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While informal settlements have been extensively studied in the Global South, their counterparts in the Global North remain under-researched, despite their critical role in shaping urban morphology. This paper introduces “Resident-Centered Narrative Mapping”, a framework designed to uncover micro-morphological knowledge through the lived spatial experiences of marginalized residents. By examining the epistemological question “whose morphology?”, this study critiques conventional urban morphological methods, which often disregard spatial practices embedded in the everyday lives of marginalized communities. Focusing on a marginalized lilong settlement in downtown Shanghai, this research work integrates critical cartography with ethnographic fieldwork to develop a micro-morphological mapping process centered on resident narratives. This process, structured around the phases of finding, inscription, and simplification, demonstrates how residents’ daily practices actively shape and reconfigure their built environment. This study offers an alternative perspective to understand the dynamic processes of urban renewal in informal settlements and emphasizes the dialectical relationship between resident-driven spatial practices and the transformation of the urban form. By broadening urban morphology’s methodological framework, this research provides insights into how resident-driven mapping can inform localized regeneration strategies. The findings highlight the potential for marginalized communities to shape urban regeneration policies, advocating for inclusive, resident-centered development.

In order to explore the influence of different pore sizes of anthracite on the methane adsorption characteristics, a low-temperature liquid nitrogen adsorption experiment was carried out. Six types of anthracite with pore sizes ranging from 10 Å to 60 Å were selected as simulation objects. By means of molecular simulation technology and using the Materials Studio 2020 software, a macromolecular model of anthracite was established, and a grand canonical Monte Carlo (GCMC) simulation comparative study was conducted. The variation laws of the interaction energy and diffusion during the process of coal adsorbing CH4 under different pore size conditions were obtained. The results show that affected by the pore size, under the same temperature condition, the peak value of the interaction energy distribution between coal and CH4 shows a downward trend with the increase in the pore size under the action of pressure, and the energy gradually decreases. The isothermal adsorption curves all conform to the Langmuir isothermal adsorption model. The Langmuir adsorption constant a shows an obvious upward trend with the increase in the pore size, with an average increase of 16.43%. Moreover, under the same pressure, when the pore size is 60 Å, the adsorption amount of CH4 is the largest, and as the pore size decreases, the adsorption amount also gradually decreases. The size of the pore size is directly proportional to the diffusion coefficient of CH4. When the pore size increases to 50 Å, the migration state of CH4 reaches the critical point of transformation, and the diffusion coefficient rapidly increases to 2.3 times the original value.

Autophagy is a vital cellular pathway in eukaryotic cells, including neurons, where it plays significant roles in neurodevelopment and maintenance. A crucial step in autophagy is the formation of the class III phosphatidylinositol 3-kinase complex 1 (PI3KC3-C1), which is essential for initiating autophagosome biogenesis. Beclin 1 is the key component of PI3KC3-C1, and its interactors have been reported to affect autophagy. The brain-enriched adaptor protein FE65 has been shown to interact with Alzheimer’s disease amyloid precursor protein (APP) to alter the processing of APP. Additionally, FE65 has been implicated in various cellular pathways, including autophagy. We demonstrate here that FE65 positively regulates autophagy. FE65, through its C-terminus, has been shown to interact with Beclin 1. Notably, the overexpression of FE65 enhances Beclin 1-mediated autophagy, whereas this process is attenuated in FE65 knockout cells. Moreover, the stimulatory effect of FE65 on Beclin 1-mediated autophagy is diminished by an FE65 C-terminus deletion mutant that disrupts the FE65–Beclin 1 interaction. Lastly, we have found that the FE65-Beclin 1 interaction modulates the kinase activity of the PI3KC3-C1 complex. Together, we have identified FE65 as a novel Beclin 1 interactor, and this interaction potentiates autophagy.

The boundary, both as social norm and physical form, is an essential element in the development of the structure of urban form. This article explores the role of boundaries: (1) through the transformation of the lilong form in Shanghai by means of a case study of the Guizhou lilong block and (2) through the extension of the methodology of morphological study. In the urbanization of China, the lilong form tracks successive organizational shifts in society. Over one hundred years, the micro-scale changes of boundaries transformed the morphology of the Guizhou lilong block from a single-family residence to a mass housing block. Accordingly, the morphological study of the boundaries in Guizhou lilong block shows how its form was changed by changing regulations applied to it as well as its changing communities. This article uses two-dimensional drawings to investigate the change of boundaries over time extending the Conzen tradition and the understanding of how the social system defines the urban form. Consequently, this article makes an argument for understanding the effect on boundaries of both the conflict and the cooperation between the authorities and the inhabitants in a morphological study following the Conzen School.

This dissertation develops methodologies to incorporate summary information from external studies to improve estimation efficiency for an internal study that has individual-level data. I first propose a penalized constrained maximum likelihood (PCML) method that simultaneously selects the external studies whose target populations match the internal study's so that their information is useful for internal model fitting and incorporates the corresponding information into internal estimation. The PCML estimator has the same efficiency as an oracle estimator that knows which external information is useful and fully incorporates that information alone. I then extend the PCML method to a more general framework by allowing the number of external studies to increase with the sample size of the internal study and apply the method to study mental health of people with bipolar disorder during the COVID-19 pandemic. I further develop a doubly penalized constrained maximum likelihood (dPCML) method that also accounts for the uncertainty in external information with more flexibility on what external information can be integrated. The dPCML method covers some existing well-known data integration methods as special cases. For the proposed methods I carry out detailed theoretical investigations, provide algorithms for implementation, and conduct comprehensive simulation studies. Based on the simulation studies, the proposed methods have excellent numerical performance. For example, when using the dPCML method with external study sample sizes similar to the internal sample size, the reduction in empirical standard errors is more than 20% for the estimates of some model parameters compared to the maximum likelihood estimator (MLE) without using the external information, and more than 10% compared to some other existing methods, without introducing bias.

Autophagy is a highly conserved catabolic mechanism by which unnecessary or dysfunctional cellular components are removed. The dysregulation of autophagy has been implicated in various neurodegenerative diseases, including Alzheimer’s disease (AD). Understanding the molecular mechanism(s)/molecules that influence autophagy may provide important insights into developing therapeutic strategies against AD and other neurodegenerative disorders. Engulfment adaptor phosphotyrosine-binding domain-containing protein 1 (GULP1) is an adaptor that interacts with amyloid precursor protein (APP) to promote amyloid-β peptide production via an unidentified mechanism. Emerging evidence suggests that GULP1 has a role in autophagy. Here, we show that GULP1 is involved in autophagy through an interaction with autophagy-related 14 (ATG14), which is a regulator of autophagosome formation. GULP1 potentiated the stimulatory effect of ATG14 on autophagy by modulating class III phosphatidylinositol 3-kinase complex 1 (PI3KC3-C1) activity. The effect of GULP1 is attenuated by a GULP1 mutation (GULP1m) that disrupts the GULP1–ATG14 interaction. Conversely, PI3KC3-C1 activity is enhanced in cells expressing APP but not in those expressing an APP mutant that does not bind GULP1, which suggests a role of GULP1–APP in regulating PI3KC3-C1 activity. Notably, GULP1 facilitates the targeting of ATG14 to the endoplasmic reticulum (ER). Moreover, the levels of both ATG14 and APP are elevated in the autophagic vacuoles (AVs) of cells expressing GULP1, but not in those expressing GULP1m. APP processing is markedly enhanced in cells co-expressing GULP1 and ATG14. Hence, GULP1 alters APP processing by promoting the entry of APP into AVs. In summary, we unveil a novel role of GULP1 in enhancing the targeting of ATG14 to the ER to stimulate autophagy and, consequently, APP processing.

FE65 is a brain-enriched adaptor with multiple protein binding domains, interacting with different cellular proteins to participate in cellular processes. One such protein is ADP-ribosylation factor 6 (ARF6). ARF6 is a vital regulator of multiple cellular processes including endocytic membrane trafficking and actin cytoskeleton motility. As a small GTPase, ARF6 functions by cycling between its ARF6-GTP (active) form and ARF6-GDP (inactive) form. Previously, we reported that FE65 interacts with ARF6 and stimulates ARF6 activation. However, how FE65 activates ARF6 remains elusive as it holds no GTPase activating function. The first part of this research focuses primarily on identifying the activation mechanism of FE65 on ARF6. In this part, I demonstrated that FE65 activates ARF6 by recruiting an ARF6 guanine nucleotide exchange factor (GEF) namely ARF nucleotide-binding site opener (ARNO). I identified the direct interaction between the FE65 C-terminal phosphotyrosine-binding (PTB) domain and the ARNO pleckstrin homology (PH) domain. The binding of FE65 to ARNO promotes ARNO GEF function and ARNO homodimerization. Moreover, a complex consisting of FE65, ARNO, and ARF6 was detected. Formation of the complex increases ARNO and ARF6 endocytic trafficking and ARNO/ARF6 plasma membrane co-localization.FE65 has been implicated in amyloid precursor protein (APP) processing. FE65 interacts with the APP intracellular domain (AICD) and promotes APP processing. However, how FE65 controls APP processing is not fully understood. In the second part of this research, possible roles of the FE65-ARNO interaction on APP processing were investigated. I demonstrated that FE65 promotes APP processing while ARNO and ARF6 inhibit APP processing. However, the stimulating effect of the ARNO-noninteracting FE65 mutant shows no substantial differences from the wild-type FE65. Moreover, the potency of FE65 stimulation on APP processing remains unaffected in the ARNO knockout cell line. These data imply that the two proteins work independently on APP processing.Previously, we have shown that ARF6 is activated via interacting with FE65 to promote neurite extension. FE65 interacts with ARF6 via the PTB1 domain and promotes activation of ARF6 and subsequent neurite outgrowth. In the first part of this research (Chapter 3), I demonstrated that FE65 stimulates ARF6 activation via ARNO. Of note, many lines of evidence have pointed out the importance of ARNO-mediated ARF6 activation in neuron development. Therefore, in the third part of this research, the possible roles of the FE65-ARNO interaction on neurite outgrowth were investigated. In this part, I demonstrated that the FE65-ARNO interaction is essential for ARF6-mediated neurite elongation. The FE65-ARNO-ARF6 complex was detected in rat embryonic neurons and co-localized to the neuronal growth cone. Moreover, I demonstrated that the ARNO autoinhibitory structure is disrupted by FE65, which might serve as an underlying mechanism for how FE65 promotes ARNO GEF function and dimerization. Collectively, I elucidate the FE65-ARNO interaction. Roles of the FE65-ARNO-ARF6 complex in APP processing and neurite outgrowth were further investigated. This study provides a better understanding of FE65 in neurite outgrowth and APP processing.

Fatigue is one of the most disabling symptoms reported by people with multiple sclerosis. Although behavioural and pharmacological interventions might be partly beneficial, their combined effects have not been evaluated for multiple sclerosis fatigue, or examined with sufficient consideration of characteristics that might affect treatment response. In this comparative effectiveness research trial, we compared the effectiveness of cognitive behavioural therapy (CBT), modafinil, and their combination for treating multiple sclerosis fatigue. This randomised, analyst-blinded, parallel-arm, comparative effectiveness trial was done at two universities in the USA. Adults (aged ≥18 years) with multiple sclerosis and problematic fatigue (Fatigue Severity Scale [FSS] score ≥4) were randomly assigned (1:1:1), using a web-based treatment assignment system with minimisation, to receive CBT, modafinil, or both for 12 weeks. Statisticians were masked to group assignment, but participants, study neurologists, CBT interventionalists, and coordinators were not masked to treatment assignment. The primary outcome was the change in Modified Fatigue Impact Scale (MFIS) from baseline to 12 weeks, assessed using multiple linear regression, adjusted for age, sex, study site, anxiety, pain, baselines MFIS score, and physical activity. Analyses were done by intent to treat. The trial was registered with clinicaltrials.gov, NCT03621761, and is completed. Between Nov 15, 2018, and June 2, 2021, 336 participants were randomly assigned treatment (114 assigned to CBT, 114 assigned to modafinil, and 108 assigned to combination therapy). At 12 weeks, CBT (n=103), modafinil (n=107), and combination therapy (n=102) were associated with clinically meaningful within-group MFIS reductions of 15·20 (SD 11·90), 16·90 (15·90), and 17·30 (16·20) points, respectively. Change in MFIS scores from baseline to 12 weeks did not differ between groups: relative to combination therapy, the adjusted total mean difference in MFIS change score was 1·88 (95% CI –2·21 to 5·96) for CBT and 1·20 (–2·83 to 5·23) for modafinil. Most common adverse events for modafinil-containing treatment groups included insomnia (eight [7%] for modafinil and eight [7%] for combination therapy) and anxiety (three [3%] for modafinil and nine [8%] for combination therapy). Modafinil, CBT, and combination therapy were associated with similar reductions in the effects of multiple sclerosis fatigue at 12 weeks. Combination therapy was not associated with augmented improvement compared with the individual interventions. Further research is needed to determine whether effects of these interventions on multiple sclerosis-related fatigue is influenced by sleep hygiene and sleepiness. No serious adverse events related to the study drug were encountered. Patient-Centered Outcomes Research Institute and National Multiple Sclerosis Society.

The Coupled Model Inter‐comparison Project Phase 6 (CMIP6) multi‐models predict future warming over Antarctica under five different scenarios, but their uncertainties remain high and have not been well constrained. Here we find that the projected Antarctic warming robustly correlates with simulated averaged temperature trends during 1958–2012 across the CMIP6 multi‐models under each scenario, which is thereby used to refine future air temperature projections using observation‐based temperature reconstruction. The median of future warming projections under the five scenarios reduces by 24%, 19%, 18%, 21%, and 21%, respectively. The constrained uncertainty ranges are narrowed down, with the likely range by the end of the century relative to 1850–1900 baseline declining from 4.2°C–6.8°C to 3.2°C–6.1°C under the highest emission scenario. The application of ERA5 for the same constraint shows an increase in future warming and constrained uncertainty ranges. This suggests a key role of observational data set uncertainties in the performance of emergent constraints.