Current Neuropharmacology - Volume 23, Issue 11, 2025

Suicide is a major global public health concern that affects people of all ages, with over 700000 individuals intentionally ending their lives every year. Suicide is a multi-factorial event related to multiple risk factors interlocking with each other, among which neurobiological factors are considered to be an objective measure of the incidence of this phenomenon and can be used as a measurable tool for evaluating suicidal tendencies.

The aim of this study is to thoroughly examine available data and assess candidate proteins as prospective biomarkers for predicting suicides and ascertaining the manner of death in forensic cases.

An electronic search was conducted on PubMed, Science Direct Scopus, and the Excerpta Medica Database. The systematic review adhered to PRISMA guidelines and encompassed case series, prospective and retrospective studies, and short communications published in English. The focus was on proteomics and suicide, specifically, those studies where researchers conducted human proteomic analyses on specimens obtained from individuals who completed or attempted suicide.

A total of 14 studies met the inclusion criteria, resulting in a dataset of numerous candidate protein biomarkers. These include tenascin-C, potassium voltage-gated channel subfamily Q member 3, vimentin-immunoreactive astrocytes, glutathione S-transferase theta 1, iron transport proteins, A-crystallin chain B, manganese superoxide dismutase, glial fibrillary acidic protein, various glycolytic pathway proteins, 14-3-3 eta and 14-3-3 theta proteins, specific cytoskeleton proteins, C-reactive protein, serum amyloid A protein 1, extrinsic coagulation pathway proteins, the vacuolar-type proton pump ATPase subunit, plasma apolipoprotein A-IV, and ER stress proteins. These proteins are proposed as a panel of biomarkers to be evaluated in conjunction with other clinical predictors of suicide.

This review aims to provide a comprehensive summary of all proteomic studies conducted on cases of attempted or completed suicide. By doing so, it seeks to bridge existing gaps in knowledge and pave the way for future investigations. The ultimate goal is to potentially identify a suicide biomarker.

Astrocytes have emerged as key players in the pathogenesis of depression and antidepressant treatment. However, comprehensive reviews in this field were absent. The bibliometric analysis can effectively illustrate research trends and hotspots of a specific domain through analysis of publications.

We conducted a bibliometric analysis to overview the current hotspots and research trends of astrocytes in depression and antidepressant treatment.

We collected publications’ data from the science citation index expanded (SCI-E) of the Web of Science (WOS) database, and bibliometric analysis was applied through CiteSpace and VOSviewer software. Results were mapped via GraphPad Prism, Adobe Photoshop, and R software.

After analysis of 2896 publications, we analyzed the content of publications, most influential publications, productive journals, most cited journals, core authors, productive countries/regions, and institutions in this field. The cooperation of main countries and organizations was mapped. Most importantly, after a thorough analysis of keywords, we found neuroinflammation was a hot topic in this research field.

The results of the bibliometric study prove neuroinflammation is a hot topic in this research field. Nowadays, many studies have investigated the role of astrocytes in depression and antidepressant treatment from the perspective of neuroinflammation. It is essential to pay more attention to elucidating the mechanisms of astrocyte-mediated neuroinflammation to identify potential targets for antidepressant development.

Akkermansia muciniphila (A. muciniphila), a bacterial species within the human gut microbiome, has shown beneficial effects on host health. Emerging research suggests that A. muciniphila also influences neurobehavioral domains through the microbiota-gut-brain axis. This meta-analysis evaluates A. muciniphila’s impact on depression, anxiety, and stress in mouse models.

We conducted a systematic search of PubMed, Science Direct, Embase, and Web of Science databases up to March 2024, identifying 15 eligible studies.

Supplementation with A. muciniphila, its outer membrane protein (Amuc_1100), and extracellular vesicles (EVs) alleviated anxiety, depressive-like behaviors, and enhanced memory in mice. Compared to controls, intervention groups exhibited reduced anxiety-like behaviors, including increased travel distance in the open-field test (OFT) and more time spent in the lightbox during the light-dark box (LDB) test and open arms in the elevated plus maze (EPM). Depression-like symptoms were reduced, with lower immobility time in the tail suspension and forced swim tests. Memory function also improved, and learning time was reduced in the Y-maze and Barnes circular maze tests. Serotonin levels increased significantly in the serum and hippocampus, while corticosterone levels decreased, though not significantly. The intervention reduced hippocampal and serum inflammatory markers (TNFα, IL1β, IL6) and altered gut microbiome composition, increasing Akkermansia, Roseburia, Caldicoprobacter, and Lachnospiraceae.

This meta-analysis provides evidence supporting the health-promoting effects of A. muciniphila, one of the next-generation probiotics, in alleviating neuropsychiatric disorders. Given the high prevalence and clinical significance of depression, anxiety, and stress, further investigation into the therapeutic utility of A. muciniphila is warranted.

Language deficits, restricted and repetitive interests, and social difficulties are among the characteristics of autism spectrum disorder (ASD). Machine learning and neuroimaging have also been combined to examine ASD. Utilizing bibliometric analysis, this study examines the current state and hot topics in machine learning for ASD.

A research bibliometric analysis of the machine learning application in ASD trends, including research trends and the most popular topics, as well as proposed future directions for research.

From 1999 to 2023, the Web of Science Core Collection (WoSCC) was searched for publications relating to machine learning and ASD. Authors, articles, journals, institutions, and countries were characterized using Microsoft Excel 2021 and VOSviewer. Analysis of knowledge networks, collaborative maps, hotspots, and trends was conducted using VOSviewer and CiteSpace.

A total of 1357 papers were identified between 1999 and 2023. There was a slow growth in publications until 2016; then, between 2017 and 2023, a sharp increase was recorded. Among the most important contributors to this field were the United States, China, India, and England. Among the top major research institutions with numerous publications were Stanford University, Harvard Medical School, the University of California, the University of Pennsylvania, and the Chinese Academy of Sciences. Wall, Dennis P. was the most productive and highest-cited author. Scientific Reports, Frontiers In Neuroscience Autism Research, and Frontiers In Psychiatry were the three productive journals. “autism spectrum disorder”, “machine learning”, “children”, “classification” and “deep learning” are the central topics in this period.

Cooperation and communication between countries/regions need to be enhanced in future research. A shift is taking place in the research hotspot from “Alzheimer's Disease”, “Mild Cognitive Impairment” and “cortex” to “artificial intelligence”, “deep learning”, “electroencephalography” and “pediatrics”. Crowdsourcing machine learning applications and electroencephalography for ASD diagnosis should be the future development direction. Future research about these hot topics would promote understanding in this field.

Inflammation is linked to the pathophysiology of schizophrenia. The neutrophil-to-lymphocyte ratio (NLR), a measure of systemic inflammation, has been reported to be associated with schizophrenia. However, few studies have examined the sex-specific association between neutrophil-to-lymphocyte ratio (NLR) and clinical symptoms in schizophrenia. This study aimed to explore sex differences in NLR and its correlation with symptoms in first-episode schizophrenia (FES) patients.

Ninety-seven FES patients and 65 control subjects were recruited. The severity of clinical symptoms was assessed using the Positive and Negative Syndrome Scale (PANSS), and white blood cells were calculated. We performed a cross-sectional analysis comparing NLR in males and females in the patient and control groups. We explored its sex-specific associations with clinical symptoms in the patient group.

We found that neutrophil (NEU) counts and NLR were higher in male patients compared to female patients with schizophrenia. There were no significant differences in white blood cell counts and NLR in healthy controls. Linear regression analysis showed that NEU counts were associated with clinical symptoms in male patients, and NLR correlated with symptoms in female patients after controlling for age, onset age, and years of education.

Our study suggests that NLR values and NEU counts were higher in male patients compared with female patients with schizophrenia and that the association between NLR or NEU and clinical symptoms was sex-specific.

It is now widely established that dopamine, despite its nature as a slow-acting biogenic monoamine, modulates fast neurotransmitters such as GABA. However, the mechanism through which this occurs still needs to be fully elucidated. The dopamine transporter (DAT) is the primary regulator of dopamine homeostasis, controlling extracellular levels of dopamine as well as its storage in vesicles.

Here, we took advantage of the availability of dopamine transporter knockout (DAT^-/-) rats, which provide a unique opportunity to investigate the response of the GABAergic system under hyperactivity of the dopaminergic system, a condition found in different disorders of the Central Nervous System. The expression levels of GABAergic markers have been evaluated by means of western blot in the whole homogenate, cytosolic fraction, and post-synaptic density of the striatum of male DAT^-/- rats.

We found a widespread down-regulation of GABAergic markers in the striatum of DAT^-/- rats. Our data show that DA overactivity critically reorganizes the striatal GABAergic synapse in a way that GABA neurotransmission appears to be toned down. Such changes are equally distributed among proteins regulating GABA synthesis (GAD67), release (vGAT) and reuptake (GAT1, GAT3). It also involves the main subunits of GABA receptors (GABA-A α1, α2, β1; GABA-B R1), their anchoring proteins (Gephyrin) and adhesion molecules (Neuroligin-2).

Taken together, such changes paint a picture showing a compromised integrity of the striatal GABAergic system under conditions of functional hyperdopaminergia, which may be of interest for several disorders of the central nervous system.