Pyramiding genes related to grain quality and resistance through marker assisted selection (MAS) is an important approach in rice breeding programs. Marker-assisted selection can be used for monitoring the presence or absence of these genes in breeding populations and can be combined with conventional breeding approaches. This study is a part of cultivar development program in Iran through integration of conventional breeding with marker assisted selection. Crosses between two high yielding transgenic lines carrying an insect resistance gene (cry1Ab, from Bacillus thuringiensis) with a local aromatic variety were made followed by selection for incorporation of insect resistance and aroma (FGR) genes in desirable single F2 plants. Finally, plants homozygous for aroma and carryingcry1Ab genes with good agronomic performance were identified. Further analyses are underway on these plants in F3 generation. These plants promise to develop new aromatic Bt rice lines through integration of classical and molecular breeding in the near future in Iran.

Background: Melanoma is an aggressive tumor caused by melanocytes characterized by a poor prognosis at the stage of metastasis. Therefore, it is crucial to identify biomarkers for progression and prognosis for the treatment of melanoma. Objectives: The study aimed to identify the specific genes related to the prognosis of melanoma utilizing bioinformatics analyses. Methods: Differentially expressed genes (DEGs) between melanoma tissues and normal tissues were screened from the GSE 3, 189 gene expression profile of Gene Expression Omnibus (GEO). A co-expression network was constructed by weighted correlation network analysis (WGCNA). Functional enrichment analysis for DEGs was performed. The risk prognostic model and nomogram predictive model were established utilizing the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. Results: Using the differential expression analysis and WGCNA, 1, 408 DEGs were screened between melanoma tissues and normal tissues. Functional enrichment analysis proved that these genes primarily participated in the cell cycle and mitotic phase regulation in cancer. In addition, 17 optimal DEGs were identified for constructing the risk score prognostic model. Cox regression analysis further revealed that ectonucleotide pyrophosphatase/phosphodiesterase 4 (ENPP4) and FGR proto-oncogene, Src family tyrosine kinase (FGR) were the key genes significantly associated with survival. A nomogram prediction model was established for individual survival probability by integrating pathological T/N/M stage, age, ENPP4, and FGR. High FGR or ENPP4 expression indicated a better prognosis in melanoma patients. Conclusion: This study identified FGR and ENPP4 as potentially useful prognostic biomarkers for melanoma. The corresponding risk score prognostic model and nomogram may be a reliable tool for predicting the prognosis of melanoma patients.

Background: Cortical folding during fetal brain development reflects neural maturation. Fetal growth restriction (FGR) may disrupt this process, potentially affecting neurodevelopmental outcomes. Although ultrasound enables noninvasive sulcal assessment, so normative data and objective tools are lacking. The purpose of the current study was to assess the impact of FGR on fetal cortical development using neurosonography and establish a third-trimester nomogram for cortical maturation. Methods: This prospective study included 425 singleton pregnancies (330 appropriate-for-gestational-age [AGA], 54 symmetrical FGR, and 41 asymmetrical FGR) at 28–36 weeks. Conducted at a Tehran tertiary center (2023–2024), the study included cases with normal anatomy and negative aneuploidy screening. Neurosonographic parameters including Sylvian fissure (SF), insula, parieto-occipital fissure (POF), cavum septum pellucidum (CSP) width, and ventricular diameter were measured and the ratios calculated relative to biparietal diameter (BPD). ANOVA and post-hoc tests were applied and statistical significance was set at p<0. 05. Results: No significant differences in neurosonographic ratios (e. g., SF/Insula, POF/ BPD, CSPW/BPD) were found between AGA and FGR groups. However, unadjusted SF and insular depths were reduced in symmetrical FGR fetuses with head circumference (HC) <10th percentile. Asymmetrical FGR showed no differences. A gestational-age-based nomogram was developed for AGA fetuses. Conclusion: While absolute sulcal measurements vary with head size in FGR, biometric adjustments (e. g., BPD ratios) improve cortical maturation assessment. The study supports ratio-based neurosonography and provides normative data for objective fetal brain evaluation.

Background: To investigate the role of pregnant-associatedplasma protein A (PAPP-A) and uterine artery Doppler ultrasound in predicting fetal growth restriction (FGR). Materials and Methods: In total, 120 pregnant women diagnosed with FGR in Shijiazhuang Obstetrics and Gynecology Hospital from January 2021 to December 2023 were selected as the FGR group, and 120 normal pregnant women were selected as the control group during the identical time frame. Maternal serum pregnancy-related protein A combined with uterine artery Doppler ultrasonography was performed during the period from the 11th, to the 13th+6 weeks of pregnancy. The course of pregnancy was observed in both groups of pregnant women. Results: The FGR group exhibited significantly reduced rates of vaginal delivery and fetal survival compared to the control group, while experiencing higher rates of preterm delivery and cesarean section, with statistical significance (P<0.001). The pulsatility index of the uterine artery (UtA-PI) and the resistance index of the uterine artery and the FGR group exhibited a higher proportion of early blood diastolic incisors compared to the normal group, with statistical significance noted at a level of P<0.001. The concentration of PAPP-A was lower than that of normal group (P<0.001). The sensitivity of combining UtA-PI and PAPP-A to predict FGR was 81.6%, and the sensitivity of combining UtA-PI and PAPP-A is 82.9%, which is 1.3% higher, but there was no statistically significant distinction between the two approaches (P>0.05). Conclusion: The implementation the combination between PAPP-A and Doppler ultrasound is an effective method to predict FGR.