Oral isotretinoin as first-line systemic therapy in a case of extensive genital warts.

Genital warts caused by human papillomavirus are one of the most common sexually transmitted diseases seen in the outpatient department. Treatment modalities of genital warts vary depending on the size, site, extent of the lesions, and patient compliance. Here, we report a case of extensive genital warts managed with oral retinoids which resulted in complete clearance.

HE-DFNETS: A Novel Hybrid Deep Learning Architecture for the Prediction of Potential Fishing Zone Areas in Indian Ocean Using Remote Sensing Images.

The Indian subcontinent is known for its larger coastline spanning, over 8100 km and is considered the habitat for many millions of people. The livelihood of their habitat is purely dependent upon the fishing activities. Often, the search for fish requires more time for catching and more resources, thus increasing the operational cost leading to low profitability. With the advent of artificial intelligence algorithms, designing intelligent algorithms for an effective prediction of fishing areas has reached new heights in terms of high accuracy (A cy ) and less time. But still, predicting the location of potential fishing zones (PFZs) is always a daunting task. To reduce these issues, this work presented the novel hybrid prediction architecture of PFZs using remote sensing images. The proposed architecture integrates the deep convolutional layers and flitter bat optimized long short-term memory (FB-LSTM)-based recurrent neural networks (RNN). These convolutional layers are utilized to remove the various color features such as chlorophyll, sea surface temperature (SST), and GPS location from the satellite images, and FB-LTSM is utilized to predict the potential locations for fishing. The extensive experimentations are carried out utilizing the satellite data from Indian National Centre for Ocean Information Services (INCOIS) and implemented using TensorFlow 1.18 with Keras API. The performance metrics such as prediction A cy , precision (P scn ), recall (R cl ) or sensitivity (S ty ), specificity (S fy ), and F1-score and compared with other existing intelligent learning models. From our observations, the proposed architecture (99% prediction A cy ) has outperformed the other existing algorithms and finds its best place in designing an intelligent system for better predicting of PFZs.

Nailfold capillaroscopy in psoriasis.

BACKGROUND: Psoriasis a chronic inflammatory skin disease manifests with microcirculatory changes within skin which may precede skin manifestations, correlate with their severity, joint involvement and resolve with treatment. Nailfold capillaroscopy (NFC) is used in rheumatology for connective tissue disorder assessment and is assuming significance in psoriasis. The aim was to study the nailfold capillaroscopic findings in patients with psoriasis. METHODS: A cross-sectional observational study was carried out at a skin center of a tertiary care hospital from January 2016 to June 2017. Selected cases underwent NFC using a portable color capillaroscope with an attached computer with software to analyze the nailfold capillaries for morphological parameters and abnormalities. Independent-samples t test and chi-square test was used to analyze the relationships between variables. RESULTS: Mean capillary loop density in 96% of study population was subnormal (<9 capillaries/mm), mean arterial limb diameter 11.37 ± 2.434µ; mean venous limb diameter 15.89 ± 3.131µ, top of the loop diameter 14.41 ± 4.373µ and length of the loop was 152.51 ± 57.21µ. Only 3 had length of loop >300µ. Bizarre morphology was seen in 15.5% of capillaries (p value < 0.001). Crossed loops/tortuous capillaries were seen in 17.3% of patients (p value < 0.001). Ramified capillaries were seen in 9.1% of patients with psoriasis (p value < 0.001). Other abnormalities observed were hemorrhage, avascular areas and subpapillary plexus. Widespread disease and psoriatic arthritis (18.2%) had irregular and haphazard distribution of capillaries (p value < 0.001). Analysis of Psoriasis Area Severity Index score, age of the patient and NFC did not reveal any statistically significant relationship. CONCLUSIONS: Nailfold capillaroscopy (NFC), a non invasive imaging technique for microcirculation evaluation can serve to prognosticate and follow up patirents with psoriasis as a simple and highly reproducible tool. Nailfold capillaroscopy is a simple and an easy method to study the microvascular abnormalities in psoriasis. Findings correlate with disease severity. It can be used for follow-up as a predictor of disease worsening or response to treatment.