Molecular investigation in support of the clinical decision: Early diagnosis and detection of pathogen drug resistance

2008 ◽  
Author(s):  
Paul Cristea ◽  
Rodica Tuduce
Keyword(s):  
Drug Resistance ◽  
Early Diagnosis ◽  
Clinical Decision ◽  
Molecular Investigation

scholarly journals A Review of ULK1-Mediated Autophagy in Drug Resistance of Cancer

Cancers ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 352 ◽  
Author(s):  
Li Liu ◽  
Lu Yan ◽  
Ning Liao ◽  
Wan-Qin Wu ◽  
Jun-Ling Shi
Keyword(s):  
Drug Resistance ◽  
Early Diagnosis ◽  
Successful Treatment ◽  
Therapeutic Target ◽  
Crucial Role ◽  
Tumor Therapy ◽  
Therapeutic Effects ◽  
Cellular Functions ◽  
Serine Threonine Kinase ◽  
Threonine Kinase

The difficulty of early diagnosis and the development of drug resistance are two major barriers to the successful treatment of cancer. Autophagy plays a crucial role in several cellular functions, and its dysregulation is associated with both tumorigenesis and drug resistance. Unc-51-like kinase 1 (ULK1) is a serine/threonine kinase that participates in the initiation of autophagy. Many studies have indicated that compounds that directly or indirectly target ULK1 could be used for tumor therapy. However, reports of the therapeutic effects of these compounds have come to conflicting conclusions. In this work, we reviewed recent studies related to the effects of ULK1 on the regulation of autophagy and the development of drug resistance in cancers, with the aim of clarifying the mechanistic underpinnings of this therapeutic target.

scholarly journals Mining signaling flow to interpret mechanisms of synergy of drug combinations using deep graph neural networks

2021 ◽  
Author(s):  
Heming Zhang ◽  
Yixin Chen ◽  
Philip R Payne ◽  
Fuhai Li
Keyword(s):  
Drug Resistance ◽  
Signaling Pathways ◽  
Drug Combination ◽  
Drug Targets ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Signaling Network ◽  
Drug Combinations ◽  
Convolutional Network ◽  
Cancer Signaling

Complex signaling pathways/networks are believed to be responsible for drug resistance in cancer therapy. Drug combinations inhibiting multiple signaling targets within cancer-related signaling networks have the potential to reduce drug resistance. Deep learning models have been reported to predict drug combinations. However, these models are hard to be interpreted in terms of mechanism of synergy (MoS), and thus cannot well support the human-AI based clinical decision making. Herein, we proposed a novel computational model, DeepSignalingFlow, which seeks to address the preceding two challenges. Specifically, a graph convolutional network (GCN) was developed based on a core cancer signaling network consisting of 1584 genes, with gene expression and copy number data derived from 46 core cancer signaling pathways. The novel up-stream signaling-flow (from up-stream signaling to drug targets), and the down-stream signaling-flow (from drug targets to down-stream signaling), were designed using trainable weights of network edges. The numerical features (accumulated information due to the signaling-flows of the signaling network) of drug nodes that link to drug targets were then used to predict the synergy scores of such drug combinations. The model was evaluated using the NCI ALMANAC drug combination screening data. The evaluation results showed that the proposed DeepSignalingFlow model can not only predict drug combination synergy score, but also interpret potentially interpretable MoS of drug combinations.

scholarly journals Long non-coding RNAs towards precision medicine in gastric cancer: early diagnosis, treatment, and drug resistance

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Li Yuan ◽  
Zhi-Yuan Xu ◽  
Shan-Ming Ruan ◽  
Shaowei Mo ◽  
Jiang-Jiang Qin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Drug Resistance ◽  
Early Diagnosis ◽  
Precision Medicine ◽  
Non Coding Rnas

scholarly journals Penerapan Inferensi Backward Chaining Pada Sistem Pakar Diagnosa Awal Penyakit Tulang

2018 ◽  
Vol 5 (1) ◽  
pp. 50-60 ◽  
Author(s):  
Asti Herliana ◽  
Visqia Ade Setiawan ◽  
Rizki Tri Prasetio
Keyword(s):  
Decision Support ◽  
Early Diagnosis ◽  
Bone Disease ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
The Body ◽  
Public Knowledge ◽  
Web Based ◽  
Backward Chaining ◽  
Early Diagnose

Abstrak Tulang merupakan bagian yang sangat penting di dalam bagian ortopedi manusia. Tulang bukan hanya kerangka penguat tubuh tetapi juga merupakan bagian dari susunan sendi, sebagai pelindung tubuh, tempat melekatnya bagian ujung otot yang melekat pada tulang. Terbatasnya jumlah pakar Penyakit Tulang serta minimnya pengetahuan masyarakat tentang penyakit tulang menjadi kendala mengapa penyakit ini tidak mudah diatasi. Banyaknya gejala yang mirip untuk menentukan suatu penyakit Tulang. Dari masalah diatas maka dibuatlah aplikasi sistem pakar diagnosa awal penyakit tulang. Dari penelitian yang dilakukan menghasilkan sebuah perangkat lunak Sistem Pendukung Keputusan Klinis berbasis web untuk diagnosa Penyakit Tulang. Informasi yang dihasilkan adalah hasil diagnosa penyakit berdasarkan gejala-gejala yang dipilih oleh user. Hasil uji coba menunjukkan bahwa aplikasi ini layak dan dapat digunakan sebagai alat bantu para medis Penyakit Tulang dalam mendiagnosa awal. Kata Kunci : Sistem Pakar, Penyakit Tulang, Diagnosa awal, Backward Chaining , Web Progaming. Abstract Bone was a very important part in the human orthopedics. Bone is not only the body's reinforcement part, but it is also part of the joints, as a protector of the body, where the attachment of the muscle ends attached to the bone. The limited number of experts in Bone Disease and the lack of public knowledge about bone disease is the reason why this disease is not easy to overcome. The number of similar symptoms for a bone disease. From the above problems then made the application of expert systems early diagnosis of bone disease. From research conducted a software Clinical Decision Support System web-based for the diagnosis of Bone Disease. The resulting information is the result of diagnosis of the disease based on the symptoms chosen by the user. The results of the trial show this application is feasible and can be used as a tool of medical ailments of bone disease in early diagnosis. Keyword : Expert System, Bone Disease, Early Diagnose, Backward Chainning, Web Programming

scholarly journals Antenatal Diagnosis of Congenital Anomalies on Ultrasound Screening

2021 ◽  
Author(s):  
Callen Kwamboka Onyambu ◽  
Norah Mukiri Tharamba
Keyword(s):  
Decision Making ◽  
Early Diagnosis ◽  
Congenital Anomalies ◽  
Clinical Decision Making ◽  
Mode Of Delivery ◽  
Clinical Decision ◽  
Antenatal Visit ◽  
Ultrasound Screening ◽  
Antenatal Screening ◽  
Screening Programs

Congenital fetal anomalies contribute to the global burden of disease in children. Various screening programs have been used for antenatal screening of these anomalies. Screening targets low risk population and is usually done in the second trimester though some are done at the mother’s first antenatal visit especially in resource constrained setting. Mother’s who have had a previous pregnancy with congenital anomaly are given targeted elaborate screening. Early diagnosis of this anomalies can lead to early intervention and better outcomes. Diagnosis of the malformations also leads to clinical decision making on mode of delivery thereby avoiding birth related trauma to the mother and the baby. In case of lethal congenital anomalies early diagnosis aids in clinical decision making on the management of the pregnancy.

scholarly journals Role of CNK1, Ephrin B1, GPR19 and SMURF1 in breast cancer early diagnosis, metastasis and drug resistance

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Afnan Abdrabou ◽  
Sara Radwan ◽  
Reham El shimy ◽  
Hala El Mesallamy
Keyword(s):  
Breast Cancer ◽  
Drug Resistance ◽  
Early Diagnosis

Pyrosequencing(PSQ) in early diagnosis of CNS tuberculosis and determining drug resistance

2019 ◽  
Author(s):  
Abhinav Bhosle ◽  
Pratibha Singhal ◽  
Vibhor Pardasani ◽  
Prajay Lunia ◽  
Kanchan Ajbani ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Early Diagnosis ◽  
Cns Tuberculosis

ABCB1 gene polymorphism associated with clinical factors can predict drug-resistant tuberculosis

2017 ◽  
Vol 131 (15) ◽  
pp. 1831-1840 ◽  
Author(s):  
Yasmin Pontual ◽  
Vanessa S.S. Pacheco ◽  
Sérgio P. Monteiro ◽  
Marcel S.B. Quintana ◽  
Marli J.M. Costa ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Skin Color ◽  
Clinical Decision Making ◽  
Efflux Pump ◽  
Direct Sequencing ◽  
Previous Treatment ◽  
Clinical Decision ◽  
Control Group ◽  
Case Group ◽  
Abcb1 Gene

Polymorphism in the ABCB1 gene encoding P-glycoprotein, a transmembrane drug efflux pump, contributes to drug resistance and has been widely studied. However, their association with rifampicin and ethambutol resistance in tuberculosis (TB) patients is still unclear. Genotype/allele/haplotype frequencies in c.1236C > T (rs1128503), c.2677G > T/A (rs2032582), and c.3435C > T (rs1045642) were obtained from 218 patients. Of these, 80 patients with rifampicin and/or ethambutol resistance were selected as the case group and 138 patients were selected for the control group through the results of their culture and drug-sensitive tests. Patients aged <18 years and HIV-positive serologic tests were excluded. ABCB1 polymorphisms were determined using a PCR direct-sequencing approach, and restriction fragment length polymorphism (RFLP). A nomogram was constructed to simulate a combined prediction of the probability of anti-TB drug resistance, with factors including genotype c.1236C > T (rs1128503) (P=0.02), clinical form (P=0.03), previous treatment (P=0.01), and skin color (P=0.03), contributing up to 90% chance of developing anti-TB drug resistance. Considering genotype analyses, CT (rs1128503) demonstrated an increased chance of anti-TB drug resistance (odds ratio (OR): 2.34, P=0.02), while the analyses for ethambutol resistance revealed an association with a rare A allele (rs2032582) (OR: 12.91, P=0.01), the haplotype TTC (OR: 5.83, P=0.05), and any haplotype containing the rare A allele (OR: 7.17, P=0.04). ABCB1 gene polymorphisms in association with others risk factors contribute to anti-TB drug resistance, mainly ethambutol. The use of the nomogram described in the present study could contribute to clinical decision-making prior to starting TB treatment.

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