SALL4 in gastrointestinal tract cancers: upstream and downstream regulatory mechanisms.

Effective therapeutic targets and early diagnosis are major challenges in the treatment of gastrointestinal tract (GIT) cancers. SALL4 is a well-known transcription factor that is involved in organogenesis during embryonic development. Previous studies have revealed that SALL4 regulates cell proliferation, survival, and migration and maintains stem cell function in mature cells. Additionally, SALL4 overexpression is associated with tumorigenesis. Despite its characterization as a biomarker in various cancers, the role of SALL4 in GIT cancers and the underlying mechanisms are unclear. We describe the functions of SALL4 in GIT cancers and discuss its upstream/downstream genes and pathways associated with each cancer. We also consider the possibility of targeting these genes or pathways as potential therapeutic options for GIT cancers.

Trends in cardiovascular risk factor prevalence, treatment, and control among US adolescents aged 12 to 19 years, 2001 to March 2020.

BACKGROUND: Early-life cardiovascular risk factors (CVRFs) are known to be associated with target organ damage during adolescence and premature cardiovascular morbidity and mortality during adulthood. However, contemporary data describing whether the prevalence of CVRFs and treatment and control rates have changed are limited. This study aimed to examine the temporal trends in the prevalence, treatment, and control of CVRFs among US adolescents over the past 2 decades. METHODS: This is a serial cross-sectional study using data from nine National Health and Nutrition Examination Survey cycles (January 2001-March 2020). US adolescents (aged 12 to 19 years) with information regarding CVRFs (including hypertension, elevated blood pressure [BP], diabetes, prediabetes, hyperlipidemia, obesity, overweight, cigarette use, inactive physical activity, and poor diet quality) were included. Age-adjusted trends in CVRF prevalence, treatment, and control were examined. Joinpoint regression analysis was performed to estimate changes in the prevalence, treatment, and control over time. The variation by sociodemographic characteristics were also described. RESULTS: A total of 15,155 US adolescents aged 12 to 19 years (representing ≈ 32.4 million people) were included. From 2001 to March 2020, there was an increase in the prevalence of prediabetes (from 12.5% [95% confidence interval (CI), 10.2%-14.9%] to 37.6% [95% CI, 29.1%-46.2%]) and overweight/obesity (from 21.1% [95% CI, 19.3%-22.8%] to 24.8% [95% CI, 21.4%-28.2%]; from 16.0% [95% CI, 14.1%-17.9%] to 20.3% [95% CI, 17.9%-22.7%]; respectively), no improvement in the prevalence of elevated BP (from 10.4% [95% CI, 8.9%-11.8%] to 11.0% [95% CI, 8.7%-13.4%]), diabetes (from 0.7% [95% CI, 0.2%-1.2%] to 1.2% [95% CI, 0.3%-2.2%]), and poor diet quality (from 76.1% [95% CI, 74.0%-78.2%] to 71.7% [95% CI, 68.5%-74.9%]), and a decrease in the prevalence of hypertension (from 8.1% [95% CI, 6.9%-9.4%] to 5.5% [95% CI, 3.7%-7.3%]), hyperlipidemia (from 34.2% [95% CI, 30.9%-37.5%] to 22.8% [95% CI, 18.7%-26.8%]), cigarette use (from 18.0% [95% CI, 15.7%-20.3%] to 3.5% [95% CI, 2.0%-5.0%]), and inactive physical activity (from 83.0% [95% CI, 80.7%-85.3%] to 9.5% [95% CI, 4.2%-14.8%]). Sex and race/ethnicity affected the evolution of CVRF prevalence differently. Whilst treatment rates for hypertension and diabetes did not improve significantly (from 9.6% [95% CI, 3.5%-15.8%] to 6.0% [95% CI, 1.4%-10.6%]; from 51.0% [95% CI, 23.3%-78.7%] to 26.5% [95% CI, 0.0%-54.7%]; respectively), BP control was relatively stable (from 75.7% [95% CI, 56.8%-94.7%] to 73.5% [95% CI, 40.3%-100.0%]), while glycemic control improved to a certain extent, although it remained suboptimal (from 11.8% [95% CI, 0.0%-31.5%] to 62.7% [95% CI, 62.7%-62.7%]). CONCLUSIONS: From 2001 to March 2020, although prediabetes and overweight/obesity increased, hypertension, hyperlipidemia, cigarette use, and inactive physical activity decreased among US adolescents aged 12 to 19 years, whereas elevated BP, diabetes, and poor diet quality remained unchanged. There were disparities in CVRF prevalence and trends across sociodemographic subpopulations. While treatment and control rates for hypertension and diabetes plateaued, BP control were stable, and improved glycemic control was observed.

Fusion of Quality Evaluation Metrics and Convolutional Neural Network Representations for ROI Filtering in LC-MS.

Region of interest (ROI) extraction is a fundamental step in analyzing metabolomic datasets acquired by liquid chromatography-mass spectrometry (LC-MS). However, noises and backgrounds in LC-MS data often affect the quality of extracted ROIs. Therefore, developing effective ROI evaluation algorithms is necessary to eliminate false positives meanwhile keep the false-negative rate as low as possible. In this study, a deep fused filter of ROIs (dffROI) was proposed to improve the accuracy of ROI extraction by combining the handcrafted evaluation metrics with convolutional neural network (CNN)-learned representations. To evaluate the performance of dffROI, dffROI was compared with peakonly (CNN-learned representation) and five handcrafted metrics on three LC-MS datasets and a gas chromatography-mass spectrometry (GC-MS) dataset. Results show that dffROI can achieve higher accuracy, better true-positive rate, and lower false-positive rate. Its accuracy, true-positive rate, and false-positive rate are 0.9841, 0.9869, and 0.0186 on the test set, respectively. The classification error rate of dffROI (1.59%) is significantly reduced compared with peakonly (2.73%). The model-agnostic feature importance demonstrates the necessity of fusing handcrafted evaluation metrics with the convolutional neural network representations. dffROI is an automatic, robust, and universal method for ROI filtering by virtue of information fusion and end-to-end learning. It is implemented in Python programming language and open-sourced at https://github.com/zhanghailiangcsu/dffROI under BSD License. Furthermore, it has been integrated into the KPIC2 framework previously proposed by our group to facilitate real metabolomic LC-MS dataset analysis.

Prediction of drug-likeness using graph convolutional attention network.

MOTIVATION: The drug-likeness has been widely used as a criterion to distinguish drug-like molecules from non-drugs. Developing reliable computational methods to predict the drug-likeness of compounds is crucial to triage unpromising molecules and accelerate the drug discovery process. RESULTS: In this study, a deep learning method was developed to predict the drug-likeness based on the graph convolutional attention network (D-GCAN) directly from molecular structures. Results showed that the D-GCAN model outperformed other state-of-the-art models for drug-likeness prediction. The combination of graph convolution and attention mechanism made an important contribution to the performance of the model. Specifically, the application of the attention mechanism improved accuracy by 4.0%. The utilization of graph convolution improved the accuracy by 6.1%. Results on the dataset beyond Lipinski's rule of five space and the non-US dataset showed that the model had good versatility. Then, the billion-scale GDB-13 database was used as a case study to screen SARS-CoV-2 3C-like protease inhibitors. Sixty-five drug candidates were screened out, most substructures of which are similar to these of existing oral drugs. Candidates screened from S-GDB13 have higher similarity to existing drugs and better molecular docking performance than those from the rest of GDB-13. The screening speed on S-GDB13 is significantly faster than screening directly on GDB-13. In general, D-GCAN is a promising tool to predict the drug-likeness for selecting potential candidates and accelerating drug discovery by excluding unpromising candidates and avoiding unnecessary biological and clinical testing. AVAILABILITY AND IMPLEMENTATION: The source code, model and tutorials are available at https://github.com/JinYSun/D-GCAN. The S-GDB13 database is available at https://doi.org/10.5281/zenodo.7054367. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Low lean mass with obesity in older adults with hypertension: prevalence and association with mortality rate.

BACKGROUND: The influence of sarcopenic obesity (SO) on overall survival in older adults with hypertension has not been addressed. The aim of this study was to investigate the prevalence and mortality predictive value of various body composition phenotypes, focusing mainly on SO, in older adults with hypertension. METHODS: We included 1105 hypertensive patients aged ≥ 60 years from the National Health and Nutrition Examination Survey 1999-2004. Sarcopenia was broadly defined based on low lean mass (LLM; as measured by dual-energy X-ray absorptiometry), and was defined using appendicular lean mass (ALM) divided by height squared (ALM/height2), weight (ALM/weight), and body mass index (BMI; ALM/BMI), respectively. Obesity was defined as BMI ≥ 30 kg/m2, body fat percentage ≥ 30/42%, or waist circumference ≥ 102/88 cm. The prevalence of LLM with obesity was estimated according to each ALM index (ALMI). Multivariable Cox regression analysis and sensitivity analysis were used to examine the association between various body composition phenotypes and all-cause mortality. RESULTS: In older adults with hypertension, the prevalence of LLM with obesity by the ALM/height2 index (9.8%) was lower relative to the ALM/weight (11.7%) and ALM/BMI indexes (19.6%). After a median follow-up of 15.4 years, 642 deaths occurred. In the fully adjusted models, LLM with obesity was significantly associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.69, 95% confidence interval [CI] 1.14-2.49, P = 0.008; HR 1.48, 95% CI 1.04-2.10, P = 0.028; HR 1.30, 95% CI 1.02-1.66, P = 0.037; respectively) compared with the normal body phenotype, with no statistical differences found in individuals with LLM or obesity alone. Sensitivity analysis confirmed the robustness of the results. CONCLUSIONS: The prevalence of LLM with obesity markedly differed in older adults with hypertension according to the 3 different ALMIs, varying from 9.8%, 11.7%, to 19.6%. Patients with both LLM and obesity had a higher risk of all-cause mortality. Further large, prospective, cohort studies are warranted to validate these findings and uncover underlying mechanisms.

The Association Between Vitamin D Levels and the 10-Year Risk of Atherosclerotic Cardiovascular Disease: A Population-Based Study.

BACKGROUND: The association between vitamin D levels and atherosclerotic cardiovascular disease (ASCVD) risk remains unclear. In this study, the association between serum 25(OH)D and 10-year ASCVD risk was examined in a national sample of middle-aged and older adults. METHODS: Cross-sectional data from the 2009-2014 National Health and Nutrition Examination Survey were analyzed. The Pooled Cohort Equations were used to estimate the risk of a first ASCVD event in 10 years. An adjusted multiple linear regression model was used to investigate the association between serum 25(OH)D and ASCVD risk. In addition, we performed sensitivity analysis and interactive analysis to assess the robustness of associations across different subgroups. RESULTS: A total of 3354 participants were included in this study. The linear regression model indicated that the risk of ASCVD decreased with the increase in serum 25(OH)D. When analyzed as a continuous variable, serum 25(OH)D was significantly associated with the estimated 10-year risk of ASCVD. In the fully adjusted model, each 10-nmol/L increase in serum 25(OH)D reduced the estimated 10-year ASCVD risk by 0.172% ( P < .001). Individuals in the moderate, insufficient, and sufficient vitamin D deficiency groups had a 0.449% ( P = .362), 0.957% ( P = .046), 1.475% ( P = .003) decrease in ASCVD risk, respectively, when a severe vitamin D deficiency group was set as a reference in the fully adjusted model. CONCLUSION: Our data suggest a negative association between vitamin D levels and the predicted 10-year risk of ASCVD. Further studies are required to investigate whether vitamin D supplements could reduce the risk of ASCVD.

Mesenchymal Stem Cell-Derived Extracellular Vesicles Alleviate M1 Microglial Activation in Brain Injury of Mice With Subarachnoid Hemorrhage via microRNA-140-5p Delivery.

BACKGROUND: It is documented that mesenchymal stem cells (MSCs) secrete extracellular vesicles (EVs) to modulate subarachnoid hemorrhage (SAH) development. miR-140-5p expression has been detected in MSC-derived EVs, while the mechanism of MSC-derived EVs containing miR-140-5p in SAH remains unknown. We aim to fill this void by establishing SAH mouse models and extracting MSCs and MSC-EVs. METHODS: After ALK5 was silenced in SAH mice, neurological function was evaluated, neuron apoptosis was detected by TdT-mediated dUTP-biotin nick end labeling with NeuN staining, and expression of serum inflammatory factors (interleukin-6, interleukin-1ß, and tumor necrosis factor-α) was determined by enzyme-linked immunosorbent assay. The effect of ALK5 on NOX2 expression was assessed by western-blot analysis. Targeting the relationship between miR-140-5p and ALK5 was evaluated by dual luciferase assay. Following extraction of MSCs and MSC-EVs, EVs and miR-140-5p were labeled by PKH67 and Cy3, respectively, to identify the transferring of miR-140-5p by MSC-EVs. SAH mice were treated with EVs from miR-140-5p mimic/inhibitor-transfected MSCs to detect effects of MSC-EV-miR-140-5p on brain injury and microglial polarization. RESULTS: ALK5 silencing increased the neurological score and reduced neuron apoptosis and neuroinflammation in SAH mice. ALK5 silencing inhibited M1 microglia activation by inactivating NOX2. ALK5 was a target gene of miR-140-5p. MSC-derived EVs contained miR-140-5p and transferred miR-140-5p into microglia. MSC-EV-delivered miR-140-3p reduced ALK5 expression to contribute to repression of brain injury and M1 microglia activation in SAH mice. CONCLUSIONS: MSC-derived EVs transferred miR-140-5p into microglia to downregulate ALK5 and NOX2, thus inhibiting M1 microglia activation in SAH mice.

The long-term efficacy and safety of combining ablation and left atrial appendage closure: A systematic review and meta-analysis.

BACKGROUND: Combined ablation and left atrial appendage closure (LAAC) is an alternative for atrial fibrillation patients with a high risk of stroke. However, the long-term outcomes of this combined procedure remain elusive. METHODS: PubMed, Embase, Cochrane Library, and Web of Science were systematically searched from the establishment of databases to 1 January 2021. Studies on the long-term (defined as a mean follow-up of approximately 12 months or longer) efficacy and safety outcomes of combined ablation and LAAC were included. RESULTS: A total of 16 studies comprising 1428 patients were enrolled. The pooled long-term freedom rate from atrial arrhythmia was 0.66 (95% confidence interval [CI]: 0.59-0.71), long-term successful rate sealing of LAAC was 1.00 (95% CI: 1.00-1.00), and ischemic stroke/transient ischemic attack/systemic embolism during follow-up was 0.01 (95% CI: 0.00-0.02). Meanwhile, of the periprocedural adverse events, phrenic nerve palsy, intracoronary air embolus, device embolization, and periprocedural death had a rate of 0.00 (95% CI: 0.00-0.00), procedure-related bleeding events of 0.03 (95% CI: 0.02-0.04), and pericardial effusion requiring or not requiring intervention of 0.00 (95% CI: 0.00-0.01). Moreover, for the long-term adverse events, device dislocation, intracranial bleeding, pericardial effusion requiring or not requiring intervention, and all-cause mortality had a rate of 0.00 (95% CI: 0.00-0.00), device embolization of 0.01 (95% CI: 0.00-0.01), and other bleeding events of 0.01 (95% CI: 0.00-0.03). CONCLUSION: This meta-analysis suggests that the combined atrial ablation and LAAC is an effective and safe strategy with long-term benefits.

His-Purkinje conduction system pacing: A systematic review and network meta-analysis in bradycardia and conduction disorders.

BACKGROUND: His-Purkinje conduction system pacing (HPCSP) has emerged as an effective alternative to overcome the limitations of right ventricular pacing (RVP) via physiological left ventricular activation, but there remains a paucity of comparative information for His bundle pacing (HBP) and left bundle branch pacing (LBBP). METHODS: A Bayesian random-effects network analysis was conducted to compare the relative effects of HBP, LBBP, and RVP in patients with bradycardia and conduction disorders. PubMed, Embase, Cochrane Library, and Web of Science were systematically searched from database inception until September 21, 2021. RESULTS: Twenty-eight studies involving 4160 patients were included in this meta-analysis. LBBP significantly improved success rate, pacing threshold, pacing impedance, and R-wave amplitude compared with HBP. LBBP also demonstrated a nonsignificant trend towards superior outcomes of lead complications, heart failure hospitalization, atrial fibrillation, and all-cause death. However, HBP was associated with significantly shorter paced QRS duration relative to LBBP. Despite higher success rates, shorter procedure/fluoroscopy duration, and fewer lead complications, patients receiving RVP were more likely to experience reduced left ventricular ejection fraction, longer paced QRS duration, and higher rates of heart failure hospitalization than those receiving HPCSP. No statistical differences were observed in the remaining outcome measures. CONCLUSIONS: This network meta-analysis demonstrates the efficacy and safety of HPCSP for the treatment of bradycardia and conduction disorders, with differences in pacing parameters, electrophysiology characteristics, and clinical outcomes between HBP and LBBP. Larger-scale, long-term comparative studies are warranted for further verification.

A method to screen left ventricular dysfunction through ECG based on convolutional neural network.

OBJECTIVE: This study aims to develop an artificial intelligence-based method to screen patients with left ventricular ejection fraction (LVEF) of 50% or lesser using electrocardiogram (ECG) data alone. METHODS: Convolutional neural network (CNN) is a class of deep neural networks, which has been widely used in medical image recognition. We collected standard 12-lead ECG and transthoracic echocardiogram (TTE) data including the LVEF value. Then, we paired the ECG and TTE data from the same individual. For multiple ECG-TTE pairs from a single individual, only the earliest data pair was included. All the ECG-TTE pairs were randomly divided into the training, validation, or testing data set in a ratio of 9:1:1 to create or evaluate the CNN model. Finally, we assessed the screening performance by overall accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. RESULTS: We retrospectively enrolled a total of 26 786 ECG-TTE pairs and randomly divided them into training (n = 21 732), validation (n = 2 530), and testing data set (n = 2 530). In the testing set, the CNN algorithm showed an overall accuracy of 73.9%, sensitivity of 69.2%, specificity of 70.5%, positive predictive value of 70.1%, and negative predictive value of 69.9%. CONCLUSION: Our results demonstrate that a well-trained CNN algorithm may be used as a low-cost and noninvasive method to identify patients with left ventricular dysfunction.

Systematic identification of key functional modules and genes in esophageal cancer.

BACKGROUND: Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods. METHODS: The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan-Meier plotter, and TIMER databases. RESULTS: We identified 1,044 DEGs from dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed a worse prognosis. However, CCNB1 'might not play an important role in immune cell infiltration. CONCLUSIONS: Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer.

Association between CRT(D)/ICD and renal insufficiency: A systematic review and meta-analysis.

Cardiac resynchronization therapy with or without a defibrillator (CRT(D)) and implantable cardioverter defibrillator (ICD) may reduce the risk of arrhythmia or heart failure-specific mortality and improves the prognosis of patients with chronic kidney disease (CKD) or dialysis. The aim of this study was to perform a meta-analysis investigating the relationship between CRT(D)/ICD and renal insufficiency. Cochrane Library, Web of Science, Embase, and Pubmed were systematically searched from inception to 29 October 2019. We included studies that report all-cause mortality of patients with renal insufficiency who received CRT(D)/ICD therapy. Twenty-six studies (n = 119,263) were included, exploring the relationship between CRT(D)/ICD and renal insufficiency from two aspects: (1) Compared with ICD-only, CRT(D) was associated with lower risk of all-cause mortality in CKD patients (odds ratios (OR) = 0.67; 95% confidence interval (CI), 0.60 to 0.75). For non-primary prevention (secondary prevention or both), the analysis revealed a lower risk of all-cause mortality in the ICD group than in the no-ICD group (OR = 0.47; 95% CI, 0.40 to 0.55). (2) CKD increased all-cause mortality in comparison with control group (OR = 2.12; 95% CI, 1.85 to 2.44), and so did dialysis (OR = 2.53; 95% CI, 2.34 to 2.73). Furthermore, compared with CKD3 (eGFR: 30-59 ml/min/1.73 m2 ), CKD4/5 (eGFR <30 ml/min/1.73 m2 ) was observed to have a significantly higher risk of all-cause mortality (OR = 2.70; 95% CI, 1.93 to 3.80). This review shows a clear association between CRT(D)/ICD and renal insufficiency in the aspect of all-cause mortality, and may provide a reference for the clinical application of CRT(D)/ICD.

Diagnostic and prognostic value of circular RNAs in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the sixth most common malignant tumour, which has posed a heavy health and financial burden worldwide. Due to limited symptoms at the early stage and the limitation in current biomarkers, HCC patients are usually diagnosed at the advanced stage with a pessimistic overall survival rate. Circular RNAs (circRNAs) are a subclass of single-stranded RNAs characterized by a covalently closed loop structure without 3'- or 5'-end. With advances in high-throughput sequencing technology and bioinformatics, accumulating studies have demonstrated the promotor or suppressor roles of circRNAs in the carcinogenesis, progression, and metastasis of HCC. Moreover, circRNAs are characteristic of higher abundance, stability and conservation compared with linear RNAs. Therefore, circRNAs have emerged as one of the most promising diagnostic and prognostic biomarkers for HCC with reliable accuracy, sensitivity and specificity. In this review, we briefly introduce the characteristics of circRNAs and summarize the roles of circRNAs in the biological procedures of HCC. Furthermore, we provide an overview on the potential diagnostic and prognostic value of circRNAs as biomarkers for patients with HCC. Finally, we discuss future perspectives of circRNAs in cancer research.

Gut microbiome and cancer immunotherapy.

Gut microbiome has received significant attention for its influences on a variety of host functions, especially immune modulation. With the next-generation sequencing methodologies, more knowledge is gathered about gut microbiome and its irreplaceable role in keeping the balance between human health and diseases is figured out. Immune checkpoint inhibitors (ICIs) are one of the most innovational cancer immunotherapies across cancer types and significantly expand the therapeutic options of cancer patients. However, a proportion of patients show no effective responses or develop immune-related adverse events when responses do occur. More important, it is demonstrated that the therapeutic response or treatment-limiting toxicity of cancer immunotherapy can be ameliorated or diminished by gut microbiome modulation. In this review, we first introduce the relationship between gut microbiome and cancer immunotherapy. And then, we expound the impact of gut microbiome on efficacy and toxicity of cancer immunotherapy. Further, we review approaches to manipulating gut microbiome to regulate response to ICIs. Finally, we discuss the current challenges and propose future directions to improve cancer immunotherapy via gut microbiome manipulation.

The long-term therapeutic effects of His-Purkinje system pacing on bradycardia and cardiac conduction dysfunction compared with right ventricular pacing: A systematic review and meta-analysis.

AIMS: His-Purkinje system pacing has been demonstrated as a synchronized ventricular pacing strategy via pacing His-Purkinje system directly, which can decrease the incidence of adverse cardiac structure alteration compared with right ventricular pacing (RVP). The purpose of this meta-analysis was to compare the effects of His-Purkinje system pacing and RVP in patients with bradycardia and cardiac conduction dysfunction. METHODS: PubMed, Embase, Cochrane Library, and Web of Science were systematically searched from the establishment of databases up to 15 December 2019. Studies on long-term clinical outcomes of His-Purkinje system pacing and RVP were included. Chronic paced QRS duration, chronic pacing threshold, left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume (LVEDV), left ventricular end-systolic volume (LVESV), all-cause mortality, and heart failure hospitalization were collected for meta-analysis. RESULTS: A total of 13 studies comprising 2348 patients were included in this meta-analysis. Compared with RVP group, patients receiving His-Purkinje system pacing showed improvement of LVEF (mean difference [MD], 5.65; 95% confidence interval [CI], 4.38-6.92), shorter chronic paced QRS duration (MD, - 39.29; 95% CI, - 41.90 to - 36.68), higher pacing threshold (MD, 0.8; 95% CI, 0.71-0.89) and lower risk of heart failure hospitalization (odds ratio [OR], 0.65; 95% CI, 0.44-0.96) during the follow-up. However, no statistical difference existed in LVEDV, LVESV and all-cause mortality between the two groups. CONCLUSION: Our meta-analysis suggests that His-bundle pacing is more suitable for the treatment of patients with bradycardia and cardiac conduction dysfunction.

Computational design of p-(dimethylamino)benzylidene-derived push-pull polyenes with high first-hyperpolarizabilities.

Multiple theoretical investigations on three new series of donor-bridge-acceptor substituted compounds are employed to aid in the design of NLO-phores with high first-hyperpolarizability ß. The effect of varying the acceptor (rhodanine, thiohydantoin and thiobarbituric acid derivative-based) and bridge parts of these D-π-A systems was analyzed in terms of geometric and optoelectronic parameters such as bond length alternation, ground state dipole moments, HOMO and LUMO energies, UV-vis absorption spectra, transition dipole moments, and electronic absorption energies. Various functionals with the AUG-cc-pVDZ basis set including B3LYP, PBE38, and ωB97XD, and the Hartree-Fock method were employed to calculate ß values, and the solvent effect was also considered by employing the SMD model. The variation of first-hyperpolarizabilities has been explained satisfactorily in terms of the PBE38/AUG-cc-pVDZ level calculated spectroscopic properties in the light of the sum-over-states method and the two-level model. The comprehensive study indicates that the most worthwhile targets for development as NLO-phores are compounds that include a longer π-bridge.

Enhanced Two-Photon Absorption of Cross-Conjugated Chalcone Derivatives: Modulation of the Effective π-Conjugated Structure.

Three cross-conjugated chalcone derivatives T3CT, T3CP2, and T3CP3 were designed and synthesized to develop excellent organic nonlinear optical (NLO) materials. In a Z-scan experiment, all compounds show good NLO absorption characteristics in the visible to near-infrared region. The photophysical mechanism is confirmed to be two-photon absorption (TPA)-induced excited-state absorption (ESA). Intramolecular charge transfer (ICT) observed in transient absorption spectra (TAS) significantly affects molecular NLO properties. We define the π-conjugated system that dominates the electron transition process in the cross-conjugated structure as the effective π-conjugated structure. Electron transition analysis shows a sufficiently strong ICT can effectively expand the effective π-conjugated structure in these cross-conjugated structures. The TPA cross sections of these compounds at 650 and 750 nm are only in the range of 17-97 GM. However, we achieve a significant enhancement of the TPA cross section at 580 nm (1737-2027 GM) by extending the effective π-conjugated structure. Excited by 580 nm femtosecond laser pulses, all compounds exhibit excellent OL performance and the minimum OL threshold is 4.71 × 10-3 J/cm2. The results show that these cross-conjugated chalcone derivatives have promising applications in OL, and their NLO performance can be effectively improved by modulating the effective π-conjugated structure.

A novel diagnostic method for pituitary adenoma based on magnetic resonance imaging using a convolutional neural network.

PURPOSE: This study was designed to develop a computer-aided diagnosis (CAD) system based on a convolutional neural network (CNN) to diagnose patients with pituitary tumors. METHODS: We included adult patients clinically diagnosed with pituitary adenoma (pituitary adenoma group), or adult individuals without pituitary adenoma (control group). After pre-processing, all the MRI data were randomly divided into training or testing datasets in a ratio of 8:2 to create or evaluate the CNN model. Multiple CNNs with the same structure were applied for different types of MR images respectively, and a comprehensive diagnosis was performed based on the classification results of different types of MR images using an equal-weighted majority voting strategy. Finally, we assessed the diagnostic performance of the CAD system by accuracy, sensitivity, specificity, positive predictive value, and F1 score. RESULTS: We enrolled 149 participants with 796 MR images and adopted the data augmentation technology to create 7960 new images. The proposed CAD method showed remarkable diagnostic performance with an overall accuracy of 91.02%, sensitivity of 92.27%, specificity of 75.70%, positive predictive value of 93.45%, and F1-score of 92.67% in separate MRI type. In the comprehensive diagnosis, the CAD achieved better performance with accuracy, sensitivity, and specificity of 96.97%, 94.44%, and 100%, respectively. CONCLUSION: The CAD system could accurately diagnose patients with pituitary tumors based on MR images. Further, we will improve this CAD system by augmenting the amount of dataset and evaluate its performance by external dataset.

Therapeutic advances for patients with intermediate hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the fifth most common malignant tumor and constitutes a major health threat globally. Intermediate HCC (Barcelona Clinic Liver Cancer Staging, stage B) encompasses a wide range of patients and is characterized by substantial heterogeneity with varying tumor burdens and liver functions. Therefore, it is paramount to evaluate the patient's overall conditions and to select the most appropriate therapy based on available evidence. Transarterial chemoembolization is the recommended first-line therapy for intermediate HCC patients. However, in clinical practice, other treatment options are also used as alternative therapies, such as hepatic resection, percutaneous thermal ablation, radiotherapy (RT), systemic treatment, immunotherapy, and so forth. In this review, we will introduce current treatment strategies for intermediate HCC, discuss their advantages and disadvantages, and propose future directions.

Identification of LINC01615 as potential metastasis-related long noncoding RNA in hepatocellular carcinoma.

Hepatocellular carcinoma is one of the most prevalent and fatal cancers. Studying the long noncoding RNA (lncRNA) alterations in hepatocellular carcinoma may lead to new therapeutic strategies. We checked whether there were correlations between The Cancer Genome Atlas expression profiles of the differentially expressed lncRNAs and their DNA methylation status or the copy number variations for hepatocellular carcinoma. We obtained 41 lncRNAs that were differentially expressed between tumor and normal samples, and their DNA methylation status was negatively correlated with the expression levels. We identified five lncRNAs that were recurrently amplified or deleted in tumor samples, but none of them were associated with the messenger RNA (mRNA) expression levels. To obtain the biological function of these lncRNAs, the coexpressed mRNAs in the hepatocellular carcinoma were figured out. A total of 10 lncRNAs were highly correlated with at least one gene. Six out of the ten lncRNAs were already known to be related with cancer previously. LINC01615 had 72 coexpressed genes, and we carried out the gene ontology (GO) term enrichment for these protein-coding genes. The results suggested that these lncRNAs were associated with extracellular matrix organization. To summarize, we identified 41 potentially cancer-related lncRNAs. In particular, we proposed that LINC01615 potentially affected the extracellular matrix and had further impacts on the metastasis of hepatocellular carcinoma.