Dishevelled: An emerging therapeutic oncogene in human cancers.

Cancer is a multifaceted and complex disorder characterized by uncontrolled rates of cell proliferation and its ability to spread and attack other organs. Emerging data indicated several pathways and molecular targets are engaged in cancer progression. Among them, the Wnt signaling pathway was shown to have a crucial role in cancer onset and progression. Dishevelled (DVL) acts in a branch point of canonical and non-canonical Wnt pathway. DVL not only acts in the cytoplasm to inactivate the destruction complex of ß-catenin but is also transported into the nucleus to affect the transcription of target genes. Available data revealed that the expression levels of DVL increased in cell and clinical specimens of various cancers, proposing that it may have an oncogenic role. DVL promoted cell invasion, migration, cell cycle, survival, proliferation, 3D-spheroid formation, stemness, and epithelial mesenchymal transition (EMT) and it suppressed cell apoptosis. The higher levels of DVL is associated with the clinicopathological characteristic of cancer-affected patients, including lymph node metastasis, tumor grade, histological type, and age. In addition, the higher levels of DVL could be a promising diagnostic and prognostic biomarker in cancer as well as it could be a mediator in cancer chemoresistance to Methotrexate, paclitaxel, and 5-fluorouracil. This study aimed to investigate the underlying molecular mechanism of DVL in cancer pathogenesis as well as to explore its importance in cancer diagnosis and prognosis as well as its role as a mediator in cancer chemotherapy.

A Computerized Analysis with Machine Learning Techniques for the Diagnosis of Parkinson's Disease: Past Studies and Future Perspectives.

According to the World Health Organization (WHO), Parkinson's disease (PD) is a neurodegenerative disease of the brain that causes motor symptoms including slower movement, rigidity, tremor, and imbalance in addition to other problems like Alzheimer's disease (AD), psychiatric problems, insomnia, anxiety, and sensory abnormalities. Techniques including artificial intelligence (AI), machine learning (ML), and deep learning (DL) have been established for the classification of PD and normal controls (NC) with similar therapeutic appearances in order to address these problems and improve the diagnostic procedure for PD. In this article, we examine a literature survey of research articles published up to September 2022 in order to present an in-depth analysis of the use of datasets, various modalities, experimental setups, and architectures that have been applied in the diagnosis of subjective disease. This analysis includes a total of 217 research publications with a list of the various datasets, methodologies, and features. These findings suggest that ML/DL methods and novel biomarkers hold promising results for application in medical decision-making, leading to a more methodical and thorough detection of PD. Finally, we highlight the challenges and provide appropriate recommendations on selecting approaches that might be used for subgrouping and connection analysis with structural magnetic resonance imaging (sMRI), DaTSCAN, and single-photon emission computerized tomography (SPECT) data for future Parkinson's research.

Imperative Role of Machine Learning Algorithm for Detection of Parkinson's Disease: Review, Challenges and Recommendations.

Parkinson's disease (PD) is a neurodegenerative disease that affects the neural, behavioral, and physiological systems of the brain. This disease is also known as tremor. The common symptoms of this disease are a slowness of movement known as 'bradykinesia', loss of automatic movements, speech/writing changes, and difficulty with walking at early stages. To solve these issues and to enhance the diagnostic process of PD, machine learning (ML) algorithms have been implemented for the categorization of subjective disease and healthy controls (HC) with comparable medical appearances. To provide a far-reaching outline of data modalities and artificial intelligence techniques that have been utilized in the analysis and diagnosis of PD, we conducted a literature analysis of research papers published up until 2022. A total of 112 research papers were included in this study, with an examination of their targets, data sources and different types of datasets, ML algorithms, and associated outcomes. The results showed that ML approaches and new biomarkers have a lot of promise for being used in clinical decision-making, resulting in a more systematic and informed diagnosis of PD. In this study, some major challenges were addressed along with a future recommendation.

Pharmacological potential of tocopherol and doxycycline against traumatic brain injury-induced cognitive/motor impairment in rats.

Primary Objective The primary objective of this study was to explore the pharmacological potential of tocopherol and doxycycline against traumatic brain injury-induced cognitive/motor impairment in rats. Research Design Weight drop model of traumatic brain injury. Methods and Procedures After TBI, the animals were treated with doxycycline (50 and 100 mg/kg; p.o), tocopherol (5 and 10 mg/kg; p.o) alone and in combination as doxycycline and tocopherol (50 and 10 mg/kg; p.o) from 1st day to 28th day. The behavioral parameters were performed on a weekly basis from 1st day to 28th day. On 29th day, animals were sacrificed and striatum and cortex were homogenized for the estimation of biochemical (LPO, nitrite, and GSH), neuroinflammatory (IL-6, IL-1ß, and TNF-α), and neurotransmitters (dopamine, norepinephrine, serotonin, GABA, and glutamate) analysis. Main Outcomes and Results Induction of TBI had significantly reduced locomotor activity, recognition memory, increased neuroinflammatory markers, and imbalance neurotransmitter levels. The treatment with doxycycline and tocopherol alone and in combination significantly attenuated locomotor activity, memory recognition, reduced neuroinflammation, preserved oxidative balance, and restored the level of neurotransmitters. Conclusions The neuroprotective effect of doxycycline and tocopherol might be due to its anti-inflammatory and free radical scavenging mechanisms. Abbreviations TBI: Traumatic brain injury; Doxy: Doxycycline; Toco: Tocopherol; LPO: Lipid peroxidation; MDA: Malondialdehyde; TNF-α: Tumor necrosis factor-alpha; IL-1b: Interleukin-1 beta; GSH: Glutathione; GABA: gamma-Aminobutyric acid.

Traumatic Brain Injury Altered Normal Brain Signaling Pathways: Implications for Novel Therapeutics Approaches.

Traumatic brain injury (TBI) is the main reason of lifelong disability and casualty worldwide. In the United State alone, 1.7 million traumatic events occur yearly, out of which 50,000 results in deaths. Injury to the brain could alter various biological signaling pathways such as excitotoxicity, ionic imbalance, oxidative stress, inflammation, and apoptosis which can result in various neurological disorders such as Psychosis, Depression, Alzheimer disease, Parkinson disease, etc. In literature, various reports have indicated the alteration of these pathways after traumatic brain injury but the exact mechanism is still unclear. Thus, in the first part of this article, we have tried to summarize TBI as a modulator of various neuronal signaling pathways. Currently, very few drugs are available in the market for the treatment of TBI and these drugs only provide the supportive care. Thus, in the second part of the article, based on TBI altered signaling pathways, we have tried to find out potential targets and promising therapeutic approaches in the treatment of TBI.

Improved Plasmodium berghei lines for conditional mutagenesis.

Conditional mutagenesis is a powerful tool for genetic analysis in Plasmodium berghei. It allows the study of proteins that function both during the parasite's pre-erythocytic and erythrocytic development. Currently available parasite lines used for conditional mutagenesis were constructed in the NK65 strain, and express a DNA recombinase under the control of pre-erythrocytic stage-specific promoters. However, the integration of the recombinase in these lines is unstable leading to inconsistent excision of the target gene. We describe improved lines of P. berghei with stably integrated DNA recombinase that allow efficient, stage-specific excision of target genes in the widely used ANKA strain.