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Acid rain and invasive plants have quintessential adverse impacts on terrestrial ecosystems. As an environmentally safe method for disposal of invasive plants, we tested the effect of biochar produced from these plants in altering soil deterioration under acid rain as compared with lime. Given the impacts of the feedstock type and soil properties on the response of soil to the added biochar, we hypothesized that the microbial community and functions would respond differently to the charred invasive plants under acid rain. A pot experiment was conducted to examine the response of soil microbiomes and functions to the biochar produced from Blackjack (Biden Pilosa), Wedelia (Wedelia trilobata), and Bitter vine (Mikania micrantha Kunth), or quicklime (CaO) at a rate of 1 % (w/w) under acid rain. Like soil pH, the nutrient contents (nitrogen, phosphorus, and potassium), calcium, and cation exchange capacity (CEC) were important as dominant edaphic factors affecting soil microbial community and functionality. In this respect, lime decreased nutrients availability, driven by 11-fold, 44 %, and 2-fold increments in calcium content, pH, and C/N ratio. Meanwhile, biochar improved nutrients availability under acid rain owing to maintaining a neutral pH (∼6.5), increasing calcium (by only 2-fold), and improving CEC, water repellency, and aggregation while decreasing the C/N ratio and aluminum content. Unlike biochar, lime decreased the relative abundance of Nitrosomonadaceae (the dominant ammonia-oxidizing bacteria) while augmenting the relative abundance of some fungal pathogens such as Spizellomycetaceae and Sporormiaceae. Given the highest nitrogen and dissolved organic carbon content than other biochar types, Wedelia-biochar resulted in the greatest relative abundance of Nitrosomonadaceae; thus, the microbial carbon and nitrogen biomasses were maximized. This study outlined the responses of the soil biogeochemical properties and the related microbial community structure and functionality to the biochar produced from invasive plants under acid rain. This study suggests that biochar can replace lime to ameliorate the effects of acid rain on soil physical, chemical and biological properties.

Fragrant rice has a high market value, and it is a popular rice type among consumers owing to its pleasant flavor. Plantation methods, nitrogen (N) fertilizers, and silicon (Si) fertilizers can affect the grain yield and fragrance of fragrant rice. However, the core commercial rice production attributes, namely the head rice yield (HRY) and 2-acetyl-1-pyrroline (2-AP) content of fragrant rice, under various nitrogen and silicon (N-Si) fertilization levels and different plantation methods remain unknown. The field experiment in this study was performed in the early seasons of 2018 and 2019 with two popular indica fragrant rice cultivars (Yuxiangyouzhan and Xiangyaxiangzhan). They were grown under six N-Si fertilization treatments (combinations of two levels of Si fertilizer, 0 kg Si ha−1 (Si0) and 150 kg Si ha−1 (Si1), and three levels of N fertilizer, 0 kg N ha−1 (N0), 150 kg N ha−1 (N1), and 220 kg N ha−1 (N2)) and three plantation methods (artificial transplanting (AT), mechanical transplanting (MT), and mechanical direct-seeding (MD)). The results showed that the N-Si fertilization treatments and all the plantation methods significantly affected the HRY and 2-AP content and related parameters of the two different fragrant rice cultivars. Compared with the Si0N0 treatment, the N-Si fertilization treatments resulted in higher HRY and 2-AP contents. The rates of brown rice, milled rice, head rice, and chalky rice of the fragrant rice also improved with the N-Si fertilization treatments. The N-Si fertilization treatments increased the activities of N metabolism enzymes and the accumulation of N and Si in various parts of the fragrant rice, and affected their antioxidant response parameters. The key parameters for the HRY and 2-AP content were assessed by redundancy analysis. Furthermore, the structural equation model revealed that the Si and N accumulation levels indirectly affected the HRY by affecting the N metabolism enzyme activity, N use efficiency, and grain quality of fragrant rice. Moreover, high N and Si accumulation directly promoted the 2-AP content or affected the antioxidant response parameters and indirectly regulated 2-AP synthesis. The interactions of the MT method with the N-Si fertilization treatments varied in the fragrant rice cultivars in terms of the HRY and 2-AP content, whereas the MD method was beneficial to the 2-AP content in both fragrant rice cultivars under the N-Si fertilization treatments.

Although immunotherapy has revolutionized cancer management, most patients do not derive benefits from it. Aiming to explore an appropriate strategy for immunotherapy efficacy prediction, we collected 6251 patients’ transcriptome data from multicohort population and analyzed the data using a machine learning algorithm. In this study, we found that patients from three immune gene clusters had different overall survival when treated with immunotherapy (P < 0.001), and that these clusters had differential states of hypoxia scores and metabolism functions. The immune gene score showed good immunotherapy efficacy prediction (AUC was 0.737 at 20 months), which was well validated. The immune gene score, tumor mutation burden, and long non-coding RNA score were further combined to build a tumor immune microenvironment signature, which correlated more strongly with overall survival (AUC, 0.814 at 20 months) than when using a single variable. Thus, we recommend using the characterization of the tumor immune microenvironment associated with immunotherapy efficacy via a multi-omics analysis of cancer.

Background: in current clinical practice, the standard evaluation for axillary lymph node (ALN) status in breast cancer has a low efficiency and is based on an invasive procedure that causes operative-associated complications in many patients. Therefore, we aimed to use machine learning techniques to develop an efficient preoperative magnetic resonance imaging (MRI) radiomics evaluation approach of ALN status and explore the association between radiomics and the tumor microenvironment in patients with early-stage invasive breast cancer.Methods: in this retrospective multicenter study, three independent cohorts of patients with breast cancer (n = 1,088) were used to develop and validate signatures predictive of ALN status. After applying the machine learning random forest algorithm to select the key preoperative MRI radiomic features, we used ALN and tumor radiomic features to develop the ALN-tumor radiomic signature for ALN status prediction by the support vector machine algorithm in 803 patients with breast cancer from Sun Yat-sen Memorial Hospital and Sun Yat-sen University Cancer Center (training cohort). By combining ALN and tumor radiomic features with corresponding clinicopathologic information, the multiomic signature was constructed in the training cohort. Next, the external validation cohort (n = 179) of patients from Shunde Hospital of Southern Medical University and Tungwah Hospital of Sun Yat-Sen University, and the prospective-retrospective validation cohort (n = 106) of patients treated with neoadjuvant chemotherapy in prospective phase 3 trials [NCT01503905], were included to evaluate the predictive value of the two signatures, and their predictive performance was assessed by the area under operating characteristic curve (AUC). This study was registered with ClinicalTrials.gov, number NCT04003558.Findings: the ALN-tumor radiomic signature for ALN status prediction comprising ALN and tumor radiomic features showed a high prediction quality with AUC of 0·88 in the training cohort, 0·87 in the external validation cohort, and 0·87 in the prospective-retrospective validation cohort. The multiomic signature incorporating tumor and lymph node MRI radiomics, clinical and pathologic characteristics, and molecular subtypes achieved better performance for ALN status prediction with AUCs of 0·90, 0·91, and 0·93 in the training cohort, the external validation cohort, and the prospective-retrospective validation cohort, respectively. Among patients who underwent neoadjuvant chemotherapy in the prospective-retrospective validation cohort, there were significant differences in the key radiomic features before and after neoadjuvant chemotherapy, especially in the gray-level dependence matrix features. Furthermore, there was an association between MRI radiomics and tumor microenvironment features including immune cells, long non-coding RNAs, and types of methylated sites.Interpretation this study presented a multiomic signature that could be preoperatively and conveniently used for identifying patients with ALN metastasis in early-stage invasive breast cancer. The multiomic signature exhibited powerful predictive ability and showed the prospect of extended application to tailor surgical management. Besides, significant changes in key radiomic features after neoadjuvant chemotherapy may be explained by changes in the tumor microenvironment, and the association between MRI radiomic features and tumor microenvironment features may reveal the potential biological underpinning of MRI radiomics.

Ferroptosis is a newly discovered form of non-apoptotic regulated cell death and is characterized by iron-dependent and lipid peroxidation. Due to the enhanced dependence on iron in cancer cells, induction of ferroptosis is becoming a promising therapeutic strategy. However, the precise underlying molecular mechanism and regulation process of ferroptosis remains largely unknown. In the present study, we demonstrate that the protein Frataxin (FXN) is a key regulator of ferroptosis by modulating iron homeostasis and mitochondrial function. Suppression of FXN expression specifically repressed the proliferation, destroyed mitochondrial morphology, impeded Fe–S cluster assembly and activated iron starvation stress. Moreover, suppression of FXN expression significantly enhanced erastin-induced cell death through accelerating free iron accumulation, lipid peroxidation and resulted in dramatic mitochondria morphological damage including enhanced fragmentation and vanished cristae. In addition, this type of cell death was confirmed to be ferroptosis, since it could be pharmacologically restored by ferroptotic inhibitor Fer-1 or GSH, but not by inhibitors of apoptosis, necrosis. Vice versa, enforced expression of FXN blocked iron starvation response and erastin-induced ferroptosis. More importantly, pharmacological or genetic blocking the signal of iron starvation could completely restore the resistance to ferroptosis in FXN knockdown cells and xenograft graft in vivo. This paper suggests that FXN is a novel ferroptosis modulator, as well as a potential provided target to improve the antitumor activity based on ferroptosis.

Paclobutrazol (PBZ) is a plant growth inhibitor and fungicide, but it is also carcinogenic and teratogenic, and has potential harm to human health. In this study, two PBZ haptens (PBZ-1, PBZ-2) were synthesized and conjugated with carrier proteins to get artificial antigens. A highly specific monoclonal antibody (mAb) against PBZ was prepared. The antibody subtype was IgG1 and the concentration was 11.03 mg/mL. A sensitive and rapid time-resolved fluorescence microsphere lateral flow immunoassay (TRFMs-LFIA) was established based on the mAb. The activated pH, the mAbs diluents, the mAb reacting concentration and the probe amount were optimized. The visual limit of detection (vLOD) and quantitative limit of detection (qLOD) of the TRFMs-LFIA for PBZ were 50 and 1.72 ng/mL respectively, and the 50% inhibiting concentration (IC50) was 9.38 ng/mL. The pretreatment procedures are simple and rapid, and the detection time of TRFMs-LFIA strip is 6 min. Qualitative and quantitative analysis of PBZ could be achieved under a UV light or with a portable fluorescence immunoassay analyzer. The average recovery rates ranged from 96.2% to 111.9% and the corresponding coefficients of variation (CV) were 4.0%–11.2% in spiked wheat and rice samples. Twenty real wheat and rice samples were measured by the TRFMs-LFIA and compared with Ultra-performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS). The measured values showed a good accordance. These results indicated that the proposed assay will provide a novel effective strategy for on-site detection of PBZ.