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\"Andrews shares reflections on her astonishing career and unveils her personal story of dealing with the demands of unimaginable success, being a new mother, the end of her first marriage, embracing two stepchildren, adopting two more children, and falling in love with Blake Edwards.\"-- From publisher's description.

ObjectiveChronic obstructive pulmonary disease (COPD) is a major cause of global illness and death, most commonly caused by cigarette smoke. The mechanisms of pathogenesis remain poorly understood, limiting the development of effective therapies. The gastrointestinal microbiome has been implicated in chronic lung diseases via the gut-lung axis, but its role is unclear.DesignUsing an in vivo mouse model of cigarette smoke (CS)-induced COPD and faecal microbial transfer (FMT), we characterised the faecal microbiota using metagenomics, proteomics and metabolomics. Findings were correlated with airway and systemic inflammation, lung and gut histopathology and lung function. Complex carbohydrates were assessed in mice using a high resistant starch diet, and in 16 patients with COPD using a randomised, double-blind, placebo-controlled pilot study of inulin supplementation.ResultsFMT alleviated hallmark features of COPD (inflammation, alveolar destruction, impaired lung function), gastrointestinal pathology and systemic immune changes. Protective effects were additive to smoking cessation, and transfer of CS-associated microbiota after antibiotic-induced microbiome depletion was sufficient to increase lung inflammation while suppressing colonic immunity in the absence of CS exposure. Disease features correlated with the relative abundance of Muribaculaceae, Desulfovibrionaceae and Lachnospiraceae family members. Proteomics and metabolomics identified downregulation of glucose and starch metabolism in CS-associated microbiota, and supplementation of mice or human patients with complex carbohydrates improved disease outcomes.ConclusionThe gut microbiome contributes to COPD pathogenesis and can be targeted therapeutically.

When disaster strikes in the form of rain on Aunt Sue's wedding day, flower girl and self-proclaimed fairy princess Geraldine finds a way to bring sunshine to the party, reminding everyone that the most important thing at a wedding is the most special sparkle of all--happiness and love.

Background Type 1 diabetes (T1D) frequently develops in childhood and is preceded by a non‐symptomatic period of autoimmunity. Alterations in the gut microbiome are implicated in T1D pathogenesis. Bifidobacterium is a significant focus due to its positive health impacts, association with breastfeeding and presence in probiotics and infant milk‐formulas. This systematic review aims to investigate Bifidobacterium's association with T1D across disease stages. Methods A comprehensive electronic search was conducted in MEDLINE, EMBASE and Web of Science, from 2011 to 2024. The search used a combination of medical subject headings and keywords related to Bifidobacterium. Studies included individuals at risk of T1D (pre‐stage, stage 1 or 2 asymptomatic T1D) and with stage 3 symptomatic T1D while excluding T2D, clinical trials and animal studies. Results The search initially retrieved 1120 articles. Of these, 25 papers met the inclusion criteria, covering 4533 individuals (842 cases with or at‐risk of T1D and 3691 healthy controls). The studies highlighted variability in Bifidobacterium abundance in T1D, with higher abundance found more often in at‐risk asymptomatic individuals and lower abundance frequently found in those with established T1D. Conclusion These findings do not support loss of Bifidobacterium as a key factor in the early development of T1D. Further studies are needed to explore Bifidobacterium's role in T1D progression and management. Bifidobacterium are generally considered beneficial bacteria, and are found in probiotic formulations currently being trialled for type 1 diabetes (T1D) prevention. In this systematic review, we find that there is a reduction in Bifidobacterium species after T1D diagnosis and an increase or no change in Bifidobacterium abundance in those at risk of T1D. These findings do not support a role for Bifidobacterium in T1D prevention.

Even though Gerry is cast as the court jester instead of the crystal princess in her ballet class's spring performance, she eventually regains her sparkle and once again feels like a fairy princess.

Diabetes-related foot ulceration (DFU) is a common complication of diabetes, with a significant impact on survival, health care costs, and health-related quality of life. The prognosis of DFU varies widely among individuals. The International Working Group on the Diabetic Foot recently updated their guidelines on how to classify ulcers using \"classical\" classification and scoring systems. No system was recommended for individual prognostication, and the group considered that more detail in ulcer characterization was needed and that machine learning (ML)-based models may be the solution. Despite advances in the field, no assessment of available evidence was done. This study aimed to identify and collect available evidence assessing the ability of ML-based models to predict clinical outcomes in people with DFU. We searched the MEDLINE database (PubMed), Scopus, Web of Science, and IEEE Xplore for papers published up to July 2023. Studies were eligible if they were anterograde analytical studies that examined the prognostic abilities of ML models in predicting clinical outcomes in a population that included at least 80% of adults with DFU. The literature was screened independently by 2 investigators (MMS and DAR or EH in the first phase, and MMS and MAS in the second phase) for eligibility criteria and data extracted. The risk of bias was evaluated using the Quality In Prognosis Studies tool and the Prediction model Risk Of Bias Assessment Tool by 2 investigators (MMS and MAS) independently. A narrative synthesis was conducted. We retrieved a total of 2412 references after removing duplicates, of which 167 were subjected to full-text screening. Two references were added from searching relevant studies' lists of references. A total of 11 studies, comprising 13 papers, were included focusing on 3 outcomes: wound healing, lower extremity amputation, and mortality. Overall, 55 predictive models were created using mostly clinical characteristics, random forest as the developing method, and area under the receiver operating characteristic curve (AUROC) as a discrimination accuracy measure. AUROC varied from 0.56 to 0.94, with the majority of the models reporting an AUROC equal or superior to 0.8 but lacking 95% CIs. All studies were found to have a high risk of bias, mainly due to a lack of uniform variable definitions, outcome definitions and follow-up periods, insufficient sample sizes, and inadequate handling of missing data. We identified several ML-based models predicting clinical outcomes with good discriminatory ability in people with DFU. Due to the focus on development and internal validation of the models, the proposal of several models in each study without selecting the \"best one,\" and the use of nonexplainable techniques, the use of this type of model is clearly impaired. Future studies externally validating explainable models are needed so that ML models can become a reality in DFU care. PROSPERO CRD42022308248; https://www.crd.york.ac.uk/PROSPERO/view/CRD42022308248.

Despite her scabby knees and dirty fingernails, Geraldine knows that she is a princess inside and shows it through her behavior at home and in school.

Diabetes-related foot ulceration (DFU), a serious but preventable complication of diabetes, is a leading cause of hospitalisation, lower extremity amputation and disability worldwide. People with DFU have a greater burden of cardiovascular risk factors, heart failure and chronic kidney disease, resulting in over two-fold higher risk of cardiovascular death compared with people with diabetes without DFU. Here, we propose a “cardio-renal-metabolic-foot” connection in people with diabetes based on shared pathophysiological mechanisms linking DFU with cardiovascular and renal disease. Whilst these mechanistic links remain to be fully elucidated, systemic inflammation and infection in the context of DFU are postulated as key mediators in the development, and progression of, cardiovascular and renal disease. However, cardiovascular and renal disease are also implicated in the pathogenesis of DFU, highlighting the multi-directional interplay between conditions. The impact of screening, prevention, and early management of cardiovascular complications associated with DFU requires further research. Multi-modality cardiac imaging could play a role in unravelling disease mechanisms leading to novel therapeutic strategies, as well as facilitating personalised risk assessment and management. Recent clinical trials have transformed the therapeutic landscape for people with type 2 diabetes, by demonstrating that sodium glucose co-transporter 2 inhibitors, glucagon-like peptide-1 agonists and non-steroidal mineralocorticoid receptor antagonists improve cardiovascular and renal outcomes. Although dedicated research in people with DFU is warranted, these therapies could target multiple facets of the “cardio-renal-metabolic-foot” connection. The holistic, person-centred approach to managing DFU should incorporate new multidisciplinary models of care focusing on the prevention and management of cardiovascular and kidney disease. Graphical abstract The cardio-renal-metabolic-foot connection in people with diabetes. There is a critical need for (1) a better understanding of mechanisms connecting DFU with cardiovascular and kidney disease, perhaps guided by cardiac imaging, novel biomarkers, multi-omics and artificial intelligence to facilitate current treatments and the development of novel therapeutic strategies, (2) more data from clinical trials, registries and biobanks to inform clinical guidelines and evidence-based medicine, and (3) health system-wide integration of structured models of care with a contemporary emphasis on cardio-renal-metabolic-foot health to improve patient outcomes. DFU diabetes-related foot ulceration. Created with BioRender.com

After spending weeks making valentines for all of her family and friends, self-proclaimed fairy princess Gerry takes the wrong folder to school and must find another way to tell her classmates how they sparkle.

Background: There are well-documented gender differences in adolescent suicidal behavior; death by suicide is more common in males, while nonfatal suicide attempts are more common among females. Over the past three decades, researchers have documented the effectiveness of a myriad of suicide prevention initiatives. However, there has been insufficient attention to which types of suicide prevention interventions are effective in changing attitudes and behaviors for young males and females. In this review of the literature, we consider common examples of primarily universal suicide prevention programs from three implementation settings: school-based, community-based, and healthcare-based. Our purpose is to delineate how the potential gender bias in such strategies may translate into youth suicide prevention efforts. Methods: Research in which gender was found to moderate program success was retrieved through online databases. Results: The results that feature programming effects for both males and females are provocative, suggesting that when gender differences are evident, in almost all cases, females seem to be more likely than males to benefit from existing prevention programming. Conclusions: We conclude by considering recommendations that may benefit males more directly. Implications for adolescent suicide prevention in particular are discussed. Personalization of suicide intervention is presented as a promising solution to reduce suicide rates.