首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   678篇
  免费   60篇
  国内免费   14篇
耳鼻咽喉   9篇
儿科学   2篇
妇产科学   5篇
基础医学   65篇
口腔科学   33篇
临床医学   72篇
内科学   52篇
皮肤病学   7篇
神经病学   16篇
特种医学   107篇
外科学   56篇
综合类   73篇
预防医学   72篇
眼科学   5篇
药学   63篇
中国医学   24篇
肿瘤学   91篇
  2024年   1篇
  2023年   4篇
  2022年   10篇
  2021年   25篇
  2020年   33篇
  2019年   16篇
  2018年   24篇
  2017年   22篇
  2016年   28篇
  2015年   27篇
  2014年   40篇
  2013年   95篇
  2012年   28篇
  2011年   35篇
  2010年   24篇
  2009年   35篇
  2008年   26篇
  2007年   27篇
  2006年   25篇
  2005年   22篇
  2004年   15篇
  2003年   23篇
  2002年   23篇
  2001年   17篇
  2000年   7篇
  1999年   11篇
  1998年   8篇
  1997年   6篇
  1996年   13篇
  1995年   12篇
  1994年   10篇
  1993年   3篇
  1992年   4篇
  1991年   5篇
  1990年   5篇
  1989年   2篇
  1988年   3篇
  1987年   10篇
  1986年   5篇
  1985年   9篇
  1984年   2篇
  1983年   2篇
  1982年   1篇
  1981年   2篇
  1980年   2篇
  1979年   3篇
  1975年   1篇
  1974年   1篇
排序方式: 共有752条查询结果,搜索用时 15 毫秒
1.
目的:初步探讨石墨烯发热膜的抗肿瘤作用。方法:体外使用96孔平底板培养对数期生长的CCD-1095SK、MCF-7、A375和B16-F10细胞,使用石墨烯发热膜或温箱在不同温度(37 ℃、40 ℃、41.5 ℃、43 ℃)下恒温处理1小时,继续培养24小时后检测细胞生存率。体内接种黑色素瘤细胞株B16-F10于6~8周龄C57BL/6小鼠和裸鼠,C57BL/6小鼠使用石墨烯发热膜处理(38.5 ℃、39.5 ℃和40.5 ℃,30分钟/次,2次/天),同时给予达卡巴嗪(dacarbazine,DTIC)80 mg/kg或PBS作为控制,每两天测量一次肿瘤体积并记录小鼠的体重和生存状况,接种后第21天处死小鼠剥离瘤体,称重,多聚甲醛固定后进行HE染色。裸鼠使用石墨烯发热膜处理(37 ℃、38.5 ℃和40 ℃,30分钟/次,2次/天),每两天测量一次肿瘤体积并记录生存状况。结果:体外石墨烯发热膜处理达到40 ℃时,对MCF-7和A375细胞增殖具有抑制作用,但对于CCD-1095SK和B16-F10细胞,需要达到41.5 ℃才具有增殖抑制作用。在免疫健全的C57BL/6小鼠模型中,石墨烯发热膜40.5 ℃处理组肿瘤体积较控制组减小,石墨烯发热膜40.5 ℃处理和DTIC联用组的肿瘤体积较单独处理组减小。对于免疫不全裸鼠肿瘤模型,石墨烯发热膜处理未能减小肿瘤体积,也未能延长小鼠的生存期。结论:体外石墨烯发热膜处理具有抑制肿瘤细胞增殖的作用,体内联合DTIC和石墨烯发热膜处理具有抑制B16-F10肿瘤模型生长的作用,其机制有可能是间接增强了抗肿瘤免疫应答。  相似文献   
2.
介绍了太阳能热水系统概念。以上海市复旦大学附属华山医院新建西院项目为例,阐述了太阳能热水系统工作原理。  相似文献   
3.
4.
目的通过监测内热针治疗(Inner heating dry needle therapy)椎间盘退行性疾病(degenerative disc disease,DDD)过程中不同时间点生命体征的变化,探讨内热针疗法的安全性。方法 2015年4月~2015年10月解放军总医院康复医学中心病区及门诊收治的椎间盘退行性疾病患者278例,进行内热针治疗,动态监测患者入室时、麻醉时、针刺时、治疗中及治疗后心率、呼吸、血压及血氧饱和度的变化。结果所有患者在心电监护下顺利完成治疗,术中无明显不适主诉,无心血管意外发生。心率、呼吸及血压在麻醉时和针刺时有升高趋势(P0.05),一般持续10~20 min,但均在可控范围之内。麻醉时心率(77.13±11.78)次/min,呼吸(18.94±3.25)次/min,收缩压(130.8±17.06)mm Hg,舒张压(75.40±12.05)mm Hg;针刺时心率(76.67±11.85)次/min,呼吸(18.10±3.29)次/min,收缩压(128.97±16.84)mm Hg,舒张压(74.23±11.79)mm Hg。血氧饱和度在各个时间点差异无统计学意义。治疗后各指标恢复至入室前状态。结论在内热针治疗椎间盘退行性疾病过程中,心率、呼吸、血压在麻醉时和针刺时可出现一过性升高,但总体波动平稳可控,对生命体征影响较小,是一种安全性的治疗方法。治疗过程中应全程动态心电监护,尤其要密切关注麻醉和针刺时各生命体征的变化。  相似文献   
5.
目的:建立金属冠脉支架磁共振适用性实验平台,以实验室测试为基础,研究金属冠脉支架的磁共振适用性。方法:金属冠脉支架磁共振适用性试验分为四个部分,在3T磁共振环境下,分别进行磁位移力试验、磁扭矩试验、致热试验和图像干扰试验。结果:退磁效果好的金属冠脉支架,磁位移力小于其自身重力,磁扭矩小于其自身重力扭矩,温度升高值小,图像畸变值小。退磁效果不好的支架,磁位移力大于其自身重力,温度升高多,图像畸变值大。结论:实验平台可以对金属冠脉支架磁共振适用性进行检测,并对其退磁效果进行评价。  相似文献   
6.
7.
For species to stay temporally tuned to their environment, they use cues such as the accumulation of degree-days. The relationships between the timing of a phenological event in a population and its environmental cue can be described by a population-level reaction norm. Variation in reaction norms along environmental gradients may either intensify the environmental effects on timing (cogradient variation) or attenuate the effects (countergradient variation). To resolve spatial and seasonal variation in species’ response, we use a unique dataset of 91 taxa and 178 phenological events observed across a network of 472 monitoring sites, spread across the nations of the former Soviet Union. We show that compared to local rates of advancement of phenological events with the advancement of temperature-related cues (i.e., variation within site over years), spatial variation in reaction norms tend to accentuate responses in spring (cogradient variation) and attenuate them in autumn (countergradient variation). As a result, among-population variation in the timing of events is greater in spring and less in autumn than if all populations followed the same reaction norm regardless of location. Despite such signs of local adaptation, overall phenotypic plasticity was not sufficient for phenological events to keep exact pace with their cues—the earlier the year, the more did the timing of the phenological event lag behind the timing of the cue. Overall, these patterns suggest that differences in the spatial versus temporal reaction norms will affect species’ response to climate change in opposite ways in spring and autumn.

To stay tuned to their environment, species need to respond to both short- and long-term variation in climatic conditions. In temperate regions, favorable abiotic conditions, key resources, and major enemies may all occur early in a warm year, whereas they may occur late in a cold year. Coinciding with such factors may thus come with pronounced effects on individual fitness and population-level performance (14). As phenological traits also show substantial variability within and among populations, they can be subject to selection in nature (57), potentially resulting in patterns of local adaptation (810).At present, the rapid rate of global change is causing shifts in species phenology across the globe (1113). Of acute interest is the extent to which different events are shifting in unison or not, sometimes creating seasonal mismatches and functionally disruptive asynchrony (3, 1416). If much of the temporal and spatial variation in seasonal timing is a product of phenotypic plasticity, then changes can be instant, and sustained synchrony among interaction partners will depend on the extent to which different species react similarly to short-term variation in climatic conditions. If geographic variation in phenology reflects local adaptive evolutionary differentiation, then, in the short term, as climate changes, phenological interactions may be disrupted due to the lag as adaptation tries to catch up (1719). By assuming that space can substitute time, it is possible to make inference about the role that adaptation to climate may play. How well species stay in synchrony will then depend on the extent to which local selective forces act similarly or differently on different species and events.Local adaptation in phenology may take two forms. 1) The magnitude of phenological change might vary along environmental gradients in ways that intensify the environmental effects on phenological traits, a process known as cogradient variation (Fig. 1B). In such a case, the covariance between the genetic influences on phenological traits and the environmental influences is positive. Under this scenario, the effect of environmental variation over space and time will be larger than if all populations were to follow the same reaction norm regardless of location. 2) Genotypes might counteract environmental effects, thereby diminishing the change in mean trait expression across the environmental gradient. In such a case, the effect of environmental variation over space and time will be smaller than if all populations were to follow the same reaction norm regardless of location. This latter scenario, termed countergradient variation, occurs when genetic and environmental influences on phenotypic traits oppose one another (Fig. 1C) (20, 21).Open in a separate windowFig. 1.Schematic illustration showing slopes of phenology on temperature. Adapted with permission from ref. 30. A corresponds to phenological plasticity with respect to temperature and no local adaptation. B reveals phenological plasticity with respect to temperature plus cogradient local adaptation. C reveals phenological plasticity with respect to temperature plus countergradient local adaptation. For each scenario, we have included two examples of events showing this type of pattern in our data. For the exact climatic cues related to these biotic events, see SI Appendix, Table S1. In each plot, the red lines correspond to the within-population reaction norms through time (i.e., temporal slopes within locations), and the blue line corresponds to the between-population reaction norm (i.e., spatial slopes). If all populations respond alike, then the same reaction norm will apply across all locations, and individuals will respond in the same way to the cue no matter where they were, and no matter whether we examine responses within or between locations. If this was the case, then the reaction norm would be the same within (red lines) and between locations, and the blue and the red slopes would be parallel (i.e., their slopes identical). This scenario is depicted in A. What we use as our estimate of local adaptation is the difference between the two, i.e., whether the slope of reaction norms within populations differs from that across populations. If the temporal slopes are estimated at a relatively short time scale (as compared to the generation length of the focal organisms), then we can assume that within-location variation in the timing of the event reflects phenotypic responses alone, not evolutionary change over time. This component is then, per definition, due to phenotypic plasticity as such, i.e., to how individuals of a constant genetic makeup respond to annual variation in their environment. By comparison, the spatial slope (i.e., the blue line) is a sum of two parts: first, it reflects the mean of how individuals of a constant genetic makeup respond to annual variation in their environment, i.e., the temporal reaction norm defined above. These means are shown by the red dots in AC. However, second, if populations differentiate across sites, then we will see variation in their response to long-term conditions, with an added element in the spatial slope reflecting mean plasticity plus local adaptation. Therefore, if the spatial slope differs from the temporal slope, this reveals local adaptation (see Materials and Methods for further details). Such local adaptation in phenological response may take two forms. 1) The magnitude of phenological change might vary along environmental gradients in ways that intensify the environmental effects on phenological traits, a process known as cogradient variation (Fig. 1B). In such a case, the covariance between the genetic influences on phenological traits and the environmental influences is positive. Under this scenario, variation in the environmental cue over space and time will cause larger variation in phenological timing than if all populations were to follow the same reaction norm regardless of location. 2) Genotypes might counteract environmental effects, thereby diminishing the change in mean trait expression across the environmental gradient. In such a case, the effect of variation in the environmental cue over space and time will be smaller than if all populations were to follow the same reaction norm regardless of location. This latter scenario, termed countergradient variation, occurs when genetic and environmental influences on phenotypic traits oppose one another (C).For phenology, the overall prevalence of co- versus countergradient patterns is crucial, as it will dictate the extent to which local adaptation will either accentuate or attenuate phenological responses to temporal shifts in climate (10). Across environmental gradients in space, the relative prevalence of counter- versus cogradient variation in spring versus autumn will critically modify how climatic variation affects the length of the activity period of the entire ecological community. Overall, geographic variation in the activity period will be maximized when events in autumn and spring differ in terms of whether they adhere to patterns of co- or countergradient variation.Although the study of individual species and local species communities has revealed fine-tuning of species to local conditions (22), and a wealth of studies report shifts in phenology worldwide (23), we still lack a general understanding of how the two tie together: how strong is local adaptation in the timing of events, and how do they vary across the season? Here, a major hurdle to progress has been a skew in the focus of past studies: our current understanding of climatic effects on phenology has been colored by springtime events (2426), whereas events with a mean occurrence later in the season have been disproportionately neglected (27). To achieve satisfactory insight into how climate and its change affect the timing of biological activity across the season, we should thus ask how strongly phenology is influenced by climatic variation, what part of this response reflects phenotypic plasticity and what part evolutionary differentiation, and how the relative imprint of the two varies across the season. Addressing these pertinent questions is logistically challenging (e.g., ref. 28). Therefore, few studies have tackled them outside of the laboratory (29).Phillimore and coworkers (10, 30) proposed an elegant technique for identifying the relative roles of plasticity and local adaptation in generating spatiotemporal patterns of phenological variation. The rationale is to use a space versus time comparison (10, 30) (but see ref. 31 for criticism), drawing on the realization that at any one site, local conditions will vary between years. To be active at the right time, species will thus need to respond to temporal variation in climatic conditions. Let us assume that a focal species times some aspect of its annual activity (a species-specific “phenological event”) by reacting to a single environmental cue (e.g., the crossing of a given temperature sum). Now, if there were no differentiation between populations and all populations followed the same reaction norm, then with variation in the relative timing of the cue over time, all populations would react in the same way to the same cue regardless of spatial location (Fig. 1A). At the level of population means across space (blue line in Fig. 1A), we would then see a relationship between phenological event and cue timing identical to year-to-year variation within locations (red lines in Fig. 1A). However, if populations differentiate across sites, then we will see an added component in the spatial slope, reflecting the contribution of local adaptation to the mean phenology of the populations. By subtracting the within-population temporal slope from the spatial slope, we will thus achieve a direct measure of local adaptation (10), henceforth called Δb (30).Importantly, the temporal slope (i.e., the local phenological response to local year-to-year variation in the cue) can be either steeper or more shallow than the spatial slope (Fig. 1B vs. Fig. 1C)—the former being a sign of countergradient local adaptation, the latter of cogradient local adaptation (20, 21, 32). For a worked-through example of how this methodology is applied to the current data, see SI Appendix, Text S1.Here, we adopt temperature sums as widely used predictors of phenological events (3335) and treat the difference between the spatial and temporal slopes of phenological events on such sums as our estimates of local adaptation in reaction norms (SI Appendix, Text S1). Pinpointing the relative roles of plasticity and microevolution from spatiotemporal observations in the absence of direct measures of fitness will, per necessity, rely on several assumptions (for a full discussion, see ref. 36). However, given the adequate precaution, such quantification allows a tractable way toward estimating local adaption on a large scale (8, 10, 30, 3638).A key requirement for the successful application of this approach to resolving patterns across events of different relative timing is the existence of abundant data covering a large geographic area (30, 36). The extensive phenological data-collection scheme implemented at hundreds of nature reserves and other monitoring sites within the area of the former Soviet Union offers unique opportunities for addressing community-level phenology across a large space and long time (39). From this comprehensive dataset spanning 472 monitoring sites, 510,165 events and a time series of up to 118 y (Fig. 2 and ref. 39), we selected those 178 phenological events for which we have at least 100 data points that represent at least 10 locations (SI Appendix, Table S1). These events concerned 91 distinct taxa (SI Appendix, Table S1).Open in a separate windowFig. 2.Study sites and spatiotemporal patterns in climatic and phenological data. A shows the depth of the data and the spatial distribution of monitoring sites, with the size of the symbol proportional to the number of events scored locally. Since the selection of sites differed between events (39), in A, we have pooled sites located within 300 km from each other for illustration purposes. B shows the mean timing (day of year) of a phenological event: the onset of blooming in dandelion (Taraxacum officinale). C shows the mean timing (day of year) of a climatic event: the day of the year when the temperature sum providing the highest temporal slope for the onset of blooming in dandelion was first exceeded, computed as the mean over the years considered in B. For a worked-through example estimating reaction norms and metrics of local adaptation (Δb) for this species, see SI Appendix, Text S1.To express data on species phenology and abiotic conditions in the same currency, we related the dates of the phenological events (e.g., the first observation of an animal, or first flowering time of a plant species; SI Appendix, Fig. S1) to the dates when a given thermal sum (34, 35) was first exceeded. This choice of units has a convenient consequence in terms of the interpretation of slope values: if the date of phenology changes follows one-to-one the date of attaining a given temperature sum, then the slope will be one—an assumption frequently made but rarely tested in studies based on growth-degree days. The observed reaction norms can then be compared to this value. A value below 1 will signal undercompensation, i.e., that the earlier the cue, the larger the relative delay of the phenological event compared to its cue. By contrast, a value larger than 1 would signal overcompensation, i.e., that with an advancement of the cue, the timing of the phenological event will be advanced even more.Since thermal sums can be formed using a variety of thresholds, we used a generic approach and considered dates for exceeding a wide range of both heating and chilling degree-day sums (34, 35) (see Material and Methods for more information). As there is also evidence that sensitivity to temperature arises after a certain time point (13, 36), we calculated each heating and chilling degree-days sum for a range of starting dates. For each of the resulting 2,926 events, we then picked the variable that offered the highest temporal slope estimate, i.e., the largest within-location change in the timing of the event with a change in the timing of the cue (see Material and Methods for more information). Following the rationale outline above, this will be the most appropriate optimization criterion, since it selects the cue to which the phenological event responds the strongest to over time.  相似文献   
8.
In our previous animal model study, we found that radiofrequency (RF) ablation of pre-frozen tumor resulted in improved therapeutic effects. To understand the underlying mechanisms and optimize the treatment protocol, the RF heating pattern in pre-frozen tissue was studied in this paper. Both ex vivo and in vivo experiments were conducted to compare the temperature profiles of RF heating with or without pre-freezing. Results showed that the heating rate of in vivo tissues was significantly higher with pre-freezing. However, little difference was observed in the heating rate of ex vivo tissues with or without pre-freezing. In the histopathologic analysis of in vivo tissues, both a larger ablation area and a wider transitional zone were found in the tissue with pre-freezing. To investigate the cause for the enhancement in RF heating, the parameters affecting the tissue temperature rise were studied. It was found that the electrical conductivity of in vivo tissue with pre-freezing was much higher at low frequencies, but little difference was found at the 460?kHz frequency commonly used in clinical applications. A finite element model for RF heating was developed and validated to fit the thermal conductivity of in vivo tissue including effects of pre-freezing and the associated blood perfusion rate. Results showed that the enhancement of the heating rate was primarily attributed to the decreased blood perfusion rate in the tissue with vascular damage caused by pre-freezing. The ablation volume was increased by 104% due to the reduced heat dissipation.  相似文献   
9.
噪声性耳聋是由于听觉长时间遭受噪声作用或因耳疲劳引起的缓慢渐进性的感音性耳聋,早期表现为听觉疲劳,离开噪声环境后可以逐渐恢复,久之则难以恢复,最终形成感音神经性聋。因此,减少或消灭噪声为当今环境保护工作中的一项重要内容。了解因噪声导致内耳、听神经等发生病变的具体机制并加深对组织结构的了解在正确引导噪声性耳聋的筛查和防治工作中起到了重要的作用。  相似文献   
10.
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号