Clinicopathological and Immunohistochemical Characterisation of Gastric Schwannomas in 29 Cases

Schwannomas are tumors arising from the nervous system that also occur infrequently in the gastrointestinal tract, most commonly in the stomach. This report characterizes 29 patients with benign or malignant gastric schwannomas. Surgical data and clinical follow-up information were available for 28 cases with a median postoperative duration of 57 months. Clinicopathological and immunohistochemical characteristics of benign and malignant schwannomas were analysed. Four cases (13.7%) were histologically diagnosed with malignant schwannoma. All tumors were positive for S-100 and CD56 proteins, displaying a diffuse staining pattern. Vimentin was expressed in 100% cases and all schwannomas were negative for smooth muscle actin, c-kit, and HMB-45. A significant difference was observed between the group of benign and malignant schwannomas as regards recurrences and metastasis after complete resection (P=0.015). The survival time of patients with benign schwannomas was longer than the malignant group (P=0.013), so gastric malignant schwannomas have a potential for recurrence and metastasis, with subsequently short survival. Complete resection with an attempt to remove all tumor tissue with negative margins is of paramount importance in the management of gastric schwannomas, particularly when they turn out to be malignant

Comparative analysis of the phenolic contents and antioxidant activities of different parts of two pomegranate (Punica granatum L.) Cultivars: ‘Tunisia’ and ‘Qingpi’

Pomegranate (Punica granatum L.), with its abundant phenolic substances and strong antioxidant activity, holds significant research and utilization potential across various organs. However, there have been few studies on the phenolic content and antioxidant activity of different parts of pomegranate, especially the placenta. This study investigated the phenolic content and antioxidant activity of fruits, flowers, and leaves of two pomegranate varieties, ‘Tunisia’ and ‘Qingpi’, throughout their growth and development. Results indicated significant variations in phenolic content among different organs, with petals exhibiting the highest total polyphenol content (TPC, 49.40 mg GAE/g FW) and total anthocyanin content (TMAC, 1938.54 nmol/g FW). Placenta contained the highest levels of total flavonoids (TFC, 173.58 mg RE/g FW) and punicalagin (109.30 mg/g FW). The peel had the highest content of total flavanols (TFAC, 19.42 mg CE/g FW). Over the course of pomegranate development, total polyphenols, total flavonoids, total flavanols, punicalagin, and antioxidant activity declined in different organs. Antioxidant activity followed the order: fruit > flower > leaf, with the placenta exhibiting the highest antioxidant activity among fruits. Antioxidant activity showed a significant positive correlation with total polyphenols (R2 = 0.77-1.00), total flavonoids (R2 = 0.71-0.99, except tegmens), and punicalagin (R2 = 0.71-1.00). This study provides a comparative analysis of the phenolic content and antioxidant activity in different organs of pomegranate, highlighting the placenta as the primary source of punicalagin. This study provides a theoretical basis for the development and utilization of pomegranate phenolic compounds

Urban cold-chain logistics demand predicting model based on improved neural network model

With the popularity of the Internet and mobile terminals, the development of e-commerce has become hotter. Therefore, e-commerce research starts to focus on the statistics and prediction of the cargo volume of logistics. This study briefly introduced the back-propagation (BP) neural network model and principal component analysis (PCA) method and combined them to obtain an improved PCA-BP neural network model. Then the traditional BP neural network model and the improved PCA-BP neural network model were used to perform the empirical analysis of the cold chain logistics demand of fruits and vegetables in city A from 2010 to 2018. The results showed that the main factors that affected the local cold chain logistics demand were the growth rate of GDP, the added value of primary industry, the planting area of fruits and vegetables, and the consumption price index of fruits and vegetables; both kinds of neural networks model could effectively predict the cold chain logistics demand, but the predicted value of the PCA-BP neural network model was more fitted with the actual value. The prediction error of the BP neural network model was larger, and the fluctuation was obvious within the prediction interval. Moreover, the time required for the prediction by the PCA-BP neural network model was less than that by the BP neural network model. In summary, the improved PCA-BP neural network model is faster and more accurate than the traditional BP model in predicting the cold chain logistics demand

Urban cold-chain logistics demand predicting model based on improved neural network model

With the popularity of the Internet and mobile terminals, the development of e-commerce has become hotter. Therefore, e-commerce research starts to focus on the statistics and prediction of the cargo volume of logistics. This study briefly introduced the back-propagation (BP) neural network model and principal component analysis (PCA) method and combined them to obtain an improved PCA-BP neural network model. Then the traditional BP neural network model and the improved PCA-BP neural network model were used to perform the empirical analysis of the cold chain logistics demand of fruits and vegetables in city A from 2010 to 2018. The results showed that the main factors that affected the local cold chain logistics demand were the growth rate of GDP, the added value of primary industry, the planting area of fruits and vegetables, and the consumption price index of fruits and vegetables; both kinds of neural networks model could effectively predict the cold chain logistics demand, but the predicted value of the PCA-BP neural network model was more fitted with the actual value. The prediction error of the BP neural network model was larger, and the fluctuation was obvious within the prediction interval. Moreover, the time required for the prediction by the PCA-BP neural network model was less than that by the BP neural network model. In summary, the improved PCA-BP neural network model is faster and more accurate than the traditional BP model in predicting the cold chain logistics demand

Correction: The influence of in-groups and out-groups on the theory-of-mind processing: evidence from different ethnic college students

According to previous studies of theory of mind (ToM), social environment and cultural background affect individuals’ cognitive ability to understand other people’s minds. There are cross-group differences in ToM. The present study aimed to examine whether social environment and culture affect the ToM in Uygur and Han groups and whether the individual’s cognitive ToM and affective ToM show in-group advantages. Han and Uygur college students were recruited as participants. The “self/other differentiation task” was used to measure cognitive ToM (Study 1), and the “Yoni task” was used to measure both cognitive and affective ToM (Study 2). We found that Han participants processed the cognitive and affective states of others faster and more accurately than Uygur ones. Uygur and Han participants processed in-group members’ cognitive and affective states faster and more accurately. Furthermore, Uygur participants were more accurate in the cognitive ToM processing of in-group members, while Han participants were faster in the affective ToM processing of in-group members. The findings indicated that ethnic culture and group identify might influence ToM processing. Strengthening exchanges between ethnic groups may enable individuals to better process out-group members’ psychological states

<i>Clostridioides difficile</i> Infection in Kidney Transplant Recipients

Clostridioides difficile (C. difficile) is a bacterial organism that typically infects the colon, which has had its homeostasis of healthy gut microbiota disrupted by antibiotics or other interventions. Patients with kidney transplantation are a group that are susceptible to C. difficile infection (CDI) and have poorer outcomes with CDI given that they conventionally require long-term immunosuppression to minimize their risk of graft rejection, weakening their responses to infection. Recognizing the risk factors and complex pathophysiological processes that exist between immunosuppression, dysbiosis, and CDI is important when making crucial clinical decisions surrounding the management of this vulnerable patient cohort. Despite the clinical importance of this topic, there are few studies that have evaluated CDI in the context of kidney transplant recipients and other solid organ transplant populations. The current recommendations on CDI management in kidney transplant and solid organ transplant recipients are mostly extrapolated from data relating to CDI management in the general population. We provide a narrative review that discusses the available evidence examining CDI in solid organ transplant recipients, with a particular focus on the kidney transplant recipient, from the epidemiology of CDI, clinical features and implications of CDI, potential risk factors of CDI, and, ultimately, prevention and management strategies for CDI, with the aim of providing areas for future research development in this topic area

Mother phubbing and harsh mothering: Mothers' irritability and adolescents' gender as moderators

Background: While extant evidence supports the link between mother phubbing (Mphubbing) and harsh mothering, the current understanding of factors that may affect this relationship is limited. Methods: Hierarchical regression analyses were conducted to examine the relation between Mphubbing and harsh mothering, as well as to explore whether mothers' irritability and adolescents' gender would moderate this relationship. The participants included 482 middle school students (51.7 % girls) and their mothers from China. Results: The results revealed a significant positive association between Mphubbing as reported by adolescents and their perception of harsh mothering. However, the predictive power of Mphubbing for harsh mothering varied based on mothers' irritability and adolescents' gender. Specifically, the association between Mphubbing and harsh mothering was perceived more strongly in girls than in boys, but this gender difference was only observed among adolescents whose mothers rated themselves as high in irritability. Conclusions: The current study offers a preliminary understanding of the association between Mphubbing and harsh mothering through mothers' irritability and adolescents' gender as moderators, which has certain theoretical and practical implications for comprehending harsh mothering in the digital age

Study on the selenium accumulation of peach seedlings

An experiment was conducted to study the effect of peach seedlings (Prunus davidiana) grown in nutrient solution with different selenium concentration. The results showed that selenium concentration were 0.05 and 0.10 mg/L which caused a marked increase of roots and shoorts biomass, and the root/shoot ratio were relatively low (0.180 and 0.170) compared with control, and other selenium treatments decreased significantly the biomass. Consequently, 0.05 and 0.10 mg/L selenium treatments were conducive to peach seedlings growth, while the peach seedlings was inhibited significantly by the increasing concentration of selenium (≥ 0.10 mg/L). Selenium content of peach seedlings increased remarkably with the increase of selenium concentration that indicated the accumulation of selenium in peach seedlings had a linear relation with the dose of selenium. Above all, when selenium concentration in the range of 0-0.10 mg/ L, which not only promotes peach seedlings growth, but also increases peach seedlings selenium content