Neurogenic pulmonary edema (NPE) is a life-threatening complication of acute central nervous system (CNS) injury, characterized by the rapid onset of hypoxemia and pulmonary fluid accumulation in the absence of underlying cardiopulmonary disease. In recent years, emerging integrative frameworks such as the “neuroimmunoaxis” and “brain-lung axis” have provided new perspectives on how CNS injury leads to systemic immune dysregulation and pulmonary dysfunction. However, critical questions remain regarding the interplay between excessive sympathetic activation, immune homeostasis disruption, and lung tissue injury. This narrative review proposes a neurotransmitter-immune-inflammatory model that integrates mechanical, adrenergic, and inflammatory pathways across the spatiotemporal evolution of NPE. We identify four progressive stages involving sympathetic storm initiation due to central autonomic network disinhibition, pulmonary vascular barrier disruption through Piezo channel activation and angiotensin II-norepinephrine synergy, inflammatory amplification from loss of the cholinergic anti-inflammatory reflex, and systemic progression involving gut-lung axis dysregulation. The model generates three testable predictions. Lesions disrupting the nucleus tractus solitarius-ventromedial hypothalamus-intermediolateral column projection should produce more severe NPE. And selective activation of TRPA1+ dorsal root ganglion neurons should attenuate sympathetic outflow and pulmonary edema. Enhancing α7 nicotinic acetylcholine receptor signaling should mitigate systemic inflammation. These predictions offer experimental avenues for validating the hijacking hypothesis. Translational implications include stage-specific interventions, early sympathetic blockade, mid-phase anti-inflammatory and neuro-modulatory strategies, and late-stage lung-protective ventilation. This study aims to offer a comprehensive analysis of NPE by exploring its pathological mechanisms—from central sympathetic signaling to peripheral lung damage. Emphasis is placed on examining the interactions between neural signals, neurotransmitters, and immune responses to uncover the spatiotemporal dynamics of NPE. By identifying potential pathways for early diagnosis and targeted therapies, the research seeks to improve disease management and contribute to better clinical outcomes for affected patients.
Intranasal esketamine plus oral antidepressant for treatment-resistant depression: acute induction and maintenance relapse-prevention outcomes in a systematic review and meta-analysis
Treatment-resistant depression (TRD) remains a major clinical challenge. Intranasal esketamine, used adjunctively with an oral antidepressant, has been evaluated in randomized trials, but uncertainty persists regarding the magnitude and consistency of benefit, durability, and key harms. This systematic review and meta-analysis included randomized controlled trials comparing intranasal esketamine plus an oral antidepressant versus placebo nasal spray plus the same oral antidepressant in TRD. Acute induction (≈4 weeks) and maintenance randomized-withdrawal phases were analyzed separately. Depression outcomes were assessed primarily using the Montgomery–Åsberg Depression Rating Scale (MADRS), and functional outcomes using the Sheehan Disability Scale (SDS). Two reviewers independently screened studies, extracted data, and assessed risk of bias using RoB 2.0. Random-effects models pooled mean differences (MD) for continuous outcomes, risk ratios (RR) for binary outcomes, and hazard ratios (HR) for relapse prevention. Certainty of evidence was rated using GRADE. From 1,518 records, nine reports representing six unique RCTs (1,836 participants) were included. Four acute induction RCTs (n=937) showed greater symptom reduction at day 28 with esketamine (MADRS MD −2.99, 95% CI −5.10 to −0.89; I²=48.5%). Rapid improvement was evident by day 2 (MD −3.25, 95% CI −4.65 to −1.85). Esketamine increased day-28 response (RR 1.44, 95% CI 1.20–1.74) and remission (RR 1.52, 95% CI 1.20–1.92), corresponding to approximately +154 responders and +106 remitters per 1,000 patients, respectively, based on pooled control risks. Functioning improved (SDS MD −1.70, 95% CI −2.61 to −0.79). Two maintenance randomized-withdrawal RCTs (n=899) demonstrated reduced relapse risk with continued esketamine (HR 0.51, 95% CI 0.42–0.62; I²=0%). In acute induction, esketamine increased any treatment-emergent adverse event (TEAE) (RR 1.37, 95% CI 1.25–1.50) and discontinuation due to adverse events (RR 2.68, 95% CI 1.35–5.29), with notable increases in dissociation (RR 7.33, 95% CI 4.49–11.98) and blood pressure increased events (RR 3.96, 95% CI 2.24–7.01). Maintenance TEAE rates were similar between groups (RR 1.07, 95% CI 0.99–1.17). Intranasal esketamine plus an oral antidepressant provides rapid, modest acute improvement and reduces relapse risk during maintenance among stabilized responders/remitters, but increases acute adverse events, supporting use within supervised care and individualized benefit–risk assessment.
<![CDATA[Expert explores fast-acting depression treatments, psilocybin trial pitfalls, and why stigma still limits buprenorphine access for opioid use disorder.]]>
Prediction of Clinically Significant Depressive Symptoms at 2-Year Follow-Up in Older Adults: Machine Learning Study Using the English Longitudinal Study of Ageing
Background: Depression in older adults is often underdiagnosed due to atypical symptom presentation and generational stigma, leading to delayed intervention. Early identification of individuals at risk of developing elevated depressive symptoms is therefore critical, but traditional approaches show limited predictive accuracy. To date, no study has applied machine learning (ML) models to predict clinically significant depressive symptoms at 2-year follow-up in older adults in the United Kingdom using data from the English Longitudinal Study of Ageing (ELSA). Moreover, the impact of encoding strategies for categorical health care variables has not been examined. Objective: This study aimed to develop and evaluate ML models to predict the clinically significant depressive symptoms at 2-year follow-up in older adults using ELSA data. We further compared ordinal and one-hot encoding strategies across different ML architectures and identified key predictors of depressive symptoms at follow-up. Methods: Data were drawn from 4 consecutive waves of ELSA, including participants aged ≥50 years without significant depressive symptoms at the baseline wave (waves 6‐9). Clinically significant depressive symptoms were defined as 8-item Center for Epidemiologic Studies Depression Scale (CES-D 8) scores of ≥4 at the subsequent wave (waves 7‐10). Over 120 features spanning sociodemographic, psychological, and health-related domains were analyzed. Eight ML models were applied, including tree-based ensembles, deep learning architectures for tabular data, distance-based methods, probabilistic methods, and linear methods. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC) and -score. Model interpretability was examined using Shapley additive explanations (SHAP). Sensitivity analyses assessed the robustness of results across alternative CES-D 8 thresholds (≥3, ≥4, and ≥5) and encoding strategies. Results: Across waves, the best-performing models achieved mean AUROC scores of 0.72‐0.73, with a peak of 0.75 in the highest-performing wave. Ordinal encoding consistently outperformed one-hot encoding across all ML models, yielding improvements in AUROCs and -scores, with the greatest increase in tree-based methods. SHAP consistently identified loneliness, sleep disturbances, and low social engagement as strong predictors of elevated depressive symptoms at follow-up. Sensitivity analyses across CES-D 8 thresholds demonstrated robust feature importance, with AUROCs ranging from 0.67 to 0.82. Traditional ML models (random forest, extreme gradient boosting, and support vector machines) generally achieved higher performance than the deep learning models for this task. Conclusions: Our findings demonstrate the feasibility of predicting clinically significant depressive symptoms at 2-year follow-up in UK older adults, with moderate accuracy. Ordinal encoding demonstrates superior performance for health care datasets with inherently ordered categorical features. The identification of consistent risk factors highlights opportunities for developing targeted clinical screening tools and preventive interventions. This study provides new evidence on depressive symptom prediction in the UK context, leveraging longitudinal data from ELSA, and contributes to advancing digital mental health research for aging populations.
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EFE-8c4, a polyamine from Elaeagnus multiflora, protects neuronal cells by regulating oxidative stress and apoptotic pathways
Neurological disorders, including depression, cognitive impairment, and neurodegenerative diseases, are closely associated with oxidative stress, apoptotic neuronal loss, and impaired neuronal differentiation. Polyamine derivatives from natural products have emerged as potential neuroprotective agents, although their mechanisms remain incompletely understood. In this study, three polyamine compounds isolated from Elaeagnus multiflora fruit were evaluated in SH-SY5Y cell models of oxidative and glucocorticoid-induced stress. Among these, EFE-8c4 exhibited the most pronounced neuroprotective activity, significantly restoring cell viability under corticosterone-induced stress and attenuating oxidative damage induced by hydrogen peroxide. Mechanistically, EFE-8c4 modulated apoptotic signaling by increasing Bcl-2 expression while suppressing Bax, caspase-8, and p53 activation, thereby restoring the balance between pro- and anti-apoptotic pathways. In addition, EFE-8c4 reduced intracellular reactive oxygen species accumulation and enhanced the expression of PCNA and βIII-tubulin, indicating improved cell survival capacity and neuronal phenotype maintenance. Furthermore, EFE-8c4 partially reduced apoptotic cell populations under corticosterone exposure. Collectively, these findings demonstrate that EFE-8c4 exerts multi-target neuroprotective effects through coordinated regulation of apoptosis, oxidative stress, and neuronal differentiation-related pathways, highlighting its potential as a candidate for the treatment of oxidative stress-associated neurological disorders.
Neuromodulation of Mood Switch Circuitry in Bipolar Disorder
Conditions: Bipolar Disorder (BD); Bipolar 1 Depression; rTMS; fMRI
Interventions: Device: MagVenture MagPro TMS system; Device: Sham Stimulation
Sponsors: Weill Medical College of Cornell University; BD2 LLC
Not yet recruiting
Interventions: Device: MagVenture MagPro TMS system; Device: Sham Stimulation
Sponsors: Weill Medical College of Cornell University; BD2 LLC
Not yet recruiting
Accelerated iTBS for PTSD and Depression
Conditions: Post Traumatic Stress Disorder PTSD; Major Depressive Disorder (MDD)
Interventions: Device: Accelerated intermittent theta burst stimulation
Sponsors: Lawson Research Institute of St. Joseph’s
Not yet recruiting
Interventions: Device: Accelerated intermittent theta burst stimulation
Sponsors: Lawson Research Institute of St. Joseph’s
Not yet recruiting
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.
The relationship between mobile phone addiction and depression, anxiety among Chinese college students: the mediating role of friendship quality and the moderating effect of preference for solitude
BackgroundThe university stage represents a critical period for the development of individual mental health. Mobile phone addiction is closely linked to depression and anxiety among college students, and both friendship quality and preference for solitude are tightly associated with college students’ mobile phone addiction and emotional health. Therefore, this study aimed to investigate the relationships and internal mechanisms among mobile phone addiction, friendship quality, preference for solitude, depression and anxiety in college students.MethodsA total of 1083 Chinese college students (58.2% female; mean age = 19.87 ± 1.692 years) were included as participants. Data were collected using the Mobile Phone Addiction Index, Friendship Quality Questionnaire, Preference for Solitude Questionnaire, and Depression Anxiety Stress Scale. Data processing and analyses were conducted using SPSS 26.0 and the PROCESS macro.Results(1) Mobile phone addiction was significantly negatively correlated with friendship quality, and significantly positively correlated with both depression and anxiety; friendship quality was significantly negatively correlated with depression and anxiety; preference for solitude was significantly positively correlated with depression and anxiety. (2) Mobile phone addiction not only directly and positively predicted depression and anxiety among college students, but also predicted depression and anxiety through the mediating role of friendship quality. (3) The direct effect of mobile phone addiction on depression and the mediating effect of friendship quality in the relationships between mobile phone addiction and depression/anxiety were both moderated by preference for solitude, whereas the moderating effect of preference for solitude on the association between mobile phone addiction and anxiety was not significant.ConclusionFriendship quality serves as an important mediating pathway between mobile phone addiction and depressive and anxiety symptoms among Chinese college students. Preference for solitude may amplify the associations of mobile phone addiction with poorer friendship quality and elevated depressive symptoms.
Smoking as a correlate of suicidal behavior and self-harm in adolescents with depressive disorders
Suicidal behavior and self-harm are major public health concerns among adolescents, particularly those with depressive disorders. While smoking has been linked to suicidality in general populations, its independent role in both suicidal behavior and self-harm within well-characterized clinical samples of youth with depressive disorders remains understudied. This study consecutively enrolled 2,343 adolescents (aged 12–18 years) diagnosed with unipolar depression, bipolar disorder, or depressive episode according to DSM-5 criteria at Nanhai Public Health Hospital of Foshan City and The Third People’s Hospital of Foshan between January 2025 and December 2025. Suicidal behavior (≥1 suicide attempt) and self-harm (intentional self-injury or poisoning regardless of intent) were assessed via clinical interviews. Multivariable binary logistic regression models were constructed to identify factors independently associated with each outcome, adjusting for age, sex, education, income, parental education, psychiatric diagnosis, family history of mental illness, physical disease, and smoking status. Among 2,343 participants (mean age 14.99 ± 1.65 years; 77.8% female), the prevalence of self-harm was 76.0% and suicidal behavior was 44.2%. In fully adjusted models, smoking status was the only variable significantly associated with suicidal behavior after adjustment for measured covariates: current smokers (OR = 2.74, 95% CI: 1.81–4.22, P<0.001) and past quitters (OR = 2.32, 95% CI: 1.66–3.28, P<0.001) had higher odds compared to never smokers. For self-harm, current smoking was significantly associated with increased risk (OR = 2.31, 95% CI: 1.33–4.37, P = 0.006). Education level showed a borderline association with self-harm, with each additional year of schooling corresponding to a 10% lower odds (OR = 0.90, 95% CI: 0.81–1.00, P = 0.050); however, this finding should be interpreted cautiously given the exploratory nature of the analysis. No other demographic or clinical variables, including age, sex, or psychiatric diagnosis, were independently associated with either outcome. Smoking was strongly associated with both suicidal behavior and self−harm after adjustment for measured demographic and clinical covariates. These findings underscore the importance of assessing tobacco use as a potential clinical marker of vulnerability in youth mental health settings.