十八味诃子利尿丸中小伞虎耳草的TLC鉴别及羟基红花黄色素A的HPLC测定

目的：建立十八味诃子利尿丸的定性定量方法。方法：通过薄层色谱对小伞虎耳草进行定性鉴别,采用HPLC测定羟基红花黄色素A的含量。结果：通过TLC法可鉴别小伞虎耳草活性成分原儿茶酸的特征斑点;羟基红花黄色素A在（0.46~2.31）μg范围内线性良好,r=0.999 9。结论：建立的鉴别方法专属性强,定量方法准确,可有效控制该药的质量。     

昆明山海棠与雷公藤药理学对照研究

昆明山海棠和雷公藤同属卫矛科雷公藤属植物,在皮肤科临床应用广泛.两者不仅在某些化学结构方面相似,而且在药理作用方面也存在相似之处,均具有抗炎、抗肿瘤、免疫抑制、抗生育等多种药理作用.但是,由于两者都为有毒植物,在用于治疗的同时可产生一些毒性反应,甚至严重时可造成病人的死亡.为了便于临床更好地选用两种药物,特将两者的药理学作用作一综述.     

过表达TrxR1重组HEK293细胞株的构建和鉴定

目的构^fa;稳定fc7;表fbe;硫氧fd8;蛋白fd8;Թf;酶1�ff08;TrxR1�ff09;的HEK293细胞株�ff0c;为TrxR1的ԩf;€fd;研究以及靶向TrxR1࠶f;物筛选提f9b;细胞模型。方法通fc7;PCR扩增�ff0c;fde;接f6c;化以及Sanger双脱氧测רf;构^fa;并筛选Qfa;TrxR1的重组慢病毒表fbe;f7d;f53;pLVX-PuroTXNRD1�ff0c;f6c;染HEK293细胞�ff0c;߬f;嘌呤霉素筛选获f97;稳定f6c;染细胞株。后续研究分为3组fdb;行�ff1a;①TrxR1fc7;表fbe;HEK293细胞�ff1a;pLVX-Puro-TXNRD1f7d;f53;稳定f6c;染细胞�ff1b;②[f9;照HEK293细胞�ff1a;pLVX-Puro空f7d;病毒f7d;f53;稳定f6c;染细胞�ff1b;③正常HEK293细胞�ff1b;通fc7;RT-qPCR、Western blot实验检测上ff0;3组细胞中TrxR1的mRNA以及蛋白表fbe;情况�ff1b;通fc7;€f0;岛素终点法以及TRFS-green探针成Ԍf;检测上ff0;3种细胞内TrxR1的酶活力�ff1b;通fc7;CCK8实验检测上ff0;3种细胞[f9;TrxR1特f02;性抑制剂auranofin的ٔf;ؑf;性。结果构^fa;f7d;f53;߬f;DNA测רf;�ff0c;成ԩf;获f97;插入TrxR1的重组慢病毒表fbe;f7d;f53;pLVX-Puro-TXNRD1。与HEK293以及HEK293-NC细胞vf8;比�ff0c;HEK293-TrxR1-OE细胞中TrxR1的mRNA和蛋白高表fbe;�ff0c;且酶活力ӥf;同样显著上升�ff08;P�ff1c;0.005�ff09;�ff1b;而与HEK293以及HEK293-NC细胞vf8;比�ff0c;auranofin[f9;HEK293-TrxR1-OE细胞中TrxR1酶活力以及细胞增殖的抑制效率均显著下降�ff08;P�ff1c;0.005�ff09;。结论通fc7;构^fa;pLVX-Puro-TXNRD1慢病毒f7d;f53;�ff0c;成ԩf;获f97;fc7;表fbe;TrxR1酶的HEK293细胞株�ff0c;该细胞[f9;特f02;性靶向TrxR1的抑制剂的抗增殖f5c;用具有抵抗�ff0c;因而Ծf;用于靶向TrxR1࠶f;物的筛选。     

腹膜透析相关腹膜炎患者治疗失败预测模型的构建和验证：一项多中心临床研究

目的构^fa;和验证腹膜ऀf;析vf8;关性腹膜炎�ff08;PDAP�ff09;患者治疗失败的风险预测模型。方法[f9;2013年1月1日~2019年12月31日在吉林省3个腹膜ऀf;析中fc3;发ݑf;PDAP的腹膜ऀf;析�ff08;PD�ff09;患者fdb;行了回顾性分析。收集入选者Wfa;߫f;临床资料�ff0c;主要研究终点为治疗失败。根据腹膜ऀf;析中fc3;地սf;的不同�ff0c;将数据分为训练集�ff08;吉林大学第二医院、吉林大学第一医院二部�ff09;和验证集�ff08;吉林市中fc3;医院�ff09;。采用Logistic风险回f52;模型筛选f71;响PDAP治疗失败的危险因素�ff0c;用Stata^fa;立预测模型�ff1b;用ROCff2;߫f;和校准ff2;߫f;评f30;模型的区分度和准确性�ff0c;并以DCAff2;߫f;评f30;列߫f;Vfe;的临床有效性。结果共纳入977f8b;次PDAP�ff0c;训练集中625f8b;次�ff0c;其中78f8b;治疗失败�ff0c;验证集中352f8b;次�ff0c;其中35f8b;治疗失败。^fa;模ॡf;列多因素Logistic回f52;分析结果显示�ff0c;血清白蛋白、第5天腹ऀf;液白细胞计数、ऀf;析 f84;和f4;病fae;ݑf;物类型٢f;治疗失败的独立危险因素�ff0c;在训练集中的C߭f;计जf;为0.827�ff08;95% CI�ff1a;0.784–0.871�ff09;。在验证集中�ff0c;C߭f;计जf;为0.825�ff08;95%CI�ff1a;0.743-0.908�ff09;。预测模型在训练和验证集的校准方面fd;表现ࠦf;好。结论Wfa;于血清白蛋白、第5天腹ऀf;液白细胞计数、ऀf;析 f84;和f4;病fae;ݑf;物类型构^fa;了预测模型�ff0c;性€fd;ࠦf;好。     

小叶榕与印度橡胶榕气生根的比较鉴别研究

【目的】对小叶榕(Ficus microcarpa Linn.f.)和印度橡胶榕(Ficus elastica Roxb.ex Hornem.)气生根进行生药学鉴别。【方法】采集小叶榕与印度橡胶榕新鲜的气生根作为样品,采用体视镜进行外观形态鉴别;采用显微镜对气生根根被表面、根尖横切面、根尖后部横纵切面及粉末结构特征进行显微鉴别。【结果】形态鉴别:小叶榕气生根数目多于印度橡胶榕,直径小于印度橡胶榕;小叶榕气生根根尖淡黄色至黄白色,有灰白色或黄白色皮孔,而印度橡胶榕根尖浅黄色或黄色,有棕色的皮孔。显微特征鉴别:小叶榕与印度橡胶榕气生根根尖及根尖后部横切面显微结构可见初生木质部束不同,小叶榕为五至七原型,印度橡胶榕为六至十一原型;二者根部纵切面均可见无节不分枝乳汁管,但印度橡胶榕乳汁管直径略大于小叶榕,大多聚生;小叶榕粉末为红棕色,主要以螺纹导管为主,常见具缘纹孔导管,而印度橡胶榕粉末为黄棕色,纤维颜色较浅,接近无色透明,常有簇晶排列成行,主要以单列小型和大型成片的具缘纹孔导管为主。【结论】研究结果可为小叶榕和印度橡胶榕气生根的药材鉴定及开发利用提供依据。     

类风湿性关节炎下肢四负重关节置换术手术方案设计及中期疗效分析

目的探讨类风ۧf;性关节炎�ff08;rheumatoid arthritis�ff0c;RA�ff09;患者下肢四࣑f;重关节f6e;换ٲf;�ff08;four major lower extremity arthroplasties�ff0c;4JA�ff09;手ٲf;方案设计方法�ff0c;总结中ٱf;疗效。方法回顾分析2012年6月—2018年9月25f8b;接受分ٱf;4JA并获२f;ࢻf;3年以上的RA患者临床资料。男3f8b;�ff0c;女22f8b;�ff1b;年 f84;27�ff5e;80 岁�ff0c;平均48.6岁。身f53;质जf;指数16.0�ff5e;28.4 kg/m²�ff0c;平均20.48 kg/m²。RA病程2�ff5e;35年�ff0c;中f4d;数21年。合并膝外ffb;8f8b;�ff08;12fa7;�ff09;�ff0c;髋fc;内陷6f8b;�ff08;12fa7;�ff09;�ff0c;髋关节f3a;vf4;5f8b;�ff08;10fa7;�ff09;。 其中20f8b;均先行髋关节手ٲf;�ff0c;5f8b;先行膝关节手ٲf;。髋关节ԩf;€fd;评Nf7;采用Harris评分、髋关节炎疗效评分�ff08;HOOS�ff09;、髋关节活动度、Trendelenburgf81;�ff1b;膝关节ԩf;€fd;评Nf7;采用f8e;Vfd;特种外科医院�ff08;HSS�ff09;评分、膝关节活动度及肌力�ff0c;末次२f;ࢻf;ef6;行计ef6;-起立-行走�ff08;timed up and go�ff0c;TUG�ff09;测试。 X߫f;片观ֽf;假f53;有无松动、yfb;f4d;。 结果25 f8b;患者均完成4JA。1f8b;�ff08;1fa7;�ff09;ٲf;后切口ؑf;染、3f8b;�ff08;3fa7;�ff09;ٲf;中股骨fd1;ޮf;骨折�ff0c;其f59;患者无并发症发ݑf;。患者均获२f;ࢻf;�ff0c;२f;ࢻf;ef6;•f4; 3.0�ff5e;8.8 年�ff0c;平均5.8年。末次२f;ࢻf;ef6;�ff0c;髋关节Harris评分、HOOS评分以及关节屈、f38;、外展活动度均f83;ٲf;前改善�ff0c;Trendelenburgf81;阳性患者Ԝf;少�ff1b;膝关节HSS评分以及关节屈、f38;活动度均f83;ٲf;前改善�ff1b;上ff0;指标手ٲf;前后比f83;差f02;均有߭f;计学ؐf;义�ff08;P<0.05�ff09;。膝关节肌力均为Ⅴ级。TUG试验为7.8�ff5e;15.3 s�ff0c;平均10.79 s。X߫f;片复查示假f53;均未见松动、yfb;f4d;及下沉。 结论RA患者接受4JAef6;�ff0c;ٲf;前充分评f30;、合理选择手ٲf;ef6;机及手ٲf;顺רf;、ٲf;中最大程度恢复下肢力߫f;�ff0c;€fd;获f97;f83;好中ٱf;疗效。     

机器人辅助与传统人工全髋关节置换术后下肢长度差异的Meta分析

目的|fb;߭f;评Nf7;机器人f85;助与f20;߭f;人工全髋关节f6e;换ٲf;�ff08;total hip arthroplasty�ff0c;THA�ff09;ٲf;后下肢ॗf;度差f02;�ff08;leg length discrepancy�ff0c;LLD�ff09;。方法计算机检索The Cochrane Library、PubMed、Web of Science、EMbase、CNKI、万方、~f4;普、CBM数据库�ff0c;搜集机器人f85;助与f20;߭f;THA比f83;的ॡf;列研究�ff0c;检索ef6;限均从^fa;库f3;2021年8月11日。由2名研究者独立筛选文献、提取资料并评Nf7;纳入研究的Ԅf;倚风险后�ff0c;f7f;用RevMan 5.3f6f;Nf6;fdb;行Meta分析。结果共纳入10个高质जf;ॡf;列研究。Meta分析结果表明�ff1a;与f20;߭f;THAvf8;比�ff0c;机器人f85;助THAٲf;后LLDff4;׀f; �ff3b;MD=−1.64�ff0c;95%CI�ff08;−2.25�ff0c;−1.04�ff09;�ff0c;P<0.001�ff3d;�ff0c;ٲf;后3、12个月Harris评分ff4;高 �ff3b;MD=1.50�ff0c;95%CI�ff08;0.44�ff0c;2.57�ff09;�ff0c;P=0.006�ff1b;MD=7.60�ff0c;95%CI�ff08;2.51�ff0c;12.68�ff09;�ff0c;P=0.003�ff3d;�ff1b;f46;手ٲf;ef6;•f4;ff4;ॗf; �ff3b;MD=8.36�ff0c;95%CI�ff08;4.56�ff0c;12.17�ff09;�ff0c;P<0.000 1�ff3d;�ff0c;ٲf;后髋fc;前倾角ff4;大 �ff3b;MD=1.91�ff0c;95%CI�ff08;1.43�ff0c;2.40�ff09;�ff0c;P<0.001�ff3d;。两组ٲf;后6个月Harris评分、关节遗fd8;度评分�ff08;FJS�ff09;以及ٲf;后髋fc;外展角、并发症发ݑf;率差f02;无߭f;计学ؐf;义�ff08;P>0.05�ff09;。 结论机器人f85;助THA在ٲf;后LLD方面f18;于f20;߭f;THA。     

皮肤深层减张缝合研究进展

目的总结皮肤mf1;层Ԝf;f20;f1d;合的研究fdb;展�ff0c;为mf1;刻理解和改ࠦf;mf1;层Ԝf;f20;f1d;合方法提f9b;|fb;߭f;性资料。方法קf;泛查阅Vfd;内外皮肤mf1;层Ԝf;f20;f1d;合的vf8;关文献�ff0c;总结各种方法的特点及临床应用。结果皮肤mf1;层Ԝf;f20;f1d;合主要包括垂vf4;褥f0f;f1d;合及其改ࠦf;f1d;合技ٲf;、水平褥f0f;f1d;合及其改ࠦf;f1d;合技ٲf;�ff0c;以及一些特殊f1d;合技ٲf;�ff0c;ڼf;种f1d;合技ٲf;fd;有其特点而适用于不同f20;力及f62;状的切口。结论外科医ݑf;应根据切口f4d;f6e;、f20;力大׀f;等因素选择vf8;应的mf1;层Ԝf;f20;f1d;合技ٲf;�ff0c;[f9;切口fdb;行充分Ԝf;f20;�ff0c;以实现切口ࠦf;好愈合�ff0c;预防瘢痕增ݑf;。     

Exceptionally strong easterly wind burst stalling El Ni?o of 2014

Intraseasonal wind bursts in the tropical Pacific are believed to affect the evolution and diversity of El Ni�f1;o events. In particular, the occurrence of two strong westerly wind bursts (WWBs) in early 2014 apparently pushed the ocean–atmosphere system toward a moderate to strong El Ni�f1;o—potentially an extreme event according to some climate models. However, the event’s progression quickly stalled, and the warming remained very weak throughout the year. Here, we find that the occurrence of an unusually strong basin-wide easterly wind burst (EWB) in June was a key factor that impeded the El Ni�f1;o development. It was shortly after this EWB that all major Ni�f1;o indices fell rapidly to near-normal values; a modest growth resumed only later in the year. The easterly burst and the weakness of subsequent WWBs resulted in the persistence of two separate warming centers in the central and eastern equatorial Pacific, suppressing the positive Bjerknes feedback critical for El Ni�f1;o. Experiments with a climate model with superimposed wind bursts support these conclusions, pointing to inherent limits in El Ni�f1;o predictability. Furthermore, we show that the spatial structure of the easterly burst matches that of the observed decadal trend in wind stress in the tropical Pacific, suggesting potential links between intraseasonal wind bursts and decadal climate variations.El Ni�f1;o, the warm phase of the El Ni�f1;o–Southern Oscillation (ENSO), is characterized by anomalously warm water appearing in the central and eastern equatorial Pacific every 2–7 years, driven by tropical ocean–atmosphere interactions with far-reaching global impacts (recent reviews are in refs. f="#r1" rid="r1" class=" bibr popnode">1f="#r2" rid="r2" class=" bibr popnode">–f="#r3" rid="r3" class=" bibr popnode tag_hotlink tag_tooltip" id="__tag_518019695">3). These interactions and El Ni�f1;o development involve several important feedbacks, including the positive Bjerknes feedback [zonal wind relaxation leads to the reduction of the zonal sea surface temperature (SST) gradient and further wind relaxation] (f="#r4" rid="r4" class=" bibr popnode">4). Since the year 2000, there has been a shift in the observed properties of El Ni�f1;o, including its magnitude, frequency, and spatial structure of temperature anomalies (f="#r5" rid="r5" class=" bibr popnode">5, f="#r6" rid="r6" class=" bibr popnode tag_hotlink tag_tooltip" id="__tag_518019703">6). For example, El Ni�f1;o events occurred more frequently than during the previous two decades, but all were weak, and none reached the extreme magnitude of the 1982 and 1997 events. Concurrently, the rise of global mean surface temperature has slowed down with the so-called global warming hiatus (f="#r7" rid="r7" class=" bibr popnode">7f="#r8" rid="r8" class=" bibr popnode tag_hotlink tag_tooltip" id="__tag_518019691">–f="#r9" rid="r9" class=" bibr popnode tag_hotlink tag_tooltip" id="__tag_518019690">9). The stalled development of the 2014 El Ni�f1;o presents a showcase to explore the relevant connection and mechanisms of these changes.At the beginning of 2014, many in the scientific community anticipated that a moderate to strong El Ni�f1;o could develop by the end of the year (f="#r10" rid="r10" class=" bibr popnode tag_hotlink tag_tooltip" id="__tag_518019698">10f="#r11" rid="r11" class=" bibr popnode tag_hotlink tag_tooltip" id="__tag_518019692">f="#r12" rid="r12" class=" bibr popnode">f="#r13" rid="r13" class=" bibr popnode">–f="#r14" rid="r14" class=" bibr popnode">14) (f="/pmc/articles/PMC4776523/figure/sfig01/" target="figure" class="fig-table-link figpopup" rid-figpopup="sfig01" rid-ob="ob-sfig01" co-legend-rid="lgnd_sfig01">Fig. S1). In March, the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center announced an “El Ni�f1;o watch” based on predictions made by dynamical and statistical models (f="#r12" rid="r12" class=" bibr popnode">12), attracting attention of the general public. Admittedly, these predictions encompassed large uncertainties because of the stochastic nature of the tropical climate system (f="#r15" rid="r15" class=" bibr popnode">15f="#r16" rid="r16" class=" bibr popnode">–f="#r17" rid="r17" class=" bibr popnode">17). In May, the National Aeronautics and Space Administration (NASA) suggested that 2014 could potentially rival the strongest on-record event of 1997/19998 (f="/pmc/articles/PMC4776523/figure/fig01/" target="figure" class="fig-table-link figpopup" rid-figpopup="fig01" rid-ob="ob-fig01" co-legend-rid="lgnd_fig01">Fig. 1B), while acknowledging the large existing uncertainty (f="#r14" rid="r14" class=" bibr popnode">14); their projection was supported by satellite observations of strong Kelvin waves evident in sea surface height (SSH) (f="/pmc/articles/PMC4776523/figure/fig02/" target="figure" class="fig-table-link figpopup" rid-figpopup="fig02" rid-ob="ob-fig02" co-legend-rid="lgnd_fig02">Fig. 2C). The spread of spring forecast plumes from some climate models, for example that of the European Centre for Medium-Range Weather Forecasts (ECMWF), included the possibility of a failed El Ni�f1;o (f="/pmc/articles/PMC4776523/figure/sfig01/" target="figure" class="fig-table-link figpopup" rid-figpopup="sfig01" rid-ob="ob-sfig01" co-legend-rid="lgnd_sfig01">Fig. S1) but only as a low-probability outcome involving unusual instances of weather noise. The observed development fell near the limit of these forecast possibilities after June and July, and eventually, the 2014 warm event barely qualified as El Ni�f1;o (f="/pmc/articles/PMC4776523/figure/fig01/" target="figure" class="fig-table-link figpopup" rid-figpopup="fig01" rid-ob="ob-fig01" co-legend-rid="lgnd_fig01">Fig. 1A).f="/pmc/articles/PMC4776523/figure/fig01/" target="figure" rid-figpopup="fig01" rid-ob="ob-fig01">f="/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=4776523_pnas.1514182113fig01.jpg" target="tileshopwindow">f="/pmc/articles/PMC4776523/figure/fig01/?report=objectonly">Open in a separate windowf="/pmc/articles/PMC4776523/figure/fig01/" target="figure" rid-figpopup="fig01" rid-ob="ob-fig01">Fig. 1.El Ni�f1;o development in (A and C) 2014 and (B and D) 1997. (A and B) Evolution of the Ni�f1;o3, Ni�f1;o4, and Ni�f1;o3.4 indices; the first two indices describe SST anomalies (in degrees Celsius) in the eastern and central equatorial Pacific, respectively, whereas the last index covers the region in between. (C and D) Variation in the zonal wind stress indices. These indices are obtained by averaging wind stress anomalies (in 10⁻² newtons per meter²) in the equatorial Pacific zonally and between 5 °S and 5 °N and then selecting negative (blue; easterly anomalies), positive (red; westerly anomalies), or full values (black) (f="#s4" rid="s4" class=" sec">Materials and Methods). The spatial averaging is intended to take into account both the magnitude and the fetch of the wind bursts. During 2014, two early year WWBs were followed by an exceptional EWB in June (highlighted by pink and blue, respectively). This easterly burst apparently led to a rapid decrease of the Ni�f1;o indices (A). In contrast, the 1997 El Ni�f1;o exhibited persistent westerly wind activity throughout the year. The graphs start on January 1.f="/pmc/articles/PMC4776523/figure/fig02/" target="figure" rid-figpopup="fig02" rid-ob="ob-fig02">f="/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=4776523_pnas.1514182113fig02.jpg" target="tileshopwindow">f="/pmc/articles/PMC4776523/figure/fig02/?report=objectonly">Open in a separate windowf="/pmc/articles/PMC4776523/figure/fig02/" target="figure" rid-figpopup="fig02" rid-ob="ob-fig02">Fig. 2.Spatiotemporal evolution of the 2014 El Ni�f1;o. (A–D) Hovm�f6;ller diagrams for anomalies in (A) SST, (B) zonal wind stress, (C) SSH, and (D) surface zonal currents in the equatorial Pacific. Time goes downward. The SSH and surface velocity plots highlight the eastward propagating downwelling Kelvin waves, especially pronounced early in the year, and a strong upwelling Kelvin wave midyear. (E and F) El Ni�f1;o development in 2014 (black line) compared with several historical (E) EP and (F) CP events. The diagrams show the position of the Warm Pool Eastern Edge (degrees of longitude) vs. the Ni�f1;o3 SST (degrees Celsius) for different months of the year. The Warm Pool Eastern Edge is defined as the position of the 29 °C isotherm at the equator. Numbers indicate monthly averages (1, January; 2, February, etc.). The light vertical line marks the Dateline. In 2014, both the warm pool displacement and Ni�f1;o3 SST anomalies were exceptionally large during May (month 5), were similar to those in 1997 and 1982 (the strongest events of the 20th century), and then, rapidly decreased by August (month 8).f="/pmc/articles/PMC4776523/figure/sfig01/" target="figure" rid-figpopup="sfig01" rid-ob="ob-sfig01">f="/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=4776523_pnas.1514182113sfig01.jpg" target="tileshopwindow">f="/pmc/articles/PMC4776523/figure/sfig01/?report=objectonly">Open in a separate windowf="/pmc/articles/PMC4776523/figure/sfig01/" target="figure" rid-figpopup="sfig01" rid-ob="ob-sfig01">Fig. S1.The El Ni�f1;o spring forecasts of the Ni�f1;o3.4 index from the European Centre for Medium-Range Weather Forecasts (ECMWF). Red lines show 50 ensemble members of the forecast plume initiated in March of 2014; the black dotted line indicates the observed Ni�f1;o3.4 index. The observed development fell outside the forecast plume in June and July and remained beyond the typical forecast spread after that. Adapted from ref. f="#r13" rid="r13" class=" bibr popnode">13.The question then arises as to which dynamic factors controlled the temporal and spatial development in the tropical Pacific in 2014. This warm event began with a rapid growth, such that, in early June, all major Ni�f1;o indices (f="#s4" rid="s4" class=" sec">Materials and Methods) along the equator were nearly identical to those during the same time of 1997 (f="/pmc/articles/PMC4776523/figure/fig01/" target="figure" class="fig-table-link figpopup" rid-figpopup="fig01" rid-ob="ob-fig01" co-legend-rid="lgnd_fig01">Fig. 1 A and B). A substantial warming also developed along the Peruvian coast (f="/pmc/articles/PMC4776523/figure/fig03/" target="figure" class="fig-table-link figpopup" rid-figpopup="fig03" rid-ob="ob-fig03" co-legend-rid="lgnd_fig03">Fig. 3A). Then, the event’s progression slowed down or even reversed. By year end, the equatorial warming barely exceeded 1 °C, but the SST anomaly stretched uncharacteristically across the entire equatorial Pacific almost uniformly (f="/pmc/articles/PMC4776523/figure/fig01/" target="figure" class="fig-table-link figpopup" rid-figpopup="fig01" rid-ob="ob-fig01" co-legend-rid="lgnd_fig01">Figs. 1A and f="/pmc/articles/PMC4776523/figure/fig02/" target="figure" class="fig-table-link figpopup" rid-figpopup="fig02" rid-ob="ob-fig02" co-legend-rid="lgnd_fig02">​and2A).2A). Accordingly, the major goal of this study is to investigate this unusual development, identify the main factors that impeded this event, and explore its broad implications.f="/pmc/articles/PMC4776523/figure/fig03/" target="figure" rid-figpopup="fig03" rid-ob="ob-fig03">f="/core/lw/2.0/html/tileshop_pmc/tileshop_pmc_inline.html?title=Click%20on%20image%20to%20zoom&p=PMC3&id=4776523_pnas.1514182113fig03.jpg" target="tileshopwindow">f="/pmc/articles/PMC4776523/figure/fig03/?report=objectonly">Open in a separate windowf="/pmc/articles/PMC4776523/figure/fig03/" target="figure" rid-figpopup="fig03" rid-ob="ob-fig03">Fig. 3.The June of 2014 EWB in satellite-based data. (A) The spatial structure of anomalies in surface winds (vectors; in meters per second) and SST (colors; in degrees Celsius) on June 12, 2014, when the burst was strongest. (B) Daily vs. weekly mean values of the zonal wind stress index (10⁻² newtons per meter²) for the period 1988–2014. The blue cross marks the peak value of the June of 2014 EWB. The wind stress index is defined as anomalous zonal wind stress averaged in the equatorial Pacific zonally and between 5 °S and 5 °N (f="#s4" rid="s4" class=" sec">Materials and Methods). Black circles are for the year 2014, red circles are for all El Ni�f1;o years before 2014, and gray circles are for all other years (La Ni�f1;a or neutral). Note that the June of 2014 EWB appears strongest in the satellite record for not only daily data but also, weekly averaged values, which confirms that the observations are robust.