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Cigarette smoke (CS) is the most common cause of chronic obstructive pulmonary diseases (COPD), including emphysema. CS exposure impacts all cell types within the airways and lung parenchyma, causing alveolar tissue destruction through four mechanisms: (1) oxidative stress; (2) inflammation; (3) proteaseinduced degradation of the extracellular matrix; and (4) enhanced alveolar epithelial and endothelial cell (EC) apoptosis. Studies in human pulmonary ECs demonstrate that macrophage migration inhibitory factor (MIF) antagonizes CS-induced apoptosis. Here, we used human microvascular ECs, an animal model of emphysema (mice challenged with chronic CS), and patient serum samples to address both the capacity of CS to alter MIF expression and the effects of MIF on disease severity. We demonstrate significantly reduced serum MIF levels in patients with COPD. In the murine model, chronic CS exposure resulted in decreased MIF mRNA and protein expression in the intact lung. MIF deficiency (Mif 2/2 ) potentiated the toxicity of CS exposure in vivo via increased apoptosis of ECs, resulting in enhanced CS-induced tissue remodeling. This was linked to MIF's capacity to protect against double-stranded DNA damage and suppress p53 expression. Taken together, MIF appears to antagonize CS-induced toxicity in the lung and resultant emphysematous tissue remodeling by suppressing EC DNA damage and controlling p53-mediated apoptosis, highlighting a critical role of MIF in EC homeostasis within the lung.

Apoptosis is a key pathologic feature in acute lung injury. Animal studies have demonstrated that pathways regulating apoptosis are necessary in the development of acute lung injury, and that activation of p38 mitogen-activated protein kinase (MAPK) is linked to the initiation of the apoptotic cascade. In this study, we assessed the role of the MAPK-activated protein kinase (MK) 2, one of p38 MAPK's immediate downstream effectors, in the development of apoptosis in an animal model of LPS-induced pulmonary vascular permeability. Our results indicate that wild-type (WT) mice exposed to LPS demonstrate increased apoptosis, as evidenced by cleavage of caspase 3 and poly (ADP-ribose) polymerase 1 and increased deoxynucleotidyl transferase-mediated dUDP nick-end labeling staining, which is accompanied by increases in markers of vascular permeability. In contrast, MK2 2/2 mice are protected from pulmonary vascular permeability and apoptosis in response to LPS. Although there was no difference in activation of caspase 3 in MK2 2/2 compared with WT mice, interestingly, cleaved caspase 3 translocated to the nucleus in WT mice while it remained in the cytosol of MK2 2/2 mice in response to LPS. In separate experiments, LPS-induced apoptosis in human lung microvascular endothelial cells was also associated with nuclear translocation of cleaved caspase 3 and apoptosis, which were both prevented by MK2 silencing. In conclusion, our data suggest that MK2 plays a critical role in the development of apoptosis and pulmonary vascular permeability, and its effects on apoptosis are in part related to its ability to regulate nuclear translocation of cleaved caspase 3.

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Individual tree crown (ITC) segmentation is an approach to isolate individual tree from the background vegetation and delineate precisely the crown boundaries for forest management and inventory purposes. ITC detection and delineation have been commonly generated from canopy height model (CHM) derived from light detection and ranging (LiDAR) data. Existing ITC segmentation methods, however, are limited in their efficiency for characterizing closed canopies, especially in tropical forests, due to the overlapping structure and irregular shape of tree crowns. Furthermore, the potential of 3-dimensional (3D) LiDAR data is not fully realized by existing CHM-based methods. Thus, the aim of this study was to develop an efficient framework for ITC segmentation in tropical forests using LiDAR-derived CHM and 3D point cloud data in order to accurately estimate tree attributes such as the tree height, mean crown width and aboveground biomass (AGB). The proposed framework entails five major steps: (1) automatically identifying dominant tree crowns by implementing semi-variogram statistics and morphological analysis; (2) generating initial tree segments using a watershed algorithm based on mathematical morphology; (3) identifying “problematic” segments based on predetermined set of rules; (4) tuning the problematic segments using a modified distance-based algorithm (DBA); and (5) segmenting and counting the number of individual trees based on the 3D LiDAR point clouds within each of the identified segment. This approach was developed in a way such that the 3D LiDAR points were only examined on problematic segments identified for further evaluations. 209 reference trees with diameter at breast height (DBH) ≥ 10 cm were selected in the field in two study areas in order to validate ITC detection and delineation results of the proposed framework. We computed tree crown metrics (e.g., maximum crown height and mean crown width) to estimate aboveground biomass (AGB) at tree level using previously published allometric equations. Accuracy assessment was performed to calculate percentage of correctly detected trees, omission and commission errors. Our method correctly identified individual tree crowns with detection accuracy exceeding 80 percent at both forest sites. Also, our results showed high agreement (R2 > 0.64) in terms of AGB estimates using 3D LiDAR metrics and variables measured in the field, for both sites. The findings from our study demonstrate the efficacy of the proposed framework in delineating tree crowns, even in high canopy density areas such as tropical rainforests, where, usually the traditional algorithms are limited in their performances. Moreover, the high tree delineation accuracy in the two study areas emphasizes the potential robustness and transferability of our approach to other densely forested areas across the globe.

Background: Cytochromes P450 (CYPs) constitute an enzyme family involved in the oxidative metabolism of a wide variety of endogenous and exogenous compounds, including anti-cancer drugs and carcinogens. Unlike other human CYPs, CYP4Z1 is highly expressed in human breast carcinoma and is associated with poor prognosis. As a result, CYP4Z1 was hypothesised to be a potential biomarker or drug target for the discovery and development of promising anti-cancer therapies. Materials and methods: CYP4Z1 expression was immunohistochemically studied in a set of 100 different human tissues, including normal, benign, malignant and metastatic tissues, which originated from 27 anatomical sites. As a tumour model for CYP4Z1 expression, a panel of different breast cancers was evaluated for CYP4Z1 expression and its relation to histopathological features and prognostic immunohistochemical markers. Results: The immunohistochemical results revealed that CYP4Z1 was expressed in only one (4.3%) of the normal tissues from the mammary glands, while the expression of the enzyme was positive in 1 (11%), 12 (19%) and 2 (40%) of the benign, malignant and metastatic tissues, respectively. Interestingly, several tumour entities showed prominent expressions of CYP4Z1, including carcinomas of adrenal cortex, squamous cells of oesophagus, lung and cervix, as well as seminoma, astrocytoma, melanoma and lastly endometrial adenocarcinoma. In breast cancers, CYP4Z1 was expressed in 82% of the cases. Its expression was significantly associated with the pathology of tumour, histological grade and status of lymph node metastasis. Importantly, it was also significantly associated with the expressions of Her2, P53 and Ki-67. Conclusion: These findings greatly support future plans for the use of CYP4Z1 as a biomarker or target for anti-cancer drugs. However, large-scale validation studies are needed to better delineate the potential use of CYP4Z1 for therapeutic purposes.