Associations of Uncertainty With Psychological Health and Quality of Life in Older Adults With Advanced Cancer

ContextOlder adults with advanced cancer face uncertainty related to their disease and treatment.ObjectivesTo evaluate the associations of uncertainty with psychological health and quality of life (QoL) in older adults with advanced cancer.MethodsSecondary cross-sectional analysis of baseline data from a national clustered geriatric assessment trial. Patients 70 years and older with advanced cancer considering a new line of chemotherapy were recruited. We measured uncertainty using the modified nine-item Mishel Uncertainty in Illness Scale. Dependent variables included anxiety (Generalized Anxiety Disorder-7), depression (Generalized Depression Scale-15), distress (distress thermometer), QoL (Functional Assessment of Cancer Therapy—General), and emotional well-being (Functional Assessment of Cancer Therapy—General subscale). We used multivariate linear regression analyses to evaluate the association of uncertainty with each dependent variable. We conducted a partial least squares analysis with a variable importance in projection (VIP) plot to assess the contribution of individual variables to the model. Variables with a VIP <0.8 were considered less influential.ResultsWe included 527 patients (median age 76 years; range 70–96). In multivariate analyses, higher levels of uncertainty were significantly associated with greater anxiety (β = 0.11; SE = 0.04), depression (β = 0.09; SE = 0.02), distress (β = 0.12; SE = 0.02), as well as lower QoL (β = ?1.08; SE = 0.11) and emotional well-being (β = ?0.29; SE = 0.03); the effect sizes were considered small. Uncertainty items related to disease and treatment were most strongly associated with psychological health and QoL scores (all VIP >0.8).ConclusionUncertainty among older patients with advanced cancer is associated with worse psychological health and QoL. Tailored uncertainty management strategies are warranted.     

Hepatitis E virus antigen detection as an early diagnostic marker: Report from India

Hepatitis E virus (HEV) is implicated in many outbreaks of viral hepatitis in the Indian subcontinent. The conventional diagnosis of such outbreaks rests on the detection of anti‐HEV IgM antibodies. However, IgM antibodies develop after 4–5 days of infection. An early‐diagnostic marker is imperative for timely diagnosis of the outbreak and also initiation of control measures. This study aimed to determine the use of hepatitis E virus antigen detection as an early diagnostic marker in an outbreak in comparison to anti‐HEV IgM and RT‐PCR analyses. Forty samples were collected during a suspected outbreak of viral hepatitis due to HEV. A total of 36 samples were positive for one or more HEV markers. The positivity for anti‐HEV IgM, HEV antigen, and RT‐PCR was 91.6%, 69.4%, and 47.2% respectively. RT‐PCR and HEV antigen detection gave the highest positive results (100%) in the first 3 days of illness. Positive HEV PCR declined to 54% by Days 4–7, whereas HEV antigen and IgM detection were 88% and 100%, respectively. Sequencing of representative HEV samples indicated that the strains responsible for this outbreak belonged to genotype I, subtype 1a. HEV antigen was found to be an early diagnostic marker of acute infection. HEV antigen was detected in three additional cases in the early phase (1–3 days), and they had no detectable anti‐HEV IgM antibodies. These three samples were also positive for HEV RNA. After Day 7, anti‐HEV IgM was the main diagnostic indicator of infection. J. Med. Virol. 85:823–827, 2013. © 2013 Wiley Periodicals, Inc.     

Ultrasonographic estimation of fetal gestational age by fetal kidney length

Introduction: Fetal kidney length vs biparietal diameter (BPD) and femur length (FL) were comparatively evaluated and the role of fetal kidney length in estimating gestational age was determined in the second and third trimesters. Materials and methods: The study was carried out on 199 women with singleton uncomplicated pregnancies attending the outdoor patient department (OPD) for routine ultrasound fetal biometry. Fetal kidney length was measured biweekly, between 18 weeks and 38 weeks of gestation. Linear regression models for estimation of gestational age were derived from biometric indices (BPD and FL) and kidney length. Result: The earliest age at which fetal kidney could be seen sonographically was the 18th week of gestation with the mean kidney length of 12 ± 1.31 mm. The mean sonographic kidney length at the 38th week of gestation was 40.4 ± 1.71 mm, indicating that the mean fetal kidney length increases as pregnancy progresses from 18 weeks to 38 weeks of gestation. Conclusion: The best linear regression model for estimating fetal gestational age is femur length, kidney length, and biparietal diameter in that order, with standard error of ±3.85 days, ±8.04 days, and ±8.75 days, respectively.     

E6-AP association promotes SOD1 aggresomes degradation and suppresses toxicity

Protein aggregation and ordered fibrillar amyloid deposition inside and outside of the central nervous system cells is the common pathologic hallmark of most aging-related neurodegenerative disorders. Dominant mutations in the gene encoding superoxide dismutase 1 (SOD1) protein are linked to familial amyotrophic lateral sclerosis (ALS), a neurodegenerative disease characterized by progressive degeneration of motor neurons, leading to muscle paralysis and death. The major histochemical hallmark in the remaining motor neurons of ALS is the intracellular accumulation of ubiquitinated inclusions consisting of insoluble aberrant protein aggregates. However, the molecular pathomechanisms underlying the process have been elusive. Here for the first time, we report that E6-AP, a homologous to E6-AP C terminus-type E3 ubiquitin ligase depleted in ALS mouse models before neurodegeneration. E6-AP coimmunoprecipitates with the SOD1 protein and is predominantly mislocalized in mutant SOD1-containing inclusion bodies. Overexpression of E6-AP increases the ubiquitination and facilitates degradation of SOD1 proteins. Finally, we show that the overexpression of E6-AP suppresses the aggregation and cell death mediated by mutated SOD1 proteins and cellular protective effect is more prominent when E6-AP is overexpressed along with Hsp70. These data suggest that enhancing the activity of E6-AP ubiquitin ligase might be a viable therapeutic strategy to eliminate mutant SOD1-mediated toxicity in ALS.     

T Cell-Epstein-Barr Virus–Associated Hemophagocytic Lymphohistiocytosis (HLH) Occurs in Non-Asians and Is Associated with a T Cell Activation State that Is Comparable to Primary HLH

Journal of Clinical Immunology - T cell-Epstein-Barr virus–associated hemophagocytic lymphohistiocytosis (T cell-EBV-HLH) is prevalent in East Asia and has poor prognosis. Understanding of...     

Artificial intelligence in brachytherapy: a summary of recent developments

Artificial intelligence (AI) applications, in the form of machine learning and deep learning, are being incorporated into practice in various aspects of medicine, including radiation oncology. Ample evidence from recent publications explores its utility and future use in external beam radiotherapy. However, the discussion on its role in brachytherapy is sparse. This article summarizes available current literature and discusses potential uses of AI in brachytherapy, including future directions. AI has been applied for brachytherapy procedures during almost all steps, starting from decision-making till treatment completion. AI use has led to improvement in efficiency and accuracy by reducing the human errors and saving time in certain aspects. Apart from direct use in brachytherapy, AI also contributes to contemporary advancements in radiology and associated sciences that can affect brachytherapy decisions and treatment. There is a renewal of interest in brachytherapy as a technique in recent years, contributed largely by the understanding that contemporary advances such as intensity modulated radiotherapy and stereotactic external beam radiotherapy cannot match the geometric gains and conformality of brachytherapy, and the integrated efforts of international brachytherapy societies to promote brachytherapy training and awareness. Use of AI technologies may consolidate it further by reducing human effort and time. Prospective validation over larger studies and incorporation of AI technologies for a larger patient population would help improve the efficiency and acceptance of brachytherapy. The enthusiasm favoring AI needs to be balanced against the short duration and quantum of experience with AI in limited patient subsets, need for constant learning and re-learning to train the AI algorithms, and the inevitability of humans having to take responsibility for the correctness and safety of treatments.