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Systemic amyloidosis involves the deposition of misfolded proteins in organs/tissues, leading to progressive organ dysfunction and failure. Congo red is the gold-standard chemical stain for visualizing amyloid deposits in tissue, showing birefringence under polarization microscopy. However, Congo red staining is tedious and costly to perform, and prone to false diagnoses due to variations in amyloid amount, staining quality and manual examination of tissue under a polarization microscope. We report virtual birefringence imaging and virtual Congo red staining of label-free human tissue to show that a single neural network can transform autofluorescence images of label-free tissue into brightfield and polarized microscopy images, matching their histochemically stained versions. Blind testing with quantitative metrics and pathologist evaluations on cardiac tissue showed that our virtually stained polarization and brightfield images highlight amyloid patterns in a consistent manner, mitigating challenges due to variations in chemical staining quality and manual imaging processes in the clinical workflow. Detecting amyloid deposits in tissue with Congo red can be limited by several factors, which can potentially lead to false diagnoses. Here, the authors use virtual birefringence imaging and virtual Congo red staining using autofluorescence of label-free human tissue, highlighting amyloid deposits in a consistent manner. [ABSTRACT FROM AUTHOR]

Phase imaging is widely used in biomedical imaging, sensing, and material characterization, among other fields. However, direct imaging of phase objects with subwavelength resolution remains a challenge. Here, we demonstrate subwavelength imaging of phase and amplitude objects based on all-optical diffractive encoding and decoding. To resolve subwavelength features of an object, the diffractive imager uses a thin, high-index solid-immersion layer to transmit high-frequency information of the object to a spatially-optimized diffractive encoder, which converts/encodes high-frequency information of the input into low-frequency spatial modes for transmission through air. The subsequent diffractive decoder layers (in air) are jointly designed with the encoder using deep-learning-based optimization, and communicate with the encoder layer to create magnified images of input objects at its output, revealing subwavelength features that would otherwise be washed away due to diffraction limit. We demonstrate that this all-optical collaboration between a diffractive solid-immersion encoder and the following decoder layers in air can resolve subwavelength phase and amplitude features of input objects in a highly compact design. To experimentally demonstrate its proof-of-concept, we used terahertz radiation and developed a fabrication method for creating monolithic multi-layer diffractive processors. Through these monolithically fabricated diffractive encoder-decoder pairs, we demonstrated phase-to-intensity (P → I) transformations and all-optically reconstructed subwavelength phase features of input objects (with linewidths of ~ λ/3.4, where λ is the illumination wavelength) by directly transforming them into magnified intensity features at the output. This solid-immersion-based diffractive imager, with its compact and cost-effective design, can find wide-ranging applications in bioimaging, endoscopy, sensing and materials characterization. [ABSTRACT FROM AUTHOR]

Objective: To construct a scoring model based on MRI signs to predict massive hemorrhage during dilatation and curettage in cesarean scar pregnancy (CSP) patients. Materials and methods: The MRIs of CSP patients admitted to a tertiary referral hospital between February 2020 and July 2022 were retrospectively reviewed. The included patients were randomly assigned to the training and validation cohorts. The univariate and multivariate logistic regression analyses were adopted to identify the independent risk factors for massive hemorrhage (the amount of bleeding ≥ 200 ml) during the dilatation and curettage. A scoring model predicting intraoperative massive hemorrhage was established where each positive independent risk factor was assigned 1 point, and the predictive power of this model was evaluated both in the training and validation cohorts via the receiver operating characteristic curve. Results: A total of 187 CSP patients were enrolled, who were divided into the training cohort (31 in 131 patients had massive hemorrhage) and validation cohort (10 in 56 patients had massive hemorrhage). The independent risk factors for intraoperative massive hemorrhage included cesarean section diverticulum area (OR = 6.957, 95% CI 1.993–21.887; P = 0.001), uterine scar thickness (OR = 5.113, 95% CI 2.086–23.829; P = 0.025) and gestational sac diameter (OR = 3.853, 95% CI 1.103–13.530; P = 0.025). A scoring model with a total point of 3 was developed and the CSP patients were divided into low-risk (Total points < 2) and high-risk groups (Total points ≥ 2) for intraoperative massive hemorrhage accordingly. This model possessed high prediction performance both in the training cohort (area under the curve [AUC] = 0.896, 95% CI 0.830–0.942) and validation cohort (AUC = 0.915, 95% CI 0.785–1.000). Conclusion: We first constructed a MRI-based scoring model for predicting intraoperative massive hemorrhage in CSP patients, which could help the decision-making of the patients' therapy strategies. Low-risk patients can be cured by D&C alone to reduce the financial burden, while high-risk patients require more adequate preoperative preparation or consideration of changing surgical approaches to reduce bleeding risk. [ABSTRACT FROM AUTHOR]

Background: Obesity and metabolic syndrome (MetS) appear in clusters and are both associated with an increased risk of cancer. However, it remains unknown whether obesity status with or without MetS increases the risk of site-specific cancers.Methods: We used data derived from 390,575 individuals (37-73 years old) from the UK Biobank who were enrolled from 2006-2016 with a median of 7.8 years of follow-up. Obesity was defined by BMI ≥ 30 kg/m2 and MetS was defined by the criteria of the Adult Treatment Panel-III (ATP-III). Cox proportional hazards models were used to investigate the associations of BMI and MetS with 22 cancers.Results: Metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) phenotypes represented 6.7% and 17.9% of the total analytic samples and 27.1% and 72.9% of the included subpopulation with obesity, respectively. Obesity was independently associated with higher risks of 10 of 22 cancers. Stratified by metabolic status, the MUO phenotype was consistently associated with 10 obesity-related cancers. In contrast, the MHO phenotype was only associated with increased risks of five cancers: endometrium, oesophagus, kidney, pancreas and postmenopausal breast cancers.Conclusion: Even in metabolically healthy individuals, obesity was associated with increased risks of five cancers, whereas we did not find that these individuals were associated with increased risks of several other obesity-related cancers. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: Accumulating evidence suggests an impact of gestational weight gain (GWG) on pregnancy outcomes; however, data on cardiometabolic risk factors later in life have not been comprehensively studied. This study aimed to evaluate the relationship between GWG and cardiometabolic risk in offspring aged 7 years.Methods: We included a total of 905 mother-child pairs who enrolled in the follow-up visit of the multicentre Hyperglycemia and Adverse Pregnancy Outcome study, at the Hong Kong Centre. Women were classified as having gained weight below, within or exceeding the 2009 Institute of Medicine (IOM) guidelines. A standardised GWG according to pre-pregnancy BMI categories was calculated to explore for any quadratic relationship.Results: Independent of pre-pregnancy BMI, gestational hyperglycaemia and other confounders, women who gained more weight than the IOM recommendations had offspring with a larger body size and increased odds of adiposity, hypertension and insulin resistance (range of p values of all the traits: 4.6 × 10−9 < p < 0.0390) than women who were within the recommended range of weight gain during pregnancy. Meanwhile, women who gained less weight than outlined in the recommendations had offspring with increased risks of hypertension and insulin resistance, compared with those who gained weight within the recommended range (7.9 × 10−3 < p < 0.0477). Quadratic relationships for diastolic blood pressure, AUC for insulin, pancreatic beta cell function and insulin sensitivity index were confirmed in the analysis of standardised GWG (1.4 × 10−3 < pquadratic < 0.0282). Further adjustment for current BMI noticeably attenuated the observed associations.Conclusions/interpretation: Both excessive and inadequate GWG have independent and significant impacts on childhood adiposity, hypertension and insulin resistance. Our findings support the notion that adverse intrauterine exposures are associated with persistent cardiometabolic risk in the offspring. [ABSTRACT FROM AUTHOR]

The article discusses the study on the determinants of poor glycemic control in Chinese men with type 2 diabetes. The study was conducted by professional organization Chinese Diabetes Association from March to June 2011. The results reportedly revealed that men below 40-years-old who are overweight or obese are at an increased risk of poor glycemic control.

This paper presents a feasible 3D collision avoidance approach for fixed-wing unmanned aerial vehicles (UAVs). The proposed strategy aims to achieve the desired relative bearing in the horizontal plane and relative elevation in the vertical plane so that the host aircraft is able to avoid collision with the intruder aircraft in 3D. The host aircraft will follow a desired trajectory in the collision avoidance course and resume the pre-arranged trajectory after collision is avoided. The approaching stopping condition is determined for the host aircraft to trigger an evasion maneuver to avoid collision in terms of measured heading. A switching controller is designed to achieve the spatial collision avoidance strategy. Simulation results demonstrate that the proposed approach can effectively avoid spatial collision, making it suitable for integration into flight control systems of UAVs. [ABSTRACT FROM AUTHOR]

This paper proposes a practical prediction procedure for vertical displacement of a Rotarywing Unmanned Aerial Vehicle (RUAV) landing deck in the presence of stochastic sea state disturbances. A proper time series model tending to capture characteristics of the dynamic relationship between an observer and a landing deck is constructed, with model orders determined by a novel principle based on Bayes Information Criterion (BIC) and coefficients identified using the Forgetting Factor Recursive Least Square (FFRLS) method. In addition, a fast-converging online multi-step predictor is developed, which can be implemented more rapidly than the Auto-Regressive (AR) predictor as it requires less memory allocations when updating coefficients. Simulation results demonstrate that the proposed prediction approach exhibits satisfactory prediction performance, making it suitable for integration into ship-helicopter approach and landing guidance systems in consideration of computational capacity of the flight computer. [ABSTRACT FROM AUTHOR]

This paper proposes a nonlinear $\mathcal{H}_{\infty}$ controller for stabilization of velocities, attitudes and angular rates of a fixed-wing unmanned aerial vehicle (UAV) in a windy environment. The suggested controller aims to achieve a steady-state flight condition in the presence of wind gusts such that the host UAV can be maneuvered to avoid collision with other UAVs during cruise flight with safety guarantees. This paper begins with building a proper model capturing flight aerodynamics of UAVs. Then a nonlinear controller is developed with gust attenuation and rapid response properties. Simulations are conducted for the Shadow UAV to verify performance of the proposed controller. Comparative studies with the proportional-integral-derivative (PID) controllers demonstrate that the proposed controller exhibits great performance improvement in a gusty environment, making it suitable for integration into the design of flight control systems for cruise flight of UAVs. [ABSTRACT FROM AUTHOR]

We have reported associations of cancer with low triglyceride and high high-density lipoprotein cholesterol (HDL-C) as well as co-presence of low low-density lipoprotein cholesterol (LDL-C) and albuminuria in type 2 diabetes (T2D). This analysis aims to test (1) whether low LDL-C and low triglyceride have synergistic effects to increase cancer risk in T2D and (2) whether high HDL-C enhances the effect of co-presence of low LDL-C and albuminuria on cancer risk. A prospective cohort of patients with T2D, established within the Prince of Wales Hospital, was used in the analysis. A total of 3,476 T2D patients in Hong Kong enrolled between 1996 and 2005, free of cancer at enrolment and not using statins or fibrates within 2.5 years before enrolment and during follow-up, were followed until 2005. The study measured additive interactions of low LDL-C with other factors for cancer using relative excess risk due to interaction (RERI) and attributable proportion due to interaction (AP). A statistically significant RERI > 0 or AP > 0 indicates additive interaction. During 5.11 years of follow-up, 199 patients developed cancer. Co-presence of triglyceride <1.70 mmol/L and LDL-C < 2.80 mmol/L was associated with increased cancer risk (multivariable hazard ratio [HR]:2.13, P = 0.0008) with significant interaction. Co-presence of HDL-C ≥ 1.30 mmol/L and LDL-C < 2.80 mmol/L plus albuminuria was also associated with increased cancer risk (HR: 3.84, P < 0.0001) with significant interaction. In T2D, low triglyceride may potentiate cancer risk associated with low LDL-C while high HDL-C enhances the synergistic effect of low LDL-C with albuminuria towards increased cancer risk. [ABSTRACT FROM AUTHOR]

Diabetes is a complex disease characterized by chronic hyperglycemia and multiple phenotypes. In 1995, we used a doctor-nurse-clerk team and structured protocol to establish the Hong Kong Diabetes Registry in a quality improvement program. By 2009, we had accrued 2616 clinical events in 9588 Chinese type 2 diabetic patients with a follow-up duration of 6 years. The detailed phenotypes at enrollment and follow-up medications have allowed us to develop a series of risk equations to predict multiple endpoints with high sensitivity and specificity. In this prospective database, we were able to validate findings from clinical trials in real practice, confirm close links between cardiovascular and renal disease, and demonstrate the emerging importance of cancer as a leading cause of death. In addition to serving as a tool for risk stratification and quality assurance, ongoing data analysis of the registry also reveals secular changes in disease patterns and identifies unmet needs. [ABSTRACT FROM AUTHOR]

We investigated the association of physical activity, TV watching time, sleeping time with the risks of obesity and hyperglycemia among 1263 offspring aged 1-5 years of mothers with gestational diabetes (GDM) in a cross-sectional study. Logistic regression models were used to obtain the odd ratios (ORs) (95% confidence intervals [CI]) of childhood obesity and hyperglycemia associated with different levels of indoor activity, outdoor activity, TV watching, and sleeping time. The multivariable-adjusted ORs of obesity based on different levels of TV watching time (0, <1.0, and ≥1.0 hour/day) were 1.00, 1.21 (95% CI 0.72-2.05), and 2.20 (95% CI 1.33-3.63) (Ptrend = 0.003), respectively. The multivariable-adjusted ORs of hyperglycemia based on different levels of indoor activity (<5.0, 5.0-6.9, and ≥7.0 hours/day) were 1.00, 0.74 (95% CI 0.45-1.21), and 0.49 (95% CI 0.28-0.84) (Ptrend = 0.034), respectively. The multivariable-adjusted ORs of hyperglycemia associated with different levels of sleeping time (<11.0, 11.0-11.9, and ≥12.0 hours/day) were 1.00, 0.67 (95% CI 0.42-1.05), and 0.39 (95% CI 0.23-0.67) (Ptrend = 0.003), respectively. The present study indicated a positive association of TV watching with the risk of obesity, and an inverse association of either indoor activity or sleeping time with the risk of hyperglycemia among offspring born to GDM mothers in Tianjin, China. [ABSTRACT FROM AUTHOR]

Serum uric acid (SUA) at high levels and bilirubin at low levels were potent antioxidant but it was uncertain that whether SUA and total bilirubin (TBIL) had additive interaction for the risk of CVD in type 2 diabetes mellitus (T2DM). We conducted a cross-sectional survey of 6713 inpatients with T2DM and admitted to 81 tertiary care hospitals. CVD was defined as having either prior coronary heart disease or stroke or peripheral arterial disease. Binary logistic regression was used to estimate odds ratios of SUA and TBIL for CVD. The effect size of additive interaction was estimated by three measures, i.e., relative excess risk due to interaction, attributable proportion due to interaction and synergy index. Among 6713 patients with T2DM, 561 (8.36%) suffered from CVD. Using ≥283 umol/L (median) to define high SUA and <11.5 umol/L (n = 2290 or 34.11%) to define low TBIL, copresence of both factors (n = 621 or 9.25%) was associated with 5.18-fold (95% CI, 4.00-6.72) risk of CVD with significant additive interactions in multivariable analysis as compared to absence of both risk factors. The copresence of both high SUA and low TBIL was associated with a large increased risk of CVD in high-risk Chinese patients with type 2 diabetes. [ABSTRACT FROM AUTHOR]