What enlightenment has the development of lung cancer bone metastasis brought in the last 22 years.

BACKGROUND: Lung cancer bone metastasis (LCBM) is a disease with a poor prognosis, high risk and large patient population. Although considerable scientific output has accumulated on LCBM, problems have emerged, such as confusing research structures. AIM: To organize the research frontiers and body of knowledge of the studies on LCBM from the last 22 years according to their basic research and translation, clinical treatment, and clinical diagnosis to provide a reference for the development of new LCBM clinical and basic research. METHODS: We used tools, including R, VOSviewer and CiteSpace software, to measure and visualize the keywords and other metrics of 1903 articles from the Web of Science Core Collection. We also performed enrichment and protein-protein interaction analyses of gene expression datasets from LCBM cases worldwide. RESULTS: Research on LCBM has received extensive attention from scholars worldwide over the last 20 years. Targeted therapies and immunotherapies have evolved into the mainstream basic and clinical research directions. The basic aspects of drug resistance mechanisms and parathyroid hormone-related protein may provide new ideas for mechanistic study and improvements in LCBM prognosis. The produced molecular map showed that ribosomes and focal adhesion are possible pathways that promote LCBM occurrence. CONCLUSION: Novel therapies for LCBM face animal testing and drug resistance issues. Future focus should centre on advancing clinical therapies and researching drug resistance mechanisms and ribosome-related pathways.

A brief review of current treatment options for osteoarthritis including disease-modifying osteoarthritis drugs (DMOADs) and novel therapeutics.

Osteoarthritis (OA) is a chronic disorder caused by degenerative changes in articular cartilage, which are mainly manifests as degeneration of cartilage, subchondral bone remodeling, as well as synovial inflammation. Over the next few decades, OA and its burden will continue to increase worldwide, posing a major public health challenge for the foreseeable future. Treatment for OA includes non-pharmacological, pharmacological, and surgical treatments. Existing conservative treatments and joint surgery can only alleviate the symptoms and cannot be cured, so new therapies for OA are urgently needed. Since advances in the understanding of OA pathophysiology, researchers have identified some potential therapeutic targets against degeneration of cartilage, subchondral bone remodeling and synovial inflammation, enabling development of the disease-modifying OA drugs (DMOADs). Additionally, a number of new technologies are also being investigated for treating OA, such as RNA interference (RNAi), CRISPR/Cas9 and PROTAC. The goal of this review is to describe the current development status of DMOADs and to discuss the potential of emerging therapeutic approaches for treating OA, thus providing a reference for OA treatments.

Short- and Long-Term Outcome of Selective Reduction by Fetoscopy-Guided Bipolar Cord Coagulation in Monochronic Twin Pregnancies.

INTRODUCTION: The aim of this study was to assess the short- and long-term outcome of selective reduction by fetoscopy-guided bipolar cord coagulation in monochronic twin pregnancies. METHODS: Retrospective analysis was conducted of a consecutive cohort of all monochorionic twin pregnancies treated with fetoscopy-guided bipolar cord coagulation between December 2015 and December 2022 in a single center in China. RESULTS: A total of 43 monochronic twin pregnancies undergoing fetoscopy-guided bipolar cord coagulation were analyzed. There were 5 intrauterine deaths with an 88.4% (38/43) survival rate overall. The preterm premature rupture of the membranes rate was 13.2%, and the preterm birth before 37 and 32 weeks was 42.1% and 13.1%, respectively. An uptrend in the survival rate (78.9 vs. 95.8%, p = 0.086) and a downtrend of procedure time (30 vs. 16.5 min, p = 0.036) were observed over time (period 1 from December 2015 to December 2019 verses period 2 from January 2020 to December 2022). Long-term outcome was assessed in 94.6% (35/37) of survivors, and 91.4% (32/35) had normal neurodevelopmental outcome. CONCLUSION: Fetoscopy-guided bipolar cord coagulation for fetal reduction in complicated monochorionic twin pregnancies could achieve a favorable short- and long-term outcome, especially in experienced hands.

Chiral dinitrogen ligand enabled asymmetric Pd/norbornene cooperative catalysis toward the assembly of C-N axially chiral scaffolds.

C - N axially chiral compounds have recently attracted significant interest among synthetic chemistry community due to their widespread application in pharmaceuticals, advanced materials and organic synthesis. Although the emerging asymmetric Catellani reaction offers great opportunity for their modular and efficient preparation, the only operative chiral NBE strategy to date requires using half stoichiometric amount of chiral NBE and 2,6-disubstituted bromoarenes as electrophiles. We herein report an efficient assembly of C-N axially chiral scaffolds through a distinct chiral ligand strategy. The crucial chiral source, a biimidazoline (BiIM) chiral dinitrogen ligand, is used in relatively low loading and permits the use of less bulky bromoarenes. The method also features the use of feedstock plain NBE, high reactivity, good enantioselectivity, ease of operation and scale-up. Applications in the preparation of chiral optoelectronic material candidates featuring two C-N chiral axes and a chiral ligand for asymmetric C-H activation have also been demonstrated.

Evaluation of plasma-derived extracellular vesicles miRNAs and their connection with hippocampal mRNAs in alcohol use disorder.

Alcohol use disorder (AUD) is a common mental illness with high morbidity and disability. The discovery of laboratory biomarkers has progressed slowly, resulting in suboptimal diagnosis and treatment of AUD. This study aimed to identify promising biomarkers, as well as the potential miRNA-mRNA networks associated with AUD pathogenesis. RNA sequencing was performed on plasma-derived small extracellular vesicles (sEVs) from AUD patients and healthy controls (HCs) to harvest miRNAs expression profiles. Machine learning (ML) models were built to screen characteristic miRNAs, whose target mRNAs were analyzed using TargetScan, miRanda and miRDB databases. Gene Expression Omnibus (GEO) datasets (GSE181804 and GSE180722) providing postmortem hippocampal gene expression profiles of AUD subjects were mined. A total of 247 differentially expressed (DE) plasma-derived sEVs miRNAs and 122 DE hippocampal mRNAs were obtained. Then, 22 overlapping sEVs miRNAs with high importance scores were gained by intersecting 5 ML models. As a result, we established a putative sEVs miRNA-hippocampal mRNA network that can effectively distinguish AUD patients from HCs. In conclusion, we proposed 5 AUD-representative sEVs miRNAs (hsa-miR-144-5p, hsa-miR-182-5p, hsa-miR-142-5p, hsa-miR-7-5p, and hsa-miR-15b-5p) that may participate in the pathogenesis of AUD by modulating downstream target hippocampal genes. These findings may provide novel insights into the diagnosis and treatment of AUD.

Elucidating the Link Between Anxiety/Depression and Alzheimer's Dementia in the Australian Imaging Biomarkers and Lifestyle (AIBL) Study.

BACKGROUND: The associations between mood disorders (anxiety and depression) and mild cognitive impairment (MCI) or Alzheimer's dementia (AD) remain unclear. METHODS: Data from the Australian Imaging, Biomarker & Lifestyle (AIBL) study were subjected to logistic regression to determine both cross-sectional and longitudinal associations between anxiety/depression and MCI/AD. Effect modification by selected covariates was analysed using the likelihood ratio test. RESULTS: Cross-sectional analysis was performed to explore the association between anxiety/depression and MCI/AD among 2,209 participants with a mean [SD] age of 72.3 [7.4] years, of whom 55.4% were female. After adjusting for confounding variables, we found a significant increase in the odds of AD among participants with two mood disorders (anxiety: OR 1.65 [95% CI 1.04-2.60]; depression: OR 1.73 [1.12-2.69]). Longitudinal analysis was conducted to explore the target associations among 1,379 participants with a mean age of 71.2 [6.6] years, of whom 56.3% were female. During a mean follow-up of 5.0 [4.2] years, 163 participants who developed MCI/AD (refer to as PRO) were identified. Only anxiety was associated with higher odds of PRO after adjusting for covariates (OR 1.56 [1.03-2.39]). However, after additional adjustment for depression, the association became insignificant. Additionally, age, sex, and marital status were identified as effect modifiers for the target associations. CONCLUSION: Our study provides supportive evidence that anxiety and depression impact on the evolution of MCI/AD, which provides valuable epidemiological insights that can inform clinical practice, guiding clinicians in offering targeted dementia prevention and surveillance programs to the at-risk populations.

Different dosage forms of GnRHa with endocrine therapy in premenopausal hormone Receptor-Positive breast cancer.

BACKGROUND: Despite the wide use of a three-month gonadotropin-releasing hormone agonist (3M GnRHa) for ovarian function suppression (OFS) in premenopausal breast cancer patients, it remains unclear whether it is as effective and safe as a one-month GnRHa regimen (1M GnRHa) when combined with selective estrogen receptor modulators (SERMs) or aromatase inhibitors (AIs), especially in younger patients. METHODS: This retrospective cohort study included 1109 premenopausal hormone receptor-positive (HR+) breast cancer patients treated with GnRHa plus SERM or AI. The estradiol (E2) inhibition rate within 1-24 months after treatment with 1M or 3M GnRHa in cohorts and different subgroups was analyzed. RESULTS: Following 1:1 propensity score matching, 950 patients with a mean age of 39 years and a median follow-up of 46 months were included. Both the 1M and 3M groups achieved >90% E2 inhibition within 24 months (94.53% vs 92.84%, 95% CI (-4.78%, 1.41%)), confirming the non-inferiority of 3M GnRHa. Both 1M and 3M GnRHa rapidly and consistently reduced E2 levels. 60 (6.3%) patients experienced incomplete ovarian function suppression (iOFS), with similar rates in the 1M and 3M groups (5.5% vs 7.2%). iOFS mainly occurred within the first 12 months, with age <40 years and no prior chemotherapy being the risk factors. Similar disease-free survival (DFS) and overall survival (OS) were found in the 1M and 3M groups, and in patients with complete and incomplete OFS (p > .05). CONCLUSIONS: The OFS with 3M GnRHa was not inferior to that with 1M GnRHa, regardless of age or combination with a SERM or an AI.

Associations of Early-Life Deprivation and Threat with Exploratory Behavior: Moderated Mediation Models of Sensation Seeking and Executive Function.

Exploratory behavior, as a crucial aspect of decision-making, plays an indispensable role in maximizing long-term benefits and is, therefore, essential in promoting adolescents' psychological well-being and social adaptation. Recent studies have shown that this adaptive behavior is influenced by previous early experiences. However, little was known about the associations between specific types of childhood maltreatment and exploratory behavior and the roles of individual motivational and cognitive factors in these relationships. The present study aimed to examine whether the subtypes of maltreatment, that is, threat and deprivation, would influence adolescents' exploratory behavior, the mediating role of sensation seeking, and the moderating role of executive function. Using a sample of 720 Chinese adolescents (Mage = 13.29, SDage = 0.82, 54.8% female), we found that sensation seeking fully mediated the relationship between threat and exploratory behavior. That is, adolescents who experienced threat were more likely to increase sensation seeking, which further promote exploratory activities. Moreover, executive function was a second-stage moderator of this full mediation pathway, with the mediating effect of sensation seeking between threat and exploratory behavior increasing with the enhancement of executive function. However, we did not observe the mediating effect of sensation seeking and the second-stage moderating effect of executive function on the relationship between deprivation and exploration. Considering the distinct impact mechanisms of threat and deprivation on exploratory behavior, our study provides empirical support for the Dimensional Model of Adversity and Psychopathology, and highlights the critical role of sensation seeking and the necessity of implementing executive function interventions for those experiencing threat experiences.

ScRNA-seq revealed the tumor microenvironment heterogeneity related to the occurrence and metastasis in upper urinary tract urothelial carcinoma.

Metastasis is the greatest clinical challenge for UTUCs, which may have distinct molecular and cellular characteristics from earlier cancers. Herein, we provide single-cell transcriptome profiles of UTUC para cancer normal tissue, primary tumor lesions, and lymphatic metastases to explore possible mechanisms associated with UTUC occurrence and metastasis. From 28,315 cells obtained from normal and tumor tissues of 3 high-grade UTUC patients, we revealed the origin of UTUC tumor cells and the homology between metastatic and primary tumor cells. Unlike the immunomicroenvironment suppression of other tumors, we found no immunosuppression in the tumor microenvironment of UTUC. Moreover, it is imperative to note that stromal cells are pivotal in the advancement of UTUC. This comprehensive single-cell exploration enhances our comprehension of the molecular and cellular dynamics of metastatic UTUCs and discloses promising diagnostic and therapeutic targets in cancer-microenvironment interactions.

Agonistic anti-DCIR antibody inhibits ITAM-mediated inflammatory signaling and promotes immune resolution.

DC inhibitory receptor (DCIR) is a C-type lectin receptor selectively expressed on myeloid cells, including monocytes, macrophages, DCs, and neutrophils. Its role in immune regulation has been implicated in murine models and human genome-wide association studies, suggesting defective DCIR function associates with increased susceptibility to autoimmune diseases such as rheumatoid arthritis, lupus, and Sjögren's syndrome. However, little is known about the mechanisms underlying DCIR activation to dampen inflammation. Here, we developed anti-DCIR agonistic antibodies that promote phosphorylation on DCIR's immunoreceptor tyrosine-based inhibitory motifs and recruitment of SH2 containing protein tyrosine phosphatase-2 for reducing inflammation. We also explored the inflammation resolution by depleting DCIR+ cells with antibodies. Utilizing a human DCIR-knock-in mouse model, we validated the antiinflammatory properties of the agonistic anti-DCIR antibody in experimental peritonitis and colitis. These findings provide critical evidence for targeting DCIR to develop transformative therapies for inflammatory diseases.

Multifunctional Integrated Organic-Inorganic-Metal Hybrid Aerogel for Excellent Thermal Insulation and Electromagnetic Shielding Performance.

Vehicles operating in space need to withstand extreme thermal and electromagnetic environments in light of the burgeoning of space science and technology. It is imperatively desired to high insulation materials with lightweight and extensive mechanical properties. Herein, a boron-silica-tantalum ternary hybrid phenolic aerogel (BSiTa-PA) with exceptional thermal stability, extensive mechanical strength, low thermal conductivity (49.6 mW m-1 K-1), and heightened ablative resistance is prepared by an expeditious method. After extremely thermal erosion, the obtained carbon aerogel demonstrates noteworthy electromagnetic interference (EMI) shielding performance with an efficiency of 31.6 dB, accompanied by notable loading property with specific modulus of 272.8 kN·m kg-1. This novel design concept has laid the foundation for the development of insulation materials in more complex extreme environments.

T2-weighted imaging-based deep-learning method for noninvasive prostate cancer detection and Gleason grade prediction: a multicenter study.

OBJECTIVES: To noninvasively detect prostate cancer and predict the Gleason grade using single-modality T2-weighted imaging with a deep-learning approach. METHODS: Patients with prostate cancer, confirmed by histopathology, who underwent magnetic resonance imaging examinations at our hospital during September 2015-June 2022 were retrospectively included in an internal dataset. An external dataset from another medical center and a public challenge dataset were used for external validation. A deep-learning approach was designed for prostate cancer detection and Gleason grade prediction. The area under the curve (AUC) was calculated to compare the model performance. RESULTS: For prostate cancer detection, the internal datasets comprised data from 195 healthy individuals (age: 57.27 ± 14.45 years) and 302 patients (age: 72.20 ± 8.34 years) diagnosed with prostate cancer. The AUC of our model for prostate cancer detection in the validation set (n = 96, 19.7%) was 0.918. For Gleason grade prediction, datasets comprising data from 283 of 302 patients with prostate cancer were used, with 227 (age: 72.06 ± 7.98 years) and 56 (age: 72.78 ± 9.49 years) patients being used for training and testing, respectively. The external and public challenge datasets comprised data from 48 (age: 72.19 ± 7.81 years) and 91 patients (unavailable information on age), respectively. The AUC of our model for Gleason grade prediction in the training set (n = 227) was 0.902, whereas those of the validation (n = 56), external validation (n = 48), and public challenge validation sets (n = 91) were 0.854, 0.776, and 0.838, respectively. CONCLUSION: Through multicenter dataset validation, our proposed deep-learning method could detect prostate cancer and predict the Gleason grade better than human experts. CRITICAL RELEVANCE STATEMENT: Precise prostate cancer detection and Gleason grade prediction have great significance for clinical treatment and decision making. KEY POINTS: Prostate segmentation is easier to annotate than prostate cancer lesions for radiologists. Our deep-learning method detected prostate cancer and predicted the Gleason grade, outperforming human experts. Non-invasive Gleason grade prediction can reduce the number of unnecessary biopsies.

DenseNet model incorporating hybrid attention mechanisms and clinical features for pancreatic cystic tumor classification.

PURPOSE: The aim of this study is to develop a deep learning model capable of discriminating between pancreatic plasma cystic neoplasms (SCN) and mucinous cystic neoplasms (MCN) by leveraging patient-specific clinical features and imaging outcomes. The intent is to offer valuable diagnostic support to clinicians in their clinical decision-making processes. METHODS: The construction of the deep learning model involved utilizing a dataset comprising abdominal magnetic resonance T2-weighted images obtained from patients diagnosed with pancreatic cystic tumors at Changhai Hospital. The dataset comprised 207 patients with SCN and 93 patients with MCN, encompassing a total of 1761 images. The foundational architecture employed was DenseNet-161, augmented with a hybrid attention mechanism module. This integration aimed to enhance the network's attentiveness toward channel and spatial features, thereby amplifying its performance. Additionally, clinical features were incorporated prior to the fully connected layer of the network to actively contribute to subsequent decision-making processes, thereby significantly augmenting the model's classification accuracy. The final patient classification outcomes were derived using a joint voting methodology, and the model underwent comprehensive evaluation. RESULTS: Using the five-fold cross validation, the accuracy of the classification model in this paper was 92.44%, with an AUC value of 0.971, a precision rate of 0.956, a recall rate of 0.919, a specificity of 0.933, and an F1-score of 0.936. CONCLUSION: This study demonstrates that the DenseNet model, which incorporates hybrid attention mechanisms and clinical features, is effective for distinguishing between SCN and MCN, and has potential application for the diagnosis of pancreatic cystic tumors in clinical practice.

Absolute Structures of a Mirror Pair of Infinite Na(H2O)4 + -Connected ε-Keggin-Al13 Species.

The absolute structures of a pair of infinite Na(H2O)4+-connected ε-Keggin-Al13 species (Na-ε-K-Al13) that were inversion structures and mirror images of each other were determined. Single crystals obtained by adding A2SO4 (A = Li, Na, K, Rb, or Cs) solution to NaOH-hydrolyzed AlCl3 solution were subjected to X-ray structure analyses. The statistical results for 36 single crystals showed that all the crystals had almost the same unit cell parameter, belonged to the same F4̅3m space group, and possessed the same structural formula [Na(H2O)4AlO4Al12(OH)24(H2O)12](SO4)4·10H2O. However, the crystals had two inverse absolute structures (denoted A and B), which had a crystallization ratio of 1:1. From Li+ to Cs+, with increasing volume of the cation coexisting in the mother solution, the degree of disorder of the four H2O molecules in the Na(H2O)4+ hydrated ion continuously decreased; they became ordered when the cation was Cs+. Absolute structures A and B are the first two infinite aluminum polycations connected by statistically occupied [(Na1/4)4(H2O)4]+ hydrated ions. The three-dimensional structure of the infinite Na-ε-K-Al13 species can be regarded as the assembly of finite ε-K-Al13 species linked by [(Na1/4)4(H2O)4]+ in a 1:1 ratio. In this assembly, each [(Na1/4)4(H2O)4]+ is connected to four ε-K-Al13 and each ε-K-Al13 is also connected to four [(Na1/4)4(H2O)4]+ in tetrahedral orientations to form a continuous rigid framework structure, which has an inverse spatial orientation between absolute structure A and B. This discovery clarifies that the ε-K-Al13 (or ε-K-GaAl12) species in Na[MO4Al12(OH)24(H2O)12](XO4)4·nH2O (M = Al, Ga; X = S, Se; n = 10-20) exists as discrete groups and deepens understanding of the formation and evolution process of polyaluminum species in forcibly hydrolyzed aluminum salt solution. The reason why Na+ statistically occupies the four sites was examined, and a formation and evolution mechanism of the infinite Na-ε-K-Al13 species was proposed.

Feasibility of rib fracture detection in low-dose computed tomography images with a large, multicenter datasets-based model.

Purpose: To evaluate the feasibility of rib fracture detection in low-dose computed tomography (CT) images with a RetinaNet-based approach and to evaluate the potential of lowdose CT for rib fracture detection compared with regular-dose CT images. Materials and methods: The RetinaNet-based deep learning model was trained using 7300 scans with 50,410 rib fractures that were used as internal training datasets from four multicenter. The external test datasets consisted of both regular-dose and low-dose chest-abdomen CT images of rib fractures; the MICCAI 2020 RibFrac Challenge Dataset was used as the public dataset. Radiologists' interpretations were used as reference standards. The performance of the model in rib fracture detection was compared with the radiologists' interpretation. Results: In total, 728 traumatic rib fractures of 100 patients [60 men (60 %); mean age, 53.45 ± 11.19 (standard deviation (SD)); range, 18-77 years] were assessed in the external datasets. In these patients, the regular-dose group had a mean CT dose index volume (CTDIvol) of 7.18 mGy (SD: 2.22) and a mean dose length product (DLP) of 305.38 mGy cm (SD: 95.31); the low-dose group had a mean CTDIvol of 2.79 mGy (SD: 1.11) and a mean DLP of 131.52 mGy cm (SD: 55.58). The sensitivity of the RetinaNet-based model and that of the radiologists was 0.859 and 0.721 in the low-dose CT images and 0.886 and 0.794 in the regular-dose CT images, respectively. Conclusions: These findings indicate that the RetinaNet-based model can detect rib fractures in low-dose CT images with a robust performance, indicating its feasibility in assisting radiologists with rib fracture diagnosis.

Exploring the link between comorbidities and Alzheimer's dementia in the Australian Imaging, Biomarker & Lifestyle (AIBL) study.

INTRODUCTION: Mounting evidence suggests that certain comorbidities may influence the clinical evolution of Alzheimer's dementia (AD). METHODS: We conducted logistic regression analyses on the medical history and cognitive health diagnoses of participants in the Australian Imaging, Biomarker & Lifestyle study (n = 2443) to investigate cross-sectional associations between various comorbidities and mild cognitive impairment (MCI)/AD. RESULTS: A mixture of associations were observed. Higher comorbidity of anxiety and other neurological disorders was associated with higher odds of AD, while arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD. DISCUSSION: This study underscores the links between specific comorbidities and MCI/AD. Further research is needed to elucidate the longitudinal comorbidity-MCI/AD associations and underlying mechanisms of these associations. Highlights: Comorbidities that significantly increased AD odds included anxiety and other neurological disorders.Arthritis, cancer, gastric complaints, high cholesterol, joint replacement, visual defect, kidney and liver disease were associated with lower odds of AD.Alcohol consumption had the most significant confounding effect in the study.Visual-AD association was modified by age, sex, and APOE ε4 allele status.Anxiety-AD and depression-AD associations were modified by sex.

Multi-Omics Characterization of Colon Mucosa and Submucosa/Wall from Crohn's Disease Patients.

Crohn's disease (CD) is a subtype of inflammatory bowel disease (IBD) characterized by transmural disease. The concept of transmural healing (TH) has been proposed as an indicator of deep clinical remission of CD and as a predictor of favorable treatment endpoints. Understanding the pathophysiology involved in transmural disease is critical to achieving these endpoints. However, most studies have focused on the intestinal mucosa, overlooking the contribution of the intestinal wall in Crohn's disease. Multi-omics approaches have provided new avenues for exploring the pathogenesis of Crohn's disease and identifying potential biomarkers. We aimed to use transcriptomic and proteomic technologies to compare immune and mesenchymal cell profiles and pathways in the mucosal and submucosa/wall compartments to better understand chronic refractory disease elements to achieve transmural healing. The results revealed similarities and differences in gene and protein expression profiles, metabolic mechanisms, and immune and non-immune pathways between these two compartments. Additionally, the identification of protein isoforms highlights the complex molecular mechanisms underlying this disease, such as decreased RTN4 isoforms (RTN4B2 and RTN4C) in the submucosa/wall, which may be related to the dysregulation of enteric neural processes. These findings have the potential to inform the development of novel therapeutic strategies to achieve TH.

Explosion of research on psychopathology and social media use after COVID-19: A scientometric study.

BACKGROUND: Despite advances in research on psychopathology and social media use, no comprehensive review has examined published papers on this type of research and considered how it was affected by the coronavirus disease 2019 (COVID-19) outbreak. AIM: To explore the status of research on psychopathology and social media use before and after the COVID-19 outbreak. METHODS: We used Bibliometrix (an R software package) to conduct a scientometric analysis of 4588 relevant studies drawn from the Web of Science Core Collection, PubMed, and Scopus databases. RESULTS: Such research output was scarce before COVID-19, but exploded after the pandemic with the publication of a number of high-impact articles. Key authors and institutions, located primarily in developed countries, maintained their core positions, largely uninfluenced by COVID-19; however, research production and collaboration in developing countries increased significantly after COVID-19. Through the analysis of keywords, we identified commonly used methods in this field, together with specific populations, psychopathological conditions, and clinical treatments. Researchers have devoted increasing attention to gender differences in psychopathological states and linked COVID-19 strongly to depression, with depression detection becoming a new trend. Developments in research on psychopathology and social media use are unbalanced and uncoordinated across countries/regions, and more in-depth clinical studies should be conducted in the future. CONCLUSION: After COVID-19, there was an increased level of concern about mental health issues and a changing emphasis on social media use and the impact of public health emergencies.