Comparison of the efficacy of Diclofenac 0.1% and Nepafenac 0.1% on anterior chamber cells in patients undergoing cataract surgery: A prospective clinical practice trial.

Objectives: To compare the efficacy of topical Nepafenac 0.1 % and Diclofenac 0.1% eye drops in reducing the aqueous cells in the anterior chamber in an un-eventful post cataract surgery. Methods: This prospective, clinical trial was conducted at an Eye OPD of Qazi Hussain Ahmad Medical Complex, Nowshera from January till December 2021. Ophthalmic assessment included Visual acuity (VA), slit-lamp examination, Intraocular pressure (IOP), Central macular thickness (CMT) by Optical coherence tomography (OCT) and anterior chamber-aqueous cells measurement pre-operatively and at day 1st, 2nd, 4th and 8th week post-operatively. Patients were randomly allocated to topical diclofenac 0.1% (TD) four times a day and nepafenac 0.1% (TN) three times a day for four weeks each along with topical steroids and antibiotics. Results: Seventy patients (70) were randomly distributed into two treatment arms of 35 each. In both the arms VA improved which achieved a level of statistical significance post-operatively, however statistically insignificant difference was observed between the groups at 8th week follow up visit (p= 0.62). However, IOP and CMT values didn't achieve statistical significance between the arms pre and post operatively. In TN arm, level of AC-cells at 2nd and 4th week post-operatively were significantly lower (10.54 ± 4.05 and 08.20 ± 4.44) than TD arm (11.28 ± 5.04 and 09. 66 ± 5.50) with statistically significant difference (p < 0.05). Conclusions: Topical Nepafenac 0.1% was more effective in suppressing the anterior chamber inflammation as compared to diclofenac during the early few post-operative weeks.

Reseek-Arrhythmia: Empirical Evaluation of ResNet Architecture for Detection of Arrhythmia.

Arrhythmia is a cardiac condition characterized by an irregular heart rhythm that hinders the proper circulation of blood, posing a severe risk to individuals' lives. Globally, arrhythmias are recognized as a significant health concern, accounting for nearly 12 percent of all deaths. As a result, there has been a growing focus on utilizing artificial intelligence for the detection and classification of abnormal heartbeats. In recent years, self-operated heartbeat detection research has gained popularity due to its cost-effectiveness and potential for expediting therapy for individuals at risk of arrhythmias. However, building an efficient automatic heartbeat monitoring approach for arrhythmia identification and classification comes with several significant challenges. These challenges include addressing issues related to data quality, determining the range for heart rate segmentation, managing data imbalance difficulties, handling intra- and inter-patient variations, distinguishing supraventricular irregular heartbeats from regular heartbeats, and ensuring model interpretability. In this study, we propose the Reseek-Arrhythmia model, which leverages deep learning techniques to automatically detect and classify heart arrhythmia diseases. The model combines different convolutional blocks and identity blocks, along with essential components such as convolution layers, batch normalization layers, and activation layers. To train and evaluate the model, we utilized the MIT-BIH and PTB datasets. Remarkably, the proposed model achieves outstanding performance with an accuracy of 99.35% and 93.50% and an acceptable loss of 0.688 and 0.2564, respectively.

Significance of Dufour and Soret aspects on dynamics of water based ternary hybrid nanofluid flow in a 3D computational domain.

The prime motive to conduct this communication is to explicate hydrothermal attributes of water by inducing new composition of nanoparticles termed as ternary particles. For this purpose, two differently natured groups one with lesser densities (Carbon nanotubes, Graphene and Aluminium oxide) and with higher densities (Copper oxide, Copper and Silver) are accounted. A 3D permeable surface is considered as a physical configuration of problem by providing dual stretching. Initially, mathematical structuring in dimensional representation expressing the constitutive relations for mass, momentum and energy conservation is manifested. Later on, a set of similar variables are executed to express attained coupled system into ordinary form. Numerical simulations are performed to find solution by employing shooting and RK-4 methods in conjunction. Description about change is displayed through graphical visualization. Subsequently, temperature distribution and heat flux coefficient against sundry variables are also measured and comprehensively discussed in pictorial and tabular format. Wall drag coefficients along (x, y) directions are also computed. It is inferred from the outcomes that velocity, temperature and concentration of base fluid is higher for ternary group 1 containing particles of low densities than for group 2 with more denser particles. It is also deduced that elevation in temperature of fluid is revealed against Soret number whereas contrary aspects is observed in view of concentration distribution. Dufour number has declining impact on temperature profile whereas it upsurges the mass distribution. It is depicted that skin friction in case of group containing particles with less densities are more than other group.

Ionic-Liquid-Stabilized TiO2 Nanostructures: A Platform for Detection of Hydrogen Peroxide.

Hydrogen peroxide (H2O2) acts as a signaling molecule to direct different biological processes. However, its excess amount results in oxidative stress, which causes the onset of different types of cancers. TiO2 nanostructure was synthesized by a facile hydrothermal method. The prepared material was characterized by FTIR spectroscopy, XRD, SEM, EDX, TGA, and Raman spectroscopy, which confirmed the formation of nanostructured material. Subsequently, the prepared nanoparticles (NPs) were capped with 1-H-3-methylimidazolium acetate ionic liquid (IL) to achieve its deagglomeration and functionalization. A new colorimetric sensing probe was prepared for the detection of H2O2 based on ionic liquid-capped TiO2 nanoparticles (TiO2/IL) and 3,3',5,5'-tetramethylbenzidine (TMB) dye, which acts as an oxidative chromogenic substrate. H2O2 reacts with TMB, in the presence of ionic liquid-coated TiO2 NPs, to form a blue-green product. The color was visualized with the naked eye, and the colorimetric change was confirmed by a UV-vis spectrophotometer. To obtain the best response of the synthesized sensor, different parameters (time, pH, concentrations, loading of nanomaterials) were optimized. It showed a low limit of detection 8.61 × 10-8 M, a high sensitivity of 2.86 × 10-7 M, and a wide linear range of 1 × 10-9-3.6 × 10-7 M, with a regression coefficient (R 2) value of 0.999. The proposed sensor showed a short incubation time of 4 min. The sensing probe did not show any interference from the coexisting species. The TiO2/IL sensor was effectively used for finding H2O2 in the urine samples of cancer patients.

Prenatal stress effects on offspring brain and behavior: Mediators, alterations and dysregulated epigenetic mechanisms.

Prenatal environment significantly influences mammalian fetal development and adverse in utero conditions have life-long consequences for the offspring health. Research has revealed that a wide variety of prenatal stress factors lead to increased risk of vulnerability to neuropsychiatric disorders in the individuals. Multiple mediators are involved in stress transfer from mother to the developing fetus, with stress hormone cortisol being a chief player. Further, the developmental programming effects of prenatal stress have been observed in the form of alterations in the offspring brain at different levels. This review covers stress transfer mediators such as cortisol, serotonin, maternal cytokines, reactive oxygen species (ROS) and the maternal microbiota, and their role in fetal programming. Prenatal stress leads to alterations in the offspring brain at multiple levels, from molecular and cellular to structural. These alterations eventually result in lasting phenotypic alterations such as in the offspring behavior and cognition. Different brain alterations induced by prenatal stress such as in neural pruning processes, neural circuit formation, brain structural connectivity and epigenetic systems regulating neural gene expression are under focus in the second part of the review. The latter constitutes a key molecular mechanism involved in prenatal stress effects and has been discussed in more detail.