlands have numerous critical ecological functions, some of which are regulated by several nitrogen (N) and carbon (C) biogeochemical processes, such as denitrification, organic matter decomposition, and methane emission. Until now, the underlying pathways of the effects of environmental and biological factors on wetland N and C cycling rates are still not fully understood. Here, we investigated soil potential/net nitrification, potential/unamended denitrification, methane production/oxidation rates in 36 riverine, lacustrine, and palustrine wetland sites on the Tibet Plateau. The results showed that all the measured N and C cycling rates did not differ significantly among the wetland types. Stepwise multiple regression analyses revealed that soil physicochemical properties (e.g., moisture, C and N concentration) explained a large amount of the variance in most of the N and C cycling rates. Microbial abundance and diversity were also important in controlling potential and unamended denitrification rates, respectively. Path analysis further revealed that soil moisture and N and C availability could impact wetland C and N processes both directly and indirectly. For instance, the indirect effect of soil moisture on methane production rates was mainly through the regulating the soil C content and methanogenic community structure. Our findings highlight that many N and C cycling processes in high-altitude and remote Tibetan wetlands are jointly regulated by soil environments and functional microorganisms. Soil properties affecting the N and C cycling rates in wetlands through altering their microbial diversity and abundance represent an important but previously underestimated indirect pathway.

Gastrin stimulates renal dopamine production by increasing the renal tubular uptake of l-DOPA.

Gastrin is a peptide hormone that is involved in the regulation of sodium balance and blood pressure. Dopamine, which is also involved in the regulation of sodium balance and blood pressure, directly or indirectly interacts with other blood pressure-regulating hormones, including gastrin. This study aimed to determine the mechanisms of the interaction between gastrin and dopamine and tested the hypothesis that gastrin produced in the kidney increases renal dopamine production to keep blood pressure within the normal range. We show that in human and mouse renal proximal tubule cells (hRPTCs and mRPTCs, respectively), gastrin stimulates renal dopamine production by increasing the cellular uptake of l-DOPA via the l-type amino acid transporter (LAT) at the plasma membrane. The uptake of l-DOPA in RPTCs from C57Bl/6J mice is lower than in RPTCs from normotensive humans. l-DOPA uptake in renal cortical slices is also lower in salt-sensitive C57Bl/6J than in salt-resistant BALB/c mice. The deficient renal cortical uptake of l-DOPA in C57Bl/6J mice may be due to decreased LAT-1 activity that is related to its decreased expression at the plasma membrane, relative to BALB/c mice. We also show that renal-selective silencing of Gast by the renal subcapsular injection of Gast siRNA in BALB/c mice decreases renal dopamine production and increases blood pressure. These results highlight the importance of renal gastrin in stimulating renal dopamine production, which may give a new perspective in the prevention and treatment of hypertension.

Multi-scale factors affecting composition, diversity, and abundance of sediment denitrifying microorganisms in Yangtze lakes.

Sediment denitrification is the dominant nitrogen removal pathway in many aquatic habitats and can be regulated by local-, landscape-, and regional-scale factors. However, the mechanisms for how these multiple scale factors and their interactions affect the sediment denitrifying communities remain poorly understood. In this study, we investigated the community composition, diversity, and abundance of nitrite reductase genes (nirK and nirS)-encoding denitrifiers in 74 sediment samples from 22 Yangtze lakes using clone library and quantitative PCR techniques. Information of location, climate, catchment land use, water quality, sediment properties, and plant communities at each sampling site was analyzed to elucidate the effects of regional, landscape, and local factors on the characteristics of sediment denitrifying communities. Results of canonical correspondence analysis indicated that local factors were the key determinants of denitrifying community composition, accounting for over 20% of the total variation. Additionally, certain regional and landscape factors, including elevation and catchment built-up land, were also significantly related to the composition of denitrifying communities. Variance partitioning analyses revealed that diversity and abundance in the nirK denitrifier community were largely influenced by local factors, while those in the nirS community were controlled by both local and regional factors. Our findings highlight the importance of using different scale factors to explain adequately the composition and structure of denitrifying communities in aquatic environments.

Dopamine D2 receptors' effects on renal inflammation are mediated by regulation of PP2A function.

Lack or downregulation of the dopamine D2 receptor (D2R) results in increased renal expression of injury markers and proinflammatory factors that is independent of a blood pressure increase. This study aimed to determine the mechanisms involved in the regulation of renal inflammation by D2Rs. Silencing D2Rs in mouse renal proximal tubule cells increased the expression of the proinflammatory TNF-α, monocyte chemoattractant protein-1 (MCP-1), and IL-6. D2R downregulation also increased Akt phosphorylation and activity, and glycogen synthase kinase-3ß (GSK3ß) phosphorylation and cyclin D1 expression, downstream targets of Akt; however. phosphatidylinositol 3-kinase (PI3K) activity was not affected. Conversely, D2R stimulation decreased Akt and GSK3ß phosphorylation and cyclin D1 expression. Increased phospho-Akt, in the absence of increased PI3K activity, may result from decreased Akt dephosphorylation. Inhibition of protein phosphatase 2A (PP2A) with okadaic acid reproduced the effects of D2R downregulation on Akt, GSK3ß, and cyclin D1. The PP2A catalytic subunit and regulatory subunit PPP2R2C coimmunoprecipitated with the D2R. Basal phosphatase activity and the expression of PPP2R2C were decreased by D2R silencing that also blunted the increase in phosphatase activity induced by D2R stimulation. Similarly, silencing PPP2R2C also increased the phosphorylation of Akt and GSK3ß. Moreover, downregulation of PPP2R2C resulted in increased expression of TNF-α, MCP-1, and IL-6, indicating that decreased phosphatase activity may be responsible for the D2R effect on inflammatory factors. Indeed, the increase in NF-κB reporter activity induced by D2R silencing was blunted by increasing PP2A activity with protamine. Our results show that D2R controls renal inflammation, at least in part, by modulation of the Akt pathway through effects on PP2A activity/expression.

HepaCAM inhibits clear cell renal carcinoma 786-0 cell proliferation via blocking PKCε translocation from cytoplasm to plasma membrane.

Hepatocyte cell adhesion molecule (HepaCAM) plays a crucial role in tumor progression and has been recognized as a novel tumor suppressor gene. The high protein expression level of protein kinase Cε (PKCε) has been discovered in many tumor types. In the present study, we determined HepaCAM and PKCε protein levels in human clear cell renal cell carcinoma (ccRCC) tissues and analyzed the correlation between them. We observed an inverse relationship in the expression of HepaCAM and PKCε in ccRCC and adjacent normal tissues. In ccRCC tissue, HepaCAM expression was undetectable while PKCε expression was high; the opposite was found in the adjacent normal tissue. Western blot analysis demonstrated that PKCε cytosolic protein levels increased while plasma membrane protein levels decreased without any change in total protein following infection of the ccRCC cell line 786-0 with adenovirus-GFP-HepaCAM (Ad-GFP-HepaCAM). Moreover, the application of Ad-GFP-HepaCAM combined with a PKCε-specific translocation inhibitor (εV1-2) effectively inhibited 786-0 cell growth. Ad-mediated expression of HepaCAM in 786-0 cells reduced the levels of phosphorylated AKT and cyclin D1 and inhibited cell proliferation. In summary, our studies point to interesting connections between HepaCAM and PKCε in tissues and in vitro. HepaCAM may prevent the translocation of PKCε from cytosolic to particulate fractions, resulting in the inhibition of 786-0 cell proliferation. Therapeutic manipulation of these novel protein targets may provide new ways of treating ccRCC.

MARes-Net: multi-scale attention residual network for jaw cyst image segmentation.

Jaw cyst is a fluid-containing cystic lesion that can occur in any part of the jaw and cause facial swelling, dental lesions, jaw fractures, and other associated issues. Due to the diversity and complexity of jaw images, existing deep-learning methods still have challenges in segmentation. To this end, we propose MARes-Net, an innovative multi-scale attentional residual network architecture. Firstly, the residual connection is used to optimize the encoder-decoder process, which effectively solves the gradient disappearance problem and improves the training efficiency and optimization ability. Secondly, the scale-aware feature extraction module (SFEM) significantly enhances the network's perceptual abilities by extending its receptive field across various scales, spaces, and channel dimensions. Thirdly, the multi-scale compression excitation module (MCEM) compresses and excites the feature map, and combines it with contextual information to obtain better model performance capabilities. Furthermore, the introduction of the attention gate module marks a significant advancement in refining the feature map output. Finally, rigorous experimentation conducted on the original jaw cyst dataset provided by Quzhou People's Hospital to verify the validity of MARes-Net architecture. The experimental data showed that precision, recall, IoU and F1-score of MARes-Net reached 93.84%, 93.70%, 86.17%, and 93.21%, respectively. Compared with existing models, our MARes-Net shows its unparalleled capabilities in accurately delineating and localizing anatomical structures in the jaw cyst image segmentation.

HIMS-Net: Horizontal-vertical interaction and multiple side-outputs network for cyst segmentation in jaw images.

Jaw cysts are mainly caused by abnormal tooth development, chronic oral inflammation, or jaw damage, which may lead to facial swelling, deformity, tooth loss, and other symptoms. Due to the diversity and complexity of cyst images, deep-learning algorithms still face many difficulties and challenges. In response to these problems, we present a horizontal-vertical interaction and multiple side-outputs network for cyst segmentation in jaw images. First, the horizontal-vertical interaction mechanism facilitates complex communication paths in the vertical and horizontal dimensions, and it has the ability to capture a wide range of context dependencies. Second, the feature-fused unit is introduced to adjust the network's receptive field, which enhances the ability of acquiring multi-scale context information. Third, the multiple side-outputs strategy intelligently combines feature maps to generate more accurate and detailed change maps. Finally, experiments were carried out on the self-established jaw cyst dataset and compared with different specialist physicians to evaluate its clinical usability. The research results indicate that the Matthews correlation coefficient (Mcc), Dice, and Jaccard of HIMS-Net were 93.61, 93.66 and 88.10% respectively, which may contribute to rapid and accurate diagnosis in clinical practice.

Basal and postprandial serum levels of gastrin in normotensive and hypertensive adults.

Gastrin is a peptide hormone, which acts not only to regulate gastric acid secretion, but also to exert physiological actions such as the regulation of sodium balance. From a case (n = 95)-control (n = 82) study in Fuyang People's Hospital, Anhui Province, China, we found that the fasting serum gastrin levels are similar in normotensive and hypertensive adults but increased to higher levels in the latter group than in the former group after a mixed meal. We suggest that gastrin is involved in the regulation of blood pressure, possibly via the regulation of sodium and water metabolism and/or renin-angiotensin-aldosterone system. However, the mechanism remains to be determined.

BiDFDC-Net: a dense connection network based on bi-directional feedback for skin image segmentation.

Accurate segmentation of skin lesions in dermoscopic images plays an important role in improving the survival rate of patients. However, due to the blurred boundaries of pigment regions, the diversity of lesion features, and the mutations and metastases of diseased cells, the effectiveness and robustness of skin image segmentation algorithms are still a challenging subject. For this reason, we proposed a bi-directional feedback dense connection network framework (called BiDFDC-Net), which can perform skin lesions accurately. Firstly, under the framework of U-Net, we integrated the edge modules into each layer of the encoder which can solve the problem of gradient vanishing and network information loss caused by network deepening. Then, each layer of our model takes input from the previous layer and passes its feature map to the densely connected network of subsequent layers to achieve information interaction and enhance feature propagation and reuse. Finally, in the decoder stage, a two-branch module was used to feed the dense feedback branch and the ordinary feedback branch back to the same layer of coding, to realize the fusion of multi-scale features and multi-level context information. By testing on the two datasets of ISIC-2018 and PH2, the accuracy on the two datasets was given by 93.51% and 94.58%, respectively.

Improved U-Net based on cross-layer connection for pituitary adenoma MRI image segmentation.

Pituitary adenoma is a common neuroendocrine neoplasm, and most of its MR images are characterized by blurred edges, high noise and similar to surrounding normal tissues. Therefore, it is extremely difficult to accurately locate and outline the lesion of pituitary adenoma. To sovle these limitations, we design a novel deep learning framework for pituitary adenoma MRI image segmentation. Under the framework of U-Net, a newly cross-layer connection is introduced to capture richer multi-scale features and contextual information. At the same time, full-scale skip structure can reasonably utilize the above information obtained by different layers. In addition, an improved inception-dense block is designed to replace the classical convolution layer, which can enlarge the effectiveness of the receiving field and increase the depth of our network. Finally, a novel loss function based on binary cross-entropy and Jaccard losses is utilized to eliminate the problem of small samples and unbalanced data. The sample data were collected from 30 patients in Quzhou People's Hospital, with a total of 500 lesion images. Experimental results show that although the amount of patient sample is small, the proposed method has better performance in pituitary adenoma image compared with existing algorithms, and its Dice, Intersection over Union (IoU), Matthews correlation coefficient (Mcc) and precision reach 88.87, 80.67, 88.91 and 97.63%, respectively.

Modified UNet++ with atrous spatial pyramid pooling for blood cell image segmentation.

Blood cell image segmentation is an important part of the field of computer-aided diagnosis. However, due to the low contrast, large differences in cell morphology and the scarcity of labeled images, the segmentation performance of cells cannot meet the requirements of an actual diagnosis. To address the above limitations, we present a deep learning-based approach to study cell segmentation on pathological images. Specifically, the algorithm selects UNet++ as the backbone network to extract multi-scale features. Then, the skip connection is redesigned to improve the degradation problem and reduce the computational complexity. In addition, the atrous spatial pyramid pooling (ASSP) is introduced to obtain cell image information features from each layer through different receptive domains. Finally, the multi-sided output fusion (MSOF) strategy is utilized to fuse the features of different semantic levels, so as to improve the accuracy of target segmentation. Experimental results on blood cell images for segmentation and classification (BCISC) dataset show that the proposed method has significant improvement in Matthew's correlation coefficient (Mcc), Dice and Jaccard values, which are better than the classical semantic segmentation network.

Group theoretic particle swarm optimization for gray-level medical image enhancement.

As a principal category in the promising field of medical image processing, medical image enhancement has a powerful influence on the intermedia features and final results of the computer aided diagnosis (CAD) system by increasing the capacity to transfer the image information in the optimal form. The enhanced region of interest (ROI) would contribute to the early diagnosis and the survival rate of patients. Meanwhile, the enhancement schema can be treated as the optimization approach of image grayscale values, and metaheuristics are adopted popularly as the mainstream technologies for medical image enhancement. In this study, we propose an innovative metaheuristic algorithm named group theoretic particle swarm optimization (GT-PSO) to tackle the optimization problem of image enhancement. Based on the mathematical foundation of symmetric group theory, GT-PSO comprises particle encoding, solution landscape, neighborhood movement and swarm topology. The corresponding search paradigm takes place simultaneously under the guidance of hierarchical operations and random components, and it could optimize the hybrid fitness function of multiple measurements of medical images and improve the contrast of intensity distribution. The numerical results generated from the comparative experiments show that the proposed GT-PSO has outperformed most other methods on the real-world dataset. The implication also indicates that it would balance both global and local intensity transformations during the enhancement process.

Temperature drives elevational diversity patterns of different types of organisms in Qinghai-Tibetan Plateau wetlands.

The spatial pattern and driving mechanism of biodiversity along elevational gradients are key topics in ecology. However, it is still unclear whether the multidimensional diversity of different types of organisms shows a similar response to elevation changes. Here, we measured the species and phylogenetic diversity of plants, bacteria, fungi, and microbial functional groups (nitrifiers, denitrifiers, methanogens, and methanotrophs) in 36 wetland sites on the Qinghai-Tibetan Plateau. The results showed that both species and phylogenetic diversity of plants, bacteria, and fungi exhibited a significant elevational gradient, in direct contrast to no significant diversity changes observed for denitrifiers, methanogens, and methanotrophs along the same altitude gradient. Our findings suggest that elevation and temperature were more likely to associate with the diversity of plants, bacteria, and fungi than the diversity of microbial functional groups, with important implications for assessing the effect of ongoing climate warming on biodiversity in Qinghai-Tibetan alpine wetlands.

PDC-Net: parallel dilated convolutional network with channel attention mechanism for pituitary adenoma segmentation.

Accurate segmentation of the medical image is the basis and premise of intelligent diagnosis and treatment, which has a wide range of clinical application value. However, the robustness and effectiveness of medical image segmentation algorithms remains a challenging subject due to the unbalanced categories, blurred boundaries, highly variable anatomical structures and lack of training samples. For this reason, we present a parallel dilated convolutional network (PDC-Net) to address the pituitary adenoma segmentation in magnetic resonance imaging images. Firstly, the standard convolution block in U-Net is replaced by a basic convolution operation and a parallel dilated convolutional module (PDCM), to extract the multi-level feature information of different dilations. Furthermore, the channel attention mechanism (CAM) is integrated to enhance the ability of the network to distinguish between lesions and non-lesions in pituitary adenoma. Then, we introduce residual connections at each layer of the encoder-decoder, which can solve the problem of gradient disappearance and network performance degradation caused by network deepening. Finally, we employ the dice loss to deal with the class imbalance problem in samples. By testing on the self-established patient dataset from Quzhou People's Hospital, the experiment achieves 90.92% of Sensitivity, 99.68% of Specificity, 88.45% of Dice value and 79.43% of Intersection over Union (IoU).

A non-human primate derived anti-P-selectin glycoprotein ligand-1 antibody curtails acute pancreatitis by alleviating the inflammatory responses.

Acute pancreatitis (AP) is a devastating disease characterized by an inflammatory disorder of the pancreas. P-selectin glycoprotein ligand-1 (PSGL-1) plays a crucial role in the initial steps of the adhesive at process to inflammatory sites, blockade of PSGL-1 might confer potent anti-inflammatory effects. In this study, we generated two non-human primate derived monoclonal antibodies capable of efficiently targeting human PSGL-1, RH001-6 and RH001-22, which were screened from immunized rhesus macaques. We found that RH001-6, can effectively block the binding of P-selectin to PSGL-1, and abolish the adhesion of leukocytes to endothelial cells in vitro. In vivo, we verified that RH001-6 relieved inflammatory responses and pancreatic injury in both caerulein and l-arginine induced AP models. We also evaluated the safety profile after RH001-6 treatment in mice, and verified that RH001-6 did not cause any significant pathological damages in vivo. Taken together, we developed a novel non-human primate derived PSGL-1 blocking antibody with high-specificity, named RH001-6, which can interrupt the binding of PSGL-1 and P-selectin and attenuate inflammatory responses during AP. Therefore, RH001-6 is highly potential to be further developed into therapeutics against acute inflammatory diseases, such as AP.

Group theoretic particle swarm optimization for multi-level threshold lung cancer image segmentation.

Background: Image segmentation is an important step during the processing of medical images. For example, for the computer aid diagnostic systems for lung cancer image analysis, the segmented regions of tumors would help doctors in early diagnosis to determine timely and appropriate treatment possibilities and thereby improve the survival rate of the patients. However, general clinical routines of manual segmentation for large number of medical images are very difficult and time consuming, which is the challenge we aim to tackle using our proposed method. Methods: A novel image segmentation method with evolutionary learning technique named Group Theoretic Particle Swarm Optimization is proposed. It can tackle multi-level thresholding optimization problem during the segmentation process and rebuild the search paradigm according to the solid mathematical foundation of symmetric group from four designable aspects, which are particle encoding, solution landscape, neighborhood movement and swarm topology, respectively. The Kapur's entropy of multi-level thresholds is assessed as the objective function. Results: In contrast to those conventional metaheuristics methods for lung cancer image segmentation, this newly presented method generates the best performance result among them. Experimental results show that its Kapur's entropy has the value of 9.07, which is 16% higher than the worst case. Computational time is acceptable at the cost of 173.730 seconds, average level of evaluation metrics [Kappa, Precision, Recall, F1-measure, intersection over union (IoU) and receiver operating characteristic (ROC)] is over 90%, and search process of multi-level threshold combination would finally converge in the later phase of iterations after 700. The ablation study indicates that all components are significant to the contributions of our proposed method. Conclusions: Group Theoretic Particle Swarm Optimization for multi-level threshold segmentation is an efficient way to split a medical image into distinct regions and extract tumor tissues regions from the background. It maintains the balanced relationship between diversification and intensification during the search process and helps clinicians to make the diagnosis more accurately. Our proposed method processes potential medical value and clinical meanings.

Intestinal Cckbr-specific knockout mouse as a novel model of salt-sensitive hypertension via sodium over-absorption.

OBJECTIVES: To investigate the value of CCKBRfl/fl villin-Cre mice as a mouse model of salt-sensitive hypertension (SSH). METHODS: In the first part, 2-month-old CCKBRfl/fl villin-Cre mice (CKO) and control CCKBRfl/fl mice (WT) were fed with normal diet (0.4% NaCl) or high salt diet (4% NaCl), separately for 6 weeks. In the rescue study, one week of hydrochlorothiazide or saline injection were treated with the CKO mice fed high salt diet. The blood pressure, biochemical indexes, and the expression of small intestinal sodium transporters (NHE3, NKCC1, eNaC) was detected. The organ injury markers (MMP2/MMP9) and the histopathological changes of kidneys were observed, whereas the changes of duodenal sodium absorption were detected by small intestinal perfusion in vivo. RESULTS: The CCKBRfl/fl villin-Cre mice with high salt intake exhibited high blood pressure, increased duodenal sodium absorption and urinary sodium excretion, and with renal injury. The protein expression of NHE3, NKCC1 and eNaC were also significant increase in the intestine of CKO-HS mice. Treatment with hydrochlorothiazide remarkably attenuated the elevated blood pressure by high salt absorption in the CCKBRfl/fl villin-Cre mice, but no significant histopathological changes were observed. CONCLUSIONS: These results support a crucial role of intestinal Cckbr deficiency on SSH development and the diuretic antihypertension effect in CCKBRfl/fl villin-Cre mice. The CCKBRfl/fl villin-Cre mice with the high salt intake may serve as a stable model of salt-sensitive hypertensive induced by sodium overloading.

Furosemide improves the stone clearance rate of extracorporeal shockwave lithotripsy for kidney stones but not ureteral stones: a systematic review and meta-analysis.

Introduction: We conducted a meta-analysis (MA) to investigate the effects of furosemide on the prognosis of extracorporeal shockwave lithotripsy (SWL) therapy to remove renal (RS) and ureteric stones (US). Methods: We screened scientific databases including PubMed, Clinicalkey, Google Scholar, Medline, Embase, and Cochrane, from the date of establishment until March 2022, to search for randomized controlled trials evaluating SWL, in combination with furosemide (experimental group) or with SWL alone (control group), in treating RS or US. Our search terms included furosemide, extracorporeal SWL, and urolithiasis. For this MA, we employed the Cochrane Collaboration's RevMan version 5.3.0. Results: Six trials, involving 1344 participants, with RS (n = 1097) and/or US (n = 247), met our predefined criteria. This included 137 proximal ureteral stones (PUSs), 35 mid-ureteral stones (MUS), and 75 distal ureteral stones (DUS). In case of RS, the experimental group exhibited significantly enhanced clearance, relative to controls (risk ratio [RR] = 1.16, 95% confidence interval [CI] = 1.07-1.25, p = 0.0002), yet there was no obvious difference in the PUS, MUS, and DUS (RR = 1.14, 95% CI = 0.97-1.33, p = 0.10; odds ratio [OR] = 1.26, 95% CI = 1.40-3.95, p = 0.69; RR = 1.21, 95% CI = 0.99-1.49, p = 0.06). There was also no marked difference between fragmentations in either group. Only reports of SWL treatment of RS provided adequate data on shocks, sessions, and complications for our analysis. Unfortunately, there was no significant alteration between the two groups. Conclusion: According to our analysis, furosemide strongly accelerates the clearance rate of SWL-treated RS. However, it does not enhance the fragmentation rate. Given this evidence, we propose that furosemide does not significantly improve the efficacy of SWL therapy in removing US. Registration: Our work is registered with PROSPERO (CRD42020204780).