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Look up! What's going on in the July night sky?

Look up! What's going on in the July night sky?

Yahoo10 hours ago
Eyes to the sky for the month of July to see the Buck Moon, two different meteor showers crisscrossing the night, and the waning phases of the Moon appearing near some of the brightest planets in the sky.
Here is the Astronomical Guide for July 2025:
July 2 — First Quarter Moon
July 10-11 — Full Buck Moon
July 12 — delta Aquariid meteor shower begins
July 15-16 — Saturn near Gibbous Moon (after midnight)
July 17 — Perseid meteor shower begins
July 18 — Last Quarter Moon
July 21 — Venus near Crescent Moon, Jupiter nearby (predawn)
July 23 — Jupiter near Crescent Moon, Venus nearby (predawn)
July 24 — New Moon
July 28 — Mars near Crescent Moon (evening)
July 28-29 — delta Aquariid Meteor Shower peaks
The astronomical events for July 2025, including the phases of the Moon, planetary conjunctions, and meteor showers. (Scott Sutherland, moon graphics from NASA's Scientific Visualization Studio, conjunctions courtesy Stellarium)
The Waxing Crescent Moon will be in the western sky during the evening hours on the first night of the month, with the First Quarter Moon rising on the second.
We will see the Waxing Gibbous Moon from the 3rd through the 9th, with the Full Buck Moon — the first Full Moon of Summer 2025 — crossing the sky from the evening on the 10th through until the morning on the 11th. However, the Moon will appear full (over 99 per cent illuminated by the Sun) from just after midnight on the morning of the 10th through until the evening of the 11th.
The Waning Gibbous Moon will shine in the sky from the 11th to the 16th. Look for it near Saturn in the hours after midnight on the night of the 15th to the 16th.
The Last Quarter Moon rises on the 17th, with the Waning Crescent Moon visible in the eastern predawn sky each morning from the 18th to the 23th. See it pass by bright Venus on the 21st, then nestled between Venus and Jupiter on the 22nd, and finally passing Jupiter on the 23rd.
The night of the 24th could be the best time to look for meteors (see below), as the New Moon gives us the darkest skies of the month.
Then, once the Waxing Crescent Moon reappears in our evening skies, look for it near the planet Mars just above the western horizon after sunset on the 28th.
DON'T MISS:
When we hear about meteor showers, often only the peak of the event gets any solid mention. It's certainly understandable, since that is when the greatest number of meteors from that particular shower are visible to us. However, meteor showers are not limited to just one night. For the dozen or so notable ones we follow each year, the shortest lasts for around 4 days, while the longest goes on for over two months!
During the month of July, we see the start of two different meteor showers, both of which are remarkable in some way.
The first begins on the night of July 17. Appearing to streak out of the constellation Perseus, in the northeastern sky, this meteor shower is known as the Perseids, and it is one of the best of the entire year.
Originating from a comet known as 109P/Swift-Tuttle, the Perseids typically deliver between 50-75 meteors per hour during the shower's mid-August peak. It also produces the greatest number of fireballs out of all the meteor showers of the year. Fireballs are meteors of exceptional brightness, many of which can be seen even through urban light pollution. While most Perseid meteors result from miniscule specks of space dust hitting the atmosphere, the fireballs are due to comet debris ranging from a grain of sand up to a pebble in size.
The Perseids start off slowly in July. For the first week or so after the shower begins, we may see just a few meteors each hour, flashing out of the northeastern sky. However, by the end of the month, it typically is already producing around 15-20 meteors per hour. Even though that's still around two weeks before the Perseid's peak, that's still equivalent to the peak of a moderate meteor shower, like the April Lyrids!
Just one night after the Perseids start, we encounter a second stream of debris in space, resulting in the Southern delta Aquariid meteor shower. While this one tends to put on a better display for those located in the southern hemisphere, skywatchers across Canada should still get a decent show out of it.
As with the Perseids, the delta Aquariids start off at a rate of just one or two meteors per hour on the nights of the first week or so. During the last few nights of July, though, this meteor shower reaches its peak, with the rate jumping up to around 20 per hour. Overlapping with Perseids at that time, the sky could be filled with crisscrossing meteors at the end of the month.
Astronomers aren't quite sure exactly which comet or asteroid the delta Aquariids come from, but right now, the most likely 'parent body' is an oddball comet called 96P/Machholz.
Discovered in 1986, Comet Machholz has a strange orbit and chemical composition compared to other similar comets. One hypothesis for this is that it could be an alien comet from some distant star system that was ejected and then captured by the gravity of our Sun. Thus, each delta Aquariid meteor could represent a piece of some distant solar system burning up in our atmosphere!
READ MORE:
The summer constellations shine this month.
In the south, Leo leads the way as the constellations cross the sky, with Virgo, Libra, Scorpius, Serpens/Ophiuchus, and Aquila in a loose lineup just after sunset. Higher up in the sky we will see Boötes, Hercules, and Cygnus.
The constellations in the southern sky at midnight on July 15-16, 2025. (Stellarium)
After midnight, Sagittarius, Capricornus, Aquarius, Pisces, and Cetus follow, with Taurus rising predawn and the "bow" of Orion poking up above the horizon just before sunrise. High up, Pegasus, Andromeda and Perseus swing around from the north.
Meanwhile, if you are facing north, Pegasus, Andromeda, and Perseus will be near the northern horizon at the start of the night. Cygnus, Cepheus, Cassiopeia, and Camelopardalis ("The Camel") will be visible low in the evening sky, along with Lynx to the northwest. Ursa Major ("The Big Dipper"), Ursa Minor ("The Little Dipper"), and Draco will be circling the north celestial pole.
The constellations in the northern sky at midnight on July 15-16, 2025. (Stellarium)
After midnight, Auriga and Taurus will rise in the northeast, with Orion showing up before dawn.
Thumbnail image shows a Perseid meteor captured by Nelson Liu from Ottawa on August 13, 2023.
Click here to view the video
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A couple tried for 18 years to get pregnant. AI made it happen
A couple tried for 18 years to get pregnant. AI made it happen

CNN

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A couple tried for 18 years to get pregnant. AI made it happen

AI Maternal health Women's health FacebookTweetLink After trying to conceive for 18 years, one couple is now pregnant with their first child thanks to the power of artificial intelligence. The couple had undergone several rounds of in vitro fertilization, or IVF, visiting fertility centers around the world in the hopes of having a baby. The IVF process involves removing a woman's egg and combining it with sperm in a laboratory to create an embryo, which is then implanted in the womb. But for this couple, the IVF attempts were unsuccessful due to azoospermia, a rare condition in which no measurable sperm are present in the male partner's semen, which can lead to male infertility. A typical semen sample contains hundreds of millions of sperm, but men with azoospermia have such low counts that no sperm cells can be found, even after hours of meticulous searching under a microscope. So the couple, who wish to remain anonymous to protect their privacy, went to the Columbia University Fertility Center to try a novel approach. It's called the STAR method, and it uses AI to help identify and recover hidden sperm in men who once thought they had no sperm at all. All the husband had to do was leave a semen sample with the medical team. 'We kept our hopes to a minimum after so many disappointments,' the wife said in an emailed statement. Researchers at the fertility center analyzed the semen sample with the AI system. Three hidden sperm were found, recovered and used to fertilize the wife's eggs via IVF, and she became the first successful pregnancy enabled by the STAR method. The baby is due in December. 'It took me two days to believe I was actually pregnant,' she said. 'I still wake up in the morning and can't believe if this is true or not. I still don't believe I am pregnant until I see the scans.' Artificial intelligence has advanced the field of fertility care in the United States: More medical facilities are using AI to help assess egg quality or screen for healthy embryos when patients are undergoing IVF. There's still more research and testing needed, but AI may now be making advancements in male infertility, in particular. Dr. Zev Williams, director of the Columbia University Fertility Center, and his colleagues spent five years developing the STAR method to help detect and recover sperm in semen samples from people who had azoospermia. They were struck by the system's results. 'A patient provided a sample, and highly skilled technicians looked for two days through that sample to try to find sperm. They didn't find any. We brought it to the AI-based STAR System. In one hour, it found 44 sperm. So right then, we realized, 'Wow, this is really a game-changer. This is going to make such a big difference for patients,' ' said Williams, who led the research team. When a semen sample is placed on a specially designed chip under a microscope, the STAR system – which stands for Sperm Tracking and Recovery – connects to the microscope through a high-speed camera and high-powered imaging technology to scan the sample, taking more than 8 million images in under an hour to find what it has been trained to identify as a sperm cell. The system instantly isolates that sperm cell into a tiny droplet of media, allowing embryologists to recover cells that they may never have been able to find or identify with their own eyes. 'It's like searching for a needle scattered across a thousand haystacks, completing the search in under an hour and doing it so gently, without any harmful lasers or stains, that the sperm can still be used to fertilize an egg,' Williams said. 'What's remarkable is that instead of the usual [200 million] to 300 million sperm in a typical sample, these patients may have just two or three. Not 2 [million] or 3 million, literally two or three,' he said. 'But with the precision of the STAR system and the expertise of our embryologists, even those few can be used to successfully fertilize an egg.' It's estimated that the male partner accounts for up to 40% of all infertility cases in the United States, and up to 10% of men with infertility are azoospermic. 'This often is a really heartbreaking and shocking and unexpected diagnosis,' Williams said. 'Most men who have azoospermia feel completely healthy and normal. There's no impairment of their sexual function, and the semen looks normal, too. The difference is that when you look at it under a microscope, instead of seeing literally hundreds of millions of sperm swimming, you just see cell debris and fragments but no sperm.' Treatment options for azoospermia traditionally have included uncomfortable surgery to retrieve sperm directly from a patient's testes. 'A part of the testes gets removed and broken into little pieces, and you try to find sperm there,' Williams said. 'It's invasive. You can only do it a couple of times before there could be permanent scarring and damage to the testes, and it's painful.' Other treatment options may include prescription hormone medications – but that will be effective only if the person has an imbalance of hormones. If no other treatment options are successful, couples may use donor sperm to have a child. Williams said the STAR method can be a new option. 'It really was a team effort to develop this, and that's what really drove and motivated everybody, the fact that you can now help couples who otherwise couldn't have that opportunity,' he said. Although the method is currently available only at the Columbia University Fertility Center, Williams and his colleagues want to publish their work and share it with other fertility centers. Using the STAR method to find, isolate and freeze sperm for a patient would cost a little under $3,000 total, he said. 'Infertility is unique in a way in that it's such an ancient part of the human experience. It's literally biblical. It's something we've had to contend with through all of human history,' he said. 'It's amazing to think that the most advanced technologies that we currently have are being used to solve this really ancient problem.' It's not the first time doctors have turned to AI to help men with azoospermia. A separate research team in Canada built an AI model that could automate and accelerate the process of searching for rare sperm in samples from men with the condition. 'The reason AI is so well-suited for this is AI really relies on learning – showing it an image of what a sperm looks like, what the shape is, what characteristics it should have – and then being able to use that learning algorithm to help identify that specific image that you're looking for,' said Dr. Sevann Helo, a urologist at Mayo Clinic with specialty interest in male infertility and male sexual dysfunction, who was not involved in the STAR method or the research in Canada. 'It's very exciting,' she said. 'AI, in general, at least in the medical community, I think is a whole new landscape and really will revolutionize the way we look at a lot of problems in medicine.' The STAR method is a novel approach to identifying sperm, but AI has been used in many other ways within fertility medicine too, said Dr. Aimee Eyvazzadeh, a San Francisco-based reproductive endocrinologist and host of the podcast 'The Egg Whisperer Show.' 'AI is helping us see what our eyes can't,' Eyvazzadeh, who was not involved in the development of STAR, wrote in an email. For instance, AI algorithms, such as one called Stork-A, have been used to analyze early-stage embryos and predict with 'surprising accuracy' which ones are likely to be healthy. Another AI tool, CHLOE, can assess the quality of a woman's eggs before she may freeze them for future use. 'AI is being used to personalize IVF medication protocols, making cycles more efficient and less of a guessing game. It's also helping with sperm selection, identifying the healthiest sperm even in difficult samples. And AI can now even predict IVF success rates with more precision than ever before, using massive data sets to give patients personalized guidance,' Eyvazzadeh said. 'The common thread? Better decisions, more confidence, and a more compassionate experience for patients.' The new STAR system is 'a game-changer,' she said. 'AI isn't creating sperm – it's helping us find the rare, viable ones that are already there but nearly invisible,' she said. 'It's a breakthrough not because it replaces human expertise, but because it amplifies it – and that's the future of fertility care.' But there is also a growing concern that the rushed application of AI in reproductive medicine could give false hope to patients, said Dr. Gianpiero Palermo, professor of embryology and director of andrology and assisted fertilization at Weill Cornell Medicine. 'AI is gaining a lot of traction nowadays to offer unbiased evaluation on embryos by looking at embryo morphology,' Palermo said in an email. 'However, current available models are still somewhat inconsistent and require additional validation.' Palermo said the STAR approach needs to be validated and would still require human embryologists to pick up sperm and inject them into an egg to create an embryo for patients undergoing IVF. 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MRI May Aid Early Pancreatic Cancer Detection in Diabetes
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MRI May Aid Early Pancreatic Cancer Detection in Diabetes

TOPLINE: MRI-based screening in patients older than 50 years with new-onset or deteriorating diabetes detected stage IB pancreatic cancer in a patient with deteriorating diabetes, highlighting the need for targeted screening in this high-risk population. METHODOLOGY: New-onset diabetes in patients older than 50 years was found to increase the risk for pancreatic cancer by six- to eight-fold, and recent evidence suggests that the deterioration of diabetes in individuals with stable, long-standing disease may also be an indicator of subclinical pancreatic cancer. Researchers conducted the PANDOME study to evaluate the effectiveness and safety of MRI-based screening for the early detection of pancreatic cancer in patients with new-onset diabetes (n = 97; median age, 61 years; 63.9% women) or deteriorating diabetes (n = 12; median age, 68 years; 58.3% women). New-onset diabetes was defined as elevated A1c levels within the past 12 months, whereas deteriorating diabetes was defined as long-standing diabetes (> 2 years) with a > 2% increase in A1c levels over the past 6 months not linked to weight gain or diabetes medication noncompliance. All patients underwent MRI/cholangiopancreatography, blood biobanking, and anxiety/depression monitoring; MRI results were scored as normal, benign-abnormal, suspicious, or incidental findings. TAKEAWAY: Compared with patients with new-onset diabetes, those with deteriorating diabetes had significantly higher A1c levels (P = .02), greater weight loss (P = .0038), and increased insulin requirements (P < .0001). Among 109 participants, more than 50% had small cystic lesions with an average size of 6 mm, prompting seven endoscopic ultrasound procedures — four of which required biopsies. Of the four pancreatic biopsies performed, one revealed stage IB pancreatic ductal adenocarcinoma in a patient with deteriorating diabetes. Extra-pancreatic incidental findings were detected in 8.2% of cases, with two requiring biopsies, revealing one new diagnosis of follicular lymphoma and one diagnosis of recurrent lymphoma. According to the Enriching New-Onset Diabetes for Pancreatic Cancer score — where a high-risk score predicts a 3.6% probability of pancreatic cancer within 3 years — the deteriorating diabetes group had a higher proportion of high-risk individuals than the new-onset diabetes group (75% vs 35.6%). IN PRACTICE: 'Preliminary results from the PANDOME study support further MRI-based PC [pancreatic cancer] screening research efforts in individuals with NOD [new-onset diabetes] and DD [deteriorating diabetes],' the authors concluded. SOURCE: This study was led by Richard Frank, MD, Division of Hematology/Oncology, Nuvance Health, Norwalk, Connecticut. It was published online in The Journal of Clinical Endocrinology & Metabolism. LIMITATIONS: T his study faced challenges with low accrual rates due to healthcare network realignments and high declination rates by potential participants. Selection bias potentially led to lower detection rates, as most participants were referred by primary care physicians or endocrinologists. Moreover, the majority of participants were White individuals (83%), despite higher pancreatic cancer risk among Black populations, limiting generalizability. DISCLOSURES: This study received support from a Tribute to Pamela/The Naughton Family Fund, the Rallye for Pancreatic Cancer, Pacific Crest Trail for Pancreatic Cancer, and the Glenn W. Bailey Foundation. The authors declared no conflicts of interest. This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

New Wearable Algorithm Improves Fitness Tracking in Obesity
New Wearable Algorithm Improves Fitness Tracking in Obesity

Medscape

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New Wearable Algorithm Improves Fitness Tracking in Obesity

A new algorithm enabled smartwatch fitness trackers to more accurately estimate energy expenditure by individuals with obesity. In two studies conducted in a total of 52 people for 1838 minutes in a lab and 14,045 minutes in a 'free-living' situation, the algorithm performed mostly as well or better than 11 'gold-standard' algorithms designed by other researchers using research-grade devices, achieving over 95% accuracy in people with obesity in real-world situations. The algorithm bridges an important gap in fitness technology — that most wearable devices are using algorithms validated mainly in people without obesity, said Nabil Alshurafa, PhD, Feinberg School of Medicine, Northwestern University, in Chicago. Alshurafa was motivated to create the algorithm after attending an exercise class with his mother-in-law, who had obesity. His mother-in-law worked hard, but her effort barely showed on the leaderboard. He realized that most current fitness trackers use activity-monitoring algorithms developed for people without obesity. 'Commercial devices calibrate their accelerometer-to-calorie models using data mostly from people with normal BMI, using algorithms that rely on 'average' gait and metabolism,' he told Medscape Medical News. 'But people with obesity are known to exhibit differences in walking gait, speed, resting energy expenditure, and physical function. When you feed 'average' motion to kcal [kilocalories] mappings for people with different gait patterns, the math does not always line up.' This may be particularly true for people with obesity who wear fitness trackers throughout the day on their hip, rather than their wrist, because of differences in gait patterns and other body movements. The study was published online in Scientific Reports . The anonymized dataset and code and documentation are publicly available for use by other researchers. 'More Inclusive and Reliable' Researchers in Alshurafa's lab developed and tested the open-source, dominant-wrist algorithm specifically tuned for people with obesity. The algorithm estimated metabolic equivalent of task (MET) values per minute from commercial smartwatch sensor data and compared them to actigraphy-based energy estimates in people with obesity. In an in-lab study, 27 participants performed activities of varying intensities while wearing a smartwatch and a metabolic cart — a mask that measures the volume of oxygen the wearer inhales and the volume of carbon dioxide the wearer exhales to calculate their energy burn in kcals and their resting metabolic rate. The activities included, among others, typing on a computer, lying still on the floor doing nothing, walking slowly on a treadmill, doing pushups against a door, and following along with an aerobics video. Each activity was performed for 5 minutes, followed by 5 minutes of rest. The researchers compared the fitness tracker results against the metabolic cart results. Another 25 participants wore a smartwatch and a body camera for 2 days in a free-living study. The body camera enabled the researchers to visually confirm when the algorithm over- or under-estimated kcals. The in-lab analysis included 2189 minutes of data and the free-living analysis included 14,045 minutes of data. Compared to the metabolic cart, the new algorithm achieved lower root mean square error across various sliding windows (analyses of continuous and overlapping data streams). In the free-living study, the algorithm's estimates fell within ±1.96 SDs of the best actigraphy-based estimates for 95.03% of minutes. 'Our proposed method accurately estimated METs compared to 11 algorithms primarily validated in nonobese populations, suggesting that commercial wrist-worn devices can provide more inclusive and reliable [energy expenditure] measures using our algorithm,' the authors wrote. Challenges Ahead More work needs to be done before apps for iOS and android driven by the new algorithm are available for use later this year, Alshurafa said. Because the model is tuned for users with obesity, 'we need a reliable way to obtain BMI or body composition, and possibly ways of turning on and off the algorithm over time or perhaps modifying the algorithm as people's fitness level changes.' 'Because we've optimized for the dominant hand, we'll need clear user guidance, and possibly user-interface prompts, to drive this cultural shift in watch placement,' he said. To ensure accuracy across diverse users, activities, and wear styles, the team will conduct field testing and pool anonymized data. 'Power, size, and regulatory requirements may force trade-offs, so we'll work closely with device manufacturers on adaptive calibration routines and streamlined firmware,' Alshurafa said. 'But the real priority is training and tailoring our systems on truly diverse data and being transparent about who's represented in that data. Too many commercial devices skip this, leading users to assume they work universally when their models actually have limitations.' For now, clinicians should be aware that the app has only been validated so far in individuals with obesity wearing their tracker on the dominant wrist and use outside that population or on the nondominant wrist may yield less accurate calorie estimates, he added. 'Beyond those parameters, though, the algorithm is ready for deployment and offers a powerful new tool for personalized activity monitoring.' Mir Ali, MD, a bariatric surgeon and medical director of MemorialCare Surgical Weight Loss Center at Orange Coast Medical Center in Fountain Valley, California, agreed that an algorithm that more accurately reflects exercise and energy expenditure of patients with obesity would be helpful, and that 'any improvements' would likely be beneficial for patients and clinicians. That said, 'a larger study comparing the new algorithm vs currently available devices would provide more validation,' Ali, who was not involved in the study, told Medscape Medical News . In addition, 'research elucidating exercise goals and calorie expenditure for obese patients could be helpful to better counsel patients on what is the optimal goal for weight loss,' he said. Ali noted that 'trackers for heart disease and pulmonary problems may be useful to help patients attain cardio-pulmonary improvement' — and indeed, Alshurafa's team will be looking at ways to tailor fitness trackers for diabetes and hypertension going forward. This study is based on work supported by the National Institute of Diabetes and Digestive and Kidney Diseases, the National Science Foundation, the National Institute of Biomedical Imaging and the National Institutes of Health's National Center for Advancing Translational Sciences. Alshurafa and Ali declared no competing interests.

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