Browse Articles

Spectrophotometric comparison of 4-Nitrophenyl carbonates & carbamates as base-labile protecting groups

Kocalar et al. | Dec 12, 2022

Spectrophotometric comparison of 4-Nitrophenyl carbonates & carbamates as base-labile protecting groups

In organic synthesis, protecting groups are derivatives of reactive functionalities that play a key role in ensuring chemoselectivity of chemical transformations. To protect alcohols and amines, acid-labile tert-butyloxycarbonyl protecting groups are often employed but are avoided when the substrate is acid-sensitive. Thus, orthogonal base-labile protecting groups have been in demand to enable selective deprotection and to preserve the reactivity of acid-sensitive substrates. To meet this demand, we present 4-nitrophenyl carbonates and carbamates as orthogonal base-labile protecting group strategies.

Read More...

Testing the Effects of Salep Derived From the Tubers of Orchis mascula, Aloe vera, and Alpha-chymotrypsin on Wound Healing in Drosophila melanogaster Larvae

Halder et al. | Sep 09, 2019

Testing the Effects of Salep Derived From the Tubers of <em>Orchis mascula</em>, <em>Aloe vera</em>, and Alpha-chymotrypsin on Wound Healing in <em>Drosophila melanogaster</em> Larvae

Aloe vera and alpha-chymotrypsin have been used in are known for their various wound healing properties. Halder et al hypothesized that these treatments would enhance wound healing in Drosophila melanogaster larvae over 2 weeks by decreasing wound size more effectively compared to controls. The results of two of the treatment groups, Salep and Aloe vera, yielded wound sizes small enough to present a significant percent decrease when compared with the wound sizes of the control group. Their results show support that both Salep and Aloe vera were effective for enhancing wound healing in epithelial cells in D. melanogaster larvae.

Read More...

Quantitative analysis and development of alopecia areata classification frameworks

Dubey et al. | Jun 03, 2024

Quantitative analysis and development of alopecia areata classification frameworks

This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.

Read More...

Combined Progestin-Estrogenic Contraceptive Pills May Promote Growth in Crop-Plants

Saha et al. | Feb 21, 2020

Combined Progestin-Estrogenic Contraceptive Pills May Promote Growth in Crop-Plants

Ethinyl estradiol and progestin norgestrel are commonly present in contraceptive tablets and it is unknown how they affect the environment. In this study, the authors investigate the role that ethinyl estradiol and progestin norgestrel have on the growth of flowering plants. The percentage germination, embryonic and adventitious tissue proliferation, root length, and shoot length were measured in V. radiata and T. aestivum treated with each compound and results demonstrate that ethinyl estradiol and progestin norgestrel can induce growth in both plants at certain concentrations. These findings have important implications as societal use of chemicals increases and more make their way into the environment.

Read More...

Estimation of cytokines in PHA-activated mononuclear cells isolated from human peripheral and cord blood

Subbiah et al. | Mar 09, 2022

Estimation of cytokines in PHA-activated mononuclear cells isolated from human peripheral and cord blood

In this study, the authors investigated the time-dependent cytokine secretion ability of phyto-hemagglutinin (PHA)-activated T cells derived from human peripheral (PB) and cord blood (CB). They hypothesized that the anti-inflammatory cytokine, IL-10, and pro-inflammatory cytokine, TNFα, levels would be higher in PHA-activated T cells obtained from PB as compared to the levels obtained from CB and would decrease over time. Upon PHA-activation, the IL-10 levels were relatively high while the TNFα levels decreased, making these findings applicable in therapeutic treatments e.g., rheumatoid arthritis, psoriasis, and organ transplantation.

Read More...

Developing anticholinergic drugs for the treatment of asthma with improved efficacy

Wong et al. | Jul 05, 2023

Developing anticholinergic drugs for the treatment of asthma with improved efficacy
Image credit: Wong et al.

Anticholinergics are used in treating asthma, a chronic inflammation of the airways. These drugs block human M1 and M2 muscarinic acetylcholine receptors, inhibiting bronchoconstriction. However, studies have reported complications of anticholinergic usage, such as exacerbated eosinophil production and worsened urinary retention. Modification of known anticholinergics using bioisosteric replacements to increase efficacy could potentially minimize these complications. The present study focuses on identifying viable analogs of anticholinergics to improve binding energy to the receptors compared to current treatment options. Glycopyrrolate (G), ipratropium (IB), and tiotropium bromide (TB) were chosen as parent drugs of interest, due to the presence of common functional groups within the molecules, specifically esters and alcohols. Docking score analysis via AutoDock Vina was used to evaluate the binding energy between drug analogs and the muscarinic acetylcholine receptors. The final results suggest that G-A3, IB-A3, and TB-A1 are the most viable analogs, as binding energy was improved when compared to the parent drug. G-A4, IB-A4, IB-A5, TB-A3, and TB-A4 are also potential candidates, although there were slight regressions in binding energy to both muscarinic receptors for these analogs. By researching the effects of bioisosteric replacements of current anticholinergics, it is evident that there is a potential to provide asthmatics with more effective treatment options.

Read More...

Association of agenesis of the corpus callosum with epilepsy and anticonvulsant drug treatment

Steger et al. | Feb 21, 2023

Association of agenesis of the corpus callosum with epilepsy and anticonvulsant drug treatment
Image credit: Robina Weermeijer on Unsplash

Agenesis of the Corpus Callosum (ACC) is a birth defect where an infant’s corpus callosum, the structure linking the brain’s two hemispheres to allow interhemispheric communication, fails to develop in a typical manner during pregnancy. Existing research on the connection between ACC and epilepsy leaves significant gaps, due to the lack of focused investigation. One important gap is the degree to which ACC may impact the course of epilepsy treatment and outcomes. The present study was conducted to test the hypotheses that epilepsy is highly prevalent among individuals with ACC, and that those with both ACC and epilepsy have a lower response rate to anticonvulsant drugs than other patients treated with anticonvulsant drugs. A weighted average of epilepsy rates was calculated from a review of existing literature, which supported the hypothesis that epilepsy was more common among individuals with ACC (25.11%) than in the general population (1.2%). An empirical survey administered to 57 subjects or parents of subjects showed that rate of intractable epilepsy among study subjects with both ACC and epilepsy was substantially higher than the rate found in the general population, indicating that individuals with both conditions had a lower response rate to the anticonvulsant drugs. This study contributes novel results regarding the potential for concurrence of ACC and epilepsy to interfere with anticonvulsant drug treatment. We also discuss implications for how medical professionals may use the findings of this study to add depth to their treatment decisions.

Read More...

Recognition of animal body parts via supervised learning

Kreiman et al. | Oct 28, 2023

Recognition of animal body parts via supervised learning
Image credit: Kreiman et al. 2023

The application of machine learning techniques has facilitated the automatic annotation of behavior in video sequences, offering a promising approach for ethological studies by reducing the manual effort required for annotating each video frame. Nevertheless, before solely relying on machine-generated annotations, it is essential to evaluate the accuracy of these annotations to ensure their reliability and applicability. While it is conventionally accepted that there cannot be a perfect annotation, the degree of error associated with machine-generated annotations should be commensurate with the error between different human annotators. We hypothesized that machine learning supervised with adequate human annotations would be able to accurately predict body parts from video sequences. Here, we conducted a comparative analysis of the quality of annotations generated by humans and machines for the body parts of sheep during treadmill walking. For human annotation, two annotators manually labeled six body parts of sheep in 300 frames. To generate machine annotations, we employed the state-of-the-art pose-estimating library, DeepLabCut, which was trained using the frames annotated by human annotators. As expected, the human annotations demonstrated high consistency between annotators. Notably, the machine learning algorithm also generated accurate predictions, with errors comparable to those between humans. We also observed that abnormal annotations with a high error could be revised by introducing Kalman Filtering, which interpolates the trajectory of body parts over the time series, enhancing robustness. Our results suggest that conventional transfer learning methods can generate behavior annotations as accurate as those made by humans, presenting great potential for further research.

Read More...

Search Articles

Search articles by title, author name, or tags

Clear all filters

Popular Tags

Browse by school level