Tag: Medication

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Boys, Masculinity, and the Looksmaxxing Trend  

By now, you’ve probably heard of the term looksmaxxing. Think pieces about the trend have popped up all over the internet. And in a recent episode of Saturday Night Live, comedians poked fun at lookmaxxing influencers obsessed with having the perfect male physique.

While this new social media craze may seem silly, it’s impacting more boys than you might think. In a study conducted last year that surveyed over 3,000 young men (ages 16–25) from the United States, United Kingdom, and Australia, nearly two-thirds of participants were regularly engaging with masculinity influencers.

Teen boys are being encouraged to change the way they look in order to fit a certain standard of attraction. The growing amount of looksmaxxing content they see online can have real effects on their self-esteem and mental health.   

What is looksmaxxing?  

Looksmaxxing originated nearly a decade ago in incel forums where men blamed their lack of romantic partners on the belief that female sexual selection is primarily based on physical qualities. So men who aren’t born with traits desirable to women are doomed to fail romantically. While traditional incels wallow in this fate, looksmaxxers seek to enhance their appearance to become more attractive. Their community claims that there is a universal standard for what the ideal man (and woman) should look like.

This is determined by a rating system called the PSL scale — the name being an amalgamation of three prominent misogynistic incel forums of the 2010s. There are many factors that go into the scaling, such as eye shape, jaw size, nose angle, and body fat percentage. Along this scale, you can land in four categories: subhuman, normie, Chadlite, and Chad (the ultimate catch).

During the pandemic, looksmaxxing went mainstream, merging with “manosphere” content on social media platforms like TikTok and Instagram. The trend became less about the ability to attract women and more of a competition among boys and men as they engaged in mog-offs — online contests where people have their faces analyzed and compared by facial recognition software to determine who’s better looking.

Self-improvement practices have gained popularity among boys. Some are considered to be softmaxxing, like developing skincare routines or eating high-protein diets, and others to be hardmaxxing, like using growth hormones or getting cosmetic surgery.

Prominent young influencers like Clavicular represent the extreme side of looksmaxxing. He practices bonesmashing (using a hammer on facial bones to try to form more angular features), injects himself with testosterone, and takes meth to maintain a low body fat percentage while still having a muscular physique.

Looksmaxxing and new beauty standards

The rise of looksmaxxing seems to have a caused a ripple effect among teen boys. While the ideal look has centered on big muscles and washboard abs for decades, there’s now an added pressure on facial beauty that’s typically been reserved for girls.

“With some of the teen boys I work with, most of whom already have self-esteem issues, I think there is a lot more concern about how they look,” observes Alnardo Martinez, LMHC, director of the Pediatric OCD Intensive Program and a mental health counselor at the Child Mind Institute. “They want to have the strong jaw, really big muscles, clear skin, and a perfect haircut.”

However, Martinez notes that it sometimes take a while for boys  to admit that they feel this pressure. They may insist that they don’t really care about that stuff. “But then, maybe a few months later, it comes out that there is a lot of comparison. They’re spending a lot of time in front of the mirror or in the bathroom trying to create this perfect image,” he observes.

What teen boys think about looksmaxxing and self-improvement

We talked to young men who were critical of Clavicular and the impact looksmaxxing can have on teens but were positive about engaging in some form of physical self-improvement.

Wyatt, now 19, remembers comparing his jawline to his peers’ when he was in 7th grade. “I just felt like they had really sharp jawlines. And I was just like, ‘Oh, I want to get closer to that.’” He would also come across TikToks advertising rubber chewing blocks and chin exercises meant to strengthen the jawline.

And so, Wyatt began to do jaw exercises he’d found online, reciting the alphabet while stretching out the muscles. “I would go through my Zoom classes throughout the day and then after that was done, I’d just go into the bathroom and go through the whole exercise. It would take like an hour sometimes,” he recalls. “It turned into more like a self-care, self-improvement session. I would do that every day after my classes. I didn’t feel like I was done with school until I finished my jawline routine.” He took photos to document his progress.  

Wyatt feels like the routine had a positive effect, because he was able to see an improvement. “I felt more satisfied with myself, a little more confident.”

Lev, now 19, remembers wanting to have some control over his body when going through puberty in high school. “Puberty is not a straightforward process. It’s not all peaches and cream. Your body changes, and it can be uncomfortable,” he explains. “But with lifting and strength training, it was very exciting to see this, you know, man energy that came out of it. I wanted to harness that and really take it by the reins. Have some agency as a man.”

And while he rejects the extreme parts of looksmaxxing, Lev does regularly practice self-improvement through weight lifting, skin care routines, and taking GLP-1 weight loss medication.

How looksmaxxing can impact boys’ mental health

Since looksmaxxing places such a strong emphasis on achieving a very specific look, clinicians are concerned about its influence on teens. “Self-esteem is pretty fragile during puberty,” Martinez says. “There’s already a ton of comparison and perceived flaws that teens don’t love about themselves.”

These insecurities can be exacerbated by the type of content teens engage with online, Martinez explains. Along with ChatGPT bots specifically designed to judge aesthetics, Reddit threads such as r/Mewing and websites like Looksmaxxing Forum encourage boys to post pictures of their faces and bodies to get rated by their peers. Boys as young as 13 visit these forums, posting pictures and asking for tips on how to improve their looks.

“These are generally places where people are already pretty harsh and critical. These boys are receiving a lot more ‘confirmation’ around the perceived things that are wrong with them or that they need to change,” Martinez says. “And it just feeds into the already present negative self-image and self-talk.”

He explains that this type of social media engagement can also compound underlying mental health issues like depression and social anxiety. “They might be less likely to go out and talk to people because they’re thinking, ‘Everyone is going to see this one thing that everyone else has told me is wrong with me. So now I can’t go out,’”he says.

Martinez is also concerned that online content can negatively affect teens with body dysmorphic disorder (BDD). “If they think they have a big nose, for example, they might go on these Reddits and ask, ‘What does my nose look like? Is it too big?’ There are trolls out there. Someone is going to say yes and then that’s going to make the BDD symptoms even worse.”

When behaviors might be concerning

In some ways, teen boys taking part in more self-improvement practices could be seen as a good thing. They’re exercising, taking care of their skin, and eating more balanced diets. The issues begin when these types of practices turn into obsession. And given the underlying ideology of looksmaxxing and the nature of social media, things can become unhealthy.

According to Martinez, there are some changes in behavior to look out for that indicate you might want to step in.

One clear change, he says, is a noticeable shift in the amount of time they’re spending on grooming themselves. “Maybe they were someone who would typically just get up and run out the door without washing their face,” he says. “But now they’re spending a lot more time in the bathroom and asking a lot of questions about how they look.”

Another warning sign can be a big change in personality. “Irritability is a big one that we’ll see a lot,” he says. “They’re unhappy with how they look, so this increases a general level of irritation.”

These behaviors paired with an unusual uptick in time spent on social media, Martinez explains, can be a sign that something’s wrong and support is needed.

How to support your child

If you’re worried that your child might be engaging in looksmaxxing-related behaviors to an unhealthy degree, says Martinez, there are a few things you can do:

  • Open communication. Martinez suggests approaching your child with curiosity. “You could start the conversation by saying something like, ‘So have you heard about this? What do you think about it? Have you ever had any thoughts yourself about how you look or desires to change your body or face?’ And then give them some space to be open and vulnerable about it. Validate their experience.” 
  • Find out where your child is getting their information. “Read it together, talk about it, and see what your child thinks about it,” Martinez advises. “And if it’s promoting something dangerous, then you can talk to them about how those practices can be harmful and what could actually happen if they do some of those things.”
  • Encourage male role models. “There’s a patient I work with now who doesn’t have a present dad,” Martinez explains. “His mom tries to talk to him about things like body image, but he feels like she doesn’t understand and can’t relate. So having someone that he can talk to and be open about this stuff with, especially someone who can also share their own struggles, can be really helpful.”
  • Seek help from a mental health professional. This is especially important if you find out that your child has been engaging in extreme forms of looksmaxxing such as bonesmashing or starvemaxxing. Martinez recommends looking for a clinician who specializes in body image or body dysmorphic disorder.

A lot of parenting comes down to open communication around what your kids are seeing and what they’re feeling. We all have things about our bodies that we might not like and wish we could change, says Martinez, and it can help to normalize those feelings. “And then you can discuss how they can make changes in healthy ways,” he suggests. “Go over what’s a realistic change and what’s a dangerous change.”

The post Boys, Masculinity, and the Looksmaxxing Trend   appeared first on Child Mind Institute.

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Michael Antonov: From Virtual Worlds to Real-World Drug Discovery

AI is often portrayed as either a technology that will revolutionize healthcare and cure disease or an overhyped force that could stifle science—but the reality is far more nuanced. While AI is already transforming biomedical research, meaningful advances in medicine require much more than powerful algorithms. That complexity is the focus of this conversation with Michael Antonov, co-founder of Oculus, who turned to biology and drug discovery after pioneering virtual reality.

To do so, he co-founded the computational drug discovery company Deep Origin. Rather than relying on AI alone, Antonov believes progress depends on integrating machine learning with physics-based molecular simulations, mechanistic models, and rigorous experimental validation. This philosophy has been fundamental for shaping Deep Origin’s AI-native platform to improve virtual drug screening, predict toxicity, and help researchers develop safer, more effective therapies.

In this episode of Behind the Breakthroughs, Anotonov examines how AI is changing drug discovery and the pharmaceutical industry’s opportunities and limitations, taking a pragmatic approach to claims that AI alone can improve human health from larger models and more computing power. This conversation offers a glimpse into biomedical innovation’s future for those interested in where AI is truly changing medicine and where human expertise and experimental science remain vital.

This interview has been edited for length and clarity.

 

IPM: Does virtual reality (VR) have a role in medicine and healthcare?

Antonov: VR is predominantly a visualization device, so it’s good for training and various other areas in terms of actual treatments. When VR has been used and is actually FDA approved, as far as I know, it presents modified images to each eye and kind of trains your brain to treat them both simultaneously. Similarly, it’s been used for PTSD treatments and some of the areas where you can maybe handle fears. I haven’t personally experimented with that.

michael antonov deep origin
Michael Antonov, co-founder of Oculus and Deep Origin [Deep Origin]

On the visualization side, for displayed molecules, there’s a company that has done a great job of allowing you to look at the molecules, and this could be useful for research. That said, it just gives you more spatial perception. It doesn’t actually solve the problem for you. 

On the training side, there are potentially huge benefits, even though you would then have to require investing a lot in software to make it actually perform well. Now, one good example is, I have invested in this company called Osso VR, which does training for knee replacement surgery, and they actually practiced it, and they did a study where their surgeons trained with their knee replacement and got 230% more proficiency.

Given the time and the accuracy of a procedure and the speed of how they learn. But to me, that felt actually very incredible that it’s actually being used. I think they also do nursing trade trainings and such. Those are probably the top areas that will probably be more brain-oriented cognitive things you could do. It would just take time to explore it.

 

IPM: What will AI’s impact be on medicine and healthcare?

Antonov: I think that there is still a lot of uncertainty. The system is overloaded. There’s a whole spectrum, and the challenge is that there are hundreds of different companies and projects with a whole different range of funding.

For pharma, it would be a big job to sift through what is actually good and what will help me take my target forward. That’s a challenge because there’s a lot more noise and there are some really good companies, but there are also many me-too, not-so-great ones. There are also certain fundamental areas that haven’t been solved yet, like toxicity and other issues, although there has been progress in some areas. There are like dozens of predictors, but they’re not necessarily super great, though they’re better than nothing. It’s hard to tell where it’s going. The biggest thing is to see what you actually prove in the lab.

The other thing is that there is a range of medicinal chemists and other knowledgeable people who haven’t been exposed to the breakthroughs or effects we might see on our side. AI may surprise us in certain biological parts of the name for certain problems. Now, more holistically at Deep Origin, our plan is to support the discovery process for small molecule drugs and have predictable outcomes.

 

IPM: How will AI drive the future of precision medicine?

Antonov: The super exciting way it could look in 20 years in that type of timeframe is that we are starting to get personalized medicine. You’re really combining the patient and the system model so that whenever you have a disease, if you have maybe a novel genomic mutation or if you have a new virus, you can literally put the data into the system.

Here is basically experimental data about whatever you collect from the virus. I don’t know if you get the structure of its protease from crystallography. I will even tell you here are the steps you need to take and which lab to run them in. But once you provide it, the system will be able to decompose the pathways and targets it’s affecting and then identify the specific concentrations you might need for these patients.

Essentially, you can provide a target in just a few months. You have good candidates, and these candidates have a much higher probability of not being toxic and having good admin properties. Let’s say we are moving from 90% failure rate to maybe 60%. That would be a huge job. That’s what the toxicity models enable, though they are hard because they need both experimental and data collection. But actually, even things like physics can help with counter screening, asking, what are all these things we should not bind to? Go and check them computationally. This whole stack basically gives you data on how to run your trial. That’s ten years. But then you level it up with populations and the individual.

This is a 2030 year outlook because then you’re pulling in the genomics data, maybe various things, and this is where the industry really becomes much more powerful and individualized. To do that, you really need these more detailed models.

 

IPM: Do you have a prediction about a current AI trend that will be around for a while?

Antonov: One of the hot topics right now is the idea of AI scientists. In our case, we have an AI discovery engine. We actually did this earlier, which is this area grant from the U.K. for picking up the disease, which can be fully drugged by AI.

We ran our AI scientist system to pick a target for endometriosis. It uses our tools to come up with a molecule. It’s currently in progress, and it did a very detailed breakdown and analysis of hundreds of targets based on very specific criteria, and I picked a particular one with all the reasons.

It’s interesting to make those kinds of tools and this whole pipeline available to almost everyday people because then, much like some genomics tools, an available AI system, which can support the full path of drug development, can in fact let a patient or an interest group just come in and take lots of steps in the direction of saying, “Here’s either maybe an RNA or a gene therapy or a drug that can serve.”

That would be a huge step toward democratizing it. It doesn’t mean that AI will do all the steps for us, but it doesn’t mean that it can do a lot of the known steps, which have been done many times and can help us along the way. Of course, the real scientist will still be very critical to all the parts.

For general accessibility, this automation that is happening and these kinds of simulation tools and large language models in general are incredible. They’ve got a little bit of a long-winded thing, but I wanted to reflect on what you said.

 

IPM: What are the pros and cons of building Deep Origin in the U.S. or China?

Antonov: Some of the more recent wisdom that I’ve heard is that if you want to survive in the U.S. or more expensive countries, you need to be taking bigger risks, and you need to be more innovative in how you approach the type of modalities and things. So that’s one line of thinking. 

Another way is to be distributed. In our case, a big part of our AI/ML team is in Armenia. My co-founder is Armenian. We have 40 people there. I have just come from spending a week and a half with the team there for model building and science. There is an AI, and there are definitely people in all of the areas. Automated labs could also probably be in any country.

In terms of the actual trials, it depends on the situation. There are certain things that it’s probably wiser to do in China for this time being, but also maybe India will be up and coming, and if there are certain scenarios where there are more rare diseases, it’s probably okay to also not stay in the States.

There’s no perfect answer. We have a challenging environment. At the end of the day, you have to have something really valuable and novel to keep going forward. They have really great scientific research there too. We have to be careful and just really go at it hard.

 

IPM: Where does China stand out from the United States in terms of pharmaceutical research and development?

Antonov: If I were to pick one area, it’s the cost of clinical trials and the way we select just all the aspects of this. And to be honest, I’m not an expert in this. And clearly there’s a lot of progress in China right now. Everybody talks about how it’s much more cost-effective and quicker to do things there. There are a lot of “right to try” opportunities that are helping.

That said, I believe that we can have a lot better kinds of social programs around this to make it like easier for people to participate and maybe take more highly educated guesses and risks. There’s software infrastructure to simplify and reduce the cost. That would be amazing. In some of those areas, AI also can help, and the models actually can help.

 

IPM: If you could work on anything, what would it be?

Antonov: I would say focusing on aging as a disease. If you look at the funding, things could shake up the type of research that the NIH and the National Institute on Aging (NIA) do, which is really fundamental to our biology because it drives the majority of diseases and has 3% of the budget, whereas oncology and Alzheimer’s have huge budgets. There’s probably more impact in aging than probably some other well-funded areas if we look at the fundamental parts. That would be a big area where you can have a multiplier effect just from the research side.

To really build an ecosystem of better computational and AI models, maybe creating some way to actually incentivize people to contribute to them, because that’s the challenge right now. You can publish a research paper, or you can build your model to make your proprietary hidden drug. But we need scientists to share those in an integrated way. How do we do that?

Maybe it’ll take some big AI companies to jump into it and do something there. But it’s not going to be solved with just a model. It really needs to be a true experiment-grounded framework where researchers can contribute their part and have it be a part of a whole.

The post Michael Antonov: From Virtual Worlds to Real-World Drug Discovery appeared first on Inside Precision Medicine.

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Inhibiting the uPAR/FPR1 interactions reduces blood-retinal barrier breakdown and improves retinal function in a rat model of diabetes

Diabetic retinopathy (DR) is a leading cause of blindness characterized by early neurovascular damage driven by hyperglycemia-induced mechanisms, including inflammation. The system composed of the urokinase-type plasminogen activator (uPA) and its receptor (uPAR) has previously emerged as a potential regulator of the pro-inflammatory events in DR, possibly through the interaction of uPAR with its lateral partners, such as formyl peptide receptors (FPRs). This study explored whether the inhibition of uPAR/FPR1 crosstalk may reduce early neurovascular alterations in DR by targeting inflammation. To this aim, the new FPR1 antagonist N-19004 was tested in a rat model of streptozotocin-induced diabetes. N-19004 was administered subcutaneously for 7 days at 1 month from diabetes onset. Immunofluorescence, RT-qPCR, Western blot and Evans blue perfusion were performed to evaluate the effects of N-19004 on inflammation, reactive gliosis, blood-retinal barrier (BRB) integrity and apoptosis. In addition, electroretinogram (ERG) was used to assess N-19004 efficacy on retinal function. N-19004 inhibited the activation of inflammation-related transcription factors, including nuclear factor kappa-light-chain-enhancer of activated B cells and signal transducer and activator of transcription 3, leading to reduced interleukin-1β and tumor necrosis factor-α expression. The attenuation of inflammatory processes resulted in reduced glial activation, as indicated by lower glial fibrillary acidic protein expression and Müller cell gliosis. The anti-inflammatory activity of N-19004 was accompanied by decreased BRB breakdown, as demonstrated by N-19004-mediated reduction of vascular endothelial growth factor, increased levels of tight junction components and diminished vessel leakage. The amelioration of BRB integrity was associated with reduced activation of caspase 3 and partial preservation of scotopic ERG a- and b-wave amplitudes, thereby improving retinal viability and function in N-19004-treated STZ rats. These results support the possible involvement of uPAR/FPR1 interactions in the regulation of DR-related inflammation and suggest a novel therapeutic target for the management of the early phases of disease.
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Endocannabinoid system modulation in bruxism: a neurobiological hypothesis and translational model of ECS-targeted intervention

Bruxism is a multifactorial motor behavior of predominantly central origin, characterized by repetitive masticatory muscle activity and associated with dysregulation of dopaminergic, serotonergic, GABAergic, and glutamatergic pathways involved in motor control, emotional regulation, and stress responsivity. The endocannabinoid system (ECS) has emerged as a key homeostatic neuromodulator capable of integrating these neurotransmitter systems, thereby influencing pain processing, sleep–wake dynamics, and motor output. This article develops a neurobiological hypothesis based on a narrative integrative synthesis of clinical, experimental, and translational evidence regarding ECS involvement in the pathophysiology of bruxism. Findings from randomized clinical trials suggest that topical cannabidiol (CBD) may modulate motor neuron excitability and reduce pain-related outcomes, while case-based and experimental evidence supports the interaction between cannabinoid signaling and neural circuits implicated in motor control and behavioral regulation. Building on this evidence, we propose a hypothesis-driven translational model in which ECS-mediated neuromodulation may influence central mechanisms underlying bruxism, including motor pattern generation, stress responsivity, and nociceptive processing. Rather than providing prescriptive therapeutic recommendations, this model is intended as a hypothesis-generating construct that integrates current knowledge on ECS signaling within the broader neurobiology of motor control. Although heterogeneity in study design and outcome measures limits definitive conclusions, the available evidence supports the ECS as a plausible modulatory system in bruxism, with potential implications for future mechanistic and clinical research in centrally mediated motor disorders.
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Association of oxidative stress, metacognition, and psychopathology in patients with schizophrenia: a case-control study

BackgroundMetacognitive deficits are common in schizophrenia (SZ) and may worsen symptoms and impair insight. Oxidative stress (OS) abnormalities have also been reported, but findings are inconsistent, and no study has examined their associations with metacognition and psychopathology.MethodsThis case-control study included 89 SZ patients and 90 healthy controls (HC). OS markers, including superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA), and glutathione peroxidase (GPX) were measured. The patient group and healthy control group underwent metacognition was assessed using the abbreviated Metacognitive Assessment Scale (MAS-A) and patients’ symptoms with the Positive and Negative Syndrome Scale (PANSS). Covariates included age, gender, education, BMI, and smoking, illness duration, onset age and medication.ResultsPatients showed significantly lower MAS-A total score and subscale scores (all p < 0.01) versus HC. Patients had lower SOD, CAT and GPX (130.69 vs 152.12 ng/L, 2.46 vs 6.62 ng/L, 158.09vs 197.75μmol/L) and higher MDA (9.22vs 7.34μmol/L) than controls (all p < 0.05). Partial correlation revealed that in patients: SOD was negatively correlated with positive/negative/PANSS total and MAS-A decentration scores; CAT was negatively correlated with general pathological/PANSS total scores, and positively correlated with MAS-A total score and its subscales (self-reflectivity, understanding the other’s mind, decentration, mastery), MDA was negatively correlated with negative symptom score and self-reflectivity score, and positively correlated with general pathological score; GPX was positively correlated with most clinical and metacognitive scores. Linear regression revealed SOD, CAT, and GPX significantly associated with the PANSS total score (β = -0.119, -6.169, -0.226; all p < 0.05), and with MAS-A total score (β = 0.021,2.879 0.049, all p < 0.001).ConclusionSchizophrenia patients exhibit OS abnormalities and metacognitive impairments. Greater OS severity correlates with worse metacognition and more severe psychopathology, suggesting OS as a key factor linking these domains.
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Bacterial ‘Docking Domains’ May Open New Paths to Next-Generation HDAC Inhibitors

Researchers have uncovered the molecular mechanism bacteria use to build a family of natural anticancer compounds, a discovery that could help scientists engineer improved versions of histone deacetylase (HDAC) inhibitors for cancer treatment.

The study, published in Nature Communications, identifies the long-elusive biosynthetic pathway for FR-901375, a naturally occurring HDAC inhibitor closely related to the approved lymphoma drug Romidepsin. The findings also explain how bacteria “mix and match” components of these molecules to generate structurally diverse compounds, providing a blueprint for designing new drug candidates.

HDAC inhibitors block histone deacetylases—enzymes that help regulate which genes are switched on or off inside cells. By inhibiting these enzymes, the drugs can reactivate genes that suppress tumor growth or trigger cancer cell death. Romidepsin (Istodax) is already approved to treat certain T-cell lymphomas, but researchers have long been interested in developing additional members of this drug family that are more selective and effective.

Although FR-901375 has been known for decades, scientists had never identified the bacterial genes or molecular machinery responsible for producing it.

The new study fills that gap.

The researchers identified the previously unknown biosynthetic gene cluster for FR-901375 in Pseudomonas chlororaphis subsp. piscium and used genetic, biochemical, and structural approaches—including AlphaFold modeling, mutagenesis, mass spectrometry, and gene deletion experiments—to determine how the compound is assembled.

Like Romidepsin and related compounds, FR-901375 belongs to a family of cyclic molecules known as depsipeptides. These drugs are built inside bacteria by enormous enzyme complexes called PKS-NRPS hybrids, which combine two natural-product assembly systems to construct the finished molecule.

A key finding was the discovery of how small protein regions known as docking domains allow different sections of this assembly line to communicate. These molecular connectors enable the portion of the machinery that builds a conserved zinc-binding pharmacophore—the business end of the drug that inhibits HDAC enzymes—to link with a second set of enzymes that constructs a variable peptide “cap.” Differences in this cap influence how individual drugs interact with different HDAC enzymes.

“The βHD domain employs a mechanism to facilitate productive engagement of PKS and NRPS subunits, involving direct binding to a conserved epitope on the SLiM-bearing ACP domain,” the authors write.

The researchers found that one docking element, known as the β-hairpin docking (βHD) domain, plays the central role in joining the two biosynthetic systems. Surprisingly, another docking element previously thought to be equally important contributed relatively little to the interaction and was not essential for FR-901375 production inside bacterial cells.

Structural modeling and laboratory experiments showed that the βHD domain directly binds a conserved region of the acyl carrier protein, allowing the growing molecule to be transferred efficiently from one enzyme complex to the next. The same interaction was conserved across several related HDAC inhibitor pathways, suggesting bacteria use a common strategy to generate multiple drug variants.

“The observation that ACP-SLiM and βHD-C di-domains from noncognate depsipeptide HDAC inhibitor assembly lines engage productively supports the view that the interaction epitope between βHD and ACP domains… plays a key role in the biosynthesis of all members of this clinically important family of anticancer agents,” the authors write.

The team also reconstructed how the FR-901375 pathway likely evolved through gene transfer, duplication, and recombination events that modified the peptide-building portion of the biosynthetic machinery while preserving its ability to connect with the conserved pharmacophore assembly system.

According to the researchers, understanding this evolutionary process could help scientists design entirely new HDAC inhibitors using the same modular strategy that bacteria have refined over millions of years.

“Our work delivers deep insight into evolutionary mechanisms underpinning the combinatorial biosynthesis of depsipeptide HDAC inhibitors,” the authors conclude. “Moreover, it provides a rational basis for developing approaches to the creation of analogues of depsipeptide HDAC inhibitors and other hybrid polyketide-nonribosomal peptides via evolution-guided biosynthetic engineering.”

The findings could ultimately accelerate efforts to develop next-generation HDAC inhibitors with improved potency, greater selectivity, and fewer side effects for treating cancer.

The post Bacterial ‘Docking Domains’ May Open New Paths to Next-Generation HDAC Inhibitors appeared first on Inside Precision Medicine.

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Post-intracerebral hemorrhage depression comorbid with obstructive sleep apnea and REM sleep behavior disorder: a case report and literature review

We report a 63-year-old male with post-cerebral hemorrhage depressive disorder. Previous adequate-dose, full-course antidepressant treatment yielded no significant improvement in depression, anxiety, or sleep disturbance. Detailed history taking and polysomnography (PSG) confirmed comorbid severe obstructive sleep apnea hypopnea syndrome (OSAHS) and rapid eye movement sleep behavior disorder (RBD). Without adjusting antidepressants, the patient first received continuous positive airway pressure (CPAP) for OSAHS, followed by individualized pharmacotherapy for RBD. With the improvement of sleep architecture and respiratory events, obvious remission of depressive and anxiety symptoms and substantial recovery of daytime function were observed. This case emphasizes the bidirectional relationship between sleep and mood disorders. For post-stroke depression (PSD) poorly responsive to antidepressants, active sleep evaluation, multidisciplinary collaboration, and targeted management of comorbid sleep disorders may be crucial to enhance therapeutic efficacy.