Stability-indicating HPLC-PDA assay for simultaneous determination of paracetamol, thiamine and pyridoxal phosphate in tablet formulations

With the increased number of multi-drug formulations, there is a need to develop new methods for simultaneous determinations of drugs. A precise, accurate and reliable liquid chromatographic method was developed for simultaneous determination of paracetamol, thiamine, and pyridoxal phosphate in pharmaceutical formulations. Separation of analytes was carried out with an Agilent Poroshell C18 column. A mixture of ammonium phosphate buffer (pH = 3.0), acetonitrile and methanol in the ratio of 86:7:7 (V/V/V) was used as the mobile phase pumped at a flow rate of 1.8 mL min-1. Detection of all three components, impurities and degradation products was performed at the selected wavelength of 270 nm. The developed method was validated in terms of linearity, specificity, precision, accuracy, LOD and LOQ as per ICH guidelines. Linearity of the developed method was found in the range 17.5-30 µg mL–1 for thiamine, 35-60 µg mL–1 for pyridoxal phosphate and 87.5-150 µg mL–1 for paracetamol. The coefficient of determination was ≥0.9981 for all three analytes. The proposed HPLC method was found to be simple and reliable for the routine simultaneous analysis of paracetamol, thiamine and pyridoxal phosphate in tablet formulations. Complete separation of analytes in the presence of degradation products indicated selectivity of the method

Diagnostic accuracy of contrast enhanced MRI pelvis in differentiating indeterminate adnexal lesions into benign and malignant with histopathological correlation

Background: The objective of our study was to determine the diagnostic accuracy of contrast-enhanced magnetic resonance imaging pelvis in differentiating indeterminate adnexal lesions into benign and malignant, while considering histopathological examinations as the gold standard.Methods: A total 880 patients who underwent contrast enhanced MRI pelvis in our institute from January 2014 to June 2016 were prospectively analyzed.Results: A total of 880 women were included in this study, of which 782 (88.8%) were younger than 50 years and 98 (11.1%) were older than 50 years. Mean patient age was 56.7 years and mean tumor size was 4.38 cm. There were 648 (73.60%) patients who had a tumor size of >4 cm, and 337 (38.29%) of these tumors were found to be malignant. Furthermore, tumors smaller than 4 cm in size were observed in 232 (26.36%) of patients, of which tumors in 225 (25.56%) patients were benign.Conclusions: The diagnostic accuracy of contrast-enhanced MRI was found to be significantly high (79.65%) in differentiating indeterminate adnexal lesions into benign and malignant lesions

Formulation development and characterization of quercetin loaded poly caprolactone nanoparticles for tumors

Cancer is a formidable health obstacle, characterized by its bleak outlook. Considerable scientific investigation has shed light on the capacity to modify the dispersion of anticancer medications at various levels within tissues and cells by enclosing them within submicronic colloidal systems, often known as nanoparticles. This approach is based on the goal of enhancing the therapeutic effectiveness of these medications while minimizing adverse effects on the entire body. Moreover, the theragnostic characteristics of these nanoparticles are widely acknowledged, hence enhancing their therapeutic potential. The current study is centered on exploring the potential anti-tumor effects of quercetin by utilizing its antioxidant capabilities. The quercetin nanoparticles are synthesized with great precision utilizing the nanoprecipitation approach, in which poly(caprolactone) is utilized as the polymer matrix. Following synthesis, the nanoparticles are extracted for further analysis. Further attempts are undertaken to enhance the drug loading process, and the resultant nanoparticles undergo a thorough analysis, including the examination of their morphology using scanning electron microscopy, and the evaluation of drug-polymer interactions using Fourier transform infrared spectroscopy and differential scanning calorimetry. The remarkable efficacy of quercetin's envelopment can be attributed to its lipophilic nature, reaching a maximum of 81%. The utilization of scanning electron microscopy allows for the observation of nanoparticles with varying forms. Conversely, the absence of noticeable interactions in Fourier-transform infrared analysis indicates the stability of poly(caprolactone) nanoparticles loaded with quercetin

Recognizing British sign language using deep learning: a contactless and privacy-preserving approach

Sign language is utilized by deaf-mute to communicate through hand movements, body postures, and facial emotions. The motions in sign language comprise a range of distinct hand and finger articulations that are occasionally synchronized with the head, face, and body. Automatic sign language recognition (SLR) is a highly challenging area and still remains in its infancy compared with speech recognition after almost three decades of research. Current wearable and vision-based systems for SLR are intrusive and suffer from the limitations of ambient lighting and privacy concerns. To the best of our knowledge, our work proposes the first contactless British sign language (BSL) recognition system using radar and deep learning (DL) algorithms. Our proposed system extracts the 2-D spatiotemporal features from the radar data and applies the state-of-the-art DL models to classify spatiotemporal features from BSL signs to different verbs and emotions, such as Help, Drink, Eat, Happy, Hate, and Sad. We collected and annotated a large-scale benchmark BSL dataset covering 15 different types of BSL signs. Our proposed system demonstrates highest classification performance with a multiclass accuracy of up to 90.07% at a distance of 141 cm from the subject using the VGGNet model

Impact of unhygienic conditions during slaughtering and processing on spread of antibiotic resistant Escherichia coli from poultry

Antibiotic resistance in Escherichia coli is a global health concern. We studied all possible routes of cross contamination of broiler meat with resistant E. coli from broiler feces at poultry shops. Various sample categories namely poultry feces, meat (n=225 for each), slaughterer hands, consumer hands, slaughterer knife, canister, tap water, carcass, feed and drinking water (n=50 for each) were collected from local poultry processing market. Samples were screened for prevalence of E. coli, resistance of isolates against ten antibiotics and presence of tetracycline- resistance genes in the isolates. Fecal samples had greatest colony count (4.1×104 CFU/g) as compared to meat (1.9×104 CFU/g) samples. Samples of consumer hands (6%) and tap water (12%) had less prevalence percentages of E. coli as compared to slaughterer hands (92%) and drinking water of broiler (86%). Isolates of eight sample categories had high resistant rate (≥90%) against oxytetracycline. On average, about 94% of the isolates from various sample categories possessed multidrug-resistance (MDR). Tetracycline-resistance genes (tetA and tetB) were identified in all sample categories except isolates of consumer hands and tap water. The distribution of tetracycline-resistance genes was significantly greater in fecal isolates (42%) than meat isolates (25%). The study depicted the spread of resistant E. coli in broiler meat through all studied routes of contamination of slaughtering periphery. This problem can be mitigated by strict monitoring of antibiotics use at poultry farms, prevention of cross contamination by adopting hygienic slaughter and vigorously screening the market meat for resistant E. coli

A novel integration of face-recognition algorithms with a soft voting scheme for efficiently tracking missing person in challenging large-gathering scenarios

The probability of losing vulnerable companions, such as children or older ones, in large gatherings is high, and their tracking is challenging. We proposed a novel integration of face-recognition algorithms with a soft voting scheme, which was applied, on low-resolution cropped images of detected faces, in order to locate missing persons in a challenging large-crowd gathering. We considered the large-crowd gathering scenarios at Al Nabvi mosque Madinah. It is a highly uncontrolled environment with a low-resolution-images data set gathered from moving cameras. The proposed model first performs real-time face-detection from camera-captured images, and then it uses the missing person’s profile face image and applies well-known face-recognition algorithms for personal identification, and their predictions are further combined to obtain more mature prediction. The presence of a missing person is determined by a small set of consecutive frames. The novelty of this work lies in using several recognition algorithms in parallel and combining their predictions by a unique soft-voting scheme, which in return not only provides a mature prediction with spatio-temporal values but also mitigates the false results of individual recognition algorithms. The experimental results of our model showed reasonably good accuracy of missing person’s identification in an extremely challenging large-gathering scenario

Third ventricular tumors: A comprehensive literature review

Third ventricle tumors are uncommon and account for 0.6 - 0.9% of all the brain tumors. Tumors of the third ventricle are classified into primary tumors, such as colloid cysts, choroid plexus papillomas, and ependymomas, or secondary tumors, such as craniopharyngiomas, optic nerve gliomas, pineal tumors, and meningiomas. Third ventricular tumors are uncommon, and their treatment involves significant morbidity and mortality. The colloid cyst has a better surgical outcome and many approaches are available to achieve a complete cure. Choroid plexus papilloma is also a common tumor documented with its treatment majorly based on surgical resection. In addition to multiple treatment options for craniopharyngiomas, surgery is the most preferred treatment option. Ependymomas also have few treatment options, with surgical resection adopted as the first line of treatment

Bioelectricity generation from bamboo leaves waste in a double chambered microbial fuel cell

This study investigated the utilization of bamboo leaf waste and two varieties of bacterial sources, chicken manure and effective microorganism, in a microbial fuel cell (MFC) at three substrate concentrations (40 g/liter, 80 g/liter, and 160 g/liter). The primary objective was to investigate the kinetics of bacterial growth at various substrate concentrations in the MFC, as well as the effect of light conditions and pH on MFC power generation. The MFC had dual chambers with graphite electrodes serving as the cathode and anode. Within 72 h, the highest power density of 90.05 mV was attained using the highest substrate concentration of bamboo leaf waste and chicken manure during the logarithmic growth phase, albeit with a shorter duration. The longest sustained phase of bacterial activity was observed during the stationary phase, at the highest substrate concentration of 160 g/liter, followed by 80 g/liter and 40 g/liter. These results indicate that the logarithmic phase is the optimal time for bacterial activity in the MFC. However, attaining long-term stability in power generation in the logarithmic phase requires careful parameter optimization