Background: Currently, the main goal of cancer research is to increase longevity of patients suffering malignant cancers. The promising results of BCc1 in vitro and vivo experiments made us look into the effect of BCc1 nanomedicine on patients with cancer in a clinical trial. Methods: The present investigation was a randomized, double-blind, placebo-controlled, parallel, and multicenter study in which 123 patients (30-to-85-year-old men and women) with metastatic and non-metastatic gastric cancer, in two separate groups of BCc1 nanomedicine or placebo, were selected using a permuted block randomization method. For metastatic and non-metastatic patients, a daily dose of 3000 and 1500 mg was prescribed, respectively. Overall survival (OS) as the primary endpoint and quality of life (measured using QLQ-STO22) and adverse effects as the secondary endpoints were studied. Results: In metastatic patients, the median OS was significantly higher in BCc1 nanomedicine (174 days [95% confidence interval (CI) 82.37–265.62]) than in placebo (62 days [95% CI 0–153.42]); hazard ratio (HR): 0.5 [95% CI 0.25–0.98; p = 0.046]. In non-metastatic patients, the median OS was significantly higher in BCc1 nanomedicine (529 days [95% CI 393.245–664.75]) than in placebo (345 days [95% CI 134.85–555.14]); HR: 0.324 [95% CI 0.97–1.07; p = 0.066]. The QLQ-STO22 assessment showed a mean difference improvement of 3.25 and 2.29 (p value > 0.05) in BCc1 nanomedicine and a mean difference deterioration of − 4.42 and − 3 (p-value < 0.05) in placebo with metastatic and non-metastatic patients, respectively. No adverse effects were observed. Conclusion: The findings of this trial has provided evidence for the potential capacity of BCc1 nanomedicine for treatment of cancer. Trial registration IRCTID, IRCT2017101935423N1. Registered on 19 October 2017, http://www.irct.ir/ IRCT2017101935423N1

Background. The aim of this study was to investigate the psychosocial adjustment to illness and its relation with spiritual health in cancer patients. Methods. This study was conducted in 2019 in Iran. It was a descriptive study with a sample of 124 cancer patients. Data were collected using two questionnaires of the psychosocial adjustment to illness scale (PAIS) with 46 questions and the Paloutzian and Ellison spiritual health scale with 20 questions. Results. The mean age of the participants in this study was 52.4±13.2 (range 18 to 87 years). The mean months of life with cancer were 16.5 months. The mean score of psychosocial adjustment to illness was 30.7±15.5. The mean score of spiritual wellbeing in the studied patients was 71.4±17.1. The results of the Pearson correlation test showed a significant inverse relationship between the mean score of psychosocial adjustment to illness and the mean score of spiritual wellbeing (p>0.001, rr=−.355). Conclusion. Cancer patients in this study had relatively good psychosocial adjustment with their illness. Spiritual wellbeing can increase psychosocial adjustment to illness in this group of patients.

Background: Our previous findings showed that BCc1, a nanoparticle designed based on nanochelating technology, can be considered a new anti-cancer nanoparticle if confirmed by complementary studies. Goal: In the present study, we investigated the effects of the BCc1 nanoparticle alone on some gene expressions influencing the apoptosis pathway, and also the effect of the mixture of BCc1 nanoparticle and doxorubicin on survival. Method: Using an in vitro study, the effects of the BCc1 nanoparticle on Bax, Bcl2, p53, Caspase7 and p21 gene expressions were assessed after a 24-h treatment using real-time PCR in MCF-7 and MEFs; in addition, using an in vivo study, 4T1 tumor-bearing female Balb/c mice were treated with different doses of the BCc1 nanoparticle and doxorubicin alone and together and then their mean and median survival was evaluated. Result: The results showed that the BCc1 nanoparticle increased gene expressions of RB, p53, Caspase7, p21, and Bax and decreased gene expressions of Bcl2 in MCF-7 significantly, but no change was observed in MEFs expressions. The findings revealed that the BCc1 nanoparticle, when used orally, had the highest mean and median survival time. A mixture of a high dose of the BCc1 nanoparticle (1 mg/kg) and a low dose of doxorubicin (0.1 mg/kg) showed synergistic effects on enhanced life span, while doxorubicin dose was prescribed approximately 50 times less than the murine applicable dose (5 mg/kg). Conclusion: Our results demonstrated that the BCc1 nanoparticle not only has the potential to become a novel nanomedicine for cancer therapy, but it can also provide the basis of a new medicine for cancer management when mixed with a lower applicable dose of doxorubicin.

In this paper, a Bayesian framework using a joint transition model for analysing longitudinal mixed ordinal and continuous responses is considered. The joint model considers a multivariate mixed model for the responses in which a transitive cumulative logistic regression model and an autoregressive regression model are used to model ordinal and continuous responses, respectively. Also, to take into account the association between longitudinal ordinal and continuous responses, a dynamic association parameter is used. A test is conducted to see whether this parameter is time-invariant and another test is presented to see whether this parameter is equal to zero or significantly far from zero. Our approach is applied to longitudinal PIAT (Peabody Individual Achievement Test) data where the Bayesian estimates of parameters are obtained.

In quality control (QC) of the individual pieces tested, the distribution of the intended variable is not normal in many cases. ‎Therefore, the use of conventional statistical methods to design the control charts (X chart) can lead to misleading and inaccurate results, and hence, it can cause problems to users; because in such a situation it would not be expected that the failure in the production line will be detected in a timely manner. ‎Therefore, in this study, the use of Extended Generalized Lambda distribution (XGLD) has been proposed for approximating the statistical distribution of data and finding a quality control chart based on it. ‎For this purpose, the distribution function of data was firstly estimated by the XGLD, and then, based on this distribution, the control limits were calculated. ‎The research data consists of the tensile strength of 149 aluminum plates categorized into 22 classes. ‎For the goodness of fit test, Chi-square test was utilized and to evaluate the effectiveness of the proposed model, the average run length (ARL) method was used. The results showed that the ARL value‏‎s‎ in the proposed method are lower than that in the conventional method. ‎Since this is true at all points, it can be concluded that the use of the new method can lead to the faster detection of the system’s failure and consequently, the subsequent costs can be reduced.‎In addition, since the XGLD is a highly flexible distribution and can estimate many conventional (and even unconventional) distributions with high precision, the use of the proposed method instead of using other cases which are based on distributions other than normal, will increase the accuracy of the system’s failure detection.‎ ‎