Peptide derived from cow's milk kills human stomach cancer cells in culture
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7-Nov-2013
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Contact: Eileen Leahy jdsmedia@elsevier.com 732-238-3628 Elsevier Health Sciences
Findings reported in the Journal of Dairy Science show promise for treatment of gastric cancer
Philadelphia, PA, November 7, 2013 New research from a team of researchers in Taiwan indicates that a peptide fragment derived from cow's milk, known as lactoferricin B25 (LFcinB25), exhibited potent anticancer capability against human stomach cancer cell cultures. The findings, published in the Journal of Dairy Science, provide support for future use of LFcinB25 as a potential therapeutic agent for gastric cancer.
"Gastric cancer is one of the most common causes of cancer-related mortality worldwide, especially in Asian countries," says Wei-Jung Chen, PhD, of the Department of Biotechnology and Animal Science of National Ilan University, Taiwan Republic of China. "In general, the main curative therapies for gastric cancer are surgery and chemotherapy, which are generally only successful if the cancer is diagnosed at an early stage. Novel treatment strategies to improve prognosis are urgently needed."
Investigators evaluated the effects of three peptide fragments derived from lactoferricin B, a peptide in milk that has antimicrobial properties. Only one of the fragments, LFcinB25 reduced the survival of human AGS (Gastric Adenocarcinoma) cells in a dose-dependent and time-dependent manner.
Under a microscope the investigators could see that after an hour of exposure to the gastric cancer cells, LFcinB25 migrated to the cell membrane of the AGS cells, and within 24 hours the cancer cells had shrunken in size and lost their ability to adhere to surfaces. In the early stages of exposure, LFcinB25 reduced cell viability through both apoptosis (programmed cell death) and autophagy (degradation and recycling of obsolete or damaged cell parts). At later stages, apoptosis appeared to dominate, possibly through caspase-dependent mechanisms, and autophagy waned.
"This is the first report describing interplay between apoptosis and autophagy in LFcinB-induced cell death of cancer cells," says Dr. Chen.
The research also suggested a target, Beclin-1, which may enhance LFcinB25's cytotoxic action. Beclin-1 is a protein in humans that plays a central role in autophagy, tumor growth, and degeneration of neurons. In this study, the investigators found that cleaved beclin-1 increased in a time-dependent manner after LFcinB25-exposure, suggesting to the authors a new approach in drug development that may boost the anticancer effects of LFcinB25.
"Optimization of LFcinB using various strategies to enhance further selectivity is expected to yield novel anticancer drugs with chemotherapeutic potential for the treatment of gastric cancer," concludes Dr. Chen.
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Peptide derived from cow's milk kills human stomach cancer cells in culture
PUBLIC RELEASE DATE:
7-Nov-2013
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]
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Contact: Eileen Leahy jdsmedia@elsevier.com 732-238-3628 Elsevier Health Sciences
Findings reported in the Journal of Dairy Science show promise for treatment of gastric cancer
Philadelphia, PA, November 7, 2013 New research from a team of researchers in Taiwan indicates that a peptide fragment derived from cow's milk, known as lactoferricin B25 (LFcinB25), exhibited potent anticancer capability against human stomach cancer cell cultures. The findings, published in the Journal of Dairy Science, provide support for future use of LFcinB25 as a potential therapeutic agent for gastric cancer.
"Gastric cancer is one of the most common causes of cancer-related mortality worldwide, especially in Asian countries," says Wei-Jung Chen, PhD, of the Department of Biotechnology and Animal Science of National Ilan University, Taiwan Republic of China. "In general, the main curative therapies for gastric cancer are surgery and chemotherapy, which are generally only successful if the cancer is diagnosed at an early stage. Novel treatment strategies to improve prognosis are urgently needed."
Investigators evaluated the effects of three peptide fragments derived from lactoferricin B, a peptide in milk that has antimicrobial properties. Only one of the fragments, LFcinB25 reduced the survival of human AGS (Gastric Adenocarcinoma) cells in a dose-dependent and time-dependent manner.
Under a microscope the investigators could see that after an hour of exposure to the gastric cancer cells, LFcinB25 migrated to the cell membrane of the AGS cells, and within 24 hours the cancer cells had shrunken in size and lost their ability to adhere to surfaces. In the early stages of exposure, LFcinB25 reduced cell viability through both apoptosis (programmed cell death) and autophagy (degradation and recycling of obsolete or damaged cell parts). At later stages, apoptosis appeared to dominate, possibly through caspase-dependent mechanisms, and autophagy waned.
"This is the first report describing interplay between apoptosis and autophagy in LFcinB-induced cell death of cancer cells," says Dr. Chen.
The research also suggested a target, Beclin-1, which may enhance LFcinB25's cytotoxic action. Beclin-1 is a protein in humans that plays a central role in autophagy, tumor growth, and degeneration of neurons. In this study, the investigators found that cleaved beclin-1 increased in a time-dependent manner after LFcinB25-exposure, suggesting to the authors a new approach in drug development that may boost the anticancer effects of LFcinB25.
"Optimization of LFcinB using various strategies to enhance further selectivity is expected to yield novel anticancer drugs with chemotherapeutic potential for the treatment of gastric cancer," concludes Dr. Chen.
###
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Now that anyone (well, anyone with an invitation) with a spare $1,500 can get their very own Google Glass, the folks in Mountain View have thoughtfully released a software update for the famous wearable. We're frankly surprised Glass owners weren't able to do this before, but you can now look up ...
New method predicts time from Alzheimer's onset to nursing home, death
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Contact: Elizabeth Streich eas2125@cumc.columbia.edu 212-305-3689 Columbia University Medical Center
Draws on information from a single patient visit
NEW YORK, NY (Nov. 7, 2013) A Columbia University Medical Center-led research team has clinically validated a new method for predicting time to full-time care, nursing home residence, or death for patients with Alzheimer's disease. The method, which uses data gathered from a single patient visit, is based on a complex model of Alzheimer's disease progression that the researchers developed by consecutively following two sets of Alzheimer's patients for 10 years each. The results were published online ahead of print in the Journal of Alzheimer's Disease.
"Predicting Alzheimer's progression has been a challenge because the disease varies significantly from one person to anothertwo Alzheimer's patients may both appear to have mild forms of the disease, yet one may progress rapidly, while the other progresses much more slowly," said senior author Yaakov Stern, PhD, professor of neuropsychology (in neurology, psychiatry, and psychology and in the Taub Institute for Research on Alzheimer's Disease and the Aging Brain and the Gertrude H. Sergievsky Center) at CUMC. "Our method enables clinicians to predict the disease path with great specificity."
"Until now, some methods of predicting the course of Alzheimer's have required data not obtained in routine clinical practice, such as specific neuropsychological or other measurements, and have been relatively inaccurate. This method is more practical for routine use," said Nikolaos Scarmeas, MD, a study co-author and associate professor of neurology, in the Taub Institute and the Sergievsky Center. "It may become a valuable tool for both physicians and patients' families."
The new method also may be used in clinical trialsto ensure that patient cohorts are balanced between those with faster-progressing Alzheimer's and those with slower-progressing diseaseand by health economists to predict the economic impact of Alzheimer's disease.
The prediction method is based on a Longitudinal Grade of Membership (L-GoM) model, developed by a research team also led by Dr. Stern and published in 2010.
The L-GoM includes 16 sets of variables, such as ability to participate in routine day-to-day activities; mental status; motor skills; estimated time of symptom onset; and duration of tremor, rigidity, or other neurological symptoms. It also includes data obtained postmortem (time and cause of death).
"The benefit of the L-GoM model is that it takes into account the complexity of Alzheimer's disease. Patients don't typically fall neatly into mild, moderate, or severe disease categories. For example, a patient may be able to live independently yet have hallucinations or behavioral outbursts," said Dr. Stern, who also directs the Cognitive Neuroscience Division at CUMC. "Our method is flexible enough to handle missing data. Not all 16 variables are needed for accurate predictionsjust as many as are available."
Results can be presented as expected time to a particular outcome. Two 68-year-old Alzheimer's patients, for example, had similar mental status scores (one a mini-mental status score (mMMS) of 38/54, the other of 39/54) at initial visit. The first patient was more dependent on his caregiver and had psychiatric symptoms (delusions). These and other subtle differences in the initial presentation of the two patients resulted in different predictions of time until death. The method accurately predicted that the first patient would die within three years, while the other would survive more than 10 years.
"In addition to time to nursing home residence or death, our method can be used to predict time to assisted living or other levels of care, such as needing help with eating or dressing, or time to incontinence," said first author Ray Razlighi, PhD, assistant professor of neurology at CUMC and adjunct assistant professor of biomedical engineering at Columbia University.
Development of the method began in 1989, when Dr. Stern received a grant from the National Institutes of Health to begin the Predictors of Severity in Alzheimer's Disease study. "The fact that work on this prediction method began nearly 25 years ago underlines the difficulties of studying Alzheimer's disease," said Richard Mayeux, MD, MS, neurology chair, the Gertrude H. Sergievsky Professor of Neurology, Psychiatry and Epidemiology and co-director of the Taub Institute and the Sergievsky Center.
Dr. Stern and colleagues at Massachusetts General Hospital and Johns Hopkins first followed 252 non-familial Alzheimer's patients every six months for 10 years. Eric Stallard, an actuary at Duke and a co-author of the paper, used the resultant data to create an L-GoM model of Alzheimer's progression. They published their results in 2010 in Medical Decision Making. The researchers then followed a separate group of 254 patients and used data from only a single patient visit to predict outcomes for this group.
Dr. Stern and his team are now developing a computer program that would allow clinicians to input the variables and receive a report. They expect the program to become available within the next two years. Eventually, such a program might be incorporated into electronic health records. "At our Alzheimer's center, patients are already filling out much of their clinical information electronically," said Dr. Stern.
The researchers are also testing the method with a third cohort. While the first two sets of patients were primarily white, educated, and of high socioeconomic status, the new cohort follows a diverse group of participants from CUMC's Washington Heights-Inwood Columbia Aging Project (WHICAP), an ongoing, community-based study of aging and dementia comprising elderly, urban-dwelling residents. Because participants may be dementia-free when they join the study, the researchers are able to capture the age of dementia onset and track symptom development over time.
###
The paper is titled, "A New Algorithm for Predicting Time to Disease Endpoints in Alzheimer's Disease Patients." The method's formula is detailed in supplementary material for the paper. The other contributors are: Anatoliy I. Yashin (Duke); Jason Brandt and Marilyn Albert (Johns Hopkins); Deborah Blacker (Massachusetts General Hospital/Harvard); and Bruce Kinosian (Philadelphia VA Medical Center).
The study was supported by a grant to Dr. Stern from the National Institute on Aging (R01 AG007370). The authors declare no financial or other conflicts of interest.
The Taub Institute for Research on Alzheimer's Disease and the Aging Brain at Columbia University Medical Center is a multidisciplinary group that has forged links between researchers and clinicians to uncover the causes of Alzheimer's, Parkinson's, and other age-related brain diseases and discover ways to prevent and cure these diseases. It has partnered with the Gertrude H. Sergievsky Center at Columbia University Medical Center, which was established by an endowment in 1977 to focus on diseases of the nervous system, and with the Departments of Pathology & Cell Biology and of Neurology to allow the seamless integration of genetic analysis, molecular, and cellular studies and clinical investigation to explore all phases of diseases of the nervous system. For more information visit The Taub Institute at http://www.cumc.columbia.edu/dept/taub/.
Columbia University Medical Center provides international leadership in basic, preclinical, and clinical research; medical and health sciences education; and patient care. The medical center trains future leaders and includes the dedicated work of many physicians, scientists, public health professionals, dentists, and nurses at the College of Physicians and Surgeons, the Mailman School of Public Health, the College of Dental Medicine, the School of Nursing, the biomedical departments of the Graduate School of Arts and Sciences, and allied research centers and institutions. Columbia University Medical Center is home to the largest medical research enterprise in New York City and State and one of the largest faculty medical practices in the Northeast. For more information, visit cumc.columbia.edu or columbiadoctors.org.
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New method predicts time from Alzheimer's onset to nursing home, death
PUBLIC RELEASE DATE:
7-Nov-2013
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Contact: Elizabeth Streich eas2125@cumc.columbia.edu 212-305-3689 Columbia University Medical Center
Draws on information from a single patient visit
NEW YORK, NY (Nov. 7, 2013) A Columbia University Medical Center-led research team has clinically validated a new method for predicting time to full-time care, nursing home residence, or death for patients with Alzheimer's disease. The method, which uses data gathered from a single patient visit, is based on a complex model of Alzheimer's disease progression that the researchers developed by consecutively following two sets of Alzheimer's patients for 10 years each. The results were published online ahead of print in the Journal of Alzheimer's Disease.
"Predicting Alzheimer's progression has been a challenge because the disease varies significantly from one person to anothertwo Alzheimer's patients may both appear to have mild forms of the disease, yet one may progress rapidly, while the other progresses much more slowly," said senior author Yaakov Stern, PhD, professor of neuropsychology (in neurology, psychiatry, and psychology and in the Taub Institute for Research on Alzheimer's Disease and the Aging Brain and the Gertrude H. Sergievsky Center) at CUMC. "Our method enables clinicians to predict the disease path with great specificity."
"Until now, some methods of predicting the course of Alzheimer's have required data not obtained in routine clinical practice, such as specific neuropsychological or other measurements, and have been relatively inaccurate. This method is more practical for routine use," said Nikolaos Scarmeas, MD, a study co-author and associate professor of neurology, in the Taub Institute and the Sergievsky Center. "It may become a valuable tool for both physicians and patients' families."
The new method also may be used in clinical trialsto ensure that patient cohorts are balanced between those with faster-progressing Alzheimer's and those with slower-progressing diseaseand by health economists to predict the economic impact of Alzheimer's disease.
The prediction method is based on a Longitudinal Grade of Membership (L-GoM) model, developed by a research team also led by Dr. Stern and published in 2010.
The L-GoM includes 16 sets of variables, such as ability to participate in routine day-to-day activities; mental status; motor skills; estimated time of symptom onset; and duration of tremor, rigidity, or other neurological symptoms. It also includes data obtained postmortem (time and cause of death).
"The benefit of the L-GoM model is that it takes into account the complexity of Alzheimer's disease. Patients don't typically fall neatly into mild, moderate, or severe disease categories. For example, a patient may be able to live independently yet have hallucinations or behavioral outbursts," said Dr. Stern, who also directs the Cognitive Neuroscience Division at CUMC. "Our method is flexible enough to handle missing data. Not all 16 variables are needed for accurate predictionsjust as many as are available."
Results can be presented as expected time to a particular outcome. Two 68-year-old Alzheimer's patients, for example, had similar mental status scores (one a mini-mental status score (mMMS) of 38/54, the other of 39/54) at initial visit. The first patient was more dependent on his caregiver and had psychiatric symptoms (delusions). These and other subtle differences in the initial presentation of the two patients resulted in different predictions of time until death. The method accurately predicted that the first patient would die within three years, while the other would survive more than 10 years.
"In addition to time to nursing home residence or death, our method can be used to predict time to assisted living or other levels of care, such as needing help with eating or dressing, or time to incontinence," said first author Ray Razlighi, PhD, assistant professor of neurology at CUMC and adjunct assistant professor of biomedical engineering at Columbia University.
Development of the method began in 1989, when Dr. Stern received a grant from the National Institutes of Health to begin the Predictors of Severity in Alzheimer's Disease study. "The fact that work on this prediction method began nearly 25 years ago underlines the difficulties of studying Alzheimer's disease," said Richard Mayeux, MD, MS, neurology chair, the Gertrude H. Sergievsky Professor of Neurology, Psychiatry and Epidemiology and co-director of the Taub Institute and the Sergievsky Center.
Dr. Stern and colleagues at Massachusetts General Hospital and Johns Hopkins first followed 252 non-familial Alzheimer's patients every six months for 10 years. Eric Stallard, an actuary at Duke and a co-author of the paper, used the resultant data to create an L-GoM model of Alzheimer's progression. They published their results in 2010 in Medical Decision Making. The researchers then followed a separate group of 254 patients and used data from only a single patient visit to predict outcomes for this group.
Dr. Stern and his team are now developing a computer program that would allow clinicians to input the variables and receive a report. They expect the program to become available within the next two years. Eventually, such a program might be incorporated into electronic health records. "At our Alzheimer's center, patients are already filling out much of their clinical information electronically," said Dr. Stern.
The researchers are also testing the method with a third cohort. While the first two sets of patients were primarily white, educated, and of high socioeconomic status, the new cohort follows a diverse group of participants from CUMC's Washington Heights-Inwood Columbia Aging Project (WHICAP), an ongoing, community-based study of aging and dementia comprising elderly, urban-dwelling residents. Because participants may be dementia-free when they join the study, the researchers are able to capture the age of dementia onset and track symptom development over time.
###
The paper is titled, "A New Algorithm for Predicting Time to Disease Endpoints in Alzheimer's Disease Patients." The method's formula is detailed in supplementary material for the paper. The other contributors are: Anatoliy I. Yashin (Duke); Jason Brandt and Marilyn Albert (Johns Hopkins); Deborah Blacker (Massachusetts General Hospital/Harvard); and Bruce Kinosian (Philadelphia VA Medical Center).
The study was supported by a grant to Dr. Stern from the National Institute on Aging (R01 AG007370). The authors declare no financial or other conflicts of interest.
The Taub Institute for Research on Alzheimer's Disease and the Aging Brain at Columbia University Medical Center is a multidisciplinary group that has forged links between researchers and clinicians to uncover the causes of Alzheimer's, Parkinson's, and other age-related brain diseases and discover ways to prevent and cure these diseases. It has partnered with the Gertrude H. Sergievsky Center at Columbia University Medical Center, which was established by an endowment in 1977 to focus on diseases of the nervous system, and with the Departments of Pathology & Cell Biology and of Neurology to allow the seamless integration of genetic analysis, molecular, and cellular studies and clinical investigation to explore all phases of diseases of the nervous system. For more information visit The Taub Institute at http://www.cumc.columbia.edu/dept/taub/.
Columbia University Medical Center provides international leadership in basic, preclinical, and clinical research; medical and health sciences education; and patient care. The medical center trains future leaders and includes the dedicated work of many physicians, scientists, public health professionals, dentists, and nurses at the College of Physicians and Surgeons, the Mailman School of Public Health, the College of Dental Medicine, the School of Nursing, the biomedical departments of the Graduate School of Arts and Sciences, and allied research centers and institutions. Columbia University Medical Center is home to the largest medical research enterprise in New York City and State and one of the largest faculty medical practices in the Northeast. For more information, visit cumc.columbia.edu or columbiadoctors.org.
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AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.
After offering birthday wishes to friend Brittny Gastineau, Kim Kardashian inadvertently raised suspicions that she is linked to the Illuminati, a conspiratorial group that theorists believe controls the world.
On Wednesday (November 7), the "Keeping up with the Kardashians" starlet posted an Instagram message to Brittny that read, “Happy Birthday to my best friend @brittgastineau We’ve shared soooo many memories over the past years! I love you! #RideorDie.” However the confusion surrounds the nature of the photo attached to the post. The snapshot features a collage of the two besties, except it showcases them within the monogram of the iconic pyramid with an eye in the center.
After hearing the feedback from followers linking her to the group, the 33-year-old posted a response the following day, writing, "I posted a IG collage for my bff @BrittGastineau & people say its the illuminate!"
Clearly confused, Kim also wrote, "What is the illuminate? A religion?… I’m a Christian. A cult?… not into that sorry! It had an eye on it, which reminded me of Britt bc her company ‘eye on glam’ & reminds me of against evil eye bracelets we wear. So sorry guys it was just a cool design I saw on one of those IG collage apps.” See for yourself, and determine whether or not Kanye West's soon-to-be wife is controlling with world as a member of the Illuminati!
Getting a jump start on keeping off that holiday weight, Maria Menounos shared her tips alongside tons of floating Ocean Spray cranberries in New York City.
Explaining some of her own routine, the EXTRA co-host began, "I like to stretch in the morning, it kinda gets everything going. Sometimes, if I have time, I'll actually go out and do some yoga. Whether it's ten minutes, fifteen minutes, I really try to fit that in. It sets the tone right for the day."
As for the festive season ahead, the 35-year-old star advises, "If you're worried about gaining weight during the holidays, obviously you're not alone and I would suggest the weeks leading up to it to try to clean out your diet a little bit. Maybe even just by 10%"
Check out Ms. Menounos' tips in the video below, as she wades in a make-shift cranberry marsh in the middle of the city.
GENEVA (AP) — Officials say U.S. Secretary of State John Kerry will fly to Geneva on Friday to participate in nuclear negotiations with Iran and other major powers.
The officials say Kerry will travel to the talks after a brief stop in Israel, where he will hold a third meeting with Israeli Prime Minister Benjamin Netanyahu. Israel's intense interest in Iran's nuclear ambitions is a likely topic between Netanyahu and Kerry as well as Israeli-Palestinian peace.
Iran's plan to cap some of the country's atomic activities in exchange for selective relief from crippling economic sanctions has been accepted by six world powers, the country's chief nuclear negotiator said Thursday.
Kerry's last-minute decision to join the talks suggests a deal could be imminent.
The officials spoke on condition of anonymity because Kerry has not been formally invited by the Europeans to join the talks.
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Now that anyone (well, anyone with an invitation) with a spare $1,500 can get their very own Google Glass, the folks in Mountain View have thoughtfully released a software update for the famous wearable. We're frankly surprised Glass owners weren't able to do this before, but you can now look up ...
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