Growing evidence suggests that lowering non-high-density lipoprotein cholesterol (non-HDL-C) levels is associated with a reduced risk of cardiovascular diseases (CVD) events. However, data on this relationship remain scarce in the Arabian Gulf region. The Gulf TriglyCeride And ResiduaL CardiovascuLar RiSk (Gulf CALLS) study investigated the association between failure to achieve non-HDL-C targets (<2.6 mmol/L) and residual CVD risk in very high-risk patients from the region who were on statin therapy and had well-controlled low-density lipoprotein cholesterol (LDL-C) levels (<1.8 mmol/L [70 mg/dL]). This retrospective study evaluated patients across 5 Arabian Gulf countries, aged > 45 years with established CVD or diabetes, LDL-C levels <1.8 mmol/L (<70 mg/dL), and triglyceride levels <4.5 mmol/L (<400 mg/dL) on lipid-lowering therapy. A total of 22% (521/2344) of the patients did not achieve the non-HDL-C target. In the adjusted Cox regression model, patients who achieved the non-HDL-C goal at baseline had a 25% lower risk of subsequent CVD events than those who did not (hazard ratio, .75; 95% confidence interval: .58-.97; P = .028). In the present study involving very high-risk patients on statin therapy, failure to achieve non-HDL-C targets was associated with a significantly higher residual CVD risk, despite well-controlled LDL-C levels.

Diabesity, the coexistence of type 2 diabetes mellitus (T2DM) and obesity, represents one of the major global health challenges. This review aims to synthesize current evidence on personalized medical nutrition therapy (MNT) and structured physical exercise as cornerstones of diabesity management, with a particular focus on very-low-energy ketogenic therapy (VLEKT).

Conventional pharmacotherapies improve glycemic control and promote weight reduction but often fail to fully address the multifactorial pathophysiology of diabesity. MNT has demonstrated significant efficacy in improving glycemic regulation, reducing weight, and modulating cardiometabolic risk factors. Among dietary strategies, the Mediterranean diet provides sustainable benefits, while more intensive interventions such as low-energy diets and ketogenic diets can induce rapid and clinically meaningful improvements, with emerging evidence supporting favorable effects on gut microbiota and inflammation. Complementary lifestyle interventions, particularly structured exercise programs combining aerobic and resistance training, further enhance metabolic outcomes and may contribute to T2DM remission in selected patients. Integration of MNT with incretin-based therapies holds promise for optimizing efficacy while preserving nutritional adequacy and functional health. Effective management of diabesity requires a multidisciplinary, precision-based approach. Personalized MNT and structured exercise represent foundational strategies, while pharmacological therapies provide valuable adjuncts. Among available options, VLEKT stands out for its ability to target key mechanisms of diabesity, including insulin resistance, adiposity, and chronic inflammation. Future diabesity care will rely on integrating nutrition, physical exercise, and pharmacotherapy within individualized frameworks to achieve sustained metabolic control and improved quality of life.

Autoimmune uveitis (AU) lacks targeted therapies beyond immunosuppression. We identified hyodeoxycholate (HDCA), a gut-derived secondary bile acid, as a key immunometabolic regulator in AU. Metabolomics revealed systemic depletion of HDCA and oleic acid (C18:1n9) in AU patients and experimental AU (EAU) mice, correlating with disease severity. HDCA administration effectively attenuated EAU by reducing pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α) and elevating IL-10. Mechanistically, HDCA inhibits Farnesoid X Receptor in splenic red pulp macrophages, activating SREBP1c-dependent fatty acid synthase, which enhances oleic acid production. Systemic oleic acid suppresses ocular Th17 responses and promotes M2 macrophage polarization, enhancing anti-inflammatory immunity. These findings define a spleen-to-eye immunometabolic axis driven by HDCA-mediated macrophage reprogramming, positioning HDCA as a promising therapeutic for AU.

Coronary artery ectasia (CAE) is a coronary abnormality characterized by arterial dilation, with inflammation, hypertension, dyslipidemia, and diabetes hypothesized to be implicated in its pathogenesis. The exact relationship between CAE and diabetes remains unclear, with previous studies reporting contradictory findings. We conducted a systematic review and meta-analysis following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PROSPERO: CRD42024627403). Four databases (PubMed, Scopus, Web of Science, and Embase) were searched up to October 2024. Eligible studies included angiographically diagnosed CAE cases and controls with reported diabetes prevalence. Relative risks (RR) were calculated for diabetes, hypertension, and dyslipidemia; mean differences for body mass index and fasting blood sugar. Subgroup analyses compared isolated versus nonisolated CAE. Forty-six studies consisting of 6215 CAE patients and 59,484 non-CAE controls were included. Pooled results showed no significant association between diabetes and CAE (RR, 1.00; 95% CI, 0.88-1.13; I2, 76.65%; P = 0.95). Subgroup analyses showed no association in isolated CAE (RR,= 1.10; 95% CI, 0.92-1.32; I2, 50.45%; P = 0.31) or nonisolated CAE (RR, 0.84; 95% CI, 0.68-1.04; I2, 82.31%; P = 0.12). Fasting blood sugar analysis showed no significant difference between CAE and controls (mean differences, 2.43; 95% CI, -1.15 to 6.02; I2, 50.60%; P = 0.18). While diabetes is a well-established risk factor for atherosclerotic coronary disease, our pooled evidence indicates its contribution to ectatic changes is limited and not associated with CAE.

This study investigated the renal protection effect and mechanism of Zuogui Jiangtang Yishen Prescription(ZGJTYSF) for db/db mice with diabetic kidney disease(DKD), focusing on the semaphorin 3a(Sema3a)/vascular endothelial growth factor A(VEGFA)/vascular endothelial growth factor receptor 2(VEGFR2) pathway. A DKD mouse model was established using 50 db/db mice(6 weeks, males) and 10 age-matched male db/m mice after 8 weeks on a regular diet. The db/db mice were randomly divided into 5 groups: the model group, the western medicine(dapagliflozin, 0.001 3 g·kg~(-1)) group, and the low-(6.4 g·kg~(-1)), medium-(12.8 g·kg~(-1)), and high-dose(25.6 g·kg~(-1)) ZGJTYSF groups, with 10 mice in each group. Another 10 db/m mice were set as the normal group. For the normal and model groups, the mice were administrated an equal amounts of saline by gavage. After intervention for 8 consecutive weeks, fasting blood glucose(FBG), urinary albumin-to-creatinine ratio(UACR), and liver and kidney function changes were detected in mice. Histopathological changes in kidney tissue of each group were observed by hematoxylin-eosin(HE), periodic acid-Schiff(PAS) staining, Masson staining, and transmission electron microscopy(TEM). Quantitative real-time polymerase chain reaction(real-time PCR) was used to detect the expression levels of glomerular endothelial cell marker(CD34), Sema3a, VEGFA, and VEGFR2 mRNA in renal tissues of each group, and Western blot was applied to measure the expression levels of CD34, Sema3a, VEGFA, and VEGFR2 proteins in renal tissues of each group. The results showed that compared with the normal group, mice in the model group had significantly higher FBG(P&lt;0.05), significantly higher UACR(P&lt;0.05), and significantly higher CD34, Sema3a, VEGFA, VEGFR2 mRNA expression and protein expression(P&lt;0.05). The model group also showed an increased glomerular volume, fused podocyte protrusions, swollen endothelial cells, narrowed and damaged capillary lumen, increased stroma, and thickened glomerular basement membrane. After intervention, ZGJTYSF groups reduced FBG and UACR in DKD mice compared with the model group, which was positively correlated with the administration dosage, and the difference was statistically significant at the 8th week of administration(P&lt;0.05). Compared with the model group, ZGJTYSF groups and the western medicine group improved glomerular and endothelial cells and podocyte injury. They could reduce CD34, Sema3a, VEGFA, VEGFR2 mRNA expression in kidney tissues, and the expression of CD34 and Sema3a mRNA was significantly reduced(P&lt;0.05). They could also reduce the expression of CD34, Sema3a, VEGFA, and VEGFR2 proteins, and VEGFA proteins expression was significantly reduced in the dapagliflozin group and the medium-dose group of ZGJTYSF(P&lt;0.05), Sema3a and VEGFR2 proteins expression were significantly reduced in the low-dose group of ZGJTYSF(P&lt;0.05). The study revealed that ZGJTYSF can delay the progression of DKD by inhibiting the Sema3a/VEGFA/VEGFR2 pathway, and its mechanism, besides improving glucose metabolism in mice, may be related to the improvement of podocyte and endothelial cell injury.

Dyslipidemia is one of the driving forces in the pathogenesis of atherosclerosis and its resultant cardiovascular disease. Both these conditions are characterized by an increase in proatherogenic lipids compared to anti-atherogenic lipids. Atherogenic Indices have been developed to predict CVD risk without increasing the cost of testing; however, most of the studies done to date have used these indices in patients who have already suffered a coronary event. Dyslipidemia is most prevalent in cases of type 2 diabetes mellitus (T2DM). Therefore, this study was designed to assess atherogenic risk (via atherogenic indices) in newly diagnosed treatment-naïve obese and lean patients of T2DM.

Treatment-naïve, newly diagnosed patients of T2DM were recruited and grouped into obese (BMI ≥ 25 kg/m²) and lean (BMI <18.5 kg/m²) groups. Blood was collected in a fasting state for the estimation of glycemic parameters and fasting lipid profile. Atherogenic indices (LDL-C/HDL-C, non-HDL-C, TC/HDL-C, atherogenic coefficient, lipoprotein combined index, and atherogenic index of plasma (AIP)) were calculated using predefined formulas.

LDL-C/HDL-C, non-HDL-C, TC/HDL-C, atherogenic coefficient, lipoprotein combined index, and AIP were higher in the obese group compared to the lean group. However, these calculated indices were above the recommended cutoffs in both obese and lean patients with T2DM.

This study is the first to document increased atherogenic risk in both obese and lean patients (newly diagnosed) with T2DM. Although CVD risk is higher among the obese patients, aggressive control of plasma lipids is required in all patients with T2DM, irrespective of BMI.

Thyroid carcinoma is the most prevalent endocrine malignancy, with a worldwide increasing incidence. Capsular invasion and neural invasion (NI) are pivotal prognostic factors for recurrence and survival; however, their preoperative noninvasive assessment remains challenging.

We aimed to identify computed tomography (CT) radiomic biomarkers associated with capsular invasion in thyroid carcinoma, construct machine learning models integrating radiomic and clinical data, and evaluate their utility for NI risk stratification.

In this retrospective cohort, 111 patients with thyroid carcinoma were divided into capsular invasion-positive (n=63) and capsular invasion-negative (n=48) groups, with 37 (33.3%) cases presenting concurrent NI. Radiomic features were extracted from arterial and venous phase CT images at original resolution, including 111 gray-level co-occurrence matrix features. Nine key radiomic features (A1-A9) were selected via least absolute shrinkage and selection operator regression (λ=0.017). To preserve the physical meaning of texture features (eg, spatial correlation and contrast reflecting tumor microstructural heterogeneity), no resampling or scaling was performed on the regions of interest during radiomic feature extraction. Nomogram models and random forest (RF) models were constructed based on clinical indicators (galectin-3, etc) and radiomic features, respectively. Additionally, a neural network (NN) model integrating multimodal data was developed. Model stability was verified using 5-fold cross-validation and 1000-time bootstrap resampling, while performance was evaluated via receiver operating characteristic curves, calibration curves, and decision curve analysis.

Model performance analysis revealed that among the nomogram models, the clinical indicator-based nomogram achieved an internally estimated area under the curve (AUC) of 0.9418 (95% CI 0.892-0.976) in the capsular invasion prediction task. The radiomic-based nomogram had an internally estimated AUC of 0.9334 (95% CI 0.881-0.968) in the capsular invasion prediction task and 0.8001 (95% CI 0.663-0.898) in the cross-label association analysis task. In RF models, clinical indicator-based and radiomic-based RFs exhibited an AUC of 0.7646 (95% CI 0.651-0.857) and 0.8102 (95% CI 0.703-0.892) in the cross-label association analysis task, respectively. The NN model performed promisingly, with an AUC of 0.775 (95% CI 0.621-0.903) in the cross-label association analysis task and a mean absolute error of <0.05 on the calibration curve.

Capsular invasion is a strong predictor of NI risk in thyroid carcinoma. Radiomic models based solely on preoperative CT images show potential for preoperative NI risk stratification. Models incorporating clinical parameters (obtained from postoperative tissue), including the integrated multimodal model, are more accurately characterized as postoperative risk stratification tools. The NN model, which integrated raw CT images with clinical data, achieved an AUC of 0.775 (95% CI 0.621-0.903), underscoring the potential of such multimodal analysis to capture complex relationships between imaging phenotypes and tissue-level biomarkers for enhanced postoperative assessment. This framework's radiomic component points toward purely image-based, preoperative evaluation tools' development.

Breast density influences both breast cancer risk and the sensitivity of mammographic screening. Several countries routinely notify women of their breast density in community-based screening programmes and provide guidance directly or through general practitioners. In contrast, BreastScreen Aotearoa (BSA) does not currently notify breast density to women, resulting in limited awareness and raising concerns relating to equitable care, patient autonomy in decision making, trust in health professionals and uncertainty regarding clinical pathways. Although the recent Health New Zealand - Te Whatu Ora technical review provides a comprehensive evidence summary and identifies areas for further investigation, policy progression has not occurred as anticipated. An implementation timeline, governance responsibility, communication planning and culturally responsive approach have not yet been specified. Although emerging evidence suggests that artificial intelligence may offer more consistent and reproducible breast density assessment than radiologists, planning for its integration has not been outlined. Research from the comparable settings suggests that misunderstanding, rather than notification itself, drives anxiety. This highlights the importance of communication design, health literacy considerations and primary care readiness. Ethical considerations around transparency and informed decision making remain relevant for screening equity. Addressing the implementation barriers is now crucial, and a coordinated and equity-driven approach is required to inform future policy on breast density notification.

Gynaecological cancers are an increasing concern in Aotearoa New Zealand, with rapid growth in uterine cancer incidence in recent years. Understanding future incidence patterns is essential for planning and service delivery at a sub-national level.

Cancer registry data (2001-2022) were combined with population projections to estimate incidence of gynaecological cancers to 2045. Projections were generated using age-period-cohort Poisson regression models, with non-parametric bootstrapping to quantify uncertainty.

Annual gynaecological cancer cases are projected to increase 82% by 2045, reaching 2,497 (95% uncertainty interval [UI] 2,263-2,774) compared with 1,375 in 2020-2022. The overall age-standardised rate is projected to rise 21% from 36.6 (95% confidence interval [CI] 35.5-37.8) to 44.2 per 100,000 (95% UI 38.9-50.3). Uterine cancer contributes the largest increase, more than doubling from 717 to 1,506 cases annually (110%). Among Māori, cases rise 132% from 214 to 497 per year (95% UI 449-553); for Pacific women, they rise 137% from 165 to 391 (95% UI 340-449). Uterine cancer age-standardised rates are projected to increase from 27.3 to 39.6 per 100,000 for Māori, and from 74.3 to 97.5 for Pacific women. Regional variation is expected: the Northern Region is projected to have the largest absolute increase (+506 cases, 527 to 1,033) and the largest percentage increase (96%).

Gynaecological cancer incidence in Aotearoa New Zealand is projected to rise substantially over the next 20 years, driven by demographic change and increasing incidence of uterine cancer likely associated with risk factors such as excess body weight and diabetes. Findings highlight the need to prioritise prevention, proactive service planning and equity-focussed early detection.

A multicancer early detection (MCED) test was developed and validated in the case-control Circulating Cell-free Genome Atlas (CCGA) study (ClinicalTrials.gov identifier: NCT02889978). Previous analysis of the second (cross-validation) CCGA substudy identified prognostic value of cancer signal detection by the MCED test with 3-year follow-up. Here, we evaluated the prognostic value of a cancer signal detected (CSD) result in the third (validation) CCGA substudy (CCGA3) using an updated statistical methodology with 5-year follow-up.

CCGA3 participants with confirmed cancer were followed for up to 5 years; overall survival was stratified by MCED test result (CSD or no CSD [NCSD]). Observed survival was compared with the expected survival of a reference population calculated from Surveillance, Epidemiology, and End Results data matched to clinical characteristics (age, sex, cancer type, and stage) in each signal detection group.

Of 2,513 participants with stageable, invasive cancer, 792 (31.5%) died and 1,683 (67.0%) were confirmed alive at follow-up, with 38 (1.5%) lost to follow-up. CSD rates were higher in participants who died during follow-up compared with those alive (85% v 34%). Overall observed survival versus expected survival was similar for CSD (43% observed v 40% expected) and NCSD (88% observed v 81% expected) groups. For NCSD, hazard ratios (HRs) were more favorable (<1) relative to the matched reference population at all stages (P < .0001); for CSD, HRs were <1 at stages III to IV (P < .0001) and ≅1 at stages I to II (P > .4).

CSD cancers had long-term survival similar to expectations, even in early stages, indicating that CSD early-stage cancers are unlikely to be more micrometastatic and lethal than cancers detected by conventional means. The MCED test was likely to find clinically significant cancers without contributing to overdiagnosis.