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1.
Kaustubh Supekar Weidong Cai Rajeev Krishnadas Lena Palaniyappan Vinod Menon 《Neuropsychopharmacology》2019,85(1):60-69
Background
Schizophrenia is a highly disabling psychiatric disorder characterized by a range of positive “psychosis” symptoms. However, the neurobiology of psychosis and associated systems-level disruptions in the brain remain poorly understood. Here, we test an aberrant saliency model of psychosis, which posits that dysregulated dynamic cross-network interactions among the salience network (SN), central executive network, and default mode network contribute to positive symptoms in patients with schizophrenia.Methods
Using task-free functional magnetic resonance imaging data from two independent cohorts, we examined 1) dynamic time-varying cross-network interactions among the SN, central executive network, and default mode network in 130 patients with schizophrenia versus well-matched control subjects; 2) accuracy of a saliency model–based classifier for distinguishing dynamic brain network interactions in patients versus control subjects; and 3) the relation between SN-centered network dynamics and clinical symptoms.Results
In both cohorts, we found that dynamic SN-centered cross-network interactions were significantly reduced, less persistent, and more variable in patients with schizophrenia compared with control subjects. Multivariate classification analysis identified dynamic SN-centered cross-network interaction patterns as factors that distinguish patients from control subjects, with accuracies of 78% and 80% in the two cohorts, respectively. Crucially, in both cohorts, dynamic time-varying measures of SN-centered cross-network interactions were correlated with positive, but not negative, symptoms.Conclusions
Aberrations in time-varying engagement of the SN with the central executive network and default mode network is a clinically relevant neurobiological signature of psychosis in schizophrenia. Our findings provide strong evidence for dysregulated brain dynamics in a triple-network saliency model of schizophrenia and inform theoretically motivated systems neuroscience approaches for characterizing aberrant brain dynamics associated with psychosis. 相似文献2.
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Wei Xiang Tong-Chuan Suo Hua Yu An-Ping Li Shou-Qing Zhang Chun-Hua Wang Yan Zhu Zheng Li 《Yao wu shi pin fen xi = Journal of food and drug analysis.》2018,26(2):858-868
Due to its chemical complexity, proper quality control for a Chinese medical preparation (CMP) has been a great challenge. Choosing the appropriate quality markers (Q-markers) for quality control of CMP is an important work. Best of all, the chosen Q-markers are the main chemical compounds from the herbals as well as the active constituents of this CMP. Only in this way the established quality control system can really achieve the purpose of controlling the quality of CMP and ensuring the safely and effectively use of CMP. To achieve the purpose, network pharmacology combined with the contents of chemical compounds in the CMP has been used in this research. We took an anti-arrhythmic CMP, Shenxian-Shengmai oral liquid (SSOL), as an example. Firstly, UPLC-QTOF-MS/MS method was used to analyze the main components of SSOL. A total of 64 compounds were unambiguously or tentatively identified and 32 of them were further validated by reference compounds. Secondly, the network was constructed based on the identified compounds to predict the effective compounds related to cardiac arrhythmias. Based on the existing database and the operation method of topology, a method of double network analysis (DNAA) was proposed, from which 10 important targets in the pathway of arrhythmia were screened out, and 26 compounds had good antiarrhythmic activity. Based on the prediction results of network pharmacology along with the contents of the compounds in this CMP, ten representative compounds were chosen as the Q-markers for the quality control of SSOL. We find that five of these ten compounds, including danshensu, rosmarinic acid, salvianolic acid A, epimedin A and icariin, have antiarrhythmic activity. Then, the UPLC-DAD method was established as the control method for SSOL. 相似文献
6.
目的研究锁阳对大鼠前列腺增生(BPH)模型的作用及相关机制研究。方法用雌/雄激素诱导大鼠前列腺增生。按体重将去势3周后大鼠随机分为3组:模型组,锁阳组(3 g·kg-1·d-1),氟他胺组(30 mg·kg-1·d-1),每组10只。另外取10只健康大鼠作为假手术组,模型组和假手术组给等量0. 9%Na Cl,均灌胃给药,每天1次,连续给药45 d。以蛋白免疫印迹检测增殖细胞核抗原(PCNA)蛋白变化;用Cyto Scape3. 5. 1软件构建和分析锁阳"化合物-靶点-前列腺增生"复杂网络。结果给药后,假手术组、模型组、锁阳组的PCNA蛋白表达灰度比值分别是0. 58±0. 11,1. 37±0. 21,0. 94±0. 31,模型组与假手术比较,差异有统计学意义(P <0. 05);锁阳组与模型组比较,差异有统计学意义(P <0. 05)。网络药理学揭示,锁阳直接作用于BPH疾病的靶点有7个,4个新发现的靶点分别为细胞周期素D1(CCND1)、磷脂酰基醇(PIK3CA)、氧化物酶体增殖物激活受体(PPARG)和过氧化物合成酶(PTGS2)。结论锁阳抑制大鼠前列腺增生可能与细胞增殖等通路以及调节细胞周期素D1(CCND1)与磷脂酰基醇(PIK3CA)等蛋白表达相关。 相似文献
7.
In this study, the spatial and seasonal bacterioplankton community dynamics were investigated in the main channel of the Middle Route of the South-to-North Water Diversion Project (MRP) using Illumina HiSeq sequencing. Water samples were collected in spring and summer from south to north at eight water quality monitoring stations, respectively. The results showed that seasonal changes had a more pronounced effect on the bacterioplankton community compositions (BCCs) than spatial variation. The diversity analysis results indicated that samples of summer have more operational taxonomic units (OTUs), higher richness and diversity than those in spring. The main phyla, Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria and Chloroflexi, displayed significant differences (P < 0.05) between spring and summer in the main channel. The Redundancy analysis (RDA) targeting all samples indicated that specific conductivity (SPC), dissolved oxygen (DO), pH and temperature (T) might be key factors in driving BCCs, while trophic status showed no significant correlation (P > 0.05). The present study provides important insights into the potential ecological roles of specific taxa in the new artificial ecosystem and it offers reference for studies on ecosystem succession of other giant interbasin water diversion project in the world. 相似文献
8.
J. De Vries H. Murtomaa M. Butler H. Cherrett P. Ferrillo M. B. Ferro C. Gadbury-Amyot N. K. Haden M. Manogue J. Mintz J. E. Mulvihill B. Murray A. Nattestad D. Nielsen E. Ogunbodede H. Parkash F. Plasschaert M. T. Reed R. L. Rupp S. Tandon B. Wang S. Wang T. Yucel R. W. Valachovic A. Watkinson D. Shanley 《European journal of dental education》2008,12(S1):167-175
9.
徐贵云 郭扬波 欧阳惠怡 党亚梅 张敏玲 林康广 XU Gui-yun GUO Yang-bo OUYANG Hui-yi DANG Ya-mei ZHANG Min-ling LIN Kang-guang 《临床精神医学杂志》2014,(5):296-300
目的:探索影响抑郁症患者抗抑郁剂疗效的预测因素。方法:241例抑郁症患者给予抗抑郁药治疗6周,治疗前后进行汉密顿抑郁量表17项(HAMD)评分,采用减分率评定疗效。分析人口学因素、基线HAMD、明尼苏达多项人格测定(MMPI-2)、认知功能评分及脑源性神经营养因子(BDNF)、5-羟色胺转运体(5-HTTLPR)和糖皮质激素受体(GR)3种基因多态对疗效的预测。结果:基线HAMD评分(β=0.771,P0.001)、MMPI-2中偏执(Pa)分(β=-0.322,P=0.032,R2=0.451)、连线测验B评分(TMT-B)(β=-0.045,P=0.013)、汉诺塔总分(β=-0.067,P=0.026)、数字广度(倒序)分(β=-0.974,P=0.025)及GR BclI基因G-等位基因携带者(P=0.05)与抗抑郁剂HAMD减分率有关。整合模型回归分析显示,结合基线HAMD评分(β=0.894,P0.001)、MMPI-2-Pa分(β=-0.155,P=0.036)和TMT-B分(β=-0.038,P=0.034)3个预测因子可解释57.1%的变异。结论:基线HAMD评分、MMPI-2-Pa分和TMT-B分可预测抗抑郁剂的疗效。 相似文献
10.
Ralf Herwig 《Dialogues in clinical neuroscience》2014,16(4):465-477
The development of novel high-throughput technologies has opened up the opportunity to deeply characterize patient tissues at various molecular levels and has given rise to a paradigm shift in medicine towards personalized therapies. Computational analysis plays a pivotal role in integrating the various genome data and understanding the cellular response to a drug. Based on that data, molecular models can be constructed that incorporate the known downstream effects of drug-targeted receptor molecules and that predict optimal therapy decisions. In this article, we describe the different steps in the conceptual framework of computational modeling. We review resources that hold information on molecular pathways that build the basis for constructing the model interaction maps, highlight network analysis concepts that have been helpful in identifying predictive disease patterns, and introduce the basic concepts of kinetic modeling. Finally, we illustrate this framework with selected studies related to the modeling of important target pathways affected by drugs. 相似文献