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Since the discovery of ABO blood types, there has been mounting evidence of the association between blood types and infectious diseases. However, so far, there is rarely available research about the potential role of ABO blood types in haemorrhagic fever with renal syndrome (HFRS) infection. Our aim was to investigate the relationship between ABO blood types and the development of HFRS infection in Qingdao, China. We carried out a retrospective study enrolling 116 HFRS patients as the case group and 373 healthy subjects as the control group. ABO blood type distribution was analysed using the Chi-square test and logistic regression analysis. Results showed that the distribution of ABO blood types between the two groups was significantly different (X2 = 18.151, P < 0.05). Blood type B was less frequently observed [odds ratio (OR), 0.404; confidence interval (CI), 0.238–0.684; P < 0.01], while blood type AB was more frequently observed in the case group (OR, 2.548; CI, 1.427–4.549; P < 0.01). Since significantly more males were affected than females, we further analysed the data by gender as well as blood types and obtained consistent results for males. Our findings indicated that populations with blood type AB might be more prone to HFRS infection, whereas those with blood type B might be less susceptible to HFRS infection, which will help to make risk stratification in infection control.
Major depressive disorder (MDD) is a clinically and biologically heterogeneous syndrome. Identifying discrete subtypes of illness with distinguishing neurobiological substrates and clinical features is a promising strategy for guiding personalised therapeutics.
This study aimed to identify depression subtypes with correlated patterns of functional network connectivity and clinical symptoms by clustering patients according to a weighted linear combination of both features in a relatively large, medication-naïve depression sample.
We recruited 115 medication-naïve adults with MDD and 129 matched healthy controls, and evaluated all participants with magnetic resonance imaging. We used regularised canonical correlation analysis to identify component mapping relationships between functional network connectivity and symptom profiles, and K-means clustering was used to define distinct subtypes of patients.
Two subtypes of MDD were identified: insomnia-dominated subtype 1 and anhedonia-dominated subtype 2. Subtype 1 was characterised by abnormal hyperconnectivity within the ventral attention network and sleep maintenance insomnia. Subtype 2 was characterised by abnormal hypoconnectivity in the subcortical and dorsal attention networks, and prominent anhedonia symptoms.
Our study identified two distinct subtypes of patients with specific neurobiological and clinical symptom profiles. These findings advance understanding of the biological and clinical heterogeneity of MDD, offering a pathway for defining categorical subtypes of illness via consideration of both biological and clinical features.
Altered resting-state functional connectivity (rsFC) has been noted in large-scale functional networks in attention-deficit/hyperactivity disorder (ADHD). However, identifying consistent abnormalities of functional networks is difficult due to varied methods and results across studies. To integrate rsFC alterations and search for coherent patterns of intrinsic functional network impairments in ADHD, this research conducts a coordinate-based meta-analysis of voxel-wise seed-based rsFC studies comparing rsFC between ADHD patients and healthy controls. A total of 25 datasets from 21 studies including 700 ADHD patients and 580 controls were analyzed. We extracted the coordinates of seeds and between-group effects. Each seed was then categorized into a seed-network by its location within priori 7-network parcellations. Then, pooled meta-analyses were conducted for the default mode network (DMN), frontoparietal network (FPN) and affective network (AN) separately, but not for the ventral attention network (VAN), dorsal attention network (DAN), somatosensory network (SSN) and visual network due to a lack of primary studies. The results showed that ADHD was characterized by hyperconnectivity between the FPN and regions of the DMN and AN as well as hypoconnectivity between the FPN and regions of the VAN and SSN. These findings not only support the triple-network model of pathophysiology associated with ADHD but also extend this model by highlighting the involvement of the SSN and AN in the mechanisms of network interactions that may account for motor hyperactivity and impulsive symptoms.
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