Which one is the best in treating deep venous thrombosis -- percutaneous mechanical thrombectomy, catheter-directed thrombolysis or combination of them?

OBJECTIVE: To compare the treatment outcomes among percutaneous mechanical thrombectomy (PMT) with AngioJet, Catheter-directed thrombolysis (CDT), and a combination of both. METHODS: One hundred forty nine patients with acute or sub-acute iliac-femoral vein thrombosis accepting CDT and/or PMT were divided into three groups respectively: PMT group, CDT group, PMT + CDT group (PMT followed by CDT). The severity of thrombosis was evaluated by venographic scoring system. Technical success was defined as restored patent deep venous blood flow after CDT and/or PMT. Clinical follow-up were assessed by ultrasound or venography imaging. The primary endpoints were recurrence of DVT, and severity level of post-thrombotic syndrome (PTS) during the follow-up. RESULTS: Technical success and immediate clinical improvements were achieved on all patients. The proportion of sub-acute DVT and the venographic scoring in PMT + CDT group were significantly higher than that in CDT group and PMT group (proportion of sub-acute DVT: p = 0.032 and p = 0.005, respectively; venographic scoring: p < 0.001, respectively). The proportion of May-Thurner Syndrome was lower in PMT group than that in CDT and PMT + CDT group (p = 0.026 and p = 0.005, respectively). The proportion of DVT recurrence/stent thrombosis was significantly higher in CDT group than that in PMT + CDT group (p = 0.04). The severity of PTS was the highest in CDT group ( χ2 = 14.459, p = 0.006) compared to PMT group (p = 0.029) and PMT + CDT group (p = 0.006). CONCLUSION: Patients with sub-acute DVT, high SVS scoring and combined May-Thurner Syndrome were recommended to take PMT + CDT treatment and might have lower rate of DVT recurrence/stent thrombosis and severe PTS. Our study provided evidence detailing of PMT + CDT therapy.

Plasma metabolomics of immune-related adverse events for patients with lung cancer treated with PD-1/PD-L1 inhibitors.

BACKGROUND: Metabolomics has the characteristics of terminal effects and reflects the physiological state of biological diseases more directly. Several current biomarkers of multiple omics were revealed to be associated with immune-related adverse events (irAEs) occurrence. However, there is a lack of reliable metabolic biomarkers to predict irAEs. This study aims to explore the potential metabolic biomarkers to predict risk of irAEs and to investigate the association of plasma metabolites level with survival in patients with lung cancer receiving PD-1/PD-L1 inhibitor treatment. METHODS: The study collected 170 plasmas of 85 patients with lung cancer who received immune checkpoint inhibitors (ICIs) treatment. 58 plasma samples of 29 patients with irAEs were collected before ICIs treatment and at the onset of irAEs. 112 plasma samples of 56 patients who did not develop irAEs were collected before ICIs treatment and plasma matched by treatment cycles to onset of irAEs patients. Untargeted metabolomics analysis was used to identify the differential metabolites before initiating ICIs treatment and during the process that development of irAEs. Kaplan-Meier curves analysis was used to detect the associations of plasma metabolites level with survival of patients with lung cancer. RESULTS: A total of 24 differential metabolites were identified to predict the occurrence of irAEs. Baseline acylcarnitines and steroids levels are significantly higher in patients with irAEs, and the model of eight acylcarnitine and six steroid metabolites baseline level predicts irAEs occurrence with area under the curve of 0.91. Patients with lower concentration of baseline decenoylcarnitine(AcCa(10:1) 2, decenoylcarnitine(AcCa(10:1) 3 and hexanoylcarnitine(AcCa(6:0) in plasma would have better overall survival (OS). Moreover, 52 differential metabolites were identified related to irAEs during ICIs treatment, dehydroepiandrosterone sulfate, corticoserone, cortisol, thyroxine and sphinganine 1-phaosphate were significantly decreased in irAEs group while oxoglutaric acid and taurocholic acid were significantly increased in irAEs group. CONCLUSIONS: High levels of acylcarnitines and steroid hormone metabolites might be risk factor to development of irAEs, and levels of decenoylcarnitine (AcCa(10:1) 2, decenoylcarnitine (AcCa(10:1) 3 and hexanoylcarnitine (AcCa(6:0) could be used to predict OS for patients with lung cancer received ICIs treatment.

Physical activity promotes brain development through serotonin during early childhood.

Early childhood serves as a critical period for neural development and skill acquisition when children are extremely susceptible to the external environment and experience. As a crucial experiential stimulus, physical activity is believed to produce a series of positive effects on brain development, such as cognitive function, social-emotional abilities, and psychological well-being. The World Health Organization recommends that children engage in sufficient daily physical activity, which has already been strongly advocated in the practice of preschool education. However, the mechanisms by which physical activity promotes brain development are still unclear. The role of neurotransmitters, especially serotonin, in promoting brain development through physical activity has received increasing attention. Physical activity has been shown to stimulate the secretion of serotonin by increasing the bioavailability of free tryptophan and enriching the diversity of gut microbiota. Due to its important role in modulating neuronal proliferation, differentiation, synaptic morphogenesis, and synaptic transmission, serotonin can regulate children's explicit cognitive and social interaction behavior in the early stages of life. Therefore, we hypothesized that serotonin emerges as a pivotal transmitter that mediates the relationship between physical activity and brain development during early childhood. Further systematic reviews and meta-analyses are needed to specifically explore whether the type, intensity, dosage, duration, and degree of voluntariness of PA may affect the role of serotonin in the relationship between physical activity and brain function. This review not only helps us understand the impact of exercise on development but also provides a solid theoretical basis for increasing physical activity during early childhood.

Cross-Linkable Binders for Si Anodes in High-Energy-Density Lithium-Ion Batteries.

Although silicon (Si) has a high theoretical capacity, the large volume expansion during lithiation has greatly hindered its application in high-energy-density lithium-ion batteries (LIBs). Among the strategies for improving the performance of Si anode, the role of binders should not be underestimated. Here, a novel strategy for designing a cross-linkable binder for Si anode has been proposed. The binder with hydroxyl and nitrile groups can be in situ covalently cross-linked through the amide group in the batteries. The cross-linked binder (c-POAH) shows high elasticity and strong adhesion to Si particles and the current collector. Si||Li half coin cells using the c-POAH binder have excellent cycle performance and the capacity retention ratio is 67.1% after 100 cycles at 0.2 C. Scanning electronic microscopy images show that the c-POAH binder can contribute to suppressing the pulverization of the Si anode. Moreover, the investigation with X-ray photoelectronic spectrum demonstrates that the decomposition of the liquid electrolyte on Si anode has been mitigated and the c-POAH binder can promote the formation of a more stable SEI film. Our strategy of endowing the binder with good elasticity through in situ cross-linking has opened up a new route for developing binders, which will definitely promote the application of Si anodes in high-energy-density LIBs.

A Review on Autism Spectrum Disorder Screening by Artificial Intelligence Methods.

PURPOSE: With the increasing prevalence of autism spectrum disorders (ASD), the importance of early screening and diagnosis has been subject to considerable discussion. Given the subtle differences between ASD children and typically developing children during the early stages of development, it is imperative to investigate the utilization of automatic recognition methods powered by artificial intelligence. We aim to summarize the research work on this topic and sort out the markers that can be used for identification. METHODS: We searched the papers published in the Web of Science, PubMed, Scopus, Medline, SpringerLink, Wiley Online Library, and EBSCO databases from 1st January 2013 to 13th November 2023, and 43 articles were included. RESULTS: These articles mainly divided recognition markers into five categories: gaze behaviors, facial expressions, motor movements, voice features, and task performance. Based on the above markers, the accuracy of artificial intelligence screening ranged from 62.13 to 100%, the sensitivity ranged from 69.67 to 100%, the specificity ranged from 54 to 100%. CONCLUSION: Therefore, artificial intelligence recognition holds promise as a tool for identifying children with ASD. However, it still needs to continually enhance the screening model and improve accuracy through multimodal screening, thereby facilitating timely intervention and treatment.

Application of deep learning classification model for regional evaluation of roof pressure support evolution effects over time in coal mining face.

Hydraulic support leg pressure serves as a crucial indicator for assessing work face support quality. Current evaluation methods for support quality primarily concentrate on static analyses-like inadequate initial support force, pressure overrun, and uneven bracket force-while neglecting dynamic column pressure changes. This paper introduces a model for assessing hydraulic support quality using deep learning techniques. Real-time data is preprocessed into a spatio-temporal pressure sub-matrix sample, which is then inputted into the model. This process assesses the support quality type and characterizes its dynamic evolution within the area. The model facilitates the identification of dynamic support quality effects in the working face area, aiding operators in making targeted adjustments to hydraulic support status. Experimental results revealed that the optimized LeNet-5 network-adjusting parameters like convolutional layer count, kernel size, and ReLU activation function-achieved the highest classification accuracy of 85.25 % for support quality, surpassed other networks. Furthermore, the improved LeNet-5 network outperformed other networks in both F1 score and recall. Additionally, the improved LeNet-5 network achieved faster convergence to the optimal solution, accelerated training speed. This highlighted its advantages in evaluating the spatio-temporal support quality of hydraulic supports in smart mining operations.

Benchmarking online food delivery applications against menu labelling laws: a cross-sectional observational analysis.

OBJECTIVE: It is unknown how well menu labelling schemes that enforce the display of kilojoule (kJ) labelling at point-of-sale have been implemented on online food delivery (OFD) services in Australia. This study aimed to examine the prevalence of kJ labelling on the online menus of large food outlets with more than twenty locations in the state or fifty locations nationally. A secondary aim was to evaluate the nutritional quality of menu items on OFD from mid-sized outlets that have fewer locations than what is specified in the current scheme. DESIGN: Cross-sectional analysis. Prevalence of kJ labelling by large food outlets on OFD from August to September 2022 was examined. Proportion of discretionary ('junk food') items on menus from mid-sized outlets was assessed. SETTING: Forty-three unique large food outlets on company (e.g. MyMacca's) and third party OFD (Uber Eats, Menulog, Deliveroo) within Sydney, Australia. Ninety-two mid-sized food outlets were analysed. PARTICIPANTS: N/A. RESULTS: On company OFD apps, 35 % (7/23) had complete kJ labelling for each menu item. In comparison, only 4·8 % (2/42), 5·3 % (2/38) and 3·6 % (1/28) of large outlets on Uber Eats, Menulog and Deliveroo had complete kJ labelling at all locations, respectively. Over three-quarters, 76·3 % (345/452) of menu items from mid-sized outlets were classified as discretionary. CONCLUSIONS: Kilojoule labelling was absent or incomplete on a high proportion of online menus. Mid-sized outlets have abundant discretionary choices and yet escape criteria for mandatory menu labelling laws. Our findings show the need to further monitor the implementation of nutrition policies on OFD.

Ben-JNK signaling is required for host mortality during Periplaneta fuliginosa densovirus infection.

BACKGROUND: Cockroaches are widely acknowledged as significant vectors of pathogenic microorganisms. The Periplaneta fuliginosa densovirus (PfDNV) infects the smoky-brown cockroach P. fuliginosa and causes host mortality, which identifies the PfDNV as a species-specific and environmentally friendly biopesticide. However, although the biochemical characterization of PfDNV has been extensively studied, the immune response against PfDNV remains largely unclear. RESULTS: Here, we investigated the replication of PfDNV and its associated pathological phenotype in the foregut and hindgut. Consequently, we dissected and performed transcriptome sequencing on the foregut, midgut, and hindgut separately. We revealed the up-regulation of immune response signaling pathway c-Jun N-terminal kinase (JNK) and apoptosis in response to viral infection. Furthermore, knockdown of the JNK upstream gene Ben resulted in a decrease in virus titer and delayed host mortality. CONCLUSION: Taken together, our findings provide evidence that the Ben-JNK signaling plays a crucial role in PfDNV infection, leading to excessive apoptosis in intestinal tissues and ultimately resulting in the death of the host. Our results indicated that the host response to PfDNV fosters viral infection, thereby increasing host lethality. This underscores the potential of PfDNV as a viable, environmentally friendly biopesticide. © 2024 Society of Chemical Industry.

Isolation, purification, and structural characterization of polysaccharides from Codonopsis pilosula and its therapeutic effects on non-alcoholic fatty liver disease in vitro and in vivo.

Codonopsis pilosula is a famous edible and medicinal plants, in which polysaccharides are recognized as one of the important active ingredients. A neutral polysaccharide (CPP-1) was purified from C. pilosula. The structure was characterized by HPSEC-MALLS-RID, UV, FT-IR, GC-MS, methylation analysis, and NMR. The results showed that CPP-1 was a homogeneous pure polysaccharide, mainly containing fructose and glucose, and a small amount of arabinose. Methylation analysis showed that CPP-1 composed of →1)-Fruf-(2→, Fruf-(1→ and Glcp-(1→ residues. Combined the NMR results the structure of CPP-1 was confirmed as α-D-Glcp-(1 â†’ [2)-ß-D-Fruf-(1 â†’ 2)-ß-D-Fruf-(1]26 â†’ 2)-ß-D-Fruf with the molecular weight of 4.890 × 103 Da. The model of AML12 hepatocyte fat damage was established in vitro. The results showed that CPP-1 could increase the activity of SOD and CAT antioxidant enzymes and reduce the content of MDA, thus protecting cells from oxidative damage. Subsequently, the liver protective effect of CPP-1 was studied in the mouse model of nonalcoholic fatty liver disease (NAFLD) induced by the high-fat diet. The results showed that CPP-1 significantly reduced the body weight, liver index, and body fat index of NAFLD mice, and significantly improved liver function. Therefore, CPP-1 should be a potential candidate for the treatment of NAFLD.

Use of online food retail platforms throughout the COVID-19 pandemic and associated diet-related chronic disease risk factors: A systematic review of emerging evidence.

Food accessibility was considerably impacted by restrictions during the coronavirus disease 2019 (COVID-19) pandemic, leading to growth in the online food retail sector, which offered contact-free delivery. This systematic review aimed to assess the change in use of online food retail platforms during COVID-19. The secondary aim was to identify diet-related chronic disease risk factors including dietary intake, eating behaviors, and/or weight status associated with the use of online food retail platforms during the pandemic. The review was registered in the International Prospective Register of Systematic Reviews (PROSPERO) (CRD42022320498) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Nine electronic databases were searched between January 2020 and October 2023. Studies that reported the frequency or change in use of online groceries, meal delivery applications, and/or meal-kit delivery services before and during the pandemic were included. A total of 53 studies were identified, including 46 cross-sectional studies, 4 qualitative studies, 2 longitudinal cohort studies, and 1 mixed-methods study. Overall, 96% (43/45) of outcomes showed an increase in the use of online groceries during COVID-19, while 55% (22/40) of outcomes showed a decrease in meal delivery applications. Eight of nine outcomes associated the use of online food retail with weight gain and emotional eating. Further research is needed to investigate the links between online food retail and obesity.

Automated graptolite identification at high taxonomic resolution using residual networks.

Graptolites, fossils significant for evolutionary studies and shale gas exploration, are traditionally identified visually by taxonomists due to their intricate morphologies and preservation challenges. Artificial intelligence (AI) holds great promise for transforming such meticulous tasks. In this paper, we demonstrate that graptolites can be identified with taxonomist accuracy using a deep learning model. We construct the most sophisticated and largest professional single organisms image dataset to date, which is composed of >34,000 images of 113 graptolite species annotated at pixel-level resolution to train the model, develop, and evaluate deep learning networks to classify graptolites. The model's performance surpassed taxonomists in accuracy, time, and generalization, achieving 86% and 81% accuracy in identifying graptolite genus and species, respectively. This AI-based method, capable of recognizing minute morphological details better than taxonomists, can be integrated into web and mobile apps, extending graptolite identification beyond research institutes and enhancing shale gas exploration efficiency.

In Situ Forming Gel Polymer Electrolyte for High Energy-Density Lithium Metal Batteries.

In situ forming gel polymer electrolyte (GPE) is one of the most feasible ways to improve the safety and cycle performances of lithium metal batteries with high energy density. However, most of the in situ formed GPEs are not compatible with high-voltage cathode materials. Here, this work provides a novel strategy to in situ form GPE based on the mechanism of Ritter reaction. The Ritter reaction in liquid electrolyte has the advantage of appropriate reaction temperature and no additional additives. The polymer chains are cross-linked by amide groups with the formation of GPE with superior electrochemical properties. The GPE has high ionic conductivity (1.84 mS cm-1 ), wide electrochemical stability window (>5.25 V) and high lithium ion transference number (≈0.78), compatible with high-voltage cathode materials. The Li|LiNi0.6 Co0.2 Mn0.2 O2 batteries with in situ formed GPE show excellent long-term cycle stability (93.4%, 300 cycles). The density functional theory calculation and X-ray photoelectron spectroscopy results verify that the amide and nitrile groups are beneficial for stabilizing cathode structure and promoting uniform Li deposition on Li anode. Furthermore, the in situ formed GPE exhibits excellent electrochemical performance in Graphite|LiMn2 O4 and Graphite|LiNi0.5 Co0.2 Mn0.3 O2 pouch batteries. This approach is adaptable to current battery technologies, which will be sure to promote the development of high energy-density lithium-ion batteries.

Siamese Unet Network for Waterline Detection and Barrier Shape Change Analysis from Long-Term and Large Numbers of Satellite Imagery.

Barrier islands are vital dynamic landforms that not only host ecological resources but often protect coastal ecosystems from storm damage. The Waisanding Barrier (WSDB) in Taiwan has suffered from continuous beach erosion in recent decades. In this study, we developed a SiamUnet network compared to three basic DeepUnet networks with different image sizes to effectively detect barrier waterlines from 207 high-resolution satellite images. The evolution of the barrier waterline shape is obtained to present two special morphologic changes at the southern end and the evolution of the entire waterline. The time periods of separation of the southern end from the main WSDB are determined and discussed. We also show that the southern L-shaped end has occurred recently from the end of 2017 until 2021. The length of the L-shaped end gradually decreases during the summer, but gradually increases during the winter. The L-shaped end obviously has a seasonal and jagged change. The attenuation rate of the land area is analyzed as -0.344 km2/year. We also explore two factors that affect the analysis results, which are the number of valid images selected and the deviation threshold from the mean sea level.

Optimization of Three Extraction Methods and Their Effect on the Structure and Antioxidant Activity of Polysaccharides in Dendrobium huoshanense.

Dendrobium huoshanense is a famous edible and medicinal herb, and polysaccharides are the main bioactive component in it. In this study, response surface methodology (RSM) combined with a Box-Behnken design (BBD) was used to optimize the enzyme-assisted extraction (EAE), ultrasound-microwave-assisted extraction (UMAE), and hot water extraction (HWE) conditions and obtain the polysaccharides named DHP-E, DHP-UM, and DHP-H. The effects of different extraction methods on the physicochemical properties, structure characteristics, and bioactivity of polysaccharides were compared. The differential thermogravimetric curves indicated that DHP-E showed a broader temperature range during thermal degradation compared with DHP-UM and DHP-H. The SEM results showed that DHP-E displayed an irregular granular structure, but DHP-UM and DHP-H were sponge-like. The results of absolute molecular weight indicated that polysaccharides with higher molecular weight detected in DHP-H and DHP-UM did not appear in DHP-E due to enzymatic degradation. The monosaccharide composition showed that DHPs were all composed of Man, Glc, and Gal but with different proportions. Finally, the glycosidic bond types, which have a significant effect on bioactivity, were decoded with methylation analysis. The results showed that DHPs contained four glycosidic bond types, including Glcp-(1→, →4)-Manp-(1→, →4)-Glcp-(1→, and →4,6)-Manp-(1→ with different ratios. Furthermore, DHP-E exhibited better DPPH and ABTS radical scavenging activities. These findings could provide scientific foundations for selecting appropriate extraction methods to obtain desired bioactivities for applications in the pharmaceutical and functional food industries.

Using Mobile Ecological Momentary Assessment to Understand Consumption and Context Around Online Food Delivery Use: Pilot Feasibility and Acceptability Study.

BACKGROUND: Mobile ecological momentary assessment (EMA) is a powerful tool for collecting real-time and contextual data from individuals. As our reliance on online technologies to increase convenience accelerates, the way we access food is changing. Online food delivery (OFD) services may further encourage unhealthy food consumption habits, given the high availability of energy-dense, nutrient-poor foods. We used EMA to understand the real-time effects of OFD on individuals' food choices and consumption behaviors. OBJECTIVE: The primary aims of this pilot study were to assess the feasibility and acceptability of using EMA in young users of OFD and compare 2 different EMA sampling methods. The secondary aims were to gather data on OFD events and their context and examine any correlations between demographics, lifestyle chronic disease risk factors, and OFD use. METHODS: This study used EMA methods via a mobile app (mEMASense, ilumivu Inc). Existing users of OFD services aged 16 to 35 years in Australia who had access to a smartphone were recruited. Participants were randomly assigned to 1 of 2 groups: signal-contingent or event-contingent. The signal-contingent group was monitored over 3 days between 7 AM and 10 PM. They received 5 prompts each day to complete EMA surveys via the smartphone app. In contrast, the event-contingent group was monitored over 7 days and was asked to self-report any instance of OFD. RESULTS: A total of 102 participants were analyzed, with 53 participants in the signal-contingent group and 49 participants in the event-contingent group. Compliance rates, indicating the feasibility of signal-contingent and event-contingent protocols, were similar at 72.5% (574/792) and 73.2% (251/343), respectively. Feedback from the participants suggested that the EMA app was not easy to use, which affected their acceptability of the study. Participants in the event-contingent group were 3.53 (95% CI 1.52-8.17) times more likely to have had an OFD event captured during the study. Pizza (23/124, 18.5%) and fried chicken (18/124, 14.5%) comprised a bulk of the 124 OFD orders captured. Most orders were placed at home (98/124, 79%) for 1 person (68/124, 54.8%). Age (incidence rate ratio 0.95, 95% CI 0.91-0.99; P=.03) and dependents (incidence rate ratio 2.01, 95% CI 1.16-3.49; P=.01) were significantly associated with the number of OFD events in a week after adjusting for gender, socioeconomic status, diet quality score, and perceived stress levels. CONCLUSIONS: This pilot study showed that EMA using an event-contingent sampling approach may be a better method to capture OFD events and context than signal-contingent sampling. The compliance rates showed that both sampling methods were feasible and acceptable. Although the findings from this study have gathered some insight on the consumption and context of OFD in young people, further studies are required to develop targeted interventions.

Prolonging dual antiplatelet therapy improves the long-term prognosis in patients with diabetes mellitus undergoing complex percutaneous coronary intervention.

OBJECTIVE: To investigate the optimal duration of dual antiplatelet therapy (DAPT) in patients with diabetes mellitus (DM) requiring complex percutaneous coronary intervention (PCI). METHODS: A total of 2403 patients with DM who underwent complex PCI from January to December 2013 were consecutively enrolled in this observational cohort study and divided according to DAPT duration into a standard group (11-13 months, n = 689) and two prolonged groups (13-24 months, n = 1133; > 24 months, n = 581). RESULTS: Baseline characteristics, angiographic findings, and complexity of PCI were comparable regardless of DAPT duration. The incidence of major adverse cardiac and cerebrovascular event was lower when DAPT was 13-24 months than when it was 11-13 months or > 24 months (4.6% vs. 8.1% vs. 6.0%, P = 0.008), as was the incidence of all-cause death (1.9% vs. 4.6% vs. 2.2%, P = 0.002) and cardiac death (1.0% vs. 3.0% vs. 1.2%, P = 0.002). After adjustment for confounders, DAPT for 13-24 months was associated with a lower risk of major adverse cardiac and cerebrovascular event [hazard ratio (HR) = 0.544, 95% CI: 0.373-0.795] and all-cause death (HR = 0.605, 95% CI: 0.387-0.944). DAPT for > 24 months was associated with a lower risk of all-cause death (HR = 0.681, 95% CI: 0.493-0.942) and cardiac death (HR = 0.620, 95% CI: 0.403-0.952). The risk of major bleeding was not increased by prolonging DAPT to 13-24 months (HR = 1.356, 95% CI: 0.766-2.401) or > 24 months (HR = 0.967, 95% CI: 0.682-1.371). CONCLUSIONS: For patients with DM undergoing complex PCI, prolonging DAPT might improve the long-term prognosis by reducing the risk of adverse ischemic events without increasing the bleeding risk.

The RNA polymerase II subunit B (RPB2) functions as a growth regulator in human glioblastoma.

Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor with a poor prognosis. The growth of GBM cells depends on the core transcriptional apparatus, thus rendering RNA polymerase (RNA pol) complex as a candidate therapeutic target. The RNA pol II subunit B (POLR2B) gene encodes the second largest subunit of the RNA pol II (RPB2); however, its genomic status and function in GBM remain unclear. Certain GBM data sets in cBioPortal were used for investigating the genomic status and expression of POLR2B in GBM. The function of RPB2 was analyzed following knockdown of POLR2B expression by shRNA in GBM cells. The cell counting kit-8 assay and PI staining were used for cell proliferation and cell cycle analysis. A xenograft mouse model was established to analyze the function of RPB2 in vivo. RNA sequencing was performed to analyze the RPB2-regulated genes. GO and GSEA analyses were applied to investigate the RPB2-regulated gene function and associated pathways. In the present study, the genomic alteration and overexpression of the POLR2B gene was described in glioblastoma. The data indicated that knockdown of POLR2B expression suppressed tumor cell growth of glioblastoma in vitro and in vivo. The analysis further demonstrated the identification of the RPB2-regulated gene sets and highlighted the DNA damage-inducible transcript 4 gene as the downstream target of the POLR2B gene. The present study provides evidence indicating that RPB2 functions as a growth regulator in glioblastoma and could be used as a potential therapeutic target for the treatment of this disease.

UDP-glucose sensing P2Y14R: A novel target for inflammation.

Uridine 5'-diphosphoglucose (UDP-G) as a preferential agonist, but also other UDP-sugars, such as UDP galactose, function as extracellular signaling molecules under conditions of cell injury and apoptosis. Consequently, UDP-G is regarded to function as a damage-associated molecular pattern (DAMP), regulating immune responses. UDP-G promotes neutrophil recruitment, leading to the release of pro-inflammatory chemokines. As a potent endogenous agonist with the highest affinity for the P2Y14 receptor (R), it accomplishes an exclusive relationship between P2Y14Rs in regulating inflammation via cyclic adenosine monophosphate (cAMP), nod-like receptor protein 3 (NLRP3) inflammasome, mitogen-activated protein kinases (MAPKs), and signal transducer and activator of transcription 1 (STAT1) pathways. In this review, we initially present a brief introduction into the expression and function of P2Y14Rs in combination with UDP-G. Subsequently, we summarize emerging roles of UDP-G/P2Y14R signaling pathways that modulate inflammatory responses in diverse systems, and discuss the underlying mechanisms of P2Y14R activation in inflammation-related diseases. Moreover, we also refer to the applications as well as effects of novel agonists/antagonists of P2Y14Rs in inflammatory conditions. In conclusion, due to the role of the P2Y14R in the immune system and inflammatory pathways, it may represent a novel target for anti-inflammatory therapy.

CD73: Friend or Foe in Lung Injury.

Ecto-5'-nucleotidase (CD73) plays a strategic role in calibrating the magnitude and chemical nature of purinergic signals that are delivered to immune cells. Its primary function is to convert extracellular ATP to adenosine in concert with ectonucleoside triphosphate diphosphohydrolase-1 (CD39) in normal tissues to limit an excessive immune response in many pathophysiological events, such as lung injury induced by a variety of contributing factors. Multiple lines of evidence suggest that the location of CD73, in proximity to adenosine receptor subtypes, indirectly determines its positive or negative effect in a variety of organs and tissues and that its action is affected by the transfer of nucleoside to subtype-specific adenosine receptors. Nonetheless, the bidirectional nature of CD73 as an emerging immune checkpoint in the pathogenesis of lung injury is still unknown. In this review, we explore the relationship between CD73 and the onset and progression of lung injury, highlighting the potential value of this molecule as a drug target for the treatment of pulmonary disease.

Association of variations in the CAT and prognosis in lung cancer patients with platinum-based chemotherapy.

PURPOSE: To explore the relationship between ATM, ATR and CAT polymorphisms and prognosis of lung cancer patients received platinum-based chemotherapy. METHODS: 404 patients with lung cancer who received platinum-chemotherapy were enrolled and DNA typing was performed. Cox regression analysis and stratification analyses was performed to assess relationships between OS and PFS with SNPs genotypes. The prognosis of lung adenocarcinomaand squamous cell carcinomapatients was analyzed with The Cancer Genome Atlas (TCGA) database according to the grouping of CAT expression. RESULTS: CAT rs769217 was significantly related to PFS of patients with lung cancer who received platinum-chemotherapy. In the Additive model, rs769217 was associated with PFS (HR = 0.747, 95% CI = 0.581-0.960, p = 0.023). In the Dominant model, CT and TT genotypes led to lung cancer progression 0.738 times more than CC genotype. In stratification analyses of association between CAT rs769217 polymorphisms and PFS, the HR of patients at stage IV in additive model was 0.73, and HR was 0.745 (p = 0.034) in dominant model. For OS analyses, HR was 0.672 in the older lung cancer patients (>55 years old) in additive model. Meanwhile, in the Dominant model, it was found that the older patients with CT and TT genotypes had better prognosis, and the risk of death after receiving platinum-based chemotherapy was 0.692 times that of patients with CC genotype (p = 0.037). TCGA data shows that LUAD patients with high CAT expression have longer OS (p = 0.020). CONCLUSION: CAT rs769217 is significantly related to PSF of platinum-based chemotherapy in lung cancer patients and may be a biomarker for predicting the prognosis of lung cancer patients with platinum-based chemotherapy.