WTAP-induced N6-methyladenosine of PD-L1 blocked T-cell-mediated antitumor activity under hypoxia in colorectal cancer.

N6-Methyladenosine (m6A) is a important process regulating gene expression post-transcriptionally. Programmed death ligand 1 (PD-L1) is a major immune inhibitive checkpoint that facilitates immune evasion and is expressed in tumor cells. In this research we discovered that Wilms' tumor 1-associated protein (WTAP) degradation caused by ubiquitin-mediated cleavage in cancer cells (colorectal cancer, CRC) under hypoxia was inhibited by Pumilio homolog 1 (PUM1) directly bound to WTAP. WTAP enhanced PD-L1 expression in a way that was m6A-dependent. m6A "reader," Insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) identified methylated PD-L1 transcripts and subsequently fixed its mRNA. Additionally, we found that T-cell proliferation and its cancer cell-killing effects were prevented by overexpression of WTAP in vitro and in vivo. Overexpression prevented T cells from proliferating and killing CRC by maintaining the expression of PD-L1. Further evidence supporting the WTAP-PD-L1 regulatory axis was found in human CRC and organoid tissues. Tumors with high WTAP levels appeared more responsive to anti-PD1 immunotherapy, when analyzing samples from patients undergoing treatment. Overall, our findings demonstrated a novel PD-L1 regulatory mechanism by WTAP-induced mRNA epigenetic regulation and the possible application of targeting WTAP as immunotherapy for tumor hypoxia.

The potential causal association between systemic lupus erythematosus and endocrine and metabolic disorders in the East Asian population: A bidirectional two-sample Mendelian randomization study.

OBJECTIVES: Observational studies indicate a significant correlation between systemic lupus erythematosus (SLE) and endocrine and metabolic disorders, but the causal association between SLE and endocrine and metabolic disorders remains unclear due to the reverse causality and confounding biases commonly presented in conventional observational research. This study endeavors to uncover the causal association between SLE and three common endocrine and metabolic disorders, including Graves' disease (GD), type 2 diabetes mellitus (T2DM), and osteoporosis (OP). METHODS: We used genome-wide association study data for SLE and three endocrine and metabolic disorders in an East Asian population, employing bidirectional two-sample Mendelian randomization (MR) analysis and sensitivity analysis to ascertain the causal association between SLE and endocrine and metabolic disorders. RESULTS: A multiplicative random-effect inverse-variance weighted approach revealed a significant positive correlation between SLE and an elevated risk of GD with an odds ratio (OR) of 1.12 (95% CI: 1.04-1.22, p < .01), and inverse-variance weighted (IVW) analysis also indicated that SLE increased the risk of OP with an OR of 1.035 (95% CI: 1.003-1.068, p < .05). Additionally, GD causally affected SLE in an IVW analysis after Bonferroni correction, with an OR of 1.33 (95% CI: 1.19-1.49, p < .05/3), but the application of multivariable MR analysis resulted in the absence of a causal association of GD on SLE (OR 1.047, 95% CI: 0.952-1.151, p > .05). Lastly, the robustness and validity of the findings were verified through a sensitivity analysis. CONCLUSIONS: We confirmed that SLE has a causal effect on GD as well as OP, but no evidence exists to substantiate a causal link between SLE and T2DM. Our study offers valuable contributions for uncovering the etiology of SLE and endocrine and metabolic disorders and furthering disease risk research while providing potential targets for disease monitoring and therapeutic intervention.

Learning CT-free attenuation-corrected total-body PET images through deep learning.

OBJECTIVES: Total-body PET/CT scanners with long axial fields of view have enabled unprecedented image quality and quantitative accuracy. However, the ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Therefore, we attempted to generate CT-free attenuation-corrected (CTF-AC) total-body PET images through deep learning. METHODS: Based on total-body PET data from 122 subjects (29 females and 93 males), a well-established cycle-consistent generative adversarial network (Cycle-GAN) was employed to generate CTF-AC total-body PET images directly while introducing site structures as prior information. Statistical analyses, including Pearson correlation coefficient (PCC) and t-tests, were utilized for the correlation measurements. RESULTS: The generated CTF-AC total-body PET images closely resembled real AC PET images, showing reduced noise and good contrast in different tissue structures. The obtained peak signal-to-noise ratio and structural similarity index measure values were 36.92 ± 5.49 dB (p < 0.01) and 0.980 ± 0.041 (p < 0.01), respectively. Furthermore, the standardized uptake value (SUV) distribution was consistent with that of real AC PET images. CONCLUSION: Our approach could directly generate CTF-AC total-body PET images, greatly reducing the radiation risk to patients from redundant anatomical examinations. Moreover, the model was validated based on a multidose-level NAC-AC PET dataset, demonstrating the potential of our method for low-dose PET attenuation correction. In future work, we will attempt to validate the proposed method with total-body PET/CT systems in more clinical practices. CLINICAL RELEVANCE STATEMENT: The ionizing radiation from CT is a major issue in PET imaging, which is more evident with reduced radiopharmaceutical doses in total-body PET/CT. Our CT-free PET attenuation correction method would be beneficial for a wide range of patient populations, especially for pediatric examinations and patients who need multiple scans or who require long-term follow-up. KEY POINTS: • CT is the main source of radiation in PET/CT imaging, especially for total-body PET/CT devices, and reduced radiopharmaceutical doses make the radiation burden from CT more obvious. • The CT-free PET attenuation correction method would be beneficial for patients who need multiple scans or long-term follow-up by reducing additional radiation from redundant anatomical examinations. • The proposed method could directly generate CT-free attenuation-corrected (CTF-AC) total-body PET images, which is beneficial for PET/MRI or PET-only devices lacking CT image poses.

Rare correlation of somatic PRKACA mutations with pregnancy-associated aldosterone- and cortisol-producing adenomas: a case report and literature review.

BACKGROUND: Somatic mutations have been observed to induce aldosterone-producing adenomas (APAs). These may be accelerated during pregnancy. Somatic PRKACA mutations are common in cortisol-producing adenomas (CPAs). However, their role in APAs, particularly aldosterone- and cortisol-producing adenomas (A/CPAs), is not well understood. This study aims to investigate the association between PRKACA mutations and the accelerated development of A/CPAs during pregnancy. CASE PRESENTATION: A patient with primary aldosteronism (PA) associated with severe Cushing's syndrome (CS) underwent surgical resection of an adrenal tumor one year after delivery. Pathologic examination revealed an adrenocortical adenoma characterized primarily by zona glomerulosa hyperplasia. Somatic mutation analysis revealed the presence of the somatic PRKACA mutation, which was validated as a deleterious mutation by various computational databases. Immunohistochemical results showed positive staining for cytochrome P450 family 11 subfamily B member 1 (CYP11B1), cytochrome P450 family 11 subfamily B member 2 (CYP11B2), and luteinizing hormone/chorionic gonadotropin receptor (LHCGR). Our study included a review of 20 previously documented cases of aldosterone- and cortisol-producing adenomas (A/CPAs), two of which were concurrently positive for both CYP11B1 and CYP11B2, consistent with our findings. CONCLUSION: Somatic mutations in PRKACA may correlate with the upregulation of LHCGR, which synergistically drives the accelerated growth of co-secretion tumors during pregnancy, thereby exacerbating disease progression.

In-situ methane enrichment in anaerobic digestion of food waste slurry by nano zero-valent iron: Long-term performance and microbial community succession.

In this work, nano zero-valent iron (nZVI) was added to a lab-scale continuous stirring tank reactor (CSTR) for food waste slurry treatment, and the effect of dosing rate and dosage of nZVI were attempted to be changed. The results showed that anaerobic digestion (AD) efficiency and biomethanation stability were optimum under the daily dosing and dosage of 0.48 g/gTCOD. The average daily methane (CH4) yield reached 495.38 mL/gTCOD, which was 43.65% higher than that at control stage, and the maximum CH4 content reached 95%. However, under single dosing rate conditions, high nZVI concentrations caused microbial cell rupture and loosely bound extracellular polymeric substances (LB-EPS) precipitation degradation. The daily dosing rate promoted the hydrogenotrophic methanogenesis pathway, and the activity of coenzyme F420 increased by 400.29%. The microbial analysis indicated that daily addition of nZVI could promote the growth of acid-producing bacteria (Firmicutes and Bacteroidetes) and methanogens (Methanothrix).

Short-axis PET image quality improvement based on a uEXPLORER total-body PET system through deep learning.

PURPOSE: The axial field of view (AFOV) of a positron emission tomography (PET) scanner greatly affects the quality of PET images. Although a total-body PET scanner (uEXPLORER) with a large AFOV is more sensitive, it is more expensive and difficult to widely use. Therefore, we attempt to utilize high-quality images generated by uEXPLORER to optimize the quality of images from short-axis PET scanners through deep learning technology while controlling costs. METHODS: The experiments were conducted using PET images of three anatomical locations (brain, lung, and abdomen) from 335 patients. To simulate PET images from different axes, two protocols were used to obtain PET image pairs (each patient was scanned once). For low-quality PET (LQ-PET) images with a 320-mm AFOV, we applied a 300-mm FOV for brain reconstruction and a 500-mm FOV for lung and abdomen reconstruction. For high-quality PET (HQ-PET) images, we applied a 1940-mm AFOV during the reconstruction process. A 3D Unet was utilized to learn the mapping relationship between LQ-PET and HQ-PET images. In addition, the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were employed to evaluate the model performance. Furthermore, two nuclear medicine doctors evaluated the image quality based on clinical readings. RESULTS: The generated PET images of the brain, lung, and abdomen were quantitatively and qualitatively compatible with the HQ-PET images. In particular, our method achieved PSNR values of 35.41 ± 5.45 dB (p < 0.05), 33.77 ± 6.18 dB (p < 0.05), and 38.58 ± 7.28 dB (p < 0.05) for the three beds. The overall mean SSIM was greater than 0.94 for all patients who underwent testing. Moreover, the total subjective quality levels of the generated PET images for three beds were 3.74 ± 0.74, 3.69 ± 0.81, and 3.42 ± 0.99 (the highest possible score was 5, and the minimum score was 1) from two experienced nuclear medicine experts. Additionally, we evaluated the distribution of quantitative standard uptake values (SUV) in the region of interest (ROI). Both the SUV distribution and the peaks of the profile show that our results are consistent with the HQ-PET images, proving the superiority of our approach. CONCLUSION: The findings demonstrate the potential of the proposed technique for improving the image quality of a PET scanner with a 320 mm or even shorter AFOV. Furthermore, this study explored the potential of utilizing uEXPLORER to achieve improved short-axis PET image quality at a limited economic cost, and computer-aided diagnosis systems that are related can help patients and radiologists.

TSAb Modulates Microglia M1 Polarization via Activation of the TSHR-Mediated NF-κB Signaling Pathway.

INTRODUCTION: Thyrotropin receptor-stimulating antibody (TSAb) is a pathogenic antibody in the serum of patients with Graves' disease. The binding of TSAb to thyroid-stimulating hormone receptor (TSHR) in non-thyroid tissue may be associated with the occurrence and development of Graves' disease-related complications. However, only few studies have been conducted on the effects of TSAb on the brain, and the pathogenesis of acute hyperthyroidism myopathy (ATM) is unclear. Therefore, this study aimed to explore the effect of TSAb on the polarization of BV-2 cells in the brain and its possible mechanism and provide a basic experimental basis for ATM. METHODS: BV-2 cells were treated with different concentrations of TSAb. The relative survival rate of BV-2 cells was determined using the CCK-8 assay; the migration ability of BV-2 cells was detected using the Transwell migration assay; and the expression levels of M1/M2 polarization markers (CD86, inducible nitric oxide synthase [iNOS], CD206, and arginase 1 [Arg-1]), TSHR, tumor necrosis factor-alpha (TNF-α), and nuclear factor-kappa B (NF-κB) protein in BV-2 cells were measured using WB. RESULTS: Compared with the negative control group, the proliferative activity of BV-2 cells was significantly increased in the 20, 50, and 100 ng/mL TSAb groups, and the migration ability of BV-2 cells was significantly enhanced in the 50 and 100 ng/mL TSAb groups. The expression levels of M1 polarization markers (CD86 and iNOS), TSHR, TNF-α, and NF-κB protein in BV-2 cells treated with 50 and 100 ng/mL TSAb for 24 h were significantly upregulated, whereas those of M2 polarization markers (CD206 and Arg-1) significantly decreased. CONCLUSIONS: TSAb can induce abnormal activation of microglia, polarize to the M1 phenotype, and promote the inflammatory cascade reaction, in which TSHR plays a key role in NF-κB activation and proinflammatory cytokine release.

Deep learning-based dynamic PET parametric Ki image generation from lung static PET.

OBJECTIVES: PET/CT is a first-line tool for the diagnosis of lung cancer. The accuracy of quantification may suffer from various factors throughout the acquisition process. The dynamic PET parametric Ki provides better quantification and improve specificity for cancer detection. However, parametric imaging is difficult to implement clinically due to the long acquisition time (~ 1 h). We propose a dynamic parametric imaging method based on conventional static PET using deep learning. METHODS: Based on the imaging data of 203 participants, an improved cycle generative adversarial network incorporated with squeeze-and-excitation attention block was introduced to learn the potential mapping relationship between static PET and Ki parametric images. The image quality of the synthesized images was qualitatively and quantitatively evaluated by using several physical and clinical metrics. Statistical analysis of correlation and consistency was also performed on the synthetic images. RESULTS: Compared with those of other networks, the images synthesized by our proposed network exhibited superior performance in both qualitative and quantitative evaluation, statistical analysis, and clinical scoring. Our synthesized Ki images had significant correlation (Pearson correlation coefficient, 0.93), consistency, and excellent quantitative evaluation results with the Ki images obtained in standard dynamic PET practice. CONCLUSIONS: Our proposed deep learning method can be used to synthesize highly correlated and consistent dynamic parametric images obtained from static lung PET. KEY POINTS: • Compared with conventional static PET, dynamic PET parametric Ki imaging has been shown to provide better quantification and improved specificity for cancer detection. • The purpose of this work was to develop a dynamic parametric imaging method based on static PET images using deep learning. • Our proposed network can synthesize highly correlated and consistent dynamic parametric images, providing an additional quantitative diagnostic reference for clinicians.

Whole fresh fruit intake and risk of incident diabetes in different glycemic stages: a nationwide prospective cohort investigation.

PURPOSE: Fruit intake is beneficial to several chronic diseases, but controversial in diabetes. We aimed to investigate prospectively the associations of whole fresh fruit intake with risk of incident type 2 diabetes (T2D) in subjects with different glucose regulation capacities. METHODS: The present study included 79,922 non-diabetic participants aged ≥ 40 years from an ongoing nationwide prospective cohort in China. Baseline fruit intake information was collected by a validated food frequency questionnaire. Plasma HbA1c, fasting and 2 h post-loading glucose levels were measured at both baseline and follow-up examinations. Cox proportional hazards models were used to calculate hazard ratio (HR) and 95% confidence intervals (CI) for incident diabetes among participants with normal glucose tolerance (NGT) and prediabetes, after adjusted for multiple confounders. Restricted cubic spline analysis was applied for dose-response relation. RESULTS: During a median 3.8-year follow-up, 5886 (7.36%) participants developed diabetes. Overall, we identified a linear and dose-dependent inverse association between dietary whole fresh fruit intake and risk of incident T2D. Each 100 g/d higher fruit intake was associated with 2.8% lower risk of diabetes (HR 0.972, 95%CI [0.949-0.996], P = 0.0217), majorly benefiting NGT subjects with 15.2% lower risk (HR 0.848, 95%CI [0.766-0.940], P = 0.0017), while not significant in prediabetes (HR 0.981, 95%CI 0.957-4.005, P = 0.1268). Similarly, the inverse association was present in normoglycemia individuals with a 48.6% lower risk of diabetes when consuming fruits > 7 times/week comparing to those < 1 time/week (HR 0.514, 95% CI [0.368-0.948]), but not in prediabetes (HR 0.883, 95% CI [0.762-1.023]). CONCLUSION: These findings suggest that higher frequency and amount of fresh fruit intake may protect against incident T2D, especially in NGT, but not in prediabetes, highlighting the dietary recommendation of higher fresh fruit consumption to prevent T2D in normoglycemia population.

Intracellular Rod Crystals in Chronic Lymphocytic Leukemia.

BACKGROUND: So far, rare cases of B cell lymphoproliferative diseases with rod crystals inclusions had been reported. METHODS: Wright's stain and MPO stain are used for cell and rod crystal staining while the immunophenotype examination, fluorescence in situ hybridization probes, routine G-band cytogenetic analysis and molecular biological tests are used to diagnose the disease which is chronic lymphocytic leukemia. RESULTS: One to six colorless rod-like crystals can be seen in some mature lymphocytes of the peripheral blood smear and also colorless by MPO staining. The immunophenotype examination with flow cytometry shows it is consistent with chronic lymphocytic leuke mia/B small lymphocytic lymphoma. CONCLUSIONS: The discovery of this rare phenomenon of rod-shaped crystallization in the peripheral blood may contribute to the diagnosis of lymphoproliferative diseases in B cells.

Parametric image generation with the uEXPLORER total-body PET/CT system through deep learning.

PURPOSE: Total-body dynamic positron emission tomography/computed tomography (PET/CT) provides much sensitivity for clinical imaging and research, bringing new opportunities and challenges regarding the generation of total-body parametric images. This study investigated parametric [Formula: see text] images directly generated from static PET images without an image-derived input function on a 2-m total-body PET/CT scanner (uEXPLORER) using a deep learning model to significantly reduce the dynamic scanning time and improve patient comfort. METHODS: [Formula: see text]F-Fluorodeoxyglucose ([Formula: see text]F-FDG) 2-m total-body PET/CT image pairs were acquired for 200 patients (scanned once) with two protocols: one parametric PET image (60 min, 0[Formula: see text]60 min) and one static PET image (10 min, range of 50[Formula: see text]60 min). A deep learning model was implemented to predict parametric [Formula: see text] images from the static PET images. Evaluation metrics, including the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and normalized mean square error (NMSE), were calculated for a 10-fold cross-validation assessment. Moreover, image quality was assessed by two nuclear medicine physicians in terms of clinical readings. RESULTS: The synthetic parametric PET images were qualitatively and quantitatively consistent with the reference images. In particular, the global mean SSIM between the synthetic and reference parametric [Formula: see text] images exceeded 0.9 across all test patients. On the other hand, the overall subjective quality of the synthetic parametric PET images was 4.00 ± 0.45 (the highest possible rating is 5) according to the two expert nuclear medicine physicians. CONCLUSION: The findings illustrated the feasibility of the proposed technique and its potential to reduce the required scanning duration for 2-m total-body dynamic PET/CT systems. Moreover, this study explored the potential of direct parametric image generation with uEXPLORER. Deep learning technologies may output high-quality synthetic parametric images, and the validation of clinical applications and the interpretability of network models still need further research in future works.

microRNA-206 Suppresses Cholangiocarcinoma Cell Growth and Invasion by Targeting Jumonji AT-Rich Interactive Domain 2.

BACKGROUND: The current study set out to elucidate the specific role of microRNA (miR)-206 in cholangiocarcinoma (CCA) cell biological activities by negatively modulating jumonji AT-rich interactive domain 2 (JARID2). METHODS: Firstly, human intrahepatic biliary epithelial cells and CCA cell lines were selected via the analysis of miR-206 and JARID2 expression patterns in CCA by qRT-PCR. Next, the target relation between miR-206 and JARID2 was predicted by Targetscan and validated using dual-luciferase reporter gene assay and RNA immunoprecipitation (RIP) assay. Subsequently, CCK-8 method, colony formation assay, scratch test, Transwell assay, and western blot analysis were performed to evaluate cancer cell development after the overexpression of miR-206 and/or JARID2, with levels of invasion-related proteins assessed. In addition, xenograft transplantation was also employed to confirm the role of miR-206 in vivo. Lastly, Ki-67 expression pattern was also quantified with immunohistochemistry. RESULTS: It was found that miR-206 was poorly expressed and JARID2 was highly expressed in CCA cell lines. Also, miR-206 overexpression brought about a suppressive effect on cancer cell proliferation, migration, and invasion. Furthermore, miR-206 was observed to target JARID2. Meanwhile, JARID2 overexpression promoted cell growth, while simultaneous overexpression of miR-206 and JARID2 impeded malignant cancer progression, indicating that miR-206 overexpression inhibited cell progression via targeting JARID2. Finally, in vivo experimentation illustrated that miR-206 overexpression suppressed tumor growth and weight, and inhibited the expressions of JARID2 N-cadherin, vimentin, and Ki-67. CONCLUSION: Altogether, our findings clarified that miR-206 inhibited CCA malignancy by negatively regulating JARID2.

MiR-122-5p promotes peritoneal fibrosis in a rat model of peritoneal dialysis by targeting Smad5 to activate Wnt/ß-catenin pathway.

Peritoneal fibrosis (PF) is the main reason leading to declining efficiency and ultrafiltration failure of peritoneum, which restricts the application of peritoneal dialysis (PD). We aimed to investigate the effects and mechanisms of miR-122-5p on the PF. Sprague-Dawley (SD) rats were infused with glucose-based standard PD fluid to establish PF model. HE staining was performed to evaluate the extent of PF. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR) and fluorescence in situ hybridization (FISH) were performed to measure the expression level of miR-122-5p. Western blot was used to test the expression of transforming growth factor (TGF)-ß1, platelet-derived growth factor (PDGF)-A, Fibronectin 1 (FN1), extracellular matrix protein 1 (ECM1), Smad5, α-smooth muscle actin (SMA), collagen type 1(COL-1), Vimentin, E-Cadherin, Wnt1, ß-catenin, p-ß-catenin, c-Myc, c-Jun, and Cyclin D1. Immunohistochemistry (IHC) staining was used to detect type I collagen alpha 1 (Col1α1), α-SMA, and E-Cadherin expression. We found PF was glucose concentration-dependently enhanced in peritoneum of PD rat. The PD rats showed increased miR-122-5p and decreased Smad5 expression. MiR-122-5p silencing improved PF and epithelial-mesenchymal transition (EMT) process in PD rats. MiR-122-5p silencing attenuated the activity of the Wnt/ß-catenin signaling pathway. Importantly, dual-luciferase reporter assay showed Smad5 was a target gene of miR-122-5p. Smad5 overexpression significantly reversed the increases of PF and EMT progression induced by miR-122-5p overexpression. Moreover, miR-122-5p mimic activated Wnt/ß-catenin activity, which was blocked by Smad5 overexpression. Overall, present results demonstrated that miR-122-5p overexpression showed a deterioration effect on PD-related PF by targeting Smad5 to activate Wnt/ß-catenin pathway.

Enhanced biogas biological upgrading from kitchen wastewater by in-situ hydrogen supply through nano zero-valent iron corrosion.

The in-situ hydrogen supply by nano zero-valent iron (nZVI, nFe0) corrosion provided a feasible way to improve the efficiency of biogas biological upgrading. This work studied the effects of nZVI at different dosages (0, 2, 4, 6, 8 and 10 g/L) on anaerobic digestion of kitchen wastewater by two buffer systems 2-[4-(2-hydroxyethyl) piperazin-1-yl] ethanesulfonic acid (HEPES) and sodium hydrogen carbonate (NaHCO3). The addition of nZVI improved the content of methane (CH4) and stability of anaerobic digestion process. In HEPES buffer system, the CH4 was all increased and the maximum reached 90.51% with 10 g/L nZVI, higher than 32.25% compared to the control. The maximum hydrogen enrichment (HE) was 113 ppb after nZVI addition, indicating the mass transfer efficiency of hydrogen (H2) was improved. Microbial community analysis showed that the total relative abundance of Methanobacterium and Methanolinea at 10 g/L nZVI was 53.72%, which was 1.62 times of the control group. However, in the NaHCO3 buffer system with 10 g/L nZVI addition, the content of CH4 and the loosely bound extracellular polymeric substances (LB-EPS) was lower than the control. The results indicated that the addition of nZVI was feasible for biogas upgrading, and the bidirectional effect of nZVI on the promotion or inhibition of bio-methanation might be related to the buffer system of the anaerobic process.

Characterization of algal organic matter as precursors for carbonaceous and nitrogenous disinfection byproducts formation: Comparison with natural organic matter.

Algal organic matter (AOM) and natural organic matter (NOM) from a typical eutrophic lake were comprehensively investigated in terms of their physico-chemical property, components and disinfection byproduct formation potentials (DBPFPs). The relationships between specific chemical properties of AOM and NOM with their corresponding DBPFPs were further evaluated during chlorination. Results indicated that AOM had lower specific UV absorbance (SUVA) but richer organic nitrogen contents than NOM. Fluorescence excitation emission matrix spectroscopy further demonstrated that AOM were chiefly composed of aromatic protein-like and soluble microbial byproduct-like matters, while NOM were mainly contributed from humic acid-like and soluble microbial byproduct-like substances. Although the molecular weight (MW) distribution of AOM and NOM showed no significant difference, size-exclusion chromatography with organic carbon as well as organic nitrogen detection (LC-OCD-OND) revealed that AOM were concentrated with the fraction of building blocks and NOM had higher concentrations of biopolymers and humics (HS). Moreover, AOM displayed higher DBPFPs than NOM, especially for nitrogenous DBPFP (N-DBPFP). MW < 1 kDa fractions both in AOM and NOM contributed the largest proportion to the formation of carbonaceous disinfection byproducts (C-DBPs). In addition, Pearson correlation analysis showed that bulk parameter SUVA was significantly relevant to the formation potentials of trihalomethane both in AOM and NOM, but was ineffective for carbonaceous DBPFP (C-DBPFP) prediction. Dissolved organic nitrogen contents in biopolymer and HS characterized by LC-OCD-OND had strong correlations with N-DBPFPs from AOM and NOM, indicating that LC-OCD-OND quantitative analysis could improve the prediction accuracy of the DBP formation than bulk parameters during NOM and AOM chlorination.

FaNet: fast assessment network for the novel coronavirus (COVID-19) pneumonia based on 3D CT imaging and clinical symptoms.

The novel coronavirus (COVID-19) pneumonia has become a serious health challenge in countries worldwide. Many radiological findings have shown that X-ray and CT imaging scans are an effective solution to assess disease severity during the early stage of COVID-19. Many artificial intelligence (AI)-assisted diagnosis works have rapidly been proposed to focus on solving this classification problem and determine whether a patient is infected with COVID-19. Most of these works have designed networks and applied a single CT image to perform classification; however, this approach ignores prior information such as the patient's clinical symptoms. Second, making a more specific diagnosis of clinical severity, such as slight or severe, is worthy of attention and is conducive to determining better follow-up treatments. In this paper, we propose a deep learning (DL) based dual-tasks network, named FaNet, that can perform rapid both diagnosis and severity assessments for COVID-19 based on the combination of 3D CT imaging and clinical symptoms. Generally, 3D CT image sequences provide more spatial information than do single CT images. In addition, the clinical symptoms can be considered as prior information to improve the assessment accuracy; these symptoms are typically quickly and easily accessible to radiologists. Therefore, we designed a network that considers both CT image information and existing clinical symptom information and conducted experiments on 416 patient data, including 207 normal chest CT cases and 209 COVID-19 confirmed ones. The experimental results demonstrate the effectiveness of the additional symptom prior information as well as the network architecture designing. The proposed FaNet achieved an accuracy of 98.28% on diagnosis assessment and 94.83% on severity assessment for test datasets. In the future, we will collect more covid-CT patient data and seek further improvement.

Identification of key candidate genes in neuropathic pain by integrated bioinformatic analysis.

This study aimed to disclose differentially expressed genes (DEGs) in dorsal root ganglia (DRGs) of neuropathic pain (NP) from spared nerve injury (SNI) model, thereby identifying specific and meaningful genetic targets for the diagnosis and treatment of NP. The GSE89224 was downloaded from the GEO database. DEGs were screened using the GEO2R online tool. Functional enrichment analysis of DEGs was then performed using the DAVID and constructed using the R ggplot2 package. Protein-protein interaction (PPI) network was constructed from the STRING database and visualized in Cytoscape software. MicroRNA targeting these DEGs was obtained from the TarBase and miRTarBase database, while transcription factor (TF)-targeting DEGs were predicted from the ENCODE database, both of which utilized the visual analytics platform NetworkAnayst. Finally, a merged microRNA-TF network was constructed based on the above two networks and was then analyzed with Cytoscape. Eighty DEGs were screened, only Vstm2b and Htr3a were downregulated and 78 genes were upregulated. The real-time polymerase chain reaction was applied to validate the gene expression of the top five DEGs (Npy, Atf3, Gpr151, Sprr1a, and Cckbr) in the DRG tissue 5 days after SNI surgery. It was found that Npy, Atf3, and Sprr1a have a significant increase after SNI stimulation, while Gpr151 and Cckbr showed a slight upward trend. Functional analysis was performed on all DEGs, of which 58 biological processes were enriched by gene ontology analysis, and 11 signaling pathways were enriched by KEGG analysis. In the PPI network, Atf3, Jun, Timp, and Npy had a higher degree. Thus, combined with various bioinformatic analyses, Npy and Atf3 may serve as the prognostic and therapeutic targets of NP. Key microRNA (mmu-mir-16-5p) and TF (MEF2A) were predicted to be associated with the pathogenetic process of NP with microRNA-TF regulatory network analysis, which were also identified as key regulators in the progression of NP.

Transcortical approach for insular gliomas: a series of 253 patients.

PURPOSE: The object of this study was to identify the distribution characteristics of insular gliomas and evaluate the efficiency of transcortical approach. METHODS: Insular gliomas patients who underwent transcortical approach for the first time between March 2011 and July 2019 at our institute were analyzed. RESULTS: A total of 253 primary insular gliomas patients were enrolled in the study. Of all patients, 176 patients (69.6%) underwent gross total resection, 61 patients (24.1%) underwent subtotal resection and 16 patients (6.3%) underwent partial resection. According to Berger-Sanai classification, the gross total resection rates of different types of insular gliomas were as follows: Zone I (90.1%), zone II (50.0%), zone III (40.0%), zone IV (89.5%), zone I + II (43.5%), zone I + IV (74.6%), zone II + III (44.4%), zone III + IV (41.7%), Giant (34.5%). According to our modified classification, the gross total resection rates were as follows: anterior type (84.9%), posterior type (45.8%), anterior-posterior type (42.9%), giant type (34.5%). After surgery, new limb motor deficit was observed in 28 patients (11.1%), and 5 patients (2.0%) were left long-term limb motor disability. New language impairment occurred in 23 patients (9.1%), and 3 patients (1.2%) were left long-term language disability. The patients were followed up for 1 to 89.2 months (average, 39.9 ± 20.3 months). At the end of follow-up, tumor progression occurred in 98 (38.7%) patients and 71 (28.1%) patients died of their disease. CONCLUSION: This study demonstrated that the maximal safe resection of insular gliomas can be achieved by transcortical approach. Insular gliomas had the characteristic of forward distribution, anterior transcortical approach can provide enough surgical freedom for anterior type of insular gliomas. If anterior tumors can make route to the posterior parts, anterior transcortical approach was also applied to some anterior-posterior and giant types of insular gliomas without resection of excessive brain, which may reduce the incidence of neurological complications.

Emerging role of miRNAs in renal fibrosis.

As one type of the most common endogenous short noncoding RNAs (ncRNAs), microRNAs (miRNAs) act as posttranscriptional regulators of gene expression and have great potential biological functions in the physiological and pathological processes of various diseases. The role of miRNAs in renal fibrosis has also attracted great attention in the previous 20 years, and new therapeutic strategies targeting miRNAs appear to be promising. Some researchers have previously reviewed the roles of miRNA in renal fibrosis disease, but numerous studies have emerged over the recent 5 years. It is necessary to update and summarize research progress in miRNAs in renal fibrosis. Thus, in this review, we summarize progress in miRNA-mediated renal fibrosis over the last 5 years and evaluate the biological functions of some miRNAs in different stages of renal fibrosis. Furthermore, we also expound the recent clinical applications of these miRNAs to provide new insights into the treatment of renal fibrosis disease.

Evaluation the impact of polystyrene micro and nanoplastics on the methane generation by anaerobic digestion.

The widespread existence of microplastics in wastewater has caused great concern. As the exposure time of microplastics in the environment increases, the microplastic leaching solution (i.e.,chemical additives) may be released into the environment causing toxic effects. In this study, the effect of polystyrene (PS) microplastics on the anaerobic digestion system was investigated. The results showed that the exposure to 80 nm and 5 µm polystyrene microplastics with the concentrations of 0.2 g/L or lower did not significantly affect the cumulative methane production (P ≥ 0.05). On the other hand, 80 nm and 5 µm PS microplastic level of 0.25 g/L led to a decrease in methane production by 19.3% (P = 2 × 10-5) and 17.9% (P = 4 × 10-5), respectively. The 80 nm PS nanoplastics therefore had slightly higher inhibition capacity on methane production than 5 µm PS microplastics. The pH of all groups remained stable at 6.7-7.5. Volatile fatty acids (VFAs) concentration and ammonium-nitrogen concentration had no obvious relationship to PS micro and nanoplastics addition. Further investigation showed that PS micro and nanoplastics concentration of 0.25 g/L or higher could inhibit acidification and methanation stage of anaerobic digestion. However, the main negative influence of PS micro and nanoplastics on methane production was due to the severe inhibition on the methanization stage.