Rapid detection of nicotine and benzoic acid in e-liquids with surface-enhanced Raman scattering and artificial intelligence-assisted spectrum interpretation.

Electronic cigarettes have rapidly gained acceptance recently. Nicotine-containing electronic cigarette liquids (e-liquids) are prohibited in some countries, but are permitted and simply available online in others. A rapid detection method is therefore required for on-site inspection or screening of a large amount of samples. Our previous study demonstrated a surface-enhanced Raman scattering (SERS)-based approach to identify nicotine-containing e-liquids; without any pre-treatment, e-liquid can be directly tested on our solid-phase SERS substrates, made of silver nanoparticle arrays embedded in anodic aluminium oxide nanochannels (Ag/AAO). However, this approach required manual determination of spectral signatures and negative samples should be validated in the second round detection. Here, after examining 406 commercial e-liquids, we refined this approach by developing artificial intelligence (AI)-assisted spectrum interpretations. We also found that nicotine and benzoic acid can be simultaneously detected in our platform. This increased test sensitivity because benzoic acid is usually used in nicotine salts. Around 64% of nicotine-positive samples in this study showed both signatures. Using either cutoffs of nicotine and benzoic acid peak intensities or a machine learning model based on the CatBoost algorithm, over 90% of tested samples can be correctly discriminated with only one round of SERS measurement. False negative and false positive rates were 2.5-4.4% and 4.4-8.9%, respectively, depending on the interpretation method and thresholds applied. The new approach takes only 1 microliter of sample and can be performed in 1-2 min, suitable for on-site inspection with portable Raman detectors. It could also be a complementary platform to reduce samples that need to be analyzed in the central labs and has the potential to identify other prohibited additives.

Functional, Anatomical, and Morphological Networks Highlight the Role of Basal Ganglia-Thalamus-Cortex Circuits in Schizophrenia.

Evidence from electrophysiological, functional, and structural research suggests that abnormal brain connectivity plays an important role in the pathophysiology of schizophrenia. However, most previous studies have focused on single modalities only, each of which is associated with its own limitations. Multimodal combinations can more effectively utilize various information, but previous multimodal research mostly focuses on extracting local features, rather than carrying out research based on network perspective. This study included 135 patients with schizophrenia and 148 sex- and age-matched healthy controls. Functional magnetic resonance imaging, diffusion tensor imaging, and structural magnetic resonance imaging data were used to construct the functional, anatomical, and morphological networks of each participant, respectively. These networks were used in combination with machine learning to identify more consistent biomarkers of brain connectivity and explore the relationships between different modalities. We found that although each modality had divergent connectivity biomarkers, the convergent pattern was that all were mostly located within the basal ganglia-thalamus-cortex circuit. Furthermore, using the biomarkers of these 3 modalities as a feature yielded the highest classification accuracy (91.75%, relative to a single modality), suggesting that the combination of multiple modalities could be effectively utilized to obtain complementary information regarding different mode networks; furthermore, this information could help distinguish patients. These findings provide direct evidence for the disconnection hypothesis of schizophrenia, suggesting that abnormalities in the basal ganglia-thalamus-cortex circuit can be used as a biomarker of schizophrenia.

The Effects of Tai Chi on Sleep Quality in Chinese American Patients With Major Depressive Disorder: A Pilot Study.

OBJECTIVE: This pilot study evaluated the effects of Tai Chi training on sleep quality (primary outcomes), and depression and social functioning levels (secondary outcomes) among patients with depression. PARTICIPANTS: Sixteen depressed Chinese patients. METHODS: Participants received 1-hr Tai Chi training sessions 2 times per week for 10 weeks. Patients' subjective sleep quality ratings, objective sleep quality measurements, and depression and social functioning levels were measured before, during, and after the intervention. RESULTS: Sleep quality and depression outcomes improved significantly. Patients reported improved Pittsburgh Sleep Quality Index (PSQI) scores (9.6 ± 3.3 to 6.6 ± 5.2, p = 0.016), and cardiopulmonary coupling (CPC) analysis of electrocardiogram (ECG) showed decreased stable sleep onset latency (75.7 ± 100.6 to 20.9 ± 18.0, p = 0.014), increased stable sleep percentages (31.5 ± 18.7 to 46.3 ± 16.9, p = 0.016), and decreased unstable sleep percentages (45.3 ± 20.1 to 30.6 ± 16.5, p = 0.003). Patients also reported decreased Hamilton Rating Scale for Depression (HAM-D-17; 20.1 ± 3.7 to 7.8 ± 5.9, p < 0.001) and Beck Depression Inventory (BDI) scores (22.3 ± 9.1 to 11.1 ± 10.6, p = 0.006). Significant correlations were found between the changes in subjective sleep assessments ΔPSQI and ΔHAM-D-17 (r = 0.6, p = 0.014), and ΔPSQI and ΔBDI (r = 0.62, p = 0.010). Correlations between changes in objective sleep measurements and changes in depression symptoms were low and not significant. CONCLUSIONS: Tai Chi training improved sleep quality and mood symptoms among depressed patients.

Risk of developing major depression and anxiety disorders among women with endometriosis: A longitudinal follow-up study.

BACKGROUNDS: Several cross-sectional studies suggested a link between endometriosis and mood disorders. However, the temporal association between endometriosis and mood disorders (depression and anxiety disorders) is still unclear. METHODS: Using the Taiwan National Health Insurance Research Database, 10,439 women with endometriosis and 10,439 (1:1) age-/sex-matched controls between 1998 and 2009 were enrolled, and followed up to the end of 2011. Those who developed depression or anxiety disorders during the follow-up were identified. RESULTS: Women with endometriosis had an increased risk of developing major depression (hazard ratio [HR]: 1.56, 95% confidence interval [CI]:1.24-1.97), any depressive disorder (HR: 1.44, 95% CI: 1.25-1.65), and anxiety disorders (HR: 1.44, 95% CI: 1.22-1.70) in later life compared to those without endometriosis. Stratified by age group, women with endometriosis aged <40 years and those aged ≧40 years were both prone to developing major depression (HR: 1.52, 95% CI: 1.15-1.99; HR: 1.69, 95% CI: 1.09-2.62), any depressive disorder (HR: 1.43, 95% CI: 1.21-1.69; HR: 1.45, 95% CI: 1.13-1.56), and anxiety disorders (HR: 1.39, 95% CI: 1.14-1.71; HR: 1.53, 95% CI: 1.15-2.04). LIMITATION: the incidence of depression and anxiety disorders may be underestimated since only those who sought medical consultation and help would be enrolled in our study. CONCLUSION: Endometriosis was associated with an elevated likelihood of developing depression and anxiety disorders. Further studies may be required to investigate the underlying pathophysiology between endometriosis and both depression and anxiety disorders.

Bidirectional Association Between Depression and Fibromyalgia Syndrome: A Nationwide Longitudinal Study.

Several cross-sectional studies have reported a common comorbidity between depression and fibromyalgia syndrome (FMS). However, a bidirectional temporal association between these 2 distinct diseases has rarely been investigated. Using the Taiwan National Health Insurance Research Database, 25,969 patients with FMS and without any psychiatric disorder and 17,142 patients with depression and without FMS between 2000 and 2008 were enrolled and separately compared with age- and sex-matched (1:4) control groups. Patients with FMS who developed a new-onset depression and those with depression who developed new-onset FMS were identified during follow-up (to the end of 2011). The conditional Cox regression analyses, after adjustment for demographic data and medical comorbidities, showed that the patients with FMS were associated with an increased risk (hazard ratio [HR] 7.46, 95% confidence interval [CI] 6.77-8.22) of subsequent depression and that those with depression were associated with an increased risk (HR 6.28, 95% CI 5.67-6.96) of subsequent FMS. Our results supported a bidirectional temporal association between depression and FMS. Each disease occurring first may increase the risk of the other subsequently. Further study may be necessary to determine the underlying mechanism between depression and FMS and to clarify whether a prompt intervention for depression or FMS may decrease the risk of the other later in life. Perspective: Our study supported a bidirectional temporal association between depression and FMS such that each disease occurring first may increase the risk of the other subsequently. This result may imply a shared pathophysiology between FMS and depression, but further investigation is needed.

Publication analysis on insomnia: how much has been done in the past two decades?

Insomnia has been a rising public concern in recent years. As one example of a multidisciplinary topic, the theme of insomnia research has gradually shifted over time; however, there is very little quantitative characterization of the research trends in insomnia. The current study aims to quantitatively analyze trends in insomnia publications for the past 20 years. We retrospectively analyzed insomnia-related publications retrieved from PubMed and Google Scholar between 1994 and from a number of different perspectives. We investigated the major areas of research focus for insomnia, journal characteristics, as well as trends in clinical management and treatment modalities. The resulting 5841 publications presented an exponential growth trend over the past two decades, with mean annual growth rates at nearly 10% for each publication type. Analysis of major research focuses indicated that depression, hypnotics and sedatives, questionnaires, and polysomnography are the most common topics at present. Furthermore, we found that while studies on drug therapy and adverse effects decreased in the most recent five years, the greatest expansion of insomnia publications were in the areas of cognitive behavioral therapy for insomnia (CBT-I) and alternative therapies. Collectively, insomnia publications present a continuous trend of increase. While sedative and hypnotic drugs dominated the treatment of insomnia, non-pharmacological therapies may have great potential for advancement in future years. Future research effort is warranted for novel tools and clinical trials, especially on insomnia treatments with inadequate evidence or not-yet-clear efficacy and side effects.