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Abstract Raman spectroscopy has tremendous potential for material analysis with its molecular fingerprinting capability in many branches of science and technology. It is also an emerging omics technique for metabolic profiling to shape precision medicine. However, precisely attributing vibration peaks coupled with specific environmental, instrumental, and specimen noise is problematic. Intelligent Raman spectral preprocessing to remove statistical bias noise and sample-related errors should provide a powerful tool for valuable information extraction. Here, we propose a novel Raman spectral preprocessing scheme based on self-supervised learning (RSPSSL) with high capacity and spectral fidelity. It can preprocess arbitrary Raman spectra without further training at a speed of ~1 900 spectra per second without human interference. The experimental data preprocessing trial demonstrated its excellent capacity and signal fidelity with an 88% reduction in root mean square error and a 60% reduction in infinite norm ( $${L}_{{\infty }}$$ L ∞ ) compared to established techniques. With this advantage, it remarkably enhanced various biomedical applications with a 400% accuracy elevation (ΔAUC) in cancer diagnosis, an average 38% (few-shot) and 242% accuracy improvement in paraquat concentration prediction, and unsealed the chemical resolution of biomedical hyperspectral images, especially in the spectral fingerprint region. It precisely preprocessed various Raman spectra from different spectroscopy devices, laboratories, and diverse applications. This scheme will enable biomedical mechanism screening with the label-free volumetric molecular imaging tool on organism and disease metabolomics profiling with a scenario of high throughput, cross-device, various analyte complexity, and diverse applications.

The evening complex (EC) plays a critical role in photoperiod flowering in Arabidopsis. Nevertheless, the underlying functions of individual components and coordinate regulation mechanism of EC genes in rice flowering remain to be elucidated. Here, we characterized the critical role of LUX ARRHYTHMO (LUX) in photoperiod perception and coordinating vegetative growth and flowering in rice. Non-functional alleles of OsLUX extremely extended vegetative phase, leading to photoperiod-insensitive late flowering and great increase of grain yield. OsLUX displayed an obvious diurnal rhythm expression with the peak at dusk and promoted rice flowering via coordinating the expression of genes associated with the circadian clock and the output integrators of photoperiodic flowering. OsLUX combined with OsELF4a and OsELF3a or OsELF3b to form two ECs, of which the OsLUX-OsELF3a-OsELF4a was likely the dominant promoter for photoperiodic flowering. In addition, OsELF4a was also essential for promoting rice flowering. Unlike OsLUX, loss OsELF4a displayed a marginal influence under short-day (SD) condition, but markedly delayed flowering time under long-day (LD) condition. These results suggest that rice EC genes share the function of promoting flowering. This is agreement with the orthologs of SD plant, but opposite to the counterparts of LD species. Taken together, rice EC genes display similar but not identical function in photoperiodic flowering, probably through regulating gene expression cooperative and independent. These findings facilitate our understanding of photoperiodic flowering in plants, especially the SD crops.

Abstract Background Famitinib is a tyrosine kinase inhibitor against multiple targets, including vascular endothelial growth factor receptor 2/3, platelet-derived growth factor receptor, and stem cell factor receptor (c-kit). Previous studies have demonstrated anti-tumour activities of famitinib against a wide variety of advanced-stage solid cancers. We aimed to determine the safety and efficacy of famitinib with concurrent chemoradiotherapy (CCRT) in patients with locoregionally advanced nasopharyngeal carcinoma (NPC). We also evaluated the feasibility of contrast-enhanced ultrasound (D-CEUS) as a predictor of early tumour response to famitinib and to correlate functional parameters with clinical efficacy. Methods The trial was conducted in subjects with stage III or IVa-b NPC using a 3 + 3 design of escalating famitinib doses. Briefly, subjects received 2 weeks of famitinib monotherapy followed by 7 weeks of famitinib plus CCRT. D-CEUS of the neck lymph nodes was performed at day 0, 8 and 15 after famitinib was administered before starting concurrent chemoradiotherapy. End points included safety, tolerability and anti-tumour activity. Results Twenty patients were enrolled (six each for 12.5, 16.5 and 20 mg and two for 25 mg). Two patients in the 25 mg cohort developed dose-limiting toxicities, including grade 4 thrombocytopenia and grade 3 hypertension. The most common grade 3/4 adverse events were leukopenia, neutropenia and radiation mucositis. D-CEUS tests showed that more than 60% of patients achieved a perfusion parameter response after 2 weeks taking famitinib alone, and the parameter response was associated with disease improvement. In the famitinib monotherapy stage, three patients (15%) showed partial responses. The complete response rate was 65% at the completion of treatment and 95% 3 months after the treatment ended. After a median follow-up of 44 months, the 3-year progression-free survival (PFS) and distant metastasis-free survival were 70% and 75%, respectively. Subjects with a decrease of perfusion parameter response, such as peak intensity decreased at least 30% after 1 week of famitinib treatment, had higher 3-year PFS (90.9% vs. 44.4%, 95% CI 73.7%–100% vs. 11.9%–76.9%, P

Abstract Background Vaccine has been one of the most successful public health interventions to date. However, vaccines are pharmaceutical products that carry risks so that many adverse events (AEs) are reported after receiving vaccines. Traditional adverse event reporting systems suffer from several crucial challenges including poor timeliness. This motivates increasing social media-based detection systems, which demonstrate successful capability to capture timely and prevalent disease information. Despite these advantages, social media-based AE detection suffers from serious challenges such as labor-intensive labeling and class imbalance of the training data. Results To tackle both challenges from traditional reporting systems and social media, we exploit their complementary strength and develop a combinatorial classification approach by integrating Twitter data and the Vaccine Adverse Event Reporting System (VAERS) information aiming to identify potential AEs after influenza vaccine. Specifically, we combine formal reports which have accurately predefined labels with social media data to reduce the cost of manual labeling; in order to combat the class imbalance problem, a max-rule based multi-instance learning method is proposed to bias positive users. Various experiments were conducted to validate our model compared with other baselines. We observed that (1) multi-instance learning methods outperformed baselines when only Twitter data were used; (2) formal reports helped improve the performance metrics of our multi-instance learning methods consistently while affecting the performance of other baselines negatively; (3) the effect of formal reports was more obvious when the training size was smaller. Case studies show that our model labeled users and tweets accurately. Conclusions We have developed a framework to detect vaccine AEs by combining formal reports with social media data. We demonstrate the power of formal reports on the performance improvement of AE detection when the amount of social media data was small. Various experiments and case studies show the effectiveness of our model.

OsMADS16, a class B floral organ identity gene, plays a pivotal role in stamen formation in rice. To date, little is known about the interacting partners of OsMADS16 except for several MADS-box proteins. In this study, we constructed a high-quality cDNA library of young panicles (< 5 cm in length) and performed yeast two-hybrid (Y2H) screening using OsMADS16 as bait. Eleven candidate proteins interacting with OsMADS16 were identified by Y2H and validated by BiFC and Co-IP assays. Subcellular localization results further confirmed the possibility of the interactions of OsMADS16 with 10 of the candidate proteins in natural rice cells. Bioinformatics analysis indicated that these partners exerted various molecular, cellular and physiological functions. Some of them were known or likely to be related to reproductive events, such as stamen primordium initiation, differentiation and development (OsMADS2, OsMADS4 and OsCOP9) and pollen development (OsbHLH40 and Os6PGDH). Our results provide an important reference for further research on OsMADS16-mediated regulation mechanism on floral organ development and pollen formation.

BACKGROUND:Aberrant expression of C-X-C motif chemokine 5 (CXCL5) contributes to the progression of various cancers. This study analyzed the clinical significance of serum CXCL5 (sCXCL5) levels of nasopharyngeal carcinoma (NPC) patients, with the goal of building a novel prognostic score model. EXPERIMENTAL DESIGN:Serum samples were collected prior to treatment from 290 NPC patients for the detection of sCXCL5 with ELISA. Half of the patients (n = 145) were randomly assigned to the training set to generate the sCXCL5 cutoff point using receiver operator characteristic (ROC) analysis, while the other half (n = 145) were assigned to the testing set for validation. Associations between sCXCL5 levels and clinical characteristics were analyzed. A prognostic score model was built using independent predictors derived from multivariate analysis. A concordance index (C-Index) was used to evaluate prognostic ability. RESULTS:The sCXCL5 cutoff point was 0.805 ng/ml. Sex, age, histology, T classification, clinical classification and local recurrence were not associated with sCXCL5 levels. However, sCXCL5 levels were positively associated with N classification, distant metastasis and disease progression (P

Pom2 is predicted to be a dual-specificity tyrosine-phosphorylation regulated kinase (DYRK) related to Pom1 in Schizosaccharomyces pombe. DYRKs share a kinase domain capable of catalyzing autophosphorylation on tyrosine and exogenous phosphorylation on serine/threonine residues. Here we show that Pom2 is functionally different from the well-characterized Pom1, although they share 55% identity in the kinase domain and the Pom2 kinase domain functionally complements that of Pom1. Pom2 localizes to mitochondria throughout the cell cycle and to the contractile ring during late stages of cytokinesis. Overexpression but not deletion of pom2 results in severe defects in cytokinesis, indicating that Pom2 might share an overlapping function with other proteins in regulating cytokinesis. Gain and loss of function analyses reveal that Pom2 is required for maintaining mitochondrial morphology independently of microtubules. Intriguingly, most meiotic pom2Δ cells form aberrant asci with meiotic and/or forespore membrane formation defects. Taken together, Pom2 is a novel DYRK kinase involved in regulating cytokinesis, mitochondrial morphology, meiosis, and sporulation in fission yeast.