关于磷酸氯喹治疗新型冠状病毒肺炎给药方案的安全性刍议

国家卫生健康委员会和国家中医药管理局2020年2月18日发布的《新型冠状病毒肺炎诊疗方案(试行第六版)》将磷酸氯喹作为抗病毒试用药物之一,其后又于同月26日发布了《关于调整试用磷酸氯喹治疗新冠肺炎用法用量的通知》,2020年3月3日发布的《新型冠状病毒肺炎诊疗方案(试行第七版)》对磷酸氯喹给药方案进行了修订。磷酸氯喹半衰期长、全身分布广泛,易在体内蓄积,且不良反应与剂量相关。本文结合磷酸氯喹的药代动力学特点对给药方案进行了安全性分析,供临床医师和药师在诊治新型冠状病毒肺炎患者时参考,以降低发生不良反应的风险。     

药品批发企业质量管理体系运行中内审问题分析与对策研究

目的： 分析药品批发企业质量管理体系运行中存在的普遍问题,提出改善药品批发企业质量体系内审管理水平的具体实施建议,持续改进批发企业质量管理水平,控制药品经营环节风险,保证药品质量。方法： 对328家药品批发企业GSP认证申报资料及现场检查报告中发现的企业内审工作中存在的具体问题进行汇总、整理、分析原因,发现当前企业普遍存在的问题,并探讨改进措施。结果与结论： 药品批发企业应通过完善内审管理,建立完整严谨的标准和工作流程,强化企业内审工作的权威性和独立性,建立企业全员参与机制,提高内审人员的综合素质和能力;寻找质量管理体系文件贯彻执行的偏差;在体系关键要素发生重大变化或调整后,完善新经营环境下质量管理体系。从而确保企业在药品采购、储存、销售、运输等日常经营过程中均严格执行药品GSP,确保企业质量管理体系保持健康正常的运行。     

我国仿制药质量关键影响因素分析

目的：研究我国仿制药质量的关键影响因素,为药品监管政策制定和实施提出合理建议。方法：采用问卷调查和探索性因子分析法研究影响仿制药质量的不同主体因素和生产企业内部因素。结果：进行了两轮问卷调查,分别发放了110和170份问卷,有效回收99和159份。研究结果显示：影响仿制药质量的因素按重要性依次为企业＞监管＞激励政策＞药品使用＞配套措施,企业内部影响因素的重要性依次为关键技术＞实施操作＞风险控制＞仪器设备＞原辅料质量。结论：仿制药质量受到企业内部因素和监管因素、产业环境因素、使用因素等多种外部因素的影响;生产企业内部因素是影响药品质量的决定因素, 其中又以企业的关键生产技术最为重要。     

Impaired fasting glucose and the prevalence and severity of angiographic coronary artery disease in high-risk Chinese patients

We assessed the relation between different fasting plasma glucose (FPG) levels of 5.6 to 6.9 mmol/L and the prevalence and severity of angiographic coronary artery disease (CAD) in high-risk Chinese patients. Among 512 subjects who were to undergo coronary angiography for the confirmation of suspected myocardial ischemia, 409 subjects were enrolled and categorized into 3 groups based on FPG levels: (1) 相似文献   

Distinct roles of GSK-3α and GSK-3β phosphorylation in the heart under pressure overload

Glycogen synthase kinase-3 (GSK-3) is a master regulator of growth and death in cardiac myocytes. GSK-3 is inactivated by hypertrophic stimuli through phosphorylation-dependent and -independent mechanisms. Inactivation of GSK-3 removes the negative constraint of GSK-3 on hypertrophy, thereby stimulating cardiac hypertrophy. N-terminal phosphorylation of the GSK-3 isoforms GSK-3α and GSK-3β by upstream kinases (e.g., Akt) is a major mechanism of GSK-3 inhibition. Nonetheless, its role in mediating cardiac hypertrophy and failure remains to be established. Here we evaluated the role of Serine(S)21 and S9 phosphorylation of GSK-3α and GSK-3β in the regulation of cardiac hypertrophy and function during pressure overload (PO), using GSK-3α S21A knock-in (αKI) and GSK-3β S9A knock-in (βKI) mice. Although inhibition of S9 phosphorylation during PO in the βKI mice attenuated hypertrophy and heart failure (HF), inhibition of S21 phosphorylation in the αKI mice unexpectedly promoted hypertrophy and HF. Inhibition of S21 phosphorylation in GSK-3α, but not of S9 phosphorylation in GSK-3β, caused phosphorylation and down-regulation of G1-cyclins, due to preferential localization of GSK-3α in the nucleus, and suppressed E2F and markers of cell proliferation, including phosphorylated histone H3, under PO, thereby contributing to decreases in the total number of myocytes in the heart. Restoration of the E2F activity by injection of adenovirus harboring cyclin D1 with a nuclear localization signal attenuated HF under PO in the αKI mice. Collectively, our results reveal that whereas S9 phosphorylation of GSK-3β mediates pathological hypertrophy, S21 phosphorylation of GSK-3α plays a compensatory role during PO, in part by alleviating the negative constraint on the cell cycle machinery in cardiac myocytes.     

Distinct neural ensemble response statistics are associated with recognition and discrimination of natural sound textures

The perception of sound textures, a class of natural sounds defined by statistical sound structure such as fire, wind, and rain, has been proposed to arise through the integration of time-averaged summary statistics. Where and how the auditory system might encode these summary statistics to create internal representations of these stationary sounds, however, is unknown. Here, using natural textures and synthetic variants with reduced statistics, we show that summary statistics modulate the correlations between frequency organized neuron ensembles in the awake rabbit inferior colliculus (IC). These neural ensemble correlation statistics capture high-order sound structure and allow for accurate neural decoding in a single trial recognition task with evidence accumulation times approaching 1 s. In contrast, the average activity across the neural ensemble (neural spectrum) provides a fast (tens of milliseconds) and salient signal that contributes primarily to texture discrimination. Intriguingly, perceptual studies in human listeners reveal analogous trends: the sound spectrum is integrated quickly and serves as a salient discrimination cue while high-order sound statistics are integrated slowly and contribute substantially more toward recognition. The findings suggest statistical sound cues such as the sound spectrum and correlation structure are represented by distinct response statistics in auditory midbrain ensembles, and that these neural response statistics may have dissociable roles and time scales for the recognition and discrimination of natural sounds.

What makes a sound natural, and what are the neural codes that support recognition and discrimination of real-world natural sounds? Although it is known that the early auditory system decomposes sounds along fundamental acoustic dimensions such as intensity and frequency, the higher-level neural computations that mediate natural sound recognition are poorly understood. This general lack of understanding is in part attributed to the structural complexity of natural sounds, which is difficult to study with traditional auditory test stimuli, such as tones, noise, or modulated sequences. Such stimuli can reveal details of the neural representation for relatively low-level acoustic cues, yet they don’t capture the rich and diverse statistical structure of natural sounds. Thus, they cannot reveal many of the computations associated with higher-level sound properties that facilitate auditory tasks such as natural sound recognition or discrimination. A class of stationary natural sounds termed textures, such as the random sounds emanating from a running stream, a crowded restaurant, or a chorus of birds, have been proposed as alternative natural stimuli which allow for manipulating high-level acoustic structure (1). Texture sounds are composed of spatially and temporally distributed acoustic elements that are collectively perceived as a single source and are defined by their statistical features. Identification of these natural sounds has been proposed to be mediated through the integration of time-averaged summary statistics, which account for high-level structures such as the sparsity and time-frequency correlation structure found in many natural sounds (1–3). Using a generative model of the auditory system to measure summary statistics from natural texture sounds, it is possible to synthesize highly realistic synthetic auditory textures (1). This suggests that high-order statistical cues are perceptually salient and that the brain might extract these statistical features to build internal representations of sounds.Although neural activity throughout the auditory pathway is sensitive to a variety of statistical cues such as the sound contrast, modulation power spectrum, and correlation structure (4–12), how sound summary statistics contribute toward basic auditory tasks such as recognition and discrimination of sounds is poorly understood. Furthermore, it is unclear where along the auditory pathway summary statistics are represented and how they are reflected in neural activity. The inferior colliculus (IC) is one candidate midlevel structure for representing such summary statistics. As the principal midbrain auditory nucleus, the IC receives highly convergent brainstem inputs with varied sound selectivities. Neurons in the IC are selective over most of the perceptually relevant range of sound modulations and neural activity is strongly driven by multiple high-order sound statistics (4–7, 10). In previous work, we showed the correlation statistics of natural sounds are highly informative about stimulus identity and they appear to be represented in the correlation statistics of auditory midbrain neuron ensembles (4). Correlations between neurons have also been proposed as mechanisms for pitch identification (13) and sound localization (14). This broadly supports the hypotheses that high-order sound statistics are reflected in the response statistics of neural ensembles and that these neural response statistics could potentially subserve basic auditory tasks.Here using natural and synthetic texture sounds, we test the hypothesis that statistical structure in natural texture sounds modulates the response statistics of neural ensembles in the IC of unanesthetized rabbits, and that distinct neural response statistics have the potential to contribute toward sound recognition and discrimination behaviors. By comparing the performance of neural decoders with human texture perception, we find that place rate representation of sounds (neural spectrum) accumulates evidence about the sounds on relatively fast time scales (tens of milliseconds) exhibiting decoding trends that mirror those seen for human texture discrimination. High-order statistical sound cues, by comparison, are reflected in the correlation statistics of neural ensembles, which require substantially longer evidence accumulation times (>500 ms) and follow trends that mirror those measured for human texture recognition. Collectively, the findings suggest that spectrum cues and accompanying place rate representation (neural spectrum) may contribute surprisingly little toward the recognition of auditory textures. Instead, high-order statistical sound structure is reflected in the distributed patterns of correlated activity across IC neural ensembles and such neural response structure has the potential to contribute toward the recognition of natural auditory textures.