Validation of a Deep Learning Model for Detecting Chest Pathologies from Digital Chest Radiographs.

Purpose: Manual interpretation of chest radiographs is a challenging task and is prone to errors. An automated system capable of categorizing chest radiographs based on the pathologies identified could aid in the timely and efficient diagnosis of chest pathologies. Method: For this retrospective study, 4476 chest radiographs were collected between January and April 2021 from two tertiary care hospitals. Three expert radiologists established the ground truth, and all radiographs were analyzed using a deep-learning AI model to detect suspicious ROIs in the lungs, pleura, and cardiac regions. Three test readers (different from the radiologists who established the ground truth) independently reviewed all radiographs in two sessions (unaided and AI-aided mode) with a washout period of one month. Results: The model demonstrated an aggregate AUROC of 91.2% and a sensitivity of 88.4% in detecting suspicious ROIs in the lungs, pleura, and cardiac regions. These results outperform unaided human readers, who achieved an aggregate AUROC of 84.2% and sensitivity of 74.5% for the same task. When using AI, the aided readers obtained an aggregate AUROC of 87.9% and a sensitivity of 85.1%. The average time taken by the test readers to read a chest radiograph decreased by 21% (p < 0.01) when using AI. Conclusion: The model outperformed all three human readers and demonstrated high AUROC and sensitivity across two independent datasets. When compared to unaided interpretations, AI-aided interpretations were associated with significant improvements in reader performance and chest radiograph interpretation time.

Design, synthesis, and computational studies of phenylacetamides as antidepressant agents.

In the present work, a hit molecule obtained from zinc 'clean drug-like database' by systematically performed computational studies was modified chemically to obtain different derivatives (VS1-VS25). Structures of synthesized derivatives were confirmed by IR, 1H-NMR, 13C-NMR, 13C-DEPT, MS, and elemental analysis. All the synthesized compounds were biologically evaluated for their antidepressant activity by using tail suspension test and forced swimming test in albino mice. All these derivatives showed moderate to good antidepressant activity. The most potent compound (VS25) among the synthesized compounds showed better antidepressant potential than the standard drugs moclobemide, imipramine, and fluoxetine. To understand the time-dependent interactions of this most active compound with MAO-A molecular dynamics was carried out and reported here. Additionally, acute oral toxicity was performed for the most active compound as per OECD guidelines.

Combined 2D and 3D-QSAR, molecular modelling and docking studies of pyrazolodiazepinones as novel phosphodiesterase 2 inhibitors.

Selective inhibition of phosphodiesterase 2 (PDE2) in cells where it is located elevates cyclic guanosine monophosphate (cGMP) and acts as novel analgesic with antinociceptive activity. Three-dimensional quantitative structure-activity relationship (QSAR) studies for pyrazolodiazepinone inhibitors exhibiting PDE2 inhibition were performed using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA) and Topomer CoMFA, and two-dimensional QSAR study was performed using a Hologram QSAR (HQSAR) method. QSAR models were generated using training set of 23 compounds and were validated using test set of nine compounds. The optimum partial least squares (PLS) for CoMFA-Focusing, CoMSIA-SDH, Topomer CoMFA and HQSAR models exhibited good 'leave-one-out' cross validated correlation coefficient (q(2)) of 0.790, 0.769, 0.840 and 0.787, coefficient of determination (r(2)) of 0.999, 0.964, 0.979 and 0.980, and high predictive power (r(2)(pred)) of 0.796, 0.833, 0.820 and 0.803 respectively. Docking studies revealed that those inhibitors able to bind to amino acid Gln859 by cGMP binding orientation called 'glutamine-switch', and also bind to the hydrophobic clamp of PDE2 isoform, could possess high selectivity for PDE2. From the results of all the studies, structure-activity relationships and structural requirements for binding to active site of PDE2 were established which provide useful guidance for the design and future synthesis of potent PDE2 inhibitors.

Case based measles surveillance in Pune: evidence to guide current and future measles control and elimination efforts in India.

BACKGROUND: According to WHO estimates, 35% of global measles deaths in 2011 occurred in India. In 2013, India committed to a goal of measles elimination by 2020. Laboratory supported case based measles surveillance is an essential component of measles elimination strategies. Results from a case-based measles surveillance system in Pune district (November 2009 through December 2011) are reported here with wider implications for measles elimination efforts in India. METHODS: Standard protocols were followed for case identification, investigation and classification. Suspected measles cases were confirmed through serology (IgM) or epidemiological linkage or clinical presentation. Data regarding age, sex, vaccination status were collected and annualized incidence rates for measles and rubella cases calculated. RESULTS: Of the 1011 suspected measles cases reported to the surveillance system, 76% were confirmed measles, 6% were confirmed rubella, and 17% were non-measles, non-rubella cases. Of the confirmed measles cases, 95% were less than 15 years of age. Annual measles incidence rate was more than 250 per million persons and nearly half were associated with outbreaks. Thirty-nine per cent of the confirmed measles cases were vaccinated with one dose of measles vaccine (MCV1). CONCLUSION: Surveillance demonstrated high measles incidence and frequent outbreaks in Pune where MCV1 coverage in infants was above 90%. Results indicate that even high coverage with a single dose of measles vaccine was insufficient to provide population protection and prevent measles outbreaks. An effective measles and rubella surveillance system provides essential information to plan, implement and evaluate measles immunization strategies and monitor progress towards measles elimination.

Novel curcumin analogs targeting TNF-induced NF-kappaB activation and proliferation in human leukemic KBM-5 cells.

Novel curcumin analogs were synthesized using Knoevenagel condensation to convert enolic diketones of curcumin into non-enolizable ones and Schiff bases were prepared using a bioactive thiosemicarbazide pharmacophore. Copper(II) conjugates of all synthesized ligands were prepared and structurally characterized as well as evaluated for their potential of inhibiting TNF-induced NF-kappaB activation and proliferation in human leukemic KBM-5 cells wherein compound 13 was found to be more potent than curcumin. Compounds were further examined on other tumor cell lines such as Jurkat, H1299, and MM1, respectively.

Eigen value analysis of HIV-1 integrase inhibitors.

A three-dimensional quantitative structure activity relationship using the eigen value analysis (EVA) paradigm applied to 41 HIV-1 integrase inhibitors that inhibit integrase mediated cleavage (3'-processing step) and integration (3'-strand transfer step) in vitro was performed. The training set consisted of 35 molecules from five structurally diverse classes: salicylhydrazines, lichen acids, coumarins, quinones, and thiazolothiazepines. Models derived using semiempirical (MOPAC AM1 and PM3) calculated normal-mode frequencies were compared. The predictive ability of each resultant model was evaluated using a test set comprised of six molecules belonging to a different structural class: hydrazides. Models derived using AM1 method showed considerable internal as well as external predictivity (r(2)(cv) = 0.806, r(2)(pred) = 0.761 for 3'-processing and r(2)(cv) = 0.677, r(2)(pred) = 0.591 for 3'-strand transfer).

Three-dimensional quantitative structure-activity relationship (3D-QSAR) of 3-aryloxazolidin-2-one antibacterials.

Three-dimensional quantitative structure-activity relationship (3D-QSAR) studies for 3-aryloxazolidin-2-one antibacterials were performed using the genetic function approximation algorithm. This study was performed using 60 compounds, in which the QSAR models were developed using a training set of 50 compounds. The in vitro minimum inhibitory concentration (MIC) against Staphylococcus aureus SFCO-1a was used for the study. The predictive ability of the QSAR model was evaluated by using a test set of 10 compounds. The statistical quality of the QSAR models was assessed using statistical parameters r(2), r(2)(cv) (cross-validated r(2)), r(2)(pred) (predictive r(2)) and lack of fit measure (LOF). The results obtained indicate that the antibacterial activity of the 3-aryloxazolidin-2-ones is strongly dependent on electronic factor as expressed by lowest unoccupied molecular orbital energy (LUMO), spatial factor as expressed by density and thermodynamic factors accounted for by molar refractivity and heat of formation. The model is presently being used to design and predict new potent molecules prior to synthesis.

A feature based pharmacophore for Candida albicans MyristoylCoA: protein N-myristoyltransferase inhibitors.

A three-dimensional pharmacophore model has been generated for Candida albicans MyristoylCoA: protein N-myristoyltransferase (NMT) inhibitors, using the software program CATALYST. The in vitro NMT inhibitory activity of a series of peptidic inhibitors was used for pharmacophore generation. The effect of altering the control parameters and feature selection was studied to arrive at the pharmacophore model. The selection of the best hypothesis model was based on the total cost, predictive ability, difference in the cost from the null hypothesis and alignment of the training set compounds on to the hypothesis. The pharmacophore model selected has four features; one hydrophobic, two hydrogen bond acceptor and one positive ionisable function. Groups identified as necessary by scanning alanine mutagenesis studies of the peptidic substrate of C. albicans NMT, have been identified as pharmacophore features. Comparison of the ligand binding with the enzyme in the crystal structure of NMT and that proposed by the phamacophore is consistent. The pharmacophore thus generated can be used as a template for designing non-peptidic inhibitors of NMT.

Molecular dynamics simulations of the three dimensional model of plasmepsin II-peptidic inhibitor complexes.

Plasmodium falciparum is a major causative agent of malaria, a disease of worldwide importance. Inhibition of a hemoglobin degrading P. falciparum aspartic protease Plasmepsin II (Plm II) provides a viable strategy for antimalarial therapy. Linear peptidic inhibitors based on the 4(S)-amino-3(S)-hydroxy-5-phenylpentanoic acid at the P1-P1' positions are known which inhibit Plm II with improved selectivity over cathepsin D. A series of computations were performed in order to gain insight into the interactions of these inhibitors with Plm II. The docking and molecular dynamics simulations were performed on a model ligand/enzyme complex to optimize the variables involved in the generation of ligand/enzyme models. This protocol of docking and molecular dynamics (MD) simulation was then used to derive the ligand-enzyme complexes of the molecules used in the present study. Different modes of binding of pepstatin and the three linear inhibitors were studied. Molecular dynamics simulation was performed at 300K for 100ps with a time step of Ifs. The structural effects of ligand binding were analyzed on the basis of hydrogen bond interactions, interaction energies, hydrophobic contacts and RMS deviations in the resulting energy-minimized structures of the receptor-ligand complexes. The results indicate that hydrophobic and hydrogen bonding interactions are responsible for selective inhibition of Plm II and improved selectivity over cathepsin D. Hydrogen bonding interaction plays an important role for amino acid residues such as Asp-34, Asp-214, Thr-217, Ser-218, Val-78, Ser-79, Tyr-192 and Gly-216. The binding of the inhibitors to the enzyme, while producing no large distortions in the enzyme active site cleft, results in significant RMS deviations of the inhibitor, which represent the distortion of the inhibitor, effected by the proteinase. Thus, the information generated from this analysis should be useful for further work in the area of antimalarial research.

Molecular electrostatic potentials as input for the alignment of HIV-1 integrase inhibitors in 3D QSAR.

Comparative molecular similarity indices analysis (CoMSIA), a three-dimensional quantitative structure activity relationship (3D QSAR) paradigm, was used to examine the correlations between the calculated physicochemical properties and the in vitro activities (3'-processing and 3'-strand transfer inhibition) of a series of human immunodeficiency virus type 1 (HIV-1) integrase inhibitors. The training set consisted of 34 molecules from five structurally diverse classes: salicylpyrazolinones, dioxepinones, coumarins, quinones, and benzoic hydrazides. The data set was aligned using extrema of molecular electrostatic potentials (MEPs). The predictive ability of the resultant model was evaluated using a test set comprised of 7 molecules belonging to a different structural class of thiazepinediones. A CoMSIA model using an MEP-based alignment showed considerable internal as well external predictive ability (r2(cv) = 0.821, r2(pred) = 0.608 for 3'-processing; and r2(cv) = 0.759, r2(pred.) = 0.660 for 3'-strand transfer).

Understanding the antifungal activity of terbinafine analogues using quantitative structure-activity relationship (QSAR) models.

Terbinafine and its analogues, which are a major class of non-azole antifungal agents, are known to act by inhibition of squalene epoxidase enzyme in fungal cells. We have performed a quantitative structure-activity relationship (QSAR) study on a series of 92 molecules using different types of physicochemical descriptors. Inhibitors were divided into five classes depending upon chemical structure. QSAR models were generated for correlation between antifungal activity against Candida albicans using genetic function approximation (GFA) technique. Equations were evaluated using internal as well as external test set predictions. Models generated for all these classes show that steric properties and conformational rigidity of side chains play an important role for the activity. The present QSAR analysis agrees with the results of the previously reported CoMFA study.

Selectivity analysis of 5-(arylthio)-2,4-diaminoquinazolines as inhibitors of Candida albicans dihydrofolate reductase by molecular dynamics simulations.

A series of 5-(arylthio)-2,4-diaminoquinazolines are known as selective inhibitors of dihydrofolate reductase (DHFR) from Candida albicans. We have performed docking and molecular dynamics simulations of these inhibitors with C. albicans and human DHFR to understand the basis for selectivity of these agents. Study was performed on a selected set of 10 compounds with variation in structure and activity. Molecular dynamics simulations were performed at 300 K for 45 ps with equilibration for 10 ps. Trajectory data was analyzed on the basis of hydrogen bond interactions, energy of binding and conformational energy difference. The results indicate that hydrogen bonds formed between the compound and the active site residues are responsible for inhibition and higher potency. The selectivity index, i.e the ratio of I50 against human DHFR to I50 against fungal DHFR, is mainly determined by the conformation adapted by the compounds within the active site of two enzymes. Since the human DHFR active site is rigid, the compound is trapped in a higher energy conformation. This energy difference between the two conformations deltaE mainly governs the selectivity against fungal DHFR. The information generated from this analysis of potency and selectivity should be useful for further work in the area of antifungal research.

Ruptured true aneurysm of the splenic artery: an unusual cause of haemoperitoneum.

True aneurysm of the splenic artery is rare. Two cases of ruptured true splenic artery aneurysms are presented. The first patient was a 62-year-old female who presented within 6 hours of the onset of symptoms. The other was a 27-year-old non-alcoholic male patient who was admitted in a state of shock after 2 days of observation in a peripheral hospital. Both patients had haemoperitoneum and were subjected to exploratory laparotomy. Aneurysmectomy was performed in both the patients in addition to left splenopancreatectomy in the first case and splenectomy in the second. However, due to the prolonged preoperative shock, the second patient succumbed on the third postoperative day.

Structure based prediction of binding affinity of human immunodeficiency virus-1 protease inhibitors.

A series of computations were performed to derive a strategy for the prediction of binding affinities of non-peptidic human immunodeficiency virus-1 (HIV-1) protease inhibitors. This paper describes the development of a 3D quantitative structure-activity relationship (3D-QSAR) methodology by using receptor information of HIV-1 protease. The docking and molecular dynamics simulations were performed on a model ligand/enzyme complex to optimize the variables involved in the generation of ligand/enzyme models. The protonation scheme of the active site aspartic acid residues of HIV-1 protease was derived from a computational study. The active site aspartate is monoprotonated with a proton placed on the OD1 atom of the ASP B25. This protocol of docking and molecular dynamics (MD) simulation was then used to derive the ligand-enzyme complexes of the molecules used in the present study. The molecular mechanics interaction descriptors were calculated from these ligand/enzyme models. A partial least squares (PLS) method was used to derive a linear correlation between the interaction descriptors and the biological activity. A good correlation was observed when the change in the energy of the ligand upon complex formation and the electrostatic contributions to the solvation energy of the ligand were included in the QSAR analysis. A highest cross-validated q2 value of 0.649 was observed. This model had a conventional r2 of 0.725, and when this model was used to predict the activity of the external test set, it produced a r2pred of 0.761. The total interaction energy was partitioned into interactions in different subsites and interactions with each of the amino acid residues of the enzyme. The PLS analysis using these descriptors helped to identify the important interactions which can be exploited for the design of HIV-1 protease inhibitors.

Three-dimensional quantitative structure activity relationships (3-D-QSAR) of antihyperglycemic agents.

A three-dimensional quantitative structure activity relationship study (3-D-QSAR) was performed on a set of thiazolidinedione antihyperglycemic agents using the comparative molecular field analysis (CoMFA) method. The CoMFA models were derived from a training set of 53 compounds. Fifteen compounds, which were not used in model generation were used to validate the CoMFA models. All the compounds were superimposed to the template structure by atom-based and shape-based strategies. The SYBYL QSAR rigid body field fit was also used for aligning the ligands. A total of twelve different alignments were generated. The resulting models exhibited a good cross-validated r2cv values (0.624-0.764) and the conventional r2 values (0.689-0.921). A more robust cross-validation test using cross-validation by 2 groups (leave half out method) was performed 100 times to ascertain the predictiveness of the CoMFA models. The mean of r2cv values from 100 runs ranged from 0.611-0.690. Few models exhibited good external predictivity. These models were then used to define a hypothetical receptor model for antihyperglycemic agents.

Use of adrenal vein conduit for splenorenal shunts: a case report.

We report a case with extrahepatic portal venous obstruction (EHPVO), who presented with recurrent bleeding following a previous devascularization procedure and needed an emergency distal spleno-renal shunt (DSRS). Due to technical difficulty because of previous scarring, the adrenal vein was used as a conduit between the splenic vein and renal vein. The shunt's patent and the patient has been bleed-free for 2 years.

Three-dimensional quantitative structure-activity relationship (QSAR) and receptor mapping of cytochrome P-450(14 alpha DM) inhibiting azole antifungal agents.

Molecular modeling was performed by a combined use of conformational analysis and 3D-QSAR methods to distinguish structural attributes common to a series of azole antifungal agents. Apex-3D program was used to recognize the common biophoric structural patterns of 13 diverse sets of azole antifungal compounds demonstrating different magnitudes of biological activity. Apex-3D identified three common biophoric features significant for activity: N1 atom of azole ring, the aromatic ring centroid 1, and aromatic ring centroid 2. A common biophore model proposed from the Apex-3D analysis can be useful for the design of novel cytochrome P-450(14 alpha DM) inhibiting antifungal agents.

Three-dimensional quantitative structure-activity relationship of interleukin 1-beta converting enzyme inhibitors: A comparative molecular field analysis study.

A three-dimensional quantitative structure-activity relationship (QSAR) study using the comparative molecular field analysis (CoMFA) method was performed on a series of interleukin 1-beta converting enzyme (ICE) inhibitors. The compounds studied have been reported to be time-dependent inhibitors of ICE. This study was performed using 49 compounds, in which the CoMFA models were developed using a training set of 39 compounds. All the compounds were modeled using the X-ray crystal structure of tetrapeptide aldehyde inhibitor/ICE complex. The inhibitor compounds were considered both as neutral species and as P1 carboxylate ionized species. Superimpositions were performed using two alignment rules, namely, an alignment of the structures based on RMS fitting of the backbone heavy atoms of each structure to compound 2 and an alignment based on SYBYL QSAR rigid body field fit of the steric and electrostatic fields of the molecules to the fields of compound 2. Use of LUMO energies or ClogP as additional descriptors in the QSAR table did not improve the significance of the CoMFA models. Steric and electrostatic fields of the inhibitors were found to be the relevant descriptors for structure-activity relationships. The predictive ability of the CoMFA model was evaluated by using a test set of 10 compounds (r2pred as high as 0.859). Further comparison of the coefficient contour maps with the steric and electrostatic properties of the receptor show a high level of compatibility.