Microenvironment niches determine cellular fates of metastatic cancer cells. However, robust and unbiased approaches to identify niche components and their molecular profiles are lacking. We established Sortase A-Based Microenvironment Niche Tagging (SAMENT), which selectively labels cells encountered by cancer cells during metastatic colonization. SAMENT was applied to multiple cancer models colonizing the same organ and the same cancer to different organs. Common metastatic niche features include macrophage enrichment and T cell depletion. Macrophage niches are phenotypically diverse between different organs. In bone, macrophages express the estrogen receptor alpha (ERα) and exhibit active ERα signaling in male and female hosts. Conditional knockout of Esr1 in macrophages significantly retarded bone colonization by allowing T cell infiltration. ERα expression was also discovered in human bone metastases of both genders. Collectively, we identified a unique population of ERα+ macrophages in the metastatic niche and functionally tied ERα signaling in macrophages to T cell exclusion during metastatic colonization. HIGHLIGHTS: SAMENT is a robust metastatic niche-labeling approach amenable to single-cell omics.Metastatic niches are typically enriched with macrophages and depleted of T cells.Direct interaction with cancer cells induces ERα expression in niche macrophages. Knockout of Esr1 in macrophages allows T cell infiltration and retards bone colonization.
Farmers' decisions on crop choice, management practices, and livelihood strategies are essential to agricultural sustainability. This data article describes three datasets on crop production in Quzhou, a county in the central part of North China Plain. The three datasets cover different scales. The village dataset assembles basic data on all 342 villages of Quzhou county, including information on population, land area, crop grown, labour, irrigation and markets. Data was sourced from the yearbook data of 2017 and a village cadres survey in 2018. The village dataset was used to create a village typology from which 35 villages belonging to seven village types (five for each type) were selected for stratified random sampling to collect information on farm characteristics and cropping practices. We surveyed these 35 villages, interviewing fifteen farmer households per village (525 in total) in 2020. The interviewees represented two farm management models: smallholder farms and business farms. The resulting household dataset provides farm-level data, including demographic data of farming decision-makers and the number of household members, land use and machinery resources, crop production management practices, and government subsidies. The crop-level dataset was derived from the household survey and included input-output inventories for each crop grown during one year on each field greater than 1/30th ha (1/2 mu) on the 525 surveyed farms within a year. This dataset comprises information on cropping practices in 1352 fields. The three datasets provide a basis for analyses on cropping practices and sustainability attributes of farms and crops in a typical agricultural county on the North China Plain.
Inorganic phosphorus (Pi) deficiency significantly impacts plant growth, development, and photosynthetic efficiency. This study evaluated 206 rice accessions from a MiniCore population under both Pi-sufficient (Pi+) and Pi-starvation (Pi-) conditions in the field to assess photosynthetic phosphorus use efficiency (PPUE), defined as the ratio of AsatPi- to AsatPi+. A genome-wide association study and differential gene expression analyses identified an acid phosphatase gene (ACP2) that responds strongly to phosphate availability. Overexpression and knockout of ACP2 led to a 67% increase and 32% decrease in PPUE, respectively, compared with wild type. Introduction of an elite allele A, by substituting the v5 SNP G with A, resulted in an 18% increase in PPUE in gene-edited ACP2 rice lines. The phosphate-responsive gene PHR2 was found to transcriptionally activate ACP2 in parallel with PHR2 overexpression, resulting in an 11% increase in PPUE. Biochemical assays indicated that ACP2 primarily catalyzes the hydrolysis of phosphoethanolamine and phospho-L-serine. In addition, serine levels increased significantly in the ACP2v8G-overexpression line, along with a concomitant decrease in the expression of all nine genes involved in the photorespiratory pathway. Application of serine enhanced PPUE and reduced photorespiration rates in ACP2 mutants under Pi-starvation conditions. We deduce that ACP2 plays a crucial role in promoting photosynthesis adaptation to Pi starvation by regulating serine metabolism in rice.
To realize the resourceful use of soilbags filled with graphite tailings, their load-bearing and deformation characteristics must be fully understood. In this study, the following results were obtained by performing geometric testing of water-filled sealing bags and uniaxial compression tests of soilbags filled with graphite tailings. The volume of the soilbag expressed in rectangular form was approximately 0.773 times the actual volume. The types of compression damage to soilbags can be defined as surface damage and overall damage. The surface damage load increases with decreasing filling density and decreases with decreasing soilbag size. Moreover, the higher the tensile capacity of the soilbag material and the lower the friction between the soilbags, the greater the surface damage load. The overall damage load increased with an increase in the tensile strength of the soilbag material and decreased with an increase in the degree of filling; the overall damage load was greater for large-sized soilbags at high degrees of filling. Thus, the existing theoretical calculation method cannot accurately calculate the damage load of soilbags filled with graphite tailings, and the test results deviate from the theoretical calculation results, with the latter showing an increasing damage load with a decreasing filling degree.
Immunotherapy is a promising approach for treating metastatic breast cancer (MBC), offering new possibilities for therapy. While checkpoint inhibitors have shown great progress in the treatment of metastatic breast cancer, their effectiveness in patients with bone metastases has been disappointing. This lack of efficacy seems to be specific to the bone environment, which exhibits immunosuppressive features. In this study, we elucidate the multiple roles of the sialic acid-binding Ig-like lectin (Siglec)-15/sialic acid glyco-immune checkpoint axis in the bone metastatic niche and explore potential therapeutic strategies targeting this glyco-immune checkpoint. Our research reveals that elevated levels of Siglec-15 in the bone metastatic niche can promote tumor-induced osteoclastogenesis as well as suppress antigen-specific T cell responses. Next, we demonstrate that antibody blockade of the Siglec-15/sialic acid glyco-immune checkpoint axis can act as a potential treatment for breast cancer bone metastasis. By targeting this pathway, we not only aim to treat bone metastasis but also inhibit the spread of metastatic cancer cells from bone lesions to other organs.
Bone Neoplasms , Breast Neoplasms , Humans , Female , Breast Neoplasms/drug therapy , N-Acetylneuraminic Acid , Bone Neoplasms/drug therapy , Immunotherapy , Antibodies, Blocking
BACKGROUND: Assessment of treatment response in triple-negative breast cancer (TNBC) may guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) measures tissue anisotropy and could be useful for characterizing changes in the tumors and adjacent fibroglandular tissue (FGT) of TNBC patients undergoing neoadjuvant systemic treatment (NAST). PURPOSE: To evaluate the potential of DTI parameters for prediction of treatment response in TNBC patients undergoing NAST. STUDY TYPE: Prospective. POPULATION: Eighty-six women (average age: 51 ± 11 years) with biopsy-proven clinical stage I-III TNBC who underwent NAST followed by definitive surgery. 47% of patients (40/86) had pathologic complete response (pCR). FIELD STRENGTH/SEQUENCE: 3.0 T/reduced field of view single-shot echo-planar DTI sequence. ASSESSMENT: Three MRI scans were acquired longitudinally (pre-treatment, after 2 cycles of NAST, and after 4 cycles of NAST). Eleven histogram features were extracted from DTI parameter maps of tumors, a peritumoral region (PTR), and FGT in the ipsilateral breast. DTI parameters included apparent diffusion coefficients and relative diffusion anisotropies. pCR status was determined at surgery. STATISTICAL TESTS: Longitudinal changes of DTI features were tested for discrimination of pCR using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC). A P value <0.05 was considered statistically significant. RESULTS: 47% of patients (40/86) had pCR. DTI parameters assessed after 2 and 4 cycles of NAST were significantly different between pCR and non-pCR patients when compared between tumors, PTRs, and FGTs. The median surface/average anisotropy of the PTR, measured after 2 and 4 cycles of NAST, increased in pCR patients and decreased in non-pCR patients (AUC: 0.78; 0.027 ± 0.043 vs. -0.017 ± 0.042 mm2 /s). DATA CONCLUSION: Quantitative DTI features from breast tumors and the peritumoral tissue may be useful for predicting the response to NAST in TNBC. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 4.
Cortisol hormone imbalances can be detected through non-invasive sweat monitoring using field-effect transistor (FET) biosensors, which provide rapid and sensitive detection. However, challenges like skin compatibility and integration with sweat collection have hindered FET biosensors as wearable sensing platforms. In this study, we present an integrated wearable sticker for real-time cortisol detection based on an extended-gate AlGaN/GaN high electron mobility transistor (HEMT) combined with a soft bottom substrate and flexible channel for sweat collection. The developed devices exhibit excellent linearity (R2 = 0.990) and a high sensitivity of 1.245 µA dec-1 for cortisol sensing from 1 nM to 100 µM in high-ionic-strength solution, with successful cortisol detection demonstrated using authentic human sweat samples. Additionally, the chip's microminiature design effectively reduces bending impact during the wearable process of traditional soft binding sweat sensors. The extendedgate structure design of the HEMT chip enhances both width-to-length ratio and active sensing area, resulting in an exceptionally low detection limit of 100 fM. Futhermore, due to GaN material's inherent stability, this device exhibits long-term stability with sustained performance within a certain attenuation range even after 60 days. These stickers possess small, lightweight, and portable features that enable real-time cortisol detection within 5 minutes through direct sweat collection. The application of this technology holds great potential in the field of personal health management, facilitating users to conveniently monitor their mental and physical conditions.
Aluminum Compounds , Biosensing Techniques , Gallium , Wearable Electronic Devices , Humans , Sweat/chemistry , Hydrocortisone/analysis , Electrons , Biosensing Techniques/methods
Plants are constantly exposed to microbial pathogens in the environment. One branch of innate plant immunity is mediated by cell-membrane-localized receptors, but less is known about associations between DNA damage and plant immune responses. Here, we show that rice (Oryza sativa) mesophyll cells are prone to DNA double-stranded breaks (DSBs) in response to ZJ173, a strain of Xanthomonas oryzae pv. oryzae (Xoo). The DSB signal transducer ataxia telangiectasia mutated (ATM), but not the ATM and Rad3-related branch, confers resistance against Xoo. Mechanistically, the MRE11-ATM module phosphorylates suppressor of gamma response 1 (SOG1), which activates several phenylpropanoid pathway genes and prompts downstream phytoalexin biosynthesis during Xoo infection. Intriguingly, overexpression of the topoisomerase gene TOP6A3 causes a switch from the classic non-homologous end joining (NHEJ) pathway to the alternative NHEJ and homologous recombination pathways at Xoo-induced DSBs. The enhanced ATM signaling of the alternative NHEJ pathway strengthens the SOG1-regulated phenylpropanoid pathway and thereby boosts Xoo-induced phytoalexin biosynthesis in TOP6A3-OE1 overexpression lines. Overall, the MRE11-ATM-SOG1 pathway serves as a prime example of plant-pathogen interactions that occur via host non-specific recognition. The function of TOP6-facilitated ATM signaling in the defense response makes it a promising target for breeding of rice germplasm that exhibits resistance to bacterial blight disease without a growth penalty.
Ataxia Telangiectasia , Oryza , Xanthomonas , Oryza/metabolism , Phytoalexins , Signal Transduction
We trained and validated a deep learning model that can predict the treatment response to neoadjuvant systemic therapy (NAST) for patients with triple negative breast cancer (TNBC). Dynamic contrast enhanced (DCE) MRI and diffusion-weighted imaging (DWI) of the pre-treatment (baseline) and after four cycles (C4) of doxorubicin/cyclophosphamide treatment were used as inputs to the model for prediction of pathologic complete response (pCR). Based on the standard pCR definition that includes disease status in either breast or axilla, the model achieved areas under the receiver operating characteristic curves (AUCs) of 0.96 ± 0.05, 0.78 ± 0.09, 0.88 ± 0.02, and 0.76 ± 0.03, for the training, validation, testing, and prospective testing groups, respectively. For the pCR status of breast only, the retrained model achieved prediction AUCs of 0.97 ± 0.04, 0.82 ± 0.10, 0.86 ± 0.03, and 0.83 ± 0.02, for the training, validation, testing, and prospective testing groups, respectively. Thus, the developed deep learning model is highly promising for predicting the treatment response to NAST of TNBC.Clinical Relevance- Deep learning based on serial and multiparametric MRIs can potentially distinguish TNBC patients with pCR from non-pCR at the early stage of neoadjuvant systemic therapy, potentially enabling more personalized treatment of TNBC patients.
Deep Learning , Multiparametric Magnetic Resonance Imaging , Triple Negative Breast Neoplasms , Humans , Triple Negative Breast Neoplasms/diagnostic imaging , Triple Negative Breast Neoplasms/drug therapy , Neoadjuvant Therapy/methods , Prospective Studies , Treatment Outcome
Early prediction of neoadjuvant systemic therapy (NAST) response for triple-negative breast cancer (TNBC) patients could help oncologists select individualized treatment and avoid toxic effects associated with ineffective therapy in patients unlikely to achieve pathologic complete response (pCR). The objective of this study is to evaluate the performance of radiomic features of the peritumoral and tumoral regions from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquired at different time points of NAST for early treatment response prediction in TNBC. This study included 163 Stage I-III patients with TNBC undergoing NAST as part of a prospective clinical trial (NCT02276443). Peritumoral and tumoral regions of interest were segmented on DCE images at baseline (BL) and after two (C2) and four (C4) cycles of NAST. Ten first-order (FO) radiomic features and 300 gray-level-co-occurrence matrix (GLCM) features were calculated. Area under the receiver operating characteristic curve (AUC) and Wilcoxon rank sum test were used to determine the most predictive features. Multivariate logistic regression models were used for performance assessment. Pearson correlation was used to assess intrareader and interreader variability. Seventy-eight patients (48%) had pCR (52 training, 26 testing), and 85 (52%) had non-pCR (57 training, 28 testing). Forty-six radiomic features had AUC at least 0.70, and 13 multivariate models had AUC at least 0.75 for training and testing sets. The Pearson correlation showed significant correlation between readers. In conclusion, Radiomic features from DCE-MRI are useful for differentiating pCR and non-pCR. Similarly, predictive radiomic models based on these features can improve early noninvasive treatment response prediction in TNBC patients undergoing NAST.
The paper introduces professor ZHUANG Li-xing's clinical experience in treatment of dyskinesia of Parkinson's disease with acupuncture at triple-acupoint prescription. In pathogenesis, dyskinesia of Parkinson's disease refers to yang deficiency and disturbing wind. In treatment, acupuncture focuses on warming yang, promoting the circulation of the governor vessel, regulating the spirit and stopping trembling; and Baihui (GV 20), Suliao (GV 25) and Dingchanxue (Extra) are selected to be "trembling relief needling". In combination with Jin's three needling, named "three-trembling needling" "three-governor-vessel needling" and "three-spasm needling", the triple-acupoint prescription is composed. To ensure the favorable therapeutic effect, this prescription is modified according to the symptoms and the specific techniques of acupuncture are combined such as conducting qi, harmonizing yin and yang, and manipulating gently for reinforcing and reducing.
Acupuncture Therapy , Acupuncture , Dyskinesias , Parkinson Disease , Humans , Acupuncture Points , Parkinson Disease/therapy , Acupuncture Therapy/methods
The UN sustainable development goals ask countries to advance sustainable production methods in agriculture. While the need for a transition to sustainable agricultural production is widely felt, there is little insight into local stakeholders' perceptions regarding agroecosystem (dis)services in areas with intensive production methods. The North China Plain is an agricultural production area with intensive production systems and simplified agricultural landscapes. We conducted a survey with 267 farmers in Quzhou county in the North China Plain in 2020 to measure the perceived level of agroecosystem (dis)services supply and the changes therein between 2015 and 2020. We analyzed which explanatory factors were associated with farmers' perceptions. Provisioning services were at a high level, while the regulating and supporting ecosystem services were considered to be in low supply, as evidenced by low scores for the presence of natural enemies and earthworms, and for natural habitats such as hedgerows and windbreaks. Most of the participants did not perceive dis-services from agriculture. Differences in perception between villages with contrasting biophysical and socio-economic conditions highlight the relevance of contextualized policy development for agricultural landscape composition and configuration to manage ecosystem (dis)services.
Ecosystem , Farmers , Humans , Agriculture/methods , Sustainable Development , China , Conservation of Natural Resources/methods
Accurate tumor segmentation is required for quantitative image analyses, which are increasingly used for evaluation of tumors. We developed a fully automated and high-performance segmentation model of triple-negative breast cancer using a self-configurable deep learning framework and a large set of dynamic contrast-enhanced MRI images acquired serially over the patients' treatment course. Among all models, the top-performing one that was trained with the images across different time points of a treatment course yielded a Dice similarity coefficient of 93% and a sensitivity of 96% on baseline images. The top-performing model also produced accurate tumor size measurements, which is valuable for practical clinical applications.
