Prolonged intermittent theta burst stimulation restores the balance between A_(2A)R-and A_(1)R-mediated adenosine signaling in the 6-hydroxidopamine model of Parkinson's disease

An imbalance in adenosine-mediated signaling,particularly the increased A_(2A)R-mediated signaling,plays a role in the pathogenesis of Parkinson's disease.Existing therapeutic approaches fail to alter disease progression,demonstrating the need for novel approaches in PD.Repetitive transcranial magnetic stimulation is a non-invasive approach that has been shown to improve motor and non-motor symptoms of Parkinson's disease.However,the underlying mechanisms of the beneficial effects of repetitive transcranial magnetic stimulation remain unknown.The purpose of this study is to investigate the extent to which the beneficial effects of prolonged intermittent theta burst stimulation in the 6-hydroxydopamine model of experimental parkinsonism are based on modulation of adenosine-mediated signaling.Animals with unilateral 6-hydroxydopamine lesions underwent intermittent theta burst stimulation for 3 weeks and were tested for motor skills using the Rotarod test.Immunoblot,quantitative reverse transcription polymerase chain reaction,immunohistochemistry,and biochemical analysis of components of adenosine-mediated signaling were performed on the synaptosomal fraction of the lesioned caudate putamen.Prolonged intermittent theta burst stimulation improved motor symptoms in 6-hydroxydopamine-lesioned animals.A 6-hydroxydopamine lesion resulted in progressive loss of dopaminergic neurons in the caudate putamen.Treatment with intermittent theta burst stimulation began 7 days after the lesion,coinciding with the onset of motor symptoms.After treatment with prolonged intermittent theta burst stimulation,complete motor recovery was observed.This improvement was accompanied by downregulation of the e N/CD73-A_(2A)R pathway and a return to physiological levels of A_(1)R-adenosine deaminase 1 after 3 weeks of intermittent theta burst stimulation.Our results demonstrated that 6-hydroxydopamine-induced degeneration reduced the expression of A_(1)R and elevated the expression of A_(2A)R.Intermittent theta burst stimulation reversed these effects by restoring the abundances of A_(1)R and A_(2A)R to control levels.The shift in ARs expression likely restored the balance between dopamine-adenosine signaling,ultimately leading to the recovery of motor control.

Comparative Study of Radiological Changes in Hands and Feet in Patients Suffering from Early Rheumatoid Arthritis by Power Doppler Ultrasound and Direct Digital Radiography

Rheumatoid arthritis is a chronic multisystem disease of unknown cause. The characteristic feature of RA is persistent inflammatory synovitis. The natural history of disease is such that the early months of the disease are critical period during which reversible joint damage occurs. So early diagnosis of RA and appropriate drug application is the only way to save a patient from this crippling disease. In India, the cost of investigations is a significant factor for most of the patients. Ultrasonography or Power Doppler Ultra Sound (PDUS) has the advantage of being economic in spite of its sensitivity in assessing both inflammatory and destructive changes. The aim of the present study was to evaluate the diagnostic efficiency of PDUS in early rheumatoid arthritis. The study was performed with the patients attending Rheumatology Clinic. A total number of 106 patients of clinically suspected rheumatoid arthritis were studied as per selection criteria. Radiological examinations of hands were done by digital radiography and PDUS in a group of 53 patients, assessment of foot changes by PDUS and Digital Radiography were done in another similar group of 53 patients. Final diagnosis by ACR EULAR-2010 criteria is done for all the patients. The comparative study reveals that synovial vascularity as demonstrated by PDUS is much more effective in diagnosing early rheumatoid arthritis, both in hand and in feet than digital radiograph. PDUS of feet may yield earlier and better findings than hands, which is conventionally used in patients suffering from early rheumatoid arthritis.

An Analysis of Liberia’s Vulnerability to Climate Change in the Context of Least Developed Countries (LDCs): A Review

Climate change is an alarming global challenge, particularly affecting the least developed countries (LDCs) including Liberia. These countries, located in regions prone to unpredictable temperature and precipitation changes, are facing significant challenges, particularly in climate-sensitive sectors such as mining and agriculture. LDCs need more resilience to adverse climate shocks but have limited capacity for adaptation compared to other developed and developing nations. This paper examines Liberia’s susceptibility to climate change as a least developed country, focusing on its exposure, sensitivity, and adaptive capacity. It provides an overview of LDCs and outlines the global distribution of carbon dioxide emissions. The paper also evaluates specific challenges that amplify Liberia’s vulnerability and constrain sustainable adaptation, providing insight into climate change’s existing and potential effects. The paper emphasizes the urgency of addressing climate impacts on Liberia and calls for concerted local and international efforts for effective and sustainable mitigation efforts. It provides recommendations for policy decisions and calls for further research on climate change mitigation and adaptation.

Development and identification of two novel wheat-rye 6R derivative lines with adult-plant resistance to powdery mildew and high-yielding potential

Powdery mildew,caused by Blumeria graminis f.sp.tritici(Bgt),is a devastating disease that seriously threatens wheat yield and quality.To control this disease,host resistance is the most effective measure.Compared with the resistance genes from common wheat,alien resistance genes can better withstand infection of this highly variable pathogen.Development of elite alien germplasm resources with powdery mildew resistance and other key breeding traits is an attractive strategy in wheat breeding.In this study,three wheat-rye germplasm lines YT4-1,YT4-2,and YT4-3 were developed through hybridization between octoploid triticale and common wheat,out of which the lines YT4-1 and YT4-2 conferred adult-plant resistance(APR)to powdery mildew while the line YT4-3 was susceptible to powdery mildew during all of its growth stages.Using genomic in situ hybridization,multi-color fluorescence in situ hybridization,multi-color GISH,and molecular marker analysis,YT4-1,YT4-2,and YT4-3 were shown to be cytogenetically stable wheat-rye 6R addition and T1RS.1BL translocation line,6RL ditelosomic addition and T1RS.1BL translocation line,and T1RS.1BL translocation line,respectively.Compared with previously reported wheat-rye derivative lines carrying chromosome 6R,YT4-1 and YT4-2 showed stable APR without undesirable pleiotropic effects on agronomic traits.Therefore,these novel wheat-rye 6R derivative lines are expected to be promising bridge resources in wheat disease breeding.

A bibliometric analysis using machine learning to track paradigm shifts and analytical advances in forest ecology and forestry journal publications from 2010 to 2022

Forest habitats are critical for biodiversity,ecosystem services,human livelihoods,and well-being.Capacity to conduct theoretical and applied forest ecology research addressing direct(e.g.,deforestation)and indirect(e.g.,climate change)anthropogenic pressures has benefited considerably from new field-and statistical-techniques.We used machine learning and bibliometric structural topic modelling to identify 20 latent topics comprising four principal fields from a corpus of 16,952 forest ecology/forestry articles published in eight ecology and five forestry journals between 2010 and 2022.Articles published per year increased from 820 in 2010 to 2,354 in 2021,shifting toward more applied topics.Publications from China and some countries in North America and Europe dominated,with relatively fewer articles from some countries in West and Central Africa and West Asia,despite globally important forest resources.Most study sites were in some countries in North America,Central Asia,and South America,and Australia.Articles utilizing R statistical software predominated,increasing from 29.5%in 2010 to 71.4%in 2022.The most frequently used packages included lme4,vegan,nlme,MuMIn,ggplot2,car,MASS,mgcv,multcomp and raster.R was more often used in forest ecology than applied forestry articles.R software offers advantages in script and workflow-sharing compared to other statistical packages.Our findings demonstrate that the disciplines of forest ecology/forestry are expanding both in number and scope,aided by more sophisticated statistical tools,to tackle the challenges of redressing forest habitat loss and the socio-economic impacts of deforestation.

A Biogas Production Model from the Combination of Pig Manure and Cow Dung in N’Zérékoré City, Republic of Guine

This present research work focuses on the valorization of pig droppings for production of biogas in mono digestion and co-digestion with proportions of cow dung from the urban commune of N’Zérékoré. It was carried out in December 2020 in the Physics laboratory of the University of N’Zérékoré. The anaerobic digestion process took 25 days in an almost constant ambient temperature of 25˚C. Five digesters were loaded on 12/06/2020, two of which with 1 kg of pig dung and 1 kg of cow dung both in mono-digestion. The 3 other digesters in co-digestion with different proportions of pig manure and cow dung. The substrate in each digester is diluted in 2 liters of water, with a proportion of (1/2). The main results obtained are: 1) the evolution of the temperature and pH during digestion process, 2) the average biogas productions 0.61 liters for (D1);1.20 liter for (D2);1.65 liter for (D3);1.51 liter for (D4) and 1.31 liter for (D5). The cumulative amounts of biogas are respectively: D1 (7.95 liters), D2 (15.60 liters), D3 (21.50 liters), D4 (19.65 liters) and D5 (17.05 liters). The total cumulative production is 81.75 liters at the end of the process. The originality of this research work is that the proposed model examines the relation between the daily biogas production and the variation of temperature, pH and pressure. The combustibility test showed the biogas produced during the first week was no combustible (contains less than 50% methane). Combustion started from the biogas produced from the 15th day and it is from the 20th day that a significant amount of stable yellow/blue flame was observed. The results of this study show the combination of pig manure and cow dung presents advantages for optimal biogas production.

Radiography Image Classification Using Deep Convolutional Neural Networks

Research has shown that chest radiography images of patients with different diseases, such as pneumonia, COVID-19, SARS, pneumothorax, etc., all exhibit some form of abnormality. Several deep learning techniques can be used to identify each of these anomalies in the chest x-ray images. Convolutional neural networks (CNNs) have shown great success in the fields of image recognition and image classification since there are numerous large-scale annotated image datasets available. The classification of medical images, particularly radiographic images, remains one of the biggest hurdles in medical diagnosis because of the restricted availability of annotated medical images. However, such difficulty can be solved by utilizing several deep learning strategies, including data augmentation and transfer learning. The aim was to build a model that would detect abnormalities in chest x-ray images with the highest probability. To do that, different models were built with different features. While making a CNN model, one of the main tasks is to tune the model by changing the hyperparameters and layers so that the model gives out good training and testing results. In our case, three different models were built, and finally, the last one gave out the best-predicted results. From that last model, we got 98% training accuracy, 84% validation, and 81% testing accuracy. The reason behind the final model giving out the best evaluation scores is that it was a well-fitted model. There was no overfitting or underfitting issues. Our aim with this project was to make a tool using the CNN model in R language, which will help detect abnormalities in radiography images. The tool will be able to detect diseases such as Pneumonia, Covid-19, Effusions, Infiltration, Pneumothorax, and others. Because of its high accuracy, this research chose to use supervised multi-class classification techniques as well as Convolutional Neural Networks (CNNs) to classify different chest x-ray images. CNNs are extremely efficient and successful at reducing the number of parameters while maintaining the quality of the primary model. CNNs are also trained to recognize the edges of various objects in any batch of images. CNNs automatically discover the relevant aspects in labeled data and learn the distinguishing features for each class by themselves.

Rational and Continuous Measurement of the Emotional Decision Making in Visual Recognition of Facial Emotional Expressions with M.A.R.I.E.: First Half

Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.

Rational and Continuous Measurement of Emotional-Fingerprint, Emotional-Quotient and Categorical vs Proportional Recognition of Facial Emotions with M.A.R.I.E., Second Half

Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.

Detection of ocean internal waves based on Faster R-CNN in SAR images

Ocean internal waves appear as irregular bright and dark stripes on synthetic aperture radar(SAR)remote sensing images.Ocean internal waves detection in SAR images consequently constituted a difficult and popular research topic.In this paper,ocean internal waves are detected in SAR images by employing the faster regions with convolutional neural network features(Faster R-CNN)framework;for this purpose,888 internal wave samples are utilized to train the convolutional network and identify internal waves.The experimental results demonstrate a 94.78%recognition rate for internal waves,and the average detection speed is 0.22 s/image.In addition,the detection results of internal wave samples under different conditions are analyzed.This paper lays a foundation for detecting ocean internal waves using convolutional neural networks.

利用CRISPR/Cas9构建敲除小鼠模型研究PPP2R3A基因对心脏功能的影响

目的 应用CRISPR/Cas9技术构建蛋白磷酸2调节亚基B″家族α亚型(PPP2R3A)基因敲除小鼠,从分子水平及组织水平上研究PPP2R3A缺失对心脏的影响。方法 将Cas9 mRNA和两个靶向PPP2R3A第3外显子翻译起始密码子附近区域的单导向RNA微注射到C57BL/6小鼠受精卵中。小鼠出生后取其基因组DNA进行聚合酶链反应(PCR)和测序以鉴定基因型,鉴定后,基因PPP2R3A缺失型小鼠为KO组,野生型C57BL/6小鼠为WT组(雄性3只,雌性2只)。小鼠心脏组织经甲醛固定并制成切片后分别进行苏木素-伊红(HE)染色和免疫组织化学染色。提取小鼠心脏组织总RNA和蛋白,应用荧光定量PCR和Western印迹验证基因敲除小鼠的有效性和检测互作蛋白表达。结果 获得F1代PPP2R3A杂合小鼠,PCR和测序结果表明突变小鼠的基因型存在113 bp的缺失突变。与WT组相比,KO组心脏组织中PPP2R3A mRNA和蛋白表达量明显下降(均P<0.05),参与心脏发育的G蛋白信号转导调控因子(RGS)19表达量明显升高(P<0.05)。PPP2R3A蛋白表达受损引起了心脏组织病理学变化。结论 PPP2R3A在体内可能通过与RGS19蛋白互作来参与心脏的发育并对心脏功能产生影响。

Black Hole Complementarity in Terms of the Outsider and Insider Perspectives

A complementarity hypothesis concerning outsider and insider perspectives of a gargantuan black hole is proposed. The two thought experiments presented herein are followed by a brief discussion of a new interpretation of black hole interior “space-and-time-reversal”. Specifically, it is proposed that the “singularity” space of the black hole interior is time-like and the expansion time of the black hole interior is space-like. The resemblance of this new insider interpretation to our own expanding and redshifting big bang universe is compelling.

Role of miR-124 in the regulation of retinoic acid-induced Neuro-2A cell differentiation

Retinoic acid can cause many types of cells,including mouse neuroblastoma Neuro-2 A cells,to differentiate into neurons.However,it is still unknown whether microRNAs(miRNAs)play a role in this neuronal differentiation.To address this issue,real-time polymerase chain reaction assays were used to detect the expression of several differentiation-related miRNAs during the differentiation of retinoic acid-treated Neuro-2 A cells.The results revealed that miR-124 and miR-9 were upregulated,while miR-125 b was downregulated in retinoic acid-treated Neuro-2 A cells.To identify the miRNA that may play a key role,miR-124 expression was regulated by transfection of miRNA mimics or inhibitors.Morphological analysis results showed that inhibition of miR-124 expression reversed the effects of retinoic acid on neurite outgrowth.Moreover,miR-124 overexpression alone caused Neuro-2 A cells to differentiate into neurons,and its inhibitor could block this effect.These results suggest that miR-124 plays an important role in retinoic acid-induced differentiation of Neuro-2 A cells.

Remodeling tumor microenvironment using pH-sensitive biomimetic co-delivery of TRAIL/R848 liposomes against colorectal cancer

Background:Despite significant advancements in the development of anticancer therapies over the past few decades,the clinical management of colorectal cancer remains a challenging task.This study aims to investigate the inhibitory effects of cancer-targeting liposomes against colorectal cancer.Materials and Methods:Liposomes consisting of 3β-[N-(N′,N′-dimethylamino ethane)carbamoyl]-cholesterol(DC-CHOL),cholesterol(CHOL),and dioleoylphosphatidylethanolamine(DOPE)at a molar ratio of 1:1:0.5 were created and used as carriers to deliver an apoptosis-inducing plasmid encoding the tumor necrosis factor-related apoptosis-inducing ligand(pTRAIL)gene,along with the toll-like receptor(TLR7)agonist Rsiquimod(R848).The rationale behind this design is that pTRAIL can trigger cancer cell apoptosis by activating the DR4/5 receptor,while R848 can stimulate the immune microenvironment.Results:Experimental results demonstrated the synergistic effects of R848 and pTRAIL encapsulated by liposomes(RTL)in suppressing the proliferation of colorectal cancer cells.Moreover,further in vivo investigations revealed the strong anti-tumor efficacy of RTL in xenograft and orthotropic in situ models of colorectal cancer.Conclusions:These findings collectively highlight the therapeutic potential of R848/pTRAIL-loaded liposomes in the treatment of colorectal cancer.

Knockdown of RCN1 contributes to the apoptosis of colorectal cancer via regulating IP3R1

Background:The incidence of colorectal cancer(CRC)has been increasing in recent years.Thus,the discovery of factors that can assist in alleviating CRC is urgently warranted.Methods:To identify a potential factor involved in the development of CRC,we screened the upregulated genes in tumor tissues through four datasets from an online database.The expression of reticulocalbin 1(RCN1),a Ca2+-binding protein,was upregulated in the four datasets.Based on loss-offunction experiments,the effect of RCN1 on cell viability was assessed by Cell Counting Kit-8(CCK-8)assay.The regulatory effect of RCN1 on apoptosis was evaluated through Annexin V-fluorescein 5-isothiocyanate(FITC)/propidium iodide(PI)staining assay and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling(TUNEL)assay in RKO and SW480 cells.Activation of endoplasmic reticulum(ER)stress signaling pathways was confirmed by estimating the phosphorylation and expression of PRKR-like ER kinase(PERK),inositol-requiring kinase-1(IRE1),transcription factor 6(ACT6),and CCAAT/enhancer-binding protein-homologous protein(CHOP).The intracellular Ca2+homeostasis regulated by RCN1 was determined through the detection of Ca2+concentration and mitochondrial membrane potential(MMP)measurement.Moreover,whether inositol 1,4,5-trisphosphate receptor type 1(IP3R1)was involved in the regulation of RCN1 in CRC was verified through the depletion of IP3R1 in RKO cells.Results:Knockdown of RCN1 reduced cell viability and facilitated apoptosis in RKO and SW480 cells.Phosphorylation of PERK and IRE1,activation of ATF6,and upregulation of CHOP were induced by the absence of RCN1,suggesting that the unfolded protein response(UPR)was activated in CRC cells.The concentration of Ca2+in mitochondria was increased after RCN1 depletion,followed by reduction in the MMP and release of cytochrome c from mitochondria to the cytoplasm in RKO and SW480 cells.Moreover,it was demonstrated that IP3R1 mediates the effect of RCN1 on apoptosis induced by ER stress in CRC cells.The downregulation of IP3R1 restored the RCN1 loss-induced apoptosis and the increased Ca2+concentration.Conclusion:Taken together,our results confirmed that silencing of RCN1 disrupted intracellular Ca2+homeostasis and promoted cell apoptosis caused by TG-induced ER stress by regulating IP3R1 and activating the UPR signaling pathways.

PPP1R14A is Associated with Immunotherapy Resistance in Head and Neck Squamous Cell Carcinoma Identified by Single-Cell and Bulk RNA-Sequencing

Objective To identify nivolumab resistance-related genes in patients with head and neck squamous cell carcinoma(HNSCC)using single-cell and bulk RNA-sequencing data.Methods The single-cell and bulk RNA-sequencing data downloaded from the Gene Expression Omnibus database were analyzed to screen out differentially expressed genes(DEGs)between nivolumab resistant and nivolumab sensitive patients using R software.The Least Absolute Shrinkage Selection Operator(LASSO)regression and Recursive Feature Elimination(RFE)algorithm were performed to identify key genes associated with nivolumab resistance.Functional enrichment of DEGs was analyzed with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses.The relationships of key genes with immune cell infiltration,differentation trajectory,dynamic gene expression profiles,and ligand-receptor interaction were explored.Results We found 83 DEGs.They were mainly enriched in T-cell differentiation,PD-1 and PD-L1 checkpoint,and T-cell receptor pathways.Among six key genes identified using machine learning algorithms,only PPP1R14A gene was differentially expressed between the nivolumab resistant and nivolumab sensitive groups both before and after immunotherapy(P<0.05).The high PPP1R14A gene expression group had lower immune score(P<0.01),higher expression of immunosuppressive factors(such as PDCD1,CTLA4,and PDCD1LG2)(r>0,P<0.05),lower differentiation of infiltrated immune cells(P<0.05),and a higher degree of interaction between HLA and CD4(P<0.05).Conclusions PPP1R14A gene is closely associated with resistance to nivolumab in HNSCC patients.Therefore,PPP1R14A may be a target to ameliorate nivolumab resistance of HNSCC patients.

Insulin-like growth factor 2 targets IGF1R signaling transduction to facilitate metastasis and imatinib resistance in gastrointestinal stromal tumors

BACKGROUND Gastrointestinal stromal tumors(GISTs)are typical gastrointestinal tract neoplasms.Imatinib is the first-line therapy for GIST patients.Drug resistance limits the long-term effectiveness of imatinib.The regulatory effect of insulin-like growth factor 2(IGF2)has been confirmed in various cancers and is related to resistance to chemotherapy and a worse prognosis.AIM To further investigate the mechanism of IGF2 specific to GISTs.METHODS IGF2 was screened and analyzed using Gene Expression Omnibus(GEO:GSE225819)data.After IGF2 knockdown or overexpression by transfection,the phenotypes(proliferation,migration,invasion,apoptosis)of GIST cells were characterized by cell counting kit 8,Transwell,and flow cytometry assays.We used western blotting to evaluate pathway-associated and epithelial-mesenchymal transition(EMT)-associated proteins.We injected transfected cells into nude mice to establish a tumor xenograft model and observed the occurrence and metastasis of GIST.RESULTS Data from the GEO indicated that IGF2 expression is high in GISTs,associated with liver metastasis,and closely related to drug resistance.GIST cells with high expression of IGF2 had increased proliferation and migration,invasiveness and EMT.Knockdown of IGF2 significantly inhibited those activities.In addition,OEIGF2 promoted GIST metastasis in vivo in nude mice.IGF2 activated IGF1R signaling in GIST cells,and IGF2/IGF1R-mediated glycolysis was required for GIST with liver metastasis.GIST cells with IGF2 knockdown were sensitive to imatinib treatment when IGF2 overexpression significantly raised imatinib resistance.Moreover,2-deoxy-D-glucose(a glycolysis inhibitor)treatment reversed IGF2 overexpressionmediated imatinib resistance in GISTs.CONCLUSION IGF2 targeting of IGF1R signaling inhibited metastasis and decreased imatinib resistance by driving glycolysis in GISTs.

基于改进Faster R-CNN的隧道衬砌中离散实体目标自动检测研究

隧道衬砌中离散实体目标的检测精度和时效性直接关乎隧道的运营安全,采用图像视觉技术进行图像自动解译可极大提升检测效率和结果的准确性,因此基于离散实体目标的雷达图像数据构建自定义雷达数据集合,并提出一套改进的Faster R-CNN算法对隧道衬砌中的离散实体目标进行自动检测。该算法首先对现有Faster R-CNN网络的特征提取模块进行改进,提出一套全新的轻量化特征提取网络ResNet_FMBConv对雷达图像特征进行深度挖掘;基于ResNet_FMBConv网络改进现有特征金字塔(FPN)结构,实现对多尺寸下目标的精准辨识。其次,基于实测和仿真的雷达图像数据构建离散实体目标的自定义雷达数据集合,通过几何变换方法对雷达图像进行数据增强后用于算法验证。结果表明,改进算法在IOU=0.50∶0.95情况下的检测精确率、召回率、F 1分数和FPS分别为45.1%、54.0%、49.1%和21.65 fps。在保证召回率基本持平的情况下,同比YOLOv3_spp、SSD、Retinanet和Faster R-CNN等目标检测算法的精确率和F 1分数分别提升2%~9%和1%~6%。同时,试验结果表明改进后的特征提取网络ResNet_FMBConv也优于现有Resnet-50、VGG16、Efficientnet_b0和Mobilenetv3等目标分类网络。

Ghrelin regulates insulin resistance by targeting insulin-like growth factor-1 receptor via miR-455-5p in hepatic cells

Objective: To explore the mechanism by which ghrelin regulates insulin sensitivity through modulation of miR-455-5p in hepatic cells. Methods: HepG2 cells were treated with or without DAG (1 μM). Glucose consumption, intracellular glycogen content, phosphorylation of PI3K and Akt stimulated by insulin, expression of miR-455-5p, as well as IGF-1R protein level were analyzed. In addition, bioinformatic analysis, dual luciferase reporter assay, miR- 455-5p mimic or inhibitor treatment was conducted to investigate the molecular mechanisms. Results: High glucose treatment upregulated miR-455-5p expression but reduced glucose consumption and glycogen content. DAG reversed the effect of high glucose on glucose metabolism, increased protein level of IGF-1R and phosphorylation of PI3K/Akt stimulated by insulin, as well as downregulated miR-455-5p expression. Bioinformatic analysis indicated IGF-1R was the target of miR-455-5p. Dual luciferase reporter assay, as well as transfection with miR-455-5p mimic/inhibitor confirmed that DAG activated IGF-1R/PI3K/Akt signaling via inhibiting miR-455-5p. Conclusion: DAG improves insulin resistance via miR-455-5p- mediated activation of IGF-1R/PI3K/Akt system, suggesting that suppression of miR-455-5p or activation of DAG may be potential targets for T2DM therapy.

Thin Layer Identification of Jiedu Shengxue Granules and Determination of Notoginsenoside R1 Content

[Objectives]To establish the quality standard of hospital preparation Jiedu Shengxue granules.[Methods]Scleromitrion diffusum and Prunella vulgaris in Jiedu Shengxue granules were qualitatively identified by thin layer chromatography(TLC).A high performance liquid chromatography(HPLC)was established to determine the content of notoginsenoside R1 in the granule.[Results]The traditional Chinese medicinal materials in Jiedu Shengxue granules could be identified by TLC,and the characteristic spots were stable and clear.Notoginsenoside R1 had a good linear relationship in the range of 10.45-104.5μg/mL,with an average recovery of 98.52%and RSD=2.36%.[Conclusions]TLC and HPLC,as the quality control methods of Jiedu Shengxue granules,have high accuracy and good repeatability,which lays a foundation for the quality control of this mixture.