Platform-directed allostery and quaternary structure dynamics of SAMHD1 catalysis.

SAMHD1 regulates cellular nucleotide homeostasis, controlling dNTP levels by catalysing their hydrolysis into 2'-deoxynucleosides and triphosphate. In differentiated CD4+ macrophage and resting T-cells SAMHD1 activity results in the inhibition of HIV-1 infection through a dNTP blockade. In cancer, SAMHD1 desensitizes cells to nucleoside-analogue chemotherapies. Here we employ time-resolved cryogenic-EM imaging and single-particle analysis to visualise assembly, allostery and catalysis by this multi-subunit enzyme. Our observations reveal how dynamic conformational changes in the SAMHD1 quaternary structure drive the catalytic cycle. We capture five states at high-resolution in a live catalytic reaction, revealing how allosteric activators support assembly of a stable SAMHD1 tetrameric core and how catalysis is driven by the opening and closing of active sites through pairwise coupling of active sites and order-disorder transitions in regulatory domains. This direct visualisation of enzyme catalysis dynamics within an allostery-stabilised platform sets a precedent for mechanistic studies into the regulation of multi-subunit enzymes.

Effect of Human Activity and Presence on the Behavior of Long-Tailed Macaques (Macaca fascicularis) in an Urban Tourism Site in Kuala Selangor, Malaysia.

The increasing overlap of resources between human and long-tailed macaque (Macaca fascicularis) (LTM) populations have escalated human-primate conflict. In Malaysia, LTMs are labeled as a 'pest' species due to the macaques' opportunistic nature. This study investigates the activity budget of LTMs in an urban tourism site and how human activities influence it. Observational data were collected from LTMs daily for a period of four months. The observed behaviors were compared across differing levels of human interaction, between different times of day, and between high, medium, and low human traffic zones. LTMs exhibited varying ecological behavior patterns when observed across zones of differing human traffic, e.g., higher inactivity when human presence is high. More concerning is the impact on these animals' welfare and group dynamics as the increase in interactions with humans takes place; we noted increased inactivity and reduced intra-group interaction. This study highlights the connection that LTMs make between human activity and sources of anthropogenic food. Only through understanding LTM interaction can the cause for human-primate conflict be better understood, and thus, more sustainable mitigation strategies can be generated.

Identifying Preferred Features of Weight Loss Programs for Adults With or at Risk of Type 2 Diabetes: A Discrete Choice Experiment With 3,960 Adults in the U.K.

OBJECTIVE: To understand preferences for features of weight loss programs among adults with or at risk of type 2 diabetes in the U.K. RESEARCH DESIGN AND METHODS: We conducted a discrete choice experiment with 3,960 U.K. adults living with overweight (n = 675 with type 2 diabetes). Preferences for seven characteristics of weight loss programs were analyzed. Simulations from choice models using the experimental data predicted uptake of available weight loss programs. Patient groups comprising those who have experience with weight loss programs, including from minority communities, informed the experimental design. RESULTS: Preferences did not differ between individuals with and without type 2 diabetes. Preferences were strongest for type of diet. Healthy eating was most preferred relative to total diet replacement (odds ratio [OR] 2.24; 95% CI 2.04-2.44). Individual interventions were more popular than group interventions (OR 1.40; 95% CI 1.34-1.47). Participants preferred programs offering weight loss of 10-15 kg (OR 1.37; 95% CI 1.28-1.47) to those offering loss of 2-4 kg. Online content was preferred over in-person contact (OR 1.24; 95% CI 1.18-1.30). There were few differences in preferences by gender or ethnicity, although weight loss was more important to women than to men, and individuals from ethnic minority populations identified more with programs where others shared their characteristics. Modeling suggested that tailoring programs to individual preferences could increase participation by ∼17 percentage points (68% in relative terms). CONCLUSIONS: Offering a range of weight loss programs targeting the preferred attributes of different patient groups could potentially encourage more people to participate in weight loss programs and support those living with overweight to reduce their weight.

The impact of the COVID-19 pandemic and associated disruptions in health-care provision on clinical outcomes in people with diabetes: a systematic review.

The COVID-19 pandemic triggered disruptions to health care and lifestyles that could conceivably impact diabetes management. We set out to identify the impact of disruptions caused by COVID-19 on clinical outcomes in people with diabetes. We performed a systematic review of the available literature in the MEDLINE and OVID databases from Jan 1, 2020, to June 7, 2023, and included 138 studies (n>1 000 000 people). All but five studies were judged to be at some risk of bias. All studies compared prepandemic with pandemic periods. All-cause mortality (six studies) and diabetes-related mortality (13 studies) showed consistent increases, and most studies indicated increases in sight loss (six studies). In adult and mixed samples, data generally suggested no difference in diabetic ketoacidosis frequency or severity, whereas in children and adolescents most studies showed increases with some due to new-onset diabetes (69 studies). Data suggested decreases in hospital admissions in adults but increases in diabetes-related admissions to paediatric intensive care units (35 studies). Data were equivocal on diabetic foot ulcer presentations (nine studies), emergency department admissions (nine studies), and overall amputation rates (20 studies). No studies investigated renal failure. Where reported, the impact was most pronounced for females, younger people, and racial and ethnic minority groups. Further studies are needed to investigate the longer-term impact of the pandemic and the on potential differential impacts, which risk further exacerbating existing inequalities within people with diabetes.

Genicular Artery Embolization: A Review of Essential Anatomic Considerations.

Genicular artery embolization is increasingly recognized as a safe and effective treatment option for symptomatic knee osteoarthritis and recurrent hemarthrosis after total knee arthroplasty. Genicular arteries are an essential contributor to vascular supply for the knee joint and demonstrate considerable variability. Familiarity with the anatomy and common variations is critical for preprocedural planning, accurate target selection, and minimizing adverse events in transarterial embolization procedures. This review aimed to provide a detailed discussion of the genicular artery anatomy that is relevant to interventional radiologists performing genicular artery embolization.

Palpable Breast Findings in High-risk Patients: Are Self- and Clinical Breast Exams Worthwhile?

OBJECTIVE: To assess breast imaging findings, biopsy rates, and malignancy rates in areas of palpable concern in women at high risk for breast cancer. METHODS: An IRB-approved retrospective review of a tertiary cancer center's breast imaging database was performed. Breast imaging and electronic medical records of high-risk women with palpable findings detected on self- or clinical breast examination from January 1, 2010, to January 1, 2016, were reviewed. Descriptive statistical analyses were conducted. RESULTS: Imaging correlates for 322 palpable findings in 238 high-risk women included 55/203 (27.1%) on mammography, 183/302 (60.6%) on US, and 20/47 (42.6%) on MRI. Biopsies were performed for 104/322 (32.3%) palpable findings: 95/104 (91.3%) under imaging guidance and 9/104 (8.7%) under palpation after negative imaging. Of 322 palpable findings, 16 (5.0%) were malignant in 16/238 (6.7%) women, yielding a positive predictive value of biopsy of 16.8% (95% CI: 9.2%-24%). Women diagnosed with cancer had 16/16 (100%) sonographic, 9/14 (64.3%) mammographic, and 7/7 (100%) MRI correlates. Cancer histopathology included 12 invasive ductal carcinomas, 1 ductal carcinoma in situ, 1 invasive lobular carcinoma, 1 malignant phyllodes tumor, and 1 metastatic carcinoid tumor. Over two years of follow-up imaging in 183/238 (76.9%) women were reviewed; 7/183 (3.8%) were diagnosed with breast cancer at least one year after presenting with a palpable concern in a different location. CONCLUSION: High-risk women with palpable findings exhibit a 6.7% malignancy rate, indicating the value of imaging workup in this population. In our cohort, imaging demonstrated a high negative predictive value.

Using Deep Learning to Improve Nonsystematic Viewing of Breast Cancer on MRI.

OBJECTIVE: To investigate the feasibility of using deep learning to identify tumor-containing axial slices on breast MRI images. METHODS: This IRB-approved retrospective study included consecutive patients with operable invasive breast cancer undergoing pretreatment breast MRI between January 1, 2014, and December 31, 2017. Axial tumor-containing slices from the first postcontrast phase were extracted. Each axial image was subdivided into two subimages: one of the ipsilateral cancer-containing breast and one of the contralateral healthy breast. Cases were randomly divided into training, validation, and testing sets. A convolutional neural network was trained to classify subimages into "cancer" and "no cancer" categories. Accuracy, sensitivity, and specificity of the classification system were determined using pathology as the reference standard. A two-reader study was performed to measure the time savings of the deep learning algorithm using descriptive statistics. RESULTS: Two hundred and seventy-three patients with unilateral breast cancer met study criteria. On the held-out test set, accuracy of the deep learning system for tumor detection was 92.8% (648/706; 95% confidence interval: 89.7%-93.8%). Sensitivity and specificity were 89.5% and 94.3%, respectively. Readers spent 3 to 45 seconds to scroll to the tumor-containing slices without use of the deep learning algorithm. CONCLUSION: In breast MR exams containing breast cancer, deep learning can be used to identify the tumor-containing slices. This technology may be integrated into the picture archiving and communication system to bypass scrolling when viewing stacked images, which can be helpful during nonsystematic image viewing, such as during interdisciplinary tumor board meetings.