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ObjectiveThe metabolism- and transporter-based drug-drug interactions (DDIs) between mycophenolate mofetil (MMF) and co-administered medications may be key factors for the high individual variability in MMF exposure. This study systematically assessed the influence of co-medications on the mycophenolic acid (MPA) pharmacokinetic (PK) process in vitro, particularly to provide mechanistic evidence of the metabolic interaction among steroids, cyclosporine (CsA), and MMF.MethodsBased on a previous study, we hypothesized that there are three main DDI pathways affecting MMF PK in vivo. A human hepatocyte induction study, transporter substrate/inhibition study using human embryonic kidney 293 cells, and multidrug resistance-associated protein 2 (MRP2) substrate/inhibition study using vesicle membrane were conducted to assess the mechanistic evidence of the metabolic interaction in triple therapies. The potential DDI risks associated with seven medications commonly co-administered with MMF in clinical practice were further evaluated.ResultsThe in vitro results suggested that prednisolone, the active metabolite of prednisone, induces the enzymatic activity of uridine 5′-diphospho-glucuronosyltransferase (UGT), particularly the UGT1A9 and UGT2B7 isoforms, resulting in increased metabolism of MPA to MPA glucuronide (MPAG). This induction potential was not observed in CsA-treated human hepatocytes. CsA inhibits organic anion-transporting polypeptide (OATP) 1B1- and OATP1B3-mediated MPAG. Prednisolone and CsA showed no inhibitory effect on MRP2-mediated MPAG efflux. Salvia miltiorrhiza significantly inhibited organic anion-transporting polypeptide and OAT 3 activities, suggesting that it affects the hepatic uptake and renal excretion of MPAG, causing increased MPAG exposure in vivo.ConclusionThese identified factors may contribute to the high inter-individual variability in MMF exposure and facilitate further development of mechanistic MMF PK models and individualized therapies.

Diffuse large B-cell lymphoma (DLBCL) is the most common pathological type of non-Hodgkin lymphoma, and is closely associated with hepatitis B virus (HBV) infection status and hepatitis B X (HBx) gene integration. This project investigated the cellular biological effects and molecular mechanisms responsible for lymphomagenesis and the progression of HBx integration in DLBCL. The data showed that clinical DLBCL cells demonstrated HBx integration, and the sequencing analysis of integrated sites validated HBx integration in the constructed HBx-transfected cells. Compared with control cells, HBx-transfected cells had a significantly reduced proportion of mitochondrial membrane potential, signals of chromosomal DNA breaks, and proportion of apoptotic cells. Further studies found that this decreased apoptosis level was associated with a significant reduction of cleaved Caspase-3 and downstream poly ADP-ribose polymerase (PARP) proteins, revealing the molecular mechanisms of HBx-associated apoptosis in DLBCL. Animal experiments also demonstrated that the protein expression of cleaved Caspase-3 and PARP was prominently reduced in HBx-transfected cells from subcutaneous tumors in mice. Furthermore, the HBx-integrated cells in clinical tissues had significantly lower cleaved PARP levels than the HBx-negative samples. Therefore, HBx integration inhibits cell apoptosis through the Caspase-3-PARP pathway in DLBCL indicating a potential biomarker and therapeutic target in HBV related DLBCL.

Esports is a rapidly growing industry and related information garners the attention of audiences both inside and outside the arena. The electronic competition system has become more structured over time and there are now standard off-seasons, which coincide tightly with an intensive period of player transfers. However, at the same time, the off-season has few events to cover and transfer information is highly confidential, so any insights regarding possible transfers are of deep interest to audiences. As a result, unofficial esports insiders often leak transfer information. To explore this phenomenon in greater depth, the methodology used in this study was based on the content analysis of information relating to 10-years in the life of the esport Counter-Strike: Global Offensive (CS:GO). Data was collected from the Perfect World Esports APP and the HLTV websites to analyze the informants and the development of transfer information and its influence. It was found that, during the off-season, insider transfer revelations became the primary focus of content in the esports media sector. As the number of viewers participating in discussions about potential transfers has grown, esports tipsters have discovered a new career path within the industry. A comprehensive assessment of the audience and professional practitioners reveals the essential qualities that esports insiders should possess to excel in this field and for their careers to develop.

Abstract With rapid economic development and urbanization in China, rural wastewater treatment has become an important issue. This study investigated 63 rural sewage treatment stations in northern, central and southern Shaanxi, China for a 1-year period, 2021 to 2022. The main purpose of the research was to investigate the quality and discharge characteristics of rural sewage, along with current problems in rural wastewater treatment, in order to provide evidence for the optimal construction and operation of rural sewage treatment stations. We found that the biodegradability of rural wastewater is adequate, and BOD5/COD ratio in sewage was 0.4, which is suitable for biological treatment. It has obvious intermittent flow cut-off characteristics, and the range of cut-off duration of sewage was 6–16 h/d, which leads to poor pollutant removal efficiency (COD: 50.0 ± 29.2%, NH4 +-N: 46.0 ± 26.1%, TN: 38.5 ± 24.9% and TP: 38.3 ± 23.8%) in sewage treatment stations. In response to the above characteristics, the rural sewage biologically enhanced internal circulation treatment (BEICT) system was constructed. After 97 days of operation, the system has a stable removal effect on TN and TP with an average removal rate of 77.42% and 89.69%, respectively, under the condition of influent interruption for 12 h per day. The activated sludge of system maintained good activity and stable sedimentation performance during the whole experiment, with MLVSS/MLSS and SVI of 0.72 and 128 mL/g, respectively. This study can provide the basis and technical support for the accurate design of rural sewage treatment facilities, and has important significance for guiding the treatment of rural domestic sewage in China.

Purpose: This study aimed to develop a retrained large language model (LLM) tailored to the needs of HN cancer patients treated with radiotherapy, with emphasis on symptom management and survivorship care. Methods: A comprehensive external database was curated for training ChatGPT-4, integrating expert-identified consensus guidelines on supportive care for HN patients and correspondences from physicians and nurses within our institution’s electronic medical records for 90 HN patients. The performance of our model was evaluated using 20 patient post-treatment inquiries that were then assessed by three Board certified radiation oncologists (RadOncs). The rating of the model was assessed on a scale of 1 (strongly disagree) to 5 (strongly agree) based on accuracy, clarity of response, completeness s, and relevance. Results: The average scores for the 20 tested questions were 4.25 for accuracy, 4.35 for clarity, 4.22 for completeness, and 4.32 for relevance, on a 5-point scale. Overall, 91.67% (220 out of 240) of assessments received scores of 3 or higher, and 83.33% (200 out of 240) received scores of 4 or higher. Conclusion: The custom-trained model demonstrates high accuracy in providing support to HN patients offering evidence-based information and guidance on their symptom management and survivorship care.

Iatrogenic copper deficiency is rare in patients with Wilson’s disease. We present a case of iatrogenic copper deficiency myeloneuropathy secondary to zinc treatment for Wilson’s disease and compare the patient’s clinical features with existing cases. Our study highlights the importance of recognizing subtle clinical manifestations and counselling patients receiving copper-reducing treatment to watch for symptoms of myeloneuropathy. Early biochemical testing, including serum copper, caeruloplasmin and zinc levels, as well as magnetic resonance imaging of the spine and electrophysiological studies, may be helpful in diagnosing copper deficiency-related myeloneuropathy due to zinc treatment. Early detection and treatment of copper deficiency may lead to good recovery of neurological symptoms.

Triterpenoid saponins from Stauntonia chinensis have been proven to be a potential candidate for inflammatory pain relief. Our pharmacological studies confirmed that the analgesic role of triterpenoid saponins from S. chinensis occurred via a particular increase in the inhibitory synaptic response in the cortex at resting state and the modulation of the capsaicin receptor. However, its analgesic active components and whether its analgesic mechanism are limited to this are not clear. In order to further determine its active components and analgesic mechanism, we used the patch clamp technique to screen the chemical components that can increase inhibitory synaptic response and antagonize transient receptor potential vanilloid 1, and then used in vivo animal experiments to evaluate the analgesic effect of the selected chemical components. Finally, we used the patch clamp technique and molecular biology technology to study the analgesic mechanism of the selected chemical components. The results showed that triterpenoid saponins from S. chinensis could enhance the inhibitory synaptic effect and antagonize the transient receptor potential vanilloid 1 through different chemical components, and produce central and peripheral analgesic effects. The above results fully reflect that “traditional Chinese medicine has multi-component, multi-target, and multi-channel synergistic regulation”.

Abstract Background Little is known about the association between the preoperative low-density lipoprotein cholesterol (LDL-C) level and prognosis in patients with renal cell carcinoma (RCC) after nephrectomy, and its prognostic value needs to be elucidated. Methods The clinical and follow-up data of 737 RCC patients who underwent nephrectomy were retrospectively analyzed. The optimal cut-off LDL-C level was determined using X-tile, and then patients were divided into low and high LDL-C groups. The association between LDL-C levels and survival of RCC patients was assessed using the Kaplan-Meier method and Cox regression analysis. Results The optimal cut-off LDL-C level was 1.93 mmol/L, and patients were divided into the low (≤ 1.93 mmol/L) and high LDL-C (> 1.93 mmol/L) groups. The Kaplan-Meier analysis showed that patients in the low LDL-C group had significantly shorter overall survival (OS), cancer-specific survival (CSS) and recurrence-free survival (RFS) than those in the high LDL-C group (P = 0.001, P = 0.001, and P = 0.003, respectively). The COX univariate analysis showed that the preoperative LDL-C level was closely associated with OS, CSS, and RFS in RCC patients (P = 0.002, P = 0.003, and P = 0.005, respectively). The multivariate analysis showed that the preoperative LDL-C level was an independent factor for predicting survival (OS, CSS and RFS) in RCC patients after nephrectomy. The low preoperative LDL-C levels predicted worse OS (hazard ratio [HR]: 2.337; 95% confidence interval [CI]: 1.192–4.581; P = 0.013), CSS (HR: 3.347; 95% CI: 1.515–7.392; P = 0.003), and RFS (HR: 2.207; 95% CI: 1.178–4.132; P = 0.013). Conclusions The preoperative LDL-C level is an independent factor for the prognosis of RCC patients after nephrectomy, and low preoperative LDL-C levels predict worse survival (OS, CSS, and RFS).

Abstract Background Osteoporotic fracture (OPF) is one of the most common skeletal diseases in an aging society. The Chinese medicine formula Buzhong Yiqi Decoction (BZYQD) is commonly used for treating OPF. However, the essential bioactive compounds and the underlying molecular mechanisms that promote fracture repair remain unclear. Methods We used network pharmacology and experimental animal validation to address this issue. First, 147 bioactive BZYQD compounds and 32 target genes for treating OPF were screened and assessed. A BZYQD-bioactive compound-target gene-disease network was constructed using the Cytoscape software. Functional enrichment showed that the candidate target genes were enriched in oxidative stress- and inflammation-related biological processes and multiple pathways, including nuclear factor kappa B (NF-κB), and mitogen-activated protein kinase (MAPK) signaling pathways. Furthermore, an OPF rat model was established and treated with BZYQD. Results The results revealed that BZYQD ameliorated OPF characteristics, including femoral microarchitecture, biomechanical properties, and histopathological changes, in a dose-dependent manner. Results of enzyme-linked immunosorbent assay showed that BZYQD reduced the serum’s pro-inflammatory cytokines [Tumor necrosis factor-alpha (TNF-α), Interleukin (IL)-1β, and IL-6] and improved oxidative stress-related factors [glutathione (GSH) and superoxide dismutase (SOD)]. BZYQD significantly decreased the protein expression of NF-κB in OPF rat femurs, suppressed NF-κB activation, and activated the nuclear factor-erythroid factor 2-related factor (Nrf2)/heme oxygenase 1 (HO-1) and p38 MAPK as well ERK pathways. Conclusions Our results suggest that BZYQD could improve inflammation and oxidative stress during fracture repair by suppressing NF-κB and activating Nrf2/MAPK signaling pathways.

Accurate urban PM2.5 forecasting serves a crucial function in air pollution warning and human health monitoring. Recently, deep learning techniques have been widely employed for urban PM2.5 forecasting. Unfortunately, two problems exist: (1) Most techniques are focused on training and prediction on a central cloud. As the number of monitoring sites grows and the data explodes, handling a large amount of data on the central cloud can cause tremendous computational pressures and increase the risk of data leakages. (2) Existing methods lack an adaptive layer to capture the varying impacts of different external factors (e.g., weather conditions, temperature, and wind speed). In this paper, a federated deep learning network (FedDeep) is developed for edge-assisted multi-urban PM2.5 forecasting. First, we assign each urban region to an edge cloud server (ECS). An external spatio-temporal network (ESTNet) is then deployed on each ECS. Data from different urban regions are uploaded to the corresponding ECS for training, which avoids processing all the data on the central cloud and effectively alleviates computational pressure and data leakage issues. Second, in ESTNet, we develop a gating fusion layer to adaptively fuse external factors to improve prediction accuracy. Finally, we adopted PM2.5 data collected from air quality monitoring sites in 13 prefecture-level cities, Jiangsu Province for validation. The experimental results proved that FedDeep outperformed the advanced baselines in terms of prediction accuracy and model efficiency.

Understanding the factors associated with cholera outbreaks is an integral part of designing better approaches to mitigate their impact. Using a rich set of georeferenced case data from the cholera epidemic that occurred in Harare from September 2018 to January 2019, we apply spatio-temporal modelling to better understand how the outbreak unfolded and the factors associated with higher risk of being a reported case. Using Call Detail Records (CDR) to estimate weekly population movement of the community throughout the city, results suggest that broader human movement (not limited to infected agents) helps to explain some of the spatio-temporal patterns of cases observed. In addition, results highlight a number of socio-demographic risk factors and suggest that there is a relationship between cholera risk and water infrastructure. The analysis shows that populations living close to the sewer network, with high access to piped water are associated with at higher risk. One possible explanation for this observation is that sewer bursts led to the contamination of the piped water network. This could have turned access to piped water, usually assumed to be associated with reduced cholera risk, into a risk factor itself. Such events highlight the importance of maintenance in the provision of SDG improved water and sanitation infrastructure.

Highly efficient cooling methods are becoming more urgent with the continuing trend for higher power and further miniaturization of components of aerospace filed. And microchannel heat sinks have been getting more attention in recent researches. Moreover, it can be fully enhanced for the heat transfer capacity of heat sinks by the bionic microchannel structure such as spider web topological structure. In this study, bionic spider web microchannel structure design method was proposed and the structural parameters and flow parameters of bionic spider web microchannel was investigated by using numerical simulation methods. It was found that the effect of the channel center angle of is not obvious for the heat exchange capacity of the spider web microchannels, while the effect for the ratio of the channel width to channel spacing is significant with a maximum temperature difference of about 15 K between the inlet and outlet. Furthermore, the parameter coupling characteristics between the center angles of channel, the average temperature difference, the flow velocity and the ratio of the channel width to channel spacing were analyzed. The fitting equation of the convective heat transfer coefficient was obtained and the overall error of convective heat transfer coefficient calculation is about 10%. The prediction equation could be used for spider web microchannel structure heat exchangers design. And the investigation results could provide the important reference for the thermal management system design of the vehicles.

Background: Abdominal pseudo-hernia secondary to herpes zoster infection is rare and the clinical features and factors affecting recovery remain poorly understood. Aim: We aimed to describe the clinical features of patients with abdominal pseudo-hernia secondary to herpes zoster infection and attempt to identify factors associated with poor recovery. Design: Literature review and retrospective Analysis. Methods: We report a case and performed a retrospective, systematic review of the demographic background, clinical characteristics and outcomes of patients with abdominal pseudo-hernia secondary to herpes zoster infection in the literature over 20 years (2001–2021). Results: We analyzed a total of 34 cases. The median age of the patients was 71.5 years. Most of the patients were male (n = 27, 79.4%). The most frequently affected dermatome was T-11 (n = 20, 66.7%). In four (12.5%) patients, abdominal pseudo-hernia started before the onset of rash. In all patients (n = 12, 100%) who underwent nerve conduction study and electromyography, there was electrophysiological evidence of acute denervation. Seven patients (20.6%) had imaging features suggestive of abdominal wall atrophy and denervation. The majority of patients had good recovery. The median follow-up time was 3 (15 days-12 months) months. Patients with pre-existing medical conditions (p = 0.03) were more likely to have a worse recovery. Conclusion: Abdominal pseudo-hernia is a rare complication of herpes zoster infection with a good prognosis for recovery, although patients with pre-existing disease appear to recover worse. In rare cases, it may occur before the onset of typical zoster rashes and should be suspected, especially in older, male patients with involvement of the lower thoracic dermatomes.

Though specific growth rate (SGR) has potential prognostic value for oropharyngeal squamous cell carcinoma (OPSCC), there is sparse literature defining these rates. Our aims were to establish the SGRs of primary tumors (PTs) and lymph nodes (LNs) in OPSCC and to correlate SGR with oncologic outcome. A pilot study was designed with a retrospective analysis examining 54 patients from the University of California, Davis with OPSCC (diagnosed 2012–2019). Radiation oncology software and pretreatment serial CT scans were used to measure PT and LN volumes to calculate SGR and doubling time (DT). The mean PT-SGR was 1.2 ± 2.2%/day and the mean LN-SGR was 1.6 ± 1.9%/day. There was no statistically significant difference between slow-growing and fast-growing cohorts in terms of age, gender, smoking status, tumor subsite, HPV status (as determined with p16 staining), initial volume, or overall stage. SGR had no impact on 2-year overall survival, disease-free survival, or disease-specific survival. We found the average daily growth rates for OPSCC to be 1.2%/day and 1.6%/day. Our findings suggest PT- and LN-SGR are independent factors, not heavily influenced by known biomarkers and patient characteristics, without a statistical impact on prognosis. This information has value in patient counseling regarding tumor growth and in providing patients worried about fast-growing tumors the appropriate reassurance.

In this study, we investigated whether radiomics features from pre-treatment positron emission tomography (PET) images could be used to predict disease progression in patients with HPV-positive oropharyngeal cancer treated with definitive proton or x-ray radiotherapy. Machine learning models were built using a dataset from Mayo Clinic, Rochester, Minnesota (n = 72) and tested on a dataset from Mayo Clinic, Phoenix, Arizona (n = 22). A total of 71 clinical and radiomics features were considered. The Mann–Whitney U test was used to identify the top 2 clinical and top 20 radiomics features that were significantly different between progression and progression-free patients. Two dimensionality reduction methods were used to define two feature sets (manually filtered or machine-driven). A forward feature selection scheme was conducted on each feature set to build models of increased complexity (number of input features from 1 to 6) and evaluate model robustness and overfitting. The machine-driven features had superior performance and were less prone to overfitting compared to the manually filtered features. The four-variable Gaussian Naïve Bayes model using the ‘Radiation Type’ clinical feature and three machine-driven features achieved a training accuracy of 79% and testing accuracy of 77%. These results demonstrate that radiomics features can provide risk stratification beyond HPV-status to formulate individualized treatment and follow-up strategies.

The laser welding-brazing technology assisted by alternating magnetic field was adapted to Mg/steel dissimilar materials with Ni interlayer. Microstructure and mechanical properties of joints were compared with and without alternating magnetic field. The results showed that the weld width L was enlarged and ensured good weld formation and weld quality by applying the alternating magnetic field. The joint was comprised of Mg side weld zone, intermetallic compound (IMC) layer and steel side weld zone. The effect of mechanical occlusion was enhanced by the appearce of zonal structures of Fe–Ni solid solution in the Mg side weld zone and the serrated Mg2Ni in the brazing zone of IMC layer. A continuous nano scale AlNi layer formed in the fusion welding zone of IMC layer, which is conducive to strengthen the joint. The optimal joint assisted by appropriate alternating magnetic field was obtained with tensile and shear strength enhanced by nearly 15%.

Abstract Spinal cord infarction may present as longitudinally extensive myelopathy, similar to inflammatory myelitis such as neuromyelitis optica. Magnetic resonance imaging features such as diffusion‐weighted imaging/apparent diffusion coefficient showing restricted diffusion and lack of contrast enhancement are helpful in the diagnosis of spinal cord infarction and differentiating them from inflammatory myelitis.

Purpose and Objectives: With increasing use of hypofractionation and extreme hypofractionation for prostate cancer, rectal dose-volume histogram (DVH) parameters that apply across dose fractionations may be helpful for treatment planning in clinical practice. We present an exploratory analysis of biologically effective rectal dose (BED) and equivalent rectal dose in 2 Gy fractions (EQD2) for rectal bleeding in patients treated with proton therapy across dose fractionations. Materials and Methods: From 2016 to 2018, 243 patients with prostate cancer were treated with definitive proton therapy. Rectal DVH parameters were obtained from treatment plans, and rectal bleeding events were recorded. The BED and EQD2 transformations were applied to each rectal DVH parameter. Univariate analysis using logistic regression was used to determine DVH parameters that were significant predictors of grade ≥ 2 rectal bleeding. Youden index was used to determine optimum cutoffs for clinically meaningful DVH constraints. Stepwise model-selection criteria were then applied to fit a “best” multivariate logistic model for predicting Common Terminology Criteria for Adverse Events grade ≥ 2 rectal bleeding. Results: Conventional fractionation, hypofractionation, and extreme hypofractionation were prescribed to 117 (48%), 84 (34%), and 42 (17.3%) patients, respectively. With a median follow-up of 20 (2.5-40) months, 10 (4.1%) patients experienced rectal bleeding. On univariate analysis, multiple rectal DVH parameters were significantly associated with rectal bleeding across BED, EQD2, and nominal doses. The BED volume receiving 55 Gy > 13.91% was found to be statistically and clinically significant. The BED volume receiving 55 Gy remained statistically significant for an association with rectal bleeding in the multivariate model (odds ratio, 9.81; 95% confidence interval, 2.4–40.5; P = .002). Conclusion: In patients undergoing definitive proton therapy for prostate cancer, dose to the rectum and volume of the rectum receiving the dose were significantly associated with rectal bleeding across conventional fractionation, hypofractionation, and extreme hypofractionation when using BED and EQD2 transformations.

Purpose: To evaluate the accuracy of deep-learning-based auto-segmentation of the superior constrictor, middle constrictor, inferior constrictor, and larynx in comparison with a traditional multi-atlas-based method. Methods and Materials: One hundred and five computed tomography image datasets from 83 head and neck cancer patients were retrospectively collected and the superior constrictor, middle constrictor, inferior constrictor, and larynx were analyzed for deep-learning versus multi-atlas-based segmentation. Eighty-three computed tomography images (40 diagnostic computed tomography and 43 planning computed tomography) were used for training the convolutional neural network, and for atlas-based model training. The remaining 22 computed tomography datasets were used for validation of the atlas-based auto-segmentation versus deep-learning-based auto-segmentation contours, both of which were compared with the corresponding manual contours. Quantitative measures included Dice similarity coefficient, recall, precision, Hausdorff distance, 95th percentile of Hausdorff distance, and mean surface distance. Dosimetric differences between the auto-generated contours and manual contours were evaluated. Subjective evaluation was obtained from 3 clinical observers to blindly score the autosegmented structures based on the percentage of slices that require manual modification. Results: The deep-learning-based auto-segmentation versus atlas-based auto-segmentation results were compared for the superior constrictor, middle constrictor, inferior constrictor, and larynx. The mean Dice similarity coefficient values for the 4 structures were 0.67, 0.60, 0.65, and 0.84 for deep-learning-based auto-segmentation, whereas atlas-based auto-segmentation has Dice similarity coefficient results at 0.45, 0.36, 0.50, and 0.70, respectively. The mean 95th percentile of Hausdorff distance (cm) for the 4 structures were 0.41, 0.57, 0.59, and 0.54 for deep-learning-based auto-segmentation, but 0.78, 0.95, 0.96, and 1.23 for atlas-based auto-segmentation results, respectively. Similar mean dose differences were obtained from the 2 sets of autosegmented contours compared to manual contours. The dose–volume discrepancies and the average modification rates were higher with the atlas-based auto-segmentation contours. Conclusion: Swallowing-related structures are more accurately generated with DL-based versus atlas-based segmentation when compared with manual contours.

Purpose: To validate the dose calculation accuracy and dose distribution of GammaTiles for brain tumors, and to suggest a surgically targeted radiation therapy (STaRT) workflow for planning, delivery, radiation safety documentation, and posttreatment validation. Methods and Materials: Novel surgically targeted radiation therapy, GammaTiles, uses Cs-131 radiation isotopes embedded in collagen-based tiles that can be resorbed after surgery. GammaTile target delineation and dose calculation were performed on MIM Symphony software. Point-based and complex seed distribution calculations in MIM Symphony were verified with hand calculations and BrachyVision calculations. Vendor-provided 2-dimensional dose distribution calculation accuracy was validated using gafchromic EBT3 film measurements at various depths. A workflow was established for safe and effective GammaTile implants. Results: Good agreement was observed between different calculations. Calculation accuracy of less than 0.5% was achieved for all points except one, which had rounding issues for very low doses and resulted in just below 5% difference. Differences in anisotropy and geometry positioning were noticed in the delineation of Cs-131 IsoRay seeds in the compared systems, resulting in minor discrepancies in the calculated dosimetry distributions. Film measurements showed profiles with relatively good agreement of 0% to 5% in nongradient regions with higher differences between 5% to 10% in the sharp dose fall-off regions. Conclusions: A comprehensive evaluation of GammaTile geometry, dose distribution, and clinical workflow was conducted. Safe intro-operative implantation of GammaTiles requires extensive preplanning and interdisciplinary collaboration. A STaRT workflow was outlined to provide a guideline for an accurate treatment planning and safe implant process at other institutions.

The association between a high-fat diet (HFD) consumption and emotional/cognitive disorders is widely documented. One distinctive feature of the prefrontal cortex (PFC), a kernel emotion- and cognition-related brain region, is its protracted adolescent maturation, which makes it highly vulnerable to the detrimental effects of environmental factors during adolescence. Disruption of the PFC structure and function is linked to emotional/cognitive disorders, especially those that emerge in late adolescence. A HFD consumption is common among adolescents, yet its potential effects on PFC-related neurobehavior in late adolescence and any related underlying mechanisms are yet to be established. In the present study, adolescent (postnatal days 28–56) male C57BL/6J mice were fed a control diet (CD) or a HFD and underwent behavioral tests in addition to Golgi staining and immunofluorescence targeting of the medial PFC (mPFC). The HFD-fed adolescent mice exhibited anxiety- and depression-like behavior and abnormal mPFC pyramidal neuronal morphology accompanied by alterations in microglial morphology indicative of a heightened state of activation and increased microglial PSD95+ inclusions signifying excessive phagocytosis of the synaptic material in the mPFC. These findings offer novel insights into the neurobehavioral effects due to adolescent HFD consumption and suggest a contributing role in microglial dysfunction and prefrontal neuroplasticity deficits for HFD-associated mood disorders in adolescents.

Although the protective effects of naringenin (Nar) on vascular smooth muscle cells (VSMCs) have been confirmed, whether it has anti-proliferation and anti-migration effects in high-glucose-induced VSMCs has remained unclear. This study aimed to clarify the potential targets and molecular mechanism of Nar when used to treat high-glucose-induced vasculopathy based on transcriptomics, network pharmacology, molecular docking, and in vivo and in vitro assays. We found that Nar has visible anti-proliferation and anti-migration effects both in vitro (high-glucose-induced VSMC proliferation and migration model) and in vivo (type 1 diabetes mouse model). Based on the results of network pharmacology and molecular docking, vascular endothelial growth factor A (VEGFA), the proto-oncogene tyrosine-protein kinase Src (Src) and the kinase insert domain receptor (KDR) are the core targets of Nar when used to treat diabetic angiopathies, according to the degree value and the docking score of the three core genes. Interestingly, not only the Biological Process (BP), Molecular Function (MF), and KEGG enrichment results from network pharmacology analysis but also transcriptomics showed that phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt) is the most likely downstream pathway involved in the protective effects of Nar on VSMCs. Notably, according to the differentially expressed genes (DEGs) in the transcriptomic analysis, we found that cAMP-responsive element binding protein 5 (CREB5) is a downstream protein of the PI3K/Akt pathway that participates in VSMCs proliferation and migration. Furthermore, the results of molecular experiments in vitro were consistent with the bioinformatic analysis. Nar significantly inhibited the protein expression of the core targets (VEGFA, Src and KDR) and downregulated the PI3K/Akt/CREB5 pathway. Our results indicated that Nar exerted anti-proliferation and anti-migration effects on high-glucose-induced VSMCs through decreasing expression of the target protein VEGFA, and then downregulating the PI3K/Akt/CREB5 pathway, suggesting its potential for treating diabetic angiopathies.

Interstock is an important agronomic technique for regulating plant growth and fruit quality, and overcoming the incompatibility between rootstocks and scions; however, the underlying mechanisms remain largely unknown. In this study, the effects and regulatory mechanisms of tangor grafting, with and without interstocks, on the growth and development of scions were analyzed by combining morphology, physiology, anatomy and transcriptomics. Morphological and physiological analyses showed that interstocks (‘Aiyuan 38’ and ‘Daya’) significantly improved the growth of seedlings, effectively enhanced the foliar accumulation of chlorophyll and carotenoids, and increased the thickness of leaf tissues. Using ‘Aiyuan 38’ as the interstock, photosynthetic efficiency and starch content of citrus seedlings improved. Transcriptomics showed that genes related to photosynthesis and photosynthetic antenna proteins were upregulated in interstock-treated seedlings, with significant upregulation of photosystem PSI- and PSII-related genes. In addition, multiple key genes may be involved in plant hormone signaling, starch and sucrose metabolism, and transcriptional regulation. Taken together, these findings provide novel insights into the role of interstocks in regulating and contributing to the growth and development of grafted seedlings, and will further define and deploy candidate genes to explore the mechanisms of rootstock-interstock-scion interactions.

Against the backdrop of global warming, the changing area of Arctic sea ice is constantly shrinking, and the fluctuation of the Arctic sea ice area is the outcome of multiple factors. This paper mainly studies the volatility, periodicity, trend and related climate factors of Arctic sea ice area variation. It is found that the period of Arctic sea ice area variation T is equal to 3.468 years by establishing a sea ice area change model, and there is a strong negative correlation between the time series of the deseasonalized temperature and the sea ice area through the correlation analysis, with a Pearson coefficient of -0.711. In addition, the Bruun rule leads to the conclusion that for every 1cm increase in sea level, the coastline will retreat by 0.5- 1m, which indirectly indicates that without considering other conditions, the continental area will decrease as the sea ice area decreases. Finally, the conclusion obtained is that the CO2 level has the highest correlation degree by establishing a grey correlation degree model for each factor. Based on this, various measures are proposed to find solutions to the relevant factors and change existing policies to minimize the harm of the warming climate.

While poverty-targeted subsidies have shown promise as a means of reducing financial constraints on low-income populations to invest in new latrines, concerns have been raised about whether they may reduce demand for new latrines among non-eligible, non-poor populations, especially in geographically limited or closed markets. Using quasi experimental methods, we investigate the interaction effects of the "CHOBA" subsidy, a partial poverty-targeted monetary incentive to build a toilet, and a sanitation marketing program (SanMark) on new latrine uptake among households from different income segments in 110 rural villages across six Cambodian provinces. These programs were implemented either jointly with or independently. Overall, we find strong complementarity of the CHOBA subsidy with SanMark where the coupled implementation of the programs increased latrine uptake across all households as compared to exclusive deployment of the programs independently. Additionally, the CHOBA subsidy alone resulted in higher gains among the poor compared to SanMark suggesting that financial constraint is indeed a significant demand barrier for new latrines. The presence of the poverty-targeted subsidies did not reduce demand for new latrine purchases among ineligible households. Instead, we find some evidence for a positive spillover effect of subsidies on uptake of latrines among ineligible households in villages where both programs were implemented indicating that the presence of sanitation subsidies and the decision to purchase latrines among non-beneficiaries can be viewed as complements. We employ multivariate logistic regressions as well as further robustness checks to estimate the effects of the different interventions, with qualitatively consistent results.

Abstract Background Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease worldwide. Current studies have shown that PNPLA3 (Patatin-like phospholipase domain containing 3) rs738409 G/C gene polymorphism is associated with adult nonalcoholic fatty liver disease [1, 2].But there is no consensus on the relationship between PNPLA3 rs738409 G/C gene polymorphism and children NAFLD due to differences in population samples. To this end, a meta-analysis of published research is conducted to comprehensively assess the relationship between PNPLA3 gene polymorphism and NAFLD in children. Methods We searched MEDLINE, PubMed, EMBASE, and CENTRAL databases from inception to May 2019. Case-control studies assessing the relationship between PNPLA3 rs738409 G/C gene polymorphism with non-alcoholic fatty liver disease in children were selected according to inclusion and exclusion criteria. Random effects model was used to quantify the association between the PNPLA3 rs738409 G/C gene polymorphism and the susceptibility of children’s NAFLD. Fixed effects model was used to quantify the relationship between the PNPLA3 rs738409 G/C gene polymorphism and the severity of NAFLD in children. The Stata 12.0 software was employed for data analysis. Results A total of nine case-control studies were included in this meta-analysis containing data of 1173 children with NAFLD and 1792 healthy controls. Five studies compared NAFLD children and non-NAFLD healthy populations. Statistical analysis showed that PNPLA3 gene polymorphism was significantly associated with children’s NAFLD in the allele contrast, dominant, recessive and over dominant models (G vs C,OR = 3.343, 95% CI = 1.524–7.334; GG + GC vs CC,OR = 3.157, 95% CI = 1.446–6.892;GG vs GC + CC,OR = 5.692, 95% CI = 1.941–16.689; GG + CC vs GC,OR = 2.756, 95% CI = 1.729–4.392). Four case-control studies compared Children with nonalcoholic fatty liver (NAFL) and children with nonalcoholic steatohepatitis (NASH). The results showed that the PNPLA3 gene polymorphism was also significantly associated with the severity of NAFLD in children in recessive gene model (GG vs GC + CC,OR = 14.43, 95% CI = 5.985–34.997); The Egger’s test revealed no significant publication bias. Conclusions Meta-analysis showed that PNPLA3 gene polymorphism was significantly associated with susceptibility and severity of NAFLD in children.

Abstract Background Impaired function of masticatory muscles will lead to trismus. Routine delineation of these muscles during planning may improve dose tracking and facilitate dose reduction resulting in decreased radiation-related trismus. This study aimed to compare a deep learning model with a commercial atlas-based model for fast auto-segmentation of the masticatory muscles on head and neck computed tomography (CT) images. Material and methods Paired masseter (M), temporalis (T), medial and lateral pterygoid (MP, LP) muscles were manually segmented on 56 CT images. CT images were randomly divided into training (n = 27) and validation (n = 29) cohorts. Two methods were used for automatic delineation of masticatory muscles (MMs): Deep learning auto-segmentation (DLAS) and atlas-based auto-segmentation (ABAS). The automatic algorithms were evaluated using Dice similarity coefficient (DSC), recall, precision, Hausdorff distance (HD), HD95, and mean surface distance (MSD). A consolidated score was calculated by normalizing the metrics against interobserver variability and averaging over all patients. Differences in dose (∆Dose) to MMs for DLAS and ABAS segmentations were assessed. A paired t-test was used to compare the geometric and dosimetric difference between DLAS and ABAS methods. Results DLAS outperformed ABAS in delineating all MMs (p 0.05). DLAS based contours had dose endpoints more closely matched with that of the manually segmented when compared with ABAS. Conclusions DLAS auto-segmentation of masticatory muscles for the head and neck radiotherapy had improved segmentation accuracy compared with ABAS with no qualitative difference in dosimetric endpoints compared to manually segmented contours.

Purpose: Post-operative prostate cancer patients are treated with full bladder instruction and the use of an endorectal balloon (ERB). We reassessed the efficacy of this practice based on daily image guidance and dose delivery using high-quality iterative reconstructed cone-beam CT (iCBCT). Methods: Fractional dose delivery was calculated on daily iCBCT for 314 fractions from 14 post-operative prostate patients (8 with and 6 without ERB) treated with volumetric modulated radiotherapy (VMAT). All patients were positioned using novel iCBCT during image guidance. The bladder, rectal wall, femoral heads, and prostate bed clinical tumor volume (CTV) were contoured and verified on daily iCBCT. The dose-volume parameters of the contoured organs at risk (OAR) and CTV coverage were assessed for the clinical impact of daily bladder volume variations and the use of ERB. Minimum bladder volume was studied, and a straightforward bladder instruction was explored for easy clinical adoption. Results: A “minimum bladder” contour, the overlap between the original bladder contour and a 15 mm anterior and superior expansion from prostate bed PTV, was confirmed to be effective in identifying cases that might fail a bladder constraint of V65% : A “minimum bladder” contour was determined that can be easily generated and followed to ensure sufficient bladder sparing. Further analysis and validation are needed to confirm the utility of the minimal bladder contour. Accurate dose delivery can be achieved for prostate bed target coverage and OAR sparing with or without the use of ERB.

Purpose: Planning target volume (PTV) expansion for post-prostatectomy radiotherapy is typically ≥5 mm. Recent clinical trials have proved the feasibility of a reduced margin of 2–3 mm for treatments on MRI-linac. We aim to study the minimum PTV margin needed using iterative cone-beam CT (iCBCT) as image guidance on conventional linacs. Materials/Methods: Fourteen patients who received post-prostatectomy irradiation (8 with an endorectal balloon and 6 without a balloon) were included in this study. Treatment was delivered with volumetric modulated radiation therapy (VMAT). Fractional dose delivery was evaluated in 165 treatment fractions. The bladder, rectal wall, femoral heads, and prostate bed clinical tumor volume (CTV) were contoured and verified on daily iCBCT. PTV margins (0 mm, 2 mm, and 4 mm) were evaluated on daily iCBCT. CTV coverage and OAR dose parameters were assessed with each PTV margin. Results: CTV D100% was underdosed with a 0 mm margin in 32% of fractions in comparison with 2 mm (6%) and 4 mm (6%) PTV margin (p ≤ 0.001). CTV D95% > 95% was met in 93–94% fractions for all PTV expansions. CTV D95% > 95% was achieved in more patients with an endorectal balloon than those without: 0 mm—90/91 (99%) vs. 63/74 (85%); 2 mm—90/91 (99%) vs. 65/75 (87%); 4 mm—90/90 (100%) vs. 63/73 (86%). There was no difference in absolute median change in CTV D95% (0.32%) for 0-, 2-, and 4 mm margins. The maximum dose remained under 108% for 100% (0 mm), 97% (2 mm), and 98% (4 mm) of images. Rectal wall maximum dose remained under 108% for 100% (0 mm), 100% (2 mm), and 98% (4 mm) of images. Conclusions: With high-quality iCBCT image guidance, PTV margin accounting for inter-fractional uncertainties can be safely reduced for post-prostatectomy radiotherapy. For fractionated radiotherapy, an isotropic expansion of 2 mm and 4 mm may be considered for margin expansion with and without the endorectal balloon. Future application for margin reduction needs to be further evaluated and considered with the advent of shorter post-prostatectomy radiation courses.

Identifying urban production–living–ecological spaces and their interactive relationships is conducive to better understanding and optimizing urban space development. This paper took the main urban area of Hangzhou city as an example, and a two-level scoring evaluation model was constructed to accurately identify urban production–living–ecological spaces using point of interest (POI) data. Then, kernel density analysis, a spatial transfer matrix, and a bivariate spatial autocorrelation model were used to reveal the spatial patterns of urban production–living–ecological spaces and their interactive relationships during 2010 and 2019. The results showed that the proposed two-level scoring evaluation model combining both the physical area and density of POIs was effective in accurately identifying urban production–living–ecological spaces using POI data, with an identification accuracy of 88.9%. Urban production space was concentrated on the south bank of the Qiantang River and around the north of Hangzhou. Urban living space had the highest proportion, mainly distributed within the ring highway of Hangzhou in a contiguous distribution pattern, and urban ecological space was concentrated around West Lake and Xiang Lake. During 2010 and 2019, the expansion of urban production–living–ecological spaces had obvious spatial differences. Additionally, the mutual transformation between production and living spaces was more frequent during the study period and was mainly distributed within the ring highway of Hangzhou. There were significant positive spatial correlations between production and living and between living and ecological spaces, while a significant negative spatial correlation occurred between production and ecological spaces. The spatial correlations of urban production–living–ecological spaces revealed obvious spatial heterogeneity. This study proposed a two-level scoring evaluation model to accurately identify the spatial patterns of urban production–living–ecological spaces and their interactive relationships using POI data, which can provide detailed information and scientific references for urban spatial planning and management in rapidly urbanizing cities.

Sepsis is a dysregulated systemic response to infection, and no effective treatment options are available. Acacetin is a natural flavonoid found in various plants, including Sparganii rhizoma, Sargentodoxa cuneata and Patrinia scabiosifolia. Studies have revealed that acacetin potentially exerts anti-inflammatory and antioxidative effects on sepsis. In this study, we investigated the potential protective effect of acacetin on sepsis and revealed the underlying mechanisms using a network pharmacology approach coupled with experimental validation and molecular docking. First, we found that acacetin significantly suppressed pathological damage and pro-inflammatory cytokine expression in mice with LPS-induced fulminant hepatic failure and acute lung injury, and in vitro experiments further confirmed that acacetin attenuated LPS-induced M1 polarization. Then, network pharmacology screening revealed EGFR, PTGS2, SRC and ESR1 as the top four overlapping targets in a PPI network, and GO and KEGG analyses revealed the top 20 enriched biological processes and signalling pathways associated with the therapeutic effects of acacetin on sepsis. Further network pharmacological analysis indicated that gap junctions may be highly involved in the protective effects of acacetin on sepsis. Finally, molecular docking verified that acacetin bound to the active sites of the four targets predicted by network pharmacology, and in vitro experiments further confirmed that acacetin significantly inhibited the upregulation of p-src induced by LPS and attenuated LPS-induced M1 polarization through gap junctions. Taken together, our results indicate that acacetin may protect against sepsis via a mechanism involving multiple targets and pathways and that gap junctions may be highly involved in this process.

Many orally administered phenolic drugs undergo enterohepatic recycling (EHR), presumably mediated by the hepatic phase II enzymes. However, the disposition of extrahepatically generated phase II metabolites is unclear. This paper aims to determine the new roles of liver and intestine in the disposition of oral phenolics. Sixteen representative phenolics were tested using direct portal vein infusion and/or intestinal perfusion. The results showed that certain glucuronides were efficiently recycled by liver. OATP1B1/1B3/2B1 were the responsible uptake transporters. Hepatic uptake is the rate-limiting step in hepatic recycling. Our findings showed that the disposition of many oral phenolics is mediated by intestinal glucuronidation and hepatic recycling. A new disposition mechanism ‘Hepatoenteric Recycling (HER)”, where intestine is the metabolic organ and liver is the recycling organ, was revealed. Further investigations focusing on HER should help interpret how intestinal aliments or co-administered drugs that alter gut enzymes (e.g. UGTs) expression/activities will impact the disposition of phenolics.

PurposeA 3D printed geometric phantom was developed that can be scanned with computed tomography (CT) and magnetic resonance imaging (MRI) to measure the geometric distortion and determine the relevant dose changes.Materials and MethodsA self-designed 3D printed photosensitive resin phantom was used, which adopts grid-like structures and has 822 1 cm2 squares. The scanning plan was delivered by three MRI scanners: the Elekta Unity MR-Linac 1.5T, GE Signa HDe 1.5T, and GE Discovery-sim 750 3.0T. The geometric distortion comparison was concentrated on two 1.5T MRI systems, whereas the 3.0T MRI was used as a supplemental experiment. The most central transverse images in each dataset were selected to demonstrate the plane distortion. Some mark points were selected to analyze the distortion in the 3D direction based on the plane geometric distortion. A treatment plan was created with the off-line Monaco system.ResultsThe distortion increases gradually from the center to the outside. The distortion range is 0.79 ± 0.40 mm for the Unity, 1.31 ± 0.56 mm for the GE Signa HDe, and 2.82 ± 1.48 mm for the GE Discovery-sim 750. Additionally, the geometric distortion slightly affects the actual planning dose of the radiotherapy.ConclusionGeometric distortion increases gradually from the center to the outside. The distortion values of the Unity were smaller than those of the GE Signa HDe, and the Unity has the smallest geometric distortion. Finally, the Unity’s dose variation best matched with the standard treatment plan.

Despite widespread use of antiretroviral therapy (ART), HIV remains a major public health issue. Even with effective ART many infected individuals still suffer from the constellation of neurological symptoms now known as neuroHIV. These symptoms can be exacerbated by substance abuse, a common comorbidity among HIV-infected individuals. The mechanism(s) by which different types of drugs impact neuroHIV remains unclear, but all drugs of abuse increase central nervous system (CNS) dopamine and elevated dopamine increases HIV infection and inflammation in human myeloid cells including macrophages and microglia, the primary targets for HIV in the brain. Thus, drug-induced increases in CNS dopamine may be a common mechanism by which distinct addictive substances alter neuroHIV. Myeloid cells are generally infected by HIV strains that use the chemokine receptor CCR5 as a co-receptor, and our data indicate that in a subset of individuals, drug-induced levels of dopamine could interfere with the effectiveness of the CCR5 inhibitor Maraviroc. CCR5 can adopt distinct conformations that differentially regulate the efficiency of HIV entry and subsequent replication and using qPCR, flow cytometry, Western blotting and high content fluorescent imaging, we show that dopamine alters the expression of specific CCR5 conformations of CCR5 on the surface of human macrophages. These changes are not affected by association with lipid rafts, but do correlate with dopamine receptor gene expression levels, specifically higher levels of D1-like dopamine receptors. These data also demonstrate that dopamine increases HIV replication and alters CCR5 conformations in human microglia similarly to macrophages. These data support the importance of dopamine in the development of neuroHIV and indicate that dopamine signaling pathways should be examined as a target in antiretroviral therapies specifically tailored to HIV-infected drug abusers. Further, these studies show the potential immunomodulatory role of dopamine, suggesting changes in this neurotransmitter may also affect the progression of other diseases.

Purpose: To develop a method for constructing customizable, multimodal quality control (QC) imaging phantoms based on 3D printing technology.Materials and Methods: Four phantoms were designed and constructed through 3D printing technology using three unique printing materials. Physical parameters of the 3D printed materials were evaluated, including density, shore hardness, porosity, deformation temperature, computed tomography (CT) number, absorption coefficient, and printing accuracy. Imaging performance of the phantoms was studied using MRI, CT, PET/MR, and PET/CT, and compared with conventional/commercial phantoms. Imaging assessments included high contrast resolution, low contrast resolution, uniformity, deformation, SNR, slice accuracy/slice thickness, location accuracy/laser alignment, CT number, relaxation time, and registration.Results: All three printing materials have a shore hardness of 90. The physical densities of these materials are 1.15 g/cm3, 0.76 g/cm3, and 1.27 g/cm3, respectively. The porosities are 9.09, 6.81, and 18.56%, respectively. The threshold temperature of deformation for the three materials is >105°C, which is higher than that of PMMA and silica gel. Imaging scans of the constructed phantoms for single modality scanners (MRI and CT) and dual-modality scanners (PET/MRI and PET/CT) were compared with those of the commercial phantoms. The standard deviation of the HU value uniformity test was

Purpose: To assess image quality and uncertainty in organ-at-risk segmentation on cone beam computed tomography (CBCT) enhanced by deep-learning convolutional neural network (DCNN) for head and neck cancer.Methods: An in-house DCNN was trained using forty post-operative head and neck cancer patients with their planning CT and first-fraction CBCT images. Additional fifteen patients with repeat simulation CT (rCT) and CBCT scan taken on the same day (oCBCT) were used for validation and clinical utility assessment. Enhanced CBCT (eCBCT) images were generated from the oCBCT using the in-house DCNN. Quantitative imaging quality improvement was evaluated using HU accuracy, signal-to-noise-ratio (SNR), and structural similarity index measure (SSIM). Organs-at-risk (OARs) were delineated on o/eCBCT and compared with manual structures on the same day rCT. Contour accuracy was assessed using dice similarity coefficient (DSC), Hausdorff distance (HD), and center of mass (COM) displacement. Qualitative assessment of users’ confidence in manual segmenting OARs was performed on both eCBCT and oCBCT by visual scoring.Results: eCBCT organs-at-risk had significant improvement on mean pixel values, SNR (p < 0.05), and SSIM (p < 0.05) compared to oCBCT images. Mean DSC of eCBCT-to-rCT (0.83 ± 0.06) was higher than oCBCT-to-rCT (0.70 ± 0.13). Improvement was observed for mean HD of eCBCT-to-rCT (0.42 ± 0.13 cm) vs. oCBCT-to-rCT (0.72 ± 0.25 cm). Mean COM was less for eCBCT-to-rCT (0.28 ± 0.19 cm) comparing to oCBCT-to-rCT (0.44 ± 0.22 cm). Visual scores showed OAR segmentation was more accessible on eCBCT than oCBCT images.Conclusion: DCNN improved fast-scan low-dose CBCT in terms of the HU accuracy, image contrast, and OAR delineation accuracy, presenting potential of eCBCT for adaptive radiotherapy.

Introduction: Colon carcinoma is a common malignant tumor worldwide. Accurately predicting prognosis of colon adenocarcinoma (CA) patients may facilitate clinical individual decision-making. Many studies have reported that microRNAs (miRNAs) were associated with prognosis for patients with colon carcinoma. This study aimed to identify the prognosis-related miRNAs for predicting the overall survival (OS) of CA patients.Methods: Firstly, we analyzed the CA datasets from the Cancer Genome Atlas (TCGA), and looked for the prognosis-related miRNAs. Then, we developed a novel prediction model based on these miRNAs and the clinical characteristics. Time-dependent receiver operating characteristics (ROC) curves and calibration plots were used to evaluate the discrimination and accuracy of the signature and model. Finally, cell function assays and bioinformatics analyses were performed to evaluate the role of these selected miRNAs in modulating biological process in CA.Results: Six prognosis-related miRNAs were included in the miRNA-based signature, and it could effectively distinguish low-risk patients and high-risk patients. Furthermore, we established a prognostic model incorporating the six-miRNA-based signature and clinical characteristics. Areas under curves (AUCs) indicated that the six-miRNA-based model has a better predictive ability than TNM stage (AUC: 0.805 vs. 0.694). The calibration plots suggested close agreement between model predictions and actual observations. GO analysis showed that the target genes of these miRNAs are mainly involved in enrichment in protein binding and regulation of transcript and cytosol. KEGG pathway enrichment analysis indicated that these genes were mainly enriched in PI3K-Akt signaling pathway. Finally, we found that the five miRNAs except miR-152 were upregulated in tumor tissues and CA cells. The functional experiments revealed that miR-1245a, miR-3682, miR-33b, and miR-5683 promoted the migratory abilities and proliferation of CA cell, whereas miR-152 showed opposite effects. However, miR-4444-2 did not influence the migratory ability and proliferation of CA cell.Conclusions: In conclusion, we developed a novel six-miRNA-based model to predict 5-year survival probabilities for CA patients. This model has the potential to facilitate individualized treatment decisions.

Combinational use of drugs has been a common strategy in cancer treatment because of synergistic advantages in reducing dose and toxicity, minimizing or delaying drug resistance. To improve the efficacy of chemotherapy, various potential combinations have been investigated. Ruthenium complex is considered a potential alternative of the platinum-based drugs due to its significant efficacy and safety. Previously, we reported that ruthenium(II) complex (Δ-Ru1) has great anticancer potential and minor toxicity toward normal tissues. However, the therapeutic efficacy and mechanism of action of ruthenium(II) complex combined with other anticancer drugs is still unknown. Here, we investigated the combinational effect of Δ-Ru1 and doxorubicin in different cancer cells. The data assessed by Chou-Talalay method showed significant synergism in MCF-7 cells. Furthermore, the results in antiproliferation efficacy indicated that the combination showed strong cytotoxicity and increasing apoptosis of MCF-7 cells in 2D and 3D multicellular tumor spheroids (MCTSs). Significant inhibition of MCF-7 cells accompanied with increased ROS generation was observed. Furthermore, the expression of PI3K/AKT was significantly down-regulated, while the expression of PTEN was strongly up-regulated in cells treated with combination of Δ-Ru1 and doxorubicin. The expression of NF-κB and XIAP decreased while the expression of P53 increased and associated with apoptosis. These findings suggest that the combination of ruthenium complex and doxorubicin has a significant synergistic effect by down-regulating the PI3K/AKT signaling pathway in MCF-7 cells. This study may trigger more research in ruthenium complex and combination therapy that will be able to provide opportunities for developing better therapeutics for cancer treatment.

Background. There is a growing number of patients with sleep-disordered breathing (SDB) referred to sleep clinics. Therefore, a simple but useful screening tool is urgent. The NoSAS score, containing only five items, has been developed and validated in population-based studies. Aim. To evaluate the performance of the NoSAS score for the screening of SDB patients from a sleep clinic in China, and to compare the predictive value of the NoSAS score with the STOP-Bang questionnaire. Methods. We enrolled consecutive patients from a sleep clinic who had undergone apnea-hypopnea index (AHI) testing by type III portable monitor device at the hospital and completed the STOP-Bang questionnaire. The NoSAS score was assessed by reviewing medical records. Sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of both screening tools were calculated at different AHI cutoffs to compare the performance of SDB screening. Results. Of the 596 eligible patients (397 males and 199 female), 514 were diagnosed with SDB. When predicting overall (AHI ≥ 5), moderate-to-severe (AHI ≥ 15), and severe (AHI ≥ 30) SDB, the sensitivity and specificity of the NoSAS score were 71.2, 80.4, and 83.1% and 62.4, 49.3, and 40.7%, respectively. At all AHI cutoffs, the AUC ranged from 0.688 to 0.715 for the NoSAS score and from 0.663 to 0.693 for the STOP-Bang questionnaire. The NoSAS score had the largest AUC (0.715, 95% CI: 0.655–0.775) of diagnosing SDB at AHI cutoff of ≥5 events/h. NoSAS performed better in discriminating moderate-to-severe SDB than STOP-Bang with a marginally significantly higher AUC (0.697 vs. 0.663, P=0.046). Conclusion. The NoSAS score had good performance on the discrimination of SDB patients in sleep clinic and can be utilized as an effective screening tool in clinical practice.

Abstract Background Crystalline silica is considered as one of the most common and serious occupational hazards to workers’ health. Although its association with lung cancer has been studied for many decades, the conclusion remains somewhat controversial. Our objectives are to review and summarize the epidemiological evidence on the relationship between occupational silica exposure and risk of lung cancer and to provide an update on this major occupational health concern. Methods Eligible studies up to 29 April 2016 were identified. Pooled effect estimates were calculated according to the reported outcome and the study design. Cohort, case control and proportional mortality studies were examined separately. Studies reporting results according to silicotic status were grouped together and analyzed. Due to the significant amount of heterogeneity expected, random effects models were implemented. Subgroup and meta-regression analyses (both univariate and multivariate) were performed in an attempt to explain heterogeneity. Studies which had adequate exposure characterization were selected to find out whether there was an exposure-response relationship between silica and lung cancer. Results The risk of lung cancer was found to be elevated in both silicotics and non-silicotics. The pooled standardized mortality ratio (SMR) was 2.32 with a 95 % confidence interval (95 % CI) of 1.91–2.81 and 1.78 (95 % CI 1.07–2.96) respectively. The pooled standardized incidence ratio (SIR) was 2.49 (95 % CI 1.87–3.33) and 1.18 (95 % CI 0.86–1.62) respectively. Subgroup analysis showed that workers in the mining industry had the highest risk of lung cancer with a pooled SMR of 1.48 (95 % CI 1.18–1.86) and the weakest association was seen in potteries with a pooled SMR of 1.14 (95 % CI 1.05–1.23). A positive exposure-response relation was found between cumulative silica exposure and risk of lung cancer. Conclusion The results of our meta-analysis supported the carcinogenic role of silica on the lungs, which was more pronounced at higher levels of exposure, in the presence of silicosis and in the mining industry. Further research is needed to evaluate whether non-silicotics are truly at risk, whether a predisposing factor would explain this potential risk, and to determine the mechanism of carcinogenicity of silica in humans.