| 1. |
|
|
| 2. |
- Kar, Rohan, et al.
(författare)
-
The FBXW7-NOTCH interactome : A ubiquitin proteasomal system-induced crosstalk modulating oncogenic transformation in human tissues
- 2021
-
Ingår i: Cancer Reports. - : John Wiley & Sons. - 2573-8348. ; 4:4
-
Forskningsöversikt (refereegranskat)abstract
- Background Ubiquitin ligases or E3 ligases are well programmed to regulate molecular interactions that operate at a post-translational level. Skp, Cullin, F-box containing complex (or SCF complex) is a multidomain E3 ligase known to mediate the degradation of a wide range of proteins through the proteasomal pathway. The three-dimensional domain architecture of SCF family proteins suggests that it operates through a novel and adaptable "super-enzymatic" process that might respond to targeted therapeutic modalities in cancer. Recent findings Several F-box containing proteins have been characterized either as tumor suppressors (FBXW8, FBXL3, FBXW8, FBXL3, FBXO1, FBXO4, and FBXO18) or as oncogenes (FBXO5, FBXO9, and SKP2). Besides, F-box members like beta TrcP1 and beta TrcP2, the ones with context-dependent functionality, have also been studied and reported. FBXW7 is a well-studied F-box protein and is a tumor suppressor. FBXW7 regulates the activity of a range of substrates, such as c-Myc, cyclin E, mTOR, c-Jun, NOTCH, myeloid cell leukemia sequence-1 (MCL1), AURKA, NOTCH through the well-known ubiquitin-proteasome system (UPS)-mediated degradation pathway. NOTCH signaling is a primitive pathway that plays a crucial role in maintaining normal tissue homeostasis. FBXW7 regulates NOTCH protein activity by controlling its half-life, thereby maintaining optimum protein levels in tissue. However, aberrations in the FBXW7 or NOTCH expression levels can lead to poor prognosis and detrimental outcomes in patients. Therefore, the FBXW7-NOTCH axis has been a subject of intense study and research over the years, especially around the interactome's role in driving cancer development and progression. Several studies have reported the effect of FBXW7 and NOTCH mutations on normal tissue behavior. The current review attempts to critically analyze these mutations prognostic value in a wide range of tumors. Furthermore, the review summarizes the recent findings pertaining to the FBXW7 and NOTCH interactome and its involvement in phosphorylation-related events, cell cycle, proliferation, apoptosis, and metastasis. Conclusion The review concludes by positioning FBXW7 as an effective diagnostic marker in tumors and by listing out recent advancements made in cancer therapeutics in identifying protocols targeting the FBXW7-NOTCH aberrations in tumors.
|
|
| 3. |
- Singh, Sachin Kumar, et al.
(författare)
-
Soil erosion control from trash residues at varying land slopes under simulated rainfall conditions
- 2023
-
Ingår i: Mathematical Biosciences and Engineering. - : American Institute of Mathematical Sciences. - 1551-0018. ; 20:6, s. 11403-11428
-
Tidskriftsartikel (refereegranskat)abstract
- Trash mulches are remarkably effective in preventing soil erosion, reducing runoff-sediment transport-erosion, and increasing infiltration. The study was carried out to observe the sediment outflow from sugar cane leaf (trash) mulch treatments at selected land slopes under simulated rainfall conditions using a rainfall simulator of size 10 m × 1.2 m × 0.5 m with the locally available soil material collected from Pantnagar. In the present study, trash mulches with different quantities were selected to observe the effect of mulching on soil loss reduction. The number of mulches was taken as 6, 8 and 10 t/ha, three rainfall intensities viz. 11, 13 and 14.65 cm/h at 0, 2 and 4% land slopes were selected. The rainfall duration was fixed (10 minutes) for every mulch treatment. The total runoff volume varied with mulch rates for constant rainfall input and land slope. The average sediment concentration (SC) and sediment outflow rate (SOR) increased with the increasing land slope. However, SC and outflow decreased with the increasing mulch rate for a fixed land slope and rainfall intensity. The SOR for no mulch-treated land was higher than trash mulch-treated lands. Mathematical relationships were developed for relating SOR, SC, land slope, and rainfall intensity for a particular mulch treatment. It was observed that SOR and average SC values correlated with rainfall intensity and land slope for each mulch treatment. The developed models' correlation coefficients were more than 90%.
|
|
| 4. |
- Singh, Vijay Kumar, et al.
(författare)
-
Novel Genetic Algorithm (GA) based hybrid machine learning-pedotransfer Function (ML-PTF) for prediction of spatial pattern of saturated hydraulic conductivity
- 2022
-
Ingår i: Engineering Applications of Computational Fluid Mechanics. - : Taylor & Francis. - 1994-2060 .- 1997-003X. ; 16:1, s. 1082-1099
-
Tidskriftsartikel (refereegranskat)abstract
- Saturated hydraulic conductivity (Ks) is an important soil characteristic that controls water moves through the soil. On the other hand, its measurement is difficult, time-consuming, and expensive; hence Pedotransfer Functions (PTFs) are commonly used for its estimation. Despite significant development over the years, the PTFs showed poor performance in predicting Ks. Using Genetic Algorithm (GA), two hybrid Machine Learning based PTFs (ML-PTF), i.e. a combination of GA with Multilayer Perceptron (MLP-GA) and Support Vector Machine (SVM-GA), were proposed in this study. We compared the performances of four machine learning algorithms for different sets of predictors. The predictor combination containing sand, clay, Field Capacity, and Wilting Point showed the highest accuracy for all the ML-PTFs. Among the ML-PTFs, the SVM-GA algorithm outperformed the rest of the PTFs. It was noticed that the SVM-GA PTF demonstrated higher efficiency than the MLP-GA algorithm. The reference model for hydraulic conductivity prediction was selected as the SVM-GA PTF paired with the K-5 predictor variables. The proposed PTFs were compared with 160 models from past literature. It was found that the algorithms advocated were an improvement over these PTFs. The current model would help in efficient spatio-temporal measurement of hydraulic conductivity using pre-available databases.
|
|
| 5. |
- Allam, Venkata Sita Rama Raju, et al.
(författare)
-
Nutraceuticals and mitochondrial oxidative stress : bridging the gap in the management of bronchial asthma
- 2022
-
Ingår i: Environmental Science and Pollution Research. - : Springer Nature. - 0944-1344 .- 1614-7499. ; 29:42, s. 62733-62754
-
Forskningsöversikt (refereegranskat)abstract
- Asthma is a chronic inflammatory disease primarily characterized by inflammation and reversible bronchoconstriction. It is currently one of the leading causes of morbidity and mortality in the world. Oxidative stress further complicates the pathology of the disease. The current treatment strategies for asthma mainly involve the use of anti-inflammatory agents and bronchodilators. However, long-term usage of such medications is associated with severe adverse effects and complications. Hence, there is an urgent need to develop newer, novel, and safe treatment modalities for the management of asthma. This has therefore prompted further investigations and detailed research to identify and develop novel therapeutic interventions from potent untapped resources. This review focuses on the significance of oxidative stressors that are primarily derived from both mitochondrial and non-mitochondrial sources in initiating the clinical features of asthma. The review also discusses the biological scavenging system of the body and factors that may lead to its malfunction which could result in altered states. Furthermore, the review provides a detailed insight into the therapeutic role of nutraceuticals as an effective strategy to attenuate the deleterious effects of oxidative stress and may be used in the mitigation of the cardinal features of bronchial asthma.
|
|
| 6. |
- Klionsky, Daniel J., et al.
(författare)
-
Guidelines for the use and interpretation of assays for monitoring autophagy
- 2012
-
Ingår i: Autophagy. - : Informa UK Limited. - 1554-8635 .- 1554-8627. ; 8:4, s. 445-544
-
Forskningsöversikt (refereegranskat)abstract
- In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.
|
|
| 7. |
- Kumar, Amarjeet, et al.
(författare)
-
Development of Novel Hybrid Models for Prediction of Drought-and Stress-Tolerance Indices in Teosinte Introgressed Maize Lines Using Artificial Intelligence Techniques
- 2022
-
Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 14:4
-
Tidskriftsartikel (refereegranskat)abstract
- Maize (Zea mays subsp. mays) is a staple food crop in the world. Drought is one of the most common abiotic challenges that maize faces when it comes to growth, development, and production. Further knowledge of drought tolerance could aid with maize production. However, there has been less study focused on investigating in depth the drought tolerance of inbred maize lines using artificial intelligence techniques. In this study, multi-layer perceptron (MLP), support vector machine (SVM), genetic algorithm-based multi-layer perceptron (MLP-GA), and genetic algorithm-based support vector machine (SVM-GA) hybrid artificial intelligence algorithms were used for the prediction of drought tolerance and stress tolerance indices in teosinte maize lines. Correspondingly, the gamma test technique was applied to determine efficient input and output vectors. The potential of the developed models was evaluated based on statistical indices and graphical representations. The results of the gamma test based on the least value of gamma and standard error indices show that days of anthesis (DOA), days of silking (DOS), yield index (YI), and gross yield per plant (GYP) information vector arrangements were determined to be an efficient information vector combination for the drought-tolerance index (DTI) as well as the stress-tolerance index (STI). The MLP, SVM, MLP-GA, and SVM-GA algorithms’ results were compared based on statistical indices and visual interpretations that have satisfactorily predict the drought-tolerance index and stress-tolerance index in maize crops. The genetic algorithm-based hybrid models (MLP-GA and SVM-GA) were found to better predict the drought-tolerance index and stress-tolerance index in maize crops. Similarly, the SVM-GA model was found to have the highest potential to forecast the DTI and STI in maize crops, compared to the MLP, SVM, and MLP-GA models.
|
|
| 8. |
- Kumar, Deepak, et al.
(författare)
-
Multi-ahead electrical conductivity forecasting of surface water based on machine learning algorithms
- 2023
-
Ingår i: Applied water science. - : Springer Nature. - 2190-5487 .- 2190-5495. ; 13:10
-
Tidskriftsartikel (refereegranskat)abstract
- The present research work focused on predicting the electrical conductivity (EC) of surface water in the Upper Ganga basin using four machine learning algorithms: multilayer perceptron (MLP), co-adaptive neuro-fuzzy inference system (CANFIS), random forest (RF), and decision tree (DT). The study also utilized the gamma test for selecting appropriate input and output combinations. The results of the gamma test revealed that total hardness (TH), magnesium (Mg), and chloride (Cl) parameters were suitable input variables for EC prediction. The performance of the models was evaluated using statistical indices such as Percent Bias (PBIAS), correlation coefficient (R), Willmott’s index of agreement (WI), Index of Agreement (PI), root mean square error (RMSE) and Legate-McCabe Index (LMI). Comparing the results of the EC models using these statistical indices, it was observed that the RF model outperformed the other algorithms. During the training period, the RF algorithm has a small positive bias (PBIAS = 0.11) and achieves a high correlation with the observed values (R = 0.956). Additionally, it shows a low RMSE value (360.42), a relatively good coefficient of efficiency (CE = 0.932), PI (0.083), WI (0.908) and LMI (0.083). However, during the testing period, the algorithm’s performance shows a small negative bias (PBIAS = − 0.46) and a good correlation (R = 0.929). The RMSE value decreases significantly (26.57), indicating better accuracy, the coefficient of efficiency remains high (CE = 0.915), PI (0.033), WI (0.965) and LMI (− 0.028). Similarly, the performance of the RF algorithm during the training and testing periods in Prayagraj. During the training period, the RF algorithm shows a PBIAS of 0.50, indicating a small positive bias. It achieves an RMSE of 368.3, R of 0.909, CE of 0.872, PI of 0.015, WI of 0.921, and LMI of 0.083. During the testing period, the RF algorithm demonstrates a slight negative bias with a PBIAS of − 0.06. The RMSE reduces significantly to 24.1, indicating improved accuracy. The algorithm maintains a high correlation (R = 0.903) and a good coefficient of efficiency (CE = 0.878). The index of agreement (PI) increases to 0.035, suggesting a better fit. The WI is 0.960, indicating high accuracy compared to the mean value, while the LMI decreases slightly to − 0.038. Based on the comparative results of the machine learning algorithms, it was concluded that RF performed better than DT, CANFIS, and MLP. The study recommended using the current month’s total hardness (TH), magnesium (Mg), and chloride (Cl) parameters as input variables for multi-ahead forecasting of electrical conductivity (ECt+1, ECt+2, and ECt+3) in future studies in the Upper Ganga basin. The findings also indicated that RF and DT models had superior performance compared to MLP and CANFIS models. These models can be applied for multi-ahead forecasting of monthly electrical conductivity at both Varanasi and Prayagraj stations in the Upper Ganga basin.
|
|
| 9. |
- Mehta, Meenu, et al.
(författare)
-
Recent trends of NFkB decoy oligodeoxynucleotide-based nanotherapeutics in lung diseases
- 2021
-
Ingår i: Journal of Controlled Release. - : Elsevier. - 0168-3659 .- 1873-4995. ; 337, s. 629-644
-
Forskningsöversikt (refereegranskat)abstract
- Nuclear factor Kappa B (NFicB) is a unique protein complex that plays a major role in lung inflammation and respi-ratory dysfunction. The NFicB signaling pathway, therefore becomes an avenue for the development of potential pharmacological interventions, especially in situations where chronic inflammation is often constitutively active and plays a key role in the pathogenesis and progression of the disease. NFicB decoy oligodeoxynucleotides (ODNs) are double-stranded and carry NFicB binding sequences. They prevent the formation of NFicB-mediated inflammatory cytokines and thus have been employed in the treatment of a variety of chronic inflammatory diseases. However, the systemic administration of naked decoy ODNs restricts their therapeutic effectiveness because of their poor pharmacokinetic profile, instability, degradation by cellular enzymes and their low cellular uptake. Both structural modification and nanotechnology have shown promising results in enhancing the pharmacokinetic profiles of potent therapeutic substances and have also shown great potential in the treatment of respiratory diseases such as asthma, chronic obstructive pulmonary disease and cystic fibrosis. In this review, we examine the contribution of NFicB activation in respiratory diseases and recent advancements in the thera-peutic use of decoy ODNs. In addition, we also highlight the limitations and challenges in use of decoy ODNs as therapeutic molecules, cellular uptake of decoy ODNs, and the current need for novel delivery systems to provide efficient delivery of decoy ODNs. Furthermore, this review provides a common platform for discussion on the existence of decoy ODNs, as well as outlining perspectives on the latest generation of delivery systems that encapsulate decoy ODNs and target NFxB in respiratory diseases.
|
|
| 10. |
- Paudel, Keshav Raj, et al.
(författare)
-
Recent Advances in Chronotherapy Targeting Respiratory Diseases
- 2021
-
Ingår i: Pharmaceutics. - : MDPI. - 1999-4923. ; 13:12
-
Forskningsöversikt (refereegranskat)abstract
- Respiratory diseases contribute to a significant percentage of mortality and morbidity worldwide. The circadian rhythm is a natural biological process where our bodily functions align with the 24 h oscillation (sleep-wake cycle) process and are controlled by the circadian clock protein/gene. Disruption of the circadian rhythm could alter normal lung function. Chronotherapy is a type of therapy provided at specific time intervals based on an individual's circadian rhythm. This would allow the drug to show optimum action, and thereby modulate its pharmacokinetics to lessen unwanted or unintended effects. In this review, we deliberated on the recent advances employed in chrono-targeted therapeutics for chronic respiratory diseases.
|
|
