Kpod vapes, zombie kids: Why it's time to raise the alarm
Etomidate is an anaesthetic used in hospitals during medical procedures, and is classified as a poison under the Poisons Act, which strictly restricts its use to licensed medical professionals.
Some parents have shared their stories about how their children have tried self-harm or attempted suicide while being high.
Through reports, commentaries and first-person accounts, ST, along with parents, readers and health professionals, have sounded the alarm on the dangerous nature of Kpods. In this episode of The Usual Place Podcast, I chat with my colleague and seasoned crime reporter Zaihan Mohamed Yusof; Yio Chu Kang SMC MP Yip Hon Weng, who has raised multiple Parliamentary Questions on vaping over the past few years; and Narasimman Tivasiha Mani, the executive director of youth mental health charity Impart, who has encountered teens using Kpods.
We will discuss the access to Kpods, what attracts young people to use them, and how Singapore can step up enforcement and awareness.
Tune in at 12pm SGT/HKT to watch the livestream and take part in the discussion on our revamped YouTube channel.
Follow The Usual Place Podcast live at noon every Thursday and get notified for new episode drops:
Channel: https://str.sg/5nfm
Apple Podcasts: https://str.sg/9ijX
Spotify: https://str.sg/cd2P
YouTube: https://str.sg/theusualplacepodcast
Source: The Straits Times © SPH Media Limited. Permission required for reproduction
Discover how to enjoy other premium articles here
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
2 hours ago
- Yahoo
BioAtla Announces Upcoming Oral Presentation at the 2025 European Society for Medical Oncology (ESMO) TAT Asia Meeting
SAN DIEGO, July 17, 2025 (GLOBE NEWSWIRE) -- BioAtla, Inc. (Nasdaq: BCAB) (the 'Company' or 'BioAtla'), a global clinical-stage biotechnology company focused on the development of Conditionally Active Biologic (CAB) antibody therapeutics for the treatment of solid tumors, today announced an oral presentation at the upcoming 2025 European Society for Medical Oncology (ESMO) TAT Asia Meeting to be held in Hong Kong Sar, China from July 18–20, 2025. Oral Presentation Details: Title: First-in-human phase I study of a dual-Conditionally Active Biologic (CAB) EpCAM x CD3 bispecific T-cell engager (TCE), BA3182, in patients with treatment refractory metastatic adenocarcinoma Authors: Jennifer B. Brooke Valerin, Jacob Thomas, J. Eva E. Selfridge, Madison Conces, Devalingam Mahalingam, Michael Cecchini, Elena G. Chiorean, Oana Danciu, Kyechin Chen, Ana Paula G. Cugnetti, Judith Llorin-Sangalang, Kartik Aysola, Alexander Starodub Presenter: Jennifer B. Brooke Valerin Presentation Number: 36O Date and Time: July 18, 2025 from 15:59‒16:06 GMT+8 A copy of the presentation materials can be accessed on the 'Publication' section of the Company's website at once the presentation has concluded. About BioAtla®, Inc. BioAtla is a global clinical-stage biotechnology company with operations in San Diego, California, and in Beijing, China through its contractual relationship with BioDuro-Sundia, a provider of preclinical development services. Utilizing its proprietary CAB platform technology, BioAtla develops novel, reversibly active monoclonal and bispecific antibodies and other protein therapeutic product candidates. CAB product candidates are designed to have more selective targeting, greater efficacy with lower toxicity, and more cost-efficient and predictable manufacturing than traditional antibodies. BioAtla has extensive and worldwide patent coverage for its CAB platform technology and products with greater than 780 active patent matters, more than 500 of which are issued patents. Broad patent coverage in all major markets includes methods of making, screening and manufacturing CAB product candidates in a wide range of formats and composition of matter coverage for specific products. To learn more about BioAtla, Inc., visit Internal Contact: Richard Waldron Chief Financial Officer BioAtla, Inc. rwaldron@ 858.356.8945 External Contact: Mike Moyer LifeSci Advisors, LLC mmoyer@ in to access your portfolio
Forbes
3 hours ago
- Forbes
How Data Science Is Transforming Drug Discovery And Medical Diagnosis
Ajit Sahu, Senior Engineering Leader – Health & Wellness Application Innovation, AI, digital transformation. Healthcare is in the midst of a data-driven revolution. With the convergence of big data, machine learning and AI, the sector is becoming smarter, faster and more predictive. These technologies are not just automating manual tasks—they are redefining how drugs are discovered, how clinical trials are run, how diseases are diagnosed and how care is delivered. Drug Discovery: From Hypotheses To High-Confidence Predictions Traditionally, drug discovery relied heavily on trial and error, with long timelines and high costs. The introduction of biostatistics helped make this process more rigorous, but the pace remained slow. Today, AI and data science are streamlining every phase, from early molecular analysis to clinical testing. AI models, like DeepMind's AlphaFold, have revolutionized how we understand protein folding and drug-target interactions. With the ability to simulate biological processes and identify optimal compounds for development, researchers are drastically cutting R&D timelines and reducing failure rates. Simultaneously, AI ensures pharmaceutical manufacturing adheres to stringent quality controls by detecting environmental deviations in real time, minimizing batch waste and improving consistency. Clinical Trials: Precision, Speed And Scalability Biostatistics remains essential in trial design, powering randomization, control group structuring and statistical significance testing. But AI adds a layer of intelligence. By analyzing historical patient data and real-time trial feedback, AI can dynamically adjust study parameters, predict adverse effects and segment patient populations more effectively. This can result in faster approvals and safer, more targeted therapies. Moreover, AI enables decentralized clinical trials, allowing remote participation, improving diversity and reducing dropout rates. Diagnosis: Real-Time, Data-Enriched Decision Making AI is also playing a key role in diagnostic medicine. Integrating data from wearables, mobile apps, imaging systems and lab results, AI models help identify disease onset and recommend treatments. Crucially, this includes analyzing vital signs over time, uncovering patterns that might be missed in traditional one-time tests. Wearable sensors powered by AI provide continuous, real-time monitoring of health metrics such as heart rate, glucose levels and activity. These sensors utilize machine learning for signal processing, personalized analytics, preventive care and dynamic resource allocation. The review underscores advancements in sensor materials and structural designs while identifying challenges and future opportunities in smart wearable health applications. Consider the example of a Covid-19 test. Even with 95% accuracy, a low prevalence rate can produce many false positives. Here, probabilistic modeling helps clinicians interpret results based on context. Such AI-supported reasoning ensures more accurate diagnoses and reduces unnecessary interventions. Smarter Resource Allocation In A Limited-Capacity World AI is helping to solve operational challenges as well. In under-resourced settings, AI-driven tools assist in staff scheduling, supply chain forecasting and infrastructure planning. During Covid-19, such insights could have mitigated issues like the rise of untreated tuberculosis cases caused by resource diversion. Hospitals and clinics also use AI to improve diagnosis, treatment and efficiency. It helps monitor patients with conditions like heart disease, cancer, diabetes and chronic diseases. AI uses machine learning to analyze sensor data, medical images, electronic health records and hospital workflows, allowing for predictive, personalized and proactive care. Going forward, AI has the potential to help balance needs across regions, ensuring care delivery doesn't compromise chronic or long-term care in the face of emergencies. Ethical Considerations And Systemic Impact While AI holds significant promise in healthcare, its implementation must be approached thoughtfully. Challenges such as bias in training data, lack of interoperability and concerns around patient consent and data privacy (particularly under HIPAA) need to be proactively addressed. Effective deployment of AI requires close collaboration between policymakers, clinicians and technologists to establish standards that ensure equitable and inclusive outcomes. From my own experience developing AI-driven tools—including OCR-based and NSFW-filtering LLM models for prescription validation—several recurring challenges stand out. These include biased training datasets, the need for continuous model retraining as new prescription formats emerge and the complexity of managing patient consent and privacy. These issues cannot be solved in isolation; they demand cross-functional coordination and governance. Fortunately, emerging standards such as the FDA's Good Machine Learning Practice (GMLP), ISO/IEC 42001 and IEEE 7003 provide essential guardrails for developing accountable and robust AI solutions. At our company, we've integrated these frameworks into our internal 'AI governance rounds'—multidisciplinary reviews involving pharmacists, data scientists, compliance experts and clinicians. These sessions help assess algorithm performance, ethical risks and clinical accuracy. For example, applying IEEE 7003's bias mitigation checklist helped us identify a gap: Our OCR tool initially underperformed on prescriptions from multilingual communities. By adjusting our dataset to better reflect linguistic diversity, we significantly reduced inaccuracies. Other promising examples of collaborative AI governance include Mayo Clinic's partnership with Google and the FDA on their 'model-in-the-loop' initiative. In this framework, AI models are reviewed collaboratively with regulators before being deployed clinically, offering a practical blueprint for responsible scaling of AI in healthcare. Still, several systemic issues remain. Current methods for collecting patient consent often fall short and struggle to keep pace with evolving data practices. We need adaptive, dynamic consent models that align with the realities of AI-enabled healthcare. Additionally, questions about liability remain unresolved: Who is responsible when AI-generated recommendations conflict with physician judgment? These gaps need to be addressed contractually and ethically. Finally, the reimbursement model based on Current Procedural Terminology codes does not yet account for AI-driven contributions to care. To unlock the full value of AI, payment structures must evolve to reward its meaningful, responsible use. Conclusion: A Smarter, Fairer Healthcare Future The future of healthcare lies in the thoughtful, responsible use of AI—not to replace human caregivers but to empower them. As AI and data science mature, they present a unique opportunity to revolutionize drug discovery, diagnostic accuracy, resource allocation and patient outcomes. Successfully addressing ethical and systemic challenges can ensure this revolution leads to a predictive, personalized and equitable healthcare system accessible to all. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
Yahoo
4 hours ago
- Yahoo
Why ginger is a lot better for your health than you may realize
There's a reason ginger has been a staple for thousands of years in both kitchens and medicine cabinets alike. It may appear like little more than a humble root, but it packs plenty of benefits that extend beyond a unique flavor profile. 'Ginger is well known for its ability to reduce nausea, but it also improves digestion and reduces inflammation, pain and can lower blood sugar,' says Kate Donelan, a registered dietitian with Stanford Health Care. While such benefits have helped ginger earn a place as one of the most scientifically backed superfoods, it's still possible to eat too much of it, and there are several adverse outcomes associated with doing so. Here's what ginger is, what it's good for and how much you'll want to actually consume. What is ginger? Ginger is a flowering plant that originated in southeast Asia but is now grown in many warm climates across the world. The root is the part of the plant most commonly eaten, which is also called the rhizome. 'Ginger is cultivated by digging up the rhizome from the soil, cleaning it, then using it fresh, dried or ground,' explains Erin Palinski-Wade, a New Jersey-based registered dietitian and author of "2-Day Diabetes Diet." Its warm, peppery flavor makes it a favorite in both sweet and savory dishes. 'As a fresh ingredient, ginger can be used in marinades or added into salads, baked goods, sauces, glazes, soup, or main dishes," explains Palinski-Wade, "but it is more commonly dried and ground and used as a spice." Ginger can also be crystallized to be used as a syrup in cocktails or sodas or turned into a chewy, candy-like treat. And for those seeking a concentrated dose, ginger supplements are also available and come in capsule, powder, oil or tincture form. Mocktails are on the rise. But are they actually better for you than alcoholic beverages? What is ginger good for? What does ginger do for the body? No matter which kind of ginger you enjoy, the spice has a long history of therapeutic uses, most of which are supported by high-quality research. One of its best-known benefits is aiding digestion. 'Ginger stimulates gastric emptying and increases the movement of food through the digestive tract, which can help relieve stomach pain and bloating,' notes Palinski-Wade. In part for these reasons, meta-analysis shows ginger being especially effective in treating nausea related to motion sickness, chemotherapy or pregnancy. Another major benefit lies in ginger's anti-inflammatory and antioxidant properties that may help prevent chronic illnesses like arthritis, heart disease and neurodegenerative diseases. These benefits are primarily due to the main bioactive compound in ginger known as gingerol, explains Palinski-Wade. Research also shows that ginger plays a role in blood sugar regulation and lowering cholesterol levels; and it can help bolster the body's defenses against viruses and bacteria – which is one reason ginger tea is a popular go-to remedy for colds and flu. Ginger also provides small but beneficial amounts of vitamin C, magnesium and potassium – all of which play key roles in immune function, muscle activity and blood pressure regulation, says Donelan. Great question: What is magnesium good for? Can I have ginger every day? Despite so many benefits, it's still best to enjoy ginger in moderation. Most adults can safely consume 3 to 4 grams of it daily, notes UCLA Health, which is about 1 to 2 teaspoons of fresh ginger. For pregnant women, the recommended maximum is closer to 1 gram per day. Consuming too much ginger "can cause acid reflux, mouth or throat discomfort or diarrhea,' says Donelan. 'And as a supplement, ginger can interact negatively with blood thinners." For such reasons, Donelan says, anyone with bleeding disorders or those taking medications for high blood pressure or diabetes "should discuss ginger use with their doctor.' Ditto for pregnant women, adds Palinski-Wade. And while allergic reactions to ginger are rare, they can occur and typically manifest as mouth irritation or skin rashes. 'So long as you're not overdoing it though," says Donelan, "ginger can be a helpful and healing addition to your diet." This article originally appeared on USA TODAY: What is ginger beneficial for?
