综合医院精神科联络会诊分析

目的探讨综合医院各临床科室请精神科联络会诊的特点。方法收集2007年7月～2008年8月共计14个月的会诊病例,通过会诊邀请单及自编的会诊情况问卷收集资料。采用SPSS12．0进行统计。结果邀请会诊年龄在5～97岁,平均（52±21）岁,男性占50％以上;按会诊分配比例由高到低的科室为神经内科、骨科、脑外科、老年病科、消化科、心内科等。结论精神科联络会诊在各年龄段均有,以中老年为主;申请科室中除神内、脑外以外,骨科和老年病科也较多;年转入率减低,而精神科药物使用在各科室逐渐增多。生物-心理-社会医学模式渐入人心。     

Feature binding and affect: emotional modulation of visuo-motor integration

The primate cortex represents the external world in a distributed fashion, which calls for a mechanism that integrates and binds the features of a perceived or processed event. Animal and patients studies provide evidence that feature binding in the visual cortex is driven by the muscarinic-cholinergic system, whereas visuo-motor integration may be under dopaminergic control. Consistent with this scenario, we present indication that the binding of visual and action features is modulated by emotions through the probable stimulation of the dopaminergic system. Interestingly, the impact of emotions on binding was restricted to tasks in which shape was task-relevant, suggesting that extracting affective information is not automatic but requires attention to shape.     

Early induced beta/gamma activity during illusory contour perception

The temporal binding hypothesis proposes that visual feature binding is achieved by neuronal synchronization. Nevertheless, the existing human neurophysiological evidence for the neuronal synchronization in visual feature binding—the oscillatory induced beta/gamma activity (IB/GA) is under suspicion. The previously observed IB/GA occurs at a later stage (after 200 ms), thus leading to the objection that IB/GA may be related to some later top-down processes rather than the early perceptual processing. However, the present EEG study identified an IB/GA as early as 90 ms after stimulus onset, which was stronger for a Kanizsa-type illusory contour (IC, a classic example of visual feature binding) than for a control stimulus. This finding provides new human evidence for the temporal binding hypothesis that neuronal synchronization occurs at the early stage of visual feature binding.     

A Wavelet Packet-Based Algorithm for the Extraction of Neural Rhythms

Neural rhythms are associated with different brain functions and pathological conditions. These rhythms are often clinically relevant for purposes of diagnosis or treatment, though their complex, time-varying features make them difficult to isolate. The wavelet packet transform has proven itself to be versatile and effective with respect to resolving signal features in both time and frequency. We propose a signal analysis technique, called neural rhythm extraction (NRE) that incorporates wavelet packet analysis along with a threshold-based scheme for separating rhythmic neural features from non-rhythmic ones. We applied NRE to rat in vitro intracellular recordings and human scalp electroencephalogram (EEG) signals, and were able to isolate and classify individual neural rhythms in signals containing large amplitude spikes and other artifacts. NRE is capable of discriminating signal features sharing similar time or frequency localization, as well as extracting low-amplitude, low-power rhythms otherwise masked by spectrally dominant signal components. The algorithm allows for independent retention and reconstruction of rhythmic features, which may serve to enhance other analysis techniques such as independent component analysis (ICA), and aid in application-specific tasks such as detection, classification or tracking.     

Goal-directed learning of features and forward models

The brain is able to perform actions based on an adequate internal representation of the world, where task-irrelevant features are ignored and incomplete sensory data are estimated. Traditionally, it is assumed that such abstract state representations are obtained purely from the statistics of sensory input for example by unsupervised learning methods. However, more recent findings suggest an influence of the dopaminergic system, which can be modeled by a reinforcement learning approach. Standard reinforcement learning algorithms act on a single layer network connecting the state space to the action space. Here, we involve in a feature detection stage and a memory layer, which together, construct the state space for a learning agent. The memory layer consists of the state activation at the previous time step as well as the previously chosen action. We present a temporal difference based learning rule for training the weights from these additional inputs to the state layer. As a result, the performance of the network is maintained both, in the presence of task-irrelevant features, and at randomly occurring time steps during which the input is invisible. Interestingly, a goal-directed forward model emerges from the memory weights, which only covers the state–action pairs that are relevant to the task. The model presents a link between reinforcement learning, feature detection and forward models and may help to explain how reward systems recruit cortical circuits for goal-directed feature detection and prediction.     

2008年肺结核病报告疫情分布特征

目的运用“疾病监测信息报告管理系统”分析深圳市肺结核报告分布特征。方法收集“疾病监测信息报告管理系统”肺结核网络直报资料进行分析。结果2008年报告肺结核5862例,与前一年同期对比增加1247例、占27．0％;报告发病率为68．0/10万;肺结核病男性多于女性,男性3826例、占65．3％,女性2036例、占34．7％;年龄分布两头低。中间高,各年龄组的男性病人均高于女性,其中15州岁的病人占了绝大多数,占85．2％;报告病例中工人占比例最大39．3％,其次是家务及待业37．2％。结论肺结核病目前主要危害具有社会创造潜力的劳动人群的身体健康及生命安全,对社会生产和经济发展影响较大。     

Feature extraction and dimensionality reduction for mass spectrometry data

Mass spectrometry is being used to generate protein profiles from human serum, and proteomic data obtained from mass spectrometry have attracted great interest for the detection of early stage cancer. However, high dimensional mass spectrometry data cause considerable challenges. In this paper we propose a feature extraction algorithm based on wavelet analysis for high dimensional mass spectrometry data. A set of wavelet detail coefficients at different scale is used to detect the transient changes of mass spectrometry data. The experiments are performed on 2 datasets. A highly competitive accuracy, compared with the best performance of other kinds of classification models, is achieved. Experimental results show that the wavelet detail coefficients are efficient way to characterize features of high dimensional mass spectra and reduce the dimensionality of high dimensional mass spectra.     

心脏内平滑肌病的临床特点及外科治疗

目的总结心脏内平滑肌瘤病（intracardiac leiomyomatosis,ICL）的临床特点及外科治疗经验。方法回顾分析1999年1月至2009年1月新乡医学院第一附属医院收治的5例心脏内平滑肌瘤病患者的临床资料。结果 5例患者均为女性,有明显心慌、胸闷、晕厥或静脉栓塞等症状。影像学检查在右房及下腔静脉发现瘤栓。其中4例有＂子宫肌瘤手术史＂,1例入院后B超检查发现＂子宫肌瘤＂。5例患者均接受手术治疗,其中1例行单纯心房内瘤体切除,半年后病变复发,再次手术后死于多器官功能衰竭。4例经胸腹联合切口行分期根治术,一期完整切除右房及下腔静脉内所有瘤体,6～9个月后由妇产科行二期手术治疗原发病灶,随访2年,心脏及下腔静脉内均无肿瘤复发,无明显临床症状。结论心脏平滑肌瘤临床发病率低,手术是最主要的治疗方法,彻底切净肿瘤是成功治疗的关键。     

Feature conjunctions and auditory sensory memory

This study sought to obtain additional evidence that transient auditory memory stores information about conjunctions of features on an automatic basis. The mismatch negativity of event-related potentials was employed because its operations are based on information that is stored in transient auditory memory. The mismatch negativity was found to be elicited by a tone that differed from standard tones in a combination of its perceived location and frequency. The result lends further support to the hypothesis that the system upon which the mismatch negativity relies processes stimuli in an holistic manner.     

SARS临床特征分析(附56例病例报告)

目的 :归纳和探讨临床诊断SARS病例的临床特征、实验室检查及X线胸片变化规律。方法 :对 5 6例临床诊断为SARS病例的临床表现、血常规、血氧饱和度和X线胸片等资料进行收集整理、归纳总结和分析。结果 :本组病例全部以高热和全身不适、乏力和肌肉酸痛为主诉症状 ;2 0例有明确一次性接触史者的平均潜伏期为 ( 4 .70± 0 .92 )d(X±SD ) ;大部分病例有干咳 ( 71 .4% )、气短 ( 4 8.2 % ) ,少数病例在病程中有短暂的胸痛、头痛和鼻塞 ,但无 1例发生腹泻。血常规检查 ,1 0 0 %的患者有白细胞减少 ( <4× 1 0 9/L)和淋巴细胞计数减少 ( <1 .5× 1 0 9/L) ,5 3.6%的病例出现血氧饱和度降低 ( <90 % )。X线胸片异常改变中双侧云雾状阴影占 62 .5 % ,单侧病变占 32 .1 % ,单一肺叶病变的仅占 5 .4%。结论 :本组SARS病人的主要临床症状与WHO提示的有关症状基本符合 ,但未见腹泻和血小板下降者 ;X线胸片单侧病变也占相当比例 ( 32 .1 + 5 .4) %。胸片病变局限可能与及时治疗干预有关。