Mikania micrantha extract enhances cutaneous wound healing activity through the activation of FAK/Akt/mTOR cell signaling pathway.

Mikania micrantha (MM) has been traditionally used for various health benefits, including mental health, anti-inflammatory, wound dressing, and healing of sores. However, the molecular mechanisms and dose required for the wound healing activity of MM have yet to be reported. Therefore, a study was conducted to evaluate the wound healing potential of a cold methanolic extract of MM through in vitro and in vivo studies. Human dermal fibroblast adult (HDFa) cells were treated with 0 (control), 75 ng/ml, 125 ng/ml, 250 ng/ml, and 500 ng/ml of MMmethanolic extract (MME) for 24 h. MME at 75 ng/ml has significantly (p˂0.05) promoted HDFa cell proliferation and migration. Further, MME has also been shown to enhance the invasiveness of human umbilical vascular endothelial cells (HUVECs), indicating the neovasculature for wound healing. The tube formation assay demonstrated a significant (p<0.05) increase in the angiogenic effect of the MME starting at a concentration of 75 ng/ml as compared to the control. Treatment of excision wounds in Wistar rats with 5% and 10% MME ointment significantly enhanced wound contraction compared to control animals. Incision wounds in rats treated with 5% and 10% MME showed a significant (p<0.01) increase in tensile strength compared to control. HDFa cells, and granulation tissue collected on day 14 post-wounding, revealed the modulation of the FAK/Akt/mTOR cell signaling pathway during the enhancement of wound healing. The results of gel zymography showed increased activity of MMP-2 and MMP-9 in the HDFa cells after treatment with the extract.  It is concluded that MMEcan potentially accelerate cutaneous wound healing.

The need of patients living with cancer for palliative care.

BACKGROUND: A comprehensive assessment of patients' problems and needs is essential for all patients with chronic diseases, including cancer. AIM: This study assesses the problems, unmet needs and requirement for palliative care (PC) among patients with cancer. METHOD: A descriptive cross-sectional design was employed using a valid self-reported questionnaire. RESULTS: On average, 62% of patients had problems that were unresolved. The need for patients to have more information about their health was identified (75.1%), followed by financial problems because of the illness and ability to afford healthcare (72.9%), and psychological issues, such as depression, anxiety and stress (67.1%). Patients stated that their spiritual needs were not being met (78.8%), and that they were experiencing psychological distress and problems with daily living that needed to be addressed through PC (78%, 75.1%, respectively). A chi-square test revealed that all problems are significantly associated with the need for PC (P<.001). CONCLUSION: Patients needed more assistance in psychological, spiritual, financial and physical domains, and this can be provided by palliative care. Palliative care in low-income countries is a human right for patients with cancer.

A convolutional neural network approach for detection of E. coli bacteria in water.

The detection of Escherichia coli bacteria is essential to prevent health diseases. According to the laboratory-based methods, 12-48 h is required to detect bacteria in water. The drawback of depending on laboratory-based methods for the detection of E. coli bacteria can be prone to human errors. Hence, the bacterial detection process must be automated to reduce error. We implement an automated E. coli bacteria detection process using convolutional neural network (CNN) to address this issue. We have also proposed a mobile application for the rapid detection of E. coli bacteria in water that uses CNN. The developed CNN model achieved an accuracy of 96% and an error (loss) of 0.10, predicting each sample in only 458ms. The performance of the model was validated using the F-score, precision, sensitivity, and accuracy statistical measures, which shows that the model is reliable and effective in detecting E. coli. The study generates a methodology for predicting E. coli bacteria in water, which can be used to predict hotspots in terms of continuous exposure to water contamination.

Centchroman prevents metastatic colonization of breast cancer cells and disrupts angiogenesis via inhibition of RAC1/PAK1/ß-catenin signaling axis.

AIMS: We have previously reported that Centchroman (CC), an oral contraceptive drug, inhibits breast cancer progression and metastasis. In this study, we investigated whether CC inhibits local invasion of tumor cells and/or their metastatic colonization with detailed underlying mechanisms. MAIN METHODS: The effect of CC on the experimental metastasis and spontaneous metastasis was demonstrated by using tail-vein and orthotopic 4T1-syngeneic mouse tumor models, respectively. The anti-angiogenic potential of CC was evaluated using well established in vitro and in vivo models. The role of RAC1/PAK1/ß-catenin signaling axis in the metastasis was investigated and validated using siRNA-mediated knockdown of PAK1 as well as by pharmacological PAK1-inhibitor. KEY FINDINGS: The oral administration of CC significantly suppressed the formation of metastatic lung nodules in the 4T1-syngeneic orthotopic as well as experimental metastatic models. More importantly, CC treatment suppressed the tube formation and migration capacities of human umbilical vein endothelial cells (HUVEC) and inhibited pre-existing vasculature as well as the formation of neovasculature. The suppression of migration and invasion capacities of metastatic breast cancer cells upon CC treatment was associated with the inhibition of small GTPases (Rac1 and Cdc42) concomitant with the downregulation of PAK1 and downstream ß-catenin signaling. In addition, CC upregulated the expression of miR-145, which is known to target PAK1. SIGNIFICANCE: This study warrants the repurposing of CC as a potential therapeutic agent against metastatic breast cancer.

Preparedness and Mitigation by projecting the risk against COVID-19 transmission using Machine Learning Techniques

The outbreak of COVID-19 is first identified in China, which later spread to various parts of the globe and was pronounced pandemic by the World Health Organization (WHO). The disease of transmissible person-to-person pneumonia caused by the extreme acute respiratory coronavirus 2 syndrome (SARS-COV-2, also known as COVID-19), has sparked a global warning. Thermal screening, quarantining, and later lockdown were methods employed by various nations to contain the spread of the virus. Though exercising various possible plans to contain the spread help in mitigating the effect of COVID-19, projecting the rise and preparing to face the crisis would help in minimizing the effect. In the scenario, this study attempts to use Machine Learning tools to forecast the possible rise in the number of cases by considering the data of daily new cases. To capture the uncertainty, three different techniques: (i) Decision Tree algorithm, (ii) Support Vector Machine algorithm, and (iii) Gaussian process regression are used to project the data and capture the possible deviation. Based on the projection of new cases, recovered cases, deceased cases, medical facilities, population density, number of tests conducted, and facilities of services, are considered to define the criticality index (CI). CI is used to classify all the districts of the country in the regions of high risk, low risk, and moderate risk. An online dashpot is created, which updates the data on daily bases for the next four weeks. The prospective suggestions of this study would aid in planning the strategies to apply the lockdown/ any other plan for any country, which can take other parameters to define the CI.

The role of electronic medical records in improving the quality of health care services: Comparative study.

PURPOSE: The purpose of this study is to identify the quality of health care services' differences between adopted Electronic Medical Record (EMR) and paper-based record hospitals. Moreover, to identify how the quality of electronic medical records affect the quality of health care services. METHODS: A cross-sectional, descriptive, and comparative design was utilized between two groups in this study. The study was conducted in two public hospitals in Jordan. One hospital which had adopted the EMR system in their works and another hospital that had paper-based record. A convenience sampling technique was used to select 410 health professionals from the selected hospitals (205 participants from each hospital). SERVQUAL and E-S-QUAL questionnaires were adopted to collect the data about the quality of EMR and quality of health care service. Statistical Package for the Social Sciences (SPSS) Version 21 was deployed to analyze the collected data. RESULT: The results indicate that the quality of health care services (expectation and perception) in EMRs adopted hospital is higher than the quality of health care services in the hospital using paper-based record. Quality of EMRs and its domains (efficiency, availability, fulfilment, and privacy) are high in both perception and expectation of health care professionals in EMR-adopted hospitals. Moreover, there is a significant relationship between the whole perception of the quality of electronic medical records and the quality of services, and between each domain of quality of EMRs and total perception of quality of services. CONCLUSION: Adoption of a high quality of EMR has a significant impact on improving the quality of health care services.

Concomitant Presence of EGFR and ALK Fusion Gene Mutation in Adenocarcinoma of Lung: A Case Report and Review of the Literature.

Empirical evidence has long suggested that oncogenic driver mutations in non-small-cell lung cancer are mutually independent. However, recent studies reported in pertinent literature reveal that concomitant epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangement can occur in a subset of patients with NSCLC. In order to shed further light on this issue, we report a case of adenocarcinoma of lung harboring both EGFR mutation in exon 21 (L861Q) and ALK rearrangement. This allows us to speculate on likely molecular mechanisms underlying this uncommon phenomenon, while also offering some practical guidelines on the therapeutic options that could benefit patients diagnosed with this dual-positive tumor.

Telomeric Repeat Containing RNA (TERRA): Aging and Cancer.

Telomeric repeat containing RNAs (TERRA) are small RNA molecules synthesized from telomeric regions which were previously considered as silent genomic domains. In normal cells, these RNAs are transcribed in a direction from subtelomeric region towards the chromosome ends, but in case of cancer cells, their expression remains limited or absent. Telomerase is a rate limiting enzyme for cellular senescence, cancer and aging. Most of the studies deal with the manipulation of telomerase enzyme in cancer and aging either by synthetic oligonucleotide or by natural phytochemicals. Here, we collected evidences and discussed intensely about the bio-molecular structure of TERRA, naturally occurring ligands of telomerase, and their genetic and epigenetic regulations in aging associated diseases. Due to their capability to act as naturally occurring ligands of telomerase, these RNAs can overcome the limitations possessed by synthetic oligonucleotides, which are aimed against telomerase. Drugs specifically targeting TERRA molecules could modulate telomerase-mediated telomere lengthening. Thus, targeting TERRA-mediated regulation of telomerase would be a promising therapeutic strategy against cancer and age-associated diseases.