Introduction to Integrating Business Operations, Information Technologies, and Consumer Behavior Minitrack

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Transgenic mice over-expressing carbonic anhydrase I showed aggravated joint inflammation and tissue destruction

BACKGROUND: Studies have demonstrated that carbonic anhydrase I (CA1) stimulates calcium salt precipitation and cell calcification, which is an essential step in new bone formation. Our study had reported that CA1 encoding gene has a strong association with rheumatoid arthritis (RA) and ankylosing spondylitis (AS), two rheumatic diseases with abnormal new bone formation and bone resorption in joints. This study investigated the effect of CA1 on joint inflammation and tissue destruction in transgenic mice that over-express CA1 (CA1-Tg). METHODS: CA1-Tg was generated with C57BL/6J mice by conventional methods. CA1-Tg was treated with collagen-II to induce arthritis (CIA). Wild-type mice, CA1-Tg treated with bovine serum albumin (BSA) and transgenic mice over-expressing PADI4 (PADI4-Tg), a gene known to be involved in rheumatoid arthritis, were used as controls. Histochemistry and X-ray radiographic assay were used to examine joint destruction. Western blotting and real time-PCR were used to examine CA1 expression. RESULTS: CIA was observed in 60% of CA1-Tg, 20% of PADI4-Tg and 20% of wild-type mice after collagen injections. No CIA was found in CA1-Tg mice that received injections of BSA. The arthritic score was 5.5 ± 0.84 in the CA1-Tgs but the score was less than 2 in the injected wild-type mice and the PADI4-Tgs. The thickness of the hind paws in the CA1-Tgs was 3.46 ± 0.11 mm, which was thicker than that of PADI4-Tgs (2.23 ± 0.08 mm), wild-type mice (2.08 ± 0.06 mm) and BSA-treated CA1-Tgs (2.04 ± 0.07 mm). Histochemistry showed obvious inflammation, synovial hyperplasia and bone destruction in the joints of CA1-Tg that was not detected in PADI4-Tgs or wild-type mice. X-ray assays showed bone fusion in the paws and spines of CA1-Tg mice. CONCLUSION: Over-expression of CA1 may aggravate joint inflammation and tissue destruction in the transgenic mice

Progression of Electrocardiographic Abnormalities in Type 1 Diabetes During 16 Years of Follow‐up: The Epidemiology of Diabetes Interventions and Complications (EDIC) Study

Background The electrocardiogram (ECG) is an objective tool for cardiovascular disease (CVD) risk assessment. Methods and Results We evaluated distribution of ECG abnormalities and risk factors for developing new abnormalities in 1314 patients with type 1 diabetes (T1D) from the Epidemiology of Diabetes Interventions and Complications (EDIC) study. Annual ECGs were centrally read. ECG abnormalities were classified as major and minor according to the Minnesota ECG Classification. At EDIC year 1 (baseline), 356 (27.1%) of the participants had at least 1 ECG abnormality (major or minor) whereas 26 (2%) had at least one major abnormality. During 16 years of follow‐up, 1016 (77.3%) participants developed at least 1 new ECG abnormality (major or minor), whereas 172 (13.1%) developed at least 1 new major abnormality. Independent risk factors for developing new major ECG abnormalities were: age, current smoking, increased systolic blood pressure, and higher glycosylated hemoglobin (hazard ratio [HR] [95% CI]: 1.04 [1.02–1.06] per 1‐year increase, 1.75 [1.22–2.53], 1.03 [1.01–1.05] per 1 mm Hg increase, and 1.16 [1.04–1.29] per 10% increase, respectively). Independent risk factors for developing any new ECG abnormalities (major or minor) were age and systolic blood pressure (HR [95% CI]: 1.02 [1.01–1.03] per 1‐year increase and 1.01 [1.00–1.02] per 1 mm Hg increase, respectively). Conclusions New ECG abnormalities commonly occur in the course of T1D, consistent with the recognized increasing risk for CVD as patients age. Advanced age, increased systolic blood pressure, smoking, and higher HbA1c are independent risk factor for developing major ECG abnormalities, which underscores the importance of tight glucose control in T1D in addition to management of common CVD risk factors

Transferrable optimization of spray-coated PbI2 films for perovskite solar cell fabrication

Ultrasonic spray coating is a promising pathway to scaling-up of perovskite solar cell production that can be implemented on any scale - from table-top to mass production. However, unlike spin-coating, spray coating processes are not easily described by a set of machine-independent parameters. In this work, in situ measurement and modeling of wet film thickness and evaporation rate are presented as a machine-independent description of the ultrasonic spray coating process, and applied to fabrication process optimization for high-performing perovskite solar cells. Optimization based on physical wet film parameters instead of machine settings leads to better understanding of the key factors affecting film quality and enables process transfer to another fabrication environment. Spray coated PbI2 film morphology is analyzed under a range of coating conditions and strong correlation is observed between spray coating parameters and PbI2 film uniformity. Premature precipitation and sparse nucleation are suggested as causes of film non-uniformity, and optimal process parameters are identified. Device fabrication based on the optimized process is demonstrated under ambient conditions with a relative humidity of 50%, achieving a power conversion efficiency of 13% in 1 cm2 area devices, with negligible hysteresis

Optimisation for clamping force of aircraft composite structure assembly considering form defects and part deformations

Given the existence of manufacturing defects and the accumulation of assembly errors, non-compliant assembly appears between components, especially for composite structure assembly. In the engineering application, the clamping force (CF) is often used to eliminate the clearance between mating components, but the improper CF may result in unwanted structure failure. Thus, on the premise of ensuring the safety of composite parts, this study proposes a procedure to systematically optimise the assembly CF. Firstly, the components mating surfaces were obtained by laser scanner, and the matching of actual surfaces was transformed and simplified based on ‘equivalent surface’ concept. Then, a mathematical optimisation model was established. The CF layout and magnitude were taken as variables, and the clearance elimination rate and the overall assembly force value were employed as objective functions. Finally, the improved genetic algorithm (GA) was used to solve this problem. A parametric finite element analysis (FEA) model was built, and model accuracy was verified by physical experiments. The finite element calculation and post-processing were carried out by Python script in ABAQUS®. Compared to the engineer’s traditional approach, the influence of form defects and part deformations were considered, which can help control the assembly stress well and ensure product performance