This is a copy of the slides presented at the meeting but not formally written up for the volume.

Single-molecule manipulation and detection of biomolecules has significantly advanced our understanding of the molecular movement, dynamics, and biological function of proteins. Fluorescence microscopy currently serves as one of the primary noninvasive techniques for the sensitive detection of molecules in solution and on surfaces. However, the performance and sensitivity of this laser-induced fluorescence technique is strongly influenced by the fluorescent labels attached to DNA, proteins or cells. Organic dyes have most commonly been used as fluorescent biolabels; however, they quickly photobleach, limiting the time scale over which molecular events can be followed. Quantum dots show great promise for fluorescence measurements due to their improved photophysical properties, such as size-tunable narrow emissions, large Stokes shifts and minimal photobleaching. However, problems still exist for the use of quantum dots as biolabels, including: photoblinking, toxic synthetic approaches, surface passivation issues and relatively large physical sizes that are comparable to proteins. Here, we report the synthesis of a new class of fluorescent labels, gold nanoclusters, which consist of several gold atoms (<1 nm in size) with strong fluorescence emission. These small fluorescent gold nanoclusters are synthesized at physiological temperature using poly(amidoamine) dendrimer as a template. Small blue emissive gold nanoclusters were produced without the use of a reductant and without concurrent nanoparticle formation. Gold nanoclusters with green and red emissions were synthesized using a mild reductant, also without nanoparticle formation. The studies of pH-dependent stability suggest that these fluorescent nanoclusters are very stable in a pH range of 6 - 8. These new approaches produce gold nanoclusters with a much higher yield and eliminate the toxicity of the previously reported process, resulting in a biologically compliant approach. This work is the first known report of fluorescent gold nanoclusters via a green-chemistry approach and without the formation of gold nanoparticles. This work is funded by Los Alamos Laboratory Directed research and Development program.

Compulsive behaviors in obsessive-compulsive disorder (OCD) have been related to impairment within the associative cortical-striatal system connecting the caudate and prefrontal cortex that underlies consciously-controlled goal-directed learning and behavior. However, little is known whether this impairment may serve as a biomarker for vulnerability to OCD.

Using resting-state functional magnetic resonance imaging (fMRI), we employed Granger causality analysis (GCA) to measure effective connectivity (EC) in previously validated striatal sub-regions, including the caudate, putamen, and the nucleus accumbens, in 35 OCD patients, 35 unaffected first-degree relatives and 35 matched healthy controls.

Both OCD patients and their first-degree relatives showed greater EC than controls between the left caudate and the orbital frontal cortex (OFC). Both OCD patients and their first-degree relatives showed lower EC than controls between the left caudate and lateral prefrontal cortex. These results are consistent with findings from task-related fMRI studies which found impairment in the goal-directed system in OCD patients.

The same changes in EC were present in both OCD patients and their unaffected first-degree relatives suggest that impairment in the goal-directed learning system may be a biomarker for OCD.

Schizophrenia is a complex mental disorder with high heritability and polygenic inheritance. Multimodal neuroimaging studies have also indicated that abnormalities of brain structure and function are a plausible neurobiological characterisation of schizophrenia. However, the polygenic effects of schizophrenia on these imaging endophenotypes have not yet been fully elucidated.

To investigate the effects of polygenic risk for schizophrenia on the brain grey matter volume and functional connectivity, which are disrupted in schizophrenia.

Genomic and neuroimaging data from a large sample of Han Chinese patients with schizophrenia (N = 509) and healthy controls (N = 502) were included in this study. We examined grey matter volume and functional connectivity via structural and functional magnetic resonance imaging, respectively. Using the data from a recent meta-analysis of a genome-wide association study that comprised a large number of Chinese people, we calculated a polygenic risk score (PGRS) for each participant.

The imaging genetic analysis revealed that the individual PGRS showed a significantly negative correlation with the hippocampal grey matter volume and hippocampus–medial prefrontal cortex functional connectivity, both of which were lower in the people with schizophrenia than in the controls. We also found that the observed neuroimaging measures showed weak but similar changes in unaffected first-degree relatives of patients with schizophrenia.

These findings suggested that genetically influenced brain grey matter volume and functional connectivity may provide important clues for understanding the pathological mechanisms of schizophrenia and for the early diagnosis of schizophrenia.

None.

Cognitive impairment in late-life depression is common and associated with a higher risk of all-cause dementia. Late-life depression patients with comorbid cardiovascular diseases (CVDs) or related risk factors may experience higher risks of cognitive deterioration in the short term. We aim to investigate the effect of CVDs and their related risk factors on the cognitive function of patients with late-life depression.

A total of 148 participants were recruited (67 individuals with late-life depression and 81 normal controls). The presence of hypertension, coronary heart disease, diabetes mellitus, or hyperlipidemia was defined as the presence of comorbid CVDs or related risk factors. Global cognitive functions were assessed at baseline and after a one-year follow-up by the Mini-Mental State Examination (MMSE). Global cognitive deterioration was defined by the reliable change index (RCI) of the MMSE.

Late-life depression patients with CVDs or related risk factors were associated with 6.8 times higher risk of global cognitive deterioration than those without any of these comorbidities at a one-year follow-up. This result remained robust after adjusting for age, gender, and changes in the Hamilton Depression Rating Scale (HAMD) scores.

This study suggests that late-life depression patients with comorbid CVDs or their related risk factors showed a higher risk of cognitive deterioration in the short-term (one-year follow up). Given that CVDs and their related risk factors are currently modifiable, active treatment of these comorbidities may delay rapid cognitive deterioration in patients with late-life depression.