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Published on: Nov 13, 2020
1 minute read
By: Dr Rajan ( Medical Second Opinion Cell)

Using The Cellular Handshake Against The Virus

Using the cellular handshake against the virus

In early November an interesting study was published in The Lancet Respiratory Medicine, describing the treatment of a severe COVID-19 patient with human recombinant soluble angiotensin-converting enzyme-2. By using the treatment, it was possible to see the disappearance of the virus swiftly from the patient's serum, nose, and lungs, as well as a reduction in the patients’ inflammatory markers. How was this achieved? And why is this so intriguing.

When we look at treating viruses, there are several strategies at work. You can prevent its spread by the use of social distancing or masks, you can use medications that prevent its replication (such as Tamiflu). Or you can stop the virus from entering the cells, the first step in viral replication.

SARS-CoV-2 appears to enter human cells through the ACE2 receptor. ACE2 is a protein in the cell membrane found across the human body, especially the lungs, heart, kidney and small intestine. It function is related to the Renin-Angiotensin System, a mechanism by which the kidneys control your blood pressure.

Angiotensin-Converting Enzyme converts angiotensin 1 to angiotensin 2, a hormone that causes blood vessels to constrict. ACE 2 instead converts it to a protein that causes dilation of blood vessels. This likely protects these critical organs and ensure they receive sufficient blood to perform their tasks. ACE2 is being investigated as a possible target for blood pressure medications.

The study used a genetically modified soluble form of ACE2 that mimics the protein found on human cell membranes. By increasing its availability in the blood, the SARS-CoV-2 virus binds to this protein, resulting in its inactivation, rather than entering lung cells and causing lung injury. Lab studies have shown that it can reduce viral growth by as much as 1000 to 5000 times, and phase 1 studies show it to be safe to use in people.

The actual described case was in a 45-year-old woman, hospitalized with COVID, suffering from severe shortness of breath, cough and fatigue. She was first treated with hydroxychloroquine and anticoagulants, but this proved ineffective, and the virus was causing increasing damage to her lungs. Nine days after her symptoms started, she received the ACE2 treatment for a week, with no side effects. This resulted in an increase in ACE2 activity (seen from her blood results), but also a marked decrease in multiple inflammatory markers associated with COVID-19, as well as a sharp decrease in COVID 19 numbers. Indeed, the viral load dropped from 32,000 per mL to just 270 per mL two days after treatment started. She was also able to produce antibodies against the virus, so this did not impair her from getting immunity.

It is certainly a very interesting case, though questions remain on how feasible it would be (as well as how expensive) to manufacture large quantities of this protein receptor for treatment use, as well as how it fairs in clinical trials.

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AI-Based Disease Detection India: How SecondMedic Is Transforming Early Diagnosis

India’s healthcare landscape is evolving rapidly, with artificial intelligence emerging as one of the most powerful tools for early disease detection. AI-based disease detection India represents a major shift from reactive healthcare to predictive, preventive, and precise medical analysis. Instead of waiting for symptoms to appear, AI enables clinicians and patients to identify risks early through advanced data interpretation.

Rising chronic diseases, increased diagnostic loads, and limited specialist availability make AI essential for early diagnosis in India. The use of AI in medical imaging, risk scoring, and pattern recognition significantly enhances accuracy while reducing time-consuming manual processes. SecondMedic integrates AI-powered diagnostic tools to help individuals detect health conditions in their earliest stages, enabling timely intervention and improved long-term outcomes.

Why India Needs AI-Based Disease Detection

India faces one of the world’s highest burdens of chronic and lifestyle diseases. Many conditions remain undiagnosed until they reach advanced stages, often due to late screenings, limited access to specialists, or lack of early symptoms.

The need for AI-based detection is driven by:

High incidence of silent diseases like diabetes and hypertension
Overloaded healthcare systems
Limited availability of expert radiologists
Rising lifestyle risk factors
Increasing demand for precision diagnostics
Need for faster, more accurate analysis

AI bridges these gaps by providing early alerts, consistent accuracy, and fast interpretations.

How AI Detects Diseases Early

AI-based disease detection uses machine learning models trained on thousands of medical datasets. These models learn to recognize abnormal patterns and subtle changes that the human eye might overlook.

AI analyzes:

Blood test patterns
Vital signs and wearable data
Imaging scans (X-rays, MRIs, CT scans)
Medical history
Genetic predispositions
Lifestyle habits

Through advanced algorithms, AI can identify risks long before symptoms appear, giving patients critical time for prevention and treatment.

AI in Medical Imaging: A Major Breakthrough for India

Medical imaging AI has transformed diagnosis speed and accuracy. In India, where access to radiologists is uneven, AI helps bridge diagnostic gaps.

AI-assisted imaging helps detect:

Lung infections and tuberculosis
Early-stage cancer indicators
Cardiac abnormalities
Brain tumors and neurological issues
Bone fractures and musculoskeletal conditions
Liver and kidney anomalies

SecondMedic uses AI-supported imaging interpretation to enhance precision and reduce reporting delays.

AI for Chronic Disease Prediction

Chronic illnesses often develop silently. By analyzing long-term trends, AI can predict disease progression and alert patients earlier.

AI helps forecast:

Prediabetes to diabetes progression
Heart attack risk
Hypertension development
Chronic kidney disease
Thyroid dysfunction
Metabolic health decline

These predictions allow individuals to take preventive action far in advance.

Personalized Disease Detection with AI

AI enables personalized diagnostics by incorporating each user’s biological and lifestyle data into prediction models.

Personalized AI detection considers:

Age and family history
Diet and activity levels
Sleep patterns
Stress levels
Blood markers
Genetic factors

This creates a highly individualized health risk profile.

SecondMedic’s AI engine creates a personalized risk score for each user, allowing targeted preventive strategies.

AI for Cancer Early Detection

Cancer often goes undiagnosed until it reaches advanced stages. AI helps detect early warning signs by analyzing subtle abnormalities.

AI supports early cancer detection in:

Breast cancer (mammograms)
Cervical cancer (Pap tests and visual scans)
Lung cancer (X-rays and CT scans)
Colon cancer indicators
Skin cancer lesion analysis

This improves survival rates by supporting early diagnosis.

Real-Time Monitoring with AI

Continuous monitoring is essential for early disease detection. AI integrates with wearable devices and digital health tools to track vital parameters in real time.

AI monitors:

Heart rate trends
Oxygen levels
Blood pressure variations
Stress levels
Sleep quality
Blood glucose fluctuations (connected devices)

Real-time alerts notify users of abnormalities that require attention.

AI in Public Health Disease Detection

AI is also used at the population level to identify disease patterns and outbreaks.

AI supports public health by:

Predicting outbreak patterns
Analyzing environmental health impact
Tracking regional disease trends
Supporting government screening programs

This strengthens India’s preventive health strategy.

How SecondMedic Uses AI for Disease Detection

SecondMedic integrates AI tools throughout its digital healthcare ecosystem, helping individuals access early detection and preventive insights.

SecondMedic’s AI capabilities include:

Risk scoring for diseases
AI analysis of medical reports
Predictive analytics dashboards
Early-warning alerts
Integration with wearables
AI-supported doctor consultations

This helps users understand risks clearly and take action early.

Challenges in AI-Based Disease Detection

While AI offers powerful benefits, it must be used responsibly.

Challenges include:

Requirement of high-quality medical data
Need for clinical validation
Maintaining data privacy
Avoiding algorithmic bias
Ensuring user awareness and understanding

SecondMedic follows ethical AI practices aligned with DPDP Act and ABDM standards.

Future of AI-Based Disease Detection in India

AI will continue to redefine diagnostics in India over the next decade.

Future developments include:

Deep AI for full-body scan interpretation
Genomic-based AI predictions
Emotion and mental health detection through AI
AI-assisted virtual triage systems
At-home AI diagnostic kits
National integrated AI health platforms

SecondMedic aims to lead in these innovations by integrating advanced predictive tools.

Conclusion

AI-based disease detection India is shaping a new era of proactive healthcare. By analyzing health patterns, detecting abnormalities early, and providing accurate risk assessment, AI empowers individuals to act before diseases progress. SecondMedic uses AI-driven diagnostic tools to support early detection, preventive care, and long-term health protection.

To explore AI-powered diagnostic support, visit www.secondmedic.com

References

NITI Aayog – AI for Healthcare in India
WHO – AI in Early Disease Detection
ICMR – Chronic Disease Patterns India
IMARC – Indian AI Healthcare Market
FICCI – AI and Precision Medicine India

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