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In contrast to the general and reductive assumption that pathologises fatness, this paper contends that fat female bodies serve as a critical nexus of intersectional oppression, where patriarchal, capitalist, and cultural power structures converge. In the light of Fay Weldon’s, The Fat Woman's Joke, in this study I will excavate the complex dynamics of fat representation, exposing the insidious mechanism of objectification, marginalization, discrimination, and commodification that perpetuate fat female oppression. Building on the theoretical foundations of Susan Bordo and Naomi Wolf, I aim to illuminate how the protagonist, Esther, embodies the tension between the cultural construction of femininity and bodily autonomy. Hence, by unpacking fat bias as a tool of social control and economic exploitation this study argues that fatness constitutes a paradigmatic site of feminist struggle, necessitating a nuanced reconsideration of identity, power and resistance in contemporary society.

Demand response (DR) strategies are recieving much attention recently for their applications in the residential sector. Electric vehicles (EVs), which are considered to be a fairly new consumer load in the power sector, have opened up new opportunities by providing the active utilization of EVs as a storage unit. Considering their storage capacities, they can be used in vehicle-to-grid (V2G) or vehicle-to-community (V2C) options instead of taking power in peak times from the grid itself. This paper suggests a community-based home energy management system for microgrids to achieve flatter power demand and peak demand shaving using particle swarm optimization (PSO) and user-defined constraints. A dynamic clustered load scheduling scheme is proposed, including a method for managing peak shaving using rules specifically designed for PV systems that are grid-connected alongside battery energy storage systems and electric vehicles. The technique being proposed involves determining the limits of feed-in and demand dynamically, using estimated load demands and profiles of PV power for the following day. Additionally, an optimal rule-based management technique is presented for the peak shaving of utility grid power that sets the charge/discharge schedules of the battery and EV one day ahead. Utilizing the PSO algorithm, the optimal inputs for implementing the rule-based peak shaving management strategy are calculated, resulting in an average improvement of about 7% in percentage peak shaving (PPS) when tested using MATLAB for numerous case studies.

BackgroundFamilial hypercholesterolaemia (FH) increases propensity for premature atherosclerotic disease. Knowledge of inpatient outcomes among patients with FH admitted with acute myocardial injury (AMI) is limited.ObjectivesOur study aimed to identify myocardial injury types, including type 1 myocardial infarction (MI), type 2 MI and takotsubo cardiomyopathy, assess lesion severity and study adverse short-term inpatient outcomes among patients with FH admitted with AMI.SettingOur study retrospectively queried the US National Inpatient Sample from 2018 to 2020.PopulationAdults admitted with AMI and dichotomised based on the presence of FH.Study outcomesWe evaluated myocardial injury types and complexity of coronary revascularisation. Primary outcome of all-cause mortality and other clinical secondary outcomes were studied.ResultsThere were 3 711 765 admissions with AMI including 2360 (0.06%) with FH. FH was associated with higher odds of ST-elevation MI (STEMI) (adjusted OR (aOR): 1.62, p<0.001) and non-ST-elevation MI (NSTEMI) (aOR: 1.29, p<0.001) but lower type 2 MI (aOR: 0.39, p<0.001) and takotsubo cardiomyopathy (aOR: 0.36, p=0.004). FH was associated with higher multistent percutaneous coronary interventions (aOR: 2.36, p<0.001), multivessel coronary artery bypass (aOR: 2.65, p<0.001), higher odds of intracardiac thrombus (aOR: 3.28, p=0.038) and mechanical circulatory support (aOR: 1.79, p<0.001). There was 50% reduction in odds of all-cause mortality (aOR: 0.50, p=0.006) and lower odds of mechanical ventilation (aOR: 0.37, p<0.001). There was no difference in rate of ventricular tachycardia, cardioversion, new implantable cardioverter defibrillator implantation, cardiogenic shock and cardiac arrest.ConclusionAmong patients hospitalised with AMI, FH was associated with higher STEMI and NSTEMI, lower type 2 MI and takotsubo cardiomyopathy, higher number of multiple stents and coronary bypasses, and mechanical circulatory support device but was associated with lower all-cause mortality and rate of mechanical ventilation.

Cutibacterium acnes is a skin commensal which is most often regarded as a contaminant when detected on blood cultures. In rare instances, it may be the causative pathogen in severe systemic illnesses. Subacute endocarditis, especially of prosthetic valves and devices, is an important grave pathology caused by Cutibacterium acnes. Herein we report two cases of prosthetic valve endocarditis with varied presentations as valve dehiscence with a \"rocking\" prosthetic valve apparatus in one encounter and as a septic embolic stroke in the second encounter. Although a rare cause of endocarditis, it becomes an especially important entity in patients with prosthetic devices and should be high in the list of differentials.

Objectives Trauma registries are essential tools for improving trauma care quality and efficiency, but many fail to capture long-term patient-reported outcome measures (PROMs). Focusing on these outcomes is crucial for understanding the extent of disability patients experience and identifying potential post-discharge interventions to optimize recovery. Studies reflecting the experience from low- and middle-income countries in this area are limited. Therefore, we aim to develop a digital trauma registry in Pakistan to prospectively capture patient-reported outcome measures at one, three, six, and twelve months post-injury. Methods We will develop and implement a digital trauma registry at two tertiary care facilities in Karachi, Pakistan: Aga Khan University Hospital and Jinnah Postgraduate Medical Center. The registry will include all admitted adult trauma patients (≥ 18 years). Data collection will be conducted digitally using tablets, with mortality, level of disability, functional status, and quality of life as primary outcomes. Follow-up data will be collected through telephone interviews with patients and caregivers. We will employ descriptive statistics to summarize participant’s socio-demographic and clinical characteristics. Additionally, we will perform survival analysis using Kaplan-Meier curves and Cox proportional hazard models and utilize mixed-effects linear regression to adjust for potential confounders for primary outcomes. Discussion The trauma registry will fill the current gap in knowledge regarding long-term outcomes among trauma patients in low- and middle-income countries (LMICs). This study will delineate future direction for capturing post-discharge data, enhancing our understanding of recovery, and informing the design of interventions aimed at improving long-term outcomes.

ObjectivesA diverse set of trauma scoring systems are used globally to predict outcomes and benchmark trauma systems. There is a significant potential benefit of using these scores in low and middle-income countries (LMICs); however, its standardized use based on type of injury is still limited. Our objective is to compare trauma scoring systems between neurotrauma and polytrauma patients to identify the better predictor of mortality in low-resource settings.MethodsData were extracted from a digital, multicenter trauma registry implemented in South Asia for a secondary analysis. Adult patients (≥18 years) presenting with a traumatic injury from December 2021 to December 2022 were included in this study. Injury Severity Score (ISS), Trauma and Injury Severity Score (TRISS), Revised Trauma Score (RTS), Mechanism/GCS/Age/Pressure score and GCS/Age/Pressure score were calculated for each patient to predict in-hospital mortality. We used receiver operating characteristic curves to derive sensitivity, specificity and area under the curve (AUC) for each score, including Glasgow Coma Scale (GCS).ResultsThe mean age of 2007 patients included in this study was 41.2±17.8 years, with 49.1% patients presenting with neurotrauma. The overall in-hospital mortality rate was 17.2%. GCS and RTS proved to be the best predictors of in-hospital mortality for neurotrauma (AUC: 0.885 and 0.874, respectively), while TRISS and ISS were better predictors for polytrauma patients (AUC: 0.729 and 0.722, respectively).ConclusionTrauma scoring systems show differing predictability for in-hospital mortality depending on the type of trauma. Therefore, it is vital to take into account the region of body injury for provision of quality trauma care. Furthermore, context-specific and injury-specific use of these scores in LMICs can enable strengthening of their trauma systems.Level of evidenceLevel III.

This study explores how green finance drives the development of green and low-carbon enterprises in China and examines the moderating role of green market demand. Using quantitative methods, data were collected from 404 valid questionnaires covering industrial enterprises of varying sizes, regions, and years of establishment. Structural equation modeling and artificial neural network analysis were employed to test the proposed framework. The findings reveal that green finance significantly supports low-carbon transformation by enabling sustainable practices. Two key mediators—optimization of financing costs and low-carbon technological innovation—play crucial roles in this process. However, increased green market demand negatively moderates the effect of financing cost optimization, while positively enhancing the impact of technological innovation. These results highlight the dual moderating effects of market demand. The study contributes by constructing a hybrid model that integrates green finance mechanisms with low-carbon enterprise development and provides empirical insights based on Chinese industrial data. It underscores the importance of tailoring green finance policies to varying market conditions. Future research may expand on these findings by examining how green finance operates in different industrial contexts or market structures.