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This study was aimed to identify efficiency  of recurrent  selection program to improve maize population. This program was applied to var. Buhooth 106 with var. 5012  Using RGCA  with the inbred Zm7 for the production of RSCA. The recurrent selection program was implemented for four consecutive seasons (2020 - 2021) at the Fields Station of the College of Agriculture - University of Anbar. In the spring season 2020, 100 top crosses  were obtained from both varieties and progeny.  During the fall season 2020, an experiment was carried out to compare the top crosses of each variety RGCA and RSCA using a 10 × 10 partially balanced lattice design.. Six genotypes from each genetic population as well as Buhooth 106 and 5012 and Zm7 inbreds). The genotype-S1-2 RSCA achieved the lowest female flowering period for females 61.50 days, the highest number of rows per ear 17.80 rows, and the highest grain yield 177.82 g. The genotype-S1-3 RSCA achieved the highest leaf area 0.593 m2 and the highest number of kernels per row 43.11 kernel. The broad sense heritability of the traits of the number of rows and the number of kernels in the row and the yield of the plant reached 53.23%, 73.85% and 41.94%, respectively, and high genetic advance for kernels per row and grain yield of 4.79 and 15.52 respectively.

In this article, we propose a new method of selecting smoothing parameters in semiparametric regression. This method is used in semiparametric regression estimation where the nonparametric component is partially approximated by multivariable Fourier Series and partly approached by multivariable Kernel. Selection of smoothing parameters using the method with Generalized Cross-Validation (GCV). To see the performance of this method, it is then applied to the data drinking water quality sourced from Regional Drinking Water Company (PDAM) Surabaya by using Fourier Series with trend and Gaussian Kernel. The results showed that this method contributed a good performance in selecting the optimal smoothing parameters.

Triple‐negative breast cancer (TNBC) remains a major clinical challenge, owing to its molecular complexity, therapeutic resistance, and lack of specific druggable targets. The herpes simplex virus thymidine kinase/ganciclovir (HSV‐TK/GCV) suicide gene therapy system has shown promise in cancer treatment, but its clinical applicability is limited by off‐target cytotoxicity. Here, we developed a breast cancer‐specific suicide gene circuit (BRAS) that integrates the screened cancer‐specific promoters RRM2 and MAFK with a microRNA specific to nontumor cells, utilizing the distinct molecular profiles of tumor and nontumor cells. This multi‐input logic gate circuit enables precise, specific expression of HSV‐TK in breast cancer cells with hardly expression in normal cell. We show that BRAS selectively induces apoptosis in patient‐derived TNBC cells while sparing normal cells. In two orthotopic breast cancer models, BRAS significantly suppressed tumor growth without affecting body weight or general health, underscoring its therapeutic potential. This approach intelligently combines molecular signals from both cancerous and healthy cells to precisely regulate therapeutic gene expression, making it a promising platform for the next‐generation cancer therapy. The BRAS comprises two modular genetic components driven by distinct tumor‐specific promoters and a failsafe layer with the NOT gate. This multi‐input logic gate circuit enables precise, specific expression of HSV‐TK in breast cancer cells with hardly expression in normal cell and effectively inhibits tumor growth in a triple‐negative breast cancer mouse model without off‐target toxicity.

A field experiment was conducted in the fields of the college of Agriculture - University of Anbar (alternative location) during winter seasons in 2015-2016 and 2016-2017. To study the effect of spraying with four concentrations of Humiforte 0, 2, 4 and 6 L.ha−1 on growth and yield of four Oats cultivars. The layout of the experiment was split plot design according to RCBD design with three replicates. The results showed the following: The characters of the yield and yield components of oats were studied in terms of performance and variability and calculated the values of genetic and environmental variability and the heterogeneity, phenotypic and inheritance. The highest percentage of genetic variations to the environment 7.2, 10.9 and 13, 7 for the flag leaf area and the number of grains by the raceme in both seasons. the highest percentage of heritability was found in flag leaf area reached 87.8%, 91.60 and the number of grains by the raceme which reached 92.72% and 87.36% in both seasons. The concentration of 6 L.ha−1 was superior compared to the other concentrations in plant height, leaf area, number of branches per plant, leaf content of chlorophyll, yield components and grain yield 6.01 and 6.29 ton.ha−1 in both seasons respectively. Genzaniya and Hamel cultivars gave the lowest number of days to reach the flowering stage, while Gensaniya cultivar gave the highest plant height, leaf area, chlorophyll leaf content, number of grains by raceme and grain yield 5.47 and 6.48 ton.ha−1 in both seasons respectively. However, Shefaa was superior in the weight of 500 grains in both seasons. The interaction between the study factors was significant in most of the studied characters. The treatment of Gensaniya at the concentration of 6 L.ha−1 gave the highest grain yield reached 6.86 and 7.22 ton.ha−1 in both seasons respectively. We conclude from this results that most components of the crop are more influenced by genetics factors. Therefore, we recommend the adoption of the number of grains per raceme in the assessment of productive capacity of the oats grains.

Tuning parameter selection is of critical importance for kernel ridge regression. To date, a data-driven tuning method for divide-and-conquer kernel ridge regression (d-KRR) has been lacking in the literature, which limits the applicability of d-KRR for large datasets. In this article, by modifying the generalized cross-validation (GCV) score, we propose a distributed generalized cross-validation (dGCV) as a data-driven tool for selecting the tuning parameters in d-KRR. Not only the proposed dGCV is computationally scalable for massive datasets, it is also shown, under mild conditions, to be asymptotically optimal in the sense that minimizing the dGCV score is equivalent to minimizing the true global conditional empirical loss of the averaged function estimator, extending the existing optimality results of GCV to the divide-and-conquer framework. Supplemental materials for this article are available online.

Chemosensitivity is one of the key factors affecting the therapeutic effect on cancer, but the clinical application of corresponding drugs is rare. Hypoxia, a common feature of many solid tumors, including hepatocellular carcinoma (HCC), has been associated with resistance to chemotherapy in part through the activation of the Sonic Hedgehog (SHh) pathway. Hypoxia has also been associated with the increased SUMOylation of multiple proteins, including GLI family proteins, which are key mediators of SHh signaling, and has become a promising target to develop drug-resistant drugs for cancer treatment. However, there are few target drugs to abrogate chemotherapy resistance. Saikosaponin-d (Ssd), one of the main bioactive components of Radix bupleuri , has been reported to exert multiple biological effects, including anticancer activity. Here, we first found that Ssd inhibits the malignant phenotype of HCC cells while increasing their sensitivity to the herpes simplex virus thymidine kinase/ganciclovir (HSVtk/GCV) drug system under hypoxia in vitro and in vivo . Furthermore, we had explored that GLI family activation and extensive protein SUMOylation were characteristics of HCC cells, and hypoxia could activate the SHh pathway and promote epithelial-mesenchymal transition (EMT), invasion, and chemosensitivity in HCC cells. SUMOylation is required for hypoxia-dependent activation of GLI proteins. Finally, we found that Ssd could reverse the effects promoted by hypoxia, specifically active sentrin/small ubiquitin-like modifier (SUMO)-specific protease 5 (SENP5), a SUMO-specific protease, in a time- and dose-dependent manner while inhibiting the expression of SUMO1 and GLI proteins. Together, these findings confirm the important role of Ssd in the chemoresistance of liver cancer, provide some data support for further understanding the molecular mechanisms of Ssd inhibition of malignant transformation of HCC cells, and provide a new perspective for the application of traditional Chinese medicine in the chemical resistance of liver cancer.

High signal-to-noise ratio (SNR) seismic waveform data are conductive to various studies in seismology. Seismic denoising aims to enhance SNR by eliminating additive noise through signal processing while preserving important features of the seismic signal. Conventional parametric seismic denoising methods often require selecting appropriate parameters to achieve optimal results, which may be limiting when dealing with various types and scales of seismic data. Here, we develop an adaptive parameter-free denoising method by combining general cross-validation (GCV) thresholding and pixel connectivity in synchrosqueezed (SS) domain. In this denoising framework, the synchrosqueezed continuous wavelet transform (SS-CWT) is first applied to obtain a high-resolution time–frequency representation. Then, the GCV approach, which allows for choosing the (nearly) optimal threshold without relying on any prior knowledge about the noise level, is employed to attenuate most of the low-energy noise. After that, the relatively isolated high-energy residual noise remaining in the SS-CWT spectrum is removed using pixel connectivity thresholding. Finally, the inverse SS-CWT is applied to the thresholded spectrum to obtain the denoised seismic record. As the thresholds for GCV and pixel connectivity are derived from the spectrum characteristics of the data being analyzed, the proposed denoising approach is highly adaptive and parameter-free. We demonstrate the effectiveness and versatility of the proposed denoising framework using synthetic data and real seismic data from diverse monitoring scenarios, including land, ocean, and emerging distributed acoustic sensing (DAS). The results indicate that the method is a stable and efficient tool for seismic data denoising. Graphical Abstract

In order to develop high-yielding genotypes of adapted maize, multilocation trials of maize were performed including forty-five maize hybrids exploiting genetic variability, trait associations, and diversity. The experiments were laid out in an RCB design and data were recorded on eight yield and yield-contributing traits, viz., days to anthesis (AD), days to silking (SD), anthesis–silking interval (ASI), plant height (PH), ear height (EH), kernels per ear (KPE), thousand-kernel weight (TKW), and grain yield (GY). An analysis of variance (ANOVA) showed significant variation present among the different traits under study. The phenotypic coefficient of variance (PCV) showed a higher value than the genotypic coefficient of variance (GCV), indicating the environmental influence on the expression of the traits. High heritability coupled with high genetic advance was found for these traits, indicative of additive gene action. The trait associations showed that genotypic correlation was higher than phenotypic correlation. Based on genetic diversity, the total genotypes were divided into four clusters, and the maximum number of 16 genotypes was found in cluster IV. Among the eight yield and yield-contributing traits, PH, ASI, EH, and TKW were the important traits for variability creation and were mostly responsible for yield. Genotypes G5, G8, G27, G29, and G42 were in the top ranks based on grain yield over locations, while a few others showed region-centric performances; all these genotypes can be recommended upon validation for commercial release. The present findings show the existence of proper genetic variability and divergence among traits, and the identified traits can be used in a maize improvement program.

The necessity of energy is continuously increasing, whereas fossil fuel sources are gradually depleting. To mitigate this problem, fish processing waste of the bluespotted stingray (Neotrygon kuhlii), available in the Borneo region, was investigated for an alternative feedstock of bioenergy production. The fish wastes are hazardous for the environment, whereas the biodiesel from fish waste is pollution-free and produces less contaminant gas and carbon dioxide than fossil fuel. From the proximate analysis, the moisture content, volatile matter, fixed carbon, and ash content of the fish waste were achieved as 4.88%, 63.80%, 15.03%, and 16.29%, respectively. The proportion of carbon, hydrogen, nitrogen, sulfur, and oxygen was found as 42.06%, 5.99%, 10.77%, 0.91%, and 40.27%, respectively, from the ultimate analysis. The calorific value was 21.53 MJ/kg, which would be highly effective in biofuel production. The morphology analysis results of the biomass are favorable for renewable energy sources. The major bondage between carbon and hydrogen and oxygen was found using Fourier transform infrared spectroscopy. The thermogravimetric analysis and derivative thermogravimetry revealed that the highest weight loss occurred at 352 °C temperature with a decomposition rate of 4.57 wt.%/min in pyrolysis circumstances, and at 606 °C temperature with a decomposition rate of 3.77 wt.%/min in combustion conditions. In the pyrolysis process for 25 °C/min heating rate, the yield of biochar, bio-oil, and bio-syngas was found as 33.96, 29.34, 23.46% at 400 °C, 47.72, 49.32, 33.87% at 500 °C, and 18.32, 21.34, 42.37% at 600 °C, respectively. The characteristics and pyrolysis yields of fish waste are suitable for being an effective renewable energy source.

Efflux transporters, namely ATP-binding cassette (ABC), are one of the primary reasons for cancer chemoresistance and the clinical failure of chemotherapy. Ganciclovir (GCV) is an antiviral agent used in herpes simplex virus thymidine kinase (HSV-TK) gene therapy. In this therapy, HSV-TK gene is delivered together with GCV into cancer cells to activate the phosphorylation process of GCV to active GCV-triphosphate, a DNA polymerase inhibitor. However, GCV interacts with efflux transporters that are responsible for the resistance of HSV-TK/GCV therapy. In the present study, it was explored whether GCV and its more lipophilic derivative (1) could inhibit effluxing of another chemotherapeutic, methotrexate (MTX), out of the human breast cancer cells. Firstly, it was found that the combination of GCV and MTX was more hemocompatible than the corresponding combination with compound 1. Secondly, both GCV and compound 1 enhanced the cellular accumulation of MTX in MCF-7 cells, the MTX exposure being 13–21 times greater compared to the MTX uptake alone. Subsequently, this also reduced the number of viable cells (41–56%) and increased the number of late apoptotic cells (46–55%). Moreover, both GCV and compound 1 were found to interact with breast cancer resistant protein (BCRP) more effectively than multidrug-resistant proteins (MRPs) in these cells. Since the expression of BCRP was higher in MCF-7 cells than in MDA-MB-231 cells, and the cellular uptake of GCV and compound 1 was smaller but increased in the presence of BCRP-selective inhibitor (Fumitremorgin C) in MCF-7 cells, we concluded that the improved apoptotic effects of higher MTX exposure were raised mainly from the inhibition of BCRP-mediated efflux of MTX. However, the effects of GCV and its derivatives on MTX metabolism and the quantitative expression of MTX metabolizing enzymes in various cancer cells need to be studied more thoroughly in the future.