Overcoming Status Quo Bias: Nudging in a Government-Led Digital Transformation Initiative

While Singaporean citizens are keen on using e-payments in retail shops, they still prefer cash payments in hawker centers and coffee shops, i.e., traditional open-air complexes selling inexpensive cooked food. A government-led initiative seeks to tackle the situation, known as status quo bias. The key actors involved in this initiative are public agencies, the central bank, and a private Singaporean electronic payment service provider. Working with these partners, we investigate the process designed to nudge citizens to use e-payments for micropayments in hawker centers and coffee shops. We employ a design ethnography methodology and adapt an existing nudging framework. Early findings reveal contingency factors that shape the nudging approach. Through this study, we expect to contribute to the theoretical development of nudging theory to overcome status quo bias in government-led digital transformation initiatives

Psychopathology and psychosocial functioning among young people with first-episode psychosis and/or first-presentation borderline personality disorder.

BACKGROUND One in five young people with first-episode psychosis (FEP) also presents with borderline personality disorder (BPD) features. Among people diagnosed with BPD, auditory verbal hallucinations occur in 29-50 % and delusions in 10-100 %. Co-occurrence of psychotic symptoms and BPD is associated with greater clinical severity and greater difficulty accessing evidence based FEP care. This study aimed to investigate psychotic symptoms and psychosocial functioning among young people presenting to an early intervention mental health service. METHOD According to the presence or absence of either FEP or BPD, 141 participants, aged 15-25 years, were assigned to one of four groups: FEP, BPD, combined FEP + BPD, or clinical comparison (CC) participants with neither FEP nor BPD. Participants completed semi-structured diagnostic interviews and interviewer and self-report measures of psychopathology and psychosocial functioning. RESULTS The FEP + BPD group had significantly more severe psychopathology and poorer psychosocial functioning than the FEP group on every measure, apart from intensity of hallucinations. Comparing the FEP or BPD groups, the BPD group had greater psychopathology, apart from intensity of psychotic symptoms, which was significantly greater in the FEP group. These two groups did not significantly differ in their overall psychosocial functioning. Compared with CC young people, both the FEP + BPD and BPD groups differed significantly on every measure, with medium to large effect sizes. CONCLUSIONS Young people with co-occurring FEP and BPD experience more severe difficulties than young people with either diagnosis alone. This combination of psychosis and severe personality pathology has been longitudinally associated with poorer outcomes among adults and requires specific clinical attention

The influence of bisphosphonates on human osteoblast migration and integrin aVb3/tenascin C gene expression in vitro

<p>Abstract</p> <p>Background</p> <p>Bisphosphonates are therapeutics of bone diseases, such as Paget's disease, multiple myeloma or osteoclastic metastases. As a severe side effect the bisphosphonate induced osteonecrosis of the jaw (BONJ) often requires surgical treatment and is accompanied with a disturbed wound healing.</p> <p>Therefore, the influence on adhesion and migration of human osteoblasts (hOB) after bisphosphonate therapy has been investigated by morphologic as well as gene expression methods.</p> <p>Methods</p> <p>By a scratch wound experiment, which measures the reduction of defined cell layer gap, the morphology and migration ability of hOB was evaluated. A test group of hOB, which was stimulated by zoledronate 5 × 10^-5M, and a control group of unstimulated hOB were applied. Furthermore the gene expression of integrin aVb3 and tenascin C was quantified by Real-Time rtPCR at 5data points over an experimental period of 14 days. The bisphosphonates zoledronate, ibandronate and clodronate have been compared with an unstimulated hOB control.</p> <p>Results</p> <p>After initially identical migration and adhesion characteristics, zoledronate inhibited hOB migration after 50 h of stimulation. The integrinavb3 and tenascin C gene expression was effected by bisphosphonates in a cell line dependent manner with decreased, respectively inconsistent gene expression levels over time. The non-nitrogen containing bisphosphonates clodronate led to decreased gene expression levels.</p> <p>Conclusion</p> <p>Bisphosphonates seem to inhibit hOB adhesion and migration. The integrin aVb3 and tenascin C gene expression seem to be dependent on the cell line. BONJ could be enhanced by an inhibition of osteoblast adhesion and migration. The gene expression results, however, suggest a cell line dependent effect of bisphosphonates, which could explain the interindividual differences of BONJ incidences.</p

SELFIES and the future of molecular string representations

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the design of new molecules. The machine needs to read and write fluently in a chemical language for each of these tasks. Strings are a common tool to represent molecular graphs, and the most popular molecular string representation, SMILES, has powered cheminformatics since the late 1980s. However, in the context of AI and ML in chemistry, SMILES has several shortcomings -- most pertinently, most combinations of symbols lead to invalid results with no valid chemical interpretation. To overcome this issue, a new language for molecules was introduced in 2020 that guarantees 100\% robustness: SELFIES (SELF-referencIng Embedded Strings). SELFIES has since simplified and enabled numerous new applications in chemistry. In this manuscript, we look to the future and discuss molecular string representations, along with their respective opportunities and challenges. We propose 16 concrete Future Projects for robust molecular representations. These involve the extension toward new chemical domains, exciting questions at the interface of AI and robust languages and interpretability for both humans and machines. We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science.Comment: 34 pages, 15 figures, comments and suggestions for additional references are welcome

SELFIES and the future of molecular string representations

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the design of new molecules. The machine needs to read and write fluently in a chemical language for each of these tasks. Strings are a common tool to represent molecular graphs, and the most popular molecular string representation, SMILES, has powered cheminformatics since the late 1980s. However, in the context of AI and ML in chemistry, SMILES has several shortcomings -- most pertinently, most combinations of symbols lead to invalid results with no valid chemical interpretation. To overcome this issue, a new language for molecules was introduced in 2020 that guarantees 100\% robustness: SELFIES (SELF-referencIng Embedded Strings). SELFIES has since simplified and enabled numerous new applications in chemistry. In this manuscript, we look to the future and discuss molecular string representations, along with their respective opportunities and challenges. We propose 16 concrete Future Projects for robust molecular representations. These involve the extension toward new chemical domains, exciting questions at the interface of AI and robust languages and interpretability for both humans and machines. We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science

SELFIES and the future of molecular string representations

Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad applications to challenging tasks in chemistry and materials science. Examples include the prediction of properties, the discovery of new reaction pathways, or the design of new molecules. The machine needs to read and write fluently in a chemical language for each of these tasks. Strings are a common tool to represent molecular graphs, and the most popular molecular string representation, Smiles, has powered cheminformatics since the late 1980s. However, in the context of AI and ML in chemistry, Smiles has several shortcomings—most pertinently, most combinations of symbols lead to invalid results with no valid chemical interpretation. To overcome this issue, a new language for molecules was introduced in 2020 that guarantees 100% robustness: SELF-referencing embedded string (Selfies). Selfies has since simplified and enabled numerous new applications in chemistry. In this perspective, we look to the future and discuss molecular string representations, along with their respective opportunities and challenges. We propose 16 concrete future projects for robust molecular representations. These involve the extension toward new chemical domains, exciting questions at the interface of AI and robust languages, and interpretability for both humans and machines. We hope that these proposals will inspire several follow-up works exploiting the full potential of molecular string representations for the future of AI in chemistry and materials science

Bilateral Sensory Abnormalities in Patients with Unilateral Neuropathic Pain; A Quantitative Sensory Testing (QST) Study

In patients who experience unilateral chronic pain, abnormal sensory perception at the non-painful side has been reported. Contralateral sensory changes in these patients have been given little attention, possibly because they are regarded as clinically irrelevant. Still, bilateral sensory changes in these patients could become clinically relevant if they challenge the correct identification of their sensory dysfunction in terms of hyperalgesia and allodynia. Therefore, we have used the standardized quantitative sensory testing (QST) protocol of the German Research Network on Neuropathic Pain (DFNS) to investigate somatosensory function at the painful side and the corresponding non-painful side in unilateral neuropathic pain patients using gender- and age-matched healthy volunteers as a reference cohort. Sensory abnormalities were observed across all QST parameters at the painful side, but also, to a lesser extent, at the contralateral, non-painful side. Similar relative distributions regarding sensory loss/gain for non-nociceptive and nociceptive stimuli were found for both sides. Once a sensory abnormality for a QST parameter at the affected side was observed, the prevalence of an abnormality for the same parameter at the non-affected side was as high as 57% (for Pressure Pain Threshold). Our results show that bilateral sensory dysfunction in patients with unilateral neuropathic pain is more rule than exception. Therefore, this phenomenon should be taken into account for appropriate diagnostic evaluation in clinical practice. This is particularly true for mechanical stimuli where the 95% Confidence Interval for the prevalence of sensory abnormalities at the non-painful side ranges between 33% and 50%

In vivo measures of cartilage deformation: patterns in healthy and osteoarthritic female knees using 3T MR imaging

ObjectiveTo explore and to compare the magnitude and spatial pattern of in vivo femorotibial cartilage deformation in healthy and in osteoarthritic (OA) knees.MethodsOne knee each in 30 women (age: 55 ± 6 years; BMI: 28 ± 2.4 kg/m(2); 11 healthy and 19 with radiographic femorotibial OA) was examined at 3Tesla using a coronal fat-suppressed gradient echo SPGR sequence. Regional and subregional femorotibial cartilage thickness was determined under unloaded and loaded conditions, with 50% body weight being applied to the knee in 20° knee flexion during imaging.ResultsCartilage became significantly (p &lt; 0.05) thinner during loading in the medial tibia (-2.7%), the weight-bearing medial femur (-4.1%) and in the lateral tibia (-1.8%), but not in the lateral femur (+0.1%). The magnitude of deformation in the medial tibia and femur tended to be greater in osteoarthritic knees than in healthy knees. The subregional pattern of cartilage deformation was similar for the different stages of radiographic OA.ConclusionOsteoarthritic cartilage tended to display greater deformation upon loading than healthy cartilage, suggesting that knee OA affects the mechanical properties of cartilage. The pattern of in vivo deformation indicated that cartilage loss in OA progression is mechanically driven