Image-based artificial intelligence for the prediction of pathological complete response to neoadjuvant chemoradiotherapy in patients with rectal cancer: a systematic review and meta-analysis

OBJECTIVE

Artificial intelligence (AI) holds enormous potential for noninvasively identifying patients with rectal cancer who could achieve pathological complete response (pCR) following neoadjuvant chemoradiotherapy (nCRT). We aimed to conduct a meta-analysis to summarize the diagnostic performance of image-based AI models for predicting pCR to nCRT in patients with rectal cancer.

METHODS

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A literature search of PubMed, Embase, Cochrane Library, and Web of Science was performed from inception to July 29, 2023. Studies that developed or utilized AI models for predicting pCR to nCRT in rectal cancer from medical images were included. The Quality Assessment of Diagnostic Accuracy Studies-AI was used to appraise the methodological quality of the studies. The bivariate random-effects model was used to summarize the individual sensitivities, specificities, and areas-under-the-curve (AUCs). Subgroup and meta-regression analyses were conducted to identify potential sources of heterogeneity. Protocol for this study was registered with PROSPERO (CRD42022382374).

RESULTS

Thirty-four studies (9933 patients) were identified. Pooled estimates of sensitivity, specificity, and AUC of AI models for pCR prediction were 82% (95% CI: 76-87%), 84% (95% CI: 79-88%), and 90% (95% CI: 87-92%), respectively. Higher specificity was seen for the Asian population, low risk of bias, and deep-learning, compared with the non-Asian population, high risk of bias, and radiomics (all P < 0.05). Single-center had a higher sensitivity than multi-center (P = 0.001). The retrospective design had lower sensitivity (P = 0.012) but higher specificity (P < 0.001) than the prospective design. MRI showed higher sensitivity (P = 0.001) but lower specificity (P = 0.044) than non-MRI. The sensitivity and specificity of internal validation were higher than those of external validation (both P = 0.005).

CONCLUSIONS

Image-based AI models exhibited favorable performance for predicting pCR to nCRT in rectal cancer. However, further clinical trials are warranted to verify the findings.

pGM-CSF as an adjuvant in DNA vaccination against SARS-CoV-2

The emergence of SARS-CoV-2 presents a significant global public health dilemma. Vaccination has long been recognized as the most effective means of preventing the spread of infectious diseases. DNA vaccines have attracted attention due to their safety profile, cost-effectiveness, and ease of production. This study aims to assess the efficacy of plasmid-encoding GM-CSF (pGM-CSF) as an adjuvant to augment the specific humoral and cellular immune response elicited by DNA vaccines based on the receptor-binding domain (RBD) antigen. Compared to the use of plasmid-encoded RBD (pRBD) alone, mice that were immunized with a combination of pRBD and pGM-CSF exhibited significantly elevated levels of RBD-specific antibody titers in serum, BALF, and nasal wash. Furthermore, these mice generated more potent neutralization antibodies against both the wild-type and Omicron pseudovirus, as well as the ancestral virus. In addition, pGM-CSF enhanced pRBD-induced CD4+ and CD8+ T cell responses and promoted central memory T cells storage in the spleen. At the same time, tissue-resident memory T (Trm) cells in the lung also increased significantly, and higher levels of specific responses were maintained 60 days post the final immunization. pGM-CSF may play an adjuvant role by promoting antigen expression, immune cells recruitment and GC B cell responses. In conclusion, pGM-CSF may be an effective adjuvant candidate for the DNA vaccines against SARS-CoV-2.

Automated and reusable deep learning (AutoRDL) framework for predicting response to neoadjuvant chemotherapy and axillary lymph node metastasis in breast cancer using ultrasound images: a retrospective, multicentre study

Background

Previous deep learning models have been proposed to predict the pathological complete response (pCR) and axillary lymph node metastasis (ALNM) in breast cancer. Yet, the models often leveraged multiple frameworks, required manual annotation, and discarded low-quality images. We aimed to develop an automated and reusable deep learning (AutoRDL) framework for tumor detection and prediction of pCR and ALNM using ultrasound images with diverse qualities.

Methods

The AutoRDL framework includes a You Only Look Once version 5 (YOLOv5) network for tumor detection and a progressive multi-granularity (PMG) network for pCR and ALNM prediction. The training cohort and the internal validation cohort were recruited from Guangdong Provincial People's Hospital (GPPH) between November 2012 and May 2021. The two external validation cohorts were recruited from the First Affiliated Hospital of Kunming Medical University (KMUH), between January 2016 and December 2019, and Shunde Hospital of Southern Medical University (SHSMU) between January 2014 and July 2015. Prior to model training, super-resolution via iterative refinement (SR3) was employed to improve the spatial resolution of low-quality images from the KMUH. We developed three models for predicting pCR and ALNM: a clinical model using multivariable logistic regression analysis, an image model utilizing the PMG network, and a combined model that integrates both clinical and image data using the PMG network.

Findings

The YOLOv5 network demonstrated excellent accuracy in tumor detection, achieving average precisions of 0.880-0.921 during validation. In terms of pCR prediction, the combined modelpost-SR3 outperformed the combined modelpre-SR3, image modelpost-SR3, image modelpre-SR3, and clinical model (AUC: 0.833 vs 0.822 vs 0.806 vs 0.790 vs 0.712, all p < 0.05) in the external validation cohort (KMUH). Consistently, the combined modelpost-SR3 exhibited the highest accuracy in ALNM prediction, surpassing the combined modelpre-SR3, image modelpost-SR3, image modelpre-SR3, and clinical model (AUC: 0.825 vs 0.806 vs 0.802 vs 0.787 vs 0.703, all p < 0.05) in the external validation cohort 1 (KMUH). In the external validation cohort 2 (SHSMU), the combined model also showed superiority over the clinical and image models (0.819 vs 0.712 vs 0.806, both p < 0.05).

Interpretation

Our proposed AutoRDL framework is feasible in automatically predicting pCR and ALNM in real-world settings, which has the potential to assist clinicians in optimizing individualized treatment options for patients.

Funding

National Key Research and Development Program of China (2023YFF1204600); National Natural Science Foundation of China (82227802, 82302306); Clinical Frontier Technology Program of the First Affiliated Hospital of Jinan University, China (JNU1AF-CFTP-2022-a01201); Science and Technology Projects in Guangzhou (202201020022, 2023A03J1036, 2023A03J1038); Science and Technology Youth Talent Nurturing Program of Jinan University (21623209); and Postdoctoral Science Foundation of China (2022M721349).

An interpretable machine learning model based on contrast-enhanced CT parameters for predicting treatment response to conventional transarterial chemoembolization in patients with hepatocellular carcinoma

OBJECTIVE

To explore the potential of pre-therapy computed tomography (CT) parameters in predicting the treatment response to initial conventional TACE (cTACE) in intermediate-stage hepatocellular carcinoma (HCC) and develop an interpretable machine learning model.

METHODS

This retrospective study included 367 patients with intermediate-stage HCC who received cTACE as first-line therapy from three centers. We measured the mean attenuation values of target lesions on multi-phase contrast-enhanced CT and further calculated three CT parameters, including arterial (AER), portal venous (PER), and arterial portal venous (APR) enhancement ratios. We used logistic regression analysis to select discriminative features and trained three machine learning models via 5-fold cross-validation. The performance in predicting treatment response was evaluated in terms of discrimination, calibration, and clinical utility. Afterward, a Shapley additive explanation (SHAP) algorithm was leveraged to interpret the outputs of the best-performing model.

RESULTS

The mean diameter, ECOG performance status, and cirrhosis were the important clinical predictors of cTACE treatment response, by multiple logistic regression. Adding the CT parameters to clinical variables showed significant improvement in performance (net reclassification index, 0.318, P < 0.001). The Random Forest model (hereafter, RF-combined model) integrating CT parameters and clinical variables demonstrated the highest performance on external validation dataset (AUC of 0.800). The decision curve analysis illustrated the optimal clinical benefits of RF-combined model. This model could successfully stratify patients into responders and non-responders with distinct survival (P = 0.001).

CONCLUSION

The RF-combined model can serve as a robust and interpretable tool to identify the appropriate crowd for cTACE sessions, sparing patients from receiving ineffective and unnecessary treatments.

Cationic Nanoemulsion-Encapsulated Retinoic Acid as an Adjuvant to Promote OVA-Specific Systemic and Mucosal Responses

Cationic nanostructures have emerged as an adjuvant and antigen delivery system that enhances dendritic cell maturation, ROS generation, and antigen uptake and then promotes antigen-specific immune responses. In recent years, retinoic acid (RA) has received increasing attention due to its effect in activating the mucosal immune response; however, in order to use RA as a mucosal adjuvant, it is necessary to solve the problem of its dissolution, loading, and delivery. Here, we describe a cationic nanoemulsion-encapsulated retinoic acid (CNE-RA) delivery system composed of the cationic lipid 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOTAP), retinoic acid, squalene as the oil phase, polysorbate 80 as surfactant, and sorbitan trioleate 85 as co-surfactant. Its physical and chemical properties were characterized using dynamic light scattering and a spectrophotometer. Immunization of mice with the mixture of antigen (ovalbumin, OVA) and CNE-RA significantly elevated the levels of anti-OVA secretory immunoglobulin A (sIgA) in vaginal lavage fluid and the small intestinal lavage fluid of mice compared with OVA alone. This protocol describes a detailed method for the preparation, characterization, and evaluation of the adjuvant effect of CNE-RA.

Akkermansia muciniphila-derived small extracellular vesicles attenuate intestinal ischemia-reperfusion-induced postoperative cognitive dysfunction by suppressing microglia activation via the TLR2/4 signaling

Akkermansia muciniphila (AKK) bacteria improve the functions of theere intestinal and blood-brain barriers (BBB) via their extracellular vesicles (AmEvs). However, their role in postoperative cognitive dysfunction (POCD) and its underlying mechanisms remain unclear. To investigate, we used C57BL/6 J mice divided into five groups: Sham, POCD, POCD+Akk, POCD+Evs, and POCD+Evs + PLX5622. POCD was induced through intestinal ischemia-reperfusion (I/R). The mice's cognitive function was assessed using behavioral tests, and possible mechanisms were explored by examining gut and BBB permeability, inflammation, and microglial function. Toll-like receptor (TLR) 2/4 pathway-related proteins were also investigated both in vitro and in vivo. PLX5622 chow was employed to eliminate microglial cells. Our findings revealed a negative correlation between AKK abundance and POCD symptoms. Supplementation with either AKK or AmEvs improved cognitive function, improved the performance of the intestinal barrier and BBB, and decreased inflammation and microglial activation in POCD mice compared to controls. Moreover, AmEvs treatment inhibited TLR2/4 signaling in the brains of POCD mice and LPS-treated microglial cells. In microglial-ablated POCD mice, however, AmEvs failed to protect BBB integrity. Overall, AmEvs is a potential therapeutic strategy for managing POCD by enhancing gut and BBB integrity and inhibiting microglial-mediated TLR2/4 signaling.

Hi-Tag: a simple and efficient method for identifying protein-mediated long-range chromatin interactions with low cell numbers

Protein-mediated chromatin interactions can be revealed by coupling proximity-based ligation with chromatin immunoprecipitation. However, these techniques require complex experimental procedures and millions of cells per experiment, which limits their widespread application in life science research. Here, we develop a novel method, Hi-Tag, that identifies high-resolution, long-range chromatin interactions through transposase tagmentation and chromatin proximity ligation (with a phosphorothioate-modified linker). Hi-Tag can be implemented using as few as 100,000 cells, involving simple experimental procedures that can be completed within 1.5 days. Meanwhile, Hi-Tag is capable of using its own data to identify the binding sites of specific proteins, based on which, it can acquire accurate interaction information. Our results suggest that Hi-Tag has great potential for advancing chromatin interaction studies, particularly in the context of limited cell availability.

Correlation of morning dry mouth with clinical features of OSA in a community population: a cross-sectional study

OBJECTIVES

Morning dry mouth, commonly seen in Obstructive Sleep Apnea (OSA) patients, is absent in current OSA screening tools. This study evaluated the link between morning dry mouth and OSA's clinical symptoms and complications, aiming to determine its viability as a screening indicator.

METHODS

This research analyses baseline data from a prospective cohort study (the PIFCOPD study). Demographic information, medical history, and the presence of morning dry mouth symptoms were collected. The STOP-Bang questionnaire was performed for OSA screening. Logistic regression analyses were employed to establish the correlations between morning dry mouth and the clinical symptoms and comorbidities of OSA.

RESULT

1291 participants (62.1±7.5 years; 501 males, 790 females) were included, of which 416 reported morning dry mouth (32.2%). 42.6% in the high-risk OSA group and 22.1% in the low-risk group reported morning dry mouth. Individuals with morning dry mouth also showed higher STOP-Bang scores (3.3±1.6 vs. 2.3±1.4, P<0.01). Significant associations were found between morning dry mouth and loud snoring, observed sleep apnea, daytime fatigue, and hyperlipidemia (P<0.01), but not with alcohol consumption, tea consumption, diabetes, or hypertension.

CONCLUSION

Morning dry mouth is associated with increased OSA risk and its clinical signs, suggesting its potential as an OSA screening symptom.

CLINICAL TRIAL REGISTRATION

This study has been registered at www.ClinicalTrials.gov (registration identifier: NCT03532893) on 21 May 2018.

Harnessing artificial intelligence to improve clinical trial design

Zhang et al. discuss how artificial intelligence (AI) can be used to optimize clinical trial design and potentially boost the success rate of clinical trials. AI has unparalleled potential to leverage real-world data and unlock valuable insights for innovative trial design.

Leveraging machine learning to distinguish between bacterial and viral induced pharyngitis using hematological markers: a retrospective cohort study

Accurate differentiation between bacterial and viral-induced pharyngitis is recognized as essential for personalized treatment and judicious antibiotic use. From a cohort of 693 patients with pharyngitis, data from 197 individuals clearly diagnosed with bacterial or viral infections were meticulously analyzed in this study. By integrating detailed hematological insights with several machine learning algorithms, including Random Forest, Neural Networks, Decision Trees, Support Vector Machine, Naive Bayes, and Lasso Regression, for potential biomarkers were identified, with an emphasis being placed on the diagnostic significance of the Monocyte-to-Lymphocyte Ratio. Distinct inflammatory signatures associated with bacterial infections were spotlighted in this study. An innovation introduced in this research was the adaptation of the high-accuracy Lasso Regression model for the TI-84 calculator, with an AUC (95% CI) of 0.94 (0.925-0.955) being achieved. Using this adaptation, pivotal laboratory parameters can be input on-the-spot and infection probabilities can be computed subsequently. This methodology embodies an improvement in diagnostics, facilitating more effective distinction between bacterial and viral infections while fostering judicious antibiotic use.

Association between adjuvant chemotherapy and survival in stage I gastric cancer patients after curative resection

Background

The efficacy of adjuvant chemotherapy (AC) on survival outcomes of patients with stage I gastric cancer (GC) after curative resection remains controversial. We aimed to determine whether these patients would benefit from AC.

Methods

This retrospective study included patients with pathologically confirmed stage I GC who underwent curative resection between November 2010 and December 2020. Patients were divided into AC and non-AC groups, then a 1:1 propensity score matching (PSM) analysis was performed to minimize the selection bias. Potential risk factors including age, pN stage, pT stage, lymphovascular invasion, perineural invasion, tumor size, histological type, and carcinoembryonic antigen level were used as matching covariates. The recurrence-free survival (RFS) and disease-specific survival (DSS) were compared between groups using the Kaplan-Meier method.

Results

A total of 902 consecutive patients were enrolled and 174 (19.3%) patients were treated with AC. PSM created 123 pairs of patients. Before PSM, patients receiving AC had lower 10-year RFS rates (90% vs 94.6%, P = 0.035) than those who did not receive AC; the two groups had similar 10-year DSS rates (93.8% vs 95.0%, P = 0.240). After PSM, there were no statistical differences in the 10-year RFS (90.9% vs 93.0%, P = 0.507) or DSS rates (93.5% vs 93.6%, P = 0.811) between the two groups. Similar results were found in the stage IA and IB subgroups. Moreover, these findings were not affected by AC cycles.

Conclusions

The addition of AC could not provide survival benefits for patients with stage I GC after surgery and follow-up is thus recommended. However, large-scale randomized clinical trials are required.

Characteristics and feasibility of ambulatory respiratory assessment of paediatric neuromuscular disease: an observational retrospective study

PURPOSE

To investigate the characteristics of respiratory involvement in Chinese paediatric neuromuscular disease (NMD) at early stage and to explore convenient monitoring methods.

MATERIALS AND METHODS

Children with NMD (age < 18) diagnosed at a multidisciplinary joint NMD clinic at Peking University First Hospital from January 2016 to April 2021 were included. Overnight polysomnography (PSG) and pulmonary function test (PFT) data were analysed, and the characteristics of four groups: congenital muscular dystrophy (CMD), congenital myopathy, spinal muscular atrophy, and Duchenne muscular dystrophy (DMD) were compared.

RESULTS

A total of 83 children with NMD were referred for respiratory assessment, of who 80 children underwent PSG; 41 performed spirometry and 38, both. The duration of pulse oxygen saturation (SpO2) <90% over apnoea and hypopnoea index (AHI) was lowest in DMD and significantly different from CMD (p = 0.033). AHI was positively correlated with the oxygen desaturation index (ODI) (r = 0.929, p = 0.000). The peak expiratory flow (PEF) were positively correlated with forced vital capacity (FVC), both as actual values and percent pred, respectively (r = 0.820, 0.719, p = 0.000). ROC derived sensitivity and specificity of prediction of AHI > 15/h or duration of SpO2<90% ≥ 60 min from FVC <51% pred was 75.8% and 85.7%, respectively.

CONCLUSIONS

AHI and hypoxia burden were independent factors in children with NMD in PSG and attention needed to be paid in both. FVC might be a daytime predictor for significant sleep-disordered breathing or hypoxia. Nocturnal consecutive oximetry with diurnal peak flow measurement may be convenient and effective for home monitoring at early stage of respiratory involvement.

Anti-influenza virus activities and mechanism of antrafenine analogs

Antrafenine is a drug initially designed for anti-inflammation uses. In this work we have synthesized a library of its structural analogs and tested the anti-influenza activities. These analogs belong to a group of 2-(quinolin-4-yl)amino benzamides or 2-(quinolin-4-yl)amino benzoate derivatives. Best performers were identified, namely 12, 34, 41, with IC50 against A/WSN/33 (H1N1) of 5.53, 3.21 and 6.73 μM respectively. These chemicals were also effective against A/PR/8/34 (H1N1), A/HK/1/68 (H3N2) and B/Florida/04/2006 viruses. Time-of-addition study and minigenome luciferase reporter assay both supported that the compounds act on the ribonucleoprotein (RNP) components. Using 34 and 41 as representative compounds, we determined by microscale thermophoresis that this group of compounds bind to both PA C-terminal domain and the nucleoprotein (NP) which is the most abundant subunit of the RNP. Taken together, we have identified a new class of anti-influenza compounds with dual molecular targets and good potential to be further developed. IMPORTANCE: The influenza viruses, especially influenza A and B subtypes, cause many deaths each year. The high mutation rate of the virus renders available therapeutics less effective with time. In this work we identify a new class of compounds, structurally similar to the anti-inflammation drug antrafenine, with good potency against influenza A strains. The IC50 of the best performers are within low micromolar range and thus have good potential for further development.

A novel indolylbenzoquinone compound HL-J6 suppresses biofilm formation and α-toxin secretion in methicillin-resistant Staphylococcus aureus

Eradication of methicillin-resistant Staphylococcus aureus (MRSA) is challenging due to multi-drug resistance of strains and biofilm formation, the latter of which is an important barrier to the penetration of antibiotics and host defences. As such, there is an urgent need to discover and develop novel agents to fight MRSA-associated infection. In this study, HL-J6, a novel indolylbenzoquinone compound, was shown to inhibit S. aureus strains, with a minimum inhibitory concentration against MRSA252 of 2 µg/mL. Moreover, HL-J6 exhibited potent antibiofilm activity in vitro and was able to kill bacteria in biofilm. In the mouse models of wound infection, HL-J6 treatment reduced the MRSA load significantly and inhibited biofilm formation on the wounds. The potent targets of its antibiofilm activity were explored by real-time reverse transcriptase polymerase chain rection, which indicated that HL-J6 downregulated the transcription levels of sarA, atlAE and icaADBC. Moreover, Western blot results showed that HL-J6 reduced the secretion level of α-toxin, a major virulence factor. These findings indicate that HL-J6 is a promising lead compound for the development of novel drugs against MRSA biofilm infections.

[Effects of Quercetin-3-O-β-D-Glucuronide on Platelet Apoptosis and Activation in Mice with Immune-Mediated Bone Marrow Failure via PI3K/AKT Pathway]

OBJECTIVE

To investigate the effect of quercetin-3-O-β-D-glucuronide(QG) on platelet apoptosis and activation in mice with immune-mediated bone marrow failure via PI3K/AKT pathway.

METHODS

An immune-mediated bone marrow failure mice model was established and forty C57BL/6 mice were randomly assigned into 4 groups: normal group, model group,cyclosporine (CsA) group and QG group, with 10 mice in each group.The mice in CsA group were intragastrically administered with 0.027 g/kg CsA daily and the mice in QG group were intragastrically administered with 0.2 g/kg QG daily, while the mice in the normal group and model group were intragastrically administered with normal saline, respectively. After three days of modeling, the mice were euthanized, and the blood was collected through the tail vein. Part of the blood was used for blood routine examination, and the other part was used to prepare washed platelets. Some of the prepared washed platelets were used to detect the expressions of BAX, BAD, caspase-9, phosphatidylserine (PS), platelet activated complex-1 (PAC-1) and P-selectin by flow cytometry; some of washed platelets was used to determine the protein contents of PI3K, p-PI3k, AKT and p-AKT by Western blot; the other part of the washed platelets was used to measure the expressions of PI3K mRNA and AKT mRNA by real-time quantitative PCR (RT-qPCR).

RESULTS

In the model group, the absolute platelet count of the mice was significantly decreased, and the levels of BAX, BAD, caspase-9, PS, PAC-1, and P-selectin in the washed platelets were significantly increased, compared to the normal group (P<0.05). At the same time, the expression levels of PI3K, p-PI3K, AKT, p-AKT proteins and PI3K mRNA, AKT mRNA in model group were significantly reduced, compared to the normal group (P<0.05). In the CsA group and QG group, the expression levels of BAX, BAD, caspase-9, PS, PAC-1, and P-selectin in the washed platelets were significantly reduced (P<0.05), while the levels of PI3K, p-PI3K, AKT, p-AKT and PI3K mRNA, AKT mRNA were significantly increased, compared to the model group (P<0.05).

CONCLUSION

QG can reduce platelet apoptosis in mice with immune-mediated bone marrow failure, and activation of some platelets is involved, which may be related to the regulation of PI3K/AKT pathway.

Morin protects chicks with T-2 toxin poisoning by decreasing heterophil extracellular traps, oxidative stress and inflammatory response

1. Fusarium tritici widely exists in a variety of grain feeds. The T-2 toxin is the main hazardous component produced by Fusarium tritici, making a serious hazard to poultry industry. Morin, belonging to the flavonoid family, can be extracted from mulberry plants and possesses anticancer, antioxidant and anti-inflammatory compounds, but whether morin protects chicks with T-2 toxin poisoning remains unclear. This experiment firstly established a chick model of T-2 toxin poisoning and then investigated the protective effects and mechanism of morin against T-2 toxin in chicks.2. The function of liver and kidney was measured by corresponding alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), blood urea nitrogen (BUN), creatinine (Cre) and uric acid (UA) kits. Histopathological changes were observed by haematoxylin-eosin staining. The status of oxidative stress was measured by MDA, SOD, CAT, GSH and GSH-PX kits. The mRNA levels of TNF-α, COX-2, IL-1β, IL-6, caspase-1, caspase-3 and caspase-11 were measured by quantitative real-time PCR. Heterophil extracellular trap (HET) release was analysed by immunofluorescence and fluorescence microplate.3. The model with T-2 toxin poisoning in chicks was successfully established. Morin significantly decreased T-2 toxin-induced ALT, AST, ALP, BUN, Cre and UA, and improved T-2 toxin-induced liver cell rupture, liver cord disorder and kidney interstitial oedema. Oxidative stress analysis showed that morin ameliorated T-2 toxin-induced damage by reducing malondialdehyde (MDA), increasing superoxide dismutase (SOD), catalase (CAT), glutathione (GSH) and glutathione peroxidase (GSH-PX). The qRT-PCR analysis showed that morin reduced T-2 toxin-induced mRNA expressions of TNF-α, COX-2, IL-1β, IL-6, caspase-1, caspase-3 and caspase-11. Moreover, morin significantly reduced the release of T-2 toxin-induced HET in vitro and in vivo.4. Morin can protect chicks from T-2 toxin poisoning by decreasing HETs, oxidative stress and inflammatory responses, which make it a useful compound against T-2 toxin poisoning in poultry feed.

Comparative Study of C-TIRADS, ACR-TIRADS, and EU-TIRADS for Diagnosis and Management of Thyroid Nodules

RATIONALE AND OBJECTIVES

Chinese Thyroid Imaging Reporting and Data Systems (C-TIRADS) was developed to provide a more simplified tool for stratifying thyroid nodules. Here we aimed to validate the efficacy of C-TIRADS in distinguishing benign from malignant and in guiding fine-needle aspiration biopsies in comparison with the American College of Radiology TIRADS (ACR-TIRADS) and European TIRADS (EU-TIRADS).

MATERIALS AND METHODS

This study retrospectively included 3438 thyroid nodules (≥10 mm) in 3013 patients (mean age, 47.1 years ± 12.9) diagnosed between January 2013 and November 2019. Ultrasound features of the nodules were evaluated and categorized according to the lexicons of the three TIRADS. We compared these TIRADS by using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), sensitivity, specificity, net reclassification improvement (NRI), and unnecessary fine-needle aspiration biopsy (FNAB) rate.

RESULTS

Of the 3438 thyroid nodules, 707 (20.6%) were malignant. C-TIRADS showed higher discrimination performance (AUROC, 0.857; AUPRC, 0.605) than ACR-TIRADS (AUROC, 0.844; AUPRC, 0.567) and EU-TIRADS (AUROC, 0.802; AUPRC, 0.455). The sensitivity of C-TIRADS (85.3%) was lower than that of ACR-TIRADS (89.1%) but higher than that of EU-TIRADS (78.4%). The specificity of C-TIRADS (76.9%) was similar to that of EU-TIRADS (78.9%) and higher than that of ACR-TIRADS (69.5%). The unnecessary FNAB rate was lowest with C-TIRADS (21.2%), followed by ACR-TIRADS (41.7%) and EU-TIRADS (58.3%). C-TIRADS obtained significant NRI for recommending FNAB over ACR-TIRADS (19.0%, P < 0.001) and EU-TIRADS (25.5%, P < 0.001).

CONCLUSION

C-TIRADS may be a clinically applicable tool to manage thyroid nodules, which warrants thorough tests in other geographic settings.

Estrogen regulates duodenal glucose absorption by affecting estrogen receptor-α on glucose transporters

The mechanisms of estrogen in glucose metabolism are well established; however, its role in glucose absorption remains unclear. In this study, we investigated the effects of estrogen on glucose absorption in humans, mice, and SCBN intestinal epithelial cells. We first observed a correlation between estrogen and blood glucose in young women and found that glucose tolerance was significantly less in the premenstrual phase than in the preovulatory phase. Similarly, with decreased serum estradiol levels in ovariectomized mice, estrogen receptors alpha (ERα) and beta (ERβ) in the duodenum were reduced, and weight and abdominal fat increased significantly. The expression of sodium/glucose cotransporter 1 (SGLT1) and glucose transporter 2 (GLUT2) and glucose absorption in the duodenum decreased significantly. Estrogen significantly upregulated SGLT1 and GLUT2 expression in SCBN cells. Silencing of ERα, but not ERβ, reversed this trend, suggesting that ERα may be key to estrogen-regulating glucose transporters. A mechanistic study revealed that downstream, estrogen regulates the protein kinase C (PKC) pathway. Overall, our findings indicate that estrogen promotes glucose absorption, and estrogen and ERα deficiency can inhibit SGLT1 and GLUT2 expression through the PKC signaling pathway, thereby reducing glucose absorption.

The m6A reader YTHDC1-mediated lncRNA CTBP1-AS2 m6A modification accelerates cholangiocarcinoma progression

Background

Cholangiocarcinoma (CCA) is a serious malignancy originating from the bile ducts and the second most common primary liver cancer. Long non-coding RNA (lncRNA) is a functional lncRNA that plays an important role in human cancers. However, the role and underlying mechanisms of CTBP1-AS2 in CCA remain unknown.

Purpose

In this study, we investigated the functional role and mechanism of long-stranded non-coding RNA (lncRNA) C-terminal binding protein 1 antisense RNA 2 (CTBP1-AS2) in CCA progression.

Result

In the present study, the bioinformatics analysis revealed that YTHDC1 and CTBP1-AS2 were significantly upregulated, and it was confirmed in cholangiocarcinoma tissues from CCA patients. Meanwhile, we demonstrated that knockdown of YTHDC1 or lncRNA CTBP1-AS2 inhibited CCA cell proliferation, migration and invasion, blocked the cell cycle in G2/M phase and promoted apoptosis of CCA cells. In addition, lncRNA CTBP1-AS2-mediated N6-methyladenosine (m6A) methylation levels were significantly elevated in cholangiocarcinoma tissues, whereas knockdown of YTHDC1 resulted in a significant down-regulation of m6A methylation levels by lncRNA CTBP1-AS2.

Conclusion

Our results suggest that YTHDC1 affects cholangiocarcinoma progression by modifying the lncRNA CTBP1-AS2 m6A, and CTBP1-AS2 may be a promising therapeutic target for CCA.

Synthetic Self-Adjuvanted Lipopeptide Vaccines Conferred Protection against Helicobacter pylori Infection

Helicobacter pylori (H. pylori) colonizes the stomach epithelium of half the world's population and is responsible for various digestive diseases and even stomach cancer. Vaccine-mediated protection against H. pylori infection depends primarily on the specific mucosal and T-cell responses. In this study, the synthetic lipopeptide vaccines, Hp4 (Pam2 Cys modified UreB T-cell epitope) and Hp10 (Pam2 Cys modified CagA T/B cell combined epitope), not only induce the bone marrow derived dendritic cells (BMDCs) maturation by activating a variety of pattern-recognition receptors (PRRs) such as Toll-like receptor (TLR), Nod-like receptor (NLR), and retinoic acid-inducing gene (RIG) I-like receptor (RLR), and but also stimulate BMDCs to secret cytokines that have the potential to modulate T-cell activation and differentiation. Although intranasal immunization with Hp4 or Hp10 elicits robust epitope-specific T-cell responses in mice, only Hp10 confers protection against H. pylori infection, possibly due to the fact that Hp10 also induces substantial specific sIgA response at mucosal sites. Interestingly, Hp4 elevates the protective response against H. pylori infection of Hp10 when administrated in combination, characterized by better protective effect and enhanced specific T-cell and mucosal antibody responses. The results suggest that synthetic lipopeptide vaccines based on the epitopes derived from the protective antigens are promising candidates for protection against H. pylori infection.

Optimal design of surface CO2 observation network to constrain China's land carbon sink

Accurate estimate of the size of land carbon sink is essential for guiding climate mitigation actions to fulfill China's net-zero ambitions before 2060. The atmospheric inversion is an effective approach to provide spatially explicit estimate of surface CO2 fluxes that are optimally consistent with atmospheric CO2 measurements. But atmospheric inversion of China's land carbon sink has enormous uncertainties, with one major source arising from the poor coverage of CO2 observation stations. Here we use a regional atmospheric inversion framework to design an observation network that could minimize uncertainties in inverted estimate of China's land carbon sink. Compared with the large spread of inverted sink (∼1PgCa-1) from state-of-the-art inversions using existing CO2 observations, the uncertainty is constrained within 0.3PgCa-1 when a total of 30 stations were deployed, and is further reduced to approximately 0.2PgCa-1 when 60 stations were deployed. The proposed stations are mostly distributed over areas with high biosphere productivity during the growing season, such as Southeast China, Northeast China, North China, and the Tibetan Plateau. Moreover, the proposed stations can cover areas where existing satellites have limited coverage due to cloud shadowing in the monsoon season or over complex topography. Such ground-based observation network will be a critical component in the future integrated observing system for monitoring China's land carbon fluxes.

Corrigendum: Identification of circRNA biomarker for gastric cancer through integrated analysis

[This corrects the article DOI: 10.3389/fmolb.2022.857320.].

Use of 6-minute walk test for assessing severity of interstitial lung disease: an observational study

BACKGROUND

The 6-minute walk test (6MWT) is a potential tool for assessing the severity of interstitial lung disease (ILD).

OBJECTIVES

To explore the relationship between 6MWT results and traditional measures including pulmonary function and chest computed tomography(CT) and to determine factors that might influence the 6-minute walk distance (6MWD).

METHODS

Seventy-three patients with ILD were enrolled at Peking University First Hospital. All patients underwent 6MWT, pulmonary CT, and pulmonary function tests and their correlations were analyzed. Multivariate regression analysis was used to identify factors that might impact 6MWD.  Results: Thirty (41.4%) of the patients were female and the mean age was 66.1 ± 9.6 years. 6MWD was correlated with forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), total lung capacity (TLC), diffusing capacity for carbon monoxide (DLCO) and DLCO%pred. The decrease in oxygen saturation (SpO2) after the test was correlated with FEV1%pred, FVC%pred, TLC, TLC%pred, DLCO, DLCO%pred and the percentage of normal lung calculated by quantitative CT. The increase in Borg dyspnea scale was correlated with FEV1, DLCO and the percentage of normal lung. The backward multivariate model (F = 15.257, P < 0.001, adjusted R2 = 0.498) indicated that 6MWD was predicted by age, height, body weight, increase in heart rate, and DLCO.

CONCLUSIONS

The 6MWT results were closely correlated with pulmonary function and quantitative CT in patients with ILD. However, in addition to disease severity, 6MWD was also influenced by individual characteristics and the degree of patient effort, which should thus be considered by clinicians when interpreting 6WMT results.

Metabolic-related gene signatures for survival prediction and immune cell subtypes associated with prognosis in intrahepatic cholangiocarcinoma

OBJECTIVES

Our study aimed to reveal the metabolic-related gene signatures for survival prediction and immune cell subtypes associated with IHCC prognosis.

METHODS

Differentially expressed metabolic genes were identified between survival group and dead group which were divided according to survival at discharge. Recursive feature elimination (RFE) and randomForest (RF) algorithms were applied to optimize the combination of feature metabolic genes, which were used to generate SVM classifier. Performance of SVM classifier was evaluated by receiver operating characteristic (ROC) curves. Gene set enrichment analysis (GSEA) was conducted to uncover the activated pathways in high risk group, and differences in immune cell distributions were revealed.

RESULTS

There were 143 differentially expressed metabolic gens. RFE and RF identified 21 overlapping differentially expressed metabolic genes, and the constructed SVM classifier had excellent accuracy in training and validation dataset. RS survival prediction model was consisted of 10 metabolic genes. RS model had reliable predictive capability in the training and validation dataset. GSEA revealed 15 significant KEGG pathways that were relatively activated in the high risk group. High risk group had obviously lower counts of B cell naive and T cell CD4+ memory resting, while higher counts of B cell plasma and macrophage M2.

CONCLUSION

Prognostic prediction model of 10 metabolic genes could accurately predict the prognosis of IHCC patients.

The Crosstalk and Clinical Implications of CircRNAs and Glucose Metabolism in Gastrointestinal Cancers

The majority of glucose in tumor cells is converted to lactate despite the presence of sufficient oxygen and functional mitochondria, a phenomenon known as the "Warburg effect" or "aerobic glycolysis". Aerobic glycolysis supplies large amounts of ATP, raw material for macromolecule synthesis, and also lactate, thereby contributing to cancer progression and immunosuppression. Increased aerobic glycolysis has been identified as a key hallmark of cancer. Circular RNAs (circRNAs) are a type of endogenous single-stranded RNAs characterized by covalently circular structures. Accumulating evidence suggests that circRNAs influence the glycolytic phenotype of various cancers. In gastrointestinal (GI) cancers, circRNAs are related to glucose metabolism by regulating specific glycolysis-associated enzymes and transporters as well as some pivotal signaling pathways. Here, we provide a comprehensive review of glucose-metabolism-associated circRNAs in GI cancers. Furthermore, we also discuss the potential clinical prospects of glycolysis-associated circRNAs as diagnostic and prognostic biomarkers and therapeutic targets in GI cancers.

New Dual Inhibitors of Bacterial Topoisomerases with Broad-Spectrum Antibacterial Activity and In Vivo Efficacy against Vancomycin-Intermediate Staphylococcus aureus

A new series of dual low nanomolar benzothiazole inhibitors of bacterial DNA gyrase and topoisomerase IV were developed. The resulting compounds show excellent broad-spectrum antibacterial activities against Gram-positive Enterococcus faecalis, Enterococcus faecium and multidrug resistant (MDR) Staphylococcus aureus strains [best compound minimal inhibitory concentrations (MICs): range, <0.03125-0.25 μg/mL] and against the Gram-negatives Acinetobacter baumannii and Klebsiella pneumoniae (best compound MICs: range, 1-4 μg/mL). Lead compound 7a was identified with favorable solubility and plasma protein binding, good metabolic stability, selectivity for bacterial topoisomerases, and no toxicity issues. The crystal structure of 7a in complex with Pseudomonas aeruginosa GyrB24 revealed its binding mode at the ATP-binding site. Expanded profiling of 7a and 7h showed potent antibacterial activity against over 100 MDR and non-MDR strains of A. baumannii and several other Gram-positive and Gram-negative strains. Ultimately, in vivo efficacy of 7a in a mouse model of vancomycin-intermediate S. aureus thigh infection was also demonstrated.

MPS-FFA: A multiplane and multiscale feature fusion attention network for Alzheimer's disease prediction with structural MRI

Structural magnetic resonance imaging (sMRI) is a popular technique that is widely applied in Alzheimer's disease (AD) diagnosis. However, only a few structural atrophy areas in sMRI scans are highly associated with AD. The degree of atrophy in patients' brain tissues and the distribution of lesion areas differ among patients. Therefore, a key challenge in sMRI-based AD diagnosis is identifying discriminating atrophy features. Hence, we propose a multiplane and multiscale feature-level fusion attention (MPS-FFA) model. The model has three components, (1) A feature encoder uses a multiscale feature extractor with hybrid attention layers to simultaneously capture and fuse multiple pathological features in the sagittal, coronal, and axial planes. (2) A global attention classifier combines clinical scores and two global attention layers to evaluate the feature impact scores and balance the relative contributions of different feature blocks. (3) A feature similarity discriminator minimizes the feature similarities among heterogeneous labels to enhance the ability of the network to discriminate atrophy features. The MPS-FFA model provides improved interpretability for identifying discriminating features using feature visualization. The experimental results on the baseline sMRI scans from two databases confirm the effectiveness (e.g., accuracy and generalizability) of our method in locating pathological locations. The source code is available at https://github.com/LiuFei-AHU/MPSFFA.

Circular RNAs: implications of signaling pathways and bioinformatics in human cancer

Circular RNAs (circRNAs) form a class of endogenous single-stranded RNA transcripts that are widely expressed in eukaryotic cells. These RNAs mediate post-transcriptional control of gene expression and have multiple functions in biological processes, such as transcriptional regulation and splicing. They serve predominantly as microRNA sponges, RNA-binding proteins, and templates for translation. More importantly, circRNAs are involved in cancer progression, and may serve as promising biomarkers for tumor diagnosis and therapy. Although traditional experimental methods are usually time-consuming and laborious, substantial progress has been made in exploring potential circRNA-disease associations by using computational models, summarized signaling pathway data, and other databases. Here, we review the biological characteristics and functions of circRNAs, including their roles in cancer. Specifically, we focus on the signaling pathways associated with carcinogenesis, and the status of circRNA-associated bioinformatics databases. Finally, we explore the potential roles of circRNAs as prognostic biomarkers in cancer.

Association between preserved ratio impaired spirometry and sleep apnea in a Chinese community

OBJECTIVE

This study investigated the association between obstructive sleep apnea (OSA) and preserved ratio impaired spirometry (PRISm) in a community population.

METHODS

Baseline data from a prospective cohort study, the Predictive Value of Combining Inflammatory Biomarkers and Rapid Decline of FEV1 for COPD (PIFCOPD), were used for cross-sectional analysis. Participants aged 40-75 years were recruited from the community and their demographic information and medical history were collected. The STOP-Bang questionnaire (SBQ) was used to assess the risk of OSA. Pulmonary function tests were performed using a portable spirometer (COPD-6) and forced expiratory volume in 1 s (FEV1) and 6 s (FEV6) were measured. Routine blood, biochemical, high-sensitivity C-reactive protein (hs-CRP), and interleukin-6 tests were also performed. The pH of the exhaled breath condensate was determined.

RESULTS

A total of 1183 participants were enrolled, of which 221 with PRISm and 962 with normal lung function. The neck circumference, waist-to-hip ratio, hs-CRP concentration, proportion of males, cigarette exposure, number of current smoker, high risk of OSA, and prevalence of nasal and ocular allergy symptoms were significantly higher in the PRISm group than in the non-PRISm group (p < .05). Logistic regression showed that the risk of OSA (odds ratio, 1.883; 95% confidence interval, 1.245-2.848), waist-to-hip ratio, current smoking, and prevalence of nasal allergy symptoms were independently associated with PRISm after correcting for age and sex.

CONCLUSION

These findings showed that OSA prevalence is independently associated with PRISm prevalence. Further studies should confirm the relationship between systemic inflammation in OSA, localized inflammation of the airways, and impaired lung function.

MRI texture-based machine learning models for the evaluation of renal function on different segmentations: a proof-of-concept study

BACKGROUND

To develop and validate an MRI texture-based machine learning model for the noninvasive assessment of renal function.

METHODS

A retrospective study of 174 diabetic patients (training cohort, n = 123; validation cohort, n = 51) who underwent renal MRI scans was included. They were assigned to normal function (n = 71), mild or moderate impairment (n = 69), and severe impairment groups (n = 34) according to renal function. Four methods of kidney segmentation on T2-weighted images (T2WI) were compared, including regions of interest covering all coronal slices (All-K), the largest coronal slices (LC-K), and subregions of the largest coronal slices (TLCO-K and PIZZA-K). The speeded-up robust features (SURF) and support vector machine (SVM) algorithms were used for texture feature extraction and model construction, respectively. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of models.

RESULTS

The models based on LC-K and All-K achieved the nonsignificantly highest accuracy in the classification of renal function (all p values > 0.05). The optimal model yielded high performance in classifying the normal function, mild or moderate impairment, and severe impairment, with an area under the curve of 0.938 (95% confidence interval [CI] 0.935-0.940), 0.919 (95%CI 0.916-0.922), and 0.959 (95%CI 0.956-0.962) in the training cohorts, respectively, as well as 0.802 (95%CI 0.800-0.807), 0.852 (95%CI 0.846-0.857), and 0.863 (95%CI 0.857-0.887) in the validation cohorts, respectively.

CONCLUSION

We developed and internally validated an MRI-based machine-learning model that can accurately evaluate renal function. Once externally validated, this model has the potential to facilitate the monitoring of patients with impaired renal function.

The role of Chemerin in human diseases

Chemerin is a protein encoded by the Rarres2 gene that acts through endocrine or paracrine regulation. Chemerin can bind to its receptor, regulate insulin sensitivity and adipocyte differentiation, and thus affect glucose and lipid metabolism. There is growing evidence that it also plays an important role in diseases such as inflammation and cancer. Chemerin has been shown to play a role in the pathogenesis of inflammatory and metabolic diseases caused by leukocyte chemoattractants in a variety of organs, but its biological function remains controversial. In conclusion, the exciting findings collected over the past few years clearly indicate that targeting Chemerin signaling as a biological target will be a major research goal in the future. This article reviews the pathophysiological roles of Chemerin in various systems and diseases,and expect to provide a rationale for its role as a clinical therapeutic target.

Integrative Scoring System for Survival Prediction in Patients With Locally Advanced Nasopharyngeal Carcinoma: A Retrospective Multicenter Study

PURPOSE

Tumor stage is crucial for prognostic evaluation and therapeutic decisions in locally advanced nasopharyngeal carcinoma (NPC) but is imprecise. We aimed to propose a new prognostic system by integrating quantitative imaging features and clinical factors.

MATERIALS AND METHODS

This retrospective study included 1,319 patients with stage III-IVa NPC between April 1, 2010, and July 31, 2019, who underwent pretherapy magnetic resonance imaging (MRI) and received concurrent chemoradiotherapy with or without induction chemotherapy. The hand-crafted and deep-learned features were extracted from MRI for each patient. After feature selection, the clinical score, radiomic score, deep score, and integrative scores were constructed via Cox regression analysis. The scores were validated in two external cohorts. The predictive accuracy and discrimination were measured by the area under the curve (AUC) and risk group stratification. The end points were progression-free survival (PFS), overall survival (OS), and distant metastasis-free survival (DMFS).

RESULTS

Both radiomics and deep learning were complementary to clinical variables (age, T stage, and N stage; all P < .05). The clinical-deep score was superior or equivalent to clinical-radiomic score, whereas it was noninferior to clinical-radiomic-deep score (all P > .05). These findings were also verified in the evaluation of OS and DMFS. The clinical-deep score yielded an AUC of 0.713 (95% CI, 0.697 to 0.729) and 0.712 (95% CI, 0.693 to 0.731) in the two external validation cohorts for predicting PFS with good calibration. This scoring system could stratify patients into high- and low-risk groups with distinct survivals (all P < .05).

CONCLUSION

We established and validated a prognostic system integrating clinical data and deep learning to provide an individual prediction of survival for patients with locally advanced NPC, which might inform clinicians in treatment decision making.

Discovery and Hit-to-Lead Optimization of Benzothiazole Scaffold-Based DNA Gyrase Inhibitors with Potent Activity against Acinetobacter baumannii and Pseudomonas aeruginosa

We have developed compounds with a promising activity against Acinetobacter baumannii and Pseudomonas aeruginosa, which are both on the WHO priority list of antibiotic-resistant bacteria. Starting from DNA gyrase inhibitor 1, we identified compound 27, featuring a 10-fold improved aqueous solubility, a 10-fold improved inhibition of topoisomerase IV from A. baumannii and P. aeruginosa, a 10-fold decreased inhibition of human topoisomerase IIα, and no cross-resistance to novobiocin. Cocrystal structures of 1 in complex with Escherichia coli GyrB24 and (S)-27 in complex with A. baumannii GyrB23 and P. aeruginosa GyrB24 revealed their binding to the ATP-binding pocket of the GyrB subunit. In further optimization steps, solubility, plasma free fraction, and other ADME properties of 27 were improved by fine-tuning of lipophilicity. In particular, analogs of 27 with retained anti-Gram-negative activity and improved plasma free fraction were identified. The series was found to be nongenotoxic, nonmutagenic, devoid of mitochondrial toxicity, and possessed no ion channel liabilities.

The role of ion channels in immune-related diseases

Ion channel is an integral membrane protein that allows the permeation of charge ions across hydrophobic phospholipid membranes, including plasma membranes and organelle membranes (such as mitochondria, endoplasmic reticulum and vacuoles), which are widely distributed in various cells and tissues, such as cardiomyocytes, smooth muscle cells, and nerve cells. Ion channels establish membrane potential by regulating ion concentration and membrane potential. Membrane potential plays an important role in cells. Studies have shown that ion channels play a role in a number of immune-related diseases caused by functional defects in ion channels on immune or non-immune cells in major human organs, usually affecting specific organs or multiple organs. The present review discusses the relationship between ion channels and immune diseases in major organs of the human body.

GABA signalling in human pancreatic islets

The pancreatic islets are essential microorgans controlling the glucose level in the blood. The islets consist of different cell types which communicate with each other by means of auto- and paracrine interactions. One of the communication molecules produced by and released within the islets is γ-aminobutyric acid (GABA), a well-known inhibitor of neuronal excitability in the mammalian nervous system. Interestingly, GABA is also present in the blood in the nanomolar concentration range. Thus, GABA can affect not only islet function per se (e.g. hormone secretion) but also interactions between immune cells and the pancreatic islet cells in physiological conditions and in pathological states (particularly in type 1 diabetes). In the last decade the interest in GABA signalling in islets has increased. The broad research scope ranges from fundamental physiological studies at the molecular and cellular level to pathological implications and clinical trials. The aim of this mini-review is to outline the current status of the islet GABA field mostly in relation to human islets, to identify the gaps in the current knowledge and what clinical implications GABA signalling may have in islets.

Protective potential of hydroxysafflor yellow A in cerebral ischemia and reperfusion injury: An overview of evidence from experimental studies

Ischemic stroke, mostly caused by thromboembolic or thrombotic arterial occlusions, is a primary leading cause of death worldwide with high morbidity and disability. Unfortunately, no specific medicine is available for the treatment of cerebral I/R injury due to its limitation of therapeutic window. Hydroxysafflor yellow A, a natural product extracted from Carthamus tinctorius, has been extensively investigated on its pharmacological properties in cerebrovascular diseases. However, review focusing on the beneficial role of HSYA against cerebral I/R injury is still lacking. In this paper, we reviewed the neuroprotective effect of HSYA in preclinical studies and the underlying mechanisms involved, as well as clinical data that support the pharmacological activities. Additionally, the sources, physicochemical properties, biosynthesis, safety and limitations of HSYA were also reviewed. As a result, HSYA possesses a wide range of beneficial effects against cerebral I/R injury, and its action mechanisms include anti-excitotoxicity, anti-oxidant stress, anti-apoptosis, anti-inflammation, attenuating BBB leakage and regulating autophagy. Collectively, HSYA might be applied as one of the promising alternatives in ischemic stroke treatment.

Evaluation of the Effects of Anti-PD-1 Therapy on Triple-Negative Breast Cancer in Mice by Diffusion Kurtosis Imaging and Dynamic Contrast-Enhanced Imaging

BACKGROUND

The monitoring of immunotherapies is still based on changes in the tumor size in imaging, with a long evaluation period and low sensitivity.

PURPOSE

To investigate the effectiveness of diffusion kurtosis imaging (DKI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing the therapeutic efficacy of anti-programmed death-1 (PD-1) therapy in a mouse triple negative breast cancer (TNBC) model.

STUDY TYPE

Prospective.

ANIMAL MODEL

A total of 54 BALB/c mouse subcutaneous 4 T1 transplantation models of TNBC.

FIELD STRENGTH/SEQUENCE

A 3.0-T; turbo spin echo (TSE) T2-weighted imaging, DKI with seven b values (0, 500, 1000, 1500, 2000, 2500, and 3000 sec/mm² ) and T1-twist DCE acquisition series.

ASSESSMENT

DKI and DCE-MRI parameters were evaluated by two radiologists independently. Regions of interest (ROIs) were drawn manually on the maximum cross-sectional area of the lesion; care was taken to avoid necrotic areas. The tumor cell density, the CD45 and CD31 levels were analyzed by two pathologists.

STATISTICAL TESTS

The two-tailed unpaired t-test, Mann-Whitney U test, Fisher's exact test and Pearson correlation coefficient were performed. A P < 0.05 was considered statistically significant.

RESULTS

The apparent diffusion coefficient (ADC), mean diffusivity (MD), K_trans and K_ep values were significantly different between the two groups at each time point after treatment. There were significant differences in the mean kurtosis (MK) and V_e values between the two groups at 5 and 10 days after treatment but no significant differences at 15 days (P = 0.317 and 0.183, respectively). The ADC and MD values were significantly correlated with tumor cell density (ADC, r = -0.833; MD, r = 0.890) and the CD45 level (ADC, r = 0.720; MD, r = 0.718). The K_trans and K_ep values were significantly correlated with the CD31 level (K_trans , r = 0.820; K_ep , r = 0.683).

DATA CONCLUSION

DKI and DCE-MRI could reflect the changes in tumor microstructure and tumor tissue vasculature after anti-PD-1 therapy, respectively.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 4.

Identification of Novel m6A-Related Long Non-Coding RNA Signatures for Cholangiocarcinoma Using Integrated Bioinformatics Analyses

Traditional methods used to treat cholangiocarcinoma are less effective, and the identification of new CHOL signature genes can help in the early clinical diagnosis and intervention of cholangiocarcinoma. In this work, we used integrated bioinformatics analysis to find new m6a-associated lncRNA signatures in cholangiocarcinoma. Pearson correlation test was used to identify m6A-lncRNAs by co-expression analysis of m6A-mrna and lncRNAs. we then selected m6A-lncRNAs co-expressed with METTL3 and METTL14 genes and screened for DEm6A-lncRNAs by comparing expression differences. we then used R package of Spearman coefficient correlation analysis to investigate the relevance of m6A-lncrna expression in CHOL. To determine the relative levels of immune cell infiltration, we performed ssGSEA analysis on all samples using the R package, and then we used graphs to illustrate the differences in immune cell infiltration between the CHOL and NC groups. The results of this study will help to identify new CHOL-causing biosignatures, which are important for the early clinical detection and management of CHOL.

Review of Generative Adversarial Networks in mono- and cross-modal biomedical image registration

Biomedical image registration refers to aligning corresponding anatomical structures among different images, which is critical to many tasks, such as brain atlas building, tumor growth monitoring, and image fusion-based medical diagnosis. However, high-throughput biomedical image registration remains challenging due to inherent variations in the intensity, texture, and anatomy resulting from different imaging modalities, different sample preparation methods, or different developmental stages of the imaged subject. Recently, Generative Adversarial Networks (GAN) have attracted increasing interest in both mono- and cross-modal biomedical image registrations due to their special ability to eliminate the modal variance and their adversarial training strategy. This paper provides a comprehensive survey of the GAN-based mono- and cross-modal biomedical image registration methods. According to the different implementation strategies, we organize the GAN-based mono- and cross-modal biomedical image registration methods into four categories: modality translation, symmetric learning, adversarial strategies, and joint training. The key concepts, the main contributions, and the advantages and disadvantages of the different strategies are summarized and discussed. Finally, we analyze the statistics of all the cited works from different points of view and reveal future trends for GAN-based biomedical image registration studies.

ABI2-mediated MEOX2/KLF4-NANOG axis promotes liver cancer stem cell and drives tumour recurrence

Tumour recurrence and drug resistance in hepatocellular carcinoma remain challenging. Cancer stem cells (CSCs) are responsible for tumour initiation because of their stemness characteristics. CSCs accounting for drug resistance and tumour relapse are promising therapeutic targets. We report that Abelson interactor 2 (ABI2) is a novel therapeutic target of HCC CSCs. First, ABI2 was upregulated in HCC tissues compared with liver tissues and was associated with tumour size, pathological grade, liver cirrhosis, worse prognosis and a high recurrence rate. Functional studies illustrate that ABI2 knockdown suppresses cell growth, migration, invasion and sorafenib resistance in vitro. Furthermore, ABI2 knockdown inhibited HCC sphere formation and decreased the CD24⁺ , CD133⁺ and CD326⁺ CSCs populations, suggesting the suppression of HCC stemness characteristics. A tumour xenograft model and limiting dilution assay demonstrated the inhibition of tumorigenicity and tumour initiation. Moreover, molecular mechanism studies showed that ABI2 recruits and directly interacts with the transcription factor MEOX2, which binds to the KLF4 and NANOG promoter regions to activate their transcription. Furthermore, overexpression of MEOX2 restored HCC malignant behaviour and the CSC population. The ABI2-mediated transcriptional axis MEOX2/KLF4-NANOG promotes HCC growth, metastasis and sorafenib resistance by maintaining the CSC population, suggesting that ABI2 is a promising CSC target in HCC treatment.

PAD4-dependent citrullination of nuclear translocation of GSK3β promotes colorectal cancer progression via the degradation of nuclear CDKN1A

Peptidylarginine deiminase 4 (PAD4), a Ca²⁺-dependent enzyme, catalyzes the conversion of arginine to citrulline and has been strongly associated with many malignant tumors. However, the molecular mechanisms of PAD4 in the development and progression of colorectal cancer (CRC) remain unclearly defined. In our study, PAD4 expression was increased in CRC tissues and cells, and was closely related to tumor size, lymph node metastasis. Moreover, the transcription factor KLF9 directly bound to PADI4 gene promoter, leading to overexpression of PAD4 in CRC cells, which augmented cell growth and migration. We revealed that PAD4 interacted with and citrullinated glycogen synthase kinase-3β (GSK3β) in CRC cells, and GSK3β Arg-344 was the dominating PAD4-citrullination site. Furthermore, IgL2 and catalytic domains of PAD4 directly bound to the kinase domain of GSK3β in CRC cells. Mechanistically, PAD4 promoted the transport of GSK3β from the cytoplasm to the nucleus, thereby increasing the ubiquitin-dependent proteasome degradation of nuclear cyclin-dependent kinase inhibitor 1 (CDKN1A). Our study is the first to reveal the details of a critical PAD4/GSK3β/CDKN1A signaling axis for CRC progression, and provides evidence that PAD4 is a potential diagnosis biomarker and therapeutic target in CRC.

ZEB2 haploinsufficient Mowat-Wilson syndrome induced pluripotent stem cells show disrupted GABAergic transcriptional regulation and function

Mowat-Wilson syndrome (MWS) is a severe neurodevelopmental disorder caused by heterozygous variants in the gene encoding transcription factor ZEB2. Affected individuals present with structural brain abnormalities, speech delay and epilepsy. In mice, conditional loss of Zeb2 causes hippocampal degeneration, altered migration and differentiation of GABAergic interneurons, a heterogeneous population of mainly inhibitory neurons of importance for maintaining normal excitability. To get insights into GABAergic development and function in MWS we investigated ZEB2 haploinsufficient induced pluripotent stem cells (iPSC) of MWS subjects together with iPSC of healthy donors. Analysis of RNA-sequencing data at two time points of GABAergic development revealed an attenuated interneuronal identity in MWS subject derived iPSC with enrichment of differentially expressed genes required for transcriptional regulation, cell fate transition and forebrain patterning. The ZEB2 haploinsufficient neural stem cells (NSCs) showed downregulation of genes required for ventral telencephalon specification, such as FOXG1, accompanied by an impaired migratory capacity. Further differentiation into GABAergic interneuronal cells uncovered upregulation of transcription factors promoting pallial and excitatory neurons whereas cortical markers were downregulated. The differentially expressed genes formed a neural protein-protein network with extensive connections to well-established epilepsy genes. Analysis of electrophysiological properties in ZEB2 haploinsufficient GABAergic cells revealed overt perturbations manifested as impaired firing of repeated action potentials. Our iPSC model of ZEB2 haploinsufficient GABAergic development thus uncovers a dysregulated gene network leading to immature interneurons with mixed identity and altered electrophysiological properties, suggesting mechanisms contributing to the neuropathogenesis and seizures in MWS.

Retraction Note: Combination therapy with metformin and IL-12 to inhibit the growth of hepatic carcinoma by promoting apoptosis and autophagy in HepG2-bearing mice

The article "Combination therapy with metformin and IL-12 to inhibit the growth of hepatic carcinoma by promoting apoptosis and autophagy in HepG2-bearing mice, by Z. Jin, B.-X. Jia, L.-D. Tan, Q.-M. Chen, Y.-H. Liu, published in Eur Rev Med Pharmacol Sci 2020; 24 (23): 12368-12379-DOI: 10.26355/eurrev_202012_24031-PMID: 33336757" has been retracted by the authors as they cannot ensure the reliability of the manuscript due to inaccuracies in the conclusions and in the experiment (the cell migration and invasion assay along with the cell cycle arrest assay are missing). The Publisher apologizes for any inconvenience this may cause https://www.europeanreview.org/article/24031.

Circ_CEA promotes the interaction between the p53 and cyclin-dependent kinases 1 as a scaffold to inhibit the apoptosis of gastric cancer

Circular RNAs (circRNAs) have been reported to play essential roles in tumorigenesis and progression. This study aimed to identify dysregulated circRNAs in gastric cancer (GC) and investigate the functions and underlying mechanism of these circRNAs in GC development. Here, we identify circ_CEA, a circRNA derived from the back-splicing of CEA cell adhesion molecule 5 (CEA) gene, as a novel oncogenic driver of GC. Circ_CEA is significantly upregulated in GC tissues and cell lines. Circ_CEA knockdown suppresses GC progression, and enhances stress-induced apoptosis in vitro and in vivo. Mechanistically, circ_CEA interacts with p53 and cyclin-dependent kinases 1 (CDK1) proteins. It serves as a scaffold to enhance the association between p53 and CDK1. As a result, circ_CEA promotes CDK1-mediated p53 phosphorylation at Ser315, then decreases p53 nuclear retention and suppresses its activity, leading to the downregulation of p53 target genes associated with apoptosis. These findings suggest that circ_CEA protects GC cells from stress-induced apoptosis, via acting as a protein scaffold and interacting with p53 and CDK1 proteins. Combinational therapy of targeting circ_CEA and chemo-drug caused more cell apoptosis, decreased tumor volume and alleviated side effect induced by chemo-drug. Therefore, targeting circ_CEA might present a novel treatment strategy for GC.

Combined cell grafting and VPA administration facilitates neural repair through axonal regeneration and synaptogenesis in traumatic brain injury

Neuronal regeneration and functional recovery are severely compromised following traumatic brain injury (TBI). Treatment options, including cell transplantation and drug therapy, have been shown to benefit TBI, although the underlying mechanisms remain elusive. In this study, neural stem cells (NSCs) are transplanted into TBI-challenged mice, together with olfactory ensheathing cells (OECs) or followed by valproic acid (VPA) treatment. Both OEC grafting and VPA treatment facilitate the differentiation of NSCs into neurons (including endogenous and exogenous neurons) and significantly attenuate neurological functional defects in TBI mice. Combination of NSCs with OECs or VPA administration leads to overt improvement in axonal regeneration, synaptogenesis, and synaptic plasticity in the cerebral cortex in TBI-challenged mice, as shown by retrograde corticospinal tract tracing, electron microscopy, growth-associated protein 43 (GAP43), and synaptophysin (SYN) analyses. However, these beneficial effects of VPA are reversed by local delivery of N-methyl-D-aspartate (NMDA) into tissues surrounding the injury epicenter in the cerebral cortex, accompanied by a pronounced drop in axons and synapses in the brain. Our findings reveal that increased axonal regeneration and synaptogenesis evoked by cell grafting and VPA fosters neural repair in a murine model of TBI. Moreover, VPA-induced neuroprotective roles are antagonized by exogenous NMDA administration and its concomitant decrease in the number of neurons of local brain, indicating that increased neurons induced by VPA treatment mediate axonal regeneration and synaptogenesis in mice after TBI operation. Collectively, this study provides new insights into NSC transplantation therapy for TBI.

The emerging roles of circular RNA-mediated autophagy in tumorigenesis and cancer progression

Circular RNA (circRNA) is characterized by a specific covalently closed ring structure. The back-splicing of precursor mRNA is the main way of circRNA generation, and various cis/trans-acting elements are involved in regulating the process. circRNAs exhibit multiple biological functions, including serving as sponges of microRNAs, interacting with proteins to regulate their stabilities and abilities, and acting as templates for protein translation. Autophagy participates in many physiological and pathological processes, especially it plays a vital role in tumorigenesis and carcinoma progression. Increasing numbers of evidences have revealed that circRNAs are implicated in regulating autophagy during tumor development. Until now, the roles of autophagy-associated circRNAs in carcinoma progression and their molecular mechanisms remain unclear. Here, the emerging regulatory roles and mechanisms of circRNAs in autophagy were summarized. Furtherly, the effects of autophagy-associated circRNAs on cancer development were described. We also prospected the potential of autophagy-associated circRNAs as novel therapeutic targets of tumors and as biomarkers for cancer diagnosis and prognosis.