Case Report: Bronchial artery embolization and chemoradiotherapy for central squamous cell lung carcinoma with rapid regression

BackgroundInterventional embolization is a common treatment for hemoptysis, one of the complications of lung cancer. However, there are no official guidelines for the use of this method in antitumor therapy.Case DescriptionHerein, we describe a case of a patient who was pathologically diagnosed as central squamous cell lung cancer. The patient received chemotherapy, interventional embolization and radiotherapy successively. The tumor regressed rapidly within 48 hours of receipt of interventional embolization. Furthermore, the tumor decreased by more than 50% in size within 7 days during radiotherapy. Unfortunately, the patient has since developed lymph node metastases and remains under treatment.ConclusionsThus, finding the suitable blood vessel embolized may be a suitable option to reduce the local tumor load and can be considered as antitumor therapy in combination with other treatments. The patient’s theoretical hypoxia state after interventional therapy still produced a good tumor regression after radiotherapy. However, so far, no related studies have reported the changes of tumor immune microenvironment in human body after intervention and radiotherapy

Distinct Biogeography of Different Fungal Guilds and Their Associations With Plant Species Richness in Forest Ecosystems

Plant pathogens are increasingly considered as important agents in promoting plant coexistence, while plant symbionts like ectomycorrhizal fungi (EMF) can facilitate plant dominance by helping conspecific individuals to defend against plant pathogens. However, we know little about their relationships with plants at large scales. Here, using soil fungal data collected from 28 forest reserves across China, we explored the latitudinal diversity gradients of overall fungi and different fungal functional guilds, including putative plant pathogens, EMF, and saprotrophic fungi. We further linked the spatial patterns of alpha diversities of putative plant pathogens and EMF to the variation of plant species richness. We found that the relationships between latitude and alpha diversities of putative plant pathogens and EMF were region-dependent with sharp diversity shifts around the mid-latitude (similar to 35 degrees N), which differed from the unimodal diversity distributions of the overall and saprotrophic fungi. The variations in the diversities of putative plant pathogens and EMF were largely explained by the spatial regions (south vs. north/subtropical zone vs. temperate zone). Additionally, the alpha diversities of these two fungal guilds exhibited opposing trends across latitude. EMF could alter the relationship between diversities of putative plant pathogens and plants in the south/subtropical region, but not vice versa. We also found that the ratio of their alpha diversities (EMF to putative plant pathogens) was negatively related to plant species richness across the spatial regions (north to south), and explained similar to 10% of the variation of plant species richness. Overall, our findings suggest that plant-microbe interactions not only shape the local plant diversity but also may have non-negligible contributions to the large-scale patterns of plant diversity in forest ecosystems.National Natural Science Foundation of China [31600403, 31800422, 41673111, U1501232, 41622106]; Natural Science Foundation of Guangdong Province, China [2016A030312003]; U.S. National Science Foundation MacroSystems Biology program [NSF EF-1065844]; Candidates at Sun Yat-Sen UniversityOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Identifying the substrate proteins of U-box E3s E4B and CHIP by orthogonal ubiquitin transfer

E3 ubiquitin (UB) ligases E4B and carboxyl terminus of Hsc70-interacting protein (CHIP) use a common U-box motif to transfer UB from E1 and E2 enzymes to their substrate proteins and regulate diverse cellular processes. To profile their ubiquitination targets in the cell, we used phage display to engineer E2-E4B and E2-CHIP pairs that were free of cross-reactivity with the native UB transfer cascades. We then used the engineered E2-E3 pairs to construct “orthogonal UB transfer (OUT)” cascades so that a mutant UB (xUB) could be exclusively used by the engineered E4B or CHIP to label their substrate proteins. Purification of xUB-conjugated proteins followed by proteomics analysis enabled the identification of hundreds of potential substrates of E4B and CHIP in human embryonic kidney 293 cells. Kinase MAPK3 (mitogen-activated protein kinase 3), methyltransferase PRMT1 (protein arginine N-methyltransferase 1), and phosphatase PPP3CA (protein phosphatase 3 catalytic subunit alpha) were identified as the shared substrates of the two E3s. Phosphatase PGAM5 (phosphoglycerate mutase 5) and deubiquitinase OTUB1 (ovarian tumor domain containing ubiquitin aldehyde binding protein 1) were confirmed as E4B substrates, and b-catenin and CDK4 (cyclin-dependent kinase 4) were confirmed as CHIP substrates. On the basis of the CHIP-CDK4 circuit identified by OUT, we revealed that CHIP signals CDK4 degradation in response to endoplasmic reticulum stress

Mining bone metastasis related key genes of prostate cancer from the STING pathway based on machine learning

BackgroundProstate cancer (PCa) is the second most prevalent malignant tumor in male, and bone metastasis occurs in about 70% of patients with advanced disease. The STING pathway, an innate immune signaling mechanism, has been shown to play a key role in tumorigenesis, metastasis, and cancerous bone pain. Hence, exploring regulatory mechanism of STING in PCa bone metastasis will bring novel opportunities for treating PCa bone metastasis.MethodsFirst, key genes were screened from STING-related genes (SRGs) based on random forest algorithm and their predictive performance was evaluated. Subsequently, a comprehensive analysis of key genes was performed to explore their roles in prostate carcinogenesis, metastasis and tumor immunity. Next, cellular experiments were performed to verify the role of RELA in proliferation and migration in PCa cells, meanwhile, based on immunohistochemistry, we verified the difference of RELA expression between PCa primary foci and bone metastasis. Finally, based on the key genes to construct an accurate and reliable nomogram, and mined targeting drugs of key genes.ResultsIn this study, three key genes for bone metastasis were mined from SRGs based on the random forest algorithm. Evaluation analysis showed that the key genes had excellent prediction performance, and it also showed that the key genes played a key role in carcinogenesis, metastasis and tumor immunity in PCa by comprehensive analysis. In addition, cellular experiments and immunohistochemistry confirmed that overexpression of RELA significantly inhibited the proliferation and migration of PCa cells, and RELA was significantly low-expression in bone metastasis. Finally, the constructed nomogram showed excellent predictive performance in Receiver Operating Characteristic (ROC, AUC = 0.99) curve, calibration curve, and Decision Curve Analysis (DCA) curve; and the targeted drugs showed good molecular docking effects.ConclusionIn sum, this study not only provides a new theoretical basis for the mechanism of PCa bone metastasis, but also provides novel therapeutic targets and novel diagnostic tools for advanced PCa treatment

Respiratory Virus Surveillance Among Children with Acute Respiratory Illnesses - New Vaccine Surveillance Network, United States, 2016-2021

The New Vaccine Surveillance Network (NVSN) is a prospective, active, population-based surveillance platform that enrolls children with acute respiratory illnesses (ARIs) at seven pediatric medical centers. ARIs are caused by respiratory viruses including influenza virus, respiratory syncytial virus (RSV), human metapneumovirus (HMPV), human parainfluenza viruses (HPIVs), and most recently SARS-CoV-2 (the virus that causes COVID-19), which result in morbidity among infants and young children (1-6). NVSN estimates the incidence of pathogen-specific pediatric ARIs and collects clinical data (e.g., underlying medical conditions and vaccination status) to assess risk factors for severe disease and calculate influenza and COVID-19 vaccine effectiveness. Current NVSN inpatient (i.e., hospital) surveillance began in 2015, expanded to emergency departments (EDs) in 2016, and to outpatient clinics in 2018. This report describes demographic characteristics of enrolled children who received care in these settings, and yearly circulation of influenza, RSV, HMPV, HPIV1-3, adenovirus, human rhinovirus and enterovirus (RV/EV),* and SARS-CoV-2 during December 2016-August 2021. Among 90,085 eligible infants, children, and adolescents (children) aged \u3c18 \u3eyear

Life Cycle Assessment of Concrete from Bauxite Residue in China

For tiden er miljøproblemet mye bekymret av samfunnet; og industrien har blitt avslørt som en stor bidragsyter av forskere. Selv om det er nyttig å lindre det med å "redusere" industriavfallet, vil det ikke være uendelig å "redusere". Siden mesteparten av "industriaktiviteten" skaper rester og trenger råmateriale samtidig, ser det teoretisk sett ut til at "gjenbruk av avfallet" har uendelige muligheter. Uansett hvilken rest som gjenbrukes på samme eller et annet felt, vil det være til fordel for miljøet ved å "utnytte industriavfall" og "redusere bruken av primærmateriale". Metallurgisk produksjon er ikke triviell i industrisektorene, og den kan ikke fjernes fra dagens menneskeliv. Siden både konstruksjon og "aluminiumsproduksjon" fortsatt er betydelige i Kina. I denne forskningen har vi tatt for oss å bruke "gjenbruk"-konseptet på fastlandet i Kina, via en casestudie om "bruk av bauksittresten til å produsere uorganisk bindemiddel for betong". Vi har undersøkt saken med ett spesifikt aluminaanlegg og brukt livssyklusvurderingen for å kvantifisere miljøpåvirkningen. Deretter har de dominerende "påvirkningskategoriene og bidragsyterne" blitt funnet ut for å støtte "beslutningstaking eller forbedringssøking". Videre har vi sammenlignet resultatene mellom en EU-sak og en kinesisk sak angående produksjon av "Bauxite Residue Concrete". I mellomtiden har 3 transportscenarier blitt analysert angående "betydningen av transport" i total innvirkning. Videre har vi forutsett mulige endringer i fremtiden, basert på regjeringens politikk og tidligere status. Ved siden av presentasjon av resultat og konklusjon er LCA-metoden introdusert. I mellomtiden ble usikkerheten diskutert, videre ble også "mulig tema for dypere forskning" angitt

A Fast Anti-Jamming Algorithm Based on Imitation Learning for WSN

Wireless sensor networks (WSNs), integral components underpinning the infrastructure of the internet of things (IoT), confront escalating threats originating from attempts at malicious jamming. Nevertheless, the limited nature of the hardware resources in distributed, low-cost WSNs, such as those for computing power and storage, poses a challenge when implementing complex and intelligent anti-jamming algorithms like deep reinforcement learning (DRL). Hence, in this paper a rapid anti-jamming method is proposed based on imitation learning in order to address this issue. First, on-network nodes obtain expert anti-jamming trajectories using heuristic algorithms, taking historical experiences into account. Second, an RNN neural network that can be used for anti-jamming decision making is trained by mimicking these expert trajectories. Finally, the late-access network nodes receive anti-jamming network parameters from the existing nodes, allowing them to obtain a policy network directly applicable to anti-jamming decision making and thus avoiding redundant learning. Experimental results demonstrate that, compared with traditional Q-learning and random frequency-hopping (RFH) algorithms, the imitation learning-based algorithm empowers late-access network nodes to swiftly acquire anti-jamming strategies that perform on par with expert strategies

Anti-Jamming Communication Using Imitation Learning

The communication reliability of wireless communication systems is threatened by malicious jammers. Aiming at the problem of reliable communication under malicious jamming, a large number of schemes have been proposed to mitigate the effects of malicious jamming by avoiding the blocking interference of jammers. However, the existing anti-jamming schemes, such as fixed strategy, Reinforcement learning (RL), and deep Q network (DQN) have limited use of historical data, and most of them only pay attention to the current state changes and cannot gain experience from historical samples. In view of this, this manuscript proposes anti-jamming communication using imitation learning. Specifically, this manuscript addresses the problem of anti-jamming decisions for wireless communication in scenarios with malicious jamming and proposes an algorithm that consists of three steps: First, the heuristic-based Expert Trajectory Generation Algorithm is proposed as the expert strategy, which enables us to obtain the expert trajectory from historical samples. The trajectory mentioned in this algorithm represents the sequence of actions undertaken by the expert in various situations. Then obtaining a user strategy by imitating the expert strategy using an imitation learning neural network. Finally, adopting a functional user strategy for efficient and sequential anti-jamming decisions. Simulation results indicate that the proposed method outperforms the RL-based anti-jamming method and DQN-based anti-jamming method regarding solving continuous-state spectrum anti-jamming problems without causing “curse of dimensionality” and providing greater robustness against channel fading and noise as well as when the jamming pattern changes

Impact of Geometrical Features on Solute Transport Behavior through Rough-Walled Rock Fractures

The solute transport in the fractured rock is dominated by a single fracture. The geometric characteristics of single rough-walled fractures considerably influence their solute transport behavior. According to the self-affinity of the rough fractures, the fractal model of single fractures is established based on the fractional Brownian motion and the successive random accumulation method. The Navier–Stokes equation and solute transport convective-dispersion equation are employed to analyze the effect of fractal dimension and standard deviation of aperture on the solute transport characteristics. The results show that the concentration front and streamline distribution are inhomogeneous, and the residence time distribution (RTD) curves have obvious tailing. For the larger fractal dimension and the standard deviation of aperture, the fracture surface becomes rougher, aperture distribution becomes more scattered, and the average flow velocity becomes slower. As a result, the average time of solute transport is a power function of the fractal dimension, while the time variance and the time skewness present a negative linear correlation with the fractal dimension. For the standard deviation of aperture, the average time exhibits a linearly decreasing trend, the time variance is increased by a power function, and the skewness is increased logarithmically

More attention with less working memory: The active inhibition of attended but outdated information

Attention has traditionally been regarded as a gateway to working memory, and almost all theoretical frameworks of attention and working memory assume that individuals always have a better memory for information that has received more attention. Here, we provide a series of counterintuitive demonstrations which show that paying more attention to a piece of information impedes, rather than enhances, the selection of this information into working memory. Experiments 1–5 provide converging evidence for an even weaker working memory trace of fully attended but outdated features, compared with baseline irrelevant features that were completely ignored. This indicates that the brain actively inhibits attended but outdated information to prevent it from entering working memory. Experiment 6 demonstrates that this inhibition processing is subject to executive control. These findings lead to a substantial reinterpretation of the relationship between attention and working memory