The single most significant risk factor for testosterone deficiency in men is obesity. The pathophysiological mechanisms involved in male obesity-related secondary hypogonadism are highly complex. Obesity-induced increase in levels of leptin, insulin, proinflammatory cytokines and oestrogen can cause a functional hypogonadotrophic hypogonadism with the defect present at the level of the hypothalamic gonadotrophin-releasing hormone (GnRH) neurons. The resulting hypogonadism by itself can worsen obesity, creating a self-perpetuating cycle. Obesity-induced hypogonadism is reversible with substantial weight loss. Lifestyle-measures form the cornerstone of management as they can potentially improve androgen deficiency symptoms irrespective of their effect on testosterone levels. In selected patients, bariatric surgery can reverse the obesity-induced hypogonadism. If these measures fail to relieve symptoms and to normalise testosterone levels, in appropriately selected men, testosterone replacement therapy could be started. Aromatase inhibitors and selective oestrogen receptor modulators are not recommended due to lack of consistent clinical trial-based evidence.

Conduct a multicenter proof-of-concept clinical evaluation to assess the accuracy of an artificial intelligence system on a smartphone for automated detection of diabetic foot ulcers. The evaluation was undertaken with patients with diabetes (n = 81) from September 2020 to January 2021. A total of 203 foot photographs were collected using a smartphone, analysed using the artificial intelligence system, and compared against expert clinician judgement, with 162 images showing at least one ulcer, and 41 showing no ulcer. Sensitivity and specificity of the system against clinician decisions was determined and inter- and intra-rater reliability analysed. Predictions/decisions made by the system showed excellent sensitivity (0.9157) and high specificity (0.8857). Merging of intersecting predictions improved specificity to 0.9243. High levels of inter- and intra-rater reliability for clinician agreement on the ability of the artificial intelligence system to detect diabetic foot ulcers was also demonstrated (Kα > 0.8000 for all studies, between and within raters). We demonstrate highly accurate automated diabetic foot ulcer detection using an artificial intelligence system with a low-end smartphone. This is the first key stage in the creation of a fully automated diabetic foot ulcer detection and monitoring system, with these findings underpinning medical device development.

Metabolic dysfunction-associated fatty liver disease (MAFLD) has now affected nearly one-third of the global population and has become the number one cause of chronic liver disease in the world because of the obesity pandemic. Chronic hepatitis resulting from hepatitis B virus (HBV) and hepatitis C virus (HCV) remain significant challenges to liver health even in the 21st century. The co-existence of MAFLD and chronic viral hepatitis can markedly alter the disease course of individual diseases and can complicate the management of each of these disorders. A thorough understanding of the pathobiological interactions between MAFLD and these two chronic viral infections is crucial for appropriately managing these patients. In this comprehensive clinical review, we discuss the various mechanisms of chronic viral hepatitis-mediated metabolic dysfunction and the impact of MAFLD on the progression of liver disease.

The intricate relationship between metabolic-associated fatty liver disease (MAFLD) and maternal complications has rapidly become a significant health threat in pregnant women. The presence of MAFLD in pregnancy increases the maternal risk of metabolic complications and comorbidities for both mother and baby. The preexistence or development of MAFLD in pregnancy is a complex multifactorial disorder that can lead to further complications for mother and baby. Therefore, as pregnant women are severely underrepresented in clinical research, there is a great need for a fair inclusion of this group in clinical trials. This review aims to explore the effects of MAFLD during pregnancy in the context of maternal complications and outcomes and explore the effects of pregnancy on the development and progression of MAFLD within the context of maternal obesity, altered metabolic profiles, gestational diabetes and altered hormonal profiles. We also addressed potential implications for the presence of MAFLD during pregnancy and its management in the clinical setting.

The gut–adipose tissue axis plays a crucial role in metabolic health. It is a two-way communication pathway between the gastrointestinal tract and adipose tissue. This axis influences physiological processes vital for maintaining metabolic health, including energy homeostasis, lipid metabolism, and inflammation. Emerging research suggests that the gut microbiota, composed of trillions of microorganisms residing in the intestines, significantly impacts this axis by modulating host metabolism. An imbalance in the gut microbiota (dysbiosis) has been linked to obesity, insulin resistance, and other metabolic disorders. Innovative therapeutic strategies and dietary interventions aimed at modulating the gut–adipose tissue axis have shown encouraging results in improving metabolic health. A deeper critical understanding of the gut–adipose tissue axis is, therefore, essential in understanding the pathophysiology of metabolic disorders so that targeted interventions can be developed to prevent and treat these metabolic disorders. This article highlights the need for integrative approaches that consider both gastrointestinal and adipose functions in metabolic health management.