Clinical application of ctDNA in early diagnosis, treatment and prognosis of patients with non-small cell lung cancer.

Lung cancer is one of the most common malignancies worldwide, with non-small cell lung cancer (NSCLC) being the most common type. As understanding of precise treatment options for NSCLC deepens, circulating tumor DNA (ctDNA) has emerged as a potential biomarker that has become a research hotspot and may represent a new approach for the individualized diagnosis and treatment of NSCLC. This article reviews the applications of ctDNA for the early screening of patients with NSCLC, guiding targeted therapy and immunotherapy, evaluating chemotherapy and postoperative efficacy, assessing prognosis and monitoring recurrence. With the in-depth study of the pathogenesis of NSCLC, plasma ctDNA may become an indispensable part of the precise treatment of NSCLC, which has great clinical application prospects.

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Application of visual transformer in renal image analysis.

Deep Self-Attention Network (Transformer) is an encoder-decoder architectural model that excels in establishing long-distance dependencies and is first applied in natural language processing. Due to its complementary nature with the inductive bias of convolutional neural network (CNN), Transformer has been gradually applied to medical image processing, including kidney image processing. It has become a hot research topic in recent years. To further explore new ideas and directions in the field of renal image processing, this paper outlines the characteristics of the Transformer network model and summarizes the application of the Transformer-based model in renal image segmentation, classification, detection, electronic medical records, and decision-making systems, and compared with CNN-based renal image processing algorithm, analyzing the advantages and disadvantages of this technique in renal image processing. In addition, this paper gives an outlook on the development trend of Transformer in renal image processing, which provides a valuable reference for a lot of renal image analysis.

Intelligent prediction of Alzheimer's disease via improved multifeature squeeze-and-excitation-dilated residual network.

This study aimed to address the issue of larger prediction errors existing in intelligent predictive tasks related to Alzheimer's disease (AD). A cohort of 487 enrolled participants was categorized into three groups: normal control (138 individuals), mild cognitive impairment (238 patients), and AD (111 patients) in this study. An improved multifeature squeeze-and-excitation-dilated residual network (MFSE-DRN) was proposed for two important AD predictions: clinical scores and conversion probability. The model was characterized as three modules: squeeze-and-excitation-dilated residual block (SE-DRB), multifusion pooling (MF-Pool), and multimodal feature fusion. To assess its performance, the proposed model was compared with two other novel models: ranking convolutional neural network (RCNN) and 3D vision geometrical group network (3D-VGGNet). Our method showed the best performance in the two AD predicted tasks. For the clinical scores prediction, the root-mean-square errors (RMSEs) and mean absolute errors (MAEs) of mini-mental state examination (MMSE) and AD assessment scale-cognitive 11-item (ADAS-11) were 1.97, 1.46 and 4.20, 3.19 within 6 months; 2.48, 1.69 and 4.81, 3.44 within 12 months; 2.67, 1.86 and 5.81, 3.83 within 24 months; 3.02, 2.03 and 5.09, 3.43 within 36 months, respectively. At the AD conversion probability prediction, the prediction accuracies within 12, 24, and 36 months reached to 88.0, 85.5, and 88.4%, respectively. The AD predication would play a great role in clinical applications.

Intelligent quality control of traditional chinese medical tongue diagnosis images based on deep learning.

BACKGROUND: Computer-aided tongue and face diagnosis technology can make Traditional Chinese Medicine (TCM) more standardized, objective and quantified. However, many tongue images collected by the instrument may not meet the standard in clinical applications, which affects the subsequent quantitative analysis. The common tongue diagnosis instrument cannot determine whether the patient has fully extended the tongue or collected the face. OBJECTIVE: This paper proposes an image quality control algorithm based on deep learning to verify the eligibility of TCM tongue diagnosis images. METHODS: We firstly gathered enough images and categorized them into five states. Secondly, we preprocessed the training images. Thirdly, we built a ResNet34 model and trained it by the transfer learning method. Finally, we input the test images into the trained model and automatically filter out unqualified images and point out the reasons. RESULTS: Experimental results show that the model's quality control accuracy rate of the test dataset is as high as 97.06%. Our methods have the strong discriminative power of the learned representation. Compared with previous studies, it can guarantee subsequent tongue image processing. CONCLUSIONS: Our methods can guarantee the subsequent quantitative analysis of tongue shape, tongue state, tongue spirit, and facial complexion.

Rice straw returning enhances cadmium activation by accelerating iron cycling thus hydroxyl radical production in paddy soils during drainage.

Straw returning is widely found elevating the bioavailability of cadmium (Cd) in paddy soils with unclear biogeochemical mechanisms. Here, a series of microcosm incubation experiments were conducted and spectroscopic and microscopic analyses were employed. The results showed that returning rice straw (RS) efficiently increased amorphous Fe and low crystalline Fe (II) to promote the production of hydroxyl radicals (OH) thus Cd availability in paddy soils during drainage. On the whole, RS increased OH and extractable Cd by 0.2-1.4 and 0.1-3.3 times, respectively. While the addition of RS effectively improved the oxidation rate of structural Fe (II) mineral (i.e., FeS) to enhance soil Cd activation (up to 38.5 %) induced by the increased OH (up to 69.2 %). Additionally, the existence of CO32- significantly increased the efficiency level on OH production and Cd activation, which was attributed to the improved reactivity of Fe (II) by CO32- in paddy soils. Conclusively, this study emphasizes risks of activating soil Cd induced by RS returning-derived OH, providing a new insight into evaluating the safety of straw recycling.

Advances in systemic immune inflammatory indices in non-small cell lung cancer: A review.

Lung cancer is one of the most prevalent cancers globally, with non-small cell lung cancers constituting the majority. These cancers have a high incidence and mortality rate. In recent years, a growing body of research has demonstrated the intricate link between inflammation and cancer, highlighting that inflammation and cancer are inextricably linked and that inflammation plays a pivotal role in cancer development, progression, and prognosis of cancer. The Systemic Immunoinflammatory Index (SII), comprising neutrophil, lymphocyte, and platelet counts, is a more comprehensive indicator of the host's systemic inflammation and immune status than a single inflammatory index. It is widely used in clinical practice due to its cost-effectiveness, simplicity, noninvasiveness, and ease of acquisition. This paper reviews the impact of SII on the development, progression, and prognosis of non-small cell lung cancer.

Ecotoxicity of hexavalent chromium [Cr (VI)] in soil presents predominate threats to agricultural production with the increase of soil Cr contamination.

The relative severity between chromium (Cr)-mediated ecotoxicity and its bioaccumulation has rarely been compared and evaluated. This study employed pot incubation experiments to simulate the soil environment with increased Cr pollution and study their effects on the growth of crops, including pepper, lettuce, wheat, and rice. Results showed that increasing total Cr presented ascendant ecotoxicity in upland soils when pH > 7.5, and significantly reduced the yield of pepper, lettuce and wheat grain by 0.3-100 %, whereas, this effect was weakened even reversed as the pH decreased. Surprisingly, a series of soils with Cr concentration of 22.7-623.5 mg kg-1 did not cause Cr accumulation in four crops over the Chinese permissible limit. The toxicity of Cr was highly associated with extractable Cr, where Cr (VI) made the greater contributions than Cr (III). Conclusively, the ecotoxicity of Cr poses a greater environmental issue as compared to the bioaccumulation of Cr in crops in upland soils, while extractable Cr (VI) makes the predominant contributions to the ecotoxicity of Cr as the total Cr increased. Our study proposes a synchronous consideration involving total Cr and Cr (VI) as the theoretical basis to establish a more reliable soil quality standard for safe production in China.