Single-cell transcriptome analyses reveal signals to activate dormant neural stem cells.

The scarcity of tissue-specific stem cells and the complexity of their surrounding environment have made molecular characterization of these cells particularly challenging. Through single-cell transcriptome and weighted gene co-expression network analysis (WGCNA), we uncovered molecular properties of CD133(+)/GFAP(-) ependymal (E) cells in the adult mouse forebrain neurogenic zone. Surprisingly, prominent hub genes of the gene network unique to ependymal CD133(+)/GFAP(-) quiescent cells were enriched for immune-responsive genes, as well as genes encoding receptors for angiogenic factors. Administration of vascular endothelial growth factor (VEGF) activated CD133(+) ependymal neural stem cells (NSCs), lining not only the lateral but also the fourth ventricles and, together with basic fibroblast growth factor (bFGF), elicited subsequent neural lineage differentiation and migration. This study revealed the existence of dormant ependymal NSCs throughout the ventricular surface of the CNS, as well as signals abundant after injury for their activation.

Exosome detection via the ultrafast-isolation system: EXODUS.

Exosomes have shown great potential in disease diagnostics and therapeutics. However, current isolation approaches are burdensome and suffer from low speed, yield and purity, limiting basic research and clinical applications. Here, we describe an efficient exosome detection method via the ultrafast-isolation system (EXODUS) that allows automated label-free purification of exosomes from varied biofluids. We obtained the ultra-efficient purification of exosomes by negative pressure oscillation and double coupled harmonic oscillator-enabled membrane vibration. Our two coupled oscillators generate dual-frequency transverse waves on the membranes, enabling EXODUS to outperform other isolation techniques in speed, purity and yield. We demonstrated EXODUS by purifying exosomes from urine samples of 113 patients and validated the practical relevance in exosomal RNA profiling with the high-resolution capability and high-throughput analysis.

Ultra-high-speed four-dimensional hyperspectral imaging.

We propose, to the best of our knowledge, a novel deep learning-enabled four-dimensional spectral imaging system composed of a reflective coded aperture snapshot spectral imaging system and a panchromatic camera. The system simultaneously captures a compressively coded hyperspectral measurement and a panchromatic measurement. The hyperspectral data cube is recovered by the U-net-3D network. The depth information of the scene is then acquired by estimating a disparity map between the hyperspectral data cube and the panchromatic measurement through stereo matching. This disparity map is used to align the hyperspectral data cube and the panchromatic measurement. A designed fusion network is used to improve the spatial reconstruction of the hyperspectral data cube by fusing aligned panchromatic measurements. The hardware prototype of the proposed system demonstrates high-speed four-dimensional spectral imaging that allows for simultaneously acquiring depth and spectral images with an 8 nm spectral resolution between 450 and 700 nm, 2.5 mm depth accuracy, and a 1.83 s reconstruction time.

Recent advances in N-glycan biomarker discovery among human diseases.

N-glycans play important roles in a variety of biological processes. In recent years, analytical technologies with high resolution and sensitivity have advanced exponentially, enabling analysts to investigate N-glycomic changes in different states. Specific glycan and glycosylation signatures have been identified in multiple diseases, including cancer, autoimmune diseases, nervous system disorders, and metabolic and cardiovascular diseases. These glycans demonstrate comparable or superior indicating capability in disease diagnosis and prognosis over routine biomarkers. Moreover, synchronous glycan alterations concurrent with disease initiation and progression provide novel insights into pathogenetic mechanisms and potential treatment targets. This review elucidates the biological significance of N-glycans, compares the existing glycomic technologies, and delineates the clinical performance of N-glycans across a range of diseases.

The genetic source tracking of human urinary exosomes.

The genetic origins of nanoscale extracellular vesicles in our body fluids remains unclear. Here, we perform a tracking analysis of urinary exosomes via RNA sequencing, revealing that urine exosomes mostly express tissue-specific genes for the bladder and have close cell-genetic relationships to the endothelial cell, basal cell, monocyte, and dendritic cell. Tracking the differentially expressed genes of cancers and corresponding enrichment analysis show urine exosomes are intensively involved in immune activities, indicating that they may be harnessed as reliable biomarkers of noninvasive liquid biopsy in cancer genomic diagnostics and precision medicine.

Neurotrophic signaling deficiency exacerbates environmental risks for Alzheimer's disease pathogenesis.

The molecular mechanism of Alzheimer's disease (AD) pathogenesis remains obscure. Life and/or environmental events, such as traumatic brain injury (TBI), high-fat diet (HFD), and chronic cerebral hypoperfusion (CCH), are proposed exogenous risk factors for AD. BDNF/TrkB, an essential neurotrophic signaling for synaptic plasticity and neuronal survival, are reduced in the aged brain and in AD patients. Here, we show that environmental factors activate C/EBPß, an inflammatory transcription factor, which subsequently up-regulates δ-secretase that simultaneously cleaves both APP and Tau, triggering AD neuropathological changes. These adverse effects are additively exacerbated in BDNF+/- or TrkB+/- mice. Strikingly, TBI provokes both senile plaque deposit and neurofibrillary tangles (NFT) formation in TrkB+/- mice, associated with augmented neuroinflammation and extensive neuronal loss, leading to cognitive deficits. Depletion of C/EBPß inhibits TBI-induced AD-like pathologies in these mice. Remarkably, amyloid aggregates and NFT are tempospatially distributed in TrkB+/- mice brains after TBI, providing insight into their spreading in the progression of AD-like pathologies. Hence, our study revealed the roles of exogenous (TBI, HFD, and CCH) and endogenous (TrkB/BDNF) risk factors in the onset of AD-associated pathologies.

Comprehensive serum N-glycan profiling identifies a biomarker panel for early diagnosis of non-small-cell lung cancer.

Aberrant serum N-glycan profiles have been observed in multiple cancers including non-small-cell lung cancer (NSCLC), yet the potential of N-glycans in the early diagnosis of NSCLC remains to be determined. In this study, serum N-glycan profiles of 275 NSCLC patients and 309 healthy controls were characterized by MALDI-TOF-MS. The levels of serum N-glycans and N-glycosylation patterns were compared between NSCLC and control groups. In addition, a panel of N-glycan biomarkers for NSCLC diagnosis was established and validated using machine learning algorithms. As a result, a total of 54 N-glycan structures were identified in human serum. Compared with healthy controls, 29 serum N-glycans were increased or decreased in NSCLC patients. N-glycan abundance in different histological types or clinical stages of NSCLC presented differentiated changes. Furthermore, an optimal biomarker panel of eight N-glycans was constructed based on logistic regression, with an AUC of 0.86 in the validation set. Notably, this model also showed a desirable capacity in distinguishing early-stage patients from healthy controls (AUC = 0.88). In conclusion, our work highlights the abnormal N-glycan profiles in NSCLC and provides supports potential application of N-glycan biomarker panel in clinical NSCLC detection.

Serum vitamin D concentration, vitamin D-related polymorphisms, and colorectal cancer risk.

Serum 25-hydroxyvitamin D (25(OH)D) has been demonstrated to be associated with risk of colorectal cancer (CRC). However, it remains unclear whether this association was modified by vitamin D-related polymorphisms. We evaluated association of serum 25(OH)D concentration with CRC risk among 403 170 participants from UK Biobank Project. Two variants of vitamin D binding protein (VDBP), rs4588 and rs7041, were included to estimate the binding affinity of 25(OH)D to VDBP, and three variants of vitamin D receptor (VDR), rs11568820, rs2228570 and rs1544410, which may influence VDR activity, were also investigated. Multivariable Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). During 4 957 677 person-years of follow-up, 5053 incident CRC cases were documented. Higher serum 25(OH)D concentrations were significantly associated with lower CRC incidence in a dose-response manner, with HR (95% CIs) being 0.94 (0.91-0.97) per 1 SD increment of serum 25(OH)D level (Ptrend < .001). When separated by anatomic site, we observed a significant association between higher 25(OH)D and lower incidence of colon cancer (Ptrend < .001), but not rectal cancer (Ptrend = .880). The inverse associations between 25(OH)D level and CRC risk were demonstrated in almost all individuals carrying different GC or VDR genotypes, except for those with rs1544410 TT or rs4588 TT genotypes. There was no significant interaction between any single variant, or haplotypes of GC or VDR, and 25(OH)D level. Our findings suggest the potential benefits of maintaining adequate vitamin D for CRC prevention, particularly for tumors from colon.

Serum untargeted metabolomics reveal metabolic alteration of non-small cell lung cancer and refine disease detection.

This study was performed to characterize the metabolic alteration of non-small-cell lung cancer (NSCLC) and discover blood-based metabolic biomarkers relevant to lung cancer detection. An untargeted metabolomics-based approach was applied in a case-control study with 193 NSCLC patients and 243 healthy controls. Serum metabolomics were determined by using an ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method. We screened differential metabolites based on univariate and multivariate analysis, followed by identification of the metabolites and related pathways. For NSCLC detection, machine learning was employed to develop and validate the model based on the altered serum metabolite features. The serum metabolic pattern of NSCLC was definitely different from the healthy condition. In total, 278 altered features were found in the serum of NSCLC patients comparing with healthy people. About one-fifth of the abundant differential features were identified successfully. The altered metabolites were enriched in metabolic pathways such as phenylalanine metabolism, linoleic acid metabolism, and biosynthesis of bile acids. We demonstrated a panel of 10 metabolic biomarkers which representing excellent discriminating capability for NSCLC discrimination, with a combined area under the curve (AUC) in the validation set of 0.95 (95% CI: 0.91-0.98). Moreover, this model showed a desirable performance for the detection of NSCLC at an early stage (AUC = 0.95, 95% CI: 0.92-0.97). Our study offers a perspective on NSCLC metabolic alteration. The finding of the biomarkers might shed light on the clinical detection of lung cancer, especially for those cancers in an early stage in Chinese population.

Assessment of 13 essential and toxic trace elements in tumor and peritumoral brain tissues from human glioblastoma.

Trace elements within the brain are important for proper neurological function, but their imbalance has been rarely investigated in glioblastoma. This study enrolled a total of 14 patients with glioblastoma, and the tumor and peritumoral brain tissues were collected while undergoing surgery. The concentrations of Mg, Ca, Cr, Mn, Fe, Co, Cu, Zn, Se, As, Cd, Tl and Pb were determined using a well-evaluated ICP-MS method. The Cu- and Cd-binding proteomes were further analyzed using the anatomic transcriptional atlas from Ivy GAP. Histological evaluation was based on rubeanic acid staining and immunohistochemistry, respectively. The 13 trace element concentrations were obtained, and the highest were Ca, Mn, Fe, Zn and Cu, ranging from a few to dozens of ug/g. Correlation analysis suggested the existence of two intra-correlated clusters: essential metals (Cu-Ca-Zn-Mg) and heavy metals (Pb-As-Cd-Tl-Co-Cr-Mn). Compared to the tumor samples, significantly higher levels of Cu and Cd were observed in the peritumoral region. Further analysis of the Cu- and Cd-binding proteins from the anatomic view suggested that DBH and NOS1 were obviously increased in the leading edge than the central tumor region. Consistent with the above findings, histological evaluation of Cu and DBH further confirmed more copper and DBH expressions in the peritumoral area compared to the tumor core. Trace elements differ in tumor and peritumoral brain zone in glioblastoma, which may associate with tumor angiogenesis.

Nakagami statistics-based photoacoustic spectroscopy used for label-free assessment of bone tissue.

Quick identification of abnormal molecular metabolism of bone tissues is challenging. Photoacoustic (PA) spectroscopy techniques have great potential in molecular imaging. However, most of them are amplitude-dependent and easily affected by the light deposition, especially for bone tissues with high optical scattering. In this Letter, we propose a Nakagami statistics-based PA spectroscopy (NSPS) method for characterizing molecules in bone tissues. We indicate that the NSPS curve can intelligently identify changes in the content of molecules in bone tissues, with a high disturbance-resisting ability. The NSPS has remarkable potential for use in the early and rapid detection of bone diseases.

Scalp ripple rates for rapid epilepsy differentiation and seizure activity assessment: Applicability and influential factors.

OBJECTIVE: We aim to determine whether automatically detected ripple rate (ADRR) of 10-min scalp electroencephalography (EEG) during slow-wave sleep can be a useful tool for rapid epilepsy differentiation and seizure activity assessment, and we analyze the clinical factors that may affect the scalp ripple rates. METHODS: We retrospectively included 336 patients who underwent long-term video-EEG with a sampling rate ≥1000 Hz, and three groups were established based on their final clinical diagnosis (non-epilepsy; non-active epilepsy [epilepsy being seizure-free for at least 1 year]; and active epilepsy [epilepsy with one or more seizures in the past year]). ADRRs between groups were compared and diagnostic thresholds set according to the maximum of Youden index with the receiver-operating characteristic curve. RESULTS: The 336 patients comprised 49 non-epilepsy and 287 epilepsy patients (95 non-active epilepsy and 192 active epilepsy). The median ADRR of the epilepsy group was significantly greater than in the non-epilepsy group, with a diagnostic threshold of 4.25 /min (specificity 89.8%, sensitivity 47.74%, p<.001). Following stratification by age, the area under the curve was greatest in the 0-20 year subgroup, threshold 4.10 /min (specificity 100%, sensitivity 52.47%, p<.001). Regarding distinguishing active epilepsy from non-active epilepsy patients, the area under the curve was also greatest in patients 0-20 years of age, threshold 13.05/min (specificity 98.36%, sensitivity 35.64%, p<.001). Following stratification by epilepsy type, the diagnostic efficiency was best in children with developmental and epileptic encephalopathies/epileptic encephalopathies (DEEs/EEs) (threshold 5.20/min, specificity 100%, sensitivity 100%) and self-limited focal epilepsies (SeLFEs) (threshold 5.45/min, specificity 80%, sensitivity 100%). Multivariate analysis revealed that the influential factors of ADRRs were age, depth of epileptogenic lesion, and seizure frequency. SIGNIFICANCE: ADRR of scalp EEG can be a rapid and specific method to differentiate epilepsy and evaluate seizure activity. This method is especially suitable for young patients.

Dietary fish and omega-3 polyunsaturated fatty acids intake and cancer survival: A systematic review and meta-analysis.

Fish and omega-3 polyunsaturated fatty acids (PUFA) have been suggested to play a role in improving cancer prognosis. However, results from epidemiological studies remain inconsistent. Here we assess the association between dietary fish and/or omega-3 PUFAs intake and cancer prognosis with meta-analysis of observational studies. A systematic search of related publications was performed using PubMed and Web of Science databases. Hazard ratios (HR) and 95% confidence intervals (CI) were extracted and then pooled using a random-effect model. Potential linear and non-linear dose-response relationships were explored using generalized least squares estimation and restricted cubic splines. As a result, 21 cohort studies were included in our analysis. Compared to the lowest category, the highest category of fish intake was associated with a significant lower mortality in patients with ovarian cancer (n = 1, HR = 0.74, 95% CI: 0.57-0.95) and overall cancer (n = 12, HR = 0.87, 95% CI: 0.81-0.94). Marine omega-3 PUFAs intake rather than total omega-3 PUFAs intake showed significant protective effects on survival of overall cancer (n = 8, HR = 0.81, 95% CI: 0.71-0.94), in particular prostate cancer (n = 2, HR = 0.62, 95% CI: 0.46-0.82). Dose-response meta-analysis indicated a nonlinear and a linear relationship between fish intake, as well as marine omega-3 PUFAs intake, and overall cancer survival, respectively. In conclusion, our analysis demonstrated a protective effect of dietary fish and marine omega-3 PUFAs consumption on cancer survival.

Analytical Evaluation and Reference Interval Investigation for Chinese Han Population in Wuhan of CA72-4 Performed on an Architect i2000sr System.

BACKGROUND: Carbohydrate antigen 72-4 (CA72-4) is a mucin-like, tumor-associated glycoprotein. Its elevation in serum has been found to be associated with various carcinomas. The purpose of this study was to evaluate the analytical performance of the Architect chemiluminescent immunoassay CA72-4 on the Architect i2000sr platform and to determine the reference interval (RI) of CA72-4 for the Chinese Han population in the city of Wuhan. METHODS: We evaluated the precision, analytical sensitivity, linearity and interference according to the guidelines of the Clinical Laboratory Standardization Institute. Additionally, the Abbott Architect i2000sr CA72-4 assay was compared to the Roche Cobas E602 CA72-4 assay. A total of 448 healthy individuals were selected to determine the RIs of CA72-4. RESULTS: The assay had an imprecision of 1.38% - 2.63% within runs, 1.41% - 2.73% between runs and a total imprecision of 2.54% - 4.10%. The limit of blank, limit of detection and limit of quantitation concentrations were 0.19 U/mL, 0.21 U/mL, and 0.21 U/mL. Linearity was confirmed across the entire measurable range. Additionally, the carryover was less than 0.065%. Interferences with hemoglobin, conjugated bilirubin and lipemia were acceptable with changes of less than 10%. A correlation coefficient of 0.9450 was determined through the method comparison experiment (95% CI 0.9318 - 0.9557). The RI for serum CA72-4 in the Han population was established as an upper limit, 11.13 U/mL (90% CI 9.39 - 12.99) by using the Abbott Architect i2000sr system. CONCLUSIONS: This study establishes a RI for the Chinese Han population in Wuhan using the Abbott Architect i2000sr CA72-4 assay and demonstrates an analytical performance for clinical use.

Combination therapy with ultrasound and 2D nanomaterials promotes recovery after spinal cord injury via Piezo1 downregulation.

Spinal cord injury (SCI) causes severe neurological dysfunction and currently has no effective treatment. Due to the complex pathophysiological processes associated with SCI and the limited efficacy of single strategies, the need for combined strategies for effective SCI therapy is becoming increasingly apparent. In this study, we evaluated the combined effects of layered double hydroxide-coupled NT3 (MgFe-LDH/NT3) nanoparticles (NPs) and ultrasound (US) both in vitro and in vivo. Combined treatment promoted neural stem cell (NSC) differentiation into neurons and exerted anti-inflammatory effects in vitro. Furthermore, combined therapy promoted behavioural and electrophysiological performance at eight weeks in a completely transected murine thoracic SCI model. Additional RNA sequencing revealed that ultrasonic-induced Piezo1 downregulation is the core mechanism by which combined therapy promotes neurogenesis and inhibits inflammation, and the Piezo1/NF-κB pathways were identified. Hence, the findings of this study demonstrated that the combination of ultrasound and functional NPs may be a promising novel strategy for repairing SCI.

Development of a nomogram model for prediction of new adjacent vertebral compression fractures after vertebroplasty.

BACKGROUND: Vertebroplasty is the main minimally invasive operation for osteoporotic vertebral compression fracture (OVCF), which has the advantages of rapid pain relief and shorter recovery time. However, new adjacent vertebral compression fracture (AVCF) occurs frequently after vertebroplasty. The purpose of this study was to investigate the risk factors of AVCF and establish a clinical prediction model. METHODS: We retrospectively collected the clinical data of patients who underwent vertebroplasty in our hospital from June 2018 to December 2019. The patients were divided into a non-refracture group (289 cases) and a refracture group (43 cases) according to the occurrence of AVCF. The independent predictive factors for postoperative new AVCF were determined by univariate analysis, least absolute shrinkage and selection operator (LASSO) logistic regression, and multivariable logistic regression analysis. A nomogram clinical prediction model was established based on relevant risk factors, and the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA) were used to evaluate the prediction effect and clinical value of the model. After internal validation, patients who underwent vertebroplasty in our hospital from January 2020 to December 2020, including a non-refracture group (156 cases) and a refracture group (21 cases), were included as the validation cohort to evaluate the prediction model again. RESULTS: Three independent risk factors of low bone mass density (BMD), leakage of bone cement and "O" shaped distribution of bone cement were screened out by LASSO regression and logistic regression analysis. The area under the curve (AUC) of the model in the training cohort and the validation cohort was 0.848 (95%CI: 0.786-0.909) and 0.867 (95%CI: 0.796-0.939), respectively, showing good predictive ability. The calibration curves showed the correlation between prediction and actual status. The DCA showed that the prediction model was clinically useful within the whole threshold range. CONCLUSION: Low BMD, leakage of bone cement and "O" shaped distribution of bone cement are independent risk factors for AVCF after vertebroplasty. The nomogram prediction model has good predictive ability and clinical benefit.

DIA-MS Based Proteomics Combined with RNA-Seq Data to Unveil the Mitochondrial Dysfunction in Human Glioblastoma.

Mitochondrial dysfunctions underlie the pathogenesis in glioblastoma multiforme (GBM). Comprehensive proteomic profiling of mitochondria-specific changes in human GBM is still insufficient. This study carried out a DIA-MS based proteomic analysis on the mitochondria isolated from human primary GBM and peritumoral tissue (as paired control), and further compared those findings with the transcriptomic datasets. A total of 538 mitochondrion-specific proteins were rigorously confirmed, among which 190 differentially expressed proteins were identified. Co-regulations of the mitochondrial dysfunction pathway networks were observed, including significant up-regulations of mitochondrial translation and apoptosis, as well as down-regulations of OXPHOS and mitochondrial dynamics. Proteins related to FA, AA metabolism and ROS also showed significant variations. Most of these alterations were consistent in trend when compared the proteomics findings with the RNA-Seq datasets, while the changes at protein levels appeared to be more dramatic. Potentially key proteins in GBM were identified, including up-regulated pro-apoptotic protein CASP3, BAX, fatty acid oxidation enzymes CPT1A, CPT2, ACADM, serine-glycine enzymes SHMT2, GATM, ROS-related protein SOD2, GPX1, and CAT; and down-regulated dynamin-related protein MFN1, MFN2, OPA1, and OXPHOS components; and also several differentially expressed ALDH isoforms. This study systematically profiled the mitochondrial dysfunctions by combining proteomic findings and mRNA datasets, which would be a valuable resource to the community for further thorough analyses.

Three Major Gastrointestinal Cancers Could Be Distinguished through Subclass-Specific IgG Glycosylation.

Esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC) are three major digestive tract tumors with higher morbidity and mortality due to significant molecular heterogeneity. Altered IgG glycosylation has been observed in inflammatory activities and disease progression, and the IgG glycome profile could be used for disease stratification. However, IgG N-glycome profiles in these three cancers have not been systematically investigated. Herein, subclass-specific IgG glycosylation in CRC, GC, and EC was comprehensively characterized by liquid chromatography-tandem mass spectrometry. It was found that IgG1 sialylation was decreased in all three cancers, and the alterations in CRC and EC may be subclass-specific. IgG4 mono-galactosylation was increased in all three cancers, which was a subclass-specific change in all of them. Additionally, glycopeptides of IgG1-H5N5, IgG2-H4N3F1, and IgG4-H4N4F1 could distinguish all three cancer groups from controls with fair diagnostic performance. Furthermore, bioinformatics verified the differential expression of relevant glycosyltransferase genes in cancer progression. Significantly, those three gastrointestinal cancers could be distinguished from each other using subclass-specific IgG glycans. These findings demonstrated the spatial and temporal diversity of IgG N-glycome among digestive cancers, increasing our understanding of the molecular mechanisms of EC, GC, and CRC pathogenesis.

Deep learning enabled reflective coded aperture snapshot spectral imaging.

Coded aperture snapshot spectral imaging (CASSI) can acquire rich spatial and spectral information at ultra-high speed, which shows extensive application prospects. CASSI innovatively employed the idea of compressive sensing to capture the spatial-spectral data cube using a monochromatic detector and used reconstruction algorithms to recover the desired spatial-spectral information. Based on the optical design, CASSI currently has two different implementations: single-disperser (SD) CASSI and dual-disperser (DD) CASSI. However, SD-CASSI has poor spatial resolution naturally while DD-CASSI increases size and cost because of the extra prism. In this work, we propose a deep learning-enabled reflective coded aperture snapshot spectral imaging (R-CASSI) system, which uses a mask and a beam splitter to receive the reflected light by utilizing the reflection of the mask. The optical path design of R-CASSI makes the optical system compact, using only one prism as two dispersers. Furthermore, an encoder-decoder structure with 3D convolution kernels is built for the reconstruction, dubbed U-net-3D. The designed U-net-3D network achieves both spatial and spectral consistency, leading to state-of-the-art reconstruction results. The real data is released and can serve as a benchmark dataset to test new reconstruction algorithms.

Associations of essential and toxic metals/metalloids in whole blood with both disease severity and mortality in patients with COVID-19.

The variations and dynamics of essential and toxic metal(loid)s in patients with COVID-19 may associate with the progression and fatal outcome of the disease, which still remains to investigate. In the present study, a retrospective analysis was performed in a cohort of 306 confirmed COVID-19 patients admitted to Tongji hospital (Wuhan, China) from February 10 to March 15, 2020. Whole blood levels of essential and/or toxic metal(loid)s were analyzed, including magnesium, calcium, chromium, manganese, iron, copper, zinc, arsenic, cadmium, mercury, thallium, and lead according to the disease severity and outcome. Compared to the non-severe COVID-19 patients, severe cases showed significant higher levels of whole blood calcium, chromium, and copper, but lower levels of magnesium, manganese, iron, zinc, arsenic, thallium, and lead. These differences were further found consistently across the clinical course since the disease onset by longitudinal analysis. Among the severe patients, chromium and cadmium were higher in the deceased group compared to the recovered group, while arsenic was lower. Whole blood iron, age, and sex were determined to be independent factors associated with the disease severity, while chromium, cadmium, and the comorbidity of cardiovascular disease were determined to be independent factors associated with the mortality. These results suggest that variations of whole blood metal(loid)s may be associated with the severe illness and fatal outcome of COVID-19, which could be persistently monitored and would be helpful in the evaluation of the dynamic changes in patients with COVID-19.