A novel attention-based cross-modal transfer learning framework for predicting cardiovascular disease.

Cardiovascular disease (CVD) remains a leading cause of death globally, presenting significant challenges in early detection and treatment. The complexity of CVD arises from its multifaceted nature, influenced by a combination of genetic, environmental, and lifestyle factors. Traditional diagnostic approaches often struggle to effectively integrate and interpret the heterogeneous data associated with CVD. Addressing this challenge, we introduce a novel Attention-Based Cross-Modal (ABCM) transfer learning framework. This framework innovatively merges diverse data types, including clinical records, medical imagery, and genetic information, through an attention-driven mechanism. This mechanism adeptly identifies and focuses on the most pertinent attributes from each data source, thereby enhancing the model's ability to discern intricate interrelationships among various data types. Our extensive testing and validation demonstrate that the ABCM framework significantly surpasses traditional single-source models and other advanced multi-source methods in predicting CVD. Specifically, our approach achieves an accuracy of 93.5%, precision of 92.0%, recall of 94.5%, and an impressive area under the curve (AUC) of 97.2%. These results not only underscore the superior predictive capability of our model but also highlight its potential in offering more accurate and early detection of CVD. The integration of cross-modal data through attention-based mechanisms provides a deeper understanding of the disease, paving the way for more informed clinical decision-making and personalized patient care.

Baseline findings of a multicentric ambispective cohort study (2021-2022) among hospitalised mucormycosis patients in India.

In India, the incidence of mucormycosis reached high levels during 2021-2022, coinciding with the COVID-19 pandemic. In response to this, we established a multicentric ambispective cohort of patients hospitalised with mucormycosis across India. In this paper, we report their baseline profile, clinical characteristics and outcomes at discharge. Patients hospitalized for mucormycosis during March-July 2021 were included. Mucormycosis was diagnosed based on mycological confirmation on direct microscopy (KOH/Calcofluor white stain), culture, histopathology, or supportive evidence from endoscopy or imaging. After consent, trained data collectors used medical records and telephonic interviews to capture data in a pre-tested structured questionnaire. At baseline, we recruited 686 patients from 26 study hospitals, of whom 72.3% were males, 78% had a prior history of diabetes, 53.2% had a history of corticosteroid treatment, and 80% were associated with COVID-19. Pain, numbness or swelling of the face were the commonest symptoms (73.3%). Liposomal Amphotericin B was the commonest drug formulation used (67.1%), and endoscopic sinus surgery was the most common surgical procedure (73.6%). At discharge, the disease was stable in 43.3%, in regression for 29.9% but 9.6% died during hospitalization. Among survivors, commonly reported disabilities included facial disfigurement (18.4%) and difficulties in chewing/swallowing (17.8%). Though the risk of mortality was only 1 in 10, the disability due to the disease was very high. This cohort study could enhance our understanding of the disease's clinical progression and help frame standard treatment guidelines.

Numerical simulation and parameter optimization of micromixer device using fuzzy logic technique.

The objective of this study is the design, simulation, and performance optimization of a micromixer device using the three input parameters of device structure, flow rate and diffusion coefficient of gold nanoparticles while the output parameters are concentration, velocity, pressure and time domain analysis. Each input parameter in the microfluidic chip influences the system output. The data were gathered through extensive study in order to optimize the diffusion control. The fuzzy logic approach is used to optimize the performance of the device with respect to the input parameters. In this study, we have chosen three different flow rates of 1, 5, and 10 µL min-1, three different diffusion coefficient values of low, average and high diffusivity gold nanofluids (15.3 e-12, 15.3 e-11, 15.3 e-10 m2 s-1) which are used in three different shapes of micromixer device, Y-shaped straight channel micromixer, herringbone-shaped micromixer, and herringbone shape with obstacles micromixer, and we measured the output performance, such as mixing efficiency, pressure drop, concentration across the microchannel and time domain. The data were obtained by fuzzy logic analysis and it was found that the herringbone shape with obstacles micromixer shows 100% mixing efficiency within a short duration of 5000 µm, and complete mixing was achieved within 10 seconds with a low pressure drop of 128 Pa.

Challenges and impact of COVID-19 lockdown on Indian optometry practice: A survey-based study.

PURPOSE: The Indian government announced a nationwide lockdown as a preventive measure to control the prevailing COVID-19 pandemic. This survey was developed and conducted to assess the impact of lockdown on Indian optometry practice. METHODS: A survey questionnaire was designed and circulated across the optometrists practicing in India through multiple social media platforms. All the data were extracted and only valid response were analyzed and reported. RESULTS: A total of 691 optometrists participated in the survey. Most of the participants (22.25%) were in private practice followed by academics (14.89%). Among the valid responses collected, it was found that 43.37% of the respondents were consulting patients during the lockdown. Of these, 27.17% of optometrists were examining infectious cases and 48.68% were examining all the patients who came for consultation. Approximately 50.94% of the participated optometrist had begun telephonic/e­mail/video consultations. In addition, 64.48% reported that optometrists were at an equal risk of clinching COVID­19 on comparison with other domains during patient examination. Nearly 30.44% respondents felt that optometrists would face challenges in approaching the patient post COVID-19 considering the close working distance. CONCLUSION: A proportion of optometrist have switched to some form of teleconsultation in order to aid patients during this prevailing pandemic. Regulatory bodies should issue appropriate guidelines regarding the safe optometry practice for the betterment of both patient and practitioners during face-to-face consultation.

Simultaneous determination of pioglitazone and glimepiride in bulk drug and pharmaceutical dosage form by RP-HPLC method.

A simple, fast, and precise reverse phase, isocratic HPLC method was developed for the separation and quantification of pioglitazone and glimepiride in bulk drug and pharmaceutical dosage form. The quantification was carried out using Inertsil ODS (250 +/- 4.6 mm, 5 micro) column and mobile phase comprised of acetonitrile and ammonium acetate (pH 4.5; 20mM) in proportion of 60:40 (v/v). The flow rate was 1.0 ml/min and the effluent was monitored at 230 nm. The retention time of pioglitazone and glimepiride were 7.0+/-0.1 and 10.2+/-0.1 min respectively. The method was validated in terms of linearity, precision, accuracy, and specificity, limit of detection and limit of quantitation. Linearity of pioglitazone and glimepiride were in the range of 2.0 to 200.0 microg/ ml and 0.5-50microg/ ml respectively. The percentage recoveries of both the drugs were 99.85% and 102.06% for pioglitazone and glimepiride respectively from the tablet formulation. The proposed method is suitable for simultaneous determination of pioglitazone and glimepiride in pharmaceutical dosage form and bulk drug.