is an indigenous plant which is frequently used as a spice in Avraman-Kurdistan region of Iran. The present study aimed to investigate the chemical composition, antimicrobial and antioxidant properties of the . In addition, rosmarinic acid and total phenolic content of was assessed by spectrophotometric method and HPTLC. The essential oil and methanolic extract were isolated by hydrodistillation and maceration methods, respectively. A total of 32 compounds representing 98.6% of the essential oil were identified by GC-MS and GC-FID. The main constituents were -pentacosane (23.8%), spathulenol (11.5%), β-bourbonen (11.3%) and-docosane (11.0%). The antibacterial activity of samples were carried out by disc diffusion method and evaluate the minimal inhibitory concentration (MIC) essential oil and methanolic extract were found to be effective against , and . The highest scavenging activity was found for methanolic extract of (21.58 µg/mL) and the total phenolics of methanolic extract of was 95.3 mg GAE/g. The rosmarinic acid content of methanolic extract was 0.83 mg/g plant. Antioxidant activity and rosmarininc acid content of suggests that the essential oil and methanolic extract of has great potential for application as a natural antimicrobial and antioxidant agent to preserve food.
The tumor suppressor p16 is a biomarker for transforming human papilloma virus (HPV) infections that can lead to contradictory results in skin carcinomas. The aim of this study was to evaluate p16 expression and HPV-16 infection in the cutaneous basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). This case-control study was performed on paraffin blocks of BCCs and SCCs and normal skin (53, 36, and 44 cases, respectively), between 2006 to 2015. Initial sections for groups were stained with hematoxylin and eosin (H & E). Immunohistochemistry was performed for p16 expression and human papilloma virus type 16 (HPV-16) infection. Normal group was skin of mammoplasty specimens and normal skin tissue in the periphery of tumors. The mean age at diagnosis was 42.1, 61.7 and 71.4 years for normal, BCC and SCC groups, respectively. P16 positivity was more in SCC and BCC groups compared to normal group (P<0.05) and HPV was negative in all patients in three groups. Also, the mean age at diagnosis and P16-positivity were higher for the SCC group than the BCC group (P<0.005). In conclusion, in non-melanoma skin cancers (SCC and BCC), p16-positivity can be a prognostic factor but there is no correlation between HPV-16 and p16 in these tumors.
Conventional data envelopment analysis (DEA) is a method for measuring the efficiency of decision-making units (DMUs). Recently, to measure the efficiency of sub-DMUs (Stages), several network DEA models have been developed, in which the results of network DEA models not only provide the overall efficiency of the whole system but also provide the efficiency of the individual stages. This study develops a bargaining game model for measuring the efficiency of DMUs that have a two-stage network structure with non-discretionary inputs, that the model as a method of dealing with the conflict arising from the intermediate measures. Under the Nash bargaining game theory, the two stages in the network DEA are considered as players and network DEA model is a cooperative game model. Here, the non-discretionary additional inputs in the second stage make changes in the cooperative game model, so that managers of units cannot change the value of non-discretionary inputs in measuring the efficiency of the bargaining game model, and this causes the desired and expected output of the managers not to be produced. In addition, it can be stated that the presence of such inputs is capable, significantly affecting the system efficiency score and stages. So that the existence of the inputs in the measuring efficiency of decision-making units reduces the efficiency score of cooperative game. In this study, linearizing the model in the presence of the non-discretionary input is a new idea in the bargaining game model. A numerical example shows the applicability of the new model.
The present study proposes a method for evaluating and ranking the
efficiency of decision-making units (DMUs) that has a two-stage network
structure in data envelopment analysis (DEA). Measuring the efficiency
of two-stage network systems in data envelopment analysis has developed
considerably, but ranking it in a logical and accurate analysis is a
subject that still needs further study. In the present study, a model is
presented that can consider the impact of each efficient DMUs on the
whole two-stage network system, as well as using the reference frontier,
the impact of each efficient DMUs in each evaluating non-efficient DMUs.
It also provided more information to rank and identify the impact of
extreme efficient DMUs on non-efficient DMUs by reference frontier. The
concept of reference frontier introduced in the present study has the
potential to determine the contribution of each extreme efficient DMUs
in constructing a reference frontier for each non-extreme efficient DMUs
and non-efficient DMUs. These facts have been investigated using logical
reasoning and proof of several theorems, and have been discussed with a
Practical example.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.