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Hosting & Domain Bonuses in HIZ Tokens + DEX Listing (Uniswap V2)

by Sophie Lin - Technology Editor February 16, 2026

written by Sophie Lin - Technology Editor

Hiz Finance is carving out a niche in the competitive web hosting and domain registration market by offering incentives in the form of its native HIZ token. The company’s model focuses on rewarding customers who bundle hosting and domain purchases, a strategy designed to foster loyalty and drive adoption of its cryptocurrency. This approach comes as decentralized finance (DeFi) continues to seek broader integration with traditional web services.

The core of Hiz Finance’s offering revolves around a bonus system. Buyers who simultaneously purchase both hosting and a domain name through the platform are eligible to claim HIZ tokens. The amount of the bonus is tiered, varying based on the specific package selected. Customers must then fill out a reward claim form to receive their tokens, adding a layer of intentional engagement with the platform. This incentive structure aims to differentiate Hiz Finance from larger, more established players in the hosting industry.

Beyond the incentive program, Hiz Finance is focused on the liquidity and accessibility of its HIZ token. The company has listed the token on decentralized exchanges (DEXs), notably Uniswap V2, enabling users to trade HIZ with other cryptocurrencies. This listing is a key step in establishing a market for the token and providing a pathway for users to convert their rewards into other digital assets. The availability of HIZ on DEXs underscores a commitment to the principles of decentralization and open access.

Uniswap V2 and the Decentralized Exchange Landscape

Uniswap V2 is a foundational protocol within the decentralized finance (DeFi) space, serving as a key infrastructure component for token trading. As outlined in documentation from Uniswap Labs, it facilitates the exchange of ERC-20 tokens without the need for a central intermediary. The protocol utilizes automated market maker (AMM) technology, relying on liquidity pools to enable trading. According to Cryptokoki, Router V2 is the smart contract powering these exchanges, managing liquidity and enabling token swaps.

The Uniswap V2 Router addresses vary depending on the network. For Ethereum, the address is 0x7a250d5630B4cF539739dF2C5dAcb4c659F2488D. PancakeSwap, another popular DEX, also utilizes a V2 router, with its Binance Smart Chain address listed as 0x10ED43C718714eb63d5aA57B78B54704E256024E. SushiSwap also leverages the V2 router, with addresses varying by network, including 0x1b02dA8Cb0d097eB8D57A175b88c7D8b47997506 for Arbitrum. These addresses are crucial for users interacting with these platforms, ensuring transactions are routed correctly.

Hiz Finance’s Token and Decentralized Finance

Hiz Finance’s use of a native token and listing on a DEX like Uniswap V2 aligns with a growing trend of integrating cryptocurrency into traditional service offerings. The company states that every buyer who purchases both hosting and a domain through their platform can claim a bonus in the form of HIZ tokens by filling out a reward claim form, as detailed on their website Hiz Finance. This strategy aims to attract users familiar with cryptocurrency and incentivize broader adoption of the platform. The HIZ token’s availability on decentralized exchanges provides a liquid market for the token, allowing users to easily buy, sell, and trade it.

The broader implications of this approach extend to the potential for increased transparency and user control within the web hosting industry. Decentralized finance principles emphasize removing intermediaries and empowering users with greater control over their assets. Hiz Finance’s model, while still operating within a centralized business structure, incorporates elements of this philosophy through the use of a token and decentralized exchange listing.

Looking ahead, the success of Hiz Finance’s strategy will likely depend on its ability to attract and retain users, build a strong community around the HIZ token, and navigate the evolving regulatory landscape surrounding cryptocurrencies. The company’s focus on a niche market – bundled hosting and domain purchases – could prove to be a key differentiator in a crowded field. Continued monitoring of HIZ token trading volume and user engagement will be crucial indicators of the platform’s long-term viability.

What are your thoughts on the integration of cryptocurrency incentives into web hosting services? Share your opinions in the comments below.

February 16, 2026 0 comments

Health

Insulin Resistance Linked to Increased Cancer Risk, AI Model Confirms

by Dr. Priya Deshmukh - Senior Editor, Health February 16, 2026

written by Dr. Priya Deshmukh - Senior Editor, Health

For decades, insulin resistance – a condition where the body’s cells don’t respond effectively to insulin, a hormone crucial for regulating blood sugar – has been recognized as a key factor in the development of type 2 diabetes, cardiovascular disease, and liver problems. Now, groundbreaking research utilizing artificial intelligence suggests a far broader impact: insulin resistance may significantly elevate the risk of developing 12 different types of cancer. Researchers at the University of Tokyo have developed a machine learning model, AI-IR, that demonstrates a population-scale link between insulin resistance and cancer, offering a new avenue for early detection and preventative strategies.

The connection between insulin resistance and cancer isn’t entirely new, but establishing definitive evidence has been challenging. The human body is incredibly complex, making it hard to pinpoint direct causal relationships between metabolic issues and disease development. However, the increasing power of artificial intelligence, particularly machine learning, is providing researchers with new tools to analyze vast datasets and uncover hidden patterns. This latest study, published in Nature Communications, represents a significant step forward in understanding these complex interactions.

“We recently made a tool, AI-IR, for predicting insulin resistance in individuals based on nine different pieces of medical information,” explained Yuta Hiraike, a researcher from the University of Tokyo Hospital. “It proved successful and made us think we could apply this tool to related concerns. While a possible link between insulin resistance and cancer has been suggested, large-scale evidence has been limited due to the difficulty of evaluating insulin resistance in the clinic. But with AI-IR, we have provided the first population-scale evidence that insulin resistance is a risk factor for cancer. And since the nine input parameters for AI-IR are obtained through standard health checkups, AI-IR could be easily implemented to identify high-risk individuals and enable focused screening of diabetes, cardiovascular disease and cancer.”

AI-IR: A New Approach to Risk Assessment

Traditionally, body mass index (BMI) has been used to predict an individual’s risk of insulin resistance and related health problems, including certain cancers. However, BMI has limitations. It can produce false positives, identifying some obese individuals as metabolically healthy when they aren’t experiencing the negative effects of obesity, and false negatives, missing insulin resistance in individuals with a normal BMI. AI-IR aims to overcome these shortcomings by providing a more nuanced and accurate assessment of insulin resistance.

The researchers found that AI-IR achieved strong predictive performance when compared with directly measured insulin resistance in validation datasets. Direct measurement of insulin resistance is often impractical outside of specialized diabetes clinics, making AI-IR a scalable alternative for population-level evaluation. By combining nine readily available clinical parameters into a single metric, the model can detect insulin resistance that BMI alone might miss. The team is now focused on understanding how genetic differences influence this risk and integrating large-scale human data with molecular biology studies to develop more effective strategies for overcoming insulin resistance.

Implications for Cancer Screening and Prevention

The findings suggest that identifying and addressing insulin resistance could become a crucial component of cancer prevention strategies. The ability to pinpoint individuals at higher risk through a simple assessment – utilizing parameters obtained during routine health checkups – could allow for more targeted screening and early intervention. This is particularly significant given that approximately one in three Americans has insulin resistance, according to the Centers for Disease Control and Prevention.

While the study establishes a correlation between insulin resistance and increased cancer risk, it does not prove causation. Further research is needed to fully understand the underlying mechanisms and determine whether interventions aimed at improving insulin sensitivity can directly reduce cancer incidence. However, the study provides compelling evidence that insulin resistance should be considered a significant risk factor in the development of multiple cancers.

The researchers are continuing to refine AI-IR and explore its potential applications in personalized medicine. They hope that this tool will ultimately contribute to a more proactive and preventative approach to cancer care, focusing on identifying and mitigating risk factors before the disease develops. The next steps involve investigating the specific biological pathways linking insulin resistance to different cancer types and developing targeted therapies to address these pathways.

Disclaimer: This article provides informational content and should not be considered medical advice. Please consult with a qualified healthcare professional for any health concerns or before making any decisions related to your health or treatment.

What are your thoughts on the potential of AI in early disease detection? Share your comments below, and please share this article with your network.

February 16, 2026 0 comments

Health

Lung Cancer in Never Smokers: Rising Cases, Causes & Early Detection Strategies

by Dr. Priya Deshmukh - Senior Editor, Health February 15, 2026

written by Dr. Priya Deshmukh - Senior Editor, Health

Lung cancer remains the leading cause of cancer-related deaths worldwide, but a concerning trend is emerging: an increasing number of diagnoses among individuals who have never smoked. This shift necessitates a re-evaluation of traditional lung cancer models and a focused effort to understand the unique biological factors at play in this growing population. Researchers are now investigating how genetics, environmental exposures and innovative screening methods could lead to earlier detection and improved outcomes for those affected by lung cancer in never smokers (LCINS).

Historically, lung cancer research and prevention efforts have centered on smokers. However, LCINS represents a significant and rising percentage of cases, even though the absolute numbers remain lower than those linked to tobacco use. This distinct form of the disease often presents with different characteristics, including a lower tumor mutational burden and a higher prevalence of actionable genetic mutations, potentially impacting treatment response. Understanding these differences is crucial for developing targeted therapies and effective screening protocols.

The Role of Genetics and Inherited Risk

Identifying individuals at elevated risk of LCINS is challenging, but emerging research points to both inherited and acquired biological predispositions. Studies have linked variations in genes like EGFR, TP53, ATM, and those within the APOBEC3 family to an increased risk of developing the disease. Specifically, mutations such as EGFR p.Thr790Met (T790M) can significantly elevate lifetime risk and potentially lead to the development of multiple lung lesions, according to research published in the journal Trends in Cancer. Population-specific genetic factors, such as deletions in the APOBEC3A/B genes, also appear to increase susceptibility in certain ethnic groups, suggesting that genetic screening could eventually play a role in risk-adapted surveillance.

Beyond inherited factors, a condition known as clonal hematopoiesis of indeterminate potential (CHIP) is gaining attention as a potential risk factor. CHIP involves mutations in hematopoietic stem cells, affecting genes like DNMT3A, TET2, and ASXL1. Individuals with a high proportion of cells carrying these mutations may face an increased risk of solid tumors, including lung cancer, independent of smoking status. The mechanism behind this link appears to involve chronic inflammation and elevated levels of interleukin-1β (IL-1β), though the effectiveness of anti-IL-1β therapies remains under investigation.

Environmental Factors and the “Exposome”

The cumulative impact of environmental exposures throughout a person’s life – known as the “exposome” – is increasingly recognized as a critical factor in LCINS development. Radon exposure, particularly in poorly ventilated indoor spaces, is a well-established carcinogen. Although historically linked to occupational exposure in miners, residential radon remains a public health concern. Exposure to secondhand smoke also increases lung cancer risk in never smokers by approximately 20–25%, though tumors in these individuals may not exhibit the same mutational signatures as those in smokers, suggesting a different underlying mechanism.

Air pollution, specifically fine particulate matter (PM2.5), is another significant environmental risk factor. High PM2.5 exposure correlates with a greater mutation burden, mutations in the TP53 gene, telomere shortening, and inflammation within the lungs. This pollution-induced inflammation, particularly involving IL-1β signaling, appears to promote tumorigenesis. However, accurately assessing risk is complicated by variations in exposure levels, especially in rapidly urbanizing areas.

Challenges and Advances in Early Detection

Early detection is paramount in improving lung cancer outcomes. Low-dose computed tomography (LDCT) screening has demonstrated a 20% reduction in lung cancer mortality among heavy smokers. However, applying LDCT to never smokers is more complex due to the difficulty in defining high-risk individuals and concerns about false positives, overdiagnosis, and cost-effectiveness. A clinical trial in Taiwan identified an elevated risk among never smokers with a first-degree family history of lung cancer, leading to an expansion of national screening criteria. Preliminary data suggest LDCT may be effective in select high-risk subgroups, such as Asian women with a familial predisposition, but further research is needed.

Emerging multi-cancer early-detection blood tests, which analyze circulating tumor DNA, are also under investigation, but their sensitivity for detecting highly early-stage lung cancer remains limited. Prevention strategies, including targeted therapies, immunotherapies, and cancer vaccines, are also being explored, particularly for individuals whose tumors harbor actionable genetic mutations.

LCINS represents a growing global health challenge that demands distinct diagnostic, screening, and therapeutic approaches. Integrating genetic susceptibility, clonal hematopoiesis, family history, and environmental exposures into comprehensive risk models may enable more precise screening and prevention strategies. Continued research is essential to advance our understanding of LCINS and develop tailored interception strategies to reduce mortality in this underrecognized patient population.

Disclaimer: This information is intended for general knowledge and informational purposes only, and does not constitute medical advice. It is essential to consult with a qualified healthcare professional for any health concerns or before making any decisions related to your health or treatment.

What are your thoughts on the potential for genetic screening to identify individuals at higher risk of lung cancer, even without a history of smoking? Share your perspectives in the comments below.

February 15, 2026 0 comments

Technology

Black Hole M87* Reveals Changing Magnetic Fields in New Images

by Sophie Lin - Technology Editor February 15, 2026

written by Sophie Lin - Technology Editor

Latest insights from the Event Horizon Telescope (EHT) collaboration have shed light on the enigmatic supermassive black hole M87*, located at the center of the galaxy M87. The latest images reveal not only the well-known glowing ring around the black hole but also fluctuations in polarized light, providing clues about the behavior of magnetic fields near its event horizon. This research, carried out by teams from the University of Waterloo and the Perimeter Institute for Theoretical Physics, indicates that while the size of the ring remains consistent, the polarization pattern—the magnetic “fingerprint”—changes dramatically from year to year.

This changing polarization suggests a turbulent environment close to the black hole, raising questions about why the magnetic signals fade and then flip. The observations show that in 2017, M87* displayed a spiraling polarization pattern, indicative of a large-scale, twisted magnetic structure. By 2018, this polarization nearly disappeared, only to reappear in 2021 with a reversed direction. The cumulative effects of these changes suggest that M87* and its surrounding environment are in a constant state of evolution.

A Steady Ring Amidst Change

The stable size of the ring around M87* reinforces theoretical predictions about the black hole’s shadow, as proposed by Einstein’s theory. Dr. Paul Tiede, an astronomer at the Center for Astrophysics | Harvard & Smithsonian, emphasized the significance of this finding, stating that the dynamic nature of the magnetized plasma near the event horizon challenges existing theoretical models. “This tells us that the magnetized plasma swirling near the event horizon is far from static; it’s dynamic and complex,” Tiede noted.

Magnetic Fields and High-Speed Jets

The EHT’s findings complicate the conventional view of black holes as perfect traps where matter is irretrievably lost. Instead, near M87*, energetic material can interact with a powerful electromagnetic field, potentially flinging material outward and feeding a jet that begins at the event horizon. This jet can reach speeds of approximately 90% the speed of light, linking the polarized light patterns to the dynamics of the jet’s formation.

As the EHT team continues to study M87*, they aim to capture new moments that reveal the complexities of this violent process. Dr. Avery Broderick, a professor in the Department of Physics and Astronomy at Waterloo, highlighted the efforts involved in reconstructing images from the EHT data. “We are now prying the answers from their grasp,” Broderick stated, emphasizing the importance of validating these findings as the team compares different years of data.

Understanding the Complex Surroundings of Black Holes

Physicists often refer to the idea that black holes “have no hair,” meaning they can be described by a few basic traits like mass, spin, and charge. However, the environment surrounding them is chaotic, and complex. Broderick explained that while black holes allow for precise predictions, the material around them can exhibit a variety of behaviors, much like different hairstyles. The moving, magnetized plasma near M87* is constantly changing, affecting how the black hole interacts with its surroundings.

In 2017, the magnetic field appeared organized enough to form a spiral structure, but by 2018, that order dissipated. The return of the spiral shape in 2021, albeit in the opposite direction, poses deeper questions for astrophysicists. They must now seek to explain what physical changes could cause such fluctuations in polarization.

Implications for Future Research

The new images from EHT provide a time-lapse view of magnetism in extreme gravitational conditions, which is crucial for understanding how black holes consume matter and launch jets. As the EHT continues to gather data over the coming years, scientists will be able to test various models and determine which withstand scrutiny against the realities observed.

the consistent size of the ring surrounding M87* reinforces confidence in the stability of certain features, allowing researchers to use it as a reliable reference point. This stability facilitates a focus on the changing aspects, such as polarization, without questioning the overall framework of their observations.

Through ongoing exploration, the EHT aims to illuminate the connections between the high-energy activities near the event horizon and the broader phenomena occurring in the jets. Understanding these relationships could enhance our knowledge of galaxy evolution, as jets significantly influence gas dynamics, dust interactions, and star formation across vast cosmic scales.

As researchers continue to unravel the complexities of M87*, the quest for knowledge about the universe’s underlying mechanisms remains a thrilling endeavor. The implications of this research extend beyond mere academic interest; they may hold the key to understanding the fundamental forces that shape our cosmos.

Readers are encouraged to follow the latest updates from the Event Horizon Telescope collaboration and engage in discussions about the implications of these discoveries. Your thoughts and insights are invaluable as we continue to explore the mysteries of the universe.