Review of nevi for medical education using digital pathology tools

A new peer reviewed article of interest:

 

The aim of the study is to use digital images of nevi as a diagnostic and prognostic tool for studying skin pathology. Studies on pigmented nevi (moles) attract medical attention by the fact that they signal to the specialized medical team possible malignant degeneration.. Nevi samples were taken from different areas of the body in children under the age of 18 years.

 

The analysis of pigmented nevi is undertaken by observations on microscopic preparations, usually colored using the Hematoxylin & Eosin stain (H&E), which enables comparative analyzes to be made with the adjacent regions of the nevi. Collated data can include classifications by age groups, by sex, by urban or rural area. In order to advance medical education, capturing digital images of nevi can provide a powerful training tool. For example through the presentation of data to medical students it is possible to draw attention to the types of traumatized nevi that could possibly degenerate into malignancy.

 

Chesca, A., Sandle, T. and Abdulina, G. (2021) Review of nevi for medical education using digital pathology tools, Medicine and Ecology, 1 (98): 54 – 59

 

Posted by Dr. Tim Sandle, Pharmaceutical Microbiology Resources (http://www.pharmamicroresources.com/)

The Future of Pharmaceutical Quality Control Will Be Digital

 

Quality control is something that has always been essential in the pharmaceutical industry. Nothing should leave the factory floor until it’s been checked and double-checked, ensuring that everything meets the expected parameters. Unfortunately, with most modern analog pharmaceutical quality control programs overseen by human agents, there is always the risk of and potential for human error, no matter how many redundancies are in place.

By Emily Newton

New technologies are helping to ensure nothing is overlooked during the quality control phase. Why is the future of pharmaceutical quality control shifting to digital?

Quality and Compliance

The terms “quality” and “compliance” are often used interchangeably, but they are not the same thing. Something meeting compliance standards may not also meet the quality standards set forth by the manufacturer, and vise versa. Keeping track of all of these different standards can often be a challenge, even for the most experienced pharmaceutical engineer. When it comes down to it, there are three primary goals for any product emerging from the pharmaceutical industry:

 

●     Quality

●     Safety

●     Efficacy

 

Compliance regulations are the bare minimum that each product needs to meet, according to the FDA or other regulatory bodies. They aren’t designed with a single product or service in mind. Instead, they need to be general enough that they can protect consumers while still covering anything that might come out of the pharmaceutical industry. While it is possible to meet all quality and compliance requirements manually, using analog techniques and technologies isn’t the most efficient way to accomplish this task anymore — especially for products in high demand.

Exploring Digital Options

Digital technologies in the pharmaceutical industry are in their infancy, which means this is a perfect time to start exploring those digital options. Right now, they’re an option. If the technology gains a foothold in the pharmaceutical industry, it won’t remain optional for long. Becoming an early adopter makes it easy for manufacturers to find a niche and claim it for themselves.

 

Digital options can be broken down into two categories: hardware and software. Hardware that can be applied to the pharmaceutical industry includes but isn’t limited to:

 

●     Drones, robotics, and other forms of automation.

●     3D printing.

●     Mobile devices and wearable technology.

●     Smart sensors and the Internet of Things (IoT).

●     RFID tracking and location detection.

 

The software side of things can include, but is not limited to:

 

●     Cloud computing.

●     Blockchain.

●     Big data analytics and machine learning.

●     Artificial intelligence (AI) and robotic processing analytics.

●     Virtual and augmented reality.

 

The potential applications for these technologies are nearly limitless, both inside the production process and inside the facility itself. Something as simple as a smart sensor attached to a water intake pipe could aid in water conservation — an important part of an industry that uses so much sterilized water in its production. Let’s take a closer look at some of these tools and how they might shape the future of the pharmaceutical industry.

Artificial Intelligence and Machine Learning

Pharmaceutical quality control generates a massive amount of data. Testing parameters, results, variables, aberrations, and more all get stored in a central database. From there, quality control professionals can analyze the results and determine if a batch of products meets the manufacturer’s quality standards. While this may have worked traditionally, it isn’t as efficient as it could be.

 

Artificial intelligence and machine learning programs can sort through the same data in a fraction of the time, achieving the same or even better results faster and more efficiently. Program these systems with the desired quality parameters and feed them the data to get the desired results. As a bonus, the more information these systems are exposed to, the smarter they become, making them even more useful in the long run.

Improving Product and Process Development

Quality control doesn’t start at the end of the production process. Every step of the process, from product and process development to manufacturing and everything in between, can all play a role in how successful a production run is. AI and machine learning, as well as other digital tools, can help improve both product and process development steps, reducing the chances that something could go wrong during production that would result in a failed quality control check.

 

This application of digital technology has mostly been restricted to consumer products, but it could easily make its way into the pharmaceutical industry with a few modifications, making it easier for manufacturers to ensure product quality throughout every step of the production process.

Predicting Failures and Identifying Defects

Machine learning programs aren’t just useful for analyzing data. With enough information, both current and historical, they can work to predict failure points and defects before they even happen. As previously mentioned, the more information these systems have to work with, the smarter they become. They’re not predicting the future with any mysticism or magic — simply analyzing past data and looking for patterns that might not be immediately visible or obvious to a human analyst.

 

In a pharmaceutical production line, this could provide invaluable opportunities, like identifying and predicting problems before an entire batch of medication has to be discarded due to a production error or failure. In addition to improving quality control throughout the entire production process, this can also save companies a lot of money by preventing discards or even recalls if something does manage to slip past quality control.

Looking Toward the Future

Quality control is an essential part of any industry that makes products for consumers, but for the pharmaceutical industry, ensuring every pill, vial, or product that leaves the factory floor meets the same high quality standards can mean the difference between life and death. Digital services, like AI and machine learning, will continue to shape the supply chain, including the pharmaceutical industry, for the foreseeable future.

 

What currently exists as an option will likely become a mandatory part of the industry moving forward. Pharmaceutical companies looking for ways to improve their quality control processes should start exploring these digital options. It’s the perfect opportunity to find a niche and secure it before everyone else starts dipping their toes in the metaphorical pool.

, Pharmaceutical Microbiology Resources (http://www.pharmamicroresources.com/)

Are some gut microbes associated with cognitive decline?

 

Can microbiology help to predict cognitive decline? This is in relation to diseases such as Alzheimer’s? It appears that this might be possible according to some new research which draws upon medical microbiology.

 

Recent research has discovered that changes in the gut microbiota (these are the trillions of bacteria and other microbes that live in the intestines, along with their genetic components) possess the capacity to alter the brain and behavior.

 

This was demonstrated by means of an experiment. For this study, mice were used and the researchers discovered that a particular balance (or imbalance) of gut microbes plays a role in exacerbating the effects of cognitive impairment.

 

This is due to how gut microbes affect the hippocampus (this is the region of the brain that is critical for memory and learning). It was discovered that the concentration of one group of bacteria of the genera Bilophila increased significantly as part of the gut microbiota of mice fed that were fed a ketogenic diet.

 

A ketogenic diet is one composed of high-fat, adequate-protein, and low-carbohydrates. In addition to being fed this diet, the mice were intermittently deprived of oxygen, creating the condition of hypoxia. It was shown that by depriving the animals of some oxygen created cause cognitive impairment.

 

The researchers found that a ketogenic diet, hypoxia and treatment with a species of Bilophila named Bilophila wadsworthia impaired the hippocampus. The consequence of this was reduced cognitive ability in mice.

 

To demonstrate this experimentally, researchers gave several mice a ketogenic diet and others a standard diet. The two groups of mice then received reduced levels of oxygen for five consecutive days. After this the mice were afforded four days to recover.

 

The scientists then observed the ability of the different groups of mice to navigate a maze. When trying to find their way out of a maze, mice on the ketogenic diet made an average of 30 percent more errors compared with mice fed on the standard diet.

 

The researchers next evaluated whether the different diets could cause any change in cognitive behavior for the mice that had not been deprived of oxygen. Here there was no appreciable difference in the mice's ability to find their way out of the maze, in relation to both the ketogenic diet or the standard diet.

 

This infers that the negative impact on cognitive ability only occurred in combination with oxygen deprivation.

 

Following this, the scientists investigated what would happen if they depleted the mice's microbiota before administering a ketogenic diet and exposing them to hypoxia. Here it was observed that the mice which had their microbiota depleted first made fewer errors in the maze compared with mice that were exposed to hypoxia and then fed a ketogenic diet but which not had changes to their microbiota first.

 

The overall data suggests that the microbes associated with the ketogenic diet and hypoxia could contribute to the detrimental effects on cognitive impairment.

 

The research appears in the journal Cell Host & Microbe, under the title “Alterations in the gut microbiota contribute to cognitive impairment induced by the ketogenic diet and hypoxia.”

 

Posted by Dr. Tim Sandle, Pharmaceutical Microbiology Resources (http://www.pharmamicroresources.com/)