Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen

There are many misconceptions about the prevalence and effects of hypoglycemia in people with type 2 diabetes (T2D), including hypoglycemia does not occur or does not have adverse consequences in T2D. This narrative review aims to help dispel these myths. Around 25% of people with T2D taking insulin for >5 years were found to have severe hypoglycemic events, which is comparable to the severe hypoglycemia rate in adults with type 1 diabetes (T1D) diagnosed within 5 years. The total number of hypoglycemic events among insulin-treated T2D, including severe hypoglycemia, is as high or higher than among those with T1D. Recent evidence suggests serious consequences of hypoglycemia may, in some respects, be greater in individuals with T2D, particularly regarding effects on the cardiovascular system. Hypoglycemia is generally patient-reported. Issues with hypoglycemia unawareness, limited glucose testing, limited recall, lack of event logging and fear of failure or shaming limits the number of hypoglycemic episodes reported by people with diabetes. Barriers to healthcare provider inquiry and reporting include lack of knowledge regarding the problem’s magnitude, competing priorities during patient visits, lack of incentives to report and limitations to documentation systems for adequate reporting. All people with diabetes should be encouraged to discuss their experiences with hypoglycemia without judgment or shame. Glucose targets, testing schedules (blood glucose or continuous glucose monitoring) and treatment plans should be reviewed often and individualized to the minimize risk of hypoglycemia. Finally, people with T2D on insulin should always be encouraged to have oral glucose and rescue medication immediately available

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Sanctuaries and reintroduction: a role in gorilla conservation?

First paragraph: The current threats to gorilla (Gorilla gorilla, Gorilla beringei) populations, and indeed African wildlife in general, are complex and inextricably interlinked, and include poverty, human population growth, loss of habitat (through logging, mining, and land conversion), and hunting (Butynski, 2001; Teleki, 2001; Nellemann and Newton, 2002). Overexploitation of wildlife is not a new phenomenon and was probably responsible for the historical and ecological extinction of many species (Rao and McGowan, 2002). However, increasing urbanization and associated market economies, modern hunting methods and road networks, have commercialized the bushmeat trade (Kemf and Wilson, 1997; Bowen-Jones, 1998; Robinson and Bodmer, 1999; Wilkie and Carpenter, 1999; Fa et al., 2002; Nellemann and Newton, 2002). The general consensus seems to be that this trade is out of control, unsustainable, and accelerating (Ammann and Pearce, 1995; Kemf and Wilson, 1997; Butynski, 2001), and that gorillas are in danger of becoming extinct in the wild if causal factors are not effectively addressed (Butynski, 2001)

The impact of firm-firm externalities on environmental standard

[[abstract]]A model of two industries (sectors) in one economy, in which a sector’s production suffers from the other sector’s pollution emission, is presented to determine the optimal regulatory emission standard and to contrast the gap between the two versions: in the presence and absence of firm-firmdamage effect. The discrepancy of the emission standard setting is surely existent in the presence of firm-firm externalities compared with in the absenceof those. The results reveal that the planned output of polluting industry ishigher in the presence of firm-firm damage effect than in the absence, butthat of nonpolluting industry depends on demand elasticity and damage function.[[notice]]補正完畢[[booktype]]紙