Nucleus accumbens deep-brain stimulation efficacy in ACTH-pretreated rats: alterations in mitochondrial function relate to antidepressant-like effects.

Mitochondrial dysfunction has a critical role in the pathophysiology of mood disorders and treatment response. To investigate this, we established an animal model exhibiting a state of antidepressant treatment resistance in male Wistar rats using 21 days of adrenocorticotropic hormone (ACTH) administration (100 µg per day). First, the effect of ACTH treatment on the efficacy of imipramine (10 mg kg(-1)) was investigated alongside its effect on the prefrontal cortex (PFC) mitochondrial function. Second, we examined the mood-regulatory actions of chronic (7 day) high-frequency nucleus accumbens (NAc) deep-brain stimulation (DBS; 130 Hz, 100 µA, 90 µS) and concomitant PFC mitochondrial function. Antidepressant-like responses were assessed in the open field test (OFT) and forced swim test (FST) for both conditions. ACTH pretreatment prevented imipramine-mediated improvement in mobility during the FST (P<0.05). NAc DBS effectively improved FST mobility in ACTH-treated animals (P<0.05). No improvement in mobility was observed for sham control animals (P>0.05). Analyses of PFC mitochondrial function revealed that ACTH-treated animals had decreased capacity for adenosine triphosphate production compared with controls. In contrast, ACTH animals following NAc DBS demonstrated greater mitochondrial function relative to controls. Interestingly, a proportion (30%) of the ACTH-treated animals exhibited heightened locomotor activity in the OFT and exaggerated escape behaviors during the FST, together with general hyperactivity in their home-cage settings. More importantly, the induction of this mania-like phenotype was accompanied by overcompensative increased mitochondrial respiration. Manifestation of a DBS-induced mania-like phenotype in imipramine-resistant animals highlights the potential use of this model in elucidating mechanisms of mood dysregulation.

Aptasensors: a review.

Aptamers are a promising class of agents for biomolecules detection due to their small size, chemical stability and cost effectiveness over conventional bioreceptors such as antibodies. Recent advances in micro/nano-fabrication and biotechnology have driven active participation of engineers and molecular biologists in the development of aptasensors. This review examines aptasensors from a developer standpoint discussing surface immobilization techniques and mechanisms used to detect biomolecular interactions in the context of biotechnology and nanomedicine. The factors that affect accuracy, sensitivity and stability of aptasensors are also addressed.

Random forest based lung nodule classification aided by clustering.

An automated lung nodule detection system can help spot lung abnormalities in CT lung images. Lung nodule detection can be achieved using template-based, segmentation-based, and classification-based methods. The existing systems that include a classification component in their structures have demonstrated better performances than their counterparts. Ensemble learners combine decisions of multiple classifiers to form an integrated output. To improve the performance of automated lung nodule detection, an ensemble classification aided by clustering (CAC) method is proposed. The method takes advantage of the random forest algorithm and offers a structure for a hybrid random forest based lung nodule classification aided by clustering. Several experiments are carried out involving the proposed method as well as two other existing methods. The parameters of the classifiers are varied to identify the best performing classifiers. The experiments are conducted using lung scans of 32 patients including 5721 images within which nodule locations are marked by expert radiologists. Overall, the best sensitivity of 98.33% and specificity of 97.11% have been recorded for proposed system. Also, a high receiver operating characteristic (ROC) A(z) of 0.9786 has been achieved.

At a glance: cellular biology for engineers.

Engineering contributions have played an important role in the rise and evolution of cellular biology. Engineering technologies have helped biologists to explore the living organisms at cellular and molecular levels, and have created new opportunities to tackle the unsolved biological problems. There is now a growing demand to further expand the role of engineering in cellular biology research. For an engineer to play an effective role in cellular biology, the first essential step is to understand the cells and their components. However, the stumbling block of this step is to comprehend the information given in the cellular biology literature because it best suits the readers with a biological background. This paper aims to overcome this bottleneck by describing the human cell components as micro-plants that form cells as micro-bio-factories. This concept can accelerate the engineers' comprehension of the subject. In this paper, first the structure and function of different cell components are described. In addition, the engineering attempts to mimic various cell components through numerical modelling or physical implementation are highlighted. Next, the interaction of different cell components that facilitate complicated chemical processes, such as energy generation and protein synthesis, are described. These complex interactions are translated into simple flow diagrams, generally used by engineers to represent multi-component processes.