A framework for detecting causal effects of risk factors at an individual level based on principles of Mendelian randomisation: applications to modelling individualised effects of lipids on coronary artery disease

Background: Mendelian Randomisation (MR) has been widely used to study the causal effects of risk factors. However, almost all MR studies concentrate on the population's average causal effects. With the advent of precision medicine, the individualised treatment effect (ITE) is often of greater interest. For instance, certain risk factors may pose a higher risk to some individuals than others, and the benefits of treatments may vary across individuals. This study proposes a framework for estimating individualised causal effects in large-scale observational studies where unobserved confounding factors may be present. Methods: We propose a framework (MR-ITE) that expands the scope of MR from estimating average causal effects to individualised causal effects. We present several approaches for estimating ITEs within this MR framework, primarily grounded on the principles of the “R-learner”. To evaluate the presence of causal effect heterogeneity, we also proposed two permutation testing methods. We employed polygenic risk score (PRS) as instruments and proposed methods to improve the accuracy of ITE estimates by removal of potentially pleiotropic single nucleotide polymorphisms (SNPs). The validity of our approach was substantiated through comprehensive simulations. The proposed framework also allows the identification of important effect modifiers contributing to individualised differences in treatment effects. We applied our framework to study the individualised causal effects of various lipid traits, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), and total cholesterol (TC), on the risk of coronary artery disease (CAD) based on the UK-Biobank (UKBB). We also studied the ITE of C-reactive protein (CRP) and insulin-like growth factor 1 (IGF-1) on CAD as secondary analyses. Findings: Simulation studies demonstrated that MR-ITE outperformed traditional causal forest approaches in identifying ITEs when unobserved confounders were present. The integration of the contamination mixture (ConMix) approach to remove invalid pleiotropic SNPs further enhanced MR-ITE's performance. In real-world applications, we identified positive causal associations between CAD and several factors (LDL-C, Total Cholesterol, and IGF-1 levels). Our permutation tests revealed significant heterogeneity in these causal associations across individuals. Using Shapley value analysis, we identified the top effect modifiers contributing to this heterogeneity. Interpretation: We introduced a new framework, MR-ITE, capable of inferring individualised causal effects in observational studies based on the MR approach, utilizing PRS as instruments. MR-ITE extends the application of MR from estimating the average treatment effect to individualised treatment effects. Our real-world application of MR-ITE underscores the importance of identifying ITEs in the context of precision medicine. Funding: This work was supported partially by a National Natural Science Foundation of China grant (NSFC; grant number 81971706), the KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Institute of Zoology and The Chinese University of Hong Kong, China, and the Lo Kwee Seong Biomedical Research Fund from The Chinese University of Hong Kong.published_or_final_versio

Reinforcement learning impairment in individuals with euthymic bipolar I disorder with a history of psychosis

Reinforcement-learning (RL) impairment is an important determinant of functional outcome in bipolar-disorder (BD). This study examined RL in 38 euthymic bipolar-I-disorder (BD-I) individuals aged 16–40 years who were treated within three years from first-episode mania with psychosis and 40 demographically-matched healthy-controls using a computerized RL-paradigm, which investigated rapid and gradual learning, and reward-driven and punishment-driven learning. Symptom severity and cognitive functions were assessed. Our results showed that BD-I individuals displayed lower lose-shift scores than controls (p = 0.03). There were no group differences in other rapid RL measures. Regarding overall RL, a repeated-measures ANOVA revealed main effect of group (F1,76 = 6.5, p = 0.03; controls performed better than patients), block (F2.87,218.45 = 43.7, p < 0.001; performance improving over time) and probability (F1,76 = 15.6, p < 0.001; better performance in 90% than in 80% condition). Post-hoc analysis revealed that controls performed better than BD-I individuals on loss-avoidance stimuli (p = 0.02). Better performance of controls relative to BD-I individuals on gain stimuli approached statistical significance (p = 0.06). No correlations of RL measures with symptoms, cognition or antipsychotic dose were observed. In conclusion, this study is among the few to examine RL impairment in euthymic BD-I with history of psychosis at a relatively early illness stage, and indicates that BD-I individuals displayed punishment-driven learning (i.e., negative RL) deficits compared with controls. Diminished punishment-sensitivity may indicate vulnerability to maladaptive behaviors, particularly in response to negative events or stress, and poorer functional impairment. Further research is required to clarify longitudinal trajectory of punishment-insensitivity and its relationship with psychosis and functional outcomes in the early-stage of BD

Evaluating the effects of topography and land use change on hydrological signatures: a comparative study of two adjacent watersheds

Watershed hydrological processes are significantly influenced by land use and land cover change (LULCC) and characteristics such as topography. In economically advanced regions, coordinating land use planning and water resource management is essential for mitigating flood risks and ensuring sustainable development. This study compares the effects of terrain slope and urbanization-driven LULCC on hydrological processes in two adjacent subtropical watersheds but with distinct terrain and land cover in the Greater Bay Area (GBA) of China. We developed an integrated surface-subsurface hydrological model (ISSHM) using the Simulator for Hydrologic Unstructured Domains (SHUD) and calibrated it with data from river and groundwater monitoring stations. The calibrated model simulated hydrological processes, including surface runoff, subsurface flow, evapotranspiration (ET), and infiltration, to quantify water movement (measured in meters) and assess the impacts of slope and LULCC. Results show that slope impacts hydrological processes differently based on watershed characteristics. In mountainous areas, there are consistent high correlations between slope and annual surface runoff, infiltration, and subsurface flow across all watersheds. However, at lower elevations, the hydrological responses of steeper watersheds correlate weakly with local slope. Urbanization, marked by increased impervious surfaces, significantly raises annual surface runoff and decreases infiltration and ET, especially in steeper watersheds. In flatter watersheds, the rise in surface runoff is proportionally less than the increase in impervious areas, indicating a buffering capacity against urbanization. However, this buffering capacity diminishes with increasing annual rainfall intensity. Overall, the ISSHM provides robust analysis of LULCC effects on watershed hydrology across scales, enabling predictive approaches to optimizing urban management for sustainable development in growing cities.</p

The Application of Artificial Intelligence in Spine Surgery: A Scoping Review

Background:A comprehensive review on the application of artificial intelligence (AI) within spine surgery as a specialty remains lacking.Methods:This scoping review was conducted upon PubMed and EMBASE databases according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Our analysis focused on publications from January 1, 2020, to March 31, 2024, with a specific focus on AI in the field of spine surgery. Review articles and articles predominantly concerning secondary validation of algorithms, medical physics, electronic devices, biomechanics, preclinical, and with a lack of clinical emphasis were excluded.Results:One hundred five studies were included after our inclusion/exclusion criteria were applied. Most studies (n = 100) were conducted through supervised learning upon prelabeled data sets. Overall, 38 studies used conventional machine learning methods upon predefined features, whereas 67 used deep learning methods, predominantly for medical image analyses. Only 25.7% of studies (27/105) collected data from more than 1,000 patients for model development and validation. Data originated from only a single center in 72 studies. The most common application was prognostication (38/105), followed by diagnosis (35/105), medical image processing (29/105), and surgical assistance (3/105).Conclusion:The application of AI within the domain of spine surgery has significant potential to advance patient-specific diagnosis, management, and surgical execution

The transition towards carbon neutrality: Land use policy, resource and energy management modes, and spatial planning options

This editorial paper synthesises the findings from the special issue dedicated to exploring the pivotal roles of land use policy, energy management, and spatial planning in achieving carbon neutrality. The eleven papers featured in this issue present innovative approaches and empirical studies that highlight crucial strategies for mitigating carbon emissions and promoting sustainable urban development. The papers in this issue explore topics ranging from the impact of urban centre layout on household carbon emissions in Chinese cities to the feasibility of 15-minute cities in the United States, and from the non-linear effects of land conveyance on urban carbon emissions to the simulations of land use carbon neutrality scenarios. Collectively, these studies provide a comprehensive overview of the complex relationships between urban form, land use, resource management, and carbon emissions. Furthermore, the issue advances our understanding of the pathways towards carbon neutrality, emphasising innovative spatial policies, governance, and implementation instruments that foster environmental and social co-benefits

CD22 modulation alleviates amyloid β-induced neuroinflammation

Neuroinflammation is a crucial driver of multiple neurodegenerative diseases, including Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS) and Parkinson's disease (PD). Yet, therapeutic targets for neurodegenerative diseases based on neuroinflammation still warrant investigation. CD22 has been implicated in neuroinflammatory diseases, namely AD. Specifically, plasma soluble CD22 (sCD22) level is upregulated in patients with AD. Direct experimental evidence for the role of CD22 in neuroinflammation is needed, as is a better understanding of its impact on microglia activation and therapeutic potential. Here we reported that sCD22 promotes neuroinflammation both in vivo and in vitro. sCD22 activated microglia via both p38 and ERK1/2 signaling pathway for the secretion of TNFα, IL-6 and CCL3. Moreover, sCD22 activated microglia via sialic acid binding domain and 2,6 linked sialic acid glycan on sCD22. The pivotal therapeutic potential of targeting CD22 was demonstrated in Amyloid β (Aβ) induced-neuroinflammation in hCD22 transgenic mice. Suciraslimab improved working memory and resolved neuroinflammation in vivo. Further, membrane CD22 inhibited Amyloid β (Aβ) induced-NFκB signaling pathway and mechanistic study delineated that suciraslimab suppressed Aβ-induced IL-1β secretion in human microglia and PBMC. Suciraslimab also suppressed IL-12 and IL-23 secretion in human PBMC. Moreover, suciraslimab reduced the surface expression of α4 integrin on B cells. Intriguingly, we discovered that CD22 interact with Aβ and suciraslimab enhanced internalization of CD22-Aβ complex in microglia. Our data highlights the importance of sCD22 in driving neuroinflammation and the dual mechanism of targeting CD22 to resolve Aβ-induced inflammation and promote Aβ phagocytosis

Recycling of Subducted Carbonates Generated the Tarim Carbonatites in Paleoproterozoic Orogenic Processes

Carbonatites are critical carriers of carbon and potential reservoirs of rare earth elements, which provide valuable insights into probing Earth’s deep processes. Recent studies have identified carbonatitic melts derived from the partial melting of sedimentary carbonates in Phanerozoic subduction zones. However, whether such carbonatites could be formed in Precambrian settings remains unclear due to high mantle temperatures and uncertain Archean–Paleoproterozoic tectonic dynamics. In this study, we sampled Paleoproterozoic carbonatites from the southeastern Tarim craton, northwest China, and conducted geochemical, isotopic, and geochronological analyses to elucidate their petrogenesis. Zircon and apatite U–Pb ages indicate carbonatite crystallization occurred at ca. 1.87 to 1.83 Ga, and mineral chemistry points to mantle depths of melt generation. However, the Tarim carbonatites have trace element patterns comparable with sedimentary carbonates and Sr–Nd isotopes (87Sr/86Sri = 0.704–0.706; 143Nd/144Ndi = 0.509895–0.510052) differing from those of mantle-derived carbonatites. In addition, their C–O isotopes (δ13CPDB = 11.78–14.32%; δ18OSMOW = 14.83–15.97%) resemble the extents of marine carbonates, which were deposited in the Lomagundi-Jatuli Event (ca. 2.3–2.0 Ga). Hence, we propose that the Tarim carbonatites originated from partial melting of subducted Lomagundi-Jatuli Event carbonates at mantle depths. Our findings provide the earliest evidence for carbonatites derived from subducted sedimentary carbon, hinting that carbon recycling at the crust–mantle scale has been operative as early as the Paleoproterozoic.link_to_subscribed_fulltex

From the fringes to the mainstream and back? The geography of pandemic-driven evolution of fare-free public transport in the United States

The article examines the surprising uptake of the fare-free public transport (FFPT) policy in the United States during the first two years of the COVID-19 pandemic. While sanitary lockdowns led to a drastic reduction of mobility, safe public transport (PT) services had to be maintained to cater for “essential workers”. To achieve this, many urban transit agencies (TAs) adopted FFPT. To examine where PT became fare-free during the pandemic, we built and analysed a new dataset based on information from nearly 400 urban TAs across the US. Our findings indicate that two-thirds of the public TAs in urban areas opted to suspend fare collection amid the pandemic, with the analysis uncovering 73 cases of full FFPT on top of the 29 that had existed before the pandemic. FFPT emerged in areas with diverse demographic and economic profiles. Localities with higher Democratic Party support were more likely to abolish fares and sustain the suspensions, while larger transit agencies with substantial vehicle fleets tended to resume fare collection sooner. These findings highlight the complex factors influencing the adoption and duration of FFPT programmes in response to the pandemic, and underscore the adaptability of PT policies in the response. In sum, we observe that FFPT has shifted from the policy margins to the mainstream, having transformed from a highly controversial measure to a widely accepted strategy. Although the number of FFPT cases decreased significantly after the initial waves of the pandemic, it nonetheless remained much higher than pre-pandemic levels, with 40 TAs continuing to offer fare-free services.link_to_subscribed_fulltex

Effectiveness of an age-modified mindfulness-based cognitive therapy (MBCT) in improving mental health in older people with depressive symptoms: a non-randomised controlled trial

Background: Emerging evidence has shown that mindfulness-based cognitive therapy (MBCT) is effective in improving depressive symptoms in the older population. However, the accessibility to MBCT is limited by the shortage of psychotherapists or mindfulness teachers. One potential solution is to involve social workers, who have the knowledge and skills to promote individual and community well-being in various settings, in delivering modified MBCT to enhance its accessibility and sustainability. This study examined the effectiveness of an eight-week age-modified MBCT led by different mental health professionals (mindfulness teacher only vs. mindfulness teacher and social worker) in improving mental health outcomes as compared with a control group. Methods: Older adults (N = 112) were recruited through five community-based centres for older adults and mental wellness in Hong Kong. Participants were allocated to one of three groups: (1) mindfulness teacher-led modified MBCT, (2) social worker/teacher co-led modified MBCT (50% led by social workers and 50% led by mindfulness teacher), or (3) control (care as usual). The age-modified MBCT consisted of eight weekly sessions, with age-related modifications including more sitting meditation, shortened duration of each session, and the removal of the retreat. Outcome variables (i.e., depressive symptoms, anxiety symptoms, perceived stress, and mindfulness) were assessed at baseline (T0), after the intervention (T1), and four weeks after the intervention (T2), through self-reported questionnaires. Linear mixed models were performed while controlling for demographic variables to examine changes in outcome variables between the groups. Results: Participants from the age-modified MBCT intervention groups (teacher-led and social worker/teacher co-led) showed significantly greater reductions in depressive symptoms and stress, as well as greater increase in mindful non-reactivity, compared to the control group post-intervention. No significant interaction effect of time and group was found for anxiety and both overall mindfulness and its other facets. The improvements in mental health and mindfulness outcomes post-intervention were not significantly different between the teacher-led and social worker/teacher co-led MCBT groups. Discussion: Age-modified MBCT is beneficial in managing depressive and stress symptoms and in improving mindful non-reactivity among older adults at risk for depression. The findings support the feasibility and effectiveness of partial task-shifting in the delivery of MBCT to trained social workers. Future studies may explore the possibility for social workers in leading MBCTs independently to further improve its scalability and service accessibility for older adults in the community. Trial registration: ClinicalTrials.gov NCT05995587. Retrospectively registered on 16 August 2023