Gene expression analysis provides a minimally invasive approach for biological dosimetry. To advance point-of-care applications, this study aimed to establish and validate an improved gene expression biodosimetry system by employing an expanded panel of radiation-responsive genes in human peripheral blood. Human B lymphoblastoid cells (AHH-1) and peripheral blood from 10 healthy donors were irradiated with ⁶⁰Co γ-rays at doses of 0, 1, 2, 4, 6, and 8 Gy (dose rate: 1 Gy/min). The expression patterns of four candidate transcriptional biomarkers (ZMAT3, SESN1, AEN, and TRIAP1) and a panel of radiation-responsive genes were characterized at 6–48 h post-irradiation. The impact of different dose rates (0.2, 1, and 2 Gy/min) on these gene expressions was also investigated. For each gene, calibration curves were established by fitting a linear regression between the logarithm of absorbed dose and ΔCt values. Gene selection and model construction were performed using stepwise regression to obtain optimized multi-gene models. The accuracy of these dosimetry models for dose prediction was validated in independent ex vivo and in vivo cohorts. The four candidate genes exhibited robust, dose-dependent expression from 6 to 48 h post-irradiation, independent of dose-rate variations (0.2–2 Gy/min). Most genes in the expanded panel, including the candidates, showed strong linear relationships between log2 of dose and ΔCt values across all time points when the 0 Gy point was excluded from regression (R² > 0.90, S < 0.50). Based on these validated genes, optimized multi-gene models achieved high predictive accuracy (R² = 0.81–0.89) with fewer genes. Furthermore, these improved models demonstrated accurate dose estimation capabilities when validated with both ex vivo- and in vivo-irradiated peripheral blood samples. Our study expanded the panel of reliable radiation biomarkers and developed optimized multi-gene models for accurate dose estimation, thereby advancing the standardization and practicality of gene expression biodosimetry.

Gene expression analysis provides a minimally invasive approach for biological dosimetry. To advance point-of-care applications, this study aimed to establish and validate an improved gene expression biodosimetry system by employing an expanded panel of radiation-responsive genes in human peripheral blood. Human B lymphoblastoid cells (AHH-1) and peripheral blood from 10 healthy donors were irradiated with ⁶⁰Co γ-rays at doses of 0, 1, 2, 4, 6, and 8 Gy (dose rate: 1 Gy/min). The expression patterns of four candidate transcriptional biomarkers (ZMAT3, SESN1, AEN, and TRIAP1) and a panel of radiation-responsive genes were characterized at 6–48 h post-irradiation. The impact of different dose rates (0.2, 1, and 2 Gy/min) on these gene expressions was also investigated. For each gene, calibration curves were established by fitting a linear regression between the logarithm of absorbed dose and ΔCt values. Gene selection and model construction were performed using stepwise regression to obtain optimized multi-gene models. The accuracy of these dosimetry models for dose prediction was validated in independent ex vivo and in vivo cohorts. The four candidate genes exhibited robust, dose-dependent expression from 6 to 48 h post-irradiation, independent of dose-rate variations (0.2–2 Gy/min). Most genes in the expanded panel, including the candidates, showed strong linear relationships between log2 of dose and ΔCt values across all time points when the 0 Gy point was excluded from regression (R² > 0.90, S < 0.50). Based on these validated genes, optimized multi-gene models achieved high predictive accuracy (R² = 0.81–0.89) with fewer genes. Furthermore, these improved models demonstrated accurate dose estimation capabilities when validated with both ex vivo- and in vivo-irradiated peripheral blood samples. Our study expanded the panel of reliable radiation biomarkers and developed optimized multi-gene models for accurate dose estimation, thereby advancing the standardization and practicality of gene expression biodosimetry.

Zephyranthes carinata is a widely distributed medicinal and ornamental plant. Here, we reported the first complete chloroplast genome using high-throughput sequencing technology. The genome was a molecule with a typical quadripartite structure and spanned 158,355 bp in size, comprising an LSC region of 86,576 bp, an SSC region of 18,313 bp, and two IRs of 26,733 bp each. Its overall GC content was 37.81%. It was annotated with 129 functional genes, including 86 protein-coding, 35 tRNA, and eight rRNA genes. Phylogenetic analysis identified Z. carinata as a basal lineage within the Hippeastrinae subtribe of Amaryllidaceae family, suggesting its ancestral status. This chloroplast genome provides a valuable genetic resource for species identification, population genetics, and phylogenetic studies in Amaryllidaceae.

Zephyranthes carinata is a widely distributed medicinal and ornamental plant. Here, we reported the first complete chloroplast genome using high-throughput sequencing technology. The genome was a molecule with a typical quadripartite structure and spanned 158,355 bp in size, comprising an LSC region of 86,576 bp, an SSC region of 18,313 bp, and two IRs of 26,733 bp each. Its overall GC content was 37.81%. It was annotated with 129 functional genes, including 86 protein-coding, 35 tRNA, and eight rRNA genes. Phylogenetic analysis identified Z. carinata as a basal lineage within the Hippeastrinae subtribe of Amaryllidaceae family, suggesting its ancestral status. This chloroplast genome provides a valuable genetic resource for species identification, population genetics, and phylogenetic studies in Amaryllidaceae.

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A dual-wire arc additive manufacturing (WAAM) strategy via in-situ alloying of AZ71 and Al-2Sc wires was proposed to fabricate a Mg-10.6Al-0.4Zn-0.2Mn-0.05Sc alloy, overcoming the limitation of wire fabrication and achieving synergistic improvement in strength and ductility. After heat treatment, the alloy achieves a yield strength ≥200 MPa with elongation ≥5.2%. In-situ formed Al₈Mn₄Sc acted as heterogeneous nuclei, refining the β-Mg₁₇Al₁₂ and enhancing its dissolution kinetics, thereby improving the ductility. Meanwhile, high Al solubility promotes the precipitation of high-density non-basal β-Mg₁₇Al₁₂ and strengthens the alloy. This work offers a novel methodology for producing high-performance WAAM Mg alloys.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.