Prediction of wheat SPAD using integrated multispectral and support vector machines.

Rapidly obtaining the chlorophyll content of crop leaves is of great significance for timely diagnosis of crop health and effective field management. Multispectral imagery obtained from unmanned aerial vehicles (UAV) is being used to remotely sense the SPAD (Soil and Plant Analyzer Development) values of wheat crops. However, existing research has not yet fully considered the impact of different growth stages and crop populations on the accuracy of SPAD estimation. In this study, 300 materials from winter wheat natural populations in Xinjiang, collected between 2020 to 2022, were analyzed. UAV multispectral images were obtained in the experimental area, and vegetation indices were extracted to analyze the correlation between the selected vegetation indices and SPAD values. The input variables for the model were screened, and a support vector machine (SVM) model was constructed to estimate SPAD values during the heading, flowering, and filling stages under different water stresses. The aim was to provide a method for the rapid acquisition of winter wheat SPAD values. The results showed that the SPAD values under normal irrigation were higher than those under water restriction. Multiple vegetation indices were significantly correlated with SPAD values. In the prediction model construction of SPAD, the different models had high estimation accuracy under both normal irrigation and water limitation treatments, with correlation coefficients of predicted and measured values under normal irrigation in different environments the value of r from 0.59 to 0.81 and RMSE from 2.15 to 11.64, compared to RE from 0.10% to 1.00%; and under drought stress in different environments, correlation coefficients of predicted and measured values of r was 0.69-0.79, RMSE was 2.30-12.94, and RE was 0.10%-1.30%. This study demonstrated that the optimal combination of feature selection methods and machine learning algorithms can lead to a more accurate estimation of winter wheat SPAD values. In summary, the SVM model based on UAV multispectral images can rapidly and accurately estimate winter wheat SPAD value.

A novel Sillén-structured Bi-based oxybromide: CdBiO2Br ultrathin nanosheets for enhanced photocatalytic activity.

According to the typical Sillén-structured BiOBr, a simple solvothermal method was used to successfully synthesise Sillén-structured bimetallic oxyhalide CdBiO2Br with the existence of 1-hexadecyl-3-methylimidazolium bromide ([C16mim]Br), a kind of reactive ionic liquid. The introduction of the metal cadmium, which can form Sillén-structured bimetallic oxyhalide, made the alternating structure of BiOBr originally [Bi2O2]2+ and bilayer Br- modified to that of [CdBiO2]+ and monolayer Br-. So that the distance between layer and layer is greatly shortened, which facilitates the migration and separation of photogenerated carriers and promotes the generation of more reactive oxygen species. After modification, the band positions of CdBiO2Br materials can make more full use of visible light and more favourable utilisation of solar resources. As confirmed by radical trapping analysis and ESR analysis, superoxide radical (·O2-) and hole (h+) acted the major part during photocatalysis. The possible intermediate products that appeared during the degradation progress were analyzed by LC-MS. Moreover, the generation of superoxide ions was quantitatively analyzed by nitroblue tetrazolium chloride (NBT). In this paper, we present an ultra-thin layered material for visible light catalysis, which enlightens a feasible scheme for the research and development of new layered photocatalytic materials.

A Three-mRNA Signature Associated with Pyrimidine Metabolism for Prognosis of BRCA.

OBJECTIVE: Breast invasive carcinoma (BRCA), as a systemic disease, is currently the most malignant tumor among women. Early detection of BRCA will increase the probability of cure. Pyrimidine metabolism (PyM) stands for an essential metabolic pathway related to DNA replication of cancer cells, which may also serve as a diagnostic marker and therapeutic target. Therefore, the aim of this research is to discover a prognostic signature associated with PyM for BRCA. METHODS: The BRCA mRNA sequencing data along with microarray data were obtained based on The Cancer Genome Atlas (TCGA) database. In addition, 4 PyM-related gene sets were profiled through gene set enrichment analysis (GSEA); it revealed the core genes differentially expressed in cancer and paracancerous tissue. Thereafter, genes were subjected to univariate as well as multivariate regression for constructing an mRNA signature to independently predict BRCA prognosis. Then, the Kaplan-Meier (KM) curve was applied for validation. The prognostic power of the signature was verified against the METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) database. RESULTS: We constructed a three-mRNA (RRM2B, NME3, and POLD2) gene signature related to PyM to predict overall survival (OS) for BRCA. The as-constructed gene signature was adopted to classify cases as high- or low-risk group, identifying patients with BRCA with poor prognosis. Additionally, the risk score obtained using our constructed 3-mRNA prognosis signature is independent from other clinical variables. CONCLUSION: Our findings suggested that PyM-related mRNA signature might be a combined prognostic biomarker for BRCA and can provide important reference that are useful for individualized treatment for BRCA patients.

The choice of a neoadjuvant chemotherapy cycle for breast cancer has significance in clinical practice: results from a population-based, real world study.

OBJECTIVE: Neoadjuvant chemotherapy (NAC) is currently used in both early stage and locally advanced breast cancers. The survival benefits of standard vs. non-standard NAC cycles are still unclear. This study aimed to investigate the relationship between NAC cycles and survival based on real world data. METHODS: We identified patients diagnosed with invasive primary breast cancers who underwent NAC followed by surgery. Patients who received at least 4 NAC cycles were defined as having received standard cycles, while patients who received less than 4 NAC cycles were defined as having received non-standard cycles. Kaplan-Meier curves and Cox proportional hazard models were used to estimate the disease-free survival (DFS) and overall survival (OS). RESULTS: Of the 1,024 included patients, 700 patients received standard NAC cycles and 324 patients received non-standard NAC cycles. The DFS estimates were 87.1% and 81.0% (P = 0.007) and the OS estimates were 90.0% and 82.6% (P = 0.001) in the standard and non-standard groups, respectively. Using multivariate analyses, patients treated with standard NAC cycles showed significant survival benefits in both DFS [hazard ratio (HR): 0.62, 95% confidence interval (CI): 0.44-0.88] and OS (HR: 0.54, 95% CI: 0.37-0.79). Using stratified analyses, standard NAC cycles were associated with improved DFS (HR: 0.59, 95% CI: 0.36-0.96) and OS (HR: 0.49, 95% CI: 0.28-0.86) in the HER2 positive group. Similar DFS (HR: 0.50, 95% CI: 0.25-0.98) and OS (HR: 0.45, 95% CI: 0.22-0.91) benefits were shown for the triple negative group. CONCLUSIONS: Standard NAC cycles were associated with a significant survival benefit, especially in patients with HER2 positive or triple negative breast cancer.

An Immune Model to Predict Prognosis of Breast Cancer Patients Receiving Neoadjuvant Chemotherapy Based on Support Vector Machine.

Tumor microenvironment has been increasingly proved to be crucial during the development of breast cancer. The theory about the conversion of cold and hot tumor attracted the attention to the influences of traditional therapeutic strategies on immune system. Various genetic models have been constructed, although the relation between immune system and local microenvironment still remains unclear. In this study, we tested and collected the immune index of 262 breast cancer patients before and after neoadjuvant chemotherapy. Five indexes were selected and analyzed to form the prediction model, including the ratio values between after and before neoadjuvant chemotherapy of CD4+/CD8+ T cell ratio; lymphosum of T, B, and natural killer (NK) cells; CD3+CD8+ cytotoxic T cell percent; CD16+CD56+ NK cell absolute value; and CD3+CD4+ helper T cell percent. Interestingly, these characters are both the ratio value of immune status after neoadjuvant chemotherapy to the baseline. Then the prediction model was constructed by support vector machine (accuracy rate = 75.71%, area under curve = 0.793). Beyond the prognostic effect and prediction significance, the study instead emphasized the importance of immune status in traditional systemic therapies. The result provided new evidence that the dynamic change of immune status during neoadjuvant chemotherapy should be paid more attention.

Tailoring 3D Carbon Foam using CNTs and MnO2 to Fabricate Stable Lithium/Dissolved Lithium Polysulfide Batteries.

The lithium-sulfur (Li-S) battery is an ideal electrochemical energy storage system owing to the high theoretical energy density and acceptable cost of finance and the environment. However, some disadvantages, including low electrical conductivity, poor sulfur utilization, and rapid capacity fading, obstruct its practical application. In this work, 3D carbon foam from a melamine resin is synthesized via high-temperature calcination. Carbon nanotubes (CNTs) and MnO2 are utilized to tailor the properties of the 3D cathode collector in the liquid Li2S6-containing Li-S battery without additional conductive agents, binders, and aluminum foil. Herein, the decorated MnO2 on the carbon fiber foam prolongs the lifespan of the Li-S battery, and adding CNTs is beneficial to enhance the capacity and cyclic performance of the Li-S battery under high sulfur loading. The Li-S battery with a sulfur loading of 3 mg cm-2 possesses a reversible capacity of 437.9 mA h g-1 after 400 cycles at 0.1 C. The capacity could be maintained at 568 mA h g-1 at 0.1 C after 80 cycles when the sulfur loading increases to 6 mg cm-2.

Leptin-elicited PBX3 confers letrozole resistance in breast cancer.

Aberrant leptin signaling and overexpression of fibroblast growth factor receptor 1 (FGFR1) are both implicated in the pathogenesis of letrozole resistance in breast cancer (BCa), but it remains unknown whether these two pathways are involved in letrozole resistance in a coordinated manner. Here, we demonstrate that expression levels of the pre-B-cell leukemia homeobox transcription factor 3 (PBX3), a pioneer factor that governs divergent biological processes, were significantly upregulated in letrozole-resistant BCa cells and tissues, and this upregulation correlated to a poorer progression-free survival in patients. By leveraging a patient-derived xenograft model with pharmacological approaches, we demonstrated that leptin activated PBX3 expression in a STAT3 (signal transducer and activator of transcription 3)-dependent manner. Our loss- and gain-of-function study further showed that PBX3 attenuated response to letrozole by potentiating BCa cell survival and anchorage-independent growth in BCa cells. By profiling BCa cells with ectopic PBX3 expression, we revealed that PBX3 conferred letrozole resistance via transactivation of the FGFR1 signaling, and this molecular event must coordinate a synergistic transcription activation programs through interacting with MTA1-HDAC2 (metastasis associated 1-histone deacetylase 2) complex. Overall, the available data reveal a novel role of leptin/PBX3 cascade linking energy homeostasis (i.e. hyperleptinemia) and endocrine therapy failure (i.e. letrozole resistance) in BCa.

A gene signature predicts response to neoadjuvant chemotherapy in triple-negative breast cancer patients.

Triple-negative breast cancer (TNBC) accounts for approximately 15% of all breast cancer cases. TNBC is highly aggressive and associated with poor prognosis. The present study aimed to compare gene expression between TNBC patients with pathological complete response (pCR) and those with not complete response (nCR) to neoadjuvant chemotherapy. Microarray data of 16 TNBC patients received neoadjuvant chemotherapy were identified from the Gene Expression Omnibus database and 10 patients of them had pCR. We found that 250 coding genes and 155 long noncoding RNAs (lncRNAs) were statistically differentially expressed between patients with pCR and nCR. Receiver operator characteristic curve and area under the curve (AUC) were calculated to assess predictive value of differentially expressed genes. A gene signature of three coding genes and two lncRNA was developed: 2.318*TCF3 + 7.349*CREB1 + 0.891*CEP44 + 0.091*NR_023392.1 + 1.424*NR_048561.1 - 106.682. The gene signature was further validated and had an AUC = 0.829. In summary, we profiled gene expression in pCR patients and developed a gene signature, which was effective to predict pCR among TNBC patients received neoadjuvant chemotherapy.

Theoretical Investigation of a Highly Sensitive Refractive-Index Sensor Based on TM0 Waveguide Mode Resonance Excited in an Asymmetric Metal-Cladding Dielectric Waveguide Structure.

This study proposes a highly sensitive refractive-index (RI) sensor based on a TM0 waveguide mode resonance excited in an asymmetric metal-cladding dielectric waveguide structure, where the analyte serves as the guiding layer. By scanning the wavelength at fixed angles of incidence, the reflection spectra of the sensor were obtained. The results showed that the resonance wavelength redshifted dramatically with increases in the analyte RI, which indicates that this approach can be used to sense both the resonance wavelength and the analyte RI. Based on this approach, we investigated the sensing properties, including the sensitivity and figure of merit, at fixed incident angles of 60° and 45°, at which the sensitivity of the sensor reached 7724.9 nm/RIU (refractive index units) and 1339 nm/RIU, respectively. Compared with surface plasmon resonance sensors, which are based on a similar structure, the proposed sensor can accept a more flexible range of incident angles and a wider sensing range of analyte RI. This approach thus has tremendous potential for use in numerous sensing domains, such as biochemical and medical analyses.

Prevalence and characterization of BRCA1 and BRCA2 germline mutations in Chinese women with familial breast cancer.

Although there are some studies to investigate germline mutations in BRCA1/2 genes in Chinese women with familial breast cancer, many of them suffer relatively small sample size. In this study, we screened germline mutations in BRCA1/2 genes in a cohort of 409 Chinese women with familial breast cancer from north China by using a PCR-sequencing assay. A total of 43 deleterious mutations in BRCA1/2 genes were identified in this cohort, including 17 novel mutations and 6 recurrent mutations. The frequencies of BRCA1 and BRCA2 mutations were 3.9% (16/409) and 6.6% (27/409), respectively; the mutation rate of BRCA2 was 1.7-fold higher than that of BRCA1. The entire mutation rate of BRCA1/2 was 10.5% in this cohort; however, the mutation rate of BRCA1/2 genes was 23.0% in 78 familial breast cancer patients whose tumors were diagnosed at or before the age of 40. The mean age at diagnosis of breast cancer in BRCA1 carriers (42.8 years) and BRCA2 carriers (45.1 years) was younger than non-carriers (51.0 years) in this cohort (P = 0.005; P = 0.01, respectively). In addition, both BRCA1 carriers and BRCA2 carriers were more likely to exhibit triple-negative breast cancer (ER-, PgR-, and HER2-) than non-carriers (BRCA1 carriers vs. non-carriers, 69.2 vs. 23.0%, P = 0.001; BRCA2 carriers vs. non-carriers, 45.8 vs. 23.0%, P = 0.01). Our study suggested that the spectrum and characteristics of BRCA1/2 mutations in Chinese familial breast cancer exhibit some unique features, and Chinese women with familial breast cancer whose tumors are diagnosed at or before the age of 40 are good candidates for BRCA1/2 testing.