OpusJournal

Online ISSN:
2831-090X

ISSN:
2831-0896

Volume 23 , Issue 2, (2023)

Published:
11.07.2023.

Open Access

Vol.23 No.2

Published: 11.07.2023.

Authors in this issue:

Abdella M Habib, Abdul-Badi Abou-Samra, Aleksandra Aracki Trenkić, Angela Pia Cazzolla, Atalla Hammouda, Benjie Xu, Boris Zec, Cheng Rao, Chenwei Li, Chunyue Feng, Dan Li, Dejan Nesic, Domenico Ciavarella, Dominik Vilímek, Dragan Stojanov, Eleonora Lo Muzio, Elina Beleva, Fang Li, Fei Liu, Feng Wang, Francesca Di Serio, Francesca Spirito, Gaofei Cao, Gordana Petrovic, Haibo Lu, Hao Jiang, Haowen Pang, Hongbing Ma, Hua Yang, Ivanka Nenova, Jan Malůš, Jaroslav Uchytil, Jianguang Shi, Jiayue Shao, Jie Gong, Jie Lian, Jieqiu Zhang, Jieyun Huang, Jin Li, Jun Wang, Justin Clark, Kai Sun, Lichun Wei, Lina Zhao, Ling-Yu Long, Lishuang Wang, Liu Shi, Lorenzo Lo Muzio, Lucia Varraso, Luigi Santacroce, Luka Nikolic, Marek Bužga, Maria Pepe, Mario Dioguardi, Matej Pekař, Mei Shi, Mengyao Zhang, Michele Di Cosola, Milica Radovanović, Milica Živanović, Miroslav Mišić, Mohan Dong, Moustapha Hamdi, Nan Xu, Omran A H Musa, Pavol Holéczy, Petr Kutáč, Qian Jiang, Qian Zhang, Qiong Qing, Quan-Bing Zhang, Ren Wang, Renato Contino, Roberto Lovero, Rui Zhang, Run Zhang, Saif Badran, Sanja Ninic, Sara Alharami, Sasa Popovic, Semir Vranic, Sergej Prijic, Shigao Huang, Shuli Tang, Siqi Liu, Snezana Ristic, Snezhana Stoencheva, Srdjan Pasic, Stasa Krasic, Suhail A Doi, Tanya Deneva, Veronika Horká, Vito Crincoli, Vladislav Vukomanovic, Vuk Milošević, Vukota Radovanović, Weijie Wu, Weiwei Li, Wen-Min Chen, Wudong Wang, Xiangyi Pang, Xiao-Jun Huang, Xiaopeng Yao, Xiaoxiao Liu, Xin Wang, Xinjian Li, Xu Wang, Xuejing Zhong, Ya-Zhen Qin, Yanhui Chen, Ying Zhang, Yingying Jin, Yongrong Zhang, Yuchen Wang, Yun Zhou, Zdeněk Švagera, Zhanet Grudeva-Popova, Zhenjing Jin, Zishan Wang,

Edited by:

Muzafer Mujic & Semir Vranic

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Editor’s choice articles

The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Artificial intelligence in renal pathology: Current status and future

Renal biopsy pathology is an essential gold standard for the diagnosis of most kidney diseases. With the increase in the incidence rate of kidney diseases, the lack of renal pathologists, and an imbalance in their distribution, there is an urgent need for a new renal pathological diagnosis model. Advances in artificial intelligence (AI) along with the growing digitization of pathology slides for diagnosis are promising approach to meet the demand for more accurate detection, classification, and prediction of the outcome of renal pathology. AI has contributed substantially to a variety of clinical applications, including renal pathology. Deep learning, a subfield of AI that is highly flexible and supports automatic feature extraction, is increasingly being used in multiple areas of pathology. In this narrative review, we first provide a general description of AI methods, and then discuss the current and prospective applications of AI in the field of renal pathology. Both diagnostic and predictive prognostic applications are covered, emphasizing AI in renal pathology images, predictive models, and 3D in renal pathology. Finally, we outline the challenges associated with the implementation of AI platforms in renal pathology and provide our perspective on how these platforms might change in this field.

Chunyue Feng, Fei Liu

16.03.2023.

Research article

Deletion of sphingosine kinase 2 attenuates cigarette smoke-mediated chronic obstructive pulmonary disease-like symptoms by reducing lung inflammation

Cigarette smoke (CS) is the leading cause of chronic obstructive pulmonary disease (COPD), which is characterized by chronic bronchial inflammation and emphysema. Growing evidence supports the hypothesis that dysfunctional cystic fibrosis transmembrane conductance regulator (CFTR) is critically involved in the pathogenesis of CS-mediated COPD. However, the underlying mechanism remains unclear. Here, we report that supressed CFTR expression is strongly associated with abnormal phospholipid metabolism and increased pulmonary inflammation. In a CS-exposed mouse model with COPD-like symptoms, we found that pulmonary expression of sphingosine kinase 2 (SphK2) and sphingosine-1-phosphate (S1P) secretion were significantly upregulated. Therefore, we constructed a SphK2 gene knockout (SphK2−/−) mouse. After CS exposure for six months, histological lung section staining showed disorganized alveolar structure, increased pulmonary fibrosis, and emphysema-like symptoms in wild-type (WT) mice, which were less pronounced in SphK2−/− mice. Further, SphK2 deficiency also decreased CS-induced pulmonary inflammation, which was reflected by a remarkable reduction in pulmonary infiltration of CD45+CD11b+ neutrophils subpopulation and low levels of IL-6 and IL-33 in bronchial alveolar lavage fluid. However, treatment with S1P receptor agonist suppressed CFTR expression and increased Nf-κB-p65 expression and its nuclear translocation in CS-exposed SphK2−/− mice, which also aggravated small airways fibrosis and pulmonary inflammation. In contrast, inhibition of S1P signaling with the S1P receptor analogue FTY720 rescued CFTR expression, suppressed Nf-κB-p65 expression and nuclear translocation, and alleviated pulmonary fibrosis and inflammation after CS exposure. Our results demonstrate that SphK2-mediated S1P production plays a crucial role in the pathogenesis of CS-induced COPD-like disease by impairing CFTR activity and promoting pulmonary inflammation and fibrosis.

Yanhui Chen, Yongrong Zhang, Cheng Rao, Jieyun Huang, Qiong Qing

16.03.2023.

Research article

Effect of vascular endothelial growth factor rs35569394 in esophageal cancer and response to chemotherapy

The objective of this study was to investigate the possible association between the single-nucleotide polymorphism, rs35569394, of the vascular endothelial growth factor (VEGF) gene and the risk of esophageal cancer (EC) in the Han Chinese population. A total of 290 EC subjects and 322 ethnically matched unrelated healthy controls free from the esophageal disease were studied. Genomic DNA was isolated from peripheral blood by salting out. Genotyping of VEGF rs35569394 polymorphism was carried out through polymerase chain reaction followed by agarose gel electrophoresis. The results showed that the distribution of genotypes was significantly different across the gender groups (p ═ 0.032) and clinical stages of the esophageal cancer (p ═ 0.034). VEGF rs35569394 was associated with EC risk (p ═ 0.012, OR ═ 1.34). A gender analysis breakdown showed that rs35569394-D allele frequency was significantly higher in females than in the controls (p ═ 0.0004, OR ═ 1.81). Moreover, significant associations were also found in females under the dominant model (II vs. ID+DD: χ2 ═ 8.18, p ═ 0.003, OR ═ 2.12) and the recessive model (II+ID vs. DD: χ2 ═ 8.25, p ═ 0.004, OR ═ 2.39). In addition, we found that the genotype, rs35569394-DD, was associated with a complete response and partial response to chemotherapy when compared with rs35569394-II (χ2 ═ 4.67, p ═ 0.030, OR ═ 0.47). In conclusion, our case–control study showed that the VEGF rs35569394 was significantly associated with the clinical stages and the increased risk of EC in Han Chinese females. In addition, the genotype rs35569394-DD showed a better response to chemotherapy.

Zishan Wang, Chenwei Li, Xinjian Li, Jianguang Shi, Weijie Wu