BEST FOR CAN - bringing empirically supported treatments to children and adolescents after child abuse and neglect: update to the study protocol.

The implementation trial BESTFORCAN aims to evaluate the dissemination of Trauma-Focused Behavioural Therapy (TF-CBT) for children and adolescents in Germany with posttraumatic stress symptoms (PTSS) after child abuse and neglect (CAN) with a focus on supervision. This update to the study protocol outlines changes made due to practical reasons in the course of the ongoing trial while maintaining methodological quality. The amendments to the original study protocol comprise (1) a more refined operationalisation of the primary outcome sufficiently adherent TF-CBT therapy (SATT), (2) changes in the study sites and (3) additional inclusion of one post-gradual psychotherapy training institute.

Nipple fluid for breast cancer diagnosis using the nanopore of Phi29 DNA-packaging motor.

Detection of cancer in its early stage is a challenging task for oncologists. Inflammatory breast cancer has symptoms that are similar to mastitis and can be mistaken for microbial infection. Currently, the differential diagnosis between mastitis and Inflammatory breast cancer via nipple aspirate fluid (NAF) is difficult.

Selection of Cancer Stem Cell-Targeting Agents Using Bacteriophage Display.

There is a growing need to develop tumor targeting agents for aggressive cancers. Aggressive cancers frequently relapse and are resistant to various therapies. Cancer stem cells (CSCs) are believed to be the cause of relapse and the aggressive nature of many cancers.

Evaluating the Use of Circulating MicroRNA Profiles for Lung Cancer Detection in Symptomatic Patients.

Importance: The overall low survival rate of patients with lung cancer calls for improved detection tools to enable better treatment options and improved patient outcomes. Multivariable molecular signatures, such as blood-borne microRNA (miRNA) signatures, may have high rates of sensitivity and specificity but require additional studies with large cohorts and standardized measurements to confirm the generalizability of miRNA signatures.

Objective: To investigate the use of blood-borne miRNAs as potential circulating markers for detecting lung cancer in an extended cohort of symptomatic patients and control participants.

Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs.

Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches.