Global, regional and national burdens of depression in adolescents and young adults aged 10-24 years, from 1990 to 2019: findings from the 2019 Global Burden of Disease study.

BACKGROUND: Depression is a significant mental health concern affecting the overall well-being of adolescents and young adults. Recently, the prevalence of depression has increased among young people. Nonetheless, there is little research delving into the longitudinal epidemiology of adolescent depression over time. AIMS: To investigate the longitudinal epidemiology of depression among adolescents and young adults aged 10-24 years. METHOD: Our research focused on young people (aged 10-24 years) with depression, using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. We explored the age-standardised prevalence, incidence and disability-adjusted life-years (DALYs) of depression in different groups, including various regions, ages, genders and sociodemographic indices, from 1990 to 2019. RESULTS: The prevalence, incidence and DALYs of depression in young people increased globally between 1990 and 2019. Regionally, higher-income regions like High-Income North America and Australasia recorded rising age-standardised prevalence and incidence rates, whereas low- or middle-income regions mostly saw reductions. Nationally, countries such as Greenland, the USA and Palestine reported the highest age-standardised prevalence and incidence rates in 2019, whereas Qatar witnessed the largest growth over time. The burden disproportionately affected females across age groups and world regions. The most prominent age effect on incidence and prevalence rates was in those aged 20-24 years. The depression burden showed an unfavourable trend in younger cohorts born after 1980, with females reporting a higher cohort risk than males. CONCLUSIONS: Between 1990 and 2019, the general pattern of depression among adolescents varied according to age, gender, time period and generational cohort, across regions and nations.

Burden of depression in adolescents in the Western Pacific Region from 1990 to 2019: An age-period-cohort analysis of the Global Burden of Disease study.

BACKGROUND: Depression is a highly prevalent and disabling mental health condition among adolescents. The epidemiology of depression in adolescents has been changing over time, reflecting changes in risk factors as well as disease concepts and diagnosis. However, few studies have characterized the longitudinal epidemiology of depression in adolescents. Understanding trends of disease burden provides key insights to improve resource allocation and design targeted interventions for this vulnerable population. The Western Pacific Region (WPR) is home to over 1.3 billion people with tremendous diversity in culture and socioeconomic development. The epidemiology of adolescent depression in WPR remains largely unknown. In this study, we aimed to estimate trends of disease burden attributable to depressive disorders among adolescents aged 10-24 years in WPR countries between 1990 and 2019, and to investigate period and cohort effects using the Global Burden of Disease (GBD) study database. METHODS: The study utilized data from the Global Burden of Disease, Injuries, and Risk Factors Study 2019, concentrating on adolescents aged 10 to 24 years with depression. We conducted an in-depth analysis of depression, including its age-standardized prevalence, incidence, and Disability-Adjusted Life Years (DALYs), across diverse demographics such as regions, ages, genders, and socio-demographic indexes, spanning from 1990 to 2019. RESULTS: The analysis found decreasing trends in the prevalence, incidence, and DALYs of adolescent depression in the WPR between 1990-2019, although some countries like Australia and Malaysia showed increases. Specifically, the prevalence of adolescent depression in the region decreased from 9,347,861.6 cases in 1990 to 5,551,341.1 cases in 2019. The incidence rate declined from 2,508.6 per 100,000 adolescents in 1990 to 1,947.9 per 100,000 in 2019. DALYs decreased from 371.9 per 100,000 in 1990 to ASR 299.7 per 100,000 in 2019. CONCLUSION: This study found an overall decreasing trend in adolescent depression burden in the Western Pacific Region between 1990 and 2019, with heterogeneity across countries. For 30 years, the 20-24 age group accounted for the majority of depression among adolescents Widening inequality in depression burden requires policy attention. Further analysis of risk factors contributing to epidemiological trends is warranted to inform prevention strategies targeting adolescent mental health in the region.

The hTERT-p50 homodimer inhibits PLEKHA7 expression to promote gastric cancer invasion and metastasis.

Although accumulating evidence has highlighted the molecular mechanisms by which hTERT promotes tumour cell invasion and metastasis, the molecular mechanisms of the properties enabling hTERT to contribute to invasion and metastasis have not been clearly illustrated. Here, we report that hTERT promotes gastric cancer invasion and metastasis by recruiting p50 to synergistically inhibit PLEKHA7 expression. We observed that the expression of PLEKHA7 in gastric cancer was significantly negatively associated with the TNM stage and lymphatic metastasis and that decreased PLEKHA7 expression dramatically increased invasion and metastasis in gastric cancer cells. Further mechanistic research showed that hTERT directly regulates PLEKHA7 expression by binding p50 and recruiting the hTERT/p50 complex to the PLEKHA7 promoter. Increased hTERT dramatically decreased PLEKHA7 expression and promoted invasion and metastasis in gastric cancer cells. The hTERT-mediated invasion/metastasis properties at least partially depended on PLEKHA7. Our work uncovers a novel molecular mechanism underlying invasion/metastasis in gastric cancer orchestrated by hTERT and p50.

ALB, HP, OAF and RBP4 as novel protein biomarkers for identifying cured patients with pulmonary tuberculosis by DIA.

BACKGROUND: Pulmonary tuberculosis (TB) is a serious infectious disease that lacks robust blood-based biomarkers to identify cured TB. Some discharged patients are not fully cured and may relapse or even develop multidrug-resistant TB. This study is committed to finding proteomic-based plasma biomarkers to support establishing laboratory standards for clinical TB cure. METHODS: Data-independent acquisition (DIA) was used to obtain the plasma protein expression profiles of TB patients at different treatment stages compared with healthy controls. Multivariate statistical methods and bioinformatics were used to analyze the data. RESULTS: Bioinformatic analysis suggests coagulation dysfunction and vitamin and lipid metabolism disturbances in TB. Albumin (ALB), haptoglobin (HP), out at first protein homolog (OAF), and retinol-binding protein 4 (RBP4) can be used to establish a diagnostic model for the efficacy evaluation of TB with an area under the curve of 0.963, which could effectively distinguish untreated TB patients from cured patients. CONCLUSIONS: Our research demonstrated that ALB, HP, OAF and RBP4 can be potential biomarkers for evaluating the efficacy of TB. These findings may provide experimental data for establishing the laboratory indicators of clinical TB cure and providing clinicians with new targets for exploring the underlying mechanisms of TB pathogenesis.

Metabolite profile of COVID-19 revealed by UPLC-MS/MS-based widely targeted metabolomics.

The metabolic characteristics of COVID-19 disease are still largely unknown. Here, 44 patients with COVID-19 (31 mild COVID-19 patients and 13 severe COVID-19 patients), 42 healthy controls (HC), and 42 patients with community-acquired pneumonia (CAP), were involved in the study to assess their serum metabolomic profiles. We used widely targeted metabolomics based on an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The differentially expressed metabolites in the plasma of mild and severe COVID-19 patients, CAP patients, and HC subjects were screened, and the main metabolic pathways involved were analyzed. Multiple mature machine learning algorithms confirmed that the metabolites performed excellently in discriminating COVID-19 groups from CAP and HC subjects, with an area under the curve (AUC) of 1. The specific dysregulation of AMP, dGMP, sn-glycero-3-phosphocholine, and carnitine was observed in the severe COVID-19 group. Moreover, random forest analysis suggested that these metabolites could discriminate between severe COVID-19 patients and mild COVID-19 patients, with an AUC of 0.921. This study may broaden our understanding of pathophysiological mechanisms of COVID-19 and may offer an experimental basis for developing novel treatment strategies against it.

A hybrid with distributed pooling blockchain protocol for image storage.

As a distributed storage scheme, the blockchain network lacks storage space has been a long-term concern in this field. At present, there are relatively few research on algorithms and protocols to reduce the storage requirement of blockchain, and the existing research has limitations such as sacrificing fault tolerance performance and raising time cost, which need to be further improved. Facing the above problems, this paper proposes a protocol based on Distributed Image Storage Protocol (DISP), which can effectively improve blockchain storage space and reduces computational costs in the help of InterPlanetary File System (IPFS). In order to prove the feasibility of the protocol, we make full use of IPFS and distributed database to design a simulation experiment for blockchain. Through distributed pooling (DP) algorithm in this protocol, we can divide image evidence into recognizable several small files and stored in several nodes. And these files can be restored to lossless original documents again by inverse distributed pooling (IDP) algorithm after authorization. These advantages in performance create conditions for large scale industrial and commercial applications.

Pyridoxal phosphate, pyridoxamine phosphate, and folic acid based on ceRNA regulatory network as potential biomarkers for the diagnosis of pulmonary tuberculosis.

BACKGROUND: Pulmonary tuberculosis (TB) is a serious disease burden worldwide, and its effective early diagnosis is still facing challenges. Knowledge, acquired from multi-omics integration analysis about the association between different types of differentially expressed molecules in the plasma of TB patients and the disease traits, is anticipated to improve the accuracy of TB diagnosis through the "integrative pattern". METHODS: In this study, the lncRNA-miRNA-mRNA interaction network was constructed based on the competing endogenous RNA (ceRNA) hypothesis by integrating our previous data sets of lncRNA, mRNA, miRNA, and metabolites. Moreover, the key regulatory axis was established by co-expression analysis and verified at the level of metabolites. RESULTS: A ceRNA regulatory network consisting of 23 lncRNAs, 10 miRNAs, and 113 mRNAs was constructed. The analysis results suggested that lncRNA (OSBPL10-AS1), miRNA (has-miR-485-5p), and mRNA (SLC23A2) might be involved in the regulation of vitamin metabolism in patients with TB. Metabolite analysis showed that compared with the normal control group, TB patients had abnormal vitamin metabolism, and the expression levels of pyridoxal phosphate, pyridoxamine phosphate, and folic acid were significantly different between the two groups (p < 0.05). CONCLUSION: Integrated multi-omics analysis showed that vitamin metabolism disorder may be one of the pathological characteristic of TB. OSBPL10-AS1, hsa-miR-485-5p, SLC23A2, pyridoxal phosphate, pyridoxamine phosphate, and folic acid may collectively constitute the "integrative pattern" of multiple biomarkers, which may provide an accurate diagnosis of TB.

Expression profiling and function analysis identified new microRNAs regulating cumulus expansion and apoptosis in cumulus cells.

Although microRNAs (miRNAs) expressed in cumulus cells (CCs) may be used to select competent oocytes/embryos, only a limited number of such miRNAs has been reported. To identify more miRNAs that regulate cumulus expansion (CE) and CC apoptosis, we first established that mouse cumulus-oocyte complexes (COCs) cultured in expansion-supporting medium supported full CE while undergoing mild apoptosis, whereas mouse oocytectomized COCs (OOXs) cultured in apoptosis-triggering medium underwent severe apoptosis while supporting no CE. RNA- and miRNA-sequencing and bioinformatics using CCs from these cultured COCs/OOXs identified candidate apoptosis- and/or CE-regulating miRNAs. Transfection of COCs/OOXs with miRNA mimic or inhibitor validated that miR-212-5p and 149-5p promoted CE by facilitating Has2 expression; miR-31-5p and 27a-3p promoted CE by increasing both Has2 and Ptx3 expression; and miR-351-5p and 503-5p inhibited CE by suppressing Ptx3 expression. Furthermore, miR-212-5p, 149-5p and Nov798 inhibited CC apoptosis, involving both Bcl2/Bax and Fas signaling. Analysis using in vivo matured COCs further verified the above apoptosis- and/or CE-regulating miRNAs, except for miR-149-5p. In conclusion, this study identified and validated new CE- and apoptosis-regulating miRNAs in CCs, which could be used as biomarkers to select competent oocytes/embryos and for elucidating how the oocyte-derived factors regulate CE and CC apoptosis.

Performance of Passive Muscle Stiffness in Diagnosis and Assessment of Disease Progression in Duchenne Muscular Dystrophy.

The aim of this study was to evaluate the performance of passive muscle stiffness in diagnosing and assessing disease progression in Duchenne muscular dystrophy (DMD). Boys with DMD and age-matched controls were recruited. Shear wave elastography (SWE) videos were collected by performing dynamic stretching of the gastrocnemius medius (GM). At ankle angles from plantar flexion (PF) 30° to dorsiflexion (DF) 20°, the shear modulus of the GM was measured for each 10° of ankle movement. Shear modulus at each ankle angle was compared between the DMD and control group. Correlation between passive muscle stiffness and motor function grading was also analyzed. A total of 26 patients with DMD and 20 healthy boys were enrolled. At multiple stretch levels, passive muscle stiffness of the GM was significantly higher in patients with DMD than in those in the control group (all p values <0.05). The shear modulus of GM at an ankle angle of DF 10° had the largest area under the receiver operating characteristic curve in differentiating DMD patients from normal subjects (AUC = 0.902, 95% confidence interval: 0.814-0.990). Motor function grading was a significant determinant of passive muscle stiffness at an ankle angle of DF 10° (B = 21.409, t = 3.372, p = 0.003). Passive muscle stiffness may potentially serve as a useful non-invasive tool to monitor disease progression in DMD patients.

Development of gestational diabetes mellitus in women with periodontitis in early pregnancy: A population-based clinical study.

AIM: This study aimed to determine whether periodontitis in early pregnancy and periodontal therapy during gestation affect the incidence of gestational diabetes mellitus (GDM) through a population-based clinical study. MATERIALS AND METHODS: Subjects without periodontitis at 1-4 weeks of gestation who met our inclusion criteria were enrolled in the non-periodontitis group. Periodontitis patients who agreed or refused to receive periodontal therapy during pregnancy were separately enrolled in the periodontitis treated or untreated group. At 12-16 weeks of gestation, gingival crevicular fluid (GCF) and venous blood were collected for analyses of bacterial species and serum inflammatory mediators, respectively. At 24-28 weeks of gestation, GDM patients were identified by oral glucose tolerance tests. The association tests were performed using Chi-squared statistics and regression analyses. RESULTS: The complete data of 3523 pregnant women were recorded during the study period. GDM incidence among the untreated periodontitis participants (84/749, 11.21%) was significantly higher than that among the non-periodontitis participants (108/2255, 4.79%) (p < .05), and periodontal treatment during gestation reduced the incidence from 11.21% (untreated group) to 7.32% (38/519, treated group) (p < .05). Based on multiple logistic regression analyses, it was found that periodontitis in early pregnancy was associated with GDM, and three-step regression analyses showed that Porphyromonas gingivalis (P. gingivalis) and the serum TNF-α and IL-8 levels played a role in the association between untreated periodontitis and GDM. Furthermore, Pearson's correlation test indicated that the existence of P. gingivalis in GCF was positively correlated with high serum levels of these two inflammatory mediators. CONCLUSIONS: This study establishes a connection between periodontitis in early pregnancy and GDM and demonstrates that the presence of P. gingivalis is associated with high levels of inflammatory mediators in serum, and thereby may contribute to the development of GDM. In-depth mechanistic studies are needed to further support these findings.

Screening and identification of potential novel lipid biomarkers for non-small cell lung cancer using ultra-high performance liquid chromatography tandem mass spectrometry.

Lung cancer is characterized by a high incidence rate and low survival rate. It is important to achieve early diagnosis of the disease. We applied ultra-high performance liquid chromatography tandem mass spectrometry to screen plasma lipid spectrum in non-small cell lung cancer (NSCLC) patients, healthy controls (HC), and community-acquired pneumonia (CAP) patients. Modeling employing orthogonal partial least squares-discriminant analysis combined with t-test was used to screen the differential lipids. Logistic regression analysis was used to establish the diagnostic model, while the accuracy was verified by 10-fold cross-validation. The results showed that the abnormal metabolism of lipid in NSCLC mainly comprised fatty acid metabolism, phospholipid metabolism, and glyceride metabolism. Four potential biomarkers, including LPC (14:0/0:0), LPI (14:1/0:0), DG (14:0/18:2/0:0), and LPC (16:1/0:0), were fitted by the receiver operating characteristic curve model with the area under curve (AUC) value of 0.856, and the specificity and sensitivity were 87.0 and 78.0%, respectively. The results of cross validation showed that the AUC value of the model was 0.812, the sensitivity was 72.9%, and the specificity was 82.6%. The positive rate of four potential lipid biomarkers in this study (>60.0%) was higher than that of existing tumor biomarkers in the clinical application. We investigated the plasma lipid profile of NSCLC patients and identified lipid biomarkers with potential diagnostic values. From the lipidomics perspective, our study may lay a foundation for the biomarker-based early diagnosis of lung cancer.

Screening and identification of potential protein biomarkers for the early diagnosis of acute myocardial infarction.

BACKGROUND: Acute myocardial infarction (AMI) is the most serious type of heart disease. Clinically, there is an urgent need to discover diagnostic biomarkers for the early diagnosis of AMI. METHODS: Serum proteomic profiles in AMI patients, healthy controls, and stable angina pectoris (SAP) patients were explored and compared by iTRAQ-2DLC-MS/MS. The clinical data of AMI patients were also analyzed. Differentially expressed proteins were validated by enzyme linked immunosorbent assay (ELISA), and diagnostic models were constructed. RESULTS: A total of 39 differentially expressed proteins were identified in AMI patients. The results showed that the serum levels of apolipoprotein E (APOE) in AMI patients were notably higher than those in the healthy controls (P=0.0172). The serum levels of aspartate aminotransferase (AATC) in AMI patients were markedly higher than those in the healthy controls and SAP patients (P<0.0001 and P<0.0001, respectively). The serum levels of fibronectin (FINC) in SAP patients were significantly higher than those in the healthy controls and AMI patients (P=0.0043 and P=0.0044, respectively). Clinical data analysis showed a considerable difference in blood glucose levels, troponin I (TNI), and creatine kinase (CK) in AMI patients compared with SAP patients and healthy controls. A diagnostic model consisting of AATC and clinical indicators [lactate dehydrogenase (LDH) and CK] was established to distinguish between AMI patients and healthy controls, with an area under the curve (AUC) value of 0.993 sensitivity and specificity of 96.2% and 96.3%, respectively. A diagnostic model consisting of AATC and CK was established to distinguish between AMI patients and SAP patients, with an AUC value of 0.975 and a sensitivity and specificity of 85.2% and 79.30%, respectively. CONCLUSIONS: In this study, differentially expressed proteins in AMI patients were combined with clinical indexes, LDH and CK, and two diagnostic models were constructed. This study may provide meaningful data for the early diagnosis of AMI.

Identifying Prognostic Significance of RCL1 and Four-Gene Signature as Novel Potential Biomarkers in HCC Patients.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly malignant disease, and it is characterized by rapid progression and low five-year survival rate. At present, there are no effective methods for monitoring the treatment and prognosis of HCC. METHODS: The transcriptome and gene expression profiles of HCC were obtained from the Cancer Genome Atlas (TCGA) program, International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. The random forest method was applied to construct a four-gene prognostic model based on RNA terminal phosphate cyclase like 1 (RCL1) expression. The Kaplan-Meier method was performed to evaluate the prognostic value of RCL1, long noncoding RNAs (AC079061, AL354872, and LINC01093), and four-gene signature (SPP1, MYBL2, TRNP1, and FTCD). We examined the relationship between RCL1 expression and immune cells infiltration, tumor mutation burden (TMB), and microsatellite instability (MSI). RESULTS: The results of multiple databases indicated that the aberrant expression of RCL1 was associated with clinical outcome, immune cells infiltration, TMB, and MSI in HCC patients. Meanwhile, we found that long noncoding RNAs (AC079061, AL354872, and LINC01093) and RCL1 were significantly coexpressed in HCC patients. We also confirmed that the four-gene signature was an independent prognostic factor for HCC patients. Ferroptosis potential index, immune checkpoint molecules, and clinical feature were found to have obvious correlations with risk score. The area under the receiver operating characteristic curve values for the model were 0.7-0.8 in the training set and the validation set, suggesting high robustness of the four-gene signature. We then built a nomogram for facilitating the use in clinical practice. CONCLUSION: Our study demonstrated that RCL1 and a novel four-gene signature can be used as prognostic biomarkers for predicting clinical outcome in HCC patients; and this model may assist in individualized treatment monitoring of HCC patients in clinical practice.

Postpartum Depression: Current Status and Possible Identification Using Biomarkers.

Postpartum depression (PPD) is a serious health issue that can affect about 15% of the female population within after giving birth. It often conveys significant negative consequences to the offsprings. The symptoms and risk factors are somewhat similar to those found in non-postpartum depression. The main difference resides in the fact that PPD is triggered by postpartum specific factors, including especially biological changes in the hormone levels. Patients are usually diagnosed using a questionnaire onsite or in a clinic. Treatment of PPD often involves psychotherapy and antidepressant medications. In recent years, there have been more researches on the identification of biological markers for PPD. In this review, we will focus on the current research status of PPD, with an emphasis on the recent progress made on the identification of PPD biomarkers.

Black phosphorous nanosheet: A novel immune-potentiating nanoadjuvant for near-infrared-improved immunotherapy.

Intrinsic immune behaviors of nanomaterials and immune systems promote research on their adjuvanticity and the design of next generation nanovaccine-based immunotherapies. Herein, we report a promising multifunctional nanoadjuvant by exploring the immune-potentiating effects of black phosphorus nanosheets (BPs) in vitro and in vivo. The facile coating of BPs with phenylalanine-lysine-phenylalanine (FKF) tripeptide-modified antigen epitopes (FKF-OVAp@BP) enables the generation of a minimalized nanovaccine by integrating high loading capacity, efficient drug delivery, comprehensive dendritic cell (DC) activation, and biocompatibility for cancer immunotherapy. Systemic immunization elicits potent antitumor cellular immunity and significantly augments checkpoint blockade (CPB) against melanoma in a mouse model. Furthermore, near-infrared (NIR) photothermal effects of BPs create an immune-favorable microenvironment for improved local immunization. This study offers new insight into the integration of immunoactivity and photothermal effects for enhanced cancer immunotherapy by using a nanoadjuvant and thus potentially advances the design and application of multifunctional adjuvant materials for cancer nanotreatment.

Cyano Derivatives of 7-Aminoquinoline That Are Highly Emissive in Water: Potential for Sensing Applications.

6-Cyano-7-aminoquinoline (6CN-7AQ) and 3-cyano-7-aminoquinoline (3CN-7AQ) were synthesized and found to exhibit intense emission with quantum yield as high as 63 % and 85 %, respectively, in water. Conversely, their derivatives 6-cyano-7-azidoquinoline (6CN-7N3 Q) and 3-cyano-7-azidoquinoline (3CN-7N3 Q) show virtually no emission, which makes them suitable to be used as recognition agents in azide reactions based on fluorescence recovery. Moreover, conjugation of 6CN-7AQ with a hydrophobic biomembrane-penetration peptide PFVYLI renders a nearly non-emissive 6CN-7AQ-PFVYLI composite, which can be digested by proteinase K, recovering the highly emissive 6CN-7AQ with ∼200-fold enhancement. The result provides an effective early confirmation for RT-qPCR in viral detection.

Novel therapeutic evaluation biomarkers of lipid metabolism targets in uncomplicated pulmonary tuberculosis patients.

Currently, the management of pulmonary tuberculosis (TB) lacks potent medications and accurate efficacy evaluation biomarkers. In view of the fact that the host lipids are the important energy source of Mycobacterium tuberculosis (Mtb), UPLC-MS/MS based on lipid metabolism was used to monitor the plasma lipid spectrum of TB patients from the initial diagnosis to cured. The analysis showed that TB patients presented aberrant metabolism of phospholipids, glycerides, and sphingolipids. Upon the treatment, the abnormal expression of Cer (d18:1/24:0), CerP (d18:1/20:3), LPE (0:0/22:0), LPA (0:0/16:0), and LPA (0:0/18:0) in TB patients were gradually normalized, indicating that the intervention of lipid metabolism could block energy metabolism and inhibit the cell wall synthesis of Mtb. Furthermore, the increase in ceramide (Cer) levels could promote autophagosome-lysosome fusion. LPA (0:0/16:0) and LPA (0:0/18:0) had a great potential in the early diagnosis (both sensitivity and specificity were 100%) and efficacy evaluation (both sensitivity and specificity were 100%) of TB, indicating that the above lipid metabolites could be used as potential biomarkers for TB.