DeepSVDNet:A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images

Artificial Intelligence(AI)is being increasingly used for diagnosing Vision-Threatening Diabetic Retinopathy(VTDR),which is a leading cause of visual impairment and blindness worldwide.However,previous automated VTDR detection methods have mainly relied on manual feature extraction and classification,leading to errors.This paper proposes a novel VTDR detection and classification model that combines different models through majority voting.Our proposed methodology involves preprocessing,data augmentation,feature extraction,and classification stages.We use a hybrid convolutional neural network-singular value decomposition(CNN-SVD)model for feature extraction and selection and an improved SVM-RBF with a Decision Tree(DT)and K-Nearest Neighbor(KNN)for classification.We tested our model on the IDRiD dataset and achieved an accuracy of 98.06%,a sensitivity of 83.67%,and a specificity of 100%for DR detection and evaluation tests,respectively.Our proposed approach outperforms baseline techniques and provides a more robust and accurate method for VTDR detection.

Increasing Crop Quality and Yield with a Machine Learning-Based Crop Monitoring System

Farming is cultivating the soil,producing crops,and keeping livestock.The agricultural sector plays a crucial role in a country’s economic growth.This research proposes a two-stage machine learning framework for agriculture to improve efficiency and increase crop yield.In the first stage,machine learning algorithms generate data for extensive and far-flung agricultural areas and forecast crops.The recommended crops are based on various factors such as weather conditions,soil analysis,and the amount of fertilizers and pesticides required.In the second stage,a transfer learningbased model for plant seedlings,pests,and plant leaf disease datasets is used to detect weeds,pesticides,and diseases in the crop.The proposed model achieved an average accuracy of 95%,97%,and 98% in plant seedlings,pests,and plant leaf disease detection,respectively.The system can help farmers pinpoint the precise measures required at the right time to increase yields.

Mechanism and effects of extramedullary hematopoiesis on anti-tumor immunity

Cancer immunotherapy is a preferred strategy for boosting anti-tumor immunity to eliminate malignant cells and is considered a major breakthrough in the field of cancer treatment however,immunosuppressive cells in the tumor microenvironment(TME)pose a major obstacle to the efficacy of immunotherapy.Myeloid cells,such as tumor-a ssociated macrophages(TAMs)and myeloid-derived suppressor cells(MDSCs).

Subsequent strategies and underlying mechanism of acquired resistance to PD-1 axis inhibitors in advanced non-small cell lung cancer

To the Editor:With the widespread application of immune checkpoint inhibitors(ICIs)in clinical practice,acquired resistance(AR)to programmed death-1(PD-1)/programmed death ligand 1(PD-L1)axis inhibitors in advanced nonsmall cell lung cancer(NSCLC)develops and limits the durability of immunotherapy.AR is a clinical condition in which a patient initially responds to ICIs but relapses and progresses after a period of time.The rates of AR have not been routinely reported in lung cancer but typically range from 12.9%to 64%.[1]However,studies on subsequent management strategies and the mechanism of AR to PD-1/PD-L1 axis inhibitors in lung cancer are limited.The main exploratory strategies are immunotherapy rechallenge and the combination of ICIs with other therapies,including local therapy,chemotherapy,antiangiogenetic treatment,and cytotoxic T lymphocyte antigen 4(CTLA-4)inhibitors.[2]The purpose of this study was to characterize the clinical patterns of AR and compare different subsequent therapies and outcomes in NSCLC patients after AR to PD-1/PD-L1 inhibitors.Moreover,we explored the underlying mechanism of AR by analyzing the alterations in next-generation sequencing(NGS)data before and after AR.

The long rather than the short allele of 5-HTTLPR predisposes Han Chinese to anxiety and reduced connectivity between prefrontal cortex and amygdala

The short allele of the serotonin-transporter gene is associated with higher risk for anxiety and depression in Caucasians, but this association is still unclear in Asians. Here, we addressed this issue using behavioral and multi-modal MRI approaches in a large group of healthy Han Chinese participants （n = 233）. In contrast to findings in Caucasians, we found that long-allele （L） carriers had higher anxiety scores. In another group （n = 64） experiencing significant levels of depression or anxiety, the L-allele frequency was also significantly higher. In healthy participants, L-carriers had reduced functional and anatomical connectivity between the amygdala and prefrontal cortex （PFC）, which was correlated with anxiety or depression scores. Our findings demonstrated that in Chinese Han participants, in contrast to Caucasians, the L-allele confers vulnerability to anxiety or depression and weakens top-down emotional control between the PFC and amygdala. Therefore, ethnic background should be taken into account in gene-related studies and their potential clinical applications.

High-throughput single-сell sequencing in cancer research

With advances in sequencing and instrument technology,bioinformatics analysis is being applied to batches of massive cells at single-cell resolution.High-throughput single-cell sequencing can be utilized for multi-omics characterization of tumor cells,stromal cells or infiltrated immune cells to evaluate tumor progression,responses to environmental perturbations,heterogeneous composition of the tumor microenvironment,and complex intercellular interactions between these factors.Particularly,single-cell sequencing of T cell receptors,alone or in combination with single-cell RNA sequencing,is useful in the fields of tumor immunology and immunotherapy.Clinical insights obtained from single-cell analysis are critically important for exploring the biomarkers of disease progression or antitumor treatment,as well as for guiding precise clinical decision-making for patients with malignant tumors.In this review,we summarize the clinical applications of single-cell sequencing in the fields of tumor cell evolution,tumor immunology,and tumor immunotherapy.Additionally,we analyze the tumor cell response to antitumor treatment,heterogeneity of the tumor microenvironment,and response or resistance to immune checkpoint immunotherapy.The limitations of single-cell analysis in cancer research are also discussed.

A potential ethnic difference in the association between 5-HTTLPR polymorphisms and the brain default mode network

The serotonin-transporter-linked polymorphic region(5-HTTLPR)is associated with mood disorders.This association is thought to be due to amygdala hyperresponsiveness to negative emotional stimuli as a result of reduced frontal cortical control.In Caucasians,the short form is associated with this effect,but in Han Chinese we recently found that the long form is involved.Serotonin receptors have rich expression in default mode network(DMN)regions and the recent studies have found an association between the short form of the 5-HTTLPR and DMN functional connectivity(FC)in Caucasians.The present study has investigated whether there may also be anethnic difference in this influence of 5-HTTLPR on the DMN.We recruited 233 young Han Chinese subjects and calculated the resting-state default-network FC.Our study found that the L carriers had decreased FC in the bilateral medial prefrontal cortex,right parahippocampal gyrus,left middle temporal gyrus,and increased FC in left precuneus(Pcu)compared to SS.The PCC-Pcu FC in L carriers was significantly negatively correlated with the depression scores.Our findings,therefore,suggest that there is also a difference between Caucasian and Han Chinese subjects in the association between the different forms of the5-HTTLPR and DMN functional connectivity.

Authors' response to “Maternal age as a potential explanation of the role of the L allele of the serotonin transporter gene in anxiety and depression in Asians”

In the letter to the editor, Dr. Comings et al. proposed a potential explanation of our findings that the L allele rather than S allele of 5-HTTLPR was associated with higher anxiety levels and reduced amygdala-prefrontal cortex （PFC） connectivity in Han Chinese[1], which demonstrated an ＇allele reversal＇ in the genetics of the 5-HTTLPR gene in Asians versus Caucasians. The authors alleged that this ＇allele reversal＇ might simply result from maternal age and suggested that we test this on our datasets. Unfortunately,