DeepLION2: deep multi-instance contrastive learning framework enhancing the prediction of cancer-associated T cell receptors by attention strategy on motifs

Introduction

T cell receptor (TCR) repertoires provide valuable insights into complex human diseases, including cancers. Recent advancements in immune sequencing technology have significantly improved our understanding of TCR repertoire. Some computational methods have been devised to identify cancer-associated TCRs and enable cancer detection using TCR sequencing data. However, the existing methods are often limited by their inadequate consideration of the correlations among TCRs within a repertoire, hindering the identification of crucial TCRs. Additionally, the sparsity of cancer-associated TCR distribution presents a challenge in accurate prediction.

Methods

To address these issues, we presented DeepLION2, an innovative deep multi-instance contrastive learning framework specifically designed to enhance cancer-associated TCR prediction. DeepLION2 leveraged content-based sparse self-attention, focusing on the top k related TCRs for each TCR, to effectively model inter-TCR correlations. Furthermore, it adopted a contrastive learning strategy for bootstrapping parameter updates of the attention matrix, preventing the model from fixating on non-cancer-associated TCRs.

Results

Extensive experimentation on diverse patient cohorts, encompassing over ten cancer types, demonstrated that DeepLION2 significantly outperformed current state-of-the-art methods in terms of accuracy, sensitivity, specificity, Matthews correlation coefficient, and area under the curve (AUC). Notably, DeepLION2 achieved impressive AUC values of 0.933, 0.880, and 0.763 on thyroid, lung, and gastrointestinal cancer cohorts, respectively. Furthermore, it effectively identified cancer-associated TCRs along with their key motifs, highlighting the amino acids that play a crucial role in TCR-peptide binding.

Conclusion

These compelling results underscore DeepLION2's potential for enhancing cancer detection and facilitating personalized cancer immunotherapy. DeepLION2 is publicly available on GitHub, at https://github.com/Bioinformatics7181/DeepLION2, for academic use only.

Enhanced hemocompatibility and rapid magnetic anastomosis of electrospun small-diameter artificial vascular grafts

Background: Small-diameter (<6 mm) artificial vascular grafts (AVGs) are urgently required in vessel reconstructive surgery but constrained by suboptimal hemocompatibility and the complexity of anastomotic procedures. This study introduces coaxial electrospinning and magnetic anastomosis techniques to improve graft performance. Methods: Bilayer poly(lactide-co-caprolactone) (PLCL) grafts were fabricated by coaxial electrospinning to encapsulate heparin in the inner layer for anticoagulation. Magnetic rings were embedded at both ends of the nanofiber conduit to construct a magnetic anastomosis small-diameter AVG. Material properties were characterized by micromorphology, fourier transform infrared (FTIR) spectra, mechanical tests, in vitro heparin release and hemocompatibility. In vivo performance was evaluated in a rabbit model of inferior vena cava replacement. Results: Coaxial electrospinning produced PLCL/heparin grafts with sustained heparin release, lower platelet adhesion, prolonged clotting times, higher Young's modulus and tensile strength versus PLCL grafts. Magnetic anastomosis was significantly faster than suturing (3.65 ± 0.83 vs. 20.32 ± 3.45 min, p < 0.001) and with higher success rate (100% vs. 80%). Furthermore, magnetic AVG had higher short-term patency (2 days: 100% vs. 60%; 7 days: 40% vs. 0%) but similar long-term occlusion as sutured grafts. Conclusion: Coaxial electrospinning improved hemocompatibility and magnetic anastomosis enhanced implantability of small-diameter AVG. Short-term patency was excellent, but further optimization of anticoagulation is needed for long-term patency. This combinatorial approach holds promise for vascular graft engineering.

An innovative gene expression modulating strategy by converting nucleic acids into HNC therapeutics using carrier-free nanoparticles

Background

Cell fate and microenvironmental changes resulting from aberrant expression of specific proteins in tumors are one of the major causes of inadequate anti-tumor immune response and poor prognosis in head and neck cancer (HNC). Eukaryotic initiation factor 3C (eIF3c) has emerged as a promising therapeutic target for HNC due to its ability to regulate protein expression levels in tumor cells, but its drug development is difficult to achieve by targeting traditional protein-protein interactions. siRNA has emerged as a highly promising modality for drug development targeting eIF3c, while its application is hindered by challenges pertaining to inadequate stability and insufficient concentration specifically within tumor sites.

Method

We employed a method to convert flexible siRNAs into stable and biologically active infinite Auric-sulfhydryl coordination supramolecular siRNAs (IacsRNAs). Through coordinated self-assembly, we successfully transformed eIF3C siRNAs into the carrier-free HNC nanotherapeutic agent Iacs-eif3c-RNA. The efficacy of this agent was evaluated in vivo using HNC xenograft models, demonstrating promising antitumor effects.

Results

Iacs-eif3c-RNA demonstrated the ability to overcome the pharmacological obstacle associated with targeting eIF3C, resulting in a significant reduction in eIF3C expression within tumor tissues, as well as effective tumor cell proliferating suppression and apoptosis promotion. In comparison to monotherapy utilizing the chemotherapeutic agent cisplatin, Iacs-eif3c-RNA exhibited superior anti-tumor efficacy and favorable biosafety.

Conclusion

The utilization of Iacs-eif3c-RNA as a carrier-free nanotherapeutic agent presents a promising and innovative approach for addressing HNC treating challenges. Moreover, this strategy demonstrates potential for the translation of therapeutic siRNAs into clinical drugs, extending its applicability to the treatment of other cancers and various diseases.

Principles, developments, and applications of spatially resolved spectroscopy in agriculture: a review

Agriculture is the primary source of human survival, which provides the most basic living and survival conditions for human beings. As living standards continue to improve, people are also paying more attention to the quality and safety of agricultural products. Therefore, the detection of agricultural product quality is very necessary. In the past decades, the spectroscopy technique has been widely used because of its excellent results in agricultural quality detection. However, traditional spectral inspection methods cannot accurately describe the internal information of agricultural products. With the continuous research and development of optical properties, it has been found that the internal quality of an object can be better reflected by separating the properties of light, such as its absorption and scattering properties. In recent years, spatially resolved spectroscopy has been increasingly used in the field of agricultural product inspection due to its simple compositional structure, low-value cost, ease of operation, efficient detection speed, and outstanding ability to obtain information about agricultural products at different depths. It can also separate optical properties based on the transmission equation of optics, which allows for more accurate detection of the internal quality of agricultural products. This review focuses on the principles of spatially resolved spectroscopy, detection equipment, analytical methods, and specific applications in agricultural quality detection. Additionally, the optical properties methods and direct analysis methods of spatially resolved spectroscopy analysis methods are also reported in this paper.

Insight into the Causal Relationship between Gut Microbiota and Back Pain: A Two Sample Bidirectional Mendelian Randomization Study

Observational studies have shown that alterations in gut microbiota composition are associated with low back pain. However, it remains unclear whether the association is causal. To reveal the causal association between gut microbiota and low back pain, a two-sample bidirectional Mendelian randomization (MR) analysis is performed. The inverse variance weighted regression (IVW) is performed as the principal MR analysis. MR-Egger and Weighted Median is further conducted as complementary analysis to validate the robustness of the results. Finally, a reverse MR analysis is performed to evaluate the possibility of reverse causation. The inverse variance weighted (IVW) method suggests that Peptostreptococcaceae (odds ratio [OR] 1.056, 95% confidence interval [CI] [1.015-1.098], P IVW = 0.010), and Lactobacillaceae (OR 1.070, 95% CI [1.026-1.115], P IVW = 0.003) are positively associated with back pain. The Ruminococcaceae (OR 0.923, 95% CI [0.849-0.997], P IVW = 0.033), Butyricicoccus (OR 0.920, 95% CI [0.868 - 0.972], P IVW = 0.002), and Lachnospiraceae (OR 0.948, 95% CI [0.903-0.994], P IVW = 0.022) are negatively associated with back pain. In this study, underlying causal relationships are identified among gut microbiota and low back pain. Notably, further research is needed on the biological mechanisms by which gut microbiota influences low back pain.

Radiotranscriptomics identified new mRNAs and miRNA markers for distinguishing prostate cancer from benign prostatic hyperplasia

The present study investigated ultrasound (US) phenotypes reflecting prostate cancer (PCa)-related genetic mutations. Herein, integration of radiotranscriptomic data, US and contrast-enhanced ultrasound (CEUS) radiomic images, and RNA sequencing was performed with the aim of significantly improving the accuracy of PCa prognosis. We performed radiotranscriptomic analysis of clinical, imaging, and two genomic (mRNA and microRNA expression) datasets from 48 and 22 men with PCa and benign prostatic hyperplasia (BPH), respectively. Twenty-three US texture features and four microvascular perfusion features were associated with various patterns of 52 differentially expressed genes related to PCa (p < 0.05); 17 overexpressed genes were associated with two key texture features. Twelve overexpressed genes were identified using microvascular perfusion features. Furthermore, mRNA and miRNA biomarkers could be used to distinguish between PCa and BPH. Compared with RNA sequencing, B-mode and CEUS features reflected genomic alterations associated with hormone receptor status, angiogenesis, and prognosis in patients with PCa. These findings indicate the potential of US to assess biomarker levels in patients with PCa.

Constructing indicator species distribution models to study the potential invasion risk of invasive plants: A case of the invasion of Parthenium hysterophorus in China

Aim

As invasive plants are often in a non-equilibrium expansion state, traditional species distribution models (SDMs) are likely underestimating their suitable habitat. New methods are necessary to identify potential invasion risk areas.

Location

Tropical monsoon rainforest and subtropical evergreen broad-leaved forest regions in China.

Methods

We took Parthenium hysterophorus as a case study to predict its potential invasion risk using climate, terrain, and human activity variables. First, a generalized joint attribute model (GJAM) was constructed using the occurrence of P. hysterophorus and its 27 closely related species in Taiwan, given it is widely distributed in Taiwan. Based on the output correlation values, two positively correlated species (Cardiospermum halicacabum and Portulaca oleracea) and one negatively correlated species (Crassocephalum crepidioides) were selected as indicator species. Second, the distributions of P. hysterophorus and its indicator species in the study area were predicted separately using an ensemble model (EM). Third, when selecting indicator species to construct indicator SDMs, two treatments (indicator species with positive correlation only, or both positive and negative correlation) were considered. The indicator species' EM predictions were overlaid using a weighted average method, and a better indicator SDMs prediction result was selected by comparison. Finally, the EM prediction result of P. hysterophorus was used to optimize the indicator SDMs result by a maximum overlay.

Results

The optimized indicator SDMs prediction showed an expanded range beyond the current geographic range compared to EM and the thresholds for predicting key environmental variables were wider. It also reinforced the human activities' influence on the potential distribution of P. hysterophorus.

Main Conclusions

For invasive plants with expanding ranges, information about indicator species distribution can be borrowed as a barometer for areas not currently invaded. The optimized indicator SDMs allow for more efficient potential invasion risk prediction. On this basis, invasive plants can be prevented earlier.

Transcriptomic and phenotype analysis revealed the role of rpoS in stress resistance and virulence of a novel ST3355 ESBL-producing hypervirulent Klebsiella pneumoniae isolate

Introduction

An extended-spectrum beta-lactamase (ESBL)-hypervirulent Klebsiella pneumoniae (HvKP) strain HKE9 was isolated from the blood in an outpatient.

Methods

The effect of the global regulatory factor RpoS on antimicrobial resistance, pathogenicity, and environmental adaptability was elucidated.

Results

HKE9 is a novel ST3355 (K20/O2a) hypervirulent strain with a positive string test and resistant to cephems except cefotetan. It has a genome size of 5.6M, including two plasmids. CTX-M-15 was found in plasmid 2, and only ompk37 was found in the chromosome. HKE9 could produce bacterial siderophores, and genes of enterobactin, yersiniabactin, aerobactin, and salmochelin have been retrieved in the genome. As a global regulatory factor, knockout of rpoS did not change antimicrobial resistance or hemolytic phenotype while increasing the virulence to Galleria mellonella larvae and showing higher viscosity. Moreover, rpoS knockout can increase bacterial competitiveness and cell adhesion ability. Interestingly, HKE9-M-rpoS decreased resistance to acidic pH, high osmotic pressure, heat shock, and ultraviolet and became sensitive to disinfectants (H2O2, alcohol, and sodium hypochlorite). Although there were 13 Type 6 secretion system (T6SS) core genes divided into two segments with tle1 between segments in the chromosome, transcriptomic analysis showed that rpoS negatively regulated T4SS located on plasmid 2, type 1, and type 3 fimbriae and positively regulate genes responsible for acidic response, hyperosmotic pressure, heat shock, oxidative stress, alcohol and hypochlorous acid metabolism, and quorum sensing.

Discussion

Here, this novel ST3355 ESBL-HvKP strain HKE9 may spread via various clonal types. The important regulation effect of rpoS is the enhanced tolerance and resistance to environmental stress and disinfectants, which may be at the cost of reducing virulence and regulated by T4SS.

Associations of lipid accumulation product, visceral adiposity index, and triglyceride-glucose index with subclinical organ damage in healthy Chinese adults

Background and aims

Obesity is an independent risk factor for cardiovascular disease development. Here, we aimed to examine and compare the predictive values of three novel obesity indices, lipid accumulation product (LAP), visceral adiposity index (VAI), and triglyceride-glucose (TyG) index, for cardiovascular subclinical organ damage.

Methods

A total of 1,773 healthy individuals from the Hanzhong Adolescent Hypertension Study cohort were enrolled. Anthropometric, biochemical, urinary albumin-to-creatinine ratio (uACR), brachial-ankle pulse wave velocity (baPWV), and Cornell voltage-duration product data were collected. Furthermore, the potential risk factors for subclinical organ damage were investigated, with particular emphasis on examining the predictive value of the LAP, VAI, and TyG index for detecting subclinical organ damage.

Results

LAP, VAI, and TyG index exhibited a significant positive association with baPWV and uACR. However, only LAP and VAI were found to have a positive correlation with Cornell product. While the three indices did not show an association with electrocardiographic left ventricular hypertrophy, higher values of LAP and TyG index were significantly associated with an increased risk of arterial stiffness and albuminuria. Furthermore, after dividing the population into quartiles, the fourth quartiles of LAP and TyG index showed a significant association with arterial stiffness and albuminuria when compared with the first quartiles, in both unadjusted and fully adjusted models. Additionally, the concordance index (C-index) values for LAP, VAI, and TyG index were reasonably high for arterial stiffness (0.856, 0.856, and 0.857, respectively) and albuminuria (0.739, 0.737, and 0.746, respectively). Lastly, the analyses of continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI) demonstrated that the TyG index exhibited significantly higher predictive values for arterial stiffness and albuminuria compared with LAP and VAI.

Conclusion

LAP, VAI, and, especially, TyG index demonstrated utility in screening cardiovascular subclinical organ damage among Chinese adults in this community-based sample. These indices have the potential to function as markers for early detection of cardiovascular disease in otherwise healthy individuals.

Inhibition of CDK1 Overcomes Oxaliplatin Resistance by Regulating ACSL4-mediated Ferroptosis in Colorectal Cancer

Oxaliplatin is a widely used chemotherapy drug for patients with advanced colorectal cancer (CRC); however, frequent drug resistance limits its therapeutic efficacy in patients. Here, this work identifies cyclin-dependent kinase 1 (CDK1) as a critical contributor to oxaliplatin resistance via in vitro and in vivo CRISPR/Cas9 screening. CDK1 is highly expressed in oxaliplatin-resistant cells and tissues due to the loss of N6-methyladenosine modification. Genetic and pharmacological blockade of CDK1 restore the susceptibility of CRC cells to oxaliplatin in vitro and in cell/patient-derived xenograft models. Mechanistically, CDK1 directly binds to and phosphorylates Acyl-CoA synthetase long-chain family 4 (ACSL4) at S447, followed by recruitment of E3 ubiquitin ligase UBR5 and polyubiquitination of ACSL4 at K388, K498, and K690, which leads to ACSL4 protein degradation. Reduced ACSL4 subsequently blocks the biosynthesis of polyunsaturated fatty acid containing lipids, thereby inhibiting lipid peroxidation and ferroptosis, a unique iron-dependent form of oxidative cell death. Moreover, treatment with a ferroptosis inhibitor nullifies the enhancement of CRC cell sensitivity to oxaliplatin by CDK1 blockade in vitro and in vivo. Collectively, the findings indicate that CDK1 confers oxaliplatin resistance to cells by suppressing ferroptosis. Therefore, administration of a CDK1 inhibitor may be an attractive strategy to treat patients with oxaliplatin-resistant CRC.

Deep learning for detecting visually impaired cataracts using fundus images

Purpose: To develop a visual function-based deep learning system (DLS) using fundus images to screen for visually impaired cataracts. Materials and methods: A total of 8,395 fundus images (5,245 subjects) with corresponding visual function parameters collected from three clinical centers were used to develop and evaluate a DLS for classifying non-cataracts, mild cataracts, and visually impaired cataracts. Three deep learning algorithms (DenseNet121, Inception V3, and ResNet50) were leveraged to train models to obtain the best one for the system. The performance of the system was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. Results: The AUC of the best algorithm (DenseNet121) on the internal test dataset and the two external test datasets were 0.998 (95% CI, 0.996-0.999) to 0.999 (95% CI, 0.998-1.000),0.938 (95% CI, 0.924-0.951) to 0.966 (95% CI, 0.946-0.983) and 0.937 (95% CI, 0.918-0.953) to 0.977 (95% CI, 0.962-0.989), respectively. In the comparison between the system and cataract specialists, better performance was observed in the system for detecting visually impaired cataracts (p < 0.05). Conclusion: Our study shows the potential of a function-focused screening tool to identify visually impaired cataracts from fundus images, enabling timely patient referral to tertiary eye hospitals.

Clinicopathological characteristics and prognostic analysis of breast cancer with a hormone receptor status of ER(-)/PR(+)

Background

It is unknown whether ER(-)/PR(+) breast cancer is an independent breast cancer subtype, how it differs from other subtypes, and what its significance is regarding treatment and prognosis. This study compared ER(-)/PR(+) breast cancer with other subtypes to better understand the biological characteristics and prognosis of ER(-)/PR(+) breast cancer, to guide clinical treatment and establish a theoretical foundation.

Methods

We retrospectively analyzed data for patients diagnosed with breast cancer in the Surveillance, Epidemiology, and End Results (SEER) database. The clinicopathological characteristics of ER(-)/PR(+) breast cancer, including age, tumor size, lymph node status, HER-2 status, pathological type and histological grade, were compared with other types of breast cancer. A risk scoring system was developed based on independent risk factors influencing prognosis to predict the patient's prognosis, and a nomogram model was created to predict the patient's survival rate. Receiver operating characteristic curve (ROC) and calibration curve was used to evaluate the predictive performance of the nomogram.

Results

The rates of T3-4, lymph node positivity, HER-2 positivity, infiltrating non-special pathological type, and G3 were significantly higher in ER(-)/PR(+) than in ER(+)/PR(+) cancer (p <0.001). ER(-)/PR(+) was similar to biological activity of ER(-)/PR(-) type. ER(-)/PR(+)/HER-2(+) patients had a better survival prognosis than ER(-)/PR(+) HER-2(-) patients (p<0.05). The prognosis of ER-/PR+ breast cancer was significantly associated with age, HER-2 status, and T stage.

Conclusion

ER(-)/PR(+) breast cancer is more similar to ER(-)/PR(-) breast cancer than other breast cancer subtypes, with an early age of onset, a high proportion of infiltrating non-special types, a high histological grade, and a high HER-2 positivity rate. Whether HER-2 positivity can improve the prognosis of ER(-)/PR(+)breast cancer is worth further discussion. The risk scoring system we developed can effectively distinguish between high-risk and low-risk patients. The nomogram we created had a concordance index of 0.736, and the calibration curve showed good agreement between the predicted and observed outcomes.

Activation of ryanodine-sensitive calcium store drives pseudo-allergic dermatitis via Mas-related G protein-coupled receptor X2 in mast cells

Mast cell (MC) activation is implicated in the pathogenesis of multiple immunodysregulatory skin disorders. Activation of an IgE-independent pseudo-allergic route has been recently found to be mainly mediated via Mas-Related G protein-coupled receptor X2 (MRGPRX2). Ryanodine receptor (RYR) regulates intracellular calcium liberation. Calcium mobilization is critical in the regulation of MC functional programs. However, the role of RYR in MRGPRX2-mediated pseudo-allergic skin reaction has not been fully addressed. To study the role of RYR in vivo, we established a murine skin pseudo-allergic reaction model. RYR inhibitor attenuated MRGPRX2 ligand substance P (SP)-induced vascular permeability and neutrophil recruitment. Then, we confirmed the role of RYR in an MC line (LAD2 cells) and primary human skin-derived MCs. In LAD2 cells, RYR inhibitor pretreatment dampened MC degranulation (detected by β-hexosaminidase retlease), calcium mobilization, IL-13, TNF-α, CCL-1, CCL-2 mRNA, and protein expression activated by MRGPRX2 ligands, namely, compound 48/80 (c48/80) and SP. Moreover, the inhibition effect of c48/80 by RYR inhibitor was verified in skin MCs. After the confirmation of RYR2 and RYR3 expression, the isoforms were silenced by siRNA-mediated knockdown. MRGPRX2-induced LAD2 cell exocytosis and cytokine generation were substantially inhibited by RYR3 knockdown, while RYR2 had less contribution. Collectively, our finding suggests that RYR activation contributes to MRGPRX2-triggered pseudo-allergic dermatitis, and provides a potential approach for MRGPRX2-mediated disorders.

NADPH-dependent ROS accumulation contributes to the impaired osteogenic differentiation of periodontal ligament stem cells under high glucose conditions

Diabetes mellitus is an established risk factor for periodontal disease that can aggravate the severity of periodontal inflammation and accelerate periodontal destruction. The chronic high glucose condition is a hallmark of diabetes-related pathogenesis, and has been demonstrated to impair the osteogenic differentiation of periodontal ligament stem cells (PDLSCs), leading to delayed recovery of periodontal defects in diabetic patients. Reactive oxygen species (ROS) are small molecules that can influence cell fate determination and the direction of cell differentiation. Although excessive accumulation of ROS has been found to be associated with high glucose-induced cell damage, the underlying mechanisms remain unclear. Nicotinamide adenine dinucleotide phosphate (NADPH) is an important electron donor and functions as a critical ROS scavenger in antioxidant systems. It has been identified as a key mediator of various biological processes, including energy metabolism and cell differentiation. However, whether NADPH is involved in the dysregulation of ROS and further compromise of PDLSC osteogenic differentiation under high glucose conditions is still not known. In the present study, we found that PDLSCs incubated under high glucose conditions showed impaired osteogenic differentiation, excessive ROS accumulation and increased NADPH production. Furthermore, after inhibiting the synthesis of NADPH, the osteogenic differentiation of PDLSCs was significantly enhanced, accompanied by reduced cellular ROS accumulation. Our findings demonstrated the crucial role of NADPH in regulating cellular osteogenic differentiation under high glucose conditions and suggested a new target for rescuing high glucose-induced cell dysfunction and promoting tissue regeneration in the future.

OCRFinder: a noise-tolerance machine learning method for accurately estimating open chromatin regions

Open chromatin regions are the genomic regions associated with basic cellular physiological activities, while chromatin accessibility is reported to affect gene expressions and functions. A basic computational problem is to efficiently estimate open chromatin regions, which could facilitate both genomic and epigenetic studies. Currently, ATAC-seq and cfDNA-seq (plasma cell-free DNA sequencing) are two popular strategies to detect OCRs. As cfDNA-seq can obtain more biomarkers in one round of sequencing, it is considered more effective and convenient. However, in processing cfDNA-seq data, due to the dynamically variable chromatin accessibility, it is quite difficult to obtain the training data with pure OCRs or non-OCRs, and leads to a noise problem for either feature-based approaches or learning-based approaches. In this paper, we propose a learning-based OCR estimation approach with a noise-tolerance design. The proposed approach, named OCRFinder, incorporates the ideas of ensemble learning framework and semi-supervised strategy to avoid potential overfitting of noisy labels, which are the false positives on OCRs and non-OCRs. Compared to different noise control strategies and state-of-the-art approaches, OCRFinder achieved higher accuracies and sensitivities in the experiments. In addition, OCRFinder also has an excellent performance in ATAC-seq or DNase-seq comparison experiments.

ATAC-seq reveals the roles of chromatin accessibility in the chondrocytes of Kashin-Beck disease compared with primary osteoarthritis

Objective: This study aimed to investigate the roles of accessible chromatin in understanding the different pathogeneses between Kashin-Beck disease (KBD) and primary osteoarthritis (OA). Methods: Articular cartilages of KBD and OA patients were collected, and after tissue digestion, primary chondrocytes were cultured in vitro. Assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) was performed to compare the accessible chromatin differences of chondrocytes between KBD and OA groups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were executed for the promoter genes. Then, the IntAct online database was used to generate networks of significant genes. Finally, we overlapped the analysis of differentially accessible region (DAR)-associated genes and differentially expressed genes (DEGs) obtained from whole-genomic microarray. Results: We obtained 2,751 total DARs, which contained 1,985 loss and 856 gain DARs and belonged to 11 location distributions. We obtained 218 motifs associated with loss DARs, 71 motifs associated with gain DARs, 30 motif enrichments of loss DARs, and 30 motif enrichments of gain DARs. In total, 1,749 genes are associated with loss DARs, and 826 genes are associated with gain DARs. Among them, 210 promoter genes are associated with loss DARs, and 112 promoter genes are associated with gain DARs. We obtained 15 terms of GO enrichment and 5 terms of KEGG pathway enrichment from loss DAR promoter genes, and 15 terms of GO enrichment and 3 terms of KEGG pathway enrichment from gain DAR promoter genes. We obtained CAPN6 and other 2 overlap genes from loss DARs-vs-down DEGs, AMOTL1 from gain DARs-vs-down DEGs, EBF3 and other 12 overlap genes from loss DARs-vs-up DEGs, and ADARB1 and other 10 overlap genes from 101 gain DARs-vs-up DEGs. These overlap genes were built into 4 gene interaction networks. Conclusion: FGF7, GPD1L, NFIB, RUNX2, and VCAM1 were the overlapped genes from the DAR-associated genes and DEGs. These genes were associated with the abnormal chondrocyte function, which may play crucial roles in different processes between KBD and OA in the way of accessible chromatin.

TMBserval: a statistical explainable learning model reveals weighted tumor mutation burden better categorizing therapeutic benefits

A high tumor mutation burden (TMB) is known to drive the response to immune checkpoint inhibitors (ICI) and is associated with favorable prognoses. However, because it is a one-dimensional numerical representation of non-synonymous genetic alterations, TMB suffers from clinical challenges due to its equal quantification. Since not all mutations elicit the same antitumor rejection, the effect on immunity of neoantigens encoded by different types or locations of somatic mutations may vary. In addition, other typical genomic features, including complex structural variants, are not captured by the conventional TMB metric. Given the diversity of cancer subtypes and the complexity of treatment regimens, this paper proposes that tumor mutations capable of causing various degrees of immunogenicity should be calculated separately. TMB should therefore, be segmented into more exact, higher dimensional feature vectors to exhaustively measure the foreignness of tumors. We systematically reviewed patients' multifaceted efficacy based on a refined TMB metric, investigated the association between multidimensional mutations and integrative immunotherapy outcomes, and developed a convergent categorical decision-making framework, TMBserval (Statistical Explainable machine learning with Regression-based VALidation). TMBserval integrates a multiple-instance learning concept with statistics to create a statistically interpretable model that addresses the broad interdependencies between multidimensional mutation burdens and decision endpoints. TMBserval is a pan-cancer-oriented many-to-many nonlinear regression model with discrimination and calibration power. Simulations and experimental analyses using data from 137 actual patients both demonstrated that our method could discriminate between patient groups in a high-dimensional feature space, thereby rationally expanding the beneficiary population of immunotherapy.

Genetic polymorphisms in CYP4F2 may be associated with lung cancer risk among females and no-smoking Chinese population

Background

Our study aimed to explore the potential association of CYP4F2 gene polymorphisms with lung cancer (LC) risk.

Methods

The five variants in CYP4F2 were genotyped using Agena MassARRAY in 507 cases and 505 controls. Genetic models and haplotypes based on logistic regression analysis were used to evaluate the potential association between CYP4F2 polymorphisms and LC susceptibility.

Results

This study observed that rs12459936 was linked to an increased risk of LC in no-smoking participants (allele: OR = 1.38, p = 0.035; homozygote: OR = 2.00, p = 0.035; additive: OR = 1.40, p = 0.034) and females (allele: OR = 1.64, p = 0.002; homozygote: OR = 2.57, p = 0.006; heterozygous: OR = 2.56, p = 0.001; dominant: OR = 2.56, p &lt; 0.002; additive: OR = 1.67, p = 0.002). Adversely, there was a significantly decreased LC risk for rs3093110 in no-smoking participants (heterozygous: OR = 0.56, p = 0.027; dominant: OR = 0.58, p = 0.035), rs3093193 (allele: OR = 0.66, p = 0.016; homozygote: OR = 0.33, p = 0.011; recessive: OR = 0.38, p = 0.021; additive: OR = 0.64, p = 0.014), rs3093144 (recessive: OR = 0.20, p = 0.045), and rs3093110 (allele: OR = 0.54, p = 0.010; heterozygous: OR = 0.50, p = 0.014; dominant: OR = 0.49, p = 0.010; additive: OR = 0.54, p = 0.011) in females.

Conclusions

The study demonstrated that CYP4F2 variants were associated with LC susceptibility, with evidence suggesting that this connection may be affected by gender and smoking status.

Prevalence of diabetes in the USA from the perspective of demographic characteristics, physical indicators and living habits based on NHANES 2009-2018

OBJECTIVE

To determine differences in DM in the U.S. population according to demographic characteristics, physical indicators and living habits.

METHODS

23 546 participants in the 2009 to 2018 National Health and Nutrition Examination Survey (NHANES) who were 20 year of age or older and not pregnant. All analyses used weighted samples and considered the stratification and clustering of the design. Specific indicators include length of leg (cm), BMI (kg/cm²), TCHOL (mg/dL), fasting plasma glucose (mg/dL) and comparison of means and the proportion of participants with DM.

RESULTS

The prevalence of DM in the USA has been rising modestly in the past decade, and were consistent and robust for the observed differences in age, sex, and ethnicity. Compared with white participants, black participants and Mexican-American were both more likely (P<0.001) to have diabetes: 14.6% (CI, 13.6% to 15.6%) among black participants, 10.6% (CI, 9.9% to 11.3%) among white participants, and 13.5% (CI, 11.9% to 15.2%) among Mexican-American participants. The prevalence of diabetes is increasing with age, males peaked around the 60s, and women around the 70s. The overall mean leg length and TCHOL was lower in diabetics than in non-diabetics (1.07 cm, 18.67 mg/dL, respectively), while mean BMI were higher in diabetics than in non-diabetics (4.27 kg/cm2). DM had the greatest effect on decline of TCHOL in white participants (23.6 mg/dL), less of an effect in black participants (9.67 mg/dL), and the least effect in Mexican-American participants (8.25 mg/dL). Notably, smoking had great effect on percent increment of DM in whites (0.2%), and have little effect on black and Mexican-Americans.

CONCLUSIONS

DM is more common in the general population than might be clinically recognized, and the prevalence of DM was associated to varying degrees with many indicators of demographic characteristics, physical indicators, and living habits. These indicators should be linked with medical resource allocation and scientific treatment methods to comprehensively implement the treatment of DM.

Cytogenetic identification and molecular marker development of a novel wheat-Leymus mollis 4Ns(4D) alien disomic substitution line with resistance to stripe rust and Fusarium head blight

Leymus mollis (Trin.) Pilg. (2n = 4x = 28, NsNsXmXm) potentially harbours useful genes that might contribute to the improvement of wheat. We describe M862 as a novel wheat-L. mollis alien disomic substitution line from a cross between wheat cv. 7182 and octoploid Tritileymus M47. Cytological observations indicate that M862 has a chromosome constitution of 2n = 42 = 21II. Two 4D chromosomes of wheat substituted by two L. mollis Ns chromosomes were observed, using the GISH and ND-FISH analyses. Molecular marker, 55K SNP array and wheat-P. huashanica liquid array (GenoBaits^®WheatplusPh) analyses further indicate that the alien chromosomes are L. mollis 4Ns. Therefore, it was deduced that M862 was a wheat-L. mollis 4Ns(4D) alien disomic substitution line. There were also changes in chromosomes 1A, 1D, 2B and 5A detected by ND-FISH analysis. Transcriptome sequencing showed that the structural variation of 1D, 1A and 5A may have smaller impact on gene expression than that for 2B. In addition, a total of 16 markers derived from Lm#4Ns were developed from transcriptome sequences, and these proved to be highly effective for tracking the introduced chromosome. M862 showed reduced height, larger grains (weight and width), and was highly resistance to CYR32 and CYR34 stripe rust races at the seedling stage and mixed stripe rust races (CYR32, CYR33 and CYR34) at the adult stage. It was also resistance to Fusarium head blight (FHB). This alien disomic substitution line M862 may be exploited as an important genetic material in the domestication of stipe rust and FHB resistance wheat varieties.

Construction of m6A-based prognosis signature and prediction for immune and anti-angiogenic response

Background: Increasing evidence illustrated that m6A regulator-mediated modification plays a crucial role in regulating tumor immune and angiogenesis microenvironment. And the combination of immune checkpoint inhibitor and anti-angiogenic therapy has been approved as new first-line therapy for advanced HCC. This study constructed a novel prognosis signature base on m6A-mediated modification and explored the related mechanism in predicting immune and anti-angiogenic responses.

Methods: Gene expression profiles and clinical information were collected from TCGA and GEO. The ssGSEA, MCPCOUNT, and TIMER 2.0 algorithm was used to Estimation of immune cell infiltration. The IC₅₀ of anti-angiogenic drugs in GDSC was calculated by the “pRRophetic” package. IMvigor210 cohort and Liu et al. cohort were used to validate the capability of immunotherapy response. Hepatocellular carcinoma single immune cells sequencing datasets GSE140228 were collected to present the expression landscapes of 5 hub genes in different sites and immune cell subpopulations of HCC patients.

Results: Three m6A clusters with distinct immune and angiogenesis microenvironments were identified by consistent cluster analysis based on the expression of m6A regulators. We further constructed a 5-gene prognosis signature (termed as m6Asig-Score) which could predict both immune and anti-angiogenic responses. We illustrated that high m6Asig-Score is associated with poor prognosis, advanced TNM stage, and high TP53 mutation frequency. Besides, the m6Asig-Score was negatively associated with immune checkpoint inhibitors and anti-angiogenic drug response. We further found that two of the five m6Asig-Score inner genes, B2M and SMOX, were associated with immune cell infiltration, immune response, and the sensitivity to sorafenib, which were validated in two independent immunotherapy cohorts and the Genomics of Drug Sensitivity in Cancer (GDSC) database.

Conclusion: We constructed a novel prognosis signature and identified B2M and SMOX for predicting immune and anti-angiogenic efficacy in HCC, which may guide the combined treatment strategies of immunotherapy and anti-angiogenic therapy in HCC.

Inquiring the inter-relationships amongst grain-filling, grain-yield, and grain-quality of Japonica rice at high latitudes of China

The widespread impacts of projected global and regional climate change on rice yield have been investigated by different indirect approaches utilizing various simulation models. However, direct approaches to assess the impacts of climatic variabilities on rice growth and development may provide more reliable evidence to evaluate the effects of climate change on rice productivity. Climate change has substantially impacted rice production in the mid-high latitudes of China, especially in Northeast China (NEC). Climatic variabilities occurring in NEC since the 1970s have resulted in an obvious warming trend, which made this region one of the three major rice-growing regions in China. However, the projections of future climate change have indicated the likelihood of more abrupt and irregular climatic changes, posing threats to rice sustainability in this region. Hence, understanding the self-adaptability and identifying adjustive measures to climate variability in high latitudes has practical significance for establishing a sustainable rice system to sustain future food security in China. A well-managed field study under randomized complete block design (RCBD) was conducted in 2017 and 2018 at two study sites in Harbin and Qiqihar, located in Heilongjiang province in NEC. Four different cultivars were evaluated: Longdao-18, Longdao-21 (longer growth duration), Longjing-21, and Suijing-18 (shorter growth duration) to assess the inter-relationships among grain-filling parameters, grain yield and yield components, and grain quality attributes. To better compare the adaptability mechanisms between grain-filling and yield components, the filling phase was divided into three sub-phases (start, middle, and late). The current study evaluated the formation and accumulation of the assimilates in superior and inferior grains during grain-filling, mainly in the middle sub-phase, which accounted for 59.60% of the yield. The grain yields for Suijing-18, Longjing-21, Longdao-21, and Longdao-18 were 8.02%, 12.78%, 17.19%, and 20.53% higher in Harbin than those in Qiqihar, respectively in 2017, with a similar trend observed in 2018. At Harbin, a higher number of productive tillers was noticed in Suijing-18, with averages of 17 and 15 in 2017 and 2018, respectively. The grain-filling parameters of yield analysis showed that the filling duration in Harbin was conducive to increased yield but the low dry weight of inferior grains was a main factor limiting the yield in Qiqihar. The average protein content values in Harbin were significantly higher (8.54% and 9.13%) than those in Qiqihar (8.34% and 9.14%) in 2017 and 2018, respectively. The amylose content was significantly higher in Harbin (20.03% and 22.27%) than those in Qiqihar (14.44% and 14.67%) in 2017 and 2018, respectively. The chalkiness percentage was higher in Qiqihar, indicating that Harbin produced good quality rice. This study provides more direct evidence of the relative changes in rice grain yield due to changes in grain-filling associated with relative changes in environmental components. These self-adaptability mechanisms to climatic variability and the inter-relationships between grain-filling and grain yield underscore the urgent to investigate and explore measures to improve Japonica rice sustainability, with better adaptation to increasing climatic variabilities. These findings may also be a reference for other global rice regions at high latitudes in addressing the impacts of climate change on future rice sustainability.

ARF2-PIF5 interaction controls transcriptional reprogramming in the ABS3-mediated plant senescence pathway

One of the hallmarks of plant senescence is the global transcriptional reprogramming coordinated by a plethora of transcription factors (TFs). However, mechanisms underlying the interactions between different TFs in modulating senescence remain obscure. Previously, we discovered that plant ABS3 subfamily MATE transporter genes regulate senescence and senescence-associated transcriptional changes. In a genetic screen for mutants suppressing the accelerated senescence phenotype of the gain-of-function mutant abs3-1D, AUXIN RESPONSE FACTOR 2 (ARF2) and PHYTOCHROME-INTERACTING FACTOR 5 (PIF5) were identified as key TFs responsible for transcriptional regulation in the ABS3-mediated senescence pathway. ARF2 and PIF5 (as well as PIF4) interact directly and function interdependently to promote senescence, and they share common target genes such as key senescence promoting genes ORESARA 1 (ORE1) and STAY-GREEN 1 (SGR1) in the ABS3-mediated senescence pathway. In addition, we discovered reciprocal regulation between ABS3-subfamily MATEs and the ARF2 and PIF5/4 TFs. Taken together, our findings reveal a regulatory paradigm in which the ARF2-PIF5/4 functional module facilitates the transcriptional reprogramming in the ABS3-mediated senescence pathway.

A novel cuproptosis-related prognostic signature and potential value in HCC immunotherapy

Background: Copper metabolism plays an important role in the tumor microenvironment, and cuproptosis is the last discovered programmed cell death process. However, the potential mechanism of cuproptosis in regulating the immune microenvironment of HCC remains unclear.

Methods: A total of 716 HCC patients with complete mRNA expression and survival information were collected from three public HCC cohorts (TCGA-LIHC cohort, n = 370; GSE76427 cohort, n = 115; ICGC-LIRI cohort, n = 231). The unsupervised clustering analysis (NMF) was performed to identify three different cuproptosis-related subtypes. The univariate-Cox, lasso-Cox and multivariate-Cox regression analyses were performed to screen the cuproptosis related and construct the cuproptosis-related prognosis signature (Cu-PS). The immune cell infiltration was estimated by both CIBERSORT and MCPcounter algorithms.

Results: This study identified three distinct cuproptosis-related metabolic patterns, which presented different pathway enrichment and immune cell infiltration. The Cu-PS, a 5-genes (C7, MAGEA6, HK2, CYP26B1 and EPO) signature, was significantly associated with TNM stage, tumor mutational burden (TMB), drugs sensitivity, and immunotherapies response.

Conclusion: This study performed a multi-genetic analysis of cuproptosis-related genes and further explored the regulatory mechanism of cuproptosis in HCC. The Cu-PS might be a useful biomarker for predicting immunotherapy response and enhancing the diagnosis and treatment of HCC.

Simulation study of inverse diffusion counterbalance method for super-resolution ion mobility spectrometry

Ion mobility spectrometer (IMS) is a powerful chemical composition analysis tool working at atmospheric pressure that can be used to separate complex samples and study molecular structures. Resolution is a key parameter for evaluating the performance of IMS. However, for the pulsed sampling technique used by drift tube IMS, there is an upper limit to the resolution due to the diffusion between ions and the drift gas. In this work, an inverse diffusion counterbalance method is proposed to break the resolution limit. The method is inspired by the stimulated emission depletion (STED). In optical microscopy systems, STED is used to break the optical diffraction limit by a ring of depleted light to counteract diffraction effects of the excited light. We modified this strategy and applied it to an IMS system for counteracting the diffusion effect of the pulsed ion packet. The method can increase the resolution up to 1.55 times through theoretical analysis, and the improvement is verified by simulations. The simulation results find that the initial width of the ion packet has an influence on the effectiveness of the method, and the narrower the initial width, the better the effect. The proposed inverse counterbalance strategy may also be applied to other spectral analysis instruments to break the resolution limit.

TMBcat: A multi-endpoint p-value criterion on different discrepancy metrics for superiorly inferring tumor mutation burden thresholds

Tumor mutation burden (TMB) is a widely recognized stratification biomarker for predicting the efficacy of immunotherapy; however, the number and universal definition of the categorizing thresholds remain debatable due to the multifaceted nature of efficacy and the imprecision of TMB measurements. We proposed a minimal joint p-value criterion from the perspective of differentiating the comprehensive therapeutic advantages, termed TMBcat, optimized TMB categorization across distinct cancer cohorts and surpassed known benchmarks. The statistical framework applies to multidimensional endpoints and is fault-tolerant to TMB measurement errors. To explore the association between TMB and various immunotherapy outcomes, we performed a retrospective analysis on 78 patients with non-small cell lung cancer and 64 patients with nasopharyngeal carcinomas who underwent anti-PD-(L)1 therapy. The stratification results of TMBcat confirmed that the relationship between TMB and immunotherapy is non-linear, i.e., treatment gains do not inherently increase with higher TMB, and the pattern varies across carcinomas. Thus, multiple TMB classification thresholds could distinguish patient prognosis flexibly. These findings were further validated in an assembled cohort of 943 patients obtained from 11 published studies. In conclusion, our work presents a general criterion and an accessible software package; together, they enable optimal TMB subgrouping. Our study has the potential to yield innovative insights into therapeutic selection and treatment strategies for patients.

Preparation and characterization of polyethylene glycol/chitosan composite water-based wound healing lubricant

The proportion of pregnant women giving birth through cesarean section is increasing annually worldwide. However, post-cesarean section scar diverticulum is a common condition that occurs and requires better surgical strategies than the methods currently used. We hypothesized that using biological lubricant topically on the incision area during C-section could be an option to minimize the scar. This water-based polyethylene glycol (PEG)/chitosan (CS) composite lubricant was prepared via ultrasonic blending. The product was characterized using scanning electron microscopy, X-ray photoelectron spectroscopy, X-ray diffraction, Fourier-transform infrared spectroscopy, and Raman spectroscopy. The thermal stability of the materials and their heat absorption and release during heating were analyzed using thermogravimetric analysis and differential scanning calorimetry. Tribological tests proved that the PEG/CS composite had a better lubrication effect than either the PEG or CS lubricant alone, and the cell viability experiments verified that it had good biocompatibility. Finally, application of the composite lubricant onto the backs of mice modeling full-thickness skin incisions further confirmed that the product improved both the re-epithelialization and the collagen levels of the wounded skin. In conclusion, we expect our newly formulated PEG/CS composite lubricant to be useful not only for managing post-cesarean section scar diverticulum but also for healing skin wounds in general.

Comprehensive analysis of the prognostic value and immune infiltration of FGFR family members in gastric cancer

Background

Fibroblast growth factor receptors (FGFRs) modulate numerous cellular processes in tumor cells and tumor microenvironment. However, the effect of FGFRs on tumor prognosis and tumor-infiltrating lymphocytes in gastric cancer (GC) remains controversial.

Methods

The expression of four different types of FGFRs was analyzed via GEPIA, TCGA-STAD, and GTEX databases and our 27 pairs of GC tumor samples and the adjacent normal tissue. Furthermore, the Kaplan–Meier plot and the TCGA database were utilized to assess the association of FGFRs with clinical prognosis. The R software was used to evaluate FGFRs co-expression genes with GO/KEGG Pathway Enrichment Analysis. In vitro and in vivo functional analyses and immunoblotting were performed to verify FGFR4 overexpression consequence. Moreover, the correlation between FGFRs and cancer immune infiltrates was analyzed by TIMER and TCGA databases. And the efficacy of anti-PD-1 mAb treatment was examined in NOG mouse models with overexpressed FGFR1 or FGFR4.

Results

The expression of FGFRs was considerably elevated in STAD than in the normal gastric tissues and was significantly correlated with poor OS and PFS. ROC curve showed the accuracy of the FGFRs in tumor diagnosis, among which FGFR4 had the highest ROC value. Besides, univariate and multivariate analysis revealed that FGFR4 was an independent prognostic factor for GC patients. According to a GO/KEGG analysis, the FGFRs were implicated in the ERK/MAPK, PI3K-AKT and extracellular matrix (ECM) receptor signaling pathways. In vivo and in vitro studies revealed that overexpression of FGFR4 stimulated GC cell proliferation, invasion, and migration. In addition, FGFR1 expression was positively correlated with infiltrating levels of CD8+ T-cells, CD4+ T-cells, macrophages, and dendritic cells in STAD. In contrast, FGFR4 expression was negatively correlated with tumor-infiltrating lymphocytes. Interestingly, overexpression of FGFR1 in the NOG mouse model improved the immunotherapeutic impact of GC, while overexpression of FGFR4 impaired the effect. When combined with an FGFR4 inhibitor, the anti-tumor effect of anti-PD-1 treatment increased significantly in a GC xenograft mouse model with overexpressed FGFR4.

Conclusions

FGFRs has critical function in GC and associated with immune cell infiltration, which might be a potential prognosis biomarker and predictor of response to immunotherapy in GC.

Physical exercise improved muscle strength and pain on neck and shoulder in military pilots

Purpose: To evaluate the effects of physical exercise on neck and shoulder muscle strength and pain in military pilots.

Method: Embase, PubMed, and Cochrane Library databases were searched studies published up to April 1, 2022. Studies that met the screening criteria were included in the final meta-analysis. We calculated neck and shoulder maximal voluntary isometric contractions (MVICs), prevalence of pain, and pain intensity. Heterogeneity was explored by subgroup and sensitivity analyses.

Result: A total of 15 studies with 907 participants were included. In the exercise group, muscle strength was significantly increased in four directions of neck motion: flexion (standardized mean difference (SMD) = 0.45; 95% CI, 0.08–0.82), extension (SMD = 0.63; 95% CI, 0.27–1.00), right lateral flexion (Rtflx) (SMD = 0.53; 95% CI, 0.12–0.94), and left lateral flexion (Ltflx) (SMD = 0.50; 95% CI, 0.09–0.91). Subgroup analysis showed that fighter pilots, strength plus endurance training, and a follow-up period <20 weeks exhibited more significant muscle strength improvements than helicopter pilots, simple strength training, and a follow-up period ≥20 weeks. Overall, the pooled odds ratio (OR) for the effect of physical exercise on the prevalence of neck pain was not statistically significant (I² = 60%). Sensitivity analysis revealed that the heterogeneity was restored after removing each of two studies (I² = 47%), and the pooled OR was statistically significant (OR = 0.46; 95% CI, 0.23 to 0.94, or OR = 0.47; 95% CI, 0.24–0.91). Furthermore, compared with observational studies (OS), the reduction in the prevalence of neck pain was more significant in randomized controlled trials (RCTs) (OR = 0.37; 95% CI, 0.18–0.78). No significant differences in the effects of exercise on shoulder muscle strength and neck and shoulder pain intensity were observed.

Conclusion: Physical exercise can improve neck muscle strength in military pilots. After removing studies that may be the source of heterogeneity, exercise showed a protective effect on neck pain, especially in RCTs. The conclusion that exercise had no effects on shoulder muscle strength and pain intensity should be taken with caution.

Effect of corticosteroids combined with cyclophosphamide or mycophenolate mofetil therapy for IgA nephropathy with stage 3 or 4 chronic kidney disease: A retrospective cohort study

Background: To determine the safety and efficacy of corticosteroids (CS) combined with cyclophosphamide (CTX), compared with CS combined with mycophenolate mofetil (MMF) for IgA nephropathy (IgAN) patients with stage 3 and 4 CKD and proteinuria ≥1.0 g/24 h in a 10-year real-world study.

Methods: We recruited 296 IgAN patients with renal insufficiency and proteinuria ≥1.0 g/24 h who received uncontrolled supportive care (USC) (n = 44), CS + CTX therapy (n = 164) and CS + MMF therapy (n = 88) in Xijing Hospital from July 2008 to December 2019. The combined event was defined as a ≥50% decrease in eGFR, ESRD, or death.

Results: The median of the follow-up period was 39.3 months. One hundred and twenty-five patients experienced the combined event, 65.9, 37.8, and 38.6% in the USC, CS + CTX, and CS + MMF group, respectively. In multivariate Cox regression analyses, CS combined with CTX (HR = 0.457, 95% CI 0.238-0.878, p = 0.019) significantly reduced the incidence of the combined event, whereas CS + MMF (HR = 0.523, 95% CI 0.246-1.109, p = 0.091) did not reduce the risk of the combined event, compared with USC. The incidence of pneumonia and death due to infection in the CS + MMF group was higher than other two groups.

Conclusion: Compared with USC and CS + MMF therapy, CS + CTX therapy was more safety and possibly more effective. The results need to be further confirmed by large randomized controlled studies.

FOXM1 is regulated by DEPDC1 to facilitate development and metastasis of oral squamous cell carcinoma

The Disheveled, EGL-10, Pleckstrin domain containing 1 (DEPDC1) is a new oncogene that has recently been described. The mechanisms and functions of its expression are yet to be determined in oral squamous cell carcinoma (OSCC). In the present study, the impact of DEPDC1 on the growth and development of OSCC was investigated using animal models, cell lines and human tissue samples. Elevated DEPDC1 expression within cancer cell lines and human OSCC has been identified. Mechanistic examination showed that restored DEPDC1 expression in vivo and in vitro stimulated OSCC tumour development. In addition, FOXM1 interacts with DEPDC1 as indicated by co-immunoprecipitation and immunofluorescence testing. Functionally, DEPDC1 facilitated Wnt/β-catenin signal transduction and β-catenin protein nuclear expression. In summary, the DEPDC1, interacting with FOXM1 via Wnt/β-catenin signaling, the closely regulated OSCC pathogenesis, suggesting that targeting the novel DEPDC1/FOXM1/β-catenin complex is an essential OSCC therapeutic approach.

Transfer RNAs-derived small RNAs and their application potential in multiple diseases

The role of tRNAs is best known as adapter components of translational machinery. According to the central dogma of molecular biology, DNA is transcribed to RNA and in turn is translated into proteins, in which tRNA outstands by its role of the cellular courier. Recent studies have led to the revision of the canonical function of transfer RNAs (tRNAs), which indicates that tRNAs also serve as a source for short non-coding RNAs called tRNA-derived small RNAs (tsRNAs). tsRNAs play key roles in cellular processes by modulating complicated regulatory networks beyond translation and are widely involved in multiple diseases. Herein, the biogenesis and classification of tsRNAs were firstly clarified. tsRNAs are generated from pre-tRNAs or mature tRNAs and are classified into tRNA-derived fragments (tRFs) and tRNA halves (tiRNA). The tRFs include five types according to the incision loci: tRF-1, tRF-2, tRF-3, tRF-5 and i-tRF which contain 3′ tiRNA and 5′ tiRNA. The functions of tsRNAs and their regulation mechanisms involved in disease processes are systematically summarized as well. The mechanisms can elaborate on the specific regulation of tsRNAs. In conclusion, the current research suggests that tsRNAs are promising targets for modulating pathological processes, such as breast cancer, ischemic stroke, respiratory syncytial virus, osteoporosis and so on, and maintain vital clinical implications in diagnosis and therapeutics of various diseases.

AttnTAP: A Dual-input Framework Incorporating the Attention Mechanism for Accurately Predicting TCR-peptide Binding

T-cell receptors (TCRs) are formed by random recombination of genomic precursor elements, some of which mediate the recognition of cancer-associated antigens. Due to the complicated process of T-cell immune response and limited biological empirical evidence, the practical strategy for identifying TCRs and their recognized peptides is the computational prediction from population and/or individual TCR repertoires. In recent years, several machine/deep learning-based approaches have been proposed for TCR-peptide binding prediction. However, the predictive performances of these methods can be further improved by overcoming several significant flaws in neural network design. The interrelationship between amino acids in TCRs is critical for TCR antigen recognition, which was not properly considered by the existing methods. They also did not pay more attention to the amino acids that play a significant role in antigen-binding specificity. Moreover, complex networks tended to increase the risk of overfitting and computational costs. In this study, we developed a dual-input deep learning framework, named AttnTAP, to improve the TCR-peptide binding prediction. It used the bi-directional long short-term memory model for robust feature extraction of TCR sequences, which considered the interrelationships between amino acids and their precursors and postcursors. We also introduced the attention mechanism to give amino acids different weights and pay more attention to the contributing ones. In addition, we used the multilayer perceptron model instead of complex networks to extract peptide features to reduce overfitting and computational costs. AttnTAP achieved high areas under the curves (AUCs) in TCR-peptide binding prediction on both balanced and unbalanced datasets (higher than 0.838 on McPAS-TCR and 0.908 on VDJdb). Furthermore, it had the highest average AUCs in TPP-I and TPP-II tasks compared with the other five popular models (TPP-I: 0.84 on McPAS-TCR and 0.894 on VDJdb; TPP-II: 0.837 on McPAS-TCR and 0.893 on VDJdb). In conclusion, AttnTAP is a reasonable and practical framework for predicting TCR-peptide binding, which can accelerate identifying neoantigens and activated T cells for immunotherapy to meet urgent clinical needs.

A Joint Model Considering Measurement Errors for Optimally Identifying Tumor Mutation Burden Threshold

Tumor mutation burden (TMB) is a recognized stratification biomarker for immunotherapy. Nevertheless, the general TMB-high threshold is unstandardized due to severe clinical controversies, with the underlying cause being inconsistency between multiple assessment criteria and imprecision of the TMB value. The existing methods for determining TMB thresholds all consider only a single dimension of clinical benefit and ignore the interference of the TMB error. Our research aims to determine the TMB threshold optimally based on multifaceted clinical efficacies accounting for measurement errors. We report a multi-endpoint joint model as a generalized method for inferring the TMB thresholds, facilitating consistent statistical inference using an iterative numerical estimation procedure considering mis-specified covariates. The model optimizes the division by combining objective response rate and time-to-event outcomes, which may be interrelated due to some shared traits. We augment previous works by enabling subject-specific random effects to govern the communication among distinct endpoints. Our simulations show that the proposed model has advantages over the standard model in terms of precision and stability in parameter estimation and threshold determination. To validate the feasibility of the proposed thresholds, we pool a cohort of 73 patients with non-small-cell lung cancer and 64 patients with nasopharyngeal carcinoma who underwent anti-PD-(L)1 treatment, as well as validation cohorts of 943 patients. Analyses revealed that our approach could grant clinicians a holistic efficacy assessment, culminating in a robust determination of the TMB screening threshold for superior patients. Our methodology has the potential to yield innovative insights into therapeutic selection and support precision immuno-oncology.

Atomically Dispersed Janus Nickel Sites on Red Phosphorus for Photocatalytic Overall Water Splitting

Single‐atom nickel catalysts hold great promise for photocatalytic water splitting due to their plentiful active sites and cost‐effectiveness. Herein, we adopt a reactive‐group guided strategy to prepare atomically dispersed nickel catalysts on red phosphorus. The hydrothermal treatment of red phosphorus leads to the formation of P−H and P−OH groups, which behave as the reactive functionalities to generate the dual structure of single‐atom P−Ni and P−O−Ni catalytic sites. The produced single‐atom sites provide two different functions: P−Ni for water reduction and P−O−Ni for water oxidation. Benefitting from this specific Janus structure, Ni‐red phosphorus shows an elevated hydrogen evolution rate compared to Ni nanoparticle‐modified red phosphorus under visible‐light irradiation. The hydrogen evolution rate was additionally enhanced with increased reaction temperature, reaching 91.51 μmol h⁻¹ at 70 °C, corresponding to an apparent quantum efficiency of 8.9 % at 420 nm excitation wavelength.

The Osteoinductivity of Calcium Phosphate-Based Biomaterials: A Tight Interaction With Bone Healing

Calcium phosphate (CaP)-based bioceramics are the most widely used synthetic biomaterials for reconstructing damaged bone. Accompanied by bone healing process, implanted materials are gradually degraded while bone ultimately returns to its original geometry and function. In this progress report, we reviewed the complex and tight relationship between the bone healing response and CaP-based biomaterials, with the emphasis on the in vivo degradation mechanisms of such material and their osteoinductive properties mediated by immune responses, osteoclastogenesis and osteoblasts. A deep understanding of the interaction between biological healing process and biomaterials will optimize the design of CaP-based biomaterials, and further translate into effective strategies for biomaterials customization.

DeepLION: Deep Multi-Instance Learning Improves the Prediction of Cancer-Associated T Cell Receptors for Accurate Cancer Detection

Recent studies highlight the potential of T cell receptor (TCR) repertoires in accurately detecting cancers via noninvasive sampling. Unfortunately, due to the complicated associations among cancer antigens and the possible induced T cell responses, currently, the practical strategy for identifying cancer-associated TCRs is the computational prediction based on TCR repertoire data. Several state-of-the-art methods were proposed in recent year or two; however, the prediction algorithms were still weakened by two major issues. To facilitate the computational processes, the algorithms prefer to decompose the original TCR sequences into length-fixed amino acid fragments, while the first dilemma comes as the lengths of cancer-associated motifs are suggested to be various. Moreover, the correlations among TCRs in the same repertoire should be further considered, which are often ignored by the existing methods. We here developed a deep multi-instance learning method, named DeepLION, to improve the prediction of cancer-associated TCRs by considering these issues. First, DeepLION introduced a deep learning framework with alternative convolution filters and 1-max pooling operations to handle the amino acid fragments with different lengths. Then, the multi-instance learning framework modeled the TCR correlations and assigned adjusted weights for each TCR sequence during the predicting process. To validate the performance of DeepLION, we conducted a series of experiments on several cohorts of patients from nine cancer types. Compared to the existing methods, DeepLION achieved, on most of the cohorts, higher prediction accuracies, sensitivities, specificities, and areas under the curve (AUCs), where the AUC reached notably 0.97 and 0.90 for thyroid and lung cancer cohorts, respectively. Thus, DeepLION may further support the detection of cancers from TCR repertoire data. DeepLION is publicly available on GitHub, at https://github.com/Bioinformatics7181/DeepLION, for academic usage only.

Establishment and Optimization of Radiomics Algorithms for Prediction of KRAS Gene Mutation by Integration of NSCLC Gene Mutation Mutual Exclusion Information

Purpose: To assess the significance of mutation mutual exclusion information in the optimization of radiomics algorithms for predicting gene mutation.

Methods: We retrospectively analyzed 258 non-small cell lung cancer (NSCLC) patients. Patients were randomly divided into training (n = 180) and validation (n = 78) cohorts. Based on radiomics features, radiomics score (RS) models were developed for predicting KRAS proto-oncogene mutations. Furthermore, a composite model combining mixedRS and epidermal growth factor receptor (EGFR) mutation status was developed.

Results: Compared with CT model, the PET/CT radiomics score model exhibited higher AUC for predicting KRAS mutations (0.834 vs. 0.770). By integrating EGFR mutation information into the PET/CT RS model, the AUC, sensitivity, specificity, and accuracy for predicting KRAS mutations were all elevated in the validation cohort (0.921, 0.949, 0.872, 0.910 vs. 0.834, 0.923, 0.641, 0.782). By adding EGFR exclusive mutation information, the composite model corrected 64.3% false positive cases produced by the PET/CT RS model in the validation cohort.

Conclusion: Integrating EGFR mutation status has potential utility for the optimization of radiomics models for prediction of KRAS gene mutations. This method may be used when repeated biopsies would carry unacceptable risks for the patient.

Frontiers and Structural Engineering for Building Flexible Zinc-Air Batteries

With the development of flexible devices, the demand for wearable power sources has increased and gradually become imperative. Zinc-air batteries (ZABs) have attracted lots of research interest due to their high theoretical energy density and excellent safety properties, which can meet the wearable energy supply requirements. Here, the flexibility of energy storage devices is discussed first, followed by the chemistries and development of flexible ZABs. The design of flexible electrodes, the properties of solid-state electrolytes (SSEs), and the construction of deformable structures are discussed in depth. The researchers working on flexible energy storage devices will benefit from the work.

Anti-Tumor Role of CAMK2B in Remodeling the Stromal Microenvironment and Inhibiting Proliferation in Papillary Renal Cell Carcinoma

The tumor microenvironment (TME) is variable across tumor types and has diverse effects on malignant progression, based on the type and number of infiltrating stromal cells. In particular, TME effector genes and their competitive endogenous RNA (ceRNA) networks play a critical role in regulating malignant tumor progression. However, the core effector molecules involved in TME modulation of kidney renal papillary cell carcinoma (KIRP) are poorly understood. To address this question, a cohort containing 233 KIRP patients was derived from The Cancer Genome Atlas (TCGA) database, and the data were processed using the ESTIMATE algorithm. We further evaluated the relationship between immune scores (ISs) and stromal scores (SSs) and disease progression and found that high SSs were associated with a poor prognosis in KIRP. Differentially expressed genes (DEGs) were therefore screened based on SS scores, resulting in 2509 DEGs, including 1668 mRNAs, 783 long noncoding (lnc)RNAs, and 58 micro (mi)RNAs. DEGs were then filtered using the random variance and subjected to hierarchical clustering using EPCLUST. Weighted gene co-expression network analysis (WGCNA) was used to assess the prognostic capacity of these DEGs and identify target ceRNA networks, and lncRNA GUSBP11/miR-432-5p/CAMK2B in the turquoise module was selected as a promising ceRNA network. From this analysis CAMK2B was selected as the core gene predicted to be involved in stromal TMA regulation. We therefore explored the expression and function of CAMK2B in vitro and in vivo and provide evidence that this protein promotes stromal TME remodulation and inhibits proliferation in KIRP. Lastly, we show that vascular endothelial growth factor (VEGF), transforming growth factor (TGF)β, and close homolog of L1 (CHL1) act as downstream effectors of CAMK2B in KIRP. Thus, in this study, we show that the TME determines prognosis of KIRP patients via the core effector molecule CAMK2B, which mediates both microenvironmental remodeling and tumor progression. Based on these findings, we propose that remodeling of the stromal microenvironment could represent an improved therapeutic approach relative to immunotherapy for KIRP.

Necroptosis of nucleus pulposus cells involved in intervertebral disc degeneration through MyD88 signaling

BACKGROUND CONTEXT

Low back pain, affecting nearly 40% of adults, mainly results from intervertebral disc degeneration (IVDD), while the pathogenesis of IVDD is still not fully elucidated. Recently, some researches have revealed that necroptosis, a programmed necrosis, participated in the progression of IVDD, nevertheless, the underlying mechanism remains unclear.

PURPOSE

To study the mechanism of necroptosis of Nucleus Pulposus (NP) cells in IVDD, focusing on the role of MyD88 signaling.

STUDY DESIGN

The expression and co-localization of necroptotic indicators and MyD88 were examined in vivo, and MyD88 inhibitor was applied to determine the role of MyD88 signaling in necroptosis of NP cells in vitro.

METHODS

Human disc specimens were collected from patients receiving diskectomy for lumbar disc herniation (LDH) or traumatic lumbar fractures after MRI scanning. According to the Pfirrmann grades, they were divided into normal (Grades 1, 2) and degenerated groups (4, 5). Tissue slides were prepared for immunofluorescence to assess the co-localization of necroptotic indicators (RIP3, MLKL, p-MLKL) and MyD88 histologically. The combination of TNFα, LPS and Z-VAD-FMK was applied to induce necroptosis of NP cells. Level of ATP, reactive oxygen species (ROS), live-cell staining and electron microscope study were employed to study the role of MyD88 signaling in necroptosis of NP cells.

RESULTS

In vivo, the increased expression and co-localization of necroptotic indicators (RIP3, MLKL, p-MLKL) and MyD88 were found in NP cells of degenerated disc, while very l low fluorescence intensity in tissue of traumatic lumbar fractures. In vitro, the MyD88 inhibitor effectively rescued the necroptosis of NP cells, accompanied by increased viability, ATP level, and decreased ROS level. The effect of MyD88 inhibition on necroptosis of NP cells was further confirmed by ultrastructure of mitochondria shown by Transmission Electron Microscope (TEM).

CONCLUSION

Our results indicated that the involvement of MyD88 signaling in the necroptosis of NP cells in IVDD, which will replenish the pathogenesis of IVDD and provide a novel potential therapeutic target for IVDD.