Mental Wellness Self-Care in Singapore With mindline.sg: A Tutorial on the Development of a Digital Mental Health Platform for Behavior Change.

BACKGROUND: Singapore, like the rest of Asia, faces persistent challenges to mental health promotion, including stigma around unwellness and seeking treatment and a lack of trained mental health personnel. The COVID-19 pandemic, which created a surge in mental health care needs and simultaneously accelerated the adoption of digital health solutions, revealed a new opportunity to quickly scale innovative solutions in the region. OBJECTIVE: In June 2020, the Singaporean government launched mindline.sg, an anonymous digital mental health resource website that has grown to include >500 curated local mental health resources, a clinically validated self-assessment tool for depression and anxiety, an artificial intelligence (AI) chatbot from Wysa designed to deliver digital therapeutic exercises, and a tailored version of the website for working adults called mindline at work. The goal of the platform is to empower Singapore residents to take charge of their own mental health and to be able to offer basic support to those around them through the ease and convenience of a barrier-free digital solution. METHODS: Website use is measured through click-level data analytics captured via Google Analytics and custom application programming interfaces, which in turn drive a customized analytics infrastructure based on the open-source platforms Titanium Database and Metabase. Unique, nonbounced (users that do not immediately navigate away from the site), engaged, and return users are reported. RESULTS: In the 2 years following launch (July 1, 2020, through June 30, 2022), the website received >447,000 visitors (approximately 15% of the target population of 3 million), 62.02% (277,727/447,783) of whom explored the site or engaged with resources (referred to as nonbounced visitors); 10.54% (29,271/277,727) of those nonbounced visitors returned. The most popular features on the platform were the dialogue-based therapeutic exercises delivered by the chatbot and the self-assessment tool, which were used by 25.54% (67,626/264,758) and 11.69% (32,469/277,727) of nonbounced visitors. On mindline at work, the rates of nonbounced visitors who engaged extensively (ie, spent ≥40 seconds exploring resources) and who returned were 51.56% (22,474/43,588) and 13.43% (5,853/43,588) over a year, respectively, compared to 30.9% (42,829/138,626) and 9.97% (13,822/138,626), respectively, on the generic mindline.sg site in the same year. CONCLUSIONS: The site has achieved desired reach and has seen a strong growth rate in the number of visitors, which required substantial and sustained digital marketing campaigns and strategic outreach partnerships. The site was careful to preserve anonymity, limiting the detail of analytics. The good levels of overall adoption encourage us to believe that mild to moderate mental health conditions and the social factors that underly them are amenable to digital interventions. While mindline.sg was primarily used in Singapore, we believe that similar solutions with local customization are widely and globally applicable.

Site-Selective Distal C(sp3)-H Bromination of Aliphatic Amines as a Gateway for Forging Nitrogen-Containing sp3 Architectures.

Herein, we disclose a new strategy that rapidly and reliably incorporates bromine atoms at distal, secondary C(sp3)-H sites in aliphatic amines with an excellent and predictable site-selectivity pattern. The resulting halogenated building blocks serve as versatile linchpins to enable a series of carbon-carbon and carbon-heteroatom bond-formations at remote C(sp3) sites, thus offering a new modular and unified platform that expediates the access to advanced sp3 architectures possessing valuable nitrogen-containing saturated heterocycles of interest in medicinal chemistry settings.

The influence of microsatellite polymorphisms in sex steroid receptor genes ESR1, ESR2 and AR on sex differences in brain structure.

The androgen receptor (AR), oestrogen receptor alpha (ESR1) and oestrogen receptor beta (ESR2) play essential roles in mediating the effect of sex hormones on sex differences in the brain. Using Voxel-based morphometry (VBM) and gene sizing in two independent samples (discovery n â€‹= â€‹173, replication â€‹= â€‹61), we determine the common and unique influences on brain sex differences in grey (GM) and white matter (WM) volume between repeat lengths (n) of microsatellite polymorphisms AR(CAG)n, ESR1(TA)n and ESR2(CA)n. In the hypothalamus, temporal lobes, anterior cingulate cortex, posterior insula and prefrontal cortex, we find increased GM volume with increasing AR(CAG)n across sexes, decreasing ESR1(TA)n across sexes and decreasing ESR2(CA)n in females. Uniquely, AR(CAG)n was positively associated with dorsolateral prefrontal and orbitofrontal GM volume and the anterior corona radiata, left superior fronto-occipital fasciculus, thalamus and internal capsule WM volume. ESR1(TA)n was negatively associated with the left superior corona radiata, left cingulum and left inferior longitudinal fasciculus WM volume uniquely. ESR2(CA)n was negatively associated with right fusiform and posterior cingulate cortex uniquely. We thus describe the neuroanatomical correlates of three microsatellite polymorphisms of steroid hormone receptors and their relationship to sex differences.

FusionSense: Emotion Classification Using Feature Fusion of Multimodal Data and Deep Learning in a Brain-Inspired Spiking Neural Network.

Using multimodal signals to solve the problem of emotion recognition is one of the emerging trends in affective computing. Several studies have utilized state of the art deep learning methods and combined physiological signals, such as the electrocardiogram (EEG), electroencephalogram (ECG), skin temperature, along with facial expressions, voice, posture to name a few, in order to classify emotions. Spiking neural networks (SNNs) represent the third generation of neural networks and employ biologically plausible models of neurons. SNNs have been shown to handle Spatio-temporal data, which is essentially the nature of the data encountered in emotion recognition problem, in an efficient manner. In this work, for the first time, we propose the application of SNNs in order to solve the emotion recognition problem with the multimodal dataset. Specifically, we use the NeuCube framework, which employs an evolving SNN architecture to classify emotional valence and evaluate the performance of our approach on the MAHNOB-HCI dataset. The multimodal data used in our work consists of facial expressions along with physiological signals such as ECG, skin temperature, skin conductance, respiration signal, mouth length, and pupil size. We perform classification under the Leave-One-Subject-Out (LOSO) cross-validation mode. Our results show that the proposed approach achieves an accuracy of 73.15% for classifying binary valence when applying feature-level fusion, which is comparable to other deep learning methods. We achieve this accuracy even without using EEG, which other deep learning methods have relied on to achieve this level of accuracy. In conclusion, we have demonstrated that the SNN can be successfully used for solving the emotion recognition problem with multimodal data and also provide directions for future research utilizing SNN for Affective computing. In addition to the good accuracy, the SNN recognition system is requires incrementally trainable on new data in an adaptive way. It only one pass training, which makes it suitable for practical and on-line applications. These features are not manifested in other methods for this problem.

Applications of CRISPR in Parasitology.

Clustered Regions of Interspersed Palindromic Repeat (CRISPR)-based techniques have been utilized in various research areas, including agriculture, biotechnology, and medicine. With the use of a short sequence guide RNA and CRISPR-associated (Cas) protein, this technique allows for robust, site-specific manipulation of the genome, aiding researchers in making important biomedical discoveries and scientific advancements. In this review, we explored the applications of CRISPR/Cas systems in the field of parasitology for the identification and validation of novel functional genes, diagnosis of parasitic infections, reduction of parasite virulence, and the disruption of disease transmission. We also discussed how CRISPR can be used for the development of therapeutics, vaccines, and drug discovery. Furthermore, the challenges and future perspectives of this technology are also highlighted.

Molecular characterization of hepatitis B virus surface antigen mutants in Singapore patients with hepatocellular carcinoma and hepatitis B virus carriers negative for HBsAg but positive for anti-HBs and anti-HBc.

BACKGROUND AND AIMS: Mutations on the a-determinant of hepatitis B virus surface antigen (HBsAg), capable of escaping detection and vaccination, are identified in HBsAg-positive/anti-HBs-positive vaccinated infants. We studied the prevalence of these mutants in HBsAg-negative/anti-HBc-positive chronic HBV carriers and patients with hepatocellular carcinoma (HCC). METHODS: DNA sequence coding for the antigenic a-determinant of HBsAg was amplified from either HCC genomic DNA or serum samples of the selected patients and sequenced. The replicative mutant genomes were reconstituted in vitro and their reactivity to commercial kits measured. RESULTS: Mutations within and/or outside the a-determinant were identified in patients seronegative for HBsAg. They were then reconstituted in vitro and transiently transfected into HepG2 cells. Culture medium containing secreted HBV viral particles was collected and assayed for their binding to commercial kits. Drastic decrease of reactivity to these kits was seen with most of the identified mutations, including those located outside the a-determinant. CONCLUSION: The existence of a more complex antigenic structure of HBsAg is indicated by the decreased reactivity to detection of mutations, some of which are outside the a-determinant, escape vaccination and may persist in seronegative patients. The high proportion of HBsAg mutants that are integrated in HCC genomes suggests a role of these mutants in hepatocarcinogenesis, possibly leading to mutant HBV-related HCC.