Application of predictive model based on CT radiomics and machine learning in diagnosis for occult locally advanced esophageal squamous cell carcinoma before treatment: A two-center study.

PURPOSE: Development and validation of a radiomics model for predicting occult locally advanced esophageal squamous cell carcinoma (LA-ESCC) on computed tomography (CT) radiomic features before implementation of treatment. METHODS: The study retrospectively collected 574 patients with esophageal squamous cell carcinoma (ESCC) from two medical centers, which were divided into three cohorts for training, internal and external validation. After delineating volume of interest (VOI), radiomics features were extracted and subjected to feature selection using three robust methods. Subsequently, 10 machine learning models were constructed, among which the optimal model was utilized to establish a radiomics signature. Furthermore, a predictive nomogram incorporating both clinical and radiomics signatures was developed. The performance of these models was evaluated through receiver operating characteristic curves, calibration curves, decision curve analysis as well as measures including accuracy, sensitivity, and specificity. RESULTS: A total of 19 radiomics features were selected. The multilayer perceptron (MLP), which was found to be optimal, achieved an AUC of 0.919, 0.864 and 0.882 in the training, internal and external validation cohorts, respectively. Similarly, MLP showed good accuracy in distinguish occult LA-ESCC in subgroup of cT1-2N0M0 diagnosed by clinicians with 0.803 and 0.789 in two validation cohorts respectively. By incorporating the radiomics signature with clinical signature, a predictive nomogram demonstrated superior prediction performance with an AUC of 0.877 and accuracy of 0.85 in external validation cohort. CONCLUSION: The radiomics and machine learning model can offers improved accuracy in prediction of occult LA-ESCC, providing valuable assistance to clinicians when choosing treatment plans.

Multi-dimensional cell-free DNA-based liquid biopsy for sensitive early detection of gastric cancer.

BACKGROUND: Gastric cancer is the fifth most common cancer type. Most patients are diagnosed at advanced stages with poor prognosis. A non-invasive assay for the detection of early-stage gastric cancer is highly desirable for reducing associated mortality. METHODS: We collected a prospective study cohort of 110 stage I-II gastric cancer patients and 139 non-cancer individuals. We performed whole-genome sequencing with plasma samples and profiled four types of cell-free DNA (cfDNA) characteristics, fragment size pattern, copy number variation, nucleosome coverage pattern, and single nucleotide substitution. With these differential profiles, we developed an ensemble model to detect gastric cancer signals. Further, we validated the assay in an in-house first validation cohort of 73 gastric cancer patients and 94 non-cancer individuals and an independent second validation cohort of 47 gastric cancer patients and 49 non-cancer individuals. Additionally, we evaluated the assay in a hypothetical 100,000 screening population by Monte Carlo simulation. RESULTS: Our cfDNA-based assay could distinguish early-stage gastric cancer from non-cancer at an AUROC of 0.962 (95% CI: 0.942-0.982) in the study cohort, 0.972 (95% CI: 0.953-0.992) in the first validation cohort and 0.937 (95% CI: 0.890-0.983) in the second validation cohort. The model reached a specificity of 92.1% (128/139) and a sensitivity of 88.2% (97/110) in the study cohort. In the first validation cohort, 91.5% (86/94) of non-cancer individuals and 91.8% (67/73) of gastric cancer patients were correctly identified. In the second validation cohort, 89.8% (44/49) of non-cancer individuals and 87.2% (41/47) of gastric cancer patients were accurately classified. CONCLUSIONS: We introduced a liquid biopsy assay using multiple dimensions of cfDNA characteristics that could accurately identify early-stage gastric cancer from non-cancerous conditions. As a cost-effective non-invasive approach, it may provide population-wide benefits for the early detection of gastric cancer. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov under the identifier NCT05269056 on March 7, 2022.

Identification of a novel prognostic cuproptosis-associated LncRNA signature for predicting prognosis and immunotherapy response in patients with esophageal cancer.

Nowadays, effective prognostic models for esophageal cancer (ESCA) are still lacking. Long noncoding RNAs (lncRNAs) are commonly utilized as indicators for diagnosing cancer and forecasting patient outcomes. Cuproptosis is regulated by multiple genes and is crucial to the progression of ESCA. However, it is not yet clear what role the cuproptosis-associated lncRNAs (CuALs) play in ESCA. To tackle this problem, a prognostic signature incorporating three CuALs was created. This signature was constructed by the use of the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. Subsequently, the signature effectively stratified ESCA samples into a high-risk group and a low-risk group. Those in the low-risk group demonstrated extended overall survival (OS), as well as increased infiltration of T cells, macrophages, and NK cells, suggesting a potentially enhanced response to immunotherapy. The ROC curve analysis demonstrated that this prognostic signature outperformed conventional clinical factors in predicting patient prognosis (AUC = 0.708). K-M survival analysis and correlation analysis identified UGDH-AS1 (a CuAL) as a protective factor positively associated with patient prognosis. The results of RT-qPCR and wound healing assays indicated that UGDH-AS1 is overexpressed in ESCA and could inhibit cancer cell migration. In general, the prognostic signature of CuALs demonstrated a robust capability in forecasting the immune environment and patient prognosis, highlighting its potential as a tool for enhancing personalized treatment strategies in ESCA.

Oligodeoxynucleotides containing CpG motifs (CpG-ODN) restores immune regulatory functions of airway macrophages of patients with asthma.

Allergic asthma is characterized by the polarization of Th2 cells and impaired immune regulation. Macrophages occupy the largest proportion of airway immune cells. This study aims to discover the mechanism that hinders the immune regulatory functions of airway macrophages. In this study, macrophages were isolated from cells in bronchoalveolar lavage fluids (BALF) collected from asthma patients and normal control (NC) subjects. The results indicated that macrophages occupied the largest portion of the cellular components in BALF. The frequency of IL-10+ macrophage was significantly lower in asthma patients than in NC subjects. The expression of IL-10 in macrophages of BALF was associated with the levels of asthma-related parameters. The immune-suppressive functions of BALF M0 cells were defective in asthma patients. The inducibility of IL-10 expression was impaired in BALF macrophages of asthma patients, which could be restored by exposing to CpG. In conclusion, the induction of IL-10 in macrophages of BALF in asthma patients was impaired, and it could be restored by exposure to CpG.

Comparative Analysis of Sucrose-Regulatory Genes in High- and Low-Sucrose Sister Clones of Sugarcane.

Sugarcane is a significant primitive source of sugar and energy worldwide. The progress in enhancing the sugar content in sugarcane cultivars remains limited due to an insufficient understanding of specific genes related to sucrose production. The present investigation examined the enzyme activities, levels of reducing and non-reducing sugars, and transcript expression using RT-qPCR to assess the gene expression associated with sucrose metabolism in a high-sucrose sugarcane clone (GXB9) in comparison to a low-sucrose sister clone (B9). Sucrose phosphate synthase (SPS), sucrose phosphate phosphatase (SPP), sucrose synthase (SuSy), cell wall invertase (CWI), soluble acid invertase (SAI), and neutral invertase (NI) are essential enzymes involved in sucrose metabolism in sugarcane. The activities of these enzymes were comparatively quantified and analyzed in immature and maturing internodes of the high- and low-sucrose clones. The results showed that the higher-sucrose-accumulating clone had greater sucrose concentrations than the low-sucrose-accumulating clone; however, maturing internodes had higher sucrose levels than immature internodes in both clones. Hexose concentrations were higher in immature internodes than in maturing internodes for both clones. The SPS and SPP enzymes activities were higher in the high-sucrose-storing clone than in the low-sucrose clone. SuSy activity was higher in the low-sucrose clone than in the high-sucrose clone; further, the degree of SuSy activity was higher in immature internodes than in maturing internodes for both clones. The SPS gene expression was considerably higher in mature internodes of the high-sucrose clones than the low-sucrose clone. Conversely, the SuSy gene exhibited up-regulated expression in the low-sucrose clone. The enhanced expression of SPS in the high-sucrose clone compared to the low-sucrose clone suggests that SPS plays a major role in the increased accumulation of sucrose. These findings provide the opportunity to improve sugarcane cultivars by regulating the activity of genes related to sucrose metabolism using transgenic techniques.

Adjuvant therapy provides no additional recurrence-free benefit for esophageal squamous cell carcinoma patients after neoadjuvant chemoimmunotherapy and surgery: a multi-center propensity score match study.

Purpose: The need for adjuvant therapy (AT) following neoadjuvant chemoimmunotherapy (nICT) and surgery in esophageal squamous cell cancer (ESCC) remains uncertain. This study aims to investigate whether AT offers additional benefits in terms of recurrence-free survival (RFS) for ESCC patients after nICT and surgery. Methods: Retrospective analysis was conducted between January 2019 and December 2022 from three centers. Eligible patients were divided into two groups: the AT group and the non-AT group. Survival analyses comparing different modalities of AT (including adjuvant chemotherapy and adjuvant chemoimmunotherapy) with non-AT were performed. The primary endpoint was RFS. Propensity score matching(PSM) was used to mitigate inter-group patient heterogeneity. Kaplan-Meier survival curves and Cox regression analysis were employed for recurrence-free survival analysis. Results: A total of 155 nICT patients were included, with 26 patients experiencing recurrence. According to Cox analysis, receipt of adjuvant therapy emerged as an independent risk factor(HR:2.621, 95%CI:[1.089,6.310], P=0.032), and there was statistically significant difference in the Kaplan-Meier survival curves between non-AT and receipt of AT in matched pairs (p=0.026). Stratified analysis revealed AT bring no survival benefit to patients with pathological complete response(p= 0.149) and residual tumor cell(p=0.062). Subgroup analysis showed no significant difference in recurrence-free survival between non-AT and adjuvant chemoimmunotherapy patients(P=0.108). However, patients receiving adjuvant chemotherapy exhibited poorer recurrence survival compared to non-AT patients (p= 0.016). Conclusion: In terms of recurrence-free survival for ESCC patients after nICT and surgery, the necessity of adjuvant therapy especially the adjuvant chemotherapy, can be mitigated.

Involvement and repair of epithelial barrier dysfunction in allergic diseases.

The epithelial barrier serves as a critical defense mechanism separating the human body from the external environment, fulfilling both physical and immune functions. This barrier plays a pivotal role in shielding the body from environmental risk factors such as allergens, pathogens, and pollutants. However, since the 19th century, the escalating threats posed by environmental pollution, global warming, heightened usage of industrial chemical products, and alterations in biodiversity have contributed to a noteworthy surge in allergic disease incidences. Notably, allergic diseases frequently exhibit dysfunction in the epithelial barrier. The proposed epithelial barrier hypothesis introduces a novel avenue for the prevention and treatment of allergic diseases. Despite increased attention to the role of barrier dysfunction in allergic disease development, numerous questions persist regarding the mechanisms underlying the disruption of normal barrier function. Consequently, this review aims to provide a comprehensive overview of the epithelial barrier's role in allergic diseases, encompassing influencing factors, assessment techniques, and repair methodologies. By doing so, it seeks to present innovative strategies for the prevention and treatment of allergic diseases.

Integrated transcriptomic and proteomic analyses of two sugarcane (Saccharum officinarum Linn.) varieties differing in their lodging tolerance.

BACKGROUND: Lodging seriously affects sugarcane stem growth and sugar accumulation, reduces sugarcane yield and sucrose content, and impedes mechanization. However, the molecular mechanisms underlying sugarcane lodging tolerance remain unclear. In this study, comprehensive transcriptomic and proteomic analyses were performed to explore the differential genetic regulatory mechanisms between upright (GT42) and lodged (GF98-296) sugarcane varieties. RESULTS: The stain test showed that GT42 had more lignin and vascular bundles in the stem than GF98-296. The gene expression analysis revealed that the genes that were differentially expressed between the two varieties were mainly involved in the phenylpropanoid pathway at the growth stage. The protein expression analysis indicated that the proteins that were differentially expressed between the two varieties were related to the synthesis of secondary metabolites, the process of endocytosis, and the formation of aminoacyl-tRNA. Time-series analysis revealed variations in differential gene expression patterns between the two varieties, whereas significant protein expression trends in the two varieties were largely consistent, except for one profile. The expression of CYP84A, 4CL, and CAD from the key phenylpropanoid biosynthetic pathway was enhanced in GT42 at stage 2 but suppressed in GF98-296 at the growth stage. Furthermore, the expression of SDT1 in the nicotinate and nicotinamide metabolism was enhanced in GT42 cells but suppressed in GF98-296 cells at the growth stage. CONCLUSION: Our findings provide reference data for mining lodging tolerance-related genes that are expected to facilitate the selective breeding of sugarcane varieties with excellent lodging tolerance.

Probing the communication patterns of different chondrocyte subtypes in osteoarthritis at the single cell level using pattern recognition and manifold learning.

The patterns of communication among different chondrocyte subtypes in human cartilage degeneration and regeneration help us understand the microenvironment of osteoarthritis and optimize cell-targeted therapies. Here, a single-cell transcriptome dataset of chondrocytes is used to explore the synergistic and communicative patterns of different chondrocyte subtypes. We collected 1600 chondrocytes from 10 patients with osteoarthritis and analyzed the active communication patterns for the first time based on network analysis and pattern recognition at the single-cell level. Manifold learning and quantitative contrasts were performed to analyze conserved and specific communication pathways. We found that ProCs (Proliferative chondrocytes), ECs (Effector chondrocytes), preHTCs (Prehypertrophic chondrocytes), HTCs (Hypertrophic chondrocytes), and FCs (Fibrocartilage chondrocytes) are more active in incoming and outgoing signaling patterns, which is consistent with studies on their close functional cooperation. Among them, preHTCs play multiple roles in chondrocyte communication, and ProCs and preHTCs have many overlapping pathways. These two subtypes are the most active among all chondrocyte subtypes. Interestingly, ECs and FCs are a pair of "mutually exclusive" subtypes, of which ECs are predominant in incoming patterns and FCs in outgoing patterns. The active signaling pathways of ECs and FCs largely do not overlap. COLLAGEN and LAMININ are the main pivotal pathways, which means they are very important in the repair and expansion of joint homeostasis. Notably, only preHTCs assume multiple roles (including sender, receiver, mediator, and influencer) and are involved in multiple communication pathways. We have examined their communication patterns from the perspective of cellular interactions, revealed the relationships among different chondrocyte subtypes, and, in particular, identified a number of active subtypes and pathways that are important for targeted therapy in the osteoarthritic microenvironment. Our findings provide a new research paradigm and new insights into understanding chondrocyte activity patterns in the osteoarthritic microenvironment.

Theoretical and Three-Dimensional Molecular Dynamics Study of Droplet Wettability and Mobility on Lubricant-Infused Porous Surfaces.

Profiting from their slippery nature, lubricant-infused porous surfaces endow with droplets excellent mobility and consequently promise remarkable heat transfer improvement for dropwise condensation. To be a four-phase wetting system, the droplet wettability configurations and the corresponding dynamic characteristics on lubricant-infused porous surfaces are closely related to many factors, such as multiple interfacial interactions, surface features, and lubricant thickness, which keeps a long-standing challenge to promulgate the underlying physics. In this work, thermodynamically theoretical analysis and three-dimensional molecular dynamics simulations with the coarse-grained water and hexane models are carried out to explore droplet wettability and mobility on lubricant-infused porous surfaces. Combined with accessible theoretical criteria, phase diagrams of droplet configurations are constructed with a comprehensive consideration of interfacial interactions, surface structures, and lubricant thickness. Subsequently, droplet sliding and coalescence dynamics are quantitatively defined under different configurations. Finally, in terms of the promotion of dropwise condensation, a non-cloaking configuration with the encapsulated state underneath the droplet is recommended to achieve high droplet mobility owing to the low viscous drag of the lubricant and the eliminated pinning effect of the contact line. On the basis of the low oil-water and water-solid interactions, a stable lubricant layer with a relatively low thickness is suggested to construct slippery surfaces.

The percentages of signet-ring cells (SRCs) affects the prognosis after radical gastrectomy for advanced gastric cancer.

PURPOSE: Only recently has the percentage of signet-ring cells (SRCs) been shown to affect the prognosis following gastric cancer surgery. It is uncertain whether the SRC percentage has a role in tumour biology or prognosis of gastric signet-ring cell carcinoma (GSRCC). For this research, we assessed the effect of the SRC percentage on the clinicopathological and prognostic characteristics of gastric cancer (GC) tumours and created and verified a prognostic nomogram to assess the overall survival (OS) of GSRCC patients. METHODS: In our study, 1100 GC patients with signet-ring cell carcinoma (SRCC) at Zhejiang Cancer Hospital from December 2013 to December 2018 who underwent curative gastric cancer resection were retrospectively analysed. The patients were separated into two groups: those with SRCC (SRC percentage >50%; n = 157) and those with partial signet-ring cell carcinoma (PSRCC) (SRC percentage ≤50%; n = 943). We compared the clinicopathological characteristics of both groups. To estimate OS and determine correlations with the SRC percentage, the Kaplan-Meier method and log-rank test were used. To develop the prognostic nomogram, independent prognostic indicators for OS were identified using Cox regression analyses. Predictions were assessed using the calibration curve and C-index. RESULTS: Our research showed that there was no discernible difference in OS between the two groups. The preoperative CA242 level, pT stage, pN stage, age, nerve invasion, neoadjuvant chemotherapy, postoperative chemotherapy, and maximum tumour diameter were independent prognostic risk factors for OS for GC (all p < 0.05). However, for advanced GC, the SRC percentage (HR = 1.571, 95% CI 1.072-2.302, p = 0.020) was an independent prognostic factor of OS. Other independent prognostic risk factors were age, pT stage, pN stage, nerve invasion, tumour location, neoadjuvant chemotherapy, postoperative chemotherapy, preoperative CA50 level, and preoperative CEA level (all p < 0.05). On these bases, nomograms were constructed for GC and advanced GC, with C-indexes of 0.806 (95%CI 0.782-0.830) and 0.728 (95%CI 0.697-0.759), respectively. CONCLUSIONS: In cases of advanced gastric cancer, the SRC percentage served as a standalone prognostic indicator for OS. An effective tool for assessing the prognosis of GSRCC was offered by the nomogram.

Efficient plasma metabolic fingerprinting as a novel tool for diagnosis and prognosis of gastric cancer: a large-scale, multicentre study.

OBJECTIVE: Metabolic biomarkers are expected to decode the phenotype of gastric cancer (GC) and lead to high-performance blood tests towards GC diagnosis and prognosis. We attempted to develop diagnostic and prognostic models for GC based on plasma metabolic information. DESIGN: We conducted a large-scale, multicentre study comprising 1944 participants from 7 centres in retrospective cohort and 264 participants in prospective cohort. Discovery and verification phases of diagnostic and prognostic models were conducted in retrospective cohort through machine learning and Cox regression of plasma metabolic fingerprints (PMFs) obtained by nanoparticle-enhanced laser desorption/ionisation-mass spectrometry (NPELDI-MS). Furthermore, the developed diagnostic model was validated in prospective cohort by both NPELDI-MS and ultra-performance liquid chromatography-MS (UPLC-MS). RESULTS: We demonstrated the high throughput, desirable reproducibility and limited centre-specific effects of PMFs obtained through NPELDI-MS. In retrospective cohort, we achieved diagnostic performance with areas under curves (AUCs) of 0.862-0.988 in the discovery (n=1157 from 5 centres) and independent external verification dataset (n=787 from another 2 centres), through 5 different machine learning of PMFs, including neural network, ridge regression, lasso regression, support vector machine and random forest. Further, a metabolic panel consisting of 21 metabolites was constructed and identified for GC diagnosis with AUCs of 0.921-0.971 and 0.907-0.940 in the discovery and verification dataset, respectively. In the prospective study (n=264 from lead centre), both NPELDI-MS and UPLC-MS were applied to detect and validate the metabolic panel, and the diagnostic AUCs were 0.855-0.918 and 0.856-0.916, respectively. Moreover, we constructed a prognosis scoring system for GC in retrospective cohort, which can effectively predict the survival of GC patients. CONCLUSION: We developed and validated diagnostic and prognostic models for GC, which also contribute to advanced metabolic analysis towards diseases, including but not limited to GC.

Efficacy and safety of ripretinib in Chinese patients with advanced gastrointestinal stromal tumors: a real-world, multicenter, observational study.

Introduction: Mutations in KIT proto-oncogene, receptor tyrosine kinase (KIT) and platelet-derived growth factor receptor-α (PDGFRA) render the available tyrosine kinase inhibitors (TKI) ineffective in treating advanced gastrointestinal stromal tumors (GIST). Ripretinib, a broad-spectrum switch-control kinase inhibitor, has shown increased efficacy and manageable safety, but real-world evidence remains scarce. This study evaluates the efficacy and safety of ripretinib among Chinese patients in a real-world setting. Methods: Advanced GIST patients (N=23) receiving ripretinib following progression on previous lines of TKI treatment were enrolled to determine the efficacy [progression-free survival (PFS) and overall survival (OS)]. Safety was assessed by the incidence and severity of adverse events (AEs). All statistical analyses were performed using SPSS version 20.0 and a p-value of <0.05 was considered significant. Results: The median PFS (mPFS) of efficacy analysis set (EAS) (N=21) was 7.1 months. mPFS of patients receiving ripretinib following ≤2 lines of previous TKI treatment and ≥3 prior lines of therapy were 7.1 and 9.2 months, respectively. The median OS (mOS) was 12.0 months and shorter interval between the end of the latest TKI and ripretinib therapy was correlated with longer median PFS and OS (p=0.054 and p=0.046), respectively. Alopecia and asthenia were the most common AEs observed. Conclusion: Compared to previous lines of TKI in advanced GIST patients, ripretinib showed superior efficacy with clinically manageable AEs. Real-world results are comparable to that of phase III INVICTUS study and its Chinese bridging study. Hence, ripretinib can be used for the clinical management of advanced GIST patients.

Deep learning radio-clinical signatures for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients.

BACKGROUND: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of locally advanced gastric cancer (LAGC). The aim of this study was to identify radio-clinical signatures from pretreatment oversampled computed tomography (CT) images to predict the response to NCT and prognosis of LAGC patients. METHODS: LAGC patients were retrospectively recruited from six hospitals from January 2008 to December 2021. An SE-ResNet50-based chemotherapy response prediction system was developed from pretreatment CT images preprocessed with an imaging oversampling method (i.e. DeepSMOTE). Then, the deep learning (DL) signature and clinic-based features were fed into the deep learning radio-clinical signature (DLCS). The predictive performance of the model was evaluated based on discrimination, calibration, and clinical usefulness. An additional model was built to predict overall survival (OS) and explore the survival benefit of the proposed DL signature and clinicopathological characteristics. RESULTS: A total of 1060 LAGC patients were recruited from six hospitals; the training cohort (TC) and internal validation cohort (IVC) patients were randomly selected from center I. An external validation cohort (EVC) of 265 patients from five other centers was also included. The DLCS exhibited excellent performance in predicting the response to NCT in the IVC [area under the curve (AUC), 0.86] and EVC (AUC, 0.82), with good calibration in all cohorts ( P >0.05). Moreover, the DLCS model outperformed the clinical model ( P <0.05). Additionally, we found that the DL signature could serve as an independent factor for prognosis [hazard ratio (HR), 0.828, P =0.004]. The concordance index (C-index), integrated area under the time-dependent ROC curve (iAUC), and integrated Brier score (IBS) for the OS model were 0.64, 1.24, and 0.71 in the test set. CONCLUSION: The authors proposed a DLCS model that combined imaging features with clinical risk factors to accurately predict tumor response and identify the risk of OS in LAGC patients prior to NCT, which can then be used to guide personalized treatment plans with the help of computerized tumor-level characterization.

Perioperative outcomes of neoadjuvant immunotherapy plus chemotherapy and neoadjuvant chemoradiotherapy in the treatment of locally advanced esophageal squamous cell carcinoma: a retrospective comparative cohort study.

Background: Neoadjuvant chemoradiotherapy (nCRT) is recommended as the preferred treatment for locally advanced esophageal squamous cell carcinoma. Recent studies have shown that immune checkpoint inhibitors are beneficial in treating advanced esophageal cancer. Therefore, a growing number of clinical centers are conducting trials of neoadjuvant immunotherapy or neoadjuvant immunotherapy plus chemotherapy (nICT) in patients with locally advanced resectable esophageal cancer. Immunocheckpoint inhibitors are expected to play a role in neoadjuvant therapy for esophageal cancer. However, there were few studies comparing nICT with nCRT. This study compared the efficacy and safety of nICT with that of nCRT administered prior to esophagectomy in patients with resectable locally advanced esophageal squamous cell carcinoma (ESCC). Methods: The study included patients with locally advanced resectable ESCC who were scheduled to receive neoadjuvant therapy at Gaozhou People's Hospital from January 1, 2019, to September 1, 2022. The enrolled patients were divided into 2 groups (nCRT or nICT) according to their neoadjuvant therapy regimen. The 2 groups were compared for their baseline data, the incidence of adverse events during neoadjuvant therapy, the clinical evaluation after neoadjuvant therapy, perioperative indicators, and the incidence of postoperative complications and postoperative pathological remission. Results: A total of 44 patients were enrolled; 23 in the nCRT group and 21 in the nICT group. There were no significant differences between the 2 groups in the baseline data. In the nCRT group, leukopenia occurred more often than in the nICT group, and hemoglobin-decreasing events were rarer (P=0.03<0.05). A significantly higher proportion of patients in the nICT group experienced erythema following neoadjuvant therapy compared to the nCRT group (23.81% vs. 0%; P=0.01<0.05). Neoadjuvant therapy showed no significant difference between the 2 groups for adverse event rates, surgery-related indicators, postoperative pathological remission rates, and postoperative complications. Conclusions: nICT was a safe and feasible treatment for locally advanced ESCC and it may be a potential new treatment modality.

Rema-Net: An efficient multi-attention convolutional neural network for rapid skin lesion segmentation.

For clinical treatment, the accurate segmentation of lesions from dermoscopic images is extremely valuable. Convolutional neural networks (such as U-Net and its numerous variants) have become the main methods for skin lesion segmentation in recent years. However, because these methods frequently have a large number of parameters and complicated algorithm structures, which results in high hardware requirements and long training time, it is difficult to effectively use them for fast training and segmentation tasks. For this reason, we proposed an efficient multi-attention convolutional neural network (Rema-Net) for rapid skin lesion segmentation. The down-sampling module of the network only uses a convolutional layer and a pooling layer, with spatial attention added to improve useful features. We also designed skip-connections between the down-sampling and up-sampling parts of the network, and used reverse attention operation on the skip-connections to strengthen segmentation performance of the network. We conducted extensive experiments on five publicly available datasets to validate the effectiveness of our method, including the ISIC-2016, ISIC-2017, ISIC-2018, PH2, and HAM10000 datasets. The results show that the proposed method reduced the number of parameters by nearly 40% when compared with U-Net. Furthermore, the segmentation metrics are significantly better than some previous methods, and the predictions are closer to the real lesion.

An ultra-sensitive one-pot RNA-templated DNA ligation rolling circle amplification-assisted CRISPR/Cas12a detector assay for rapid detection of SARS-CoV-2.

Rapid, sensitive, and one-pot diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays an extremely important role in point-of-care testing (POCT). Herein, we report an ultra-sensitive and rapid one-pot enzyme-catalyzed rolling circle amplification-assisted CRISPR/FnCas12a assay, termed OPERATOR. OPERATOR employs a single well-designed single-strand padlock DNA, containing a protospacer adjacent motif (PAM) site and a sequence complementary to the target RNA which procedure converts and amplifies genomic RNA to DNA by RNA-templated DNA ligation and multiply-primed rolling circle amplification (MRCA). The MRCA amplicon of single-stranded DNA is cleaved by the FnCas12a/crRNA complex and detected via a fluorescence reader or lateral flow strip. OPERATOR presents outstanding advantages including ultra-sensitivity (1.625 copies per reaction), high specificity (100%), rapid reaction speed (∼30 min), easy operation, low cost, and on-spot visualization. Furthermore, we established a POCT platform by combining OPERATOR with rapid RNA release and a lateral flow strip without professional equipment. The high performance of OPERATOR in SARS-CoV-2 tests was confirmed using both reference materials and clinical samples, and the results suggest that is readily adaptable for point-of-care testing of other RNA viruses.

Nitrogen fixation and phytohormone stimulation of sugarcane plant through plant growth promoting diazotrophic Pseudomonas.

Diazotrophic microorganisms are free-living groups of organisms that can convert atmospheric nitrogen (N) into bioavailable nitrogen for plants, which increases crop development and production. The purpose of the current study was to ascertain how diazotrophic plant growth promoting (PGP) Pseudomonas strains (P. koreensis CY4 and P. entomophila CN11) enhanced nitrogen fixation, defense activity, and PGP attributes of sugarcane varieties; GT11 and G×B9. A 15N isotope-dilution study was conducted to confirm the sugarcane strains' capacity to fix nitrogen, and the results indicated that between 21 to 35% of plant, nitrogen is fixed biologically by selected rhizobacteria. In comparison to the control, after 30, 60, and 90 days, both CY4 and CN11 strains significantly increased defense-related enzymes (catalase, peroxidase, phenylalanine ammonia-lyase, superoxide dismutase, glucanase, and chitinase) and phytohormones (abscisic acid, ABA, cytokinin, etc.) in GT11 and GXB. Additionally, the expression of SuCHI, SuGLU, SuCAT, SuSOD, and SuPAL genes was found to be elevated in Pseudomonas strains inoculated plants using real-time quantitative polymerase chain reaction (RT-qPCR). Both bacterial strains increased all physiological parameters and chlorophyll content in sugarcane plants more than their control. The effects of P. koreensis CY4 and P. entomophila CN11 strains on sugarcane growth promotion and nitrogen fixation under greenhouse conditions are described here for the first time systematically. The results of confirmation studies demonstrated that P. koreensis CY4 and P. entomophila are PGP bacterial strains with the potential to be employed as a biofertilizer for sugarcane growth, nitrogen nutrient absorption, and reduced application of chemical nitrogenous fertilizers in agricultural fields. .

Integrative proteomic characterization of adenocarcinoma of esophagogastric junction.

The incidence of adenocarcinoma of the esophagogastric junction (AEG) has been rapidly increasing in recent decades, but its molecular alterations and subtypes are still obscure. Here, we conduct proteomics and phosphoproteomics profiling of 103 AEG tumors with paired normal adjacent tissues (NATs), whole exome sequencing of 94 tumor-NAT pairs, and RNA sequencing in 83 tumor-NAT pairs. Our analysis reveals an extensively altered proteome and 252 potential druggable proteins in AEG tumors. We identify three proteomic subtypes with significant clinical and molecular differences. The S-II subtype signature protein, FBXO44, is demonstrated to promote tumor progression and metastasis in vitro and in vivo. Our comparative analyses reveal distinct genomic features in AEG subtypes. We find a specific decrease of fibroblasts in the S-III subtype. Further phosphoproteomic comparisons reveal different kinase-phosphosubstrate regulatory networks among AEG subtypes. Our proteogenomics dataset provides valuable resources for understanding molecular mechanisms and developing precision treatment strategies of AEG.

DAGM-fusion: A dual-path CT-MRI image fusion model based multi-axial gated MLP.

Medical imaging technology provides a good understanding of human tissue structure. MRI provides high-resolution soft tissue information, and CT provides high-quality bone density information. By creating CT-MRI fusion images of complex diagnostic situations, experts can develop diagnoses and treatment plans more quickly and precisely. We propose a dual-path CT-MRI image fusion model based on multi-axial gated MLP to create high-quality CT-MRI fusion images. The model employs the feature fusion module SFT-block to effectively integrate detailed Local-Path information guided by global Global-Path information. The fusion is completed through triple constraints, namely global constraints, local constraints, and overall constraints. We design a multi-axial gated MLP module (Ag-MLP). The multi-axial structure maintains the computational complexity linear and increases MLP's inductive bias, allowing MLP to work in shallower or pixel-level small dataset tasks. Ag-MLP and CNN are combined in the network so that the model has both globality and locality. In addition, we design a loss calculation method based on image patches that adaptively generates weights for each patch based on image pixel intensity. The details of the image are efficiently increased when patch-loss is used. Numerous studies demonstrate that the results of our model are superior to those of the latest mainstream fusion model, which are more in accordance with actual clinical diagnostic standards. The ablation studies successfully validate the performance of the model's constituent parts. It is worth mentioning that the model can also be excellently generalized to other modal image fusion tasks.