High-Temperature Phase Transition Containing Switchable Dielectric Behavior, Long Fluorescence Lifetime, and Distinct Photoluminescence Changes in a 2D Hybrid CuBr4 Perovskite.

A novel organic-inorganic hybrid perovskite crystal, [ClC6H4(CH2)2NH3]2CuBr4 (1), having experienced an invertible high-temperature phase transition near Tc (the Curie temperature Tc = 355 K), has been successfully synthesized. The phase-transition characteristics for compound 1 are thoroughly revealed by specific heat capacity (Cp), differential thermal analysis, and differential scanning calorimetry tests, possessing 16 K broad thermal hysteresis. Multiple-temperature powder X-ray diffraction analysis further proves the phase-transition behavior of compound 1. Moreover, compound 1 exhibits a significant steplike dielectric response near Tc, revealing that it can be deemed to be a promising dielectric switching material. The variable-temperature fluorescence experiments show distinct photoluminescence (PL) changes of compound 1. Further investigation and calculation disclose that the fluorescence lifetime of compound 1 can reach as long as 55.46 µs, indicating that it can be a potential PL material. All of these researches contribute a substitutable avenue in the design and construction of neoteric phase-transition compounds combining high Curie temperature and PL properties.

[Variation Characteristics and Source Analysis of Carbonaceous Aerosols in Winter in Jiashan].

Organic carbon (OC), elemental carbon (EC), and PM2.5 concentration data obtained from Shanxi Super Station in Jiashan County of Jiaxing City, in the winter of 2018 and 2019, were analyzed to determine the variation and potential source areas of carbonaceous aerosols. The results show that OC concentrations in the winter of 2018 and 2019 were 6.90 µg·m-3 and 5.63 µg·m-3, respectively, while EC concentrations were 2.47 µg·m-3 and 1.57 µg·m-3, respectively. The concentrations of OC and EC in the winter of 2019 were lower than those in the winter of 2018, by approximately 18.4% and 36.4%, respectively. In 2018 and 2019, the concentrations of secondary organic carbon (SOC), calculated using the minimum R-squared (MRS) method, were 1.49 µg·m-3 and 1.97 µg·m-3, respectively, and the concentrations of primary organic carbon (POC) were 5.41 µg·m-3 and 3.66 µg·m-3, respectively. The proportion of POC in OC showed a downward trend, from 96.0% in December 2018 to 64.9% in February 2020, indicating a decrease of 31.1 percentage points. SOC showed an upward trend, increasing by 31.1 percentage points from 4.0% in December 2018 to 35.1% in February 2020. It is worth noting that with the increase in PM2.5 concentration, the concentration of OC and EC increased by 474.7% and 408.2%, respectively, although the proportion of OC in PM2.5 decreased from 18.8% to 12.3%. and the percentage of OC decreased from 5.8% to 3.3%. The contribution of POC to PM2.5 did not fluctuate, and only decreased significantly above 150 µg·m-3, while the contribution of SOC to PM2.5 first decreased and then increased. In Jiaxing, the potential sources of OC and EC were mainly southern Jiangsu, southeastern Anhui, local Jiaxing, and northern Zhejiang. In the winter of the contribution concentrations of OC and EC in the main potential source regions were approximately 2 µg·m-3 and 6 µg·m-3 lower, respectively, than in winter 2018. The range of high values in the potential source regions also decreased in 2019. Before the COVID-19 epidemic, it was affected by both motor vehicle exhaust emissions and coal burning. During the Spring Festival and home isolation, due to traffic control and other reasons, motor vehicle emissions were reduced, which leaving coal burning as the main contributor.

Endoscopic resection of the pancreatic tail and subsequent wound healing mechanisms in a porcine model.

BACKGROUND: Laparoscopic resection of the pancreatic body and tail is the predominant methodology to remove lesions in these locations; its safety and surgical planning are relatively mature, but it remains a complex and high-precision surgical operation, requiring abundant experience and skills in laparoscopic surgery, with a 10% rate of complications. AIM: To verify the feasibility and safety, as well as to examine the complications of endoscopic pancreatectomy and healing mechanisms of pancreatic wounds after endoscopic resection. METHODS: Transgastric endoscopic resections of varying sizes of pancreases were performed in 15 healthy Bama miniature pigs. The technical success rate, the incidence of serious complications, and the survival of the animals were studied. The healing of the wounds was evaluated by sacrificing the animals at various time points. Finally, the expression of transforming growth factor-ß1 and Smad3/Smad7 in the surgical site was examined by immunohistochemistry to explore the role of these factors in wound healing of the pancreas. RESULTS: Partial and total resections were successfully performed in two groups of animals, respectively. The technical success rate and the survival rate of the pigs were both 100%. We obtained 12 pancreatic tissue samples by endoscopic resection. The pancreatic wounds were closed with metal clips in one group and the wounds healed well by forming scars. There was a small amount of pancreatic leakage in the other group, but it can be fully encapsulated. The level of transforming growth factor-ß1 (TGF-ß1) in the wounds increased during the inflammatory and fibrous hyperplasia phases, and decreased in the scar phase. The expression of Smad3 paralleled that of TGF-ß1, while the expression of Smad7 had an inverse relationship with the expression of TGF-ß1. CONCLUSION: Purely transgastric endoscopic resection of the pancreas is a safe, effective, and feasible procedure, but the incidence of pancreatic leakage in total pancreatic tail resection is high. The expression of TGF-ß1 and Smad3/Samd7 is related to the progression of pancreatic wound healing.

[Value of auto-fluorescence spectrum combined with tumor markers in diagnosis of lung cancer].

To improve the diagnostic efficiency of cancer, serum fluorescence spectrum combined with tumor marker groups was proved more powerful, especially when used with mathematical evaluation model, that is, artificial neural network (ANN) modeling. ANN modeling is very suitable for the discrimination of lung cancer. ANN has evident superiority in solving nonlinear, multi-parameter and uncertain complicated problems. In the present paper, serum fluorescence spectrum was applied to study the difference among normal, benign and malignant groups and develop the relevant method of determination. On the other hand, combined with tumor markers, CEA, NSE, SCC-Ag, CYFRA21-1 and p16 methylation, artificial neural network and Fisher linear discriminatory analysis were used to develop the prediction models of diagnosis of lung cancer, and compared by ROC. It was shown that the result of the fluorescence spectrum combined with tumor markers based on ANN model is superior to that of the fluorescence spectrum ANN model. The performance of ANN model is superior to that of Fisher linear discriminatory analysis.