The Role of Integrin Receptor's α and ß Subunits of Mouse Mesenchymal Stem Cells on the Interaction of Marine-Derived Blacktip Reef Shark (Carcharhinus melanopterus) Skin Collagen.

Marine collagen (MC) has recently attracted more attention in tissue engineering as a biomaterial substitute due to its significant role in cellular signaling mechanisms, especially in mesenchymal stem cells (MSCs). However, the actual signaling mechanism of MC in MSC growth, which is highly influenced by their molecular pattern, is poorly understood. Hence, we investigated the integrin receptors (α1ß1, α2ß1, α10ß1, and α11ß1) binding mechanism and proliferation of MCs (blacktip reef shark collagen (BSC) and blue shark collagen (SC)) compared to bovine collagen (BC) on MSCs behavior through functionalized collagen molecule probing for the first time. The results showed that BSC and SC had higher proliferation rates and accelerated scratch wound healing by increasing migratory rates of MSCs. Cell adhesion and spreading results demonstrated that MC had a better capacity to anchor MSCs and maintain cell morphology than controls. Living cell observations showed that BSC was gradually assembled by cells into the ECM network within 24 h. Interestingly, qRT-PCR and ELISA revealed that the proliferative effect of MC was triggered by interacting with specific integrin receptors such as α2ß1, α10ß1, and α11ß1 of MSCs. Accordingly, BSC accelerated MSCs' growth, adhesion, shape, and spreading by interacting with specific integrin subunits (α2 and ß1) and thereby triggering further signaling cascade mechanisms.

Isolation and Biochemical Properties of Type II Collagen from Blue Shark (Prionace glauca) Cartilage.

Numerous studies have shown that type II collagen (CII) has a potential role in the treatment of rheumatoid arthritis. However, most of the current studies have used terrestrial animal cartilage as a source of CII extraction, with fewer studies involving marine organisms. Based on this background, collagen (BSCII) was isolated from blue shark (Prionace glauca) cartilage by pepsin hydrolysis and its biochemical properties including protein pattern, total sugar content, microstructure, amino acid composition, spectral characteristics and thermal stability were further investigated in the present study. The SDS-PAGE results confirmed the typical characteristic of CII, comprising three identical α1 chains and its dimeric ß chain. BSCII had the fibrous microstructure typical of collagen and an amino acid composition represented by high glycine content. BSCII had the typical UV and FTIR spectral characteristics of collagen. Further analysis revealed that BSCII had a high purity, while its secondary structure comprised 26.98% of ß-sheet, 35.60% of ß-turn, 37.41% of the random coil and no α-helix. CD spectra showed the triple helical structure of BSCII. The total sugar content, denaturation temperature and melting temperature of BSCII were (4.20 ± 0.03)%, 42 °C and 49 °C, respectively. SEM and AFM images confirmed a fibrillar and porous structure of collagen and denser fibrous bundles formed at higher concentrations. Overall, CII was successfully extracted from blue shark cartilage in the present study, and its molecular structure was intact. Therefore, blue shark cartilage could serve as a potential source for CII extraction with applications in biomedicine.

Paradoxical Duel Role of Collagen in Rheumatoid Arthritis: Cause of Inflammation and Treatment.

In biology, collagen-biomaterial regulates several signaling mechanisms of bone and immune cells involved in tissue repair and any imbalance in collagen turnover may affect the homeostasis of cells, becoming a major cause of several complications. In this case, the administration of oral collagen may play a potential role in returning cells to their normal function. For several decades, the beneficial effects of collagen have been explored widely, and thus many commercial products are available in cosmetics, food, and biomedical fields. For instance, collagen-based-products have been widely used to treat the complications of cartilage-related-disorders. Many researchers are reporting the anti-arthritogenic properties of collagen-based materials. In contrast, collagen, especially type-II collagen (CII), has been widely used to induce arthritis by immunization in an animal-model with or without adjuvants, and the potentially immunogenic-properties of collagen have been continuously reported for a long time. Additionally, the immune tolerance of collagen is mainly regulated by the T-lymphocytes and B-cells. This controversial hypothesis is getting more and more evidence nowadays from both sides to support its mechanism. Therefore, this review links the gap between the arthritogenic and anti-arthritogenic effects of collagen and explored the actual mechanism to understand the fundamental concept of collagen in arthritis. Accordingly, this review opens-up several unrevealed scientific knots of collagen and arthritis and helps the researchers understand the potential use of collagen in therapeutic applications.

Comparison of Physicochemical and Structural Properties of Acid-Soluble and Pepsin-Soluble Collagens from Blacktip Reef Shark Skin.

Fish collagen has been widely used in tissue engineering (TE) applications as an implant, which is generally transplanted into target tissue with stem cells for better regeneration ability. In this case, the success rate of this research depends on the fundamental components of fish collagen such as amino acid composition, structural and rheological properties. Therefore, researchers have been trying to find an innovative raw material from marine origins for tissue engineering applications. Based on this concept, collagens such as acid-soluble (ASC) and pepsin-soluble (PSC) were extracted from a new type of cartilaginous fish, the blacktip reef shark, for the first time, and were further investigated for physicochemical, protein pattern, microstructural and peptide mapping. The study results confirmed that the extracted collagens resemble the protein pattern of type-I collagen comprising the α1, α2, ß and γ chains. The hydrophobic amino acids were dominant in both collagens with glycine and hydroxyproline as major amino acids. From the FTIR spectra, α helix (27.72 and 26.32%), ß-sheet (22.24 and 23.35%), ß-turn (21.34 and 22.08%), triple helix (14.11 and 14.13%) and random coil (14.59 and 14.12%) structures of ASC and PSC were confirmed, respectively. Collagens retained their triple helical and secondary structure well. Both collagens had maximum solubility at 3% NaCl and pH 4, and had absorbance maxima at 234 nm, respectively. The peptide mapping was almost similar for ASC and PSC at pH 2, generating peptides ranging from 15 to 200 kDa, with 23 kDa as a major peptide fragment. The microstructural analysis confirmed the homogenous fibrillar nature of collagens with more interconnected networks. Overall, the preset study concluded that collagen can be extracted more efficiently without disturbing the secondary structure by pepsin treatment. Therefore, the blacktip reef shark skin could serve as a potential source for collagen extraction for the pharmaceutical and biomedical applications.

Discovery of 6,7-dihydro-5H-pyrrolo[3,4-d] pyrimidine derivatives as a new class of ATR inhibitors.

Ataxia telangiectasia and Rad3-related (ATR) kinase is a key regulating protein within the DNA damage response (DDR), responsible for sensing replication stress (RS), and has been considered as a potential target for cancer therapy. Herein, we report the discovery of a series of 6,7-dihydro-5H-pyrrolo[3,4-d]-pyrimidine derivatives as a new class of ATR inhibitors. Among them, compound 5g exhibits an IC50 value of 0.007 µM against ATR kinase. In vitro, 5g displays good anti-tumor activity and could significantly reduce the phosphorylation level of ATR and its downstream signaling protein. Overall, this study provides a promising lead compound for subsequent drug discovery targeting ATR kinase.

An integrated machine learning framework for a discriminative analysis of schizophrenia using multi-biological data.

Finding effective and objective biomarkers to inform the diagnosis of schizophrenia is of great importance yet remains challenging. Relatively little work has been conducted on multi-biological data for the diagnosis of schizophrenia. In this cross-sectional study, we extracted multiple features from three types of biological data, including gut microbiota data, blood data, and electroencephalogram data. Then, an integrated framework of machine learning consisting of five classifiers, three feature selection algorithms, and four cross validation methods was used to discriminate patients with schizophrenia from healthy controls. Our results show that the support vector machine classifier without feature selection using the input features of multi-biological data achieved the best performance, with an accuracy of 91.7% and an AUC of 96.5% (p < 0.05). These results indicate that multi-biological data showed better discriminative capacity for patients with schizophrenia than single biological data. The top 5% discriminative features selected from the optimal model include the gut microbiota features (Lactobacillus, Haemophilus, and Prevotella), the blood features (superoxide dismutase level, monocyte-lymphocyte ratio, and neutrophil count), and the electroencephalogram features (nodal local efficiency, nodal efficiency, and nodal shortest path length in the temporal and frontal-parietal brain areas). The proposed integrated framework may be helpful for understanding the pathophysiology of schizophrenia and developing biomarkers for schizophrenia using multi-biological data.

Clinical Characteristics and Abnormal Parameters Evolution in Patients With Novel Coronavirus Infection: A Case Series of 272 Cases in Guangzhou.

OBJECTIVE: The aim of this study was to present the clinical characteristics and dynamic changes in laboratory parameters of the coronavirus disease 2019 (COVID-19) in Guangzhou, and explore the probable early warning indicators of disease progression. METHOD: We enrolled all the patients diagnosed with COVID-19 in the Guangzhou No. 8 People's Hospital. The patients' demographic and epidemiologic data were collected, including chief complaints, lab results, and imaging examination findings. RESULTS: The characteristics of the patients in Guangzhou are different from those in Wuhan. The patients were younger in age, predominately female, and their condition was not commonly combined with other diseases. A total of 75% of patients suffered fever on admission, followed by cough occurring in 62% patients. Comparing the mild/normal and severe/critical patients, being male, of older age, combined with hypertension, abnormal blood routine test results, raised creatine kinase, glutamic oxaloacetic transaminase, lactate dehydrogenase, C-reactive protein, procalcitonin, D-dimer, fibrinogen, activated partial thromboplastin time, and positive proteinuria were early warning indicators of severe disease. CONCLUSION: The patients outside epidemic areas showed different characteristics from those in Wuhan. The abnormal laboratory parameters were markedly changed 4 weeks after admission, and also were different between the mild and severe patients. More evidence is needed to confirm highly specific and sensitive potential early warning indicators of severe disease.

The Effects of Repetitive Transcranial Magnetic Stimulation in Patients with Chronic Schizophrenia: Insights from EEG Microstates.

The objective of this study was to investigate the effects of 10 Hz repetitive transcranial magnetic stimulation (rTMS) in patients with schizophrenia using EEG microstates. Thirty-eight patients with chronic schizophrenia were included in a double-blind, randomized and sham-controlled trial (19 participants in the active group and 19 participants in the sham group) and received 10 Hz active or sham rTMS stimulation to the left dorsolateral prefrontal cortex (left DLPFC) 5 days per week over for 4 weeks. Four classical microstate classes (i.e., classes A, B, C and D) were identified by clustering, and the parameters (i.e., duration, occurrence and contribution) of each class were computed. Our results showed that (1) after stimulation, the positive and negative syndrome scale (PANSS) positive scores decreased significantly in the active group; (2) the duration of the microstate of class C derived from EEG data decreased significantly in the active group; and (3) the change of the duration of class D in the active group was significantly higher than that in the sham group. Our findings demonstrated that 10 Hz active rTMS stimulation was beneficial to improving the positive symptoms of patients with chronic schizophrenia, and the EEG microstate could be an effective indicator of symptom improvements.

Homocysteine level, body mass index and clinical correlates in Chinese Han patients with schizophrenia.

Obesity is common comorbidity in patients with schizophrenia. Previous studies have reported that homocysteine (Hcy) is increased in schizophrenia. However, no study has reported the association between BMI and Hcy levels in schizophrenia. This cross-sectional naturalistic study aimed to evaluate the relationship between BMI, Hcy and clinical symptoms in Chinese Han patients with chronic schizophrenia. Clinical and anthropometric data as well as plasma Hcy level and glycolipid parameters were collected. Psychopathology was measured with the Positive and Negative Syndrome Scale (PANSS). Our results showed that compared with the low BMI group, the high BMI group had a higher PANSS general psychopathology subscore, higher levels of blood glucose, total cholesterol and high-density lipoprotein (HDL) cholesterol (all p < 0.05). Hcy levels were negatively associated with BMI in patients (p < 0.001). Hcy level, the PANSS general psychopathology subscale, total cholesterol and education (all p < 0.05) were the influencing factors of high BMI. Our study suggest that Hcy level may be associated with BMI in patients with schizophrenia. Moreover, patients with high BMI show more severe clinical symptoms and higher glucose and lipid levels.

Altered gut microbiota associated with symptom severity in schizophrenia.

BACKGROUND: The gut microbiome and microbiome-gut-brain (MGB) axis have been receiving increasing attention for their role in the regulation of mental behavior and possible biological basis of psychiatric disorders. With the advance of next-generation sequencing technology, characterization of the gut microbiota in schizophrenia (SZ) patients can provide rich clues for the diagnosis and prevention of SZ. METHODS: In this study, we compared the differences in the fecal microbiota between 82 SZ patients and 80 demographically matched normal controls (NCs) by 16S rRNA sequencing and analyzed the correlations between altered gut microbiota and symptom severity. RESULTS: The alpha diversity showed no significant differences between the NC and SZ groups, but the beta diversity revealed significant community-level separation in microbiome composition between the two groups (pseudo-F =3.337, p < 0.001, uncorrected). At the phylum level, relatively more Actinobacteria and less Firmicutes (p < 0.05, FDR corrected) were found in the SZ group. At the genus level, the relative abundances of Collinsella, Lactobacillus, Succinivibrio, Mogibacterium, Corynebacterium, undefined Ruminococcus and undefined Eubacterium were significantly increased, whereas the abundances of Adlercreutzia, Anaerostipes, Ruminococcus and Faecalibacterium were decreased in the SZ group compared to the NC group (p < 0.05, FDR corrected). We performed PICRUSt analysis and found that several metabolic pathways differed significantly between the two groups, including the Polyketide sugar unit biosynthesis, Valine, Leucine and Isoleucine biosynthesis, Pantothenate and CoA biosynthesis, C5-Branched dibasic acid metabolism, Phenylpropanoid biosynthesis, Ascorbate and aldarate metabolism, Nucleotide metabolism and Propanoate metabolism pathways (p < 0.05, FDR corrected). Among the SZ group, the abundance of Succinivibrio was positively correlated with the total Positive and Negative Syndrome Scale (PANSS) scores (r = 0.24, p < 0.05, uncorrected) as well as the general PANSS scores (r = 0.22, p < 0.05, uncorrected); Corynebacterium was negatively related to the negative scores of PANSS (r = 0.22, p < 0.05, uncorrected). CONCLUSIONS: Our findings provided evidence of altered gut microbial composition in SZ group. In addition, we found that Succinvibrio and Corynebacterium were associated with the severity of symptoms for the first time, which may provide some new biomarkers for the diagnosis of SZ.

[Research on electroencephalogram specifics in patients with schizophrenia under cognitive load].

Cognitive impairment is one of the three primary symptoms of schizophrenic patients and shows important value in early detection and warning for high-risk individuals. To study the specifics of electroencephalogram (EEG) in patients with schizophrenia under the cognitive load, we collected EEG signals from 17 schizophrenic patients and 19 healthy controls, extracted signals of each band based on wavelet transform, calculated the characteristics of nonlinear dynamic and functional brain networks, and automatically classified the two groups of people by using a machine learning algorithm. Experimental results indicated that the correlation dimension and sample entropy showed significant differences in α, ß, θ, and γ rhythm of the Fp1 and Fp2 electrodes between groups under the cognitive load. These results implied that the functional disruptions in the frontal lobe might be the important factors of cognitive impairments in schizophrenic patients. Further results of the automatic classification analysis indicated that the combination of nonlinear dynamics and functional brain network properties as the input characteristics of the classifier showed the best performance, with the accuracy of 76.77%, sensitivity of 72.09%, and specificity of 80.36%. The results of this study demonstrated that the combination of nonlinear dynamics and function brain network properties may be potential biomarkers for early screening and auxiliary diagnosis of schizophrenia.

Remotely sensed assessment of water quality levels in the Pearl River Estuary, China.

In this paper, a method of assessing water quality from satellite data is introduced. The composite pollution index (CPI) was calculated from measured chemical oxygen demand (COD) and nutrient concentration. The relationships between CPI and 240 band combinations of SeaWiFS water-leaving radiance were analyzed and the optimal band combination for estimating CPI was chosen from the 240 band combinations. An algorithm for retrieval of CPI was developed using the optimal band combination, (L(443)xL(510))/(L(412)+L(490)). The CPI was estimated from atmospherically corrected SeaWiFS data by employing the algorithm. Furthermore, the CPI value range for each water quality level was determined based on data obtained from 850 samples taken in the Pearl River Estuary. The remotely sensed CPIs were then transferred to water quality levels and appropriate maps were derived. The remotely sensed water quality level maps displayed a similar distribution of levels based on in situ investigation issued by the State Ocean Administration, China. This study demonstrates that remote sensing can play an important role in water quality assessment.