The long-term cement sheath sealing integrity is essential for maintaining zonal isolation during oil and gas well operations. However, conventional self-healing evaluation methods often involve specimen transfer among separate curing, damage-generation, healing, and testing devices, which may disturb the original leakage pathway and affect the measured recovery. In this study, an integrated evaluation method was developed to perform cement curing, pressure-induced leakage pathway generation, gas-triggered healing, and sealing evaluation on the same specimen. Three operational indicators were employed: fracture-creation pressure-bearing capacity, flow-based self-healing efficiency, and secondary self-healing efficiency. At 90°C and a slurry density of 1.90 g/cm 3 , the conventional cement slurry showed no measurable sealing recovery within 72h. The expansive type system exhibited rapid recovery, reaching 88.24% at 12h and 84.12% at 72h, whereas the dissolution-viscosity type system increased progressively from 12.5% to 50.0%. In repeated damage-healing tests, the secondary self-healing efficiency of the two systems were 57.50% and 57.14%, respectively. Higher temperatures enhanced sealing recovery, and both systems approached approximately 90% after extended healing. The dissolution-viscosity type system also exhibited a higher initial fracture-creation pressure and lower initial gas flow rate. The proposed method enables continuous, time-resolved comparison of cement sheath sealing recovery while reducing specimen-transfer disturbance.
Objective Thyroid cancer incidence has risen steadily, and elevated body mass index (BMI) is a modifiable risk factor for it. We assessed the disease burden of high BMI-attributable thyroid cancer across the BRICS countries (Brazil, Russia, India, China, and South Africa), which have undergone rapid lifestyle transitions, and characterized temporal, age, period, and birth-cohort patterns from 1990 to 2021. Methods In this cross-sectional, population-based secondary analysis, we used modelled attributable-burden estimates from the Global Burden of Disease Study 2021 (GBD 2021) to evaluate spatiotemporal trends in disability-adjusted life years (DALYs; the primary endpoint) and mortality attributable to high BMI-related thyroid cancer from 1990 to 2021, applying descriptive analyses, Joinpoint regression, and age–period–cohort (APC) modeling. Results In 2021, Russia exhibited the highest age-standardized DALYs rate (ASDR) (2.09 per 100,000 population), followed by South Africa and Brazil, while China and India demonstrated the lowest burden. Although women bore more DALYs overall, men showed more pronounced increasing trends, particularly in China (annual percentage change [AAPC]: 2.31% in men vs. -0.35% in women). DALY rates rose with age in all five countries. Period effects showed sustained increases in China and India but declining trends in Russia. Cohort effects indicated elevated risk among younger birth cohorts in China and India (relative risk [RR] >1.7 for 1997 birth cohort), contrasting with stable or decreasing patterns in Russia and Brazil. Conclusions Cross-national and sex-specific disparities exist in the high BMI-attributable thyroid cancer burden among BRICS nations. The pronounced increase among Chinese and Indian male populations and younger birth cohorts highlights the potential value of enhanced public-health investment in obesity prevention, risk-based assessment of thyroid disease, and improved surveillance of high-risk populations, rather than population-wide thyroid cancer screening.
Objective Patients with malignancies often require frequent contrast-enhanced CT for treatment monitoring, but renal dysfunction or hypersensitivity reactions frequently restrict the use of iodinated contrast agents. This study aimed to evaluate whether adding deep learning (DL)-generated synthetic contrast images to precontrast CT enhances diagnostic performance in oncology patients in whom iodinated contrast is contraindicated or limited. Methods A DL model was trained using 200 pairs of precontrast and contrast-enhanced abdominal CT scans. For clinical validation, 214 patients with various malignancies were included. A radiologist (15+ years experience in interpretation of abdominal images) evaluated two sets: precontrast CT only and precontrast CT supplemented with synthetic contrast images. A second radiologist independently re-read the cohort to assess inter-observer agreement. Diagnostic performance, including sensitivity, specificity, and area under the ROC curve (AUC), was compared. Decision curve analysis (DCA) was performed to assess clinical utility. Results The addition of synthetic contrast images significantly increased sensitivity from 45.2% to 67.7% (p = 0.0391). The AUC also significantly improved from 0.718 to 0.817 (p = 0.0282). Specificity remained high at 95.6%. Qualitative assessment showed 79.4% of cases were of diagnostically acceptable quality (score 3 or 4). Inter-observer agreement was substantial to almost perfect and improved with the addition of synthetic contrast (Cohen’s κ, 0.69 to 0.84). The incremental diagnostic benefit was reproduced by an independent second reader. DCA demonstrated greater net benefit for the supplemented set across all relevant threshold probabilities. Conclusions Adding DL-based synthetic contrast images to precontrast CT was associated with improved sensitivity and diagnostic discrimination in this single-center retrospective cohort. This approach may have potential as an adjunct for assessing treatment response in oncology patients for whom iodinated contrast administration is limited or contraindicated, although external validation is required.
Accurate prediction of the temperature field in breast tissue is central to thermal diagnostics and to hyperthermia treatment planning. This study develops a two-dimensional transient bioheat model based on the Chen-Holmes equation which, unlike the classical Pennes formulation, accounts for the directional transport of heat by blood flow. The governing equation is solved using an implicit finite volume method (FVM) on a rectangular tissue domain with isothermal conditions on the left and bottom boundaries, a zero-flux condition on the right boundary, and a convective condition at the skin surface ( y = H ). A uniform velocity field with horizontal dominance ( u > v ) is introduced to represent the predominantly lateral convective transport between the chest wall and the nipple. Three blood-perfusion laws, constant, linear and non-linear, are examined to capture the temperature-dependent vascular response. To the authors’ knowledge, this particular combination of a horizontally dominant convective field, temperature-dependent perfusion laws and a convective skin boundary has not previously been examined together for breast tissue. The solver is verified by a grid-convergence study and benchmarked against published numerical results, showing close agreement throughout the transient and steady states, with tissue temperatures confined to the physiological 30 to 40 °C range; no experimental or clinical validation is undertaken. The results show that higher tissue and blood thermal conductivities, together with the horizontal-dominant velocity, produce faster and more uniform heat dispersion along the x -axis; raising the convective coefficient markedly increases surface cooling; and the non-linear perfusion model delivers the strongest temperature-dependent feedback, suppressing overheating in high-temperature regions while the constant model yields the most uniform but least adaptive field. Together these features offer a physically motivated description of heat transfer in perfused breast tissue and provide a basis for further work on thermal-therapy and diagnostic applications.
Objective To investigate the individual and joint associations of methylmalonic acid (MMA) and the albumin/neutrophil-to-lymphocyte ratio (ANLR) with self-reported diabetic retinopathy (DR), and to explore the potential involvement of ANLR in the association between MMA and DR. Methods Based on NHANES 2011-2014 cross-sectional data, weighted multiple logistic regression and restricted cubic splines (RCS) were performed to assess the associations of MMA and ANLR with DR. Joint analysis was used to evaluate the association of MMA combined with ANLR with DR, while exploratory mediation analysis was used to examine the statistical role of ANLR in the association between MMA and DR. Sensitivity analyses were performed by additionally adjusting for vitamin B12, glycated hemoglobin(HbA1c), and insulin or other glucose-lowering medication use. Results This study included 1,029 participants, of whom 205 (19.9%) reported physician-diagnosed DR. The analysis showed a positive association between log(MMA) and the odds of DR (OR=1.542, 95% CI: 1.004-2.369). A significant negative association was observed for log (ANLR) (OR=0.563, 95% CI: 0.355-0.894). RCS analysis suggested a positive association between log (MMA) and the odds of DR (P-nonlinear = 0.758) and a negative association between log (ANLR) and the odds of DR (P-nonlinear = 0.295). High MMA and low ANLR (MMA ≥250 nmol/L and log[ANLR] ≤ median) were associated with higher odds of DR (fully adjusted OR=2.233, 95% CI: 1.303–3.824). In the exploratory mediation analysis, ANLR accounted for 29.7% of the observed association between MMA and DR (P=0.028). The associations remained significant in sensitivity analyses with additional adjustment for serum vitamin B12, HbA1c, and insulin or other glucose-lowering medication use. Conclusions Elevated MMA was associated with greater odds of self-reported DR, while exploratory mediation analysis suggested that ANLR statistically accounted for part of this association. Joint consideration of MMA and ANLR may provide complementary information regarding self-reported DR.
