Nearly 16.5-foot cayenne pepper plant might be world's tallest
Henry Pope, the lead grower and plant geneticist for Mississippi Foundation for Renewable Energy, said he spent seven years cross-pollinating specific pepper plants with an aim toward creating a variety of plant ideal for vertical gardening.
"Opportunity for creating a world record of any kind was never the goal," Pope told the Clarion-Ledger newspaper. "The goal was the same as it always is for us, to produce a natural variety of edible plant that is beneficial to those who wish to become less reliant on the grocery store."
The current record was set in 1999, when California woman Laura Liang's plant grew to be 16 feet tall.
Pope had a team of measurement specialists, plant experts and local officials measure his cayenne for an official application to Guinness World Records. His cayenne was measured at about 16 feet and 5.5 inches tall.
The record-keeping organization must now review evidence from the measuring before the record becomes official.
Hashtags

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


UPI
16 hours ago
- UPI
Watch: 'Upload' Season 4 trailer teases 4-part finale
Robbie Amell (Nathan), Owen Daniels (A.I. Guy) star in "Upload." The fourth and final season arrives on Prime Video Aug. 25. Photo courtesy of Liane Hentscher/Prime Video Aug. 12 (UPI) -- Prime Video is previewing the final season of the sci-fi comedy series Upload ahead of its four-part finale, arriving on the streamer Aug. 25. The trailer released Tuesday shows Nora (Andy Allo) embrace Nathan (Robbie Amell), only to realize he is an apparent hologram. "Come find me," he says before disappearing. The show exists in a world where the wealthy don't die and instead upload their consciousness to a virtual reality afterlife. Season 4's last episodes show what happens when "sentient AI rapidly turns evil, threatening to wipe out Lakeview (and the world)!" according to an official synopsis. Greg Daniels, well known for his work on The Office, Parks and Recreation and King of the Hill, created the series. Kvin Bigley, Allegra Edwards, Zainab Johnson and Owen Daniels also star.


UPI
17 hours ago
- UPI
Clinical trial shows promise for new pancreatic cancer vaccine
A small clinical trial suggests a new vaccine aimed at a common cancer gene mutation could help stop aggressive pancreatic cancers from coming back. File Photo by Debbie Hill/UPI | License Photo A new vaccine aimed at a common cancer gene mutation could help stop aggressive pancreatic cancers from coming back, a small clinical trial suggests. Pancreatic cancer is one of the most lethal cancers, with a five-year survival rate of about 13%, according to the American Cancer Society. Further, up to 80% of cases return after treatment, the National Institutes of Health says. "If you were to ask me what disease most needs something to prevent recurrences, I'd say this one," Dr. Zev Wainberg, a leader of the trial, told NBC News. He's co-director of the University of California, Los Angeles gastrointestinal oncology program. The experimental vaccine targets KRAS gene mutations, which are found in about 25% of all cancers, the University of Texas MD Anderson Cancer Center says. This includes up to 90% of pancreatic cancers and roughly 40% of colon cancers. While these mutations have long been considered impossible to treat with drugs, researchers are finding new ways to target them. The vaccine, called ELI-002 2P, uses small chains of amino acids called peptides to train the immune system to spot and destroy cells with KRAS mutations. Unlike many cancer vaccines that are custom-made for each patient, this one is designed to be off the shelf, meaning it doesn't require the tumor to be sequenced before it's used, NBC News reported. The Phase 1 study -- reported Tuesday in Nature Medicine -- included 20 people with pancreatic cancer and five with colon cancer. All had KRAS mutations and had already undergone surgery and chemotherapy. Blood tests after surgery showed microscopic evidence of residual disease - cancer cells too small to see on scans. These leftover cells can cause the cancer to spread and return. Post-surgery, participants received up to six priming doses of the vaccine, with 13 also getting booster shots. In all, the process took six months. Here's what the results showed: 85% (21 of 25 participants) had an immune response to the KRAS mutations. About two-thirds of those had a strong enough response to help clear lingering cancer cells. Nearly 70% developed immunity to other tumor targets not included in the vaccine. A few "super-responders" had exceptionally strong immune reactions and the best outcomes. In the pancreatic cancer group, patients survived for an average of 29 months, staying recurrence-free for more than 15 months after vaccination. "That far exceeds the rates with resectable [surgically removable] cancers," Wainberg said. Cancer vaccines have been difficult to create because cancer cells share many proteins with healthy cells, making safe targets hard to find. Advances in mRNA technology and faster gene sequencing are now making more effective cancer vaccines possible. The peptides in this vaccine also have a unique "tail" that helps them stay in lymph nodes, where immune cells are activated -- a feature past peptide vaccines didn't have, said Stephanie Dougan, an associate professor at Dana-Farber Cancer Institute in Boston, who was not involved in the study. More research is needed to confirm the findings, and a Phase 2 trial is now underway to compare the vaccine with standard care. "The fact that the long-term survival really correlated with T-cell response suggests that the vaccine caused this," Dougan said, referring to the specific immune cells activated by the vaccine. "The idea that you can target KRAS is really exciting." More information The Mayo Clinic has more on pancreatic cancer. Copyright © 2025 HealthDay. All rights reserved.


UPI
18 hours ago
- UPI
Study: AI programs might help ER overcrowding in hospitals
New York researchers said artificial intelligence programs can help doctors and nurses predict hours earlier which ER patients will likely require hospital admission. File Photo by Thomas Maresca/UPI | License Photo Artificial intelligence programs can help doctors and nurses predict hours earlier which ER patients will likely require hospital admission, a new study says. An AI program trained on nearly 2 million patient visits became slightly more accurate than ER nurses in predicting which patients would need to be admitted, according to findings published Aug. 11 in the journal Mayo Clinic Proceedings: Digital Health. If this approach proves successful, it could help reduce overcrowding in hospital emergency departments, researchers say. "Emergency department overcrowding and boarding have become a national crisis, affecting everything from patient outcomes to financial performance," said lead researcher Jonathan Nover, vice president of nursing and emergency services at Mount Sinai Health System in New York City. "Industries like airlines and hotels use bookings to forecast demand and plan. In the ED, we don't have reservations," he continued in a news release. "Could you imagine airlines and hotels without reservations, solely forecasting and planning from historical trends? Welcome to health care." Up to 35% of ER patients who require admission wind up spending four or more hours biding their time in spare rooms or busy hallways awaiting a bed, a practice known as "boarding," according to a recent study in the journal Health Affairs. Worse, nearly 5% of patients wait a full day for a bed during the busy winter months, the earlier study found. "Our goal was to see if AI combined with input from our nurses could help hasten admission planning, a reservation of sorts," Nover said. "We developed a tool to forecast admissions needs before an order is placed, offering insights that could fundamentally improve how hospitals manage patient flow, leading to better outcomes." For the project, researchers trained the AI on more than 1.8 million ER visits that had occurred between 2019 and 2023. "By training the algorithm on more than a million patient visits, we aimed to capture meaningful patterns that could help anticipate admissions earlier than traditional methods," co-senior researcher Dr. Eyal Klang, chief of generative AI at the Icahn School of Medicine at Mount Sinai, said in a news release. The team then put the AI up against a cadre of more than 500 ER nurses in evaluating nearly 47,000 patient visits that occurred in September and October 2024 at six emergency departments in the Mount Sinai Health System. The nurses were asked to judge whether a patient would need hospital admission, after performing a quick triage. Researchers also fed the triage results to the AI, to see what it would predict. The nurses proved about 81% accurate in predicting which patients would need hospital admission, compared to 85% accuracy from the AI. "We were encouraged to see that AI could stand on its own in making complex predictions," co-senior researcher Robert Freeman, chief digital transformation officer at Mount Sinai Health System, said in a news release. "But just as important, this study highlights the vital role of our nurses -- more than 500 participated directly -- demonstrating how human expertise and machine learning can work hand in hand to reimagine care delivery." Researchers next plan to implement their AI into real-time workflows and monitor how the program affects boarding times and patient flow through the ER. "This tool isn't about replacing clinicians; it's about supporting them. By predicting admissions earlier, we can give care teams the time they need to plan, coordinate, and ultimately provide better, more compassionate care," Freeman said. "It's inspiring to see AI emerge not as a futuristic idea, but as a practical, real-world solution shaped by the people delivering care every day." More information The American College of Emergency Physicians has more on ER boarding and crowding. Copyright © 2025 HealthDay. All rights reserved.