Psychological Health Conditions and COVID-19-Related Stressors Among University Students: A Repeated Cross-Sectional Survey

The Coronavirus Disease 2019 (COVID-19) pandemic has broadly impacted university students’ customary life, resulting in remarkable levels of stress and psychological suffering. Although the acute phase of the crisis has been overcome, it does not imply that perceived stress related to the risk of contagion and to the changes in the relational life experienced over more than 1 year of the pandemic will promptly and abruptly decrease. This study aims at comparing university students’ psychological health conditions before and during the COVID-19 pandemic, but also at providing information on how psychological health conditions evolved over the 1 year of the pandemic. We analyzed data from a repeated cross-sectional survey on different samples of university students before the pandemic in 2017 (n = 545) and during the pandemic (n = 671). During the pandemic, data were collected at three stages (Stage 1, April 2020 n = 197; Stage 2, November 2020 n = 274; and Stage 3, April 2021 n = 200). The COVID-19 Student Stress Questionnaire (CSSQ) and the Symptom-Checklist-90-Revised (SCL-90-R) were used to assess, respectively, COVID-19-related stressors (Relationships and Academic Life, Isolation, and Fear of Contagion) and the presence of psychological symptoms. Psychological health conditions were compared at baseline and during the pandemic, whereas both psychological health conditions and perceived levels of COVID-19-related stressors were compared over the three pandemic stages. In addition, Logistic Regression was used to explore the associations between COVID-19-related stressors and psychological symptoms. Findings revealed a significant increase in symptoms of Depression (DEP), Phobic-Anxiety (PHOB), Obsessive-Compulsive (O-C), and Psychoticism (PSY) from pre to during the pandemic. Perceived levels of COVID-19-related stress and specific psychological symptoms significantly increased as the pandemic was progressing. COVID-19-related stressors emerged as significantly associated with several psychopathological symptoms. Findings are discussed with the aim of providing tailored interventions to prevent mental disease and promote psychological adjustment in this specific stage of transition within this exceptional global emergency.

Pre- and Post-treatment Levels of Plasma Metabolites in Patients With Bipolar Depression

Background: Bipolar disorder (BD) is a serious mental disease with complex clinical manifestations and high recurrence rate. The purpose of this study was to detect metabolites related to the diagnosis and efficacy evaluation of bipolar depression in plasma samples by metabolomics.Methods: Thirty-one bipolar depression patients were recruited and completed 8 weeks medication and a matched group of 47 healthy controls (HCs) was recruited. Nuclear magnetic resonance spectroscopy was used to profile plasma samples of bipolar depression patients at baseline and after 8 weeks medication, and HCs. Then Multivariate statistical analysis was performed to analyze differences of plasma metabolites among the three groups.Results: We detected seven specific differential metabolites in bipolar depression. Six of the metabolites were returned to the normal levels in different degrees after 8 weeks medication, only Glycine continuously decreased in the acute and significant improvement stages of bipolar depression (VIP > 1 and p < 0.05). These differential metabolites involved several metabolic pathways.Limitations: The small sample size was one of the most prominent limitations. Each BD patient was given an individualized medication regimen according to the clinical guidelines.Conclusion: There were metabolites changes before and after 8 weeks medication. Glycine may be a characteristic marker of bipolar depression and does not change with the improvement of bipolar depression, while other 6 differential metabolites may be biomarkers associated with the pathological development or the improvement of bipolar depression. And, these differential metabolites mainly related to energy metabolism, amino acid metabolism and gut microbiota metabolism.

A Bibliometric and Visualization Analysis of Mindfulness and Meditation Research from 1900 to 2021

This study comprehensively summarizes research in the field of meditation, especially mindfulness meditation from 1900 to 2021, by analyzing the knowledge map through CiteSpace and VOSviewer software. Using “mindfulness *” or “meditation *” as the topic, articles included in the Science Citation Index Expanded and Social Sciences Citation Index were searched in the web of science core database, resulting in the selection of 19,752 articles. Over half a century ago, Deikman published the field’s first article in the Journal of Nervous and Mental Disease in 1963, and publications have soared in subsequent decades. The USA is in the core position in terms of global collaboration, total publication numbers, and total citations. The Mindfulness journal ranked first for the most published articles and citations. “The benefits of being present: Mindfulness and its role in psychological well-being,” written by Brown and Ryan, was the most cited article. Mindfulness, meditation, depression, intervention, stress reduction, stress, and anxiety are the top co-occurrence keywords. The timeline of cluster analysis discloses that before 2010, hypertension, cancer, mindfulness, generalized anxiety disorder, and other topics received great attention. In the decade since 2010, scholars have shown interest in meta-analysis, attention, and self-assessment, and keen attention to mindfulness-based interventions. These findings provide an important foundation to direct future research.

Zooming in on the cell biology of disease

Today’s cell biology could be considered a fusion of disciplines that blends advanced genetics, molecular biology, biochemistry, and engineering to answer fundamental as well as medically relevant scientific questions. Accordingly, our understanding of diseases is greatly aided by an existing vast knowledge base of fundamental cell biology. Gunter Blobel captured this concept when he said, “the tremendous acquisition of basic knowledge will allow a much more rational treatment of cancer, viral infection, degenerative disease and mental disease.” In other words, without cell biology can we truly understand, prevent, or effectively treat a disease?

Patient Behavioral Analysis with Smart Healthcare and IoT

Patient behavioral analysis is the key factor for providing treatment to patients who may suffer from various difficulties including neurological disease, head trauma, and mental disease. Analyzing the patient’s behavior helps in determining the root cause of the disease. In traditional healthcare, patient behavioral analysis has lots of challenges that were much more difficult. The patient behavior can be easily analyzed with the development of smart healthcare. Information technology plays a key role in understanding the concept of smart healthcare. A new generation of information technologies including IoT and cloud computing is used for changing the traditional healthcare system in all ways. Using Internet of Things in the healthcare institution enhances the effectiveness as well as makes it more personalized and convenient to the patients. The first thing that will be discussed in the article is the technologies that have been used to support the smart class, and further, there will be a discussion on the existing problems with the smart healthcare system and how these problems can be solved. This study can provide essential information about the role of smart healthcare and IoT in maintaining behavior of patent. Various biomarkers are maintained properly with the help of these technologies. This study can provide effective information about importance of smart health system. This smart healthcare is conducted with the involvement of proper architecture. This is treated as effective energy efficiency architecture. Artificial intelligence is used increasingly in healthcare to maintain diagnosis and other important factors of healthcare. This application is also used to maintain patient engagement, which is also included in this study. Major hardware components are also included in this technology such as CO sensor and CO2 sensor.

When Non-Compliance Carries the Day: Evaluating the Effectiveness of an Employment Program for the Severely Mentally Ill

Background: Mental disease is increasing worldwide and people who suffer from it show lower employment rates and lower earnings. Various approaches have been tried to increase the employment rate of people with mental disease. In the US, empirical studies show that individual placement and support(IPS)—a rapid transition to the job market, with some external assistance—is effective in increasing the employment rate of the mentally ill. Europe lacks such evidence. Purpose: The study assesses the impact of an IPS-like program undertaken in Italy on the employment rate of people with severe mental illness. Methods: The analysis is based on a RCT that tests whether offering people with severe mental illness the support of a “job coach” increases their chances of being employed. Moreover, using a battery of tests—one of which is made available by the RCT itself—we show that the large non-compliance with the protocol showed by the RCT is ignorable. This motivates estimating the impact of carrying out a traineeship during the experimental period on employment using non-experimental methods. Results and Conclusions: The study finds that the availability of a coach boosts the patients’ chances of finding a traineeship during the experimental period; moreover, undertaking a traineeship almost doubles the likelihood of being at work one year later. JEL CODES: J78, J48, J38

Based on UPLC-Q-TOF-MS/MS, Systematic Network Pharmacology, and Molecular Docking to Explore the Potential Mechanism of Fructus Aurantii for Major Depression Disorder

Background. Major Depression Disorder (MDD) is a common mental disease that has become one of the world’s major medical diseases. Currently, the Fructus Aurantii (FA) has been widely used to treat depression. However, the active substance ingredients and potential mechanisms of the shell antidepression have not yet been clarified. Method. First, we used ultraperformance liquid chromatography-quadrupole/time-of-flight tandem mass (UPLC-QTOF-MS/MS) technology to identify the chemical composition of the FA. Then, it is predicted for active ingredients, pharmaceutical disease target screening by DiscoveryStudio 2016 (DS), Metascape, and other databases, PPI network diagram, and FC core pathway. Finally, the system network pharmacology results are verified by molecular contact verification. Results. Forty-six compounds in FA were identified, and twelve active ingredients were determined. Various database information, PPI network analysis of 41 intersections, and 20 core targets including DRD2, MTOR, FASP3, and PIK3P1 were integrated. Finally, the MDD treatment is indicated by molecular docking, and the most relevant potential signal pathway is the PI3K-Akt signaling pathway.

Common and disorder-specific upregulation of the inflammatory markers TRAIL and CCL20 in depression and schizophrenia

Schizophrenia (SZ) and major depressive disorder (MDD) are severe mental disorders, which have been associated with alterations of the peripheral inflammatory network. However, studies for both disorders have not been fully consistent and have focused on few canonical markers with high relevance to the innate immune system, while the role of the adaptive immune system is studied less. Furthermore, it is unclear to what extent inflammatory abnormalities are diagnosis-specific or transdiagnostic. The purpose of this study was to investigate 75 peripheral inflammatory markers including the acute phase protein high-sensitivity C-reactive protein (hsCRP) in patients with MDD (n = 37), SZ (n = 42) and healthy controls (HC) (n = 17), while considering possible confounders and correcting rigorously for multiple testing in group comparisons. We identified C–C chemokine ligand 20 (CCL20) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) as the inflammatory markers with significant group differences after controlling for multiple comparisons and adjusting for BMI, sex and smoking as confounders. TRAIL was elevated in both MDD and SZ compared to HC. CCL20 was specifically increased in SZ compared to MDD and HC. There were no significant group differences in hsCRP after correcting for multiple testing. Finally, we observed no significant correlations among CCL20, TRAIL and CRP. TRAIL is a transdiagnostic marker for SZ and MDD, with both markers being independent from CRP and body mass index (BMI). CCL20 may be a novel and specific biomarker of schizophrenia, but an influence of antipsychotic medication cannot be excluded. Identifying novel markers in mental disease bears the potential for future research towards novel treatment strategies by modifying inflammation-related processes.

Fear of COVID-19 Among Elderly Patients with a Chronic Physical or Mental Disease

Older age renders individuals vulnerable during public emergency crises. Considering that older adults are a highly heterogeneous and continuously growing demographic subgroup, this study aimed to assess the mental health impact of COVID-19 on two groups of older patients: a group of chronic physical disease and a group of chronic mental disease. A total of 102 patients completed the Fear of COVID-19 Scale, the Generalized Anxiety Disorder scale, the Brief Patient Health Questionnaire (PHQ-9) and several questions regarding demographic characteristics. Suicidality was assessed by the 9th item of the PHQ-9.According to the results, older chronic disease patients showed higher levels of fear, whereas anxiety and depressive symptoms were present mainly in the group of older psychiatric patients. Suicidality was reported from a subtotal of 25.4% that was composed of 7.8% chronic disease patients and 17.6% psychiatric patients. Chronic physical disease and higher anxiety predicted more severe COVID-19-related fear.

Transformations in Plasma Metabolic Profiles of Patients with Major Depression During Treatment: A Pilot Metabolomics Study

Background Major depression disorder (MDD) is a mental disease that seriously endangers human physical and mental health. The purpose of present study is to detect the differences of plasma metabolic profiles between MDD patients and healthy controls. Moreover, the hospitalization process of MDD patients was followed to explore the reversal of metabolic abnormalities in MDD patients by conventional treatment in the form of self-control.Methods Ultra-Performance Liquid Chromatography- Mass Spectrometry (UPLC-MS) was used to detect the metabolic profiles in 47 plasma samples from 12 controls and 12 MDD patients. Multivariate statistical analysis and K-means clustering were operated to search for significantly different metabolites (SDMs) between pair-comparison groups and specific metabolites (SMs) with ideal variation trend in relative content. Finally, the metabolites were integrated into Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to preliminarily explore the potential mechanism of MDD disrupting the metabolic process.Results There were significant differences in plasma metabolic profiles between healthy controls and MDD patients. A total of 14 SDMs between untreated MDD patients and healthy controls were classified into the top ten KEGG pathways enrichment, among which the relative contents of 4 SMs, 9-HPODE, imidazoleacetic acid, thromboxane B2 (TXB2), and arachidonic acid (AA) showed a regular variation trend after MDD patients’ treatment. A new metabolite-pathway network containing 4 SMs and 8 pathways was accessed after further integration analysis. The sample size calculation showed that a verification set of 84-135 subjects (containing healthy controls and MDD paients) was desired to confirm the results of this study.Conclusion The results indicate that the transition in metabolic pathways during the occurrence and treatment process of MDD is mainly dominated by transformations in lipid metabolism and its relevant signaling pathway system. Additionally, histidine metabolism is also engaged. Subsequent large-scale validation study is acquired to evaluate whether the selected metabolites have the potential to diagnose and access the therapeutic effect of MDD, and to explore the probable mechanism of MDD in combination with other technologies.