24 research outputs found
Effective adsorption of drug from aqueous solution using citric acid functionalized magnetite nanoparticles and their antibacterial studies
The synthesis of magnetite nanoparticles and their applications after surface modification have drawn in the eye of researchers toward it all through the previous a few times. In the present study, the synthesis of citric acid-modified magnetic nanoparticles has been reported. Numerous technical approaches such as x-ray diffraction, field emission scanning electron microscopy, thermogravimetric analysis and fourier transform infrared spectroscopy were accustomed to characterize these synthesized magnetite nanoparticles. The main emphasis of this examination was to study the adsorption behavior of these synthesized nanoparticles for ciprofloxacin drug from aqueous solution. The influences of various experimental parameters including pH, the contact time, amount of nanoparticles and initial concentration of ciprofloxacin drug, were investigated simultaneously. Moreover, isotherm study was observed to follow Langmuir isotherm model and the value of maximum adsorption capacity was 20.65 mg/g as calculated. Furthermore, the kinetic study was found to fit well with pseudo-second-order kinetics model. The overall study suggested that these functionalized magnetite nanoparticles can be utilized as a proficient tool for the adsorption of drug from aqueous solution. The antibacterial behavior of these drug loaded nanoparticles was also scrutinized
Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning
Understanding the spatial organization of tissues is of critical importance for both basic and translational research. While recent advances in tissue imaging are opening an exciting new window into the biology of human tissues, interpreting the data that they create is a significant computational challenge. Cell segmentation, the task of uniquely identifying each cell in an image, remains a substantial barrier for tissue imaging, as existing approaches are inaccurate or require a substantial amount of manual curation to yield useful results. Here, we addressed the problem of cell segmentation in tissue imaging data through large-scale data annotation and deep learning. We constructed TissueNet, an image dataset containing >1 million paired whole-cell and nuclear annotations for tissue images from nine organs and six imaging platforms. We created Mesmer, a deep learning-enabled segmentation algorithm trained on TissueNet that performs nuclear and whole-cell segmentation in tissue imaging data. We demonstrated that Mesmer has better speed and accuracy than previous methods, generalizes to the full diversity of tissue types and imaging platforms in TissueNet, and achieves human-level performance for whole-cell segmentation. Mesmer enabled the automated extraction of key cellular features, such as subcellular localization of protein signal, which was challenging with previous approaches. We further showed that Mesmer could be adapted to harness cell lineage information present in highly multiplexed datasets. We used this enhanced version to quantify cell morphology changes during human gestation. All underlying code and models are released with permissive licenses as a community resource
Kinetics and Mechanism of Oxidation of L-Arabinose by Pyridinium Chlorochromate in Aqueous Acetic Acid
We report in the present paper the kinetic and mechanistic study of the oxidation of L-arabinose by pyridinium chlorochromate C 5 H 5 NHCrO 3 Cl, The reaction has been carried out in aqueous acetic acid 50 % (v/v) medium in presence of perchloric acid at constant ionic strength. The reaction has been found to be first order with respect to each of the oxidant and substrate under pseudo-first order conditions. The reaction is catalyzed by acid and follows a first order dependence on H
ion concentration. The ionic strength variation has no effect on the reaction rate. The decreases in dielectric constant of the medium increase the rate of reaction. A 1:1 stoichiometry is observed in the oxidation and the reaction rate is not retarded by the addition of radical trapping agent acrylonitrile. Effect of temperature on the rate of oxidation has been studied to show the validity of Arhenius equation and various activation parameters have been computed. The products are identified to be L-erythrose and formic acid. On the observed facts a hydride ion transfer mechanism is proposed.Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΊΠΈΠ½Π΅ΡΠΈΠΊΠΈ ΠΈ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠ° ΠΎΠΊΠΈΡΠ»Π΅Π½ΠΈΡ L-Π°ΡΠ°Π±ΠΈΠ½ΠΎΠ·Ρ Ρ
Π»ΠΎΡΡ
ΡΠΎΠΌΠ°ΡΠΎΠΌ ΠΏΠΈΡΠΈΠ΄ΠΈΠ½Π° (C5H5NHCrO3Cl) Π² Π²ΠΎΠ΄Π½ΠΎΠΌ ΡΠ°ΡΡΠ²ΠΎΡΠ΅ ΡΠΊΡΡΡΠ½ΠΎΠΉ ΠΊΠΈΡΠ»ΠΎΡΡ 50 % ΠΎΠ±. Π² ΠΏΡΠΈΡΡΡΡΡΠ²ΠΈΠΈ Ρ
Π»ΠΎΡΠ½ΠΎΠΉ ΠΊΠΈΡΠ»ΠΎΡΡ ΠΏΡΠΈ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠΉ ΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΈΠ»Π΅. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΠ΅Π°ΠΊΡΠΈΡ ΠΈΠΌΠ΅Π΅Ρ ΠΏΠ΅ΡΠ²ΡΠΉ ΠΏΠΎΡΡΠ΄ΠΎΠΊ ΠΏΠΎ ΠΊΠ°ΠΆΠ΄ΠΎΠΌΡ ΠΈΠ· ΠΎΠΊΠΈΡΠ»ΠΈΡΠ΅Π»Π΅ΠΉ ΠΈ ΠΏΡΠ΅Π²Π΄ΠΎΠΏΠ΅ΡΠ²ΡΠΉ ΠΏΠΎΡΡΠ΄ΠΎΠΊ ΠΏΠΎ ΡΡΠ±ΡΡΡΠ°ΡΡ. Π Π΅Π°ΠΊΡΠΈΡ ΠΊΠ°ΡΠ°Π»ΠΈΠ·ΠΈΡΡΠ΅ΡΡΡ ΠΊΠΈΡΠ»ΠΎΡΠΎΠΉ, ΠΈ Π΅Ρ ΡΠΊΠΎΡΠΎΡΡΡ Π·Π°Π²ΠΈΡΠΈΡ ΠΎΡ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ ΠΈΠΎΠ½ΠΎΠ² Π+. Π‘ΠΊΠΎΡΠΎΡΡΡ ΡΠ΅Π°ΠΊΡΠΈΠΈ Π½Π΅ Π·Π°Π²ΠΈΡΠΈΡ ΠΎΡ ΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΈΠ»Ρ ΡΠ°ΡΡΠ²ΠΎΡΠ° ΠΈ ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°Π΅ΡΡΡ Ρ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΠ΅ΠΌ Π΄ΠΈΡΠ»Π΅ΠΊΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΡΠΎΠ½ΠΈΡΠ°Π΅ΠΌΠΎΡΡΠΈ ΡΠ΅Π°ΠΊΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΡΠ΅Π΄Ρ. ΠΡΠΈ ΡΡΠ΅Ρ
ΠΈΠΎΠΌΠ΅ΡΡΠΈΠΈ 1:1 Π½Π°Π±Π»ΡΠ΄Π°Π»ΠΎΡΡ ΠΎΠΊΠΈΡΠ»Π΅Π½ΠΈΠ΅ ΠΈ ΠΎΡΡΡΡΡΡΠ²ΡΠ΅Ρ ΡΠΎΡΠΌΠΎΠΆΠ΅Π½ΠΈΠ΅ ΡΠ΅Π°ΠΊΡΠΈΠΈ ΠΏΡΠΈ Π΄ΠΎΠ±Π°Π²Π»Π΅Π½ΠΈΠΈ Π°ΠΊΡΠΈΠ»ΠΎΠ½ΠΈΡΡΠΈΠ»Π° Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ Π»ΠΎΠ²ΡΡΠΊΠΈ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΠΎΠ². ΠΠ·ΡΡΠ΅Π½ΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΡ Π½Π° ΡΠΊΠΎΡΠΎΡΡΡ ΠΎΠΊΠΈΡΠ»Π΅Π½ΠΈΡ ΠΈ ΡΠ°ΡΡΡΠΈΡΠ°Π½Ρ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΠΡΠ΅Π½ΠΈΡΡΠ°. ΠΡΠΎΠ΄ΡΠΊΡΠ°ΠΌΠΈ ΡΠ΅Π°ΠΊΡΠΈΠΈ ΡΠ²Π»ΡΡΡΡΡ L-ΡΡΠΈΡΡΠΎΠ·Π° ΠΈ ΠΌΡΡΠ°Π²ΡΠΈΠ½Π°Ρ ΠΊΠΈΡΠ»ΠΎΡΠ°. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΡ
Π΄Π°Π½Π½ΡΡ
ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌ ΡΠ΅Π°ΠΊΡΠΈΠΈ
Synthesis and anti-inflammatory activity evaluation of some sulfonamide and amidine derivatives of 4-aryl-3-(2 or 4-picolyl)-2-imino-4-thiazolines
1076-1082Condensation of 2-
and 4-picolylaminehydrochloride 2a,b
with (un) substituted phenacylthiocyanate 1a-d
gives 4-aryl-3-(2- or 4-picolyl)-2-imino-4-thiazolines 3a-h in moderate yields. Sulfonamide derivatives 4a-h have been synthesized by
condensation of 4-aryl-3-(2- or 4-picolyl)-2-imino-4-thiazolines 3a-h with methanesulfonylchloride in
good yields. Condensation of 2-cyanopyridine with thiazolines 3a, 3e and of 4-cyanopyridine with 3a,
c, e and h gives amidine derivatives 5a,
b and 6a-d respectively. Thiazoline
derivatives 3a-h, sulfonamide
derivatives 4a-h and amidine
derivatives 5a, b; 6a-d are characterized by IR, 1H
NMR, GC-MS spectral data and elemental analysis. Anti-inflammatory activity
evaluation of 3a-h, 4a-d, g-h, 5a,b and 6a-c using carageenan induced paw oedema assay at 50 mg/kg p.o. has
been carried out and compound 6a exhibited
anti-inflammatory activity comparable to standard drug ibuprofen
Recommended from our members
A robust and interpretable end-to-end deep learning model for cytometry data.
Cytometry technologies are essential tools for immunology research, providing high-throughput measurements of the immune cells at the single-cell level. Existing approaches in interpreting and using cytometry measurements include manual or automated gating to identify cell subsets from the cytometry data, providing highly intuitive results but may lead to significant information loss, in that additional details in measured or correlated cell signals might be missed. In this study, we propose and test a deep convolutional neural network for analyzing cytometry data in an end-to-end fashion, allowing a direct association between raw cytometry data and the clinical outcome of interest. Using nine large cytometry by time-of-flight mass spectrometry or mass cytometry (CyTOF) studies from the open-access ImmPort database, we demonstrated that the deep convolutional neural network model can accurately diagnose the latent cytomegalovirus (CMV) in healthy individuals, even when using highly heterogeneous data from different studies. In addition, we developed a permutation-based method for interpreting the deep convolutional neural network model. We were able to identify a CD27- CD94+ CD8+ T cell population significantly associated with latent CMV infection, confirming the findings in previous studies. Finally, we provide a tutorial for creating, training, and interpreting the tailored deep learning model for cytometry data using Keras and TensorFlow (https://github.com/hzc363/DeepLearningCyTOF)
Synthesis, anti-inflammatory and anticancer activity evaluation of some novel acridine derivatives
Condensation of 9-chloro-2,4-(un)substituted acridines (1aβc) with various amines (2aβe) and 9-isothiocyanato-
2,4-(un)substituted acridines (4a,b) with different amines (2a,b,d,e) gave condensed products 3aβo and 5aβg respectively. Compounds 3aβo and 5aβg were screened for anti-inflammatory activity at a dose of 50 mg/kg p.o. Compound 3e exhibited 41.17% anti-inflammatory activity which is better than most commonly used standard drug ibuprofen which showed 39% anti-inflammatory (at 50 mg/kg p.o.) activity. Anticancer activity evaluation of compounds 3aβo and 5aβg was carried out against a small panel of human cancer cell lines and compounds 3g, 3m and 5g exhibited good anticancer activity against breast (MCF-7), liver (HEP-2), colon (COLO-205, 502713, HCT-15), lung (A-549)and neuroblastoma (IMR-32) cancer cell lines at a concentration of 1οΏ½ 10οΏ½5 M
Solvent free synthesis, anti-inflammatory and anticancer activity evaluation of tricyclic and tetracyclic benzimidazole derivatives
Heterocyclic benzimidazole derivatives 3aβh, 5aβc and 7aβd have been synthesized by condensation of succinic acid (1) homophthalic acid (4) and 2,3-pyrazinedicarboxlic acid (6) with various substituted diamines under microwave irradiation in good yields. Structures assigned to 3aβh, 5aβc and 7aβd are fully supported by spectral data. All these compounds were screened for anti-inflammatory and anticancer activities. At a dose of 50 mg/kg po compounds 3b (39.4%) and 3c (39.2%) exhibited anti-inflammatory
activity, comparable to standard ibuprofen which showed 39% activity at 50 mg/kg po and compound 7c exhibit good anticancer activity against ovary (IGR-OV-1), breast (MCF-7) and CNS(SF-295) human cancer cell lines
Kinetics and Mechanism of Oxidation of L-Arabinose by Pyridinium Chlorochromate in Aqueous Acetic Acid
We report in the present paper the kinetic and mechanistic study of the oxidation of L-arabinose by pyridinium chlorochromate C 5 H 5 NHCrO 3 Cl, The reaction has been carried out in aqueous acetic acid 50 % (v/v) medium in presence of perchloric acid at constant ionic strength. The reaction has been found to be first order with respect to each of the oxidant and substrate under pseudo-first order conditions. The reaction is catalyzed by acid and follows a first order dependence on H
ion concentration. The ionic strength variation has no effect on the reaction rate. The decreases in dielectric constant of the medium increase the rate of reaction. A 1:1 stoichiometry is observed in the oxidation and the reaction rate is not retarded by the addition of radical trapping agent acrylonitrile. Effect of temperature on the rate of oxidation has been studied to show the validity of Arhenius equation and various activation parameters have been computed. The products are identified to be L-erythrose and formic acid. On the observed facts a hydride ion transfer mechanism is proposed.Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΠ·ΡΡΠ΅Π½ΠΈΡ ΠΊΠΈΠ½Π΅ΡΠΈΠΊΠΈ ΠΈ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠ° ΠΎΠΊΠΈΡΠ»Π΅Π½ΠΈΡ L-Π°ΡΠ°Π±ΠΈΠ½ΠΎΠ·Ρ Ρ
Π»ΠΎΡΡ
ΡΠΎΠΌΠ°ΡΠΎΠΌ ΠΏΠΈΡΠΈΠ΄ΠΈΠ½Π° (C5H5NHCrO3Cl) Π² Π²ΠΎΠ΄Π½ΠΎΠΌ ΡΠ°ΡΡΠ²ΠΎΡΠ΅ ΡΠΊΡΡΡΠ½ΠΎΠΉ ΠΊΠΈΡΠ»ΠΎΡΡ 50 % ΠΎΠ±. Π² ΠΏΡΠΈΡΡΡΡΡΠ²ΠΈΠΈ Ρ
Π»ΠΎΡΠ½ΠΎΠΉ ΠΊΠΈΡΠ»ΠΎΡΡ ΠΏΡΠΈ ΠΏΠΎΡΡΠΎΡΠ½Π½ΠΎΠΉ ΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΈΠ»Π΅. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΠ΅Π°ΠΊΡΠΈΡ ΠΈΠΌΠ΅Π΅Ρ ΠΏΠ΅ΡΠ²ΡΠΉ ΠΏΠΎΡΡΠ΄ΠΎΠΊ ΠΏΠΎ ΠΊΠ°ΠΆΠ΄ΠΎΠΌΡ ΠΈΠ· ΠΎΠΊΠΈΡΠ»ΠΈΡΠ΅Π»Π΅ΠΉ ΠΈ ΠΏΡΠ΅Π²Π΄ΠΎΠΏΠ΅ΡΠ²ΡΠΉ ΠΏΠΎΡΡΠ΄ΠΎΠΊ ΠΏΠΎ ΡΡΠ±ΡΡΡΠ°ΡΡ. Π Π΅Π°ΠΊΡΠΈΡ ΠΊΠ°ΡΠ°Π»ΠΈΠ·ΠΈΡΡΠ΅ΡΡΡ ΠΊΠΈΡΠ»ΠΎΡΠΎΠΉ, ΠΈ Π΅Ρ ΡΠΊΠΎΡΠΎΡΡΡ Π·Π°Π²ΠΈΡΠΈΡ ΠΎΡ ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ ΠΈΠΎΠ½ΠΎΠ² Π+. Π‘ΠΊΠΎΡΠΎΡΡΡ ΡΠ΅Π°ΠΊΡΠΈΠΈ Π½Π΅ Π·Π°Π²ΠΈΡΠΈΡ ΠΎΡ ΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΈΠ»Ρ ΡΠ°ΡΡΠ²ΠΎΡΠ° ΠΈ ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°Π΅ΡΡΡ Ρ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΠ΅ΠΌ Π΄ΠΈΡΠ»Π΅ΠΊΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΡΠΎΠ½ΠΈΡΠ°Π΅ΠΌΠΎΡΡΠΈ ΡΠ΅Π°ΠΊΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΡΠ΅Π΄Ρ. ΠΡΠΈ ΡΡΠ΅Ρ
ΠΈΠΎΠΌΠ΅ΡΡΠΈΠΈ 1:1 Π½Π°Π±Π»ΡΠ΄Π°Π»ΠΎΡΡ ΠΎΠΊΠΈΡΠ»Π΅Π½ΠΈΠ΅ ΠΈ ΠΎΡΡΡΡΡΡΠ²ΡΠ΅Ρ ΡΠΎΡΠΌΠΎΠΆΠ΅Π½ΠΈΠ΅ ΡΠ΅Π°ΠΊΡΠΈΠΈ ΠΏΡΠΈ Π΄ΠΎΠ±Π°Π²Π»Π΅Π½ΠΈΠΈ Π°ΠΊΡΠΈΠ»ΠΎΠ½ΠΈΡΡΠΈΠ»Π° Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ Π»ΠΎΠ²ΡΡΠΊΠΈ ΡΠ°Π΄ΠΈΠΊΠ°Π»ΠΎΠ². ΠΠ·ΡΡΠ΅Π½ΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΡ Π½Π° ΡΠΊΠΎΡΠΎΡΡΡ ΠΎΠΊΠΈΡΠ»Π΅Π½ΠΈΡ ΠΈ ΡΠ°ΡΡΡΠΈΡΠ°Π½Ρ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΡ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΠΡΠ΅Π½ΠΈΡΡΠ°. ΠΡΠΎΠ΄ΡΠΊΡΠ°ΠΌΠΈ ΡΠ΅Π°ΠΊΡΠΈΠΈ ΡΠ²Π»ΡΡΡΡΡ L-ΡΡΠΈΡΡΠΎΠ·Π° ΠΈ ΠΌΡΡΠ°Π²ΡΠΈΠ½Π°Ρ ΠΊΠΈΡΠ»ΠΎΡΠ°. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΡ
Π΄Π°Π½Π½ΡΡ
ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌ ΡΠ΅Π°ΠΊΡΠΈΠΈ