Identification of novel biomarkers differentially expressed between African-American and Caucasian-American prostate cancer patients

Prostate cancer (PCa) incidence and mortality rate vary among racial and ethnic groups with the highest occurrence in African American (AA) men who have mortality rates twice that of Caucasians (CA). In this study, we focused on differential expression of proteins in AA prostate cancer compared to CA using Protein Pathway Array Analysis (PPAA), in order to identify protein biomarkers associated with PCa racial disparity. Fresh frozen prostate samples (n=90) obtained from radical prostatectomy specimens with PCa, including 25 AA tumor, 21 AA benign, 23 CA tumor, 21 CA benign samples were analyzed. A total of 286 proteins and phosphoproteins were assessed using PPAA. By PPAA analysis, 33 proteins were found to be significantly differentially expressed in tumor tissue (n=48, including both CA and AA) in comparison to benign tissue (n=42). We further compared protein expression levels between AA and CA tumor groups and found that 3 proteins were differentially expressed (P<0.05 and q<5%). Aurora was found to be significantly increased in AA tumors, while Cyclin D1 and HNF-3a proteins were downregulated in AA tumors. Predicted risk score was significantly different between AA and CA ethnic groups using logistic regression analysis. In conclusion, we identified Aurora, Cyclin D1 and HNF-3a proteins as being differentially expressed between AA and CA in PCa tissue. Our study suggests that these proteins might be involved in different pathways that lead to aggressive PCa behavior in AA patients, potentially serving as biomarkers for the PCa racial disparity.

Self-replicating Biophotoelectrochemistry System for Sustainable CO Methanation

Efficient conversion of CO-rich gas to methane (CH₄) provides an effective energy solution by taking advantage of existing natural gas infrastructures. However, traditional chemical and biological conversions face different challenges. Herein, an innovative biophotoelectrochemistry (BPEC) system using Methanosarcina barkeri-CdS as a biohybrid catalyst was successfully employed for CO methanation. Compared with CO₂-fed BPEC, BPEC-CO significantly extended the CH₄ producing time by 1.7-fold and exhibited a higher CH₄ yield by 9.5-fold under light irradiation. This superior conversion of CO resulted from the fact that CO could serve as an effective quencher of reactive species along with the photoelectron production. In addition, CO was used as a carbon source either directly or indirectly via the produced CO₂ for M. barkeri. Such a process improved the redox activities of membrane-bound proteins for BPEC methanogenesis. These results were consistent with the transcriptomic analyses, in which the genes for the putative CO oxidation and CO₂ reduction pathways in M. barkeri were highly expressed, while the gene expression for reactive oxygen species detoxification remained relatively stable under light irradiation. This study has provided the first proof-of-concept evidence for sustainable CO methanation under a mild condition in the self-replicating BPEC system.

MicroRNA-29a-3p regulates chemosensitivity in hypopharyngeal carcinoma via targeting Cdc42

INTRODUCTION

Hypopharyngeal carcinoma is one kind of high malignant tumour followed by poor prognosis in head and neck carcinomas. This study aimed to detect miR-29a-3p and Cdc42 in patients with hypopharyngeal carcinoma.

MATERIALS AND METHODS

The expression of miR-29a-3p and Cdc42 mRNA were detected, and the correlation between miR-29a-3p/Cdc42 and clinical stages was investigated.

RESULTS

The relative expression of miR-29a-3p in stage II, III and IV hypopharyngeal carcinoma tissues was significantly lower than that of stage I (P< 0.05). The relative expression of Cdc42 mRNA in stage I, III and IV tissues was significantly higher than that of stage I (P< 0.05). The expression of miR-29a-3p in hypopharyngeal carcinoma with lymph node metastasis was significantly lower than that without lymph node metastasis (P = 0.045).

CONCLUSION

MiR-29a-3p and Cdc42 mRNA could be potential diagnostic biomarkers of hypopharyngeal carcinoma.

The prognosis of late-onset anti-N-methyl-D-aspartate receptor encephalitis in China

OBJECTIVES

Early-onset anti-N-methyl-D-aspartate receptor encephalitis (anti-NMDARE) differs from late-onset anti-NMDARE regarding clinical characteristics. Until recently, research focusing on prognosis of elder adults has been scarce and showed inconsistent results. This study aims to evaluate the prognosis of late-onset anti-NMDARE in China.

MATERIALS & METHODS

One hundred and twelve adults diagnosed as anti-NMDARE in four hospitals in China were reviewed retrospectively. Outcome data were assessed using modified Rankin Scale (mRS) score in short term (3 months after discharge) and long term (≥12 months after discharge). The relapse rate was also computed. Multivariable logistic regression was used to evaluate whether there are substantial differences in functional outcomes and recurrence rate across two groups.

RESULTS

Of the 112 patients with anti-NMDARE, 81 (72.3%) were early-onset disease and 31 (27.7%) were late-onset disease. Of these, all had short-term follow-up and 70 completed long-term follow-up. Late-onset anti-NMDARE group showed better short-term (OR 2.70, 95% CI 1.09-6.71) and long-term prognoses (OR 10.25, 95% CI 1.90-55.15). Recurrence rates were statistically different between the groups (OR 4.25, 95% CI 1.22-14.75).

CONCLUSION

The prognosis for anti-NMDARE in China was poorer for older adults relative to younger adults. The relapse rates were higher in late-onset group compared to early-onset group.

Intrinsic Brain Activity in Temporal Lobe Epilepsy With and Without Depression: Insights From EEG Microstates

Background: Depression is the most common psychiatric comorbidity of temporal lobe epilepsy (TLE). In the recent years, studies have focused on the common pathogenesis of TLE and depression. However, few of the studies focused on the dynamic characteristics of TLE with depression. We tested the hypotheses that there exist abnormalities in microstates in patients with TLE with depression.

Methods: Participants were classified into patients with TLE with depression (PDS) (n = 19) and patients with TLE without depression (nPDS) (n = 19) based upon the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V). Microstate analysis was applied based on 256-channel electroencephalography (EEG) to detect the dynamic changes in whole brain. The coverage (proportion of time spent in each state), frequency of occurrence, and duration (average time of each state) were calculated.

Results: Patients with PDS showed a shorter mean microstate duration with higher mean occurrence per second compared to patients with nPDS. There was no difference between the two groups in the coverage of microstate A–D.

Conclusion: This is the first study to present the temporal fluctuations of EEG topography in comorbid depression in TLE using EEG microstate analysis. The temporal characteristics of the four canonical EEG microstates were significantly altered in patients with TLE suffer from comorbid depression.

Insertion Specificity of the hATx-6 Transposase of Hydra magnipapillata

Transposable elements (TE) are mobile genetic elements, present in all domains of life. They commonly encode a single transposase enzyme, that performs the excision and reintegration reactions, and these enzymes have been used in mutagenesis and creation of next-generation sequencing libraries. All transposases have some bias in the DNA sequence they bind to when reintegrating the TE DNA. We sought to identify a transposase that showed minimal sequence bias and could be produced recombinantly, using information from the literature and a novel bioinformatic analysis, resulting in the selection of the hATx-6 transposase from Hydra vulgaris (aka Hydra magnipapillata) for further study. This transposase was tested and shown to be active both in vitro and in vivo, and we were able to demonstrate very low sequence bias in its integration preference. This transposase could be an excellent candidate for use in biotechnology, such as the creation of next-generation sequencing libraries.

High-frequency oscillations detected by electroencephalography as biomarkers to evaluate treatment outcome, mirror pathological severity and predict susceptibility to epilepsy

High-frequency oscillations (HFOs) in the electroencephalography (EEG) have been extensively investigated as a potential biomarker of epileptogenic zones. The understanding of the role of HFOs in epilepsy has been advanced considerably over the past decade, and the use of scalp EEG facilitates recordings of HFOs. HFOs were initially applied in large scale in epilepsy surgery and are now being utilized in other applications. In this review, we summarize applications of HFOs in 3 subtopics: (1) HFOs as biomarkers to evaluate epilepsy treatment outcome; (2) HFOs as biomarkers to measure seizure propensity; (3) HFOs as biomarkers to reflect the pathological severity of epilepsy. Nevertheless, knowledge regarding the above clinical applications of HFOs remains limited at present. Further validation through prospective studies is required for its reliable application in the clinical management of individual epileptic patients.

Identification of Epileptogenic and Non-epileptogenic High-Frequency Oscillations Using a Multi-Feature Convolutional Neural Network Model

Accurately identifying epileptogenic zone (EZ) using high-frequency oscillations (HFOs) is a challenge that must be mastered to transfer HFOs into clinical use. We analyzed the ability of a convolutional neural network (CNN) model to distinguish EZ and non-EZ HFOs. Nineteen medically intractable epilepsy patients with good surgical outcomes 2 years after surgery were studied. Five-minute interictal intracranial electroencephalogram epochs of slow-wave sleep were selected randomly. Then 5 s segments of ripples (80–200 Hz) and fast ripples (FRs, 200–500 Hz) were detected automatically. The EZs and non-EZs were identified using the surgery resection range. We innovatively converted all epochs into four types of images using two scales: original waveforms, filtered waveforms, wavelet spectrum images, and smoothed pseudo Wigner–Ville distribution (SPWVD) spectrum images. Two scales were fixed and fitted scales. We then used a CNN model to classify the HFOs into EZ and non-EZ categories. As a result, 7,000 epochs of ripples and 2,000 epochs of FRs were randomly selected from the EZ and non-EZ data for analysis. Our CNN model can distinguish EZ and non-EZ HFOs successfully. Except for original ripple waveforms, the results from CNN models that are trained using fixed-scale images are significantly better than those from models trained using fitted-scale images (p < 0.05). Of the four fixed-scale transformations, the CNN based on the adjusted SPWVD (ASPWVD) produced the best accuracies (80.89 ± 1.43% and 77.85 ± 1.61% for ripples and FRs, respectively, p < 0.05). The CNN using ASPWVD transformation images is an effective deep learning method that can be used to classify EZ and non-EZ HFOs.

Biophotoelectrochemistry for renewable energy and environmental applications

Biophotoelectrochemistry (BPEC) is an interdisciplinary research field and combines bioelectrochemistry and photoelectrochemistry through the utilization of the catalytic abilities of biomachineries and light harvesters to accomplish the production of energy or chemicals driven by solar energy. The BPEC process may act as a new approach for sustainable green chemistry and waste minimization. This review provides the state-of-the-art introduction of BPEC basics and systems, with a focus on light harvesters and biocatalysts, configurations, photoelectron transfer mechanisms, and the potential applications in energy and environment. Several examples of BPEC applications are discussed including H2 production, CO2 reduction, chemical synthesis, pollution control, and biogeochemical cycle of elements. The challenges about BPEC systems are identified and potential solutions are proposed. The review aims to encourage further research of BPEC toward development of practical BPEC systems for energy and environmental applications.

Expression of 5-methylcytosine regulators is highly associated with the clinical phenotypes of prostate cancer and DNMTs expression predicts biochemical recurrence

In patients with prostate cancer (PCa), there is a high rate of overdiagnosis and frequent overtreatment. Therefore, there is an urgent need for more accurate prediction of biochemical recurrence (BCR). DNA methylation regulation patterns play crucial roles in tumorigenicity, progression, and treatment efficacy in PCa. However, the global relationship between epigenetic alterations, changes in mRNA levels, and pathologic phenotypes of PCa remain largely undefined. Here, we conducted a systematic analysis to identify global coexpression and comethylation modules in PCa. We identified coregulated methylation and expression modules and the relationships between epigenetic modifications, tumor progression, and the corresponding immune microenvironment in PCa. Our results show that DNA methyltransferases (DNMTs) are strongly associated with pathologic phenotypes and immune infiltration patterns in PCa. We built a two-factor predictive model using the expression features of DNMT3B and DNMT1. The model was used to predict the BCR status of patients with PCa and achieved area under the receiver operating characteristic curve values of 0.70 and 0.88 in the training and independent testing datasets, respectively.

Dysfunctional Brain Dynamics of Parkinson's Disease and the Effect of Acute Deep Brain Stimulation

Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease, and deep brain stimulation (DBS) can effectively alleviate PD symptoms. Although previous studies have detected network features of PD and DBS, few studies have considered their dynamic characteristics.

Objective: We tested two hypotheses. (1) Reduced brain dynamics, as evidenced by slowed microstate dynamic change, is a characteristic of PD and is related to the movement disorders of patients with PD. (2) Therapeutic acute DBS can partially reverse slow brain dynamics in PD to healthy levels.

Methods: We used electroencephalography (EEG) microstate analysis based on high density (256-channel) EEG to detect the effects of PD and DBS on brain dynamic changes on a sub-second timescale. We compared 21 healthy controls (HCs) with 20 patients with PD who were in either DBS-OFF or DBS-ON states. Assessment of movement disorder using the Unified Parkinson's Disease Rating Scale III was correlated with microstate parameters.

Results: Compared with HCs, patients with PD displayed a longer mean microstate duration with reduced occurrence per second, which were significantly associated with movement disorders. In patients with PD, some parameters of microstate analysis were restored toward healthy levels after DBS.

Conclusions: Resting-state EEG microstate analysis is an important tool for investigating brain dynamic changes in PD and DBS. PD can slow down brain dynamic change, and therapeutic acute DBS can partially reverse this change toward a healthy level.

A facile and fast strategy for cathodic electroactive-biofilm assembly via magnetic nanoparticle bioconjugation

Microbial electrosynthesis is a promising electricity-driven technology for converting carbon dioxide into value-added compounds, but the formation of cathodic electroactive-biofilms (CEBs) is challenging. Herein, we have demonstrated an innovative strategy for CEBs assembly via magnetic nanoparticle bioconjugation, which lies in the synergistic interactions among a bonder (Streptavidin, SA), conductive nanomaterials (Fe₃O₄), and a methanogen (M. barkeri). The results showed that the bioconjugated M. barkeri-SA-Fe₃O₄ biohybrids significantly enhanced both methane yield (33.2-fold) and faradaic efficiency (5.6-fold), compared with that of bare M. barkeri. Such an enhancement was attributed to the improved viability of CEBs with a higher biomass density. Particularly, more live cells were presented in the inner biofilms and promoted the long-distance electron exchange between the live outer-layer biofilm and the cathode electrode. Meanwhile, the higher redox activity of CEBs with the M. barkeri-SA-Fe₃O₄ biohybrids resulted in an improved transient charge storage capability, which was beneficial for the biological CO₂-to-CH₄ conversion via acting as an additional electron donor. This work has provided a new approach to accelerate the formation of CEBs and subsequent electron transfer, which holds a great potential for accomplishing electrosynthesis and CO₂ fixation.

A useful epitope tag derived from maltose binding protein

Maltose binding protein (MBP) is used in recombinant protein expression as an affinity and solubility tag. The monoclonal antibody B48 binds MBP tightly and has no cross-reactivity to other proteins in an Escherichia coli lysate. This high level of specificity suggested that MBP contains an epitope that could prove useful as a purification and visualization tag for proteins expressed in E. coli. To discover the MBP epitope, a co-crystal structure was determined for MBP bound to its antibody and four amino acids of MBP were identified as critical for the binding interaction. Fusions of various fragments of MBP to the glutathione S-transferase protein were engineered in order to identify the smallest fragment still recognized by the α-MBP antibody. Stabilization of the epitope via mutational engineering resulted in a minimized 14 amino-acid tag.

A Validated Nomogram That Predicts Prognosis of Autoimmune Encephalitis: A Multicenter Study in China

The aim of this retrospective study was to derive and validate a reliable nomogram for predicting prognosis of autoimmune encephalitis (AE). A multi-center retrospective study was conducted in four hospitals in China, using a random split-sample method to allocate 173 patients into either a training (n = 126) or validation (n = 47) dataset. Demographic, radiographic and therapeutic presentation, combined with clinical features were collected. A modified Rankin Scale (mRS) at discharge was the principal outcome variable. A backward-stepwise approach based on the Akaike information criterion was used to test predictors and construct the final, parsimonious model. Multivariable analysis was conducted using logistic regression to develop a prognosis model and validate a nomogram using an independent dataset. The performance of the model was assessed using receiver operating characteristic curves and a Hosmer-Lemeshow test. The final nomogram model considered age, viral prodrome, consciousness impairment, memory dysfunction and autonomic dysfunction as predictors. Model validations displayed a good level of discrimination in the validation set: area under the Receiver operator characteristic curve = 0.72 (95% Confidence Interval: 0.56–0.88), Hosmer–Lemeshow analysis suggesting good calibration (chi-square: 10.33; p = 0.41). The proposed nomogram demonstrated considerable potential for clinical utility in prediction of prognosis in autoimmune encephalitis.

Identification of UBE2C as hub gene in driving prostate cancer by integrated bioinformatics analysis

BACKGROUND

The aim of this study was to identify novel genes in promoting primary prostate cancer (PCa) progression and to explore its role in the prognosis of prostate cancer.

METHODS

Four microarray datasets containing primary prostate cancer samples and benign prostate samples were downloaded from Gene Expression Omnibus (GEO), then differentially expressed genes (DEGs) were identified by R software (version 3.6.2). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to identify the function of DEGs. Using STRING and Cytoscape (version 3.7.1), we constructed a protein-protein interaction (PPI) network and identified the hub gene of prostate cancer. Clinical data on GSE70770 and TCGA was collected to show the role of hub gene in prostate cancer progression. The correlations between hub gene and clinical parameters were also indicated by cox regression analysis. Gene Set Enrichment Analysis (GSEA) was performed to highlight the function of Ubiquitin-conjugating enzyme complex (UBE2C) in prostate cancer.

RESULTS

243 upregulated genes and 298 downregulated genes that changed in at least two microarrays have been identified. GO and KEGG analysis indicated significant changes in the oxidation-reduction process, angiogenesis, TGF-beta signaling pathway. UBE2C, PDZ-binding kinase (PBK), cyclin B1 (CCNB1), Cyclin-dependent kinase inhibitor 3 (CDKN3), topoisomerase II alpha (TOP2A), Aurora kinase A (AURKA) and MKI67 were identified as the candidate hub genes, which were all correlated with prostate cancer patient' disease-free survival in TCGA. In fact, only UBE2C was highly expressed in prostate cancer when compared with benign prostate tissue in TCGA and the expression of UBE2C was also in parallel with the Gleason score of prostate cancer. Cox regression analysis has indicated UBE2C could function as the independent prognostic factor of prostate cancer. GSEA showed UBE2C had played an important role in the pathway of prostate cancer, such as NOTCH signaling pathway, WNT-β-catenin signaling pathway.

CONCLUSIONS

UBE2C was pivotal for the progression of prostate cancer and the level of UBE2C was important to predict the prognosis of patients.

The Transcriptomic Landscape of Prostate Cancer Development and Progression: An Integrative Analysis

Next-generation sequencing of primary tumors is now standard for transcriptomic studies, but microarray-based data still constitute the majority of available information on other clinically valuable samples, including archive material. Using prostate cancer (PC) as a model, we developed a robust analytical framework to integrate data across different technical platforms and disease subtypes to connect distinct disease stages and reveal potentially relevant genes not identifiable from single studies alone. We reconstructed the molecular profile of PC to yield the first comprehensive insight into its development, by tracking changes in mRNA levels from normal prostate to high-grade prostatic intraepithelial neoplasia, and metastatic disease. A total of nine previously unreported stage-specific candidate genes with prognostic significance were also found. Here, we integrate gene expression data from disparate sample types, disease stages and technical platforms into one coherent whole, to give a global view of the expression changes associated with the development and progression of PC from normal tissue through to metastatic disease. Summary and individual data are available online at the Prostate Integrative Expression Database (PIXdb), a user-friendly interface designed for clinicians and laboratory researchers to facilitate translational research.

The Association Between Age and Prognosis in Patients Under 45 Years of Age With Anti-NMDA Receptor Encephalitis

This study aims to evaluate the association between age and prognosis in patients with anti-N-methyl-D-aspartate receptor encephalitis (anti-NMDARE) under the age of 45 years. A retrospective study was conducted in patients younger than 45 years diagnosed as anti-NMDARE in four hospitals in China. Age at admission was divided into four categories: <15, 15–24, 25–34, 35–45 years. Neurological prognosis was evaluated using modified Rankin Scale. Adjusted multivariable logistic regression was used to analyze the association. The multivariable-adjusted odds ratios (95% confidence interval) of prognosis in anti-NMDARE across the categories of age were as follows: in males, 1.00 (reference), 4.76 (0.39–58.76), 13.50 (0.79–230.40), and 8.81 (0.36–218.39) (P for trend = 0.171); in females, 1.00 (reference), 7.27 (0.36–146.19), 20.08 (1.09–370.39), and 54.41 (1.60–1,849.10) (P for trend = 0.01). We concluded that the increasing age was associated with a poorer prognosis of anti-NMDARE in females but not males.

Improved production of Humira antibody in the genetically engineered Escherichia coli SHuffle, by co-expression of human PDI-GPx7 fusions

Abstract

Microbial production of antibodies offers the promise of cheap, fast, and efficient production of antibodies at an industrial scale. Limiting this capacity in prokaryotes is the absence of the post-translational machinery, present in dedicated antibody producing eukaryotic cell lines, such as B cells. There has been few and limited success in producing full-length, correctly folded, and assembled IgG in the cytoplasm of prokaryotic cell lines. One such success was achieved by utilizing the genetically engineered Escherichia coli strain SHuffle with an oxidative cytoplasm. Due to the genetic disruption of reductive pathways, SHuffle cells are under constant oxidative stress, including increased levels of hydrogen peroxide (H₂O₂). The oxidizing capacity of H₂O₂ was linked to improved disulfide bond formation, by expressing a fusion of two endoplasmic reticulum-resident proteins, the thiol peroxidase GPx7 and the protein disulfide isomerase, PDI. In concert, these proteins mediate disulfide transfer from H₂O₂ to target proteins via PDI-Gpx7 fusions. The potential of this new strain was tested with Humira, a blockbuster antibody usually produced in eukaryotic cells. Expression results demonstrate that the new engineered SHuffle strain (SHuffle2) could produce Humira IgG four-fold better than the parental strain, both in shake-flask and in high-density fermentation. These preliminary studies guide the field in genetically engineering eukaryotic redox pathways in prokaryotes for the production of complex macromolecules.

Key points

• A eukaryotic redox pathway was engineered into the E. coli strain SHuffle in order to improve the yield of the blockbuster antibody Humira.

• The best peroxidase-PDI fusion was selected using bioinformatics and in vivo studies.

• Improved yields of Humira were demonstrated at shake-flask and high-density fermenters.

Electronic supplementary material

The online version of this article (10.1007/s00253-020-10920-5) contains supplementary material, which is available to authorized users.

Enhancing colorimetric loop-mediated isothermal amplification speed and sensitivity with guanidine chloride

Loop-mediated isothermal amplification (LAMP) is a versatile technique for detection of target DNA and RNA, enabling rapid molecular diagnostic assays with minimal equipment. The global SARS-CoV-2 pandemic has presented an urgent need for new and better diagnostic methods, with colorimetric LAMP utilized in numerous studies for SARS-CoV-2 detection. However, the sensitivity of colorimetric LAMP in early reports has been below that of the standard RT-qPCR tests, and we sought to improve performance. Here we report the use of guanidine hydrochloride and combined primer sets to increase speed and sensitivity in colorimetric LAMP, bringing this simple method up to the standards of sophisticated techniques and enabling accurate, high-throughput diagnostics.