Differentiable cortical networks for inferences concerning people's intentions versus physical causality

Cortical activity associated with generating an inference was measured using fMRI. Participants read three-sentence passages that differed in whether or not an inference needed to be drawn to understand them. The inference was based on either a protagonist's intention or a physical consequence of a character's action. Activation was expected in Theory of Mind brain regions for the passages based on protagonists' intentions but not for the physical consequence passages. The activation measured in the right temporo-parietal junction was greater in the intentional passages than in the consequence passages, consistent with predictions from a Theory of Mind perspective. In contrast, there was increased occipital activation in the physical inference passages. For both types of passage, the cortical activity related to the reading of the critical inference sentence demonstrated a recruitment of a common inference cortical network. This general inference-related activation appeared bilaterally in the language processing areas (the inferior frontal gyrus, the temporal gyrus, and the angular gyrus), as well as in the medial to superior frontal gyrus, which has been found to be active in Theory of Mind tasks. These findings are consistent with the hypothesis that component areas of the discourse processing network are recruited as needed based on the nature of the inference. A Protagonist monitoring and synthesis network is proposed as a more accurate account for Theory of Mind activation during narrative comprehension.     

Somatoform disorders and causal attributions in patients with suspected allergies: Do somatic causal attributions matter?

Objective

Somatic causal illness attributions are being considered as potential positive criteria for somatoform disorders (SFDs) in DSM-V. The aim of this study was to investigate whether patients diagnosed with SFDs tend towards a predominantly somatic attribution style.

Methods

We compared the causal illness attributions of 48 SFD and 149 non-somatoform disorder patients, in a sample of patients presenting for an allergy diagnostic work-up, and those of 47 controls hospitalised for allergen-specific venom immunotherapy. The SFD diagnosis was established by means of the Structured Clinical Interview for DSM-IV. Both spontaneous and prompted causal illness attributions were recorded through interview and by means of the causal dimension of the Revised Illness Perception Questionnaire (IPQ-R), respectively. Patients' spontaneous and prompted responses were assigned to a psychosocial, somatic, or mixed attribution style.

Results

Both in the free-response task and in their responses to the IPQ-R, SFD patients were no more likely than their nonsomatoform counterparts to focus on somatic explanations for their symptoms. They were just as likely to make psychosocial or mixed causal attributions. However, patients with SFDs were significantly more likely to find fault with medical care in the past.

Conclusion

Our data do not support the use of somatic causal illness attributions as positive criteria for SFDs. They confirm the dynamic and multidimensional nature of causal illness attributions. Clinical implications of these findings are discussed.     

Explanations of depression among Irish migrants in Britain

Irish geographical and cultural propinquity to the UK might be considered as an advantage to migrants. However, research over 40 years shows Irish migrants to have consistent high vulnerability to mental disorders. Only recently have researchers begun to explore the reasons for this morbidity. Taking a previous epidemiological study on depression and Irish migrants as a point of departure, we explored the reasons for this morbidity--we hypothesised that depression may be related to unprepared or spontaneous migration. We report on a qualitative study in order to clarify how, from the migrant's perspective, migration might be related to depression. These perspectives were obtained through in-depth interviews with Irish-born migrants aged 18 and over living in London in order to explore psychological distress through a contextualised 'insiders' account. The interviews were completed with men and women who experienced depression and others who had not. We found that previous theories on Irish migrant psychiatric disorder such as racial discrimination were not supported by the narratives of Irish migrant experience. For many participants, the origins of distress are located in Ireland or in difficult life events and circumstances without a direct relationship to migration. This paper examines the causal attributes to depression among Irish migrants in the UK in the context of pre- and post-migration experiences with particular focus on gender and age.     

The role of biomedical knowledge in diagnosis of difficult clinical cases

Although biomedical knowledge is believed to be of little value in diagnosis of routine clinical cases, studies of clinical reasoning have found that physicians revert to use of basic biomedical knowledge when faced with challenging clinical problems. The current paper presents two experiments that empirically examine the role of biomedical knowledge in diagnosis of difficult cases by novice diagnosticians. Novices are taught to diagnose a series of artificial diseases using either knowledge of causal mechanisms or a list of clinical features. In Experiment 1, participants are then tested on two types of clinical challenges: (1) case summaries with irrelevant findings; (2) cases using unfamiliar terminology. Participants with an understanding of underlying mechanisms out performed their counterparts on both types of cases. In Experiment 2, participants are tested 1 week after initial training. Participants with knowledge of causal mechanisms were found to do better on cases with unfamiliar terminology. The results of the two studies provide additional support for the critical role of biomedical knowledge in diagnosis of difficult clinical cases.     

Epidemiology and causation

Epidemiologists’ discussions on causation are not always very enlightening with regard to the notion of ‘cause’ in epidemiology. Epidemiologists rightly work from a science-based approach to causation in epidemiology, but largely disagree about the matter. Disagreement may be partly due to confusion of the question of useful concepts for causal inference in epidemiological practice with the question of the metaphysical presuppositions of causal concepts used in epidemiology. In other words, epidemiologists seem to confuse the practical results of epidemiological research at the population level with the metaphysical views about the reality of disease causation at the individual level in their writings on causation.

疟疾防治药物的研究——Ⅺ.2,4-二氨基-6-(N-取代-对氯苄氨基)喹唑啉衍生物的合成及其抗疟作用

合成2,4-二氨基-6-(N-取代-对氯苄氨基)喹唑啉衍生物33个,经伯氏鼠疟原虫(Plasmodium berghei)抑制性治疗筛选,剂量20mg/kg×3d,有10个化合物(1,2,5～8,14,20,21,26)抑制率在90%以上。经约氏鼠疟原虫(P.yoelii)斯氏按蚊系统的病因性预防筛选,剂量5mg/kg×3d,有26个化合物(1～12,14,20～22,24～33)使小白鼠全部得到保护;剂量下降到0.625mg/kg×3d,有14个化合物(5～12,14,20,21,26,31,33)使小白鼠全部得到保护(表1)。4个化合物(1,8,20,25,表2,3)进行了猴疟(P.cynomolgi)试验,效果不及伯喹和乙胺嘧啶。     

基于孟德尔随机化探索臀围与2型糖尿病的因果关系

  目的   采用孟德尔随机化分析方法, 探讨臀围与2型糖尿病的因果关联。   方法   将分别来自人体测量特征遗传研究(genetic investigation of anthropometric traits, GIANT)和糖尿病遗传学验证和荟萃分析(diabetes genetics replication and Meta-analysis, DIAGRAM)数据库的臀围和2型糖尿病遗传位点数据, 据单核苷酸多态性(single nucleotide polymorphism, SNP)编号匹配合并, 以与臀围密切相关的SNP为工具变量, 运用逆方差加权法、MR-Egger回归模型和加权中位数法分析臀围对2型糖尿病的因果效应。   结果   不分性别队列、女性队列和男性队列中分别匹配到52、9和15个SNP。异质性检验结果提示SNP间同质。三个队列的OR值及其95%的置信区间分别为1.065(1.030~1.100)、1.103(1.057~1.150)和1.583(1.273~1.968), 均有统计学意义(均有P < 0.05)。敏感性分析结果显示三个队列逐一移除SNP, 其因果效应不受影响, 结果稳健。   结论   人体臀围与2型糖尿病之间均存在因果关联, 臀围可能为2型糖尿病的危险因素。     

孟德尔随机化研究应用于因果推断的影响因素及其结果解读面临的挑战

孟德尔随机化（Mendelian randomization,MR）研究使用遗传变异作为工具变量,推断暴露因素与结局之间的因果关系,能够有效克服混杂和反向因果问题所导致的偏倚。然而,MR研究中的工具变量须满足关联性、独立性和排他性3个核心假设。即使核心假设成立,MR研究在因果推断中的应用还受到其他局限性的影响。此外,MR研究结果的解读需要基于综合证据。本文将围绕MR研究应用于因果推断的影响因素和研究结果的解读进行综述,以期为MR研究结果应用提供指导。     

Estimation of treatment effect in a subpopulation: An empirical Bayes approach

It is well recognized that the benefit of a medical intervention may not be distributed evenly in the target population due to patient heterogeneity, and conclusions based on conventional randomized clinical trials may not apply to every person. Given the increasing cost of randomized trials and difficulties in recruiting patients, there is a strong need to develop analytical approaches to estimate treatment effect in subpopulations. In particular, due to limited sample size for subpopulations and the need for multiple comparisons, standard analysis tends to yield wide confidence intervals of the treatment effect that are often noninformative. We propose an empirical Bayes approach to combine both information embedded in a target subpopulation and information from other subjects to construct confidence intervals of the treatment effect. The method is appealing in its simplicity and tangibility in characterizing the uncertainty about the true treatment effect. Simulation studies and a real data analysis are presented.