Reasonable deep application of sheep manure fertilizer to alleviate soil acidification to improve tea yield and quality

Soil acidification in Chinese tea plantations is widespread, and it has significantly affected the growth of tea trees; it was important to explore soil remediation of acidified tea plantations in depth for the sustainable development of tea industry. In this study, the effects of sheep manure fertilizer with different application depths on soil acidification, tea yield and quality, and soil nitrogen transformation in tea plantations were analyzed for five consecutive years from 2018 to 2022. The results showed that long-term use of sheep manure fertilizer significantly reduced soil acidification (P< 0.05) in tea plantations, improved soil pH and soil ammonium nitrogen content, enhanced root activity and root nitrogen uptake capacity of tea trees, and thus improved tea yield and quality. The effect of different application depths of sheep manure fertilizer on tea yield and quality was mainly reflected in the transformation ability of soil ammonium nitrogen and nitrate nitrogen, which showed that high transformation ability of soil ammonium nitrogen and high ammonium nitrogen content were beneficial to high tea yield and vice versa, and the best effect was achieved when sheep manure was applied at a depth of 50 cm and 70 cm. The topsis analysis confirmed that sheep manure fertilization had a greater effect on root activity, ammonium nitrogen, ammonia intensity, and nifH gene. This study provided an important practical basis for the restoration of acidified tea plantation soil through sheep manure fertilizer management

HoVer-Trans: Anatomy-aware HoVer-Transformer for ROI-free Breast Cancer Diagnosis in Ultrasound Images

Ultrasonography is an important routine examination for breast cancer diagnosis, due to its non-invasive, radiation-free and low-cost properties. However, the diagnostic accuracy of breast cancer is still limited due to its inherent limitations. It would be a tremendous success if we can precisely diagnose breast cancer by breast ultrasound images (BUS). Many learning-based computer-aided diagnostic methods have been proposed to achieve breast cancer diagnosis/lesion classification. However, most of them require a pre-define ROI and then classify the lesion inside the ROI. Conventional classification backbones, such as VGG16 and ResNet50, can achieve promising classification results with no ROI requirement. But these models lack interpretability, thus restricting their use in clinical practice. In this study, we propose a novel ROI-free model for breast cancer diagnosis in ultrasound images with interpretable feature representations. We leverage the anatomical prior knowledge that malignant and benign tumors have different spatial relationships between different tissue layers, and propose a HoVer-Transformer to formulate this prior knowledge. The proposed HoVer-Trans block extracts the inter- and intra-layer spatial information horizontally and vertically. We conduct and release an open dataset GDPH&SYSUCC for breast cancer diagnosis in BUS. The proposed model is evaluated in three datasets by comparing with four CNN-based models and two vision transformer models via five-fold cross validation. It achieves state-of-the-art classification performance with the best model interpretability. In the meanwhile, our proposed model outperforms two senior sonographers on the breast cancer diagnosis when only one BUS image is given

Residential Pesticide Usage in Older Adults Residing in Central California

Information on residential pesticide usage and behaviors that may influence pesticide exposure was collected in three population-based studies of older adults residing in the three Central California counties of Fresno, Kern, and Tulare. We present data from participants in the Study of Use of Products and Exposure Related Behaviors (SUPERB) study (N = 153) and from community controls ascertained in two Parkinson’s disease studies, the Parkinson’s Environment and Gene (PEG) study (N = 359) and The Center for Gene-Environment Studies in Parkinson’s Disease (CGEP; N = 297). All participants were interviewed by telephone to obtain information on recent and lifetime indoor and outdoor residential pesticide use. Interviews ascertained type of product used, frequency of use, and behaviors that may influence exposure to pesticides during and after application. Well over half of all participants reported ever using indoor and outdoor pesticides; yet frequency of pesticide use was relatively low, and appeared to increase slightly with age. Few participants engaged in behaviors to protect themselves or family members and limit exposure to pesticides during and after treatment, such as ventilating and cleaning treated areas, or using protective equipment during application. Our findings on frequency of use over lifetime and exposure related behaviors will inform future efforts to develop population pesticide exposure models and risk assessment

S2 Table. All T-RFs detectd using T-RFLP

<p>All T-RFs detectd using T-RFLP</p

S2 Table. The optical density (OD) at 590 nm change with incubation time

<p>The optical density (OD) at 590 nm change with incubation time</p

S5 Table. Principal components analysis

<p>Principal components analysis</p

S2 Table Bacterial community detected in all soil samples

<p>Bacterial community detected in all soil samples</p

S4 Table. PLFA determination of microbial community composition (25 years stand soil)

<p>PLFA determination of microbial community composition (25 years stand soil)</p