Novel OX40 and 4-1BB derived spacers enhance CD30 CAR activity and safety in CD30 positive lymphoma models.

The chimeric antigen receptor (CAR) derived from the CD30 specific murine antibody, HRS-3, has produced promising clinical efficacy with a favorable safety profile in the treatment of relapsed or refractory CD30-positive lymphomas. However, persistence of the autologous CAR-T cells was brief, and many patients relapsed a year after treatment. The lack of persistence may be attributed to the use of a wild-type immunoglobulin (Ig)G1 spacer that can associate with Fc receptors. We first identified the cysteine-rich domain (CRD) 5 of CD30 as the primary binding epitope of HRS-3 and armed with this insight, attempted to improve the HRS-3 CAR functionality with a panel of novel spacer designs. We demonstrate that HRS-3 CARs with OX40 and 4-1BB derived spacers exhibited similar anti-tumor efficacy, circumvented interactions with Fc receptors, and secreted lower levels of cytokines in vitro than a CAR employing the IgG1 spacer. Humanization of the HRS-3 scFv coupled with the 4-1BB spacer preserved potent on-target, on-tumor efficacy, and on-target, off-tumor safety. In a lymphoma mouse model of high tumor burden, T cells expressing humanized HRS-3 CD30.CARs with the 4-1BB spacer potently killed tumors with low levels of circulating inflammatory cytokines, providing a promising candidate for future clinical development in the treatment of CD30-positive malignancies.

Phenotypic screening in Organ-on-a-Chip systems: a 1537 kinase inhibitor library screen on a 3D angiogenesis assay.

Modern drug development increasingly requires comprehensive models that can be utilized in the earliest stages of compound and target discovery. Here we report a phenotypic screening exercise in a high-throughput Organ-on-a-Chip setup. We assessed the inhibitory effect of 1537 protein kinase inhibitors in an angiogenesis assay. Over 4000 micro-vessels were grown under perfusion flow in microfluidic chips, exposed to a cocktail of pro-angiogenic factors and subsequently exposed to the respective kinase inhibitors. Efficacy of compounds was evaluated by reduced angiogenic sprouting, whereas reduced integrity of the main micro-vessel was taken as a measure for toxicity. The screen yielded 53 hits with high anti-angiogenicity and low toxicity, of which 44 were previously unassociated with angiogenic pathways. This study demonstrates that Organ-on-a-Chip models can be screened in high numbers to identify novel compounds and targets. This will ultimately reduce bias in early-stage drug development and increases probability to identify first in class compounds and targets for today's intractable diseases.

Pain trajectories and their associations with cognition among older adults: a 10-year cohort study from network perspective.

BACKGROUND: Few studies have examined the associations between pain trajectories and cognitive function in older adults. This study explored the associations between pain trajectories and different cognitive domains in older adults from a network perspective. METHODS: Data on pain trajectories were derived from the Health and Retirement Study between 2010 and 2020 using latent class growth analyses. Measurements of key cognition domains, including memory, attention, calculation, orientation and language, were included. Linear regression and network analysis were performed to evaluate the associations between different pain trajectories and cognition. RESULTS: A total of 9,551 older adults were included in this study and three trajectories of pain were identified. After controlling for the covariates, persistent severe pain trajectory was associated with poorer overall cognition, memory and calculation ability when compared to mild or non-persistent pain trajectory. In the pain and cognition network model, memory (expected influence (EI) = 0.62), language (EI = 0.58) and calculation (EI = 0.41) were the most central domains. CONCLUSIONS: Pain trajectories appeared stable over time among older adults in this study. Severity of persistent pain was an important risk factor for poor cognition, especially in relation to memory and calculation domains. Interventions targeting memory, language and calculation domains might be useful in addressing cognitive decline in older adults with persistent pain.

The Influence of Personality Disorder Symptoms on Treatment Outcomes in Bipolar Disorder: A Secondary Analysis of a Randomised Controlled Trial: L'influence des symptômes du trouble de la personnalité sur les résultats du traitement dans le trouble bipolaire : Une analyse secondaire d'un essai randomisé contrôlé.

OBJECTIVES: Many people who are diagnosed with bipolar disorder also have comorbid personality disorder. Few studies have explored how personality disorder may influence pharmacological treatment outcomes. The aim of this study was to conduct a secondary analysis of data from a clinical trial of adjunctive nutraceutical treatments for bipolar depression, to determine whether maladaptive personality traits influence treatment outcomes. METHODS: Scores on the Standardised Assessment of Personality - Abbreviated Scale screener were used to classify participants as having bipolar disorder with (n = 119) and without (n = 29) above threshold personality disorder symptoms (personality disorder). Outcome measures included: The Montgomery Åsberg Depression Rating Scale, Clinical Global Impressions and Improvement Severity Scales, Patient Global Impressions-Improvement scale, Bipolar Depression Rating Scale, Range of Impaired Functioning Tool, Social and Occupational Functioning Assessment Scale and Quality of Life and Enjoyment Scale (Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form). Generalised estimated equations examined the two-way interactions of personality disorder by time or treatment and investigated personality disorder as a non-specified predictor of outcomes. RESULTS: Over time, the Patient Global Impressions-Improvement scores were significantly higher in those in the personality disorder group. No other significant differences in the two-way interactions of personality disorder by treatment group or personality disorder by time were found. Personality disorder was a significant but non-specific predictor of poorer outcomes on the Bipolar Depression Rating Scale, Range of Impaired Functioning Tool, and Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form, regardless of time or treatment group. CONCLUSIONS: This study highlights the potential impact of maladaptive personality traits on treatment outcomes and suggests that the presence of comorbid personality disorder may confer additional burden and compromise treatment outcomes. This warrants further investigation as does the corroboration of these exploratory findings. This is important because understanding the impact of comorbid personality disorder on bipolar disorder may enable the development of effective psychological and pharmacotherapeutic options for personalised treatments.

COVID-19 and Sleep Problems: A Perspective from Bibliometric Analysis.

OBJECTIVES: The Coronavirus Disease 2019 (COVID-19) pandemic and the containment measures for COVID-19 have affected sleep quality in the population. This study explored sleep-related research from a bibliometric perspective to provide an overview of the research outputs in this field. METHODS: Original and review articles were retrieved from the Web of Science Core Collection (WOSCC) database from December 2019 to 7 Aug 2023. R package "bibliometrix" was used to summarize the number of articles of authors, institutions, and countries; count the citations of the articles, and generate a Three-Fields Plot. VOSviewer software was applied to visualize the collaboration network among authors and institutions, and to conduct a co-occurrence analysis of keywords. RESULTS: A total of 4,499 articles on COVID-19 and sleep, and 25,883 articles on non-COVID-19 and sleep were included. Sleep related articles were mainly published by authors from China, the USA, and Italy. For COVID-19 and sleep research, Huazhong University of Science was the most productive institution. The Psychiatry Research was the most influential journal across the different subject categories of this field. "Mental health", "anxiety", and "depression" were the most common keywords, while "sleep quality" and "quality of life" were the likely topic areas in terms of future research directions. CONCLUSIONS: Our findings provide a comprehensive perspective for researchers to understand the wider landscape of both COVID-19 and non-COVID-19 sleep-related research area.

General quasi-equilibrium multivalent binding model to study diverse and complex drug-receptor interactions of biologics.

Pharmacokinetics and pharmacodynamics of many biologics are influenced by their complex binding to biological receptors. Biologics consist of diverse groups of molecules with different binding kinetics to its receptors including IgG with simple one-to-one drug receptor bindings, bispecific antibody (BsAb) that binds to two different receptors, and antibodies that can bind to six or more identical receptors. As the binding process is typically much faster than elimination (or internalization) and distribution processes, quasi-equilibrium (QE) binding models are commonly used to describe drug-receptor binding kinetics of biologics. However, no general QE modeling framework is available to describe complex binding kinetics for diverse classes of biologics. In this paper, we describe novel approaches of using differential algebraic equations (DAE) to solve three QE multivalent drug-receptor binding (QEMB) models. The first example describes the binding kinetics of three-body equilibria of BsAb that binds to 2 different receptors for trimer formation. The second example models an engineered IgG variant (Multabody) that can bind to 24 identical target receptors. The third example describes an IgG with modified neonatal Fc receptor (FcRn) binding affinity that competes for the same FcRn receptor as endogenous IgG. The model parameter estimates were obtained by fitting the model to all data simultaneously. The models allowed us to study potential roles of cooperative binding on bell-shaped drug exposure-response relationships of BsAb, and concentration-depended distribution of different drug-receptor complexes for Multabody. This DAE-based QEMB model platform can serve as an important tool to better understand complex binding kinetics of diverse classes of biologics.

Target-mediated drug disposition model for drugs with N > 2 binding sites that bind to a target with one binding site.

The paper extended the TMDD model to drugs with more than two (N > 2) identical binding sites (N-to-one TMDD). The quasi-steady-state (N-to-one QSS), quasi-equilibrium (N-to-one QE), irreversible binding (N-to-one IB), and Michaelis-Menten (N-to-one MM) approximations of the model were derived. To illustrate properties of new equations and approximations, N = 4 case was investigated numerically. Using simulations, the N-to-one QSS approximation was compared with the full N-to-one TMDD model. As expected, and similarly to the standard TMDD for monoclonal antibodies (mAb), N-to-one QSS predictions were nearly identical to N-to-one TMDD predictions, except for times of fast changes following initiation of dosing, when equilibrium has not yet been reached. Predictions for mAbs with soluble targets (slow elimination of the complex) were simulated from the full 4-to-one TMDD model and were fitted to the 4-to-one TMDD model and to its QSS approximation. It was demonstrated that the 4-to-one QSS model provided nearly identical description of not only the observed (simulated) total drug and total target concentrations, but also unobserved concentrations of the free drug, free target, and drug-target complexes. For mAb with a membrane-bound target, the 4-to-one MM approximation adequately described the data. The 4-to-one QSS approximation converged 8 times faster than the full 4-to-one TMDD.

The Brain Economy: Advancing Brain Science to Better Understand the Modern Economy.

The coming years are likely to be turbulent due to a myriad of factors or polycrisis, including an escalation in climate extremes, emerging public health threats, weak productivity, increases in global economic instability and further weakening in the integrity of global democracy. These formidable challenges are not exogenous to the economy but are in some cases generated by the system itself. They can be overcome, but only with far-reaching changes to global economics. Our current socio-economic paradigm is insufficient for addressing these complex challenges, let alone sustaining human development, well-being and happiness. To support the flourishing of the global population in the age of polycrisis, we need a novel, person-centred and collective paradigm. The brain economy leverages insights from neuroscience to provide a novel way of centralising the human contribution to the economy, how the economy in turn shapes our lives and positive feedbacks between the two. The brain economy is primarily based on Brain Capital, an economic asset integrating brain health and brain skills, the social, emotional, and the diversity of cognitive brain resources of individuals and communities. People with healthy brains are essential to navigate increasingly complex systems. Policies and investments that improve brain health and hence citizens' cognitive functions and boost brain performance can increase productivity, stimulate greater creativity and economic dynamism, utilise often underdeveloped intellectual resources, afford social cohesion, and create a more resilient, adaptable and sustainability-engaged population.

Prevalence of insomnia and its association with quality of life in caregivers of psychiatric inpatients during the COVID-19 pandemic: a network analysis.

BACKGROUND: Studies on sleep problems among caregivers of psychiatric patients, especially during the COVID-19 pandemic, are limited. This study examined the prevalence and correlates of insomnia symptoms (insomnia hereafter) among caregivers of psychiatric inpatients during the COVID-19 pandemic as well as the association with quality of life (QoL) from a network analysis perspective. METHODS: A multi-center cross-sectional study was conducted on caregivers of inpatients across seven tertiary psychiatric hospitals and psychiatric units of general hospitals. Network analysis explored the structure of insomnia using the R program. The centrality index of "Expected influence" was used to identify central symptoms in the network, and the "flow" function was adopted to identify specific symptoms that were directly associated with QoL. RESULTS: A total of 1,101 caregivers were included. The overall prevalence of insomnia was 18.9% (n = 208; 95% CI = 16.7-21.3%). Severe depressive (OR = 1.185; P < 0.001) and anxiety symptoms (OR = 1.099; P = 0.003), and severe fatigue (OR = 1.320; P < 0.001) were associated with more severe insomnia. The most central nodes included ISI2 ("Sleep maintenance"), ISI7 ("Distress caused by the sleep difficulties") and ISI1 ("Severity of sleep onset"), while "Sleep dissatisfaction" (ISI4), "Distress caused by the sleep difficulties" (ISI7) and "Interference with daytime functioning" (ISI5) had the strongest negative associations with QoL. CONCLUSION: The insomnia prevalence was high among caregivers of psychiatric inpatients during the COVID-19 pandemic, particularly in those with depression, anxiety and fatigue. Considering the negative impact of insomnia on QoL, effective interventions that address insomnia and alteration of sleep dissatisfaction should be developed.

Hikikomori: A perspective from bibliometric analysis.

AIMS: Hikikomori is a common phenomenon reported in Japan and many other countries. However, the broad trends of the research publications on hikikomori are unclear. Therefore, this study examined the patterns of research on hikikomori using bibliometric analysis. METHODS: Relevant publications were searched in Web of Science. Bibliometric analyses were performed with CiteSpace, R and VOSviewer. RESULTS: In total, 297 publications on hikikomori met the eligibility criteria. The International Journal of Social Psychiatry (IF = 10.461) published the most papers (K = 17, or 5.7%) on hikikomori. Takahiro A. Kato from Kyushu University (41; 13.8%; H-index = 18) was the most influential author, while Takahiro A. Kato (total link strength [TLS]: 235), Alan R. Teo (TLS: 157), and Masaru Tateno (TLS: 153) separately had the strongest research collaboration with other researchers. Of all countries that published on hikikomori, Japan had the highest number of publications (K = 91). The keywords "United States" and "psychiatric diagnosis" received the most attention between 2013 and 2015, whereas "health" and "autism spectrum disorder" received the most attention in 2021 and 2022. CONCLUSIONS: Peer-reviewed research publications on hikikomori are growing rapidly and the research trends in this field are also changing.