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In general multiple medical devices orthogonal frequency-division multiplexing (OFDM) communication systems, all the interfering medical users are legitimate but will cause disturbance to the desired user. In this work, we evaluate three deep learning (DL) algorithms: fully connected deep neural networks, convolutional neural networks, and long short-term memory neural networks for signal processing and detection in uncoded multiple medical devices OFDM communications systems. The bit error rates (BER) of these DL methods are compared with the conventional linear minimum mean squared error (LMMSE) detector. Additionally, the relationships between the BER and signal-to-interference ratio, signal-to-noise ratio, the number of interferences, and modulation type are investigated. Numerical results show that DL methods outperform LMMSE under different multiple medical device interference situations and are robust when the wireless channel has high variability. Also, DL methods are proven to have strong anti-interference ability and are useful in multiple medical devices OFDM systems.

This study aimed to characterize carotenoid profiles and unravel the genetic mechanisms underlying flesh color variation in white and yellow-fleshed peaches, with a focus on the hybrid cultivar ‘ZY29’ derived from two white-fleshed parents (‘Yulu’ and ‘Hujing Honey Dew’). Using UPLC-APCI-MS/MS, we quantified carotenoids in the pericarp (exocarp) and flesh (mesocarp) of parental and hybrid fruits. Results showed that ‘ZY29’ accumulated significantly higher levels of β-carotene and lutein compared to its white-fleshed parents. Transcriptome analysis revealed upregulation of carotenoid biosynthesis genes (PSY, LCYB, and ZDS) and downregulation of the carotenoid cleavage gene CCD4 in ‘ZY29’, explaining enhanced carotenoid accumulation. Integrative metabolome-transcriptome analysis identified core regulatory networks associated with metabolic shifts, including transcription factors (MYB and WRKY). These findings provide novel insights into the molecular basis of yellow flesh formation in peaches, offering potential targets (PSY and LCYB) and metabolic markers (β-carotene and lutein) for breeding nutritionally enriched cultivars. These findings contribute to a better understanding of the genetic factors and parental regulatory mechanisms involved in the formation of yellow flesh color in peaches. Our results have important implications for breeding new peach varieties with desirable color and nutritional qualities and may provide valuable insights for future research in this area.

Using large-scale analysis of protein interactions and bioinformatics, Li et al . describe the organization of the core-scaffold machinery of the postsynaptic density and its assembly in protein-interaction networks. The authors show how mutations associated with complex brain disorders are distributed along spatiotemporal protein complexes and modulate their protein interactions. The postsynaptic density (PSD) contains a collection of scaffold proteins used for assembling synaptic signaling complexes. However, it is not known how the core-scaffold machinery associates in protein-interaction networks or how proteins encoded by genes involved in complex brain disorders are distributed through spatiotemporal protein complexes. Here using immunopurification, proteomics and bioinformatics, we isolated 2,876 proteins across 41 in vivo interactomes and determined their protein domain composition, correlation to gene expression levels and developmental integration to the PSD. We defined clusters for enrichment of schizophrenia, autism spectrum disorders, developmental delay and intellectual disability risk factors at embryonic day 14 and adult PSD in mice. Mutations in highly connected nodes alter protein–protein interactions modulating macromolecular complexes enriched in disease risk candidates. These results were integrated into a software platform, Synaptic Protein/Pathways Resource (SyPPRes), enabling the prioritization of disease risk factors and their placement within synaptic protein interaction networks.

Sweet cherry (Prunus avium L.), renowned for its vibrant color and distinctive flavor, enjoys widespread popularity and is planted in temperate climates. This study investigated four short-chilling requirement cultivars in southeast China, which is known as a subtropical climate region, and determined several key fruit qualities, such as color, size, weight, and nutrient attributes (e.g., vitamin C, soluble sugar, organic acid, protein, gibberellin, and brassinolide) at four maturities due to the climate’s effect on the fruit color and the main color substance: anthocyanin accumulation. Therefore, the color index (a*, b*, and L*) and anthocyanin content were determined, and the anthocyanin-related gene expression was quantitative and analyzed using WGCNA. The results showed that the red variety, ‘Jiangnanhong’, exhibited the highest fruit weight and diameter as well as the greatest concentration of cyanidin-3-rutinoside (C3R). Conversely, the yellow variety, ‘Chaoyang 1’, demonstrated higher L* and b* values along with a greater vitamin C content. The research confirmed that C3R is the predominant anthocyanin present in sweet cherries during ripening. Additionally, three genes—LOC110744862, LOC110749842, and LOC110753376—were identified as playing crucial roles in anthocyanin biosynthesis. Anthocyanins significantly influence both the visual appeal and nutritional quality of the fruit. These results provide a theoretical foundation for understanding the differences among sweet cherry varieties in southeast China.

Peach (Prunus persica (L.)) fruits are abundant in nutrients, with fruit shape and sugar content serving as critical indicators of fruit quality. Melatonin plays a pivotal role in peach fruit development; however, the mechanisms by which it regulates fruit shape development, sugar metabolism, and secondary metabolites remain largely unknown. In this study, peach trees were sprayed with 150 µM melatonin 20 days after pollination. Traditional methods were used to investigate fruit morphology, total soluble solids (TSSs), and titratable acidity content (TAC), while liquid chromatography–mass spectrometry (LC-MS) was employed to analyze sugar metabolites during fruit development. The results indicated that melatonin treatment augmented the transverse and longitudinal diameters of peach fruits by 12% and 6%, respectively, and elevated the contents of soluble solids and titratable acid by 7% and 6%, respectively. The single fruit weight experienced a significant increase of 29.4%, whereas fruit firmness at maturity remained unchanged. Metabolite analysis demonstrated that melatonin decreased the levels of sucrose and D-sorbitol in mature fruits but enhanced the accumulation of D-fructose, L-rhamnose, and xylose. Significantly, melatonin expedited the degradation of galactose, D-mannose, and methyl-D-pyranogalactoside prior to maturity (all three substances naturally decline with fruit ripening), highlighting its role in promoting fruit ripening. In conclusion, exogenous melatonin improves the internal nutrition and flavor quality of fruit by regulating the accumulation of primary and secondary metabolites during fruit ripening. Specifically, the increase in D-fructose (a major contributor to sweetness) and L-rhamnose (a potential precursor for aroma compounds) enhances fruit flavor profile. The accelerated degradation of galactose, D-mannose, and methyl-D-pyranogalactoside (components of cell wall polysaccharides) prior to maturity, alongside the metabolic shift favoring fructose accumulation over sucrose, highlights melatonin’s role in promoting fruit ripening and softening processes. It also promotes fruit enlargement and single fruit weight without affecting fruit firmness. This study establishes a theoretical basis for the further investigation of the molecular mechanisms underlying melatonin’s role in peach fruits and for enhancing quality-focused breeding practices.

BACKGROUNDAxicabtagene ciloleucel (axi-cel), anti-CD19 chimeric antigen receptor (CAR) T cell therapy, demonstrated remarkable efficacy with manageable toxicity in relapsed/refractory indolent B cell lymphomas in the ZUMA-5 trial.METHODSHere, we report associations of product attributes, serum biomarkers, clinical features, and tumor characteristics with outcome in 124 patients with follicular lymphoma (FL).RESULTSIn univariate and multivariate analyses, pretreatment inflammatory markers, including TNF-α and IL-12p40, as well as total metabolic tumor volume (TMTV), associated with disease progression. Conversely, T-naive-like product phenotype associated with improved outcome, particularly in patients with high TMTV. These covariates improved risk stratification when combined with the FL International Prognostic Index. Postinfusion, CAR T cell expansion associated with improved outcome, while serum inflammatory and immunomodulatory markers, including TNF-α, associated with disease progression and occurrence of high-grade cytokine release syndrome or neurologic events, presenting targets to improve the therapeutic index of axi-cel in FL. Tumor gene expression profiling revealed that both type I and II IFN signaling associated with disease progression and higher expression of T cell exhaustion markers, including TIM3 and LAG3. Pre- or posttreatment CD19 expression on tumor was not associated with outcome.CONCLUSIONThese findings offer insights into mechanisms of resistance and toxicity, risk stratification, and strategies for development of next generation CAR-T approaches.TRIAL REGISTRATIONClinicalTrials.gov NCT03105336.FUNDINGKite, a Gilead Company.

The Internet economy is flourishing, and the form of consumption has shifted from offline brick-and-mortar shopping to online consumption. At the same time, COVID-19 led to many offline stores being constrained in many ways, accelerating the conversion of shopping. The purpose of the study is to enable users to effectively use mobile products and optimize their service experience during furniture consumption. This study compares the relevant theories and the current state of research. Through qualitative and quantitative methods, user needs are investigated and data analysis is conducted to summarize interface improvement suggestions. The high-fidelity prototype design was conducted, and the interactive prototype was delivered to users for testing to verify the effect and feasibility of interface optimization and to propose improvement suggestions for the mobile terminal of furnishings.

The diversity of fruit color in sweet cherry (Prunus avium L.) has been attributed to the presence of either anthocyanin or carotenoid. We profiled the anthocyanin and carotenoid metabolites to investigate the different pigments and the underlying regulatory mechanisms of differential expression genes (DEGs) between red and yellow fruits of sweet cherry. We profiled two cultivars, ‘Jiangnanhong’(JNH, red fruits) and ‘Chaoyang’(CY, yellow fruits) to establish their anthocyanin and carotenoid metabolites by LC-MS/MS and transcriptome analysis by RNA-seq to test the difference in gene expression and metabolic substances between the two varieties. Cyanidin-3-O-rutinoside was the most different pigment between two cultivars, the content of which in red fruit was significantly higher than in the yellow one during the whole ripening stage (stage 3 and stage 4). The total carotenoid content in the two color types of fruits was close, but the content in yellow fruit was shown to be more stable after harvest. Based on the transcriptome data, the heatmap of selected structural DEGs showed that all of the anthocyanin genes expressed significantly higher levels in red fruits than that in yellow fruits. Two unigenes encoding chalcone synthase (CHS) and UDP glucose-flavonoid 3-O-glucosyltransferase (UFGT) were expressed 1134.58 and 1151.24 times higher in red than in yellow fruits at stage 4, respectively. Correlation analysis showed that anthocyanin genes in JNH were negatively correlated with those in CY; by contrast, there were some strong correlations observed between the two cultivars in carotenoid genes. Thus, the coloration of sweet cherry was mainly attributed to anthocyanin-related genes.

Background The identification of genes responsible for human inherited diseases is one of the most challenging tasks in human genetics. Recent studies based on phenotype similarity and gene proximity have demonstrated great success in prioritizing candidate genes for human diseases. However, most of these methods rely on a single protein-protein interaction (PPI) network to calculate similarities between genes, and thus greatly restrict the scope of application of such methods. Meanwhile, independently constructed and maintained PPI networks are usually quite diverse in coverage and quality, making the selection of a suitable PPI network inevitable but difficult. Methods We adopt a linear model to explain similarities between disease phenotypes using gene proximities that are quantified by diffusion kernels of one or more PPI networks. We solve this model via a Bayesian approach, and we derive an analytic form for Bayes factor that naturally measures the strength of association between a query disease and a candidate gene and thus can be used as a score to prioritize candidate genes. This method is intrinsically capable of integrating multiple PPI networks. Results We show that gene proximities calculated from PPI networks imply phenotype similarities. We demonstrate the effectiveness of the Bayesian regression approach on five PPI networks via large scale leave-one-out cross-validation experiments and summarize the results in terms of the mean rank ratio of known disease genes and the area under the receiver operating characteristic curve (AUC). We further show the capability of our approach in integrating multiple PPI networks. Conclusions The Bayesian regression approach can achieve much higher performance than the existing CIPHER approach and the ordinary linear regression method. The integration of multiple PPI networks can greatly improve the scope of application of the proposed method in the inference of disease genes.

Background The phytohormone ethylene is involved in a wide range of developmental processes and in mediating plant responses to biotic and abiotic stresses. Ethylene signalling acts via a linear transduction pathway leading to the activation of Ethylene Response Factor genes ( ERF ) which represent one of the largest gene families of plant transcription factors. How an apparently simple signalling pathway can account for the complex and widely diverse plant responses to ethylene remains yet an unanswered question. Building on the recent release of the complete tomato genome sequence, the present study aims at gaining better insight on distinctive features among ERF proteins. Results A set of 28 cDNA clones encoding ERFs in the tomato ( Solanum lycopersicon ) were isolated and shown to fall into nine distinct subclasses characterised by specific conserved motifs most of which with unknown function. In addition of being able to regulate the transcriptional activity of GCC-box containing promoters, tomato ERFs are also shown to be active on promoters lacking this canonical ethylene-responsive-element. Moreover, the data reveal that ERF affinity to the GCC-box depends on the nucleotide environment surrounding this cis -acting element. Site-directed mutagenesis revealed that the nature of the flanking nucleotides can either enhance or reduce the binding affinity, thus conferring the binding specificity of various ERFs to target promoters. Based on their expression pattern, ERF genes can be clustered in two main clades given their preferential expression in reproductive or vegetative tissues. The regulation of several tomato ERF genes by both ethylene and auxin, suggests their potential contribution to the convergence mechanism between the signalling pathways of the two hormones. Conclusions The data reveal that regions flanking the core GCC-box sequence are part of the discrimination mechanism by which ERFs selectively bind to their target promoters. ERF tissue-specific expression combined to their responsiveness to both ethylene and auxin bring some insight on the complexity and fine regulation mechanisms involving these transcriptional mediators. All together the data support the hypothesis that ERFs are the main component enabling ethylene to regulate a wide range of physiological processes in a highly specific and coordinated manner.