Prevalence of Pulmonary Tuberculosis, Failure of Treatment, and its Related Factors in Kashan During 2004-2017

Background: Mycobacterium tuberculosis affects the lungs in 85% of all cases and the remaining 15% through extra pulmonary affecting other parts of the body such as lymph nodes, pleura, and the genitourinary system. This study aimed to investigate extra-pulmonary tuberculosis (TB) associated factors, failure of treatment, and trends between 2004-2017 in Kashan, Iran.Materials and Methods: This study was conducted during 2004-2017 on newly registered extrapulmonary tuberculosis patients referred to TB Referral Center in Isfahan province, Kashan city, Iran. Information (demographic characteristics, related factors of the disease, and treatment status) of 197 extrapulmonary tuberculosis (EPTB) patients was extracted from Medical case records.Results: In total, 527 cases of Tuberculosis were reported, of which, 159 (30.17%) were confirmedextrapulmonary TB. Eighty-five (53.5%) and 74 (46.5%) were male and female, respectively. Also, 74(46.5%), and 84 (53.5%) of EPTB were from Iran, and Afghanistan immigrants, respectively. The average age of patients was 41.9±2.18. Among underlying diseases in extrapulmonary TB positive, diabetes mellitus (DM) was predominant with a prevalence of 31 (19.5%), while, 128 (80.5%) cases did not show any underlying disease. Most of the patients were in the age group (21-40 years) with a frequency of 60 (37.7%), and the lowest of patients belonged to the age group (>80 years) with a frequency of 9 (5.7%). No correlation was found between related factors and infection with EPTB (p> 0.05).Conclusion: Our findings showed that the prevalence of EPTB in Kashan was relatively high, but, a relative decrease was shown during 2004-2017, which with preventative measures can be reduced the prevalence

Molecular Genotyping of the Human Cystic Echinococcosis in Mazandaran Province, North of Iran

Background: The larval stage of the tapeworm (cestode) Echinococcus granulosus is the etiological agent of hydatidosis or cystic echinococcosis, which is the zoonotic parasitic disease causing morbidity and mortality in both humans and livestock. Due to a lack of accurate data on the human isolates of E. granulosus in Mazandaran Province, northern Iran, the current study aimed to survey the population genetic pattern of cystic echinococcosis isolated from humans by sequencing the mitochondrial genes of NADH dehydrogenase subunit 1 (nad1). Methods: Overall, 47 formalin fixed paraffin-embedded tissue (FFPT) blocks were collected from patients' files in various pathology departments of Mazandaran Province in Iran from 2003 to 2015. PCR was performed to amplify a 398bp DNA fragment of mitochondrial nad1. PCR products were sequenced by Bioneer Corporation (South Korea), and the resulting data were analyzed via relevant software to determine the genotypes. Results: The nad1 gene was successfully amplified on 10 from all of the E. granulosus isolates. Overall, 66.6% and 33.3% of the isolates in the studied area displayed the G1 and G2-G3 genotypes, respectively. Conclusion: This study may provide the foundation for further studies in revealing the regional transmission patterns and also in designing adequate control procedures

Factors Affecting the Length of Hospital Stay in Patients with Ischemic Stroke Treated by Intravenous Thrombolysis

Background and purpose: Ischemic stroke is one of the most common neurological diseases that leads to disability in many cases. The aim of this study was to investigate the factors affecting the duration of hospitalization in patients with ischemic stroke undergoing thrombolytic therapy. Materials and methods: This retrospective descriptive-analytical study was performed in consecutive adult patients with ischemic stroke who underwent thrombolytic treatment in Neurology Department of Sari Bu Ali Sina Hospital 2016-2018. Factors associated with duration of hospitalization were investigated. Results: The records of 173 patients (54.9% males) were studied and the mean age of patients was 68.5 ± 12.3 years. During hospitalization, pneumonia, urinary tract infection, and other infections were seen in 19.7%, 9.8%, and 1.2%, respectively. Among the patients, 12.7% experienced hemorrhagic complications. Duration of hospitalization was <7 days in 52.6% and ≥7 days in 47.4% of the patients. Length of hospitalization was significantly associated with hyperlipidemia (P=0.005), stroke severity (P=0.02), large vessel stroke (P<0.001), hemorrhagic complications (P=0.004), and nosocomial infections (P<0.001). Conclusion: Hyperlipidemia, stroke severity, complications of thrombolysis, and nosocomial infections affect the length of hospital stay in patients with ischemic stroke who received alteplase. Therefore, appropriate approach is needed in management of these patients to prevent and eliminate the aforementioned factors

The Relationship between Immature Defense Mechanisms and Postpartum Depression: The Mediating Role of Social Loneliness among Women in Postpartum Period

Postpartum depression, one of the most common postpartum disorders, disrupts the mother's adjustment to the newborn and raising the child in a healthy relationship with the mother by causing harmful and destructive changes in the mother's mood and family environment. Therefore, the present study aimed to investigate the mediating role of social loneliness on the relationship between immature defence mechanisms and postpartum depression. In a correlational study, we selected 227 women visiting Tehran health centres by convenience sampling among all postpartum women in Tehran. They were asked to answer the Edinburgh Postpartum Depression Scale, Andrews and colleagues' Defense Styles questionnaire, and the Social Loneliness Scale. Data were analyzed using the Pearson correlation test and structural equation modelling by AMOS software and SPSS. The results showed that at the 95% confidence level of the structural model of the research, it has a good fit; Thus, immature defence mechanisms have a positive indirect effect due to social loneliness on postpartum depression, and they can increase the risk of the disorder.‌‌Postpartum Depression, Immature Defense Mechanism, Social Loneliness, Women in Postpartum Period.‌‌IntroductionEntering the stage of motherhood leads to significant changes in the individual and social identity of the mother and other family members. Also, it increases the risk of postpartum depression due to substantial changes in physiological and psychological dimensions ( Dennis & Vigod, 2020), which begins with symptoms of depressed mood, excessive anxiety, insomnia, and weight change within four weeks after childbirth. Such a situation can negatively affect the degree of attachment between mother and baby and other family relationships and pose a threat to the safety and health of the baby and other children (Norouzi & Mohammadi, 2015). Among the psychological factors that can affect postpartum depression are defence mechanisms, which are subconscious psychological processes that protect “the ego” from anxiety, painful thoughts, and feelings away from the realm of consciousness (Freud, 1923).  Moreover, it can be said that neurosis is due to the continuous use of immature defences. Given this relationship, it is crucial to identify the mediating structures between them, one of which is social loneliness. If newly delivered women do not receive the social support they need or do not consider existing sources of support as social support, they will feel lonely, predicting postpartum depression (Pourkhaleghi, Askarizadeh, & Fazilat-Pour, 2017). Considering the effect of immature defence mechanisms and social loneliness on postpartum depression, it is vital to discover the mechanism of these relationships. Therefore, this study investigates the relationship between immature defence mechanisms and postpartum depression concerning the mediating role of social loneliness. MethodologyThe research method of the present study is descriptive, and the statistical population consists of all newly delivered women in Tehran in 1400. To determine the sample size in multivariate regression studies, between 5 and 15 observations per measured (observed) variable are considered (Hooman, 2005). Considering that the number of variables measured in the present study is equal to 12 subscales, the minimum sample size was estimated to be 60, and the ideal volume was estimated to be 180. According to the probability of falling subjects, 230 people were considered. Participants were selected based on inclusion and exclusion criteria through the available sampling method. After deleting the distorted data, the information of 227 participants was statistically analyzed using SPSS and AMOS software. The instruments used in this study included the Edinburgh Postpartum Depression Scale, the Defense Styles Questionnaire, and the Social Loneliness Scale, which was completed by newly delivered women referring to health centres after obtaining informed consent. Firstly, the correlations between the variables were calculated using the Pearson correlation coefficient. Then, path analysis was used to investigate the mediating role of social loneliness in the relationship between immature defence mechanisms and postpartum depression. FindingsThe mean age of newly delivered women was 28.44, and its standard deviation was 4.55 (age range: 20-45). The highest frequency in terms of age group is related to the class of 20 to 29 years. Also, 127 of them (55.9%) had a cesarean delivery, and 100 (44.1%) had a normal delivery. In addition, in terms of educational level, the highest frequency is related to undergraduate education, and in terms of employment status, the highest frequency is allocated to the housewife class. Social loneliness showed a significant positive correlation with immature defence mechanisms (r = 0.37, p <0.01) and postpartum depression (r = 0.46, p <0.01). The path analysis method was used to test the mediation pattern of social loneliness with immature defence mechanisms and postpartum depression. In this model, the direct pathway from immature defence mechanisms to postpartum depression was statistically significant (p = 0.040). The values of good fit indices obtained for the final model showed that the assumed model perfectly fits the data. The bootstrap procedure's indirect effect study results that immature defence mechanisms could significantly predict postpartum depression through social mediation alone. The indirect effect of immature defence mechanisms on postpartum depression was 0.15 and statistically significant (p <0.001). In the final model, 0.14% of the variance of social loneliness was explained by immature defence mechanisms, and 0.23% of the variance of postpartum depression was explained by defence mechanisms mediated by social loneliness. ResultThe results showed that immature defence mechanisms and postpartum depression were significantly correlated. Due to the use of immature defence mechanisms, they feel more social loneliness, which in turn causes depressive symptoms. It can be said that with the birth of a child, the mother becomes a new and unique psychological organization that is closely related to representations, unconscious processes, feelings, and experiences that are often overlooked in other moments of life (Stern, 1995). Thus, childbirth and the need to reorganize the conscious and subconscious aspects of representing oneself and others may reactivate unprocessed experiences, such as loss and grief. Also, based on the interaction hypothesis, it can be said that the emotion of depression activates the compensatory mechanism, and the compensatory mechanism, in turn, intensifies the feeling of depression. If "the ego" can not find another way out in the face of these emotions and fails to regulate and manage emotions, a mood disorder such as depression will form or persist. As a result, finding immature defence mechanisms in newborn women therapists and informing mothers about the function of these mechanisms in different life situations can change their perception of social loneliness. In this case, by reducing the feeling of social loneliness, the occurrence and persistence of postpartum depression can be prevented

Artificial Intelligence in Cancer Care: From Diagnosis to Prevention and Beyond

&lt;p&gt;Artificial Intelligence (AI) has made significant strides in revolutionizing cancer care, encompassing various aspects from diagnosis to prevention and beyond. With its ability to analyze vast amounts of data, recognize patterns, and make accurate predictions, AI has emerged as a powerful tool in the fight against cancer. This article explores the applications of AI in cancer care, highlighting its role in diagnosis, treatment decision-making, prevention, and ongoing management. In the realm of cancer diagnosis, AI has demonstrated remarkable potential. By processing patient data, including medical imaging, pathology reports, and genetic profiles, AI algorithms can assist in early detection and accurate diagnosis. Image recognition algorithms can analyze radiological images, such as mammograms or CT scans, to detect subtle abnormalities and assist radiologists in identifying potential tumors. AI can also aid pathologists in analyzing tissue samples, leading to more precise and efficient cancer diagnoses. AI's impact extends beyond diagnosis into treatment decision-making. The integration of AI algorithms with clinical data allows for personalized treatment approaches. By analyzing patient characteristics, disease stage, genetic markers, and treatment outcomes, AI can provide valuable insights to oncologists, aiding in treatment planning and predicting response to specific therapies. This can lead to more targeted and effective treatment strategies, improving patient outcomes and reducing unnecessary treatments and side effects. Furthermore, AI plays a crucial role in cancer prevention. By analyzing genetic and environmental risk factors, AI algorithms can identify individuals at higher risk of developing certain cancers. This enables targeted screening programs and early interventions, allowing for timely detection and prevention of cancer. Additionally, AI can analyze population-level data to identify trends and patterns, contributing to the development of public health strategies for cancer prevention and control. AI's involvement in cancer care goes beyond diagnosis and treatment, encompassing ongoing management and survivorship. AI-powered systems can monitor treatment response, track disease progression, and detect recurrence at an early stage. By continuously analyzing patient data, including imaging, laboratory results, and clinical assessments, AI algorithms can provide real-time insights, facilitating timely interventions and adjustments to treatment plans. This proactive approach to disease management improves patient outcomes and enhances quality of life.&lt;/p&gt