Sea-ATI unravels novel vocabularies of plant active cistrome.

The cistrome consists of all cis-acting regulatory elements recognized by transcription factors (TFs). However, only a portion of the cistrome is active for TF binding in a specific tissue. Resolving the active cistrome in plants remains challenging. In this study, we report the assay sequential extraction assisted-active TF identification (sea-ATI), a low-input method that profiles the DNA sequences recognized by TFs in a target tissue. We applied sea-ATI to seven plant tissues to survey their active cistrome and generated 41 motif models, including 15 new models that represent previously unidentified cis-regulatory vocabularies. ATAC-seq and RNA-seq analyses confirmed the functionality of the cis-elements from the new models, in that they are actively bound in vivo, located near the transcription start site, and influence chromatin accessibility and transcription. Furthermore, comparing dimeric WRKY CREs between sea-ATI and DAP-seq libraries revealed that thermodynamics and genetic drifts cooperatively shaped their evolution. Notably, sea-ATI can identify not only positive but also negative regulatory cis-elements, thereby providing unique insights into the functional non-coding genome of plants.

Evaluation of the Influence of Varied Juncao Grass Substrates on Physiological and Enzymatic Reactions of Pleurotus ostreatus.

Pleurotus ostreutus is one of the world's most commonly consumed mushrooms. The cultivation of mushrooms using wood resources usually results in environmental issues such as deforestation. Juncao grasses, namely (JJ) Cenchrus fungigraminus, (AR) Saccharum arundinaceum, and (MS) Miscanthus floridulus, supplemented with 20% wheat brain, 1% ground coffee, 1% gysum, and 1% lime, were used as the culture mediums in this research, which offers a composting system with a simple formulation that is cheap and feasible for small farms to use in cultivating oyster mushrooms. The present study assessed the different juncao grasses as substrates for growing Pleurotus ostreatus given their enzyme activities, growth, and yields. The results demonstrated that the yields of pleurotus ostreatus grown on JJ, AR, and MS substrates were significantly different at the level of 0.05 and were recorded as follows: 159.2 g/bag, 132 g/bag, and 65.1 g/bag on average, respectively. The biological efficiency of Pleurotus ostreatus cultivated in three different substrates was 75.2%, 63.4%, and 28.7%, respectively. Lignin peroxidase (LiP) was the most active enzyme in each culture material among the other enzyme activities expressed differently between the substrate and growing stages. At the same time, other enzyme activities were differently expressed between the substrate and different developmental stages. Nutrient analysis revealed significant variations, with differences in polysaccharides, proteins, and amino acids among substrates, as well as the presence of heavy metals such as arsenic, lead, mercury, and cadmium in all samples within safe limits. The obtained results indicated that Saccharum arundinaceum is a good substrate in place of Cenchrus fungigraminus, and that using Miscanthus floridulus is not productive. Moreover, the juncao grasses offer a sustainable approach that reduces reliance on wood-based substrates and enhances environmental sustainability.

CDKN2A somatic copy number amplification in normal tissues surrounding gastric carcinoma reduces cancer metastasis risk in droplet digital PCR analysis.

BACKGROUND: The CDKN2A gene is frequently affected by somatic copy number variations (SCNVs, including deletions and amplifications [SCNdel and SCNamp]) in the cancer genome. Using surgical gastric margin tissue samples (SMs) as the diploid reference in SCNV analysis via CDKN2A/P16-specific real-time PCR (P16-Light), we previously reported that the CDKN2A SCNdel was associated with a high risk of metastasis of gastric carcinoma (GC). However, the status of CDKN2A SCNVs in SMs and their clinical significance have not been reported. METHODS: Peripheral white blood cell (WBC) and frozen GC and SM tissue samples were collected from patients (n = 80). Droplet digital PCR (ddPCR) was used to determine the copy number (CN) of the CDKN2A gene in tissue samples using paired WBCs as the diploid reference. RESULTS: A novel P16-ddPCR system was initially established with a minimal proportion (or limit, 10%) of the detection of CDKN2A CN alterations. While CDKN2A SCNamp events were detected in both SMs and GCs, fewer CDKN2A SCNdel events were detected in SMs than in GCs (15.0% vs. 41.3%, P = 4.77E-04). Notably, significantly more SCNamp and fewer SCNdel of the CDKN2A gene were detected in SMs from GC patients without metastasis than in those from patients with lymph node metastasis by P16-ddPCR (P = 0.023). The status of CDKN2A SCNVs in SM samples was significantly associated with overall survival (P = 0.032). No cancer deaths were observed among the 11 patients with CDKN2A SCNamp. CONCLUSION: CDKN2A SCNVs in SMs identified by P16-ddPCR are prevalent and significantly associated with GC metastasis and overall survival.

Electron-transferring flavoprotein and its dehydrogenase contributed to growth development and virulence in Beauveria bassiana.

Electron-transferring flavoprotein (Etf) and its dehydrogenase (Etfdh) are integral components of the electron transport chain in mitochondria. In this study, we characterize two putative etf genes (Bbetfa and Bbetfb) and their dehydrogenase gene Bbetfdh in the entomopathogenic fungus Beauveria bassiana. Individual deletion of these genes caused a significant reduction in vegetative growth, conidiation, and delayed conidial germination. Lack of these genes also led to abnormal metabolism of fatty acid and increasing lipid body accumulation. Furthermore, the virulence of Bbetfs and Bbetfdh deletion mutants was severely impaired due to decreasing infection structure formation. Additionally, all deletion strains showed reduced ATP synthesis compared to the wild-type strain. Taken together, Bbetfa and Bbetfb, along with Bbetfdh, play principal roles in fungal vegetative growth, conidiation, conidial germination, and pathogenicity of B. bassiana due to their essential functions in fatty acid metabolism.

Comparison of different criteria for estimating major pathological response in resectable non-small cell lung cancer treated with neoadjuvant chemoimmunotherapy.

BACKGROUND: Major pathological response (MPR) is proposed as a surrogate endpoint for survival in non-small cell lung cancer (NSCLC) after neoadjuvant chemoimmunotherapy. However, the criteria for estimating MPR differ between the recommendations of the International Association for the Study of Lung Cancer (IASLC) and the immune-related pathologic response criterion (irPRC). IASLC's criteria focus solely on evaluating the primary tumor, while irPRC's criteria encompass both the primary tumor and lymph node metastasis. Our objective is to compare the prognostic value of different criteria for estimating MPR. METHODS: We conducted a retrospective study on a cohort of 235 patients with NSCLC after neoadjuvant chemoimmunotherapy. The survival endpoint was event-free survival (EFS). The MPR status of each patient was evaluated using both IASLC's criteria and irPRC's criteria. The prognostic value was compared using the Area Under Curve (AUC). RESULTS: The MPR rates were 63.4 % (149/235) and 57.4 % (135/235) according to IASLC's and irPRC's criteria, respectively. Inconsistent cases, characterized by MPR status according to IASLC's criteria but non-MPR status according to irPRC's criteria, constituted 6.0 % (14/235) of the overall cohort and 15.2 % (14/92) of patients with pretreatment N positive disease. Interestingly, all inconsistent patients showed no recurrence during the study period. Although both MPR statuses according to IASLC (p = 0.00039) and irPRC (p = 0.0094) were associated with improved EFS, IASLC's criteria (AUC = 0.65) were superior to irPRC's criteria (AUC = 0.62) with a higher AUC value. CONCLUSION: IASLC's criteria for estimating MPR were superior to irPRC's criteria in predicting EFS for NSCLC after neoadjuvant chemoimmunotherapy.

Secondary metabolites from the fungus Cladosporium xylophilum.

A new cladosporol derivative xylophilum A (1), together with 10 known compounds (2-11), were isolated from the rice fermentation of the fungus Cladosporium xylophilum. Their structures were established by extensive spectroscopic methods and comparison of their NMR data with literatures. The antimicrobial activity of compound 1 against 11 kinds of pathogenic microbial was evaluated, but no significant activity was found (MIC >100 µg/ml).

Exploring the Evolutionary History and Phylogenetic Relationships of Giant Reed (Arundo donax) through Comprehensive Analysis of Its Chloroplast Genome.

Giant reed (Arundo donax) is widely distributed across the globe and is considered an important energy crop. This study presents the first comprehensive analysis of the chloroplast genome of giant reed, revealing detailed characteristics of this species' chloroplast genome. The chloroplast genome has a total length of 137,153 bp, containing 84 protein-coding genes, 38 tRNA genes, and 8 rRNA genes, with a GC content of 39%. Functional analysis indicates that a total of 45 photosynthesis-related genes and 78 self-replication-related genes were identified, which may be closely associated with its adaptability and growth characteristics. Phylogenetic analysis confirmed that Arundo donax cv. Lvzhou No.1 belongs to the Arundionideae clade and occupies a distinct evolutionary position compared to other Arundo species. The findings of this study not only enhance our understanding of the giant reed genome but also provide valuable genetic resources for its application in biotechnology, bioenergy crop development, and ecological restoration.

A Spatiotemporal Transcriptome Reveals Stalk Development in Pearl Millet.

Pearl millet is a major cereal crop that feeds more than 90 million people worldwide in arid and semi-arid regions. The stalk phenotypes of Poaceous grasses are critical for their productivity and stress tolerance; however, the molecular mechanisms governing stalk development in pearl millet remain to be deciphered. In this study, we spatiotemporally measured 19 transcriptomes for stalk internodes of four different early developmental stages. Data analysis of the transcriptomes defined four developmental zones on the stalks and identified 12 specific gene sets with specific expression patterns across the zones. Using weighted gene co-expression network analysis (WGCNA), we found that two co-expression modules together with candidate genes were involved in stalk elongation and the thickening of pearl millet. Among the elongation-related candidate genes, we established by SELEX that a MYB-family transcription factor PMF7G02448 can bind to the promoters of three cell wall synthases genes (CesAs). In summary, these findings provide insights into stalk development and offer potential targets for future genetic improvement in pearl millet.

Deep learning prediction model for central lymph node metastasis in papillary thyroid microcarcinoma based on cytology.

Controversy exists regarding whether patients with low-risk papillary thyroid microcarcinoma (PTMC) should undergo surgery or active surveillance; the inaccuracy of the preoperative clinical lymph node status assessment is one of the primary factors contributing to the controversy. It is imperative to accurately predict the lymph node status of PTMC before surgery. We selected 208 preoperative fine-needle aspiration (FNA) liquid-based preparations of PTMC as our research objects; all of these instances underwent lymph node dissection and, aside from lymph node status, were consistent with low-risk PTMC. We separated them into two groups according to whether the postoperative pathology showed central lymph node metastases. The deep learning model was expected to predict, based on the preoperative thyroid FNA liquid-based preparation, whether PTMC was accompanied by central lymph node metastases. Our deep learning model attained a sensitivity, specificity, positive prediction value (PPV), negative prediction value (NPV), and accuracy of 78.9% (15/19), 73.9% (17/23), 71.4% (15/21), 81.0% (17/21), and 76.2% (32/42), respectively. The area under the receiver operating characteristic curve (value was 0.8503. The predictive performance of the deep learning model was superior to that of the traditional clinical evaluation, and further analysis revealed the cell morphologies that played key roles in model prediction. Our study suggests that the deep learning model based on preoperative thyroid FNA liquid-based preparation is a reliable strategy for predicting central lymph node metastases in thyroid micropapillary carcinoma, and its performance surpasses that of traditional clinical examination.

Camrelizumab in different PD-L1 expression cohorts of pre-treated advanced or metastatic non-small cell lung cancer: a phase II study.

BACKGROUND: This phase II study evaluated camrelizumab in different PD-L1 expression cohorts of patients with previously treated advanced/metastatic non-small cell lung cancer (NSCLC; NCT03085069, registered March 21, 2017). METHODS: Patients who progressed during/after chemotherapy were enrolled and divided into four cohorts based on PD-L1 tumor proportion score (TPS). Patients with EGFR/ALK alterations and PD-L1 TPS ≥ 50% were also eligible. All enrolled patients received camrelizumab at 200 mg IV Q2W. The primary endpoint was objective response rate. RESULTS: A total of 146 patients were enrolled. As of data cutoff on Aug 20, 2020, the median follow-up was 29.5 months (95% CI 27.4-30.8). Objective response rate was 17.8% (95% CI 12.0-25.0) and improved with the increasing PD-L1 TPS (TPS < 1%, 12.2% [95% CI 5.7-21.8]; ≥ 1-< 25%, 19.4% [95% CI 7.5-37.5]; ≥ 25-< 50%, 36.4% [95% CI 10.9-69.2]; ≥ 50%, 23.3% [95% CI 9.9-42.3]). No response was observed in the five patients harboring EGFR mutations. Median progression-free survival was 3.2 months (95% CI 2.0-3.4), and patients with positive PD-L1 TPS had longer progression-free survival. Median overall survival was 14.8 months (95% CI 10.2-18.7). Treatment-related adverse events (TRAEs) of any grade occurred in 87.7% of patients, and 21.2% had grade ≥ 3 TRAEs. CONCLUSION: Camrelizumab showed improved efficacy compared with historical data of the second-line chemotherapy in pre-treated advanced/metastatic NSCLC. Patients with positive PD-L1 expression derived greater benefit from camrelizumab. Camrelizumab has a manageable safety profile.

Heterogeneity of programmed death-ligand 1 expression and infiltrating lymphocytes in paired resected primary and metastatic non-small cell lung cancer.

Metastatic tumors (MTs) may show different characteristics of the immune microenvironment from primary tumors (PTs) in non-small cell lung cancer (NSCLC). The heterogeneity of immune markers in metastatic NSCLC and its associated factors has not been well demonstrated. In this study, 64 surgically resected specimens of paired PTs and MTs were obtained from 28 patients with NSCLC. Multiplex immunofluorescence (mIF; panel including programmed death-ligand 1 (PD-L1), Cytokeratin, CD8, and CD68) was performed on whole sections. The heterogeneity of the immune contexture of PD-L1 expression, infiltrating lymphocytes, and immune-to-tumor cell distances was quantified via digital image analysis. In a quantitative comparison of MTs and corresponding PTs, MTs showed higher PD-L1 expression levels, lower density of CD8+ cytotoxic T lymphocytes (CTLs), and longer spatial distance between CTLs and tumor cells. Subgroup analysis, which associated clinical factors, revealed that the heterogeneity of immune markers was more obvious in extrapulmonary, metachronous, and treated MTs, while fewer differences were observed in intrapulmonary, synchronous, and untreated MTs. In particular, MTs showed significantly higher PD-L1 expression and lower lymphocyte infiltration in metastatic NSCLC with EGFR mutations. Prognosis analysis showed that an increased density of CD8+ CTLs in MTs was associated with better overall survival (OS). Therefore, significant discrepancies in PD-L1 expression and lymphocyte infiltration in metastatic NSCLC are most likely associated with temporal heterogeneity with a history of anti-treatment and correlated with EGFR mutations. The detection of immune markers in re-obtained metastatic specimens may be required for immunotherapy prediction in these patients with metastatic NSCLC.

Artificial intelligence-assisted system for precision diagnosis of PD-L1 expression in non-small cell lung cancer.

Standardized programmed death-ligand 1 (PD-L1) assessment in non-small cell lung cancer (NSCLC) is challenging, owing to inter-observer variability among pathologists and the use of different antibodies. There is a strong demand for the development of an artificial intelligence (AI) system to obtain high-precision scores of PD-L1 expression in clinical diagnostic scenarios. We developed an AI system using whole slide images (WSIs) of the 22c3 assay to automatically assess the tumor proportion score (TPS) of PD-L1 expression based on a deep learning (DL) model of tumor detection. Tests were performed to show the diagnostic ability of the AI system in the 22c3 assay to assist pathologists and the reliability of the application in the SP263 assay. A robust high-performance DL model for automated tumor detection was devised with an accuracy and specificity of 0.9326 and 0.9641, respectively, and a concrete TPS value was obtained after tumor cell segmentation. The TPS comparison test in the 22c3 assay showed strong consistency between the TPS calculated with the AI system and trained pathologists (R = 0.9429-0.9458). AI-assisted diagnosis test confirmed that the repeatability and efficiency of untrained pathologists could be improved using the AI system. The Ventana PD-L1 (SP263) assay showed high consistency in TPS calculations between the AI system and pathologists (R = 0.9787). In conclusion, a high-precision AI system is proposed for the automated TPS assessment of PD-L1 expression in the 22c3 and SP263 assays in NSCLC. Our study also indicates the benefits of using an AI-assisted system to improve diagnostic repeatability and efficiency for pathologists.

Clinical validation of a 90-gene expression test for tumor tissue of origin diagnosis: a large-scale multicenter study of 1417 patients.

BACKGROUND: Once malignancy tumors were diagnosed, the determination of tissue origin and tumor type is critical for clinical management. Although the significant advance in imaging techniques and histopathological approaches, the diagnosis remains challenging in patients with metastatic and poorly differentiated or undifferentiated tumors. Gene expression profiling has been demonstrated the ability to classify multiple tumor types. The present study aims to assess the performance of a 90-gene expression test for tumor classification (i.e. the determination of tumor tissue of origin) in real clinical settings. METHODS: Formalin-fixed paraffin-embedded samples and associated clinicopathologic information were collected from three cancer centers between January 2016 and January 2021. A total of 1417 specimens that met quality control criteria (RNA quality, tumor cell content ≥ 60% and so on) were analyzed by the 90-gene expression test to identify the tumor tissue of origin. The performance was evaluated by comparing the test results with histopathological diagnosis. RESULTS: The 1417 samples represent 21 main tumor types classified by common tissue origins and anatomic sites. Overall, the 90-gene expression test reached an accuracy of 94.4% (1338/1417, 95% CI: 0.93 to 0.96). Among different tumor types, sensitivities were ranged from 74.2% (head&neck tumor) to 100% (adrenal carcinoma, mesothelioma, and prostate cancer). Sensitivities for the most prevalent cancers of lung, breast, colorectum, and gastroesophagus are 95.0%, 98.4%, 93.9%, and 90.6%, respectively. Moreover, specificities for all 21 tumor types are greater than 99%. CONCLUSIONS: These findings showed robust performance of the 90-gene expression test for identifying the tumor tissue of origin and support the use of molecular testing as an adjunct to tumor classification, especially to those poorly differentiated or undifferentiated tumors in clinical practice.

Characterization of a fungal competition factor: Production of a conidial cell-wall associated antifungal peptide.

Competition is one of the fundamental driving forces of natural selection. Beauveria bassiana is a soil and plant phylloplane/root fungus capable of parasitizing insect hosts. Soil and plant environments are often enriched with other fungi against which B. bassiana competes for survival. Here, we report an antifungal peptide (BbAFP1), specifically expressed and localized to the conidial cell wall and is released into the surrounding microenvironment inhibiting growth of competing fungi. B. bassiana strains expressing BbAFP1, including overexpression strains, inhibited growth of Alternaria brassicae in co-cultured experiments, whereas targeted gene deletion of BbAFP1 significantly decreased (25%) this inhibitory effect. Recombinant BbAFP1 showed chitin and glucan binding abilities, and growth inhibition of a wide range of phytopathogenic fungi by disrupting membrane integrity and eliciting reactive oxygen species (ROS) production. A phenylalanine residue (F50) contributes to chitin binding and antifungal activity, but was not required for the latter. Expression of BbAFP1 in tomato resulted in transgenic plants with enhanced resistance to plant fungal pathogens. These results highlight the importance of fungal competition in shaping primitive competition strategies, with antimicrobial compounds that can be embedded in the spore cell wall to be released into the environment during the critical initial phases of germination for successful growth in its environmental niche. Furthermore, these peptides can be exploited to increase plant resistance to fungal pathogens.

Percentage of Newly Proposed High-Grade Patterns Is Associated with Prognosis of Pathological T1-2N0M0 Lung Adenocarcinoma.

OBJECTIVE: To evaluate the prognostic value of the percentage of high-grade patterns (micropapillary, solid, and complex glands) in early-stage lung adenocarcinoma (LUAD). METHODS: A total of 1049 patients undergoing radical surgery with pathological T1-2N0M0 LUAD were screened retrospectively, and 191 patients were involved in the final analysis. Disease-free survival (DFS) was evaluated using the Kaplan-Meier curve and Cox regression analysis. The optimal cut-off value was determined using maximally selected rank statistics. RESULTS: The entire cohort was divided into quartile groups based on the percentage of high-grade patterns: Group 1 (≤ 30%), Group 2 (31-55%), Group 3 (56-85%), and Group 4 (≥ 86%). There were significant differences in smoking history (P = 0.041), EGFR mutations (P < 0.001), and ALK rearrangement (P = 0.010) between the four groups, but no significant differences in other clinicopathological features. Kaplan-Meier analysis showed that a higher percentage of high-grade patterns predicted worse DFS (P = 0.001), and multivariate analysis indicated that the percentage of high-grade patterns was an independent predictor (Group 2 vs. Group 1, HR = 2.136, P = 0.228; Group 3 vs. Group 1, HR = 3.355, P = 0.035; Group 4 vs. Group 1, HR = 5.147, P = 0.003, respectively). A cut-off value of 20% (P = 0.048) and 50% (P <0.001) for high-grade patterns were tested, and both revealed a significant difference in distinguishing DFS between subgroups. CONCLUSIONS: The percentage of high-grade patterns is associated with the prognosis of early-stage invasive LUAD. A higher percentage indicates a worse prognosis.

Post-discharge experiences of patients with extracorporeal membrane oxygenation support: A qualitative study.

PURPOSE: To explore the life experiences of patients who have been discharged after undergoing extracorporeal membrane oxygenation (ECMO) support. DESIGN: A qualitative descriptive approach was used. METHODS: Patients who have undergone ECMO support and have been discharged were recruited. Thirteen participants were involved in this study. The data were collected through a semi-structured interview and analyzed using the Colaizzi method. FINDINGS: Four major themes in life experiences were reported by the participants: changes in physical function, changes in psychological state, active adaptation to daily life, and substantial rehabilitation needs. CONCLUSION: Different, continuous, and convenient post-discharge physical and mental interventions, social support, spiritual support, and rehabilitation services should be provided according to the patient's circumstances. We also call on the government to increase the patient reimbursement rate for ECMO treatment. These measures may help to improve the quality of life of patients.

Ergosterol-targeting fusion antifungal peptide significantly increases the Verticillium wilt resistance of cotton.

Increasing the targeting ability of antifungal proteins towards specific components of fungal cells has the potential to improve their antifungal activity and reduce harmful effects to nontarget cells. To obtain effective disease resistance genes against cotton Verticillium wilt, we constructed several fusion genes, in which binding domains targeting chitin, sphingolipid or ergosterol in the fungal cell wall or cell membrane were individually fused to the antifungal peptide BbAFP1 from entomopathogenic fungus Beauveria bassiana. Transient expression of fusion genes in cotton cotyledons indicated that the BbAFP1::ErBD fusion peptide with an ergosterol binding domain exhibited better disease resistance against V. dahliae than wild-type BbAFP1 and other fusion genes. BbAFP1::ErBD and BbAFP1 transgenic cotton were obtained and verified by Southern and Western blotting. Compared with BbAFP1-expressing cotton, BbAFP1::ErBD-expressing cotton showed higher disease resistance against V. dahliae, with smaller lesion areas (0.07 cm2 vs. 0.16 cm2 ) on the leaves and a lower disease index (23.9 vs. 34.5). Overexpression of BbAFP1::ErBD by transgenic tobacco also showed enhanced disease resistance against V. dahliae compared with that of the wild-type gene. These results indicated that construction of fusion antifungal peptides that target fungal cells is a powerful strategy to obtain new anti-disease genes, and the obtained fusion gene BbAFP1::ErBD has the potential to defend against plant fungal diseases.

Major pathologic response assessment and clinical significance of metastatic lymph nodes after neoadjuvant therapy for non-small cell lung cancer.

For neoadjuvant therapy in patients with non-small cell lung cancer, the major pathologic response of primary tumors may be an assessable and reliable surrogate measure of survival. Few studies have examined the pathologic evaluation of metastatic lymph node responses and their prognostic significance. This retrospective study enrolled 336 patients with non-small cell lung cancer (squamous cell carcinoma, n = 216; adenocarcinoma, n = 120) treated with neoadjuvant therapy including chemotherapy (n = 316) and targeted therapy (adenocarcinoma, n = 20). The treatment response of the primary tumor and lymph node metastases (LNM) were pathologically assessed according to the multidisciplinary recommendations of the International Association for the Study of Lung Cancer. The relationship of overall survival (OS) and disease-free survival (DFS) with the responses of the primary tumor or LNM was analyzed. The optimal cutoff value of the residual viable tumor (%RVT) of the primary tumor was 12% for both OS (P < 0.001) and DFS (P < 0.001). The pathologic assessment identified LNM in 208 patients. The optimal %RVT cutoff value in LNM was 8% for both OS (P = 0.003) and DFS (P < 0.001). The Spearman's rank correlation coefficient between primary tumors and corresponding LNM was 0.487 for %RVT (P < 0.001), which indicated a positive correlation. On multivariable analysis, an RVT of the primary tumor ≤12% was an independent prognostic factor for improved OS (P = 0.024), whereas an RVT of LNM ≤ 8% was an independent prognostic factor for increased DFS (P = 0.018). Furthermore, in the neoadjuvant chemotherapy group, the optimal %RVT cutoff values for OS in patients with squamous cell carcinoma and adenocarcinoma in the primary tumor were 12% and 58%, respectively. Considering its convenience and operability in clinical application, a 10% threshold RVT value can be used for prognostic evaluation of LNM and primary tumors of squamous cell carcinoma histology; further studies are needed to confirm the optimal cutoff value for primary tumors of adenocarcinoma.

A Review of Artificial Intelligence in Precise Assessment of Programmed Cell Death-ligand 1 and Tumor-infiltrating Lymphocytes in Non-Small Cell Lung Cancer.

Advances in immunotherapy have increased the need for stratified predictive biomarkers in patients with non-small cell lung cancer. However, precise evaluation of tumor tissue-based immune biomarkers, such as programmed cell death-ligand 1 (PD-L1) and the characteristics of tumor infiltrating lymphocytes (TILs), is a challenge in clinical practice. In recent years, the digitization of whole-slide images of tissue has accelerated the implementation of artificial intelligence (AI) approaches in tumor pathology and provided an opportunity to use AI tools to improve the interpretation of immune biomarkers. This review describes the current challenges in the assessment of PD-L1 scoring and TILs and demonstrates the role of AI in helping pathologists integrate PD-L1 and biomarkers of the tumor immune microenvironment. Computer-aided PD-L1 scoring is highly consistent with pathologists and reduces the variation among interobservers, providing a promising diagnostic tool in pathology clinics. In addition, applications of image analysis algorithms, in combination with multiplex staining, enable in-depth quantitative and spatial analysis of the broader tumor microenvironment. Upon combining digital pathology and AI, an automatic analysis system of PD-L1 and TILs, which was established using a set of digital staining images and deep learning algorithms, might be an effective way to overcome the challenges in the precise assessment of immune biomarkers.

Ganoderic acid alleviates chemotherapy-induced fatigue in mice bearing colon tumor.

Chemotherapy-related fatigue (CRF) is increasingly being recognized as one of the severe symptoms in patients undergoing chemotherapy, which not only largely reduces the quality of life in patients, but also diminishes their physical and social function. At present, there is no effective drug for preventing and treating CRF. Ganoderic acid (GA), isolated from traditional Chinese medicine Ganoderma lucidum, has shown a variety of pharmacological activities such as anti-tumor, anti-inflammation, immunoregulation, etc. In this study, we investigated whether GA possessed anti-fatigue activity against CRF. CT26 tumor-bearing mice were treated with 5-fluorouracil (5-FU, 30 mg/kg) and GA (50 mg/kg) alone or in combination for 18 days. Peripheral and central fatigue-related behaviors, energy metabolism and inflammatory factors were assessed. We demonstrated that co-administration of GA ameliorated 5-FU-induced peripheral muscle fatigue-like behavior via improving muscle quality and mitochondria function, increasing glycogen content and ATP production, reducing lactic acid content and LDH activity, and inhibiting p-AMPK, IL-6 and TNF-α expression in skeletal muscle. Co-administration of GA also retarded the 5-FU-induced central fatigue-like behavior accompanied by down-regulating the expression of IL-6, iNOS and COX2 in the hippocampus through inhibiting TLR4/Myd88/NF-κB pathway. These results suggest that GA could attenuate 5-FU-induced peripheral and central fatigue in tumor-bearing mice, which provides evidence for GA as a potential drug for treatment of CRF in clinic.