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Predictive genomic tools in disease stratification and targeted prevention: a recent update in personalized therapy advancements

Jain N, Nagaich U, Pandey M, Chellappan DK, Dua K

EPMA J, 2022 Dec;13(4):561-580.
PMID: 36505888 DOI: 10.1007/s13167-022-00304-2

In the current era of medical revolution, genomic testing has guided the healthcare fraternity to develop predictive, preventive, and personalized medicine. Predictive screening involves sequencing a whole genome to comprehensively deliver patient care via enhanced diagnostic sensitivity and specific therapeutic targeting. The best example is the application of whole-exome sequencing when identifying aberrant fetuses with healthy karyotypes and chromosomal microarray analysis in complicated pregnancies. To fit into today's clinical practice needs, experimental system biology like genomic technologies, and system biology viz., the use of artificial intelligence and machine learning is required to be attuned to the development of preventive and personalized medicine. As diagnostic techniques are advancing, the selection of medical intervention can gradually be influenced by a person's genetic composition or the cellular profiling of the affected tissue. Clinical genetic practitioners can learn a lot about several conditions from their distinct facial traits. Current research indicates that in terms of diagnosing syndromes, facial analysis techniques are on par with those of qualified therapists. Employing deep learning and computer vision techniques, the face image assessment software DeepGestalt measures resemblances to numerous of disorders. Biomarkers are essential for diagnostic, prognostic, and selection systems for developing personalized medicine viz. DNA from chromosome 21 is counted in prenatal blood as part of the Down's syndrome biomarker screening. This review is based on a detailed analysis of the scientific literature via a vigilant approach to highlight the applicability of predictive diagnostics for the development of preventive, targeted, personalized medicine for clinical application in the framework of predictive, preventive, and personalized medicine (PPPM/3 PM). Additionally, targeted prevention has also been elaborated in terms of gene-environment interactions and next-generation DNA sequencing. The application of 3 PM has been highlighted by an in-depth analysis of cancer and cardiovascular diseases. The real-time challenges of genome sequencing and personalized medicine have also been discussed.
Miniaturized Polymeric Systems for the Intravaginal Gene Therapies: Recent Update on Unconventional Delivery

Pandey M, Ting JSS, Gorain B, Jain N, Mayuren J

Curr Pharm Des, 2023;29(40):3254-3262.
PMID: 37438899 DOI: 10.2174/1381612829666230712162540

The prevalence of vaginal infection is increasing among women, especially at reproductive age. For proper eradication of infection, the effective concentration of a drug is required at the infection site. Therefore, local delivery is recommended to exert a direct therapeutic effect at the site action that causes a reduction in dose and side effects. The main focus of vaginal drug delivery is to enhance retention time and patient compliance. The high recurrence rate of vaginal infection due to the lack of effective treatment strategies opens the door for new therapeutic approaches. To combat these setbacks, intravaginal gene therapies have been investigated. High attention has been gained by vaginal gene therapy, especially for sexually transmitted infection treatment. Despite much research, no product is available in the market, although in vitro and preclinical data support the vaginal route as an effective route for gene administration. The main focus of this review is to discuss the recent advancement in miniaturized polymeric systems for intravaginal gene therapies to treat local infections. An overview of different barriers to vaginal delivery and challenges of vaginal infection treatment are also summarised.
Fulltext An Emotion Care Model using Multimodal Textual Analysis on COVID-19

Gupta V, Jain N, Katariya P, Kumar A, Mohan S, Ahmadian A, et al.

Chaos Solitons Fractals, 2021 Mar;144:110708.
PMID: 33519125 DOI: 10.1016/j.chaos.2021.110708

At the dawn of the year 2020, the world was hit by a significant pandemic COVID-19, that traumatized the entire planet. The infectious spread grew in leaps and bounds and forced the policymakers and governments to move towards lockdown. The lockdown further compelled people to stay under house arrest, which further resulted in an outbreak of emotions on social media platforms. Perceiving people's emotional state during these times becomes critically and strategically important for the government and the policymakers. In this regard, a novel emotion care scheme has been proposed in this paper to analyze multimodal textual data contained in real-time tweets related to COVID-19. Moreover, this paper studies 8-scale emotions (Anger, Anticipation, Disgust, Fear, Joy, Sadness, Surprise, and Trust) over multiple categories such as nature, lockdown, health, education, market, and politics. This is the first of its kind linguistic analysis on multiple modes pertaining to the pandemic to the best of our understanding. Taking India as a case study, we inferred from this textual analysis that 'joy' has been lesser towards everything (~9-15%) but nature (~17%) due to the apparent fact of lessened pollution. The education system entailed more trust (~29%) due to teachers' fraternity's consistent efforts. The health sector witnessed sadness (~16%) and fear (~18%) as the dominant emotions among the masses as human lives were at stake. Additionally, the state-wise and emotion-wise depiction is also provided. An interactive internet application has also been developed for the same.
Fulltext Prediction modelling of COVID using machine learning methods from B-cell dataset

Jain N, Jhunthra S, Garg H, Gupta V, Mohan S, Ahmadian A, et al.

Results Phys, 2021 Feb;21:103813.
PMID: 33495725 DOI: 10.1016/j.rinp.2021.103813

Coronavirus is a pandemic that has become a concern for the whole world. This disease has stepped out to its greatest extent and is expanding day by day. Coronavirus, termed as a worldwide disease, has caused more than 8 lakh deaths worldwide. The foremost cause of the spread of coronavirus is SARS-CoV and SARS-CoV-2, which are part of the coronavirus family. Thus, predicting the patients suffering from such pandemic diseases would help to formulate the difference in inaccurate and infeasible time duration. This paper mainly focuses on the prediction of SARS-CoV and SARS-CoV-2 using the B-cells dataset. The paper also proposes different ensemble learning strategies that came out to be beneficial while making predictions. The predictions are made using various machine learning models. The numerous machine learning models, such as SVM, Naïve Bayes, K-nearest neighbors, AdaBoost, Gradient boosting, XGBoost, Random forest, ensembles, and neural networks are used in predicting and analyzing the dataset. The most accurate result was obtained using the proposed algorithm with 0.919 AUC score and 87.248% validation accuracy for predicting SARS-CoV and 0.923 AUC and 87.7934% validation accuracy for predicting SARS-CoV-2 virus.
Chitosan and hyaluronic acid-based nanocarriers for advanced cancer therapy and intervention

Rohtagi P, Garg U, Triveni, Jain N, Pandey M, Amin MCIM, et al.

Biomater Adv, 2024 Feb;157:213733.
PMID: 38118207 DOI: 10.1016/j.bioadv.2023.213733

Cancer has become a major public health issue leading to one of the foremost causes of morbidity and death in the world. Despite the current advances in diagnosis using modern technologies and treatment via surgery or chemo- and radio-therapies, severe side effects or after-effects limit the application of these treatment modalities. Novel drug delivery systems have shown the potential to deliver chemotherapeutics directly to cancer cells, thus minimizing unnecessary exposure to healthy cells. Concurrently, to circumvent difficulties associated with conventional deliveries of cancer therapeutics, natural polysaccharides have gained attention for the fabrication of such deliveries owing to biocompatibility, low toxicity, and biodegradability. It has been exhibited that natural polysaccharides can deliver high therapeutic concentrations of the entrapped drug to the target cells by sustained and targeted release. Considering the immense potential of natural polymers, the present work focuses on naturally generated biopolymer carriers based on chitosan and hyaluronic acid. This review delineated on the role of chitosan and its derivation from renewable resources as a biocompatible, biodegradable, nonimmunogenic material with notable antitumor activity as a drug delivery carrier in oncotherapy. Moreover, hyaluronic acid, itself by its structure or when linked with other molecules contributes to developing promising pharmaceutical delivery systems to setback the restrictions related to conventional cancer treatment.
Nano vs Resistant Tuberculosis: Taking the Lung Route

Sharma D, Pooja, Nirban S, Ojha S, Kumar T, Jain N, et al.

AAPS PharmSciTech, 2023 Dec 04;24(8):252.
PMID: 38049695 DOI: 10.1208/s12249-023-02708-3

Tuberculosis (TB) is among the top 10 infectious diseases worldwide. It is categorized among the leading killer diseases that are the reason for the death of millions of people globally. Although a standardized treatment regimen is available, non-adherence to treatment has increased multi-drug resistance (MDR) and extensive drug-resistant (XDR) TB development. Another challenge is targeting the death of TB reservoirs in the alveoli via conventional treatment. TB Drug resistance may emerge as a futuristic restraint of TB with the scarcity of effective Anti-tubercular drugs. The paradigm change towards nano-targeted drug delivery systems is mostly due to the absence of effective therapy and increased TB infection recurrent episodes with MDR. The emerging field of nanotechnology gave an admirable opportunity to combat MDR and XDR via accurate diagnosis with effective treatment. The new strategies targeting the lung via the pulmonary route may overcome the new incidence of MDR and enhance patient compliance. Therefore, this review highlights the importance and recent research on pulmonary drug delivery with nanotechnology along with prevalence, the need for the development of nanotechnology, beneficial aspects of nanomedicine, safety concerns of nanocarriers, and clinical studies.
Nanoneuroscience: Cutting-edge Approach for Disease Management

Malhotra S, Jain N, Rathee J, Kaul S, Nagaich U, Pandey M, et al.

Recent Pat Nanotechnol, 2024;18(2):256-271.
PMID: 38197418 DOI: 10.2174/1872210517666230403105152

Neurological disorders (ND) have affected a major part of our society and have been a challenge for medical and biosciences for decades. However, many of these disorders haven't responded well to currently established treatment approaches. The fact that many active pharmaceutical ingredients can't get to their specified action site inside the body is one of the main reasons for this failure. Extracellular and intracellular central nervous system (CNS) barriers prevent the transfer of drugs from the blood circulation to the intended location of the action. Utilizing nanosized drug delivery technologies is one possible way to overcome these obstacles. These nano-drug carriers outperform conventional dosage forms in many areas, including good drug encapsulation capacity, targeted drug delivery, less toxicity, and enhanced therapeutic impact. As a result, nano-neuroscience is growing to be an intriguing area of research and a bright alternative approach for delivering medicines to their intended action site for treating different neurological and psychiatric problems. In this review, we have included a short overview of the pathophysiology of neurological diseases, a detailed discussion about the significance of nanocarriers in NDs, and a focus on its recent advances. Finally, we highlighted the patented technologies and market trends, including the predictive analysis for the years 2021-2028.
Fulltext Improved COVID-19 detection with chest x-ray images using deep learning

Gupta V, Jain N, Sachdeva J, Gupta M, Mohan S, Bajuri MY, et al.

Multimed Tools Appl, 2022;81(26):37657-37680.
PMID: 35968409 DOI: 10.1007/s11042-022-13509-4

The novel coronavirus disease, which originated in Wuhan, developed into a severe public health problem worldwide. Immense stress in the society and health department was advanced due to the multiplying numbers of COVID carriers and deaths. This stress can be lowered by performing a high-speed diagnosis for the disease, which can be a crucial stride for opposing the deadly virus. A good large amount of time is consumed in the diagnosis. Some applications that use medical images like X-Rays or CT-Scans can pace up the time used in diagnosis. Hence, this paper aims to create a computer-aided-design system that will use the chest X-Ray as input and further classify it into one of the three classes, namely COVID-19, viral Pneumonia, and healthy. Since the COVID-19 positive chest X-Rays dataset was low, we have exploited four pre-trained deep neural networks (DNNs) to find the best for this system. The dataset consisted of 2905 images with 219 COVID-19 cases, 1341 healthy cases, and 1345 viral pneumonia cases. Out of these images, the models were evaluated on 30 images of each class for the testing, while the rest of them were used for training. It is observed that AlexNet attained an accuracy of 97.6% with an average precision, recall, and F1 score of 0.98, 0.97, and 0.98, respectively.
Intraductal delivery of nanocarriers for ductal carcinoma in situ treatment: a strategy to enhance localized delivery

Pandey M, Wen PX, Ning GM, Xing GJ, Wei LM, Kumar D, et al.

Nanomedicine (Lond), 2022 Oct;17(24):1871-1889.
PMID: 36695306 DOI: 10.2217/nnm-2022-0234

Ductal carcinoma in situ describes the most commonly occurring, noninvasive malignant breast disease, which could be the leading factor in invasive breast cancer. Despite remarkable advancements in treatment options, poor specificity, low bioavailability and dose-induced toxicity of chemotherapy are the main constraint. A unique characteristic of nanocarriers may overcome these problems. Moreover, the intraductal route of administration serves as an alternative approach. The direct nanodrug delivery into mammary ducts results in the accumulation of anticancer agents at targeted tissue for a prolonged period with high permeability, significantly decreasing the tumor size and improving the survival rate. This review focuses mainly on the intraductal delivery of nanocarriers in treating ductal carcinoma in situ, together with potential clinical translational research.
Machine learning for cognitive behavioral analysis: datasets, methods, paradigms, and research directions

Bhatt P, Sethi A, Tasgaonkar V, Shroff J, Pendharkar I, Desai A, et al.

Brain Inform, 2023 Jul 31;10(1):18.
PMID: 37524933 DOI: 10.1186/s40708-023-00196-6

Human behaviour reflects cognitive abilities. Human cognition is fundamentally linked to the different experiences or characteristics of consciousness/emotions, such as joy, grief, anger, etc., which assists in effective communication with others. Detection and differentiation between thoughts, feelings, and behaviours are paramount in learning to control our emotions and respond more effectively in stressful circumstances. The ability to perceive, analyse, process, interpret, remember, and retrieve information while making judgments to respond correctly is referred to as Cognitive Behavior. After making a significant mark in emotion analysis, deception detection is one of the key areas to connect human behaviour, mainly in the forensic domain. Detection of lies, deception, malicious intent, abnormal behaviour, emotions, stress, etc., have significant roles in advanced stages of behavioral science. Artificial Intelligence and Machine learning (AI/ML) has helped a great deal in pattern recognition, data extraction and analysis, and interpretations. The goal of using AI and ML in behavioral sciences is to infer human behaviour, mainly for mental health or forensic investigations. The presented work provides an extensive review of the research on cognitive behaviour analysis. A parametric study is presented based on different physical characteristics, emotional behaviours, data collection sensing mechanisms, unimodal and multimodal datasets, modelling AI/ML methods, challenges, and future research directions.
Antifungal activity of synthetic xanthenone against fluconazole-resistant Candida auris and its mechanism of action

Ramli AH, Jayathilaka EHTT, Dias MKHM, Abdul Malek E, Jain N, An J, et al.

Microb Pathog, 2024 Jul 17.
PMID: 39029597 DOI: 10.1016/j.micpath.2024.106797

Candida auris, an emerging multidrug-resistant fungal pathogen discovered in Japan in 2009, poses a significant global health threat, with infections reported in about 25 countries. The escalation of drug-resistant strains underscores the urgent need for new treatment options. This study aimed to investigate the antifungal potential of 2,3,4,4a-tetrahydro-1H-xanthen-1-one (XA1) against C. auris, as well as its mechanism of action and toxic profile. The antifungal activity of XA1 was first evaluated by determining the minimum inhibitory concentration (MIC), time-kill kinetics and biofilm inhibition. In addition, structural changes, membrane permeability, reactive oxygen species (ROS) production, and in vitro and in vivo toxicity of C. auris after exposure to XA1 were investigated. The results indicated that XA1 exhibited an MIC of 50 μg/mL against C. auris, with time-kill kinetics highlighting its efficacy. Field emission scanning electron microscopy (FE-SEM) showed structural damage in XA1-treated cells, supported by increased membrane permeability leading to cell death. Furthermore, XA1 induced ROS production and significantly inhibited biofilm formation. Importantly, XA1 exhibited low cytotoxicity in human epidermal keratinocytes (HaCaT), with a cell viability of over 90% at 6.25 μg/mL. In addition, an LD50 of 17.68 μg/mL was determined in zebrafish embryos 24 hours post fertilization (hpf), with developmental delay observed at prolonged exposure at 6.25 μg/mL (48-96 hpf). These findings position XA1 as a promising candidate for further research and development of an effective antifungal agent.
Fulltext A Global Survey on the Impact of COVID-19 on Urological Services

Teoh JY, Ong WLK, Gonzalez-Padilla D, Castellani D, Dubin JM, Esperto F, et al.

Eur Urol, 2020 Aug;78(2):265-275.
PMID: 32507625 DOI: 10.1016/j.eururo.2020.05.025

BACKGROUND: The World Health Organization (WHO) declared coronavirus disease-19 (COVID-19) as a pandemic on March 11, 2020. The impact of COVID-19 on urological services in different geographical areas is unknown.
OBJECTIVE: To investigate the global impact of COVID-19 on urological providers and the provision of urological patient care.
DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional, web-based survey was conducted from March 30, 2020 to April 7, 2020. A 55-item questionnaire was developed to investigate the impact of COVID-19 on various aspects of urological services. Target respondents were practising urologists, urology trainees, and urology nurses/advanced practice providers.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The primary outcome was the degree of reduction in urological services, which was further stratified by the geographical location, degree of outbreak, and nature and urgency of urological conditions. The secondary outcome was the duration of delay in urological services.
RESULTS AND LIMITATIONS: A total of 1004 participants responded to our survey, and they were mostly based in Asia, Europe, North America, and South America. Worldwide, 41% of the respondents reported that their hospital staff members had been diagnosed with COVID-19 infection, 27% reported personnel shortage, and 26% had to be deployed to take care of COVID-19 patients. Globally, only 33% of the respondents felt that they were given adequate personal protective equipment, and many providers expressed fear of going to work (47%). It was of concerning that 13% of the respondents were advised not to wear a surgical face mask for the fear of scaring their patients, and 21% of the respondents were advised not to discuss COVID-19 issues or concerns on media. COVID-19 had a global impact on the cut-down of urological services, including outpatient clinic appointments, outpatient investigations and procedures, and urological surgeries. The degree of cut-down of urological services increased with the degree of COVID-19 outbreak. On average, 28% of outpatient clinics, 30% of outpatient investigations and procedures, and 31% of urological surgeries had a delay of >8 wk. Urological services for benign conditions were more affected than those for malignant conditions. Finally, 47% of the respondents believed that the accumulated workload could be dealt with in a timely manner after the COVID-19 outbreak, but 50% thought the postponement of urological services would affect the treatment and survival outcomes of their patients. One of the limitations of this study is that Africa, Australia, and New Zealand were under-represented.
CONCLUSIONS: COVID-19 had a profound global impact on urological care and urology providers. The degree of cut-down of urological services increased with the degree of COVID-19 outbreak and was greater for benign than for malignant conditions. One-fourth of urological providers were deployed to assist with COVID-19 care. Many providers reported insufficient personal protective equipment and support from hospital administration.
PATIENT SUMMARY: Coronavirus disease-19 (COVID-19) has led to significant delay in outpatient care and surgery in urology, particularly in regions with the most COVID-19 cases. A considerable proportion of urology health care professionals have been deployed to assist in COVID-19 care, despite the perception of insufficient training and protective equipment.

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