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目的探讨妊娠合并肾移植术后的患者的妊娠结局。方法回顾性分析2015年1月至2021年5月在中山大学附属第一医院住院分娩的12例妊娠合并肾移植术后的患者的临床资料，并随访妊娠结局。结果12例肾移植术后患者中，3例足月分娩，9例未足月分娩。患者平均分娩年龄（32.3±4.5）岁，距离肾移植平均时间为（63.3±34.7）月，平均分娩孕周为（34.8±2.3）周。所有患者孕期的免疫抑制方案为他克莫司+泼尼松+硫唑嘌呤，孕期监测他克莫司血药浓度均在有效范围，其中6例患者孕早期吗替麦考酚酯更换为硫唑嘌呤。12例患者中7例妊娠晚期并发子痫前期，妊娠期糖尿病3例，中度贫血4例，轻度贫血2例，中央性前置胎盘1例。剖宫产11例，阴道分娩1例，均无产后出血和产褥感染，其中2例患者在产后42 d复查肾功能，出现移植肾功能不全，需透析治疗。12例新生儿均为单胎活产，平均出生体质量为（2 348±698.8） g，低出生体质量儿7例，转NICU 8例，出生时均无出生缺陷，平均住院天数14 d，均为人工喂养，随访中生长发育指标均达标，未发生免疫系统缺陷。结论肾移植术后妊娠是高危妊娠，需在多学科协作诊疗团队密切监护下，制定个体化的精准治疗方案，选择适当的妊娠时机、严密母胎监护，适时终止妊娠，方可改善妊娠合并肾移植术后的患者的妊娠结局。

【目的】探讨SPAG5对卵巢高级别浆液性癌细胞生长及紫杉醇药物敏感性的影响，分析原发灶组织中表达水 平差异与患者预后关系。【方法】体外实验中通过瞬时敲降卵巢腺癌细胞株中SPAG5，紫杉醇处理细胞后，MTT法检测细胞 活力及绘制细胞生长曲线，研究SPAG5对细胞生长增殖及紫醇敏感性的影响；然后通过免疫组织化学染色，研究110例患 者组织中SPAG5表达水平与患者预后的关系。【结果】SKOV3细胞中敲降SPAG5后发生细胞周期G2/M期阻滞，使细胞生长 明显受抑；免疫组织化学染色显示，12例接受新辅助化疗患者肿瘤组织中SPGA5表达明显升高，对于未接受新辅助化疗患 者，SPAG5低表达者疾病无进展生存较差，早期患者中差异更显著，患者总生存也有相似趋势，但差异无统计学意义；在卵 巢腺癌细胞株OVCAR3 A2780及SKOV3中敲降SPAG5后，细胞对0.5 μmol/L紫杉醇抵抗能力增强。【结论】SPAG5在卵巢腺 癌细胞中调控细胞周期，促进细胞增殖，但早期卵巢高级别浆液性癌患者中SPAG5低表达者对紫杉醇的药物作用敏感性 差，相应预后差，因此卵巢高级别浆液性癌辅助化疗方案应个体化选择。

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近年来，化疗基础上加用抗表皮生长因子受体2 药物、抗血管生成药物及免疫检查点抑制剂，不仅可提高晚期胃癌 （GC）患者治疗的有效率，而且可明显改善患者预后。然而，目前晚期GC患者治疗后的生存获益远落后于肺癌、结直肠癌及乳腺 癌等实体肿瘤，靶向治疗仍需进一步探索。随着分子生物学技术的发展，新的治疗靶点如Claudin 18.2、基质金属蛋白酶（MMP）、 Dickkopf 相关蛋白1（DKK-1）、RAD3 相关蛋白激酶（ATR）被发现在GC细胞中表达，针对这些靶点的药物逐渐在临床治疗中崭露 头角，并显示出较好的临床应用前景。阐述晚期GC治疗中靶点的作用机制及靶向药物的研究进展，对提高GC的临床治疗疗效 具有重要意义. [ABSTRACT FROM AUTHOR]

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Objectives: Atmospheric weighted average temperature Tm is essential for calculating water vapour conversion factor and atmospheric precipitation. Methods: Based on the global geodetic observing system (GGOS) Atmosphere Tm grid data and European centre for medium‑range weather forecasts (ECMWF) 2 m temperature data from 2007 to 2017, a Tm model (qTm) suitable for Australia was established and the seasonal and daily variation of Tm residuals was taken into account. In addition, GGOS Atmosphere Tm grid data and radiosonde data in 2018 were selected to evaluate the model. Results: The results reveal that the qTm model is more accurate and applicable in the Australian region. Compared with GGOS Atmosphere Tm, the annual average Bias and RMSE(root mean square error) of the qTm model are －0.31 K and 1.97 K, respectively. While compared to the GPT2w(global pressure and temperature 2 wet) ‑ 1 and GPT2w ‑ 5, RMSE of qTm model increased by 21.8% and 25.9%, respectively. qTm model values are more consis‑ tent with sounding integral values, and the model's annual average Bias and RMSE are －0.44 K and 2.45 K, respectively. Compared with GPT2w ‑1 and GPT2w‑5, they increased by 10.2% and 11.8%, respectively. Conclusions: The qTm model can provide accurate Tm values for the Australian region and is a basis for the region's atmospheric moisture analysis and El Niño studies. [ABSTRACT FROM AUTHOR]

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