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Abstract Background Integrin alpha 5 (ITGA5) was previously confirmed to be related to prognosis in several cancer types; however, its function in clear cell renal cell carcinoma (ccRCC) and how this molecule regulates tumor progression and the tumor microenvironment (TME) remain to be elucidated. Methods We investigated the prognostic implications of ITGA5 with a machine learning model and evaluated biological behaviors of different levels of ITGA5 expression in vitro. Bioinformatic analysis was performed to explain the comprehensive effect of ITGA5 on the TME and drug sensitivity. Results We constructed a machine learning model to elaborate the prognostic implication of ITGA5. As tumorigenesis of ccRCC was tightly relevant with several mutant genes, we investigated the correlation between ITGA5 expression and frequent mutations and found ITGA5 upregulation in VHL mutant ccRCC (P = 0.016). Through overexpressing, silencing, and blocking ITGA5, we verified the role of ITGA5 in promoting ccRCC adverse biological activities; and the potential functions of ITGA5 in ccRCC were bioinformatically demonstrated, summarizing as cell proliferation, migration, and angiogenesis. The localization of ITGA5 primarily in endothelia and macrophages further verified its magnitude in angiogenesis and aroused our excavation in ITGA5 regulation of immune infiltration landscape. Generally, ITGA5-high ccRCC presented an immunosuppressive TME by inducing a lower level of CD8 + T cell infiltration. For the last part we predicted drug sensitivity relevant to ITGA5 and concluded that a joint medication of ITGA5 inhibitors and VEGFR-target drugs (including sunitinib, axitinib, pazopanib, and motesanib) might be a promising therapeutic strategy. Conclusion Our findings clarified the adverse outcome induced by high expression of ITGA5 in ccRCC patients. In vitro experiments and bioinformatical analysis identified ITGA5 function as predominantly cell proliferation, migration, angiogenesis, and macrophage recruitment. Further, we predicted immune infiltration and medication sensitivity regulation by ITGA5 and proposed a joint use of ITGA5 inhibitors and anti-angiogenetic drugs as a potential potent therapeutic strategy.

Abstract Background Major depressive disorder (MDD) is a highly heterogeneous disease, with differences in clinical manifestations among depression patients based on onset ages and genders. The neural mechanisms underlying these differences remain unclear. In this study, we utilized resting state functional imaging data from a large sample database and adopted the ReHo method to investigate gender differences in local brain function in MDD patients across different onset age groups. Methods The study included 364 MDD patients and 695 healthy participants who were part of the REST-meta-MDD project. Regional homogeneity (ReHo) assessed gender disparities in MDD and healthy individuals within groups delineated by gender and onset age (young group: 18–29 years; middle-aged group: 30–45 years). Results Among the young MDD groups, there were significant gender differences in the right superior frontal gyrus, right inferior frontal gyrus, left superior temporal gyrus, and right superior parietal lobule, with male MDD patients having higher ReHo values compared to females. When compared to healthy males, male MDD patients exhibited elevated ReHo values in the right superior parietal lobule. In the middle-aged groups, a marked ReHo difference was observed in the bilateral cerebellum posterior lobe, with female MDD patients showing higher ReHo values. Conclusions The functional mechanisms of MDD differ between genders and show distinct variations across different onset age groups. These findings underscore the importance of developing personalized interventions that address the unique needs of MDD patients, tailored to their gender and age, and necessitate the development of antidepressant medications targeted at each gender-age subgroup.

Abstract Objective To collect maternal maternity information on preterm births in two tertiary hospitals in the urban area of Baota District, Yan'an City, from January 2018 to December 2020, to explore the long-term and short-term effects of air pollutants (PM2.5, PM10, SO2, NO2, CO and O3) and preterm births, and to explore changes in blood cell counts due to air pollutants. Methods Daily average mass concentration data of six air pollutants in the urban area of Yan'an City from January 1, 2017 to December 31, 2020 were collected from the monitoring station in Baota District, Yan'an City. Meteorological information was obtained from the Meteorological Bureau of Yan'an City, including temperature,relative humidity and wind speed for the time period. The mass concentration of air pollutants in each exposure window of pregnant women was assessed by the nearest monitoring station method, and conditional logistic regression was used to analyze the relationship between air pollutants and preterm births, as well as the lagged and cumulative effects of air pollutants. Multiple linear regression was used to explore the relationship between air pollutants and blood tests after stepwise linear regression was used to determine confounders for each blood test. Results The long-term effects of pollutants showed that PM2.5, PM10, SO2, NO2and CO were risk factors for preterm birth. In the two-pollutant model, PM2.5, PM10, SO2 and NO2 mixed with other pollutants were associated with preterm birth. The lagged effect showed that PM2.5, PM10, SO2, NO, and CO were associated with preterm birth; the cumulative effect showed that other air pollutants except O3 were associated with preterm birth. The correlation study between air pollutants and blood indicators showed that air pollutants were correlated with leukocytes, monocytes, basophils, erythrocytes, hs-CRPand not with CRP. Conclusion Exposure to air pollutants is a risk factor for preterm birth. Exposure to air pollutants was associated with changes in leukocytes, monocytes, basophils and erythrocytes and hs-CRP.

Reuse represents a critical strategy for prolonging the utility of items while conserving resources. The aim of this meta-analysis is to aggregate and reanalyze previous studies on factors influencing reuse behavior. By integrating data from 59 studies comprising 366 samples, the research assess the relationship between factors based on different motivational goals and reuse behavior. The results reveal that the factors of attitudes, outcome efficacy and knowledge are most strongly associated with public reuse behaviors. Furthermore, the study found that the public showed a higher level of acceptance for reusing products following remanufacturing than for other reuse treatment processes. In terms of economic considerations, there is a marked preference for the reuse of higher-priced items among the public. The study contributes to a systematic summary of reuse behaviors and enriches existing research by offering strategies to encourage item reuse.

ObjectiveTo investigate the association between exposure to atmospheric pollutants and preterm birth in a river valley-type city and its critical exposure windows.MethodsA retrospective cohort study was used to collect data from the medical records of preterm and full-term deliveries in two hospitals in urban areas of a typical river valley-type city from January 2018 to December 2019. A total of 7,288 cases were included in the study with general information such as pregnancy times, the number of cesarean sections, occupation, season of conception and regularity of the menstrual cycle. And confounding factors affecting preterm birth were inferred using the chi-square test. The effects of exposure to each pollutant, including particulate matter 2.5 (PM2.5), particulate matter 10 (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone (O3), during pregnancy on preterm birth and the main exposure windows were explored by establishing a logistic regression model with pollutants introduced as continuous variables.ResultsMaternal age, pregnancy times, number of births, number of cesarean sections, season of conception, complications diseases, comorbidities diseases, hypertension disorder of pregnancy and neonatal low birth weight of the newborn were significantly different between preterm and term pregnant women. Logistic regression analysis after adjusting for the above confounders showed that the risk of preterm birth increases by 0.9, 0.6, 2.4% in T2 and by 1.0, 0.9, 2.5% in T3 for each 10 μg/m3 increase in PM2.5, PM10, NO2 concentrations, respectively. The risk of preterm birth increases by 4.3% in T2 for each 10 μg/m3 increase in SO2 concentrations. The risk of preterm birth increases by 123.5% in T2 and increases by 188.5% in T3 for each 10 mg/m3 increase in CO concentrations.ConclusionMaternal exposure to PM2.5, PM10, NO2, CO was associated with increased risk on preterm birth in mid-pregnancy (T2) and late pregnancy (T3), SO2 exposure was associated with increased risk on preterm birth in mid-pregnancy (T2).

Abstract Background Raising the birth rate can effectively increase the resulting labour supply and minimise the adverse impact of an ageing population on high-quality economic development since the demographic dividend is rapidly declining. The Chinese government has a “three-child” policy in place, yet the fertility rate is still falling. This study intends to investigate the present fertility intentions of female university students and assess the extent to which feminism has affected their intentions. It will next investigate the degree to which and the mechanisms by which the psychosocial factors have an impact on those intentions. Methods A cross-sectional survey of female university students was conducted in Nanjing, China, from February to March 2023. To assure the representativeness of the sample, a technique of stratified proportional sampling, PPS sampling, and convenience sampling was utilized. A total of 1124 valid samples were acquired from female university students in 15 comprehensive universities. The data were mined and analysed by SPSS (version 24.0) and AMOS (version 24.0) software. Results Overall female university students’ fertility intentions are low at this stage, with more than half (53.55%) of them having no clear desire to have children. The level of feminist identity significantly negatively affected the Intensity of desire to have children (-0.32) and child-number desires (-0.7). Psychosocial factors had a greater degree of influence on fertility intentions. The direct effect of the level of feminist identity and the perception of fertility hindrances on childbearing desires was -0.63 and -0.50 respectively, and the direct effect of the perception of fertility supports on childbearing intentions was 0.79. Conclusion The level of feminist identity is significantly and negatively related to childbearing desires. Psychosocial factors have a greater degree of influence on fertility intentions, with the level of feminist identity, the perception of fertility hindrances and the perception of fertility supports all significantly impacting fertility intentions. The findings of this study emphasise the importance of the government providing a full range of social security and employers providing better employee benefits to promote a fertility-friendly society.

The application of a hybrid-fruit-peel (HFP) coagulant used as an external carbon source (ECS) in both simulated water and real sewage having a low carbon source treated with sequencing batch reactor (SBR) was studied, compared with that of sodium acetate (NaAc). The impact of HFP on sludge properties (such as extracellular polymer substance (EPS), dehydrogenase activity (DHA), charged property, size, microscopic images and bacteria phase) was characterized. The results showed that as an ECS, HFP basically gave similar nitrogen removal to NaAc and also gave a similar developing trend of both dissolved oxygen (DO) and pH. HFP promoted more proliferation of microorganisms and posed higher levels of protein (PN) and polysaccharide (PS) than NaAc, but gave slightly lower DHA than NaAc. After HFP was added as an ECS, the types and quantities of microorganisms increased significantly, the effluent qualities were improved and the sludge size and extensibility became larger, which was conducive to direct contact and remove pollutants. HFP played a similar role to NaAc as ECS and can be used as a quality and slow-releasing ECS for low carbon source wastewaters. HIGHLIGHTS Application of HFP coagulant as an external carbon source (ECS) for low C/N wastewater was studied and gave a similar effect to NaAc.; HFP can be used as a quality and slow-releasing ECS for low C/N wastewater.; HFP produced sludge has a larger size and better extensibility.; HFP promoted more proliferation of microorganisms and gave better effluent qualities.;

Background: The tumor microenvironment (TME) performs a crucial function in the tumorigenesis and response to immunotherapies of clear cell renal cell carcinoma (ccRCC). However, a lack of recognized pre-clinical TME-based risk models poses a great challenge to investigating the risk factors correlated with prognosis and treatment responses for patients with ccRCC. Methods: Stromal and immune contexture were assessed to calculate the TMErisk score of a large sample of patients with ccRCC from public and real-world cohorts using machine-learning algorithms. Next, analyses for prognostic efficacy, correlations with clinicopathological features, functional enrichment, immune cell distributions, DNA variations, immune response, and heterogeneity were performed and validated. Results: Clinical hub genes, including INAFM2, SRPX, DPYSL3, VSIG4, APLNR, FHL5, A2M, SLFN11, ADAMTS4, IFITM1, NOD2, CCR4, HLA-DQB2, and PLAUR, were identified and incorporated to develop the TMErisk signature. Patients in the TMEhigh risk group (category) exhibited a considerably grim prognosis, and the TMErisk model was shown to independently function as a risk indicator for the overall survival (OS) of ccRCC patients. Expression levels of immune checkpoint genes were substantially increased in TMEhigh risk group, while those of the human leukocyte antigen (HLA) family genes were prominently decreased. In addition, tumors in the TMEhigh group showed significantly high infiltration levels of tumor-infiltrated lymphocytes, including M2 macrophages, CD8+ T cells, B cells, and CD4+ T cells. In heterogeneity analysis, more frequent somatic mutations, including pro-tumorigenic BAP1 and PBRM1, were observed in the TMEhigh group. Importantly, 19.3% of patients receiving immunotherapies in the TMEhigh group achieved complete or partial response compared with those with immune tolerance in the TMElow group, suggesting that TMErisk prominently differentiates prognosis and responses to immunotherapy for patients with ccRCC. Conclusions: We first established the TMErisk score of ccRCC using machine-learning algorithms based on a large-scale population. The TMErisk score can be utilized as an innovative independent prognosis predictive marker with high sensitivity and accuracy. Our discovery also predicted the efficacy of immunotherapy in ccRCC patients, indicating the intimate link between tumor immune microenvironment and intratumoral heterogeneity.

Abstract The tyrosine kinase inhibitor (TKI) Sunitinib is one the therapies approved for advanced renal cell carcinoma. Here, we undertake proteogenomic profiling of 115 tumors from patients with clear cell renal cell carcinoma (ccRCC) undergoing Sunitinib treatment and reveal the molecular basis of differential clinical outcomes with TKI therapy. We find that chromosome 7q gain-induced mTOR signaling activation is associated with poor therapeutic outcomes with Sunitinib treatment, whereas the aristolochic acid signature and VHL mutation synergistically caused enhanced glycolysis is correlated with better prognosis. The proteomic and phosphoproteomic analysis further highlights the responsibility of mTOR signaling for non-response to Sunitinib. Immune landscape characterization reveals diverse tumor microenvironment subsets in ccRCC. Finally, we construct a multi-omics classifier that can detect responder and non-responder patients (receiver operating characteristic–area under the curve, 0.98). Our study highlights associations between ccRCC molecular characteristics and the response to TKI, which can facilitate future improvement of therapeutic responses.

Abstract Implanted bioelectronic devices can form distributed networks capable of sensing health conditions and delivering therapy throughout the body. Current clinically-used approaches for wireless communication, however, do not support direct networking between implants because of signal losses from absorption and reflection by the body. As a result, existing examples of such networks rely on an external relay device that needs to be periodically recharged and constitutes a single point of failure. Here, we demonstrate direct implant-to-implant wireless networking at the scale of the human body using metamaterial textiles. The textiles facilitate non-radiative propagation of radio-frequency signals along the surface of the body, passively amplifying the received signal strength by more than three orders of magnitude (>30 dB) compared to without the textile. Using a porcine model, we demonstrate closed-loop control of the heart rate by wirelessly networking a loop recorder and a vagus nerve stimulator at more than 40 cm distance. Our work establishes a wireless technology to directly network body-integrated devices for precise and adaptive bioelectronic therapies.

Abstract Tertiary lymphoid structures (TLS) are organized aggregates of immune cells that form under pathological conditions. However, the predictive value of TLS in clear cell renal cell carcinoma (ccRCC) for immunotherapies remains unclear. We comprehensively assessed the implications for prognosis and immunological responses of the TLS spatial and maturation heterogeneity in 655 ccRCC patients. A higher proportion of early‐TLS was found in peritumoral TLS, while intratumoral TLS mainly comprised secondary follicle‐like TLS (SFL‐TLS), indicating markedly better survival. Notably, presence of TLS, especially intratumoral TLS and SFL‐TLS, significantly correlated with better survival and objective reflection rate for ccRCC patients receiving anti‐Programmed Cell Death Protein‐1 (PD‐1)/Programmed Cell Death‐Ligand‐1 (PD‐L1) immunotherapies. In peritumoral TLS cluster, primary follicle‐like TLS, the proportion of tumor‐associated macrophages, and Treg infiltration in the peritumoral regions increased prominently, suggesting an immunosuppressive tumor microenvironment. Interestingly, spatial transcriptome annotation and multispectral fluorescence showed that an abundance of mature plasma cells within mature TLS has the capacity to produce IgA and IgG, which demonstrate significantly higher objective response rates and a superior prognosis for ccRCC patients subjected to immunotherapy. In conclusion, this study revealed the implications of TLS spatial and maturation heterogeneity on the immunological status and clinical responses, allowing the improvement of precise immunotherapies of ccRCC.

Background Tertiary lymphoid structures (TLS) are organized aggregates of immune cells that develop postnatally in non-lymphoid tissues and are associated with pathological conditions. TLS typically comprise B-cell follicles containing and are encompassed by T- cell zones and dendritic cells. The prognostic and predictive value of TLS in the tumor microenvironment (TME) as potential mediators of antitumor immunity have gained interest. However, the precise relationship between localization and maturation of TLS and the clinical outcome of their presence in clear cell renal cell carcinoma (ccRCC) is yet to be elucidated.Methods Immunohistochemistry and multispectral fluorescence were used to evaluate the TLS heterogeneity along with TME cell-infiltrating characterizations. A thorough investigation of the prognostic implications of the TLS heterogeneity in 395 patients with ccRCC from two independent cohorts was conducted. Associations between TLS heterogeneity and immunologic activity were assessed by quantifying the immune cell infiltration.Results Infiltrated TLS were identified in 34.2% of the ccRCC samples (N=395). These TLS were found to be tumor-proximal, tumor-distal, or both in 37.8%, 74.1%, and 11.9% of the TLS-positive cases, respectively. A higher proportion of early TLS was found in tumor-distal TLS (p=0.016), while tumor-proximal TLS primarily comprised secondary follicle-like structures (p=0.004). In the main study cohort (Fudan University Shanghai Cancer Center, N=290), Kaplan-Meier analyses revealed a significant correlation between the presence of tumor-proximal TLS and improved progression-free survival (PFS, p0.80). Additionally, ccRCC samples with tumor-distal TLS enriched with primary follicle-like TLS exhibited higher programmed death-ligand 1 tumor-associated macrophages levels and regulatory T cells infiltration in the tumor-distal region, indicative of a suppressive TME.Conclusion This study for the first time elucidates the impact of TLS localization and maturation heterogeneities on the divergent clinical outcomes of ccRCC. The findings reveal that most TLS in ccRCC are located in the tumor-distal area and are associated with immature, immunosuppressive characterizations. Furthermore, our findings corroborate previous research demonstrating that tumor-proximal TLS were associated with favorable clinical outcomes.

Abstract Kidney, bladder, and prostate cancer are the three major tumor types of the urologic system that seriously threaten human health. Circular RNAs (CircRNAs), special non-coding RNAs with a stabile structure and a unique back-splicing loop-forming ability, have received recent scientific attention. CircRNAs are widely distributed within the body, with important biologic functions such as sponges for microRNAs, as RNA binding proteins, and as templates for regulation of transcription and protein translation. The abnormal expression of circRNAs in vivo is significantly associated with the development of urologic tumors. CircRNAs have now emerged as potential biomarkers for the diagnosis and prognosis of urologic tumors, as well as targets for the development of new therapies. Although we have gained a better understanding of circRNA, there are still many questions to be answered. In this review, we summarize the properties of circRNAs and detail their function, focusing on the effects of circRNA on proliferation, metastasis, apoptosis, metabolism, and drug resistance in kidney, bladder, and prostate cancers.

Abstract Background Papillary renal cell carcinoma (PRCC) can be divided into type 1 (PRCC1) and type 2 (PRCC2) and PRCC2 share a more invasive phenotype and worse prognosis. This study aims to identify potential prognostic and therapeutic biomarkers in PRCC2. Methods A cohort from The Cancer Genome Atlas and two datasets from Gene Expression Omnibus were examined. Common differentially expressed genes (DEGs) were screened and potential biomarkers were explored by using Kaplan–Meier method and cox regression analysis. Functional enrichment analysis was utilized to evaluate the potential biological functions. Tumor infiltrating immune cells were estimated by CIBERSORT algorithm. Ninety-two PRCC2 samples from Fudan University Shanghai Cancer Center were obtained, and immunostaining was performed to validate prognostic and therapeutic significance of the potential biomarker. Results PRCC2 has worse overall survival and shares distinct molecular characteristics from PRCC1. There was significant higher expression level of Targeting protein for Xklp2 (TPX2) in PRCC2 compared with normal tissues. Higher expression level of TPX2 was significantly associated with worse overall survival in PRCC2 and kinesin family genes expression were found significantly elevated in high risk PRCC2. Abundance of tumor infiltrating M1 macrophage was significantly higher in PRCC2 and it was also associated with worse overall survival. In the FUSCC cohort, higher TPX2 expression was significantly correlated with worse overall and progression-free survival. Retrospective analysis indicated that mTOR inhibitor (everolimus) had greater efficacy in the high-risk group than in the low-risk group (overall response rate: 28.6% vs. 16.7%) and that everolimus had greater efficacy than sunitinib in the high-risk group (overall response rate: 28.6% vs. 20%). Conclusions TPX2 was a prognostic and therapeutic biomarker in PRCC2. Higher abundance of tumor infiltrating M1 macrophage was significantly associated with worse overall survival in PRCC2. mTOR inhibitors may have good efficacy in patients with high-risk PRCC2.

This paper presents a holistic and authoritative review of the role of microwave technologies in enabling a new generation of wearable devices. A human-centric Internet of Things (IoT) covering remote healthcare, distributed sensing, and consumer electronics, calls for high-performance wearable devices integrated into clothing, which require interdisciplinary research efforts to emerge. Microwaves, the “interconnect” of wireless networks, can enable, rather than solely connect, the next generation of autonomous, sustainable, and wearable-friendly electronics. First, enabling technologies including wireless power transmission and RF energy harvesting, backscattering and passive communication, RFID, and electromagnetic sensing are reviewed. We then discuss the key integration platforms, covering smart fabrics and electronic textiles, additive manufacturing, printed electronics, natively-flexible and organic RF semiconductors, and fully-integrated CMOS systems, where opportunities for hybrid integration are highlighted. The emerging research trends, from mmWave 6G, RF sensing and imaging, to healthcare applications including neural implants, drug delivery, and safety upon exposure to microwaves are re-visited and discussed, presenting a future roadmap for interdisciplinary research towards sustainable and reliable next-generation wearables.

The molecular landscape of microphthalmia transcription factor family translocation renal cell carcinoma tumours remain to be characterised. Here, the authors perform proteogenomic analysis and reveal dysregulation of DNA repair, mTOR signalling and metabolic processes.

Background There is scant data on the association of the Pulsed wave-Doppler tissue imaging (PW-DTI)-derived tricuspid lateral annular peak systolic velocity (S’) and poor short-term prognosis of patients with acute decompensated heart failure (ADHF).Patients and methods A total number of 732 participants from the Heb-ADHF registry in China were divided into three groups according to the corresponding status of tricuspid S′. Demographic characteristics, comorbidities, physical examinations, lab tests, and medications were compared among the different groups. Different logistic regression models were utilized to gauge the relationship between S′ and the risk of a composite of short-term all-cause mortality or 30-day heart failure (HF)-related rehospitalization.Results The number of composite outcome events identified in the study population was 85, with the short-term all-cause death coupled with 30-day HF readmission events reaching 23 and 62, respectively. As per the multivariable adjusted analysis, S′ was inversely related to the risk of a composite outcome [11 cm/s. When S′ was analysed as a continuous variable, per 1 cm/s increase, the OR (95% CI) for a composite outcome was [0.87 (0.77–0.99), p = 0.028]. Area under curve (AUC) of S′ for predicting outcome of ADHF was 0.631 (95%CI: 0.573–0.690, p

Objective This study aims to identify potential prognostic and therapeutic biomarkers in papillary renal cell carcinoma (pRCC). Methods Two microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified. The protein-protein interaction (PPI) networks and functional annotations of DEGs were established. Survival analysis was utilized to evaluate the prognostic significance of the DEGs and the association between the expression level of candidate biomarkers and various tumour-infiltrating immune cells was explored. The role of PTTG1 in tumour microenvironments (TME) was further explored using Single-cell RNA-seq and its prognostic and therapeutic significance was validated in Fudan University Shanghai Cancer Centre (FUSCC) cohort. Results Eight genes, including BUB1B, CCNB1, CCNB2, MAD2L1, TTK, CDC20, PTTG1, and MCM were found to be negatively associated with patients’ prognosis. The expression level of PTTG1 was found to be significantly associated with lymphocytes, immunomodulators, and chemokine in the TCGA cohort. Single-cell RNA-seq information indicated that PTTG1 was strongly associated with the proliferation of T cells. In the FUSCC cohort, the expression level of PTTG1 was also statistically significant for both progression-free survival (PFS) and overall survival (OS) prediction (HR = 2.683, p

The viability of Zea mays seed plays a critical role in determining the yield of corn. Therefore, developing a fast and non-destructive method is essential for rapid and large-scale seed viability detection and is of great significance for agriculture, breeding, and germplasm preservation. In this study, hyperspectral imaging (HSI) technology was used to obtain images and spectral information of maize seeds with different aging stages. To reduce data input and improve model detection speed while obtaining more stable prediction results, successive projections algorithm (SPA) was used to extract key wavelengths that characterize seed viability, then key wavelength images of maize seed were divided into small blocks with 5 pixels ×5 pixels and fed into a multi-scale 3D convolutional neural network (3DCNN) for further optimizing the discrimination possibility of single-seed viability. The final discriminant result of single-seed viability was determined by comprehensively evaluating the result of all small blocks belonging to the same seed with the voting algorithm. The results showed that the multi-scale 3DCNN model achieved an accuracy of 90.67% for the discrimination of single-seed viability on the test set. Furthermore, an effort to reduce labor and avoid the misclassification caused by human subjective factors, a YOLOv7 model and a Mask R-CNN model were constructed respectively for germination judgment and bud length detection in this study, the result showed that mean average precision (mAP) of YOLOv7 model could reach 99.7%, and the determination coefficient of Mask R-CNN model was 0.98. Overall, this study provided a feasible solution for detecting maize seed viability using HSI technology and multi-scale 3DCNN, which was crucial for large-scale screening of viable seeds. This study provided theoretical support for improving planting quality and crop yield.

Abstract Background To identify the malignant potential and prognostic indicators of renal epithelioid angiomyolipoma (eAML), clinicopathological and molecular features as well as the drug efficacy of 67 eAML cases were analyzed. Materials and methods Sixty-seven renal eAML patients were enrolled and the immunohistochemical features of these patients were examined. FFPE slides of all patients were re-examined. 21 patients with metastasis received Everolimus 10 mg orally once daily. Responses were evaluated with RECIST criteria by three authors. A risk stratification model was constructed using the following factors: pT3 and pT4, presence of necrosis, mitotic count ≥ 2; the presence of atypical mitoses; severe nuclear atypia, SMA negative, Ki-67 ≥ 10%. Results The average percentage of the epithelioid component was 85.6% (range 80–95%). Immunohistochemically, Ki-67 ≥ 10% and negative SMA staining were significantly correlated with malignant characteristics (Ki-67: p

Background: The genomic background affects the occurrence and metastasis of cancers, including clear cell renal cell carcinoma (ccRCC). However, reports focusing on the prognostic mutational signature of Chinese ccRCC are lacking. Methods: Overall, 929 patients, including a training cohort with Chinese patients (n = 201), a testing cohort with Caucasian patients (n = 274), and a validation cohort (n = 454) were analyzed for the genomic landscape of ccRCC. Then, machine-learning algorithms were used to identify and evaluate the genomic mutational signature (GMS) in ccRCC. Analyses for prognosis, immune microenvironment, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies (ICTs) were performed. Results: The DNA variation data of 929 patients with ccRCC suggested markedly differential genomic mutational frequency of the most frequent genes, such as VHL, PBRM1, BAP1, SETD2, and KDM5C between the Chinese and Caucasian populations. PBRM1 showed significant co-occurrence with VHL and SETD2. We then successfully identified a seven-gene mutational signature (GMSMut) that included mutations in FBN1, SHPRH, CELSR1, COL6A6, DST, ABCA13, and BAP1. The GMSMut significantly predicted progressive progression (P < 0.0001, HR = 2.81) and poor prognosis (P < 0.0001, HR = 3.89) in the Chinese training cohort. Moreover, ccRCC patients with the GMSMut had poor survival rates in the testing cohort (P = 0.020) and poor outcomes were predicted for those treated with ICTs in the validation cohort (P = 0.036). Interestingly, a favorable clinical response to ICTs, elevated expression of immune checkpoints, and increased abundance of tumor-infiltrated lymphocytes, specifically CD8+ T cells, Tregs, and macrophages, were observed in the GMSMut cluster. Conclusions: This study described the pro-tumorigenic GMSMut cluster that improved the prognostic accuracy in Chinese patients with ccRCC. Our discovery of the novel independent prognostic signature highlights the relationship between tumor phenotype and genomic mutational characteristics of ccRCC.

Abstract Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant genitourinary cancers with high recurrence risk worldwide. Recently, multi-omics data facilitate obtaining a molecular landscape of tumor development, and were implemented to affect pathogenesis, phenotype, and prognosis of ccRCC. In this study, after screening for differential expressed microRNAs based on multiply datasets, we tested expression levels and prognostic value of miR-187-3p in ccRCC samples, and transfected miR-187-3p mimics or negative controls into ccRCC cells. Up-regulation of miR-187-3p restrains proliferation, migration and promotes apoptosis ability in human ccRCC A498 and 786O cells. In addition, Luciferase reporter assay revealed that miR-187-3p directly targets LRFN1-3’-UTR and negatively modulates LRFN1 expression. LRFN1 rescues proliferation and invasion capacities after miR-187-3p mimic transfection in vitro and in subcutaneous xenograft models. We further performed deep-sequencing technology and bioinformatics analyses to evaluate the biological functions and potential clinical implications of LRFN1 expression in ccRCC. Interestingly, LRFN1 could serve as an independent and potential biomarker for prognosis in over 1000 patients with ccRCC from multiply independent cohorts. Besides, the up-regulated LRFN1 expression prominently promoted intra-tumoral heterogeneity and immune-infiltrating microenvironment, represented by elevated M2 macrophage infiltration, CD8+ T cells activity and PD-L1 expression. In conclusion, this study revealed the tumor-specific and immunological role of miR-187-3p/LRFN1 axis in the progression and reshaping of tumor immune microenvironment of ccRCC.

Hitherto, the intelligent detection of black tea fermentation quality is still a thought-provoking problem because of one-side sample information and poor model performance. This study proposed a novel method for the prediction of major chemical components including total catechins, soluble sugar and caffeine using hyperspectral imaging technology and electrical properties. The multielement fusion information were used to establish quantitative prediction models. The performance of model using multielement fusion information was better than that of model using single information. Subsequently, the stacking combination model using fusion data combined with feature selection algorithms for evaluating the fermentation quality of black tea. Our proposed strategy achieved better performance than classical linear and nonlinear algorithms, with the correlation coefficient of the prediction set (Rp) for total catechins, soluble sugar and caffeine being 0.9978, 0.9973 and 0.9560, respectively. The results demonstrated that our proposed strategy could effectively evaluate the fermentation quality of black tea.

The rapid and intelligent evaluation of black tea taste quality during the fermentation process is an unsolved problem because of the complexity and hysteretic of the current taste evaluation method. Common infrared spectroscopy and machine vision technologies can rapidly evaluate the taste quality of black tea, but they can not obtain comprehensive sample information. To obtain comprehensive sample information and achieve the rapid evaluation of the taste quality of black tea, the fusion data from hyperspectral images of fermentation samples were applied to predict the taste quality. The successive projection algorithm (SPA) and ant colony optimization (ACO) were used to select effective bands for spectral data. Subsequently, the color images were synthesized using three carefully selected effective bands obtained through the SPA and ACO. The 18 image features were extracted from each synthesized color image and fused with spectral effective bands. The fusion data and three different algorithms, such as partial least squares regression (PLSR), support vector machine regression (SVR), and extreme learning machine (ELM), were employed to establish the regression model for taste quality. Specifically, the fusion-SPA-PLSR model exhibited the best performance. This study provides a novel method for the intelligent evaluation of taste quality during black tea fermentation and lays a theoretical foundation for the intelligent processing and control of black tea.

Transporter associated with antigen processing 1(TAP1) serves as a protein to transport antigenic peptides from the surface of the endoplasmic reticulum to the lumen of the endoplasmic reticulum when the antigens are presented by major histocompatibility complex type I (MHC-I), which has been identified to play a critical role in antigen presentation in innate immunity. In tumors, the role of TAP1 seems to remain controversial. On the one hand, given the role of TAP1 in antigen presentation, it is indicated that high TAP1 expression corresponds to the emergence of more neoantigens epitopes that facilitate the recognition for phagocytes, T cells and other cells. On the other hand, the genetic ablation of transporter associated with antigen processing (TAP) results in the presentation of new class I-restricted epitopes encoded in house-keeping products. Opposite result has been revealed by studies in other tumors suggest, which implies a more complex function of TAP1. Therefore, it’s significant to clarify the role of TAP1 in clear cell renal cell carcinoma (ccRCC). In this study, we found the elevated expression levels in mRNA and protein of TAP1 in ccRCC tissues, which indicated a relatively worse prognosis. Transwell assay and Scratch assay in vitro demonstrated the promotive role of TAP1 in ccRCC migration as well as a significant role in metastasis. And the increased expression of TAP1 resulted in more immune cells infiltrated in cancer tissues. TAP1 was also demonstrated to be related to immune regulator genes, as gene set enrichment analysis (GSEA) indicated its significant role in immune regulation. The results of CancerSEA indicated the positive association of the high-level TAP1 expression with epithelial–mesenchymal transition (EMT) and the inverse association with Cell Cycle. The effective drugs were also predicted based on TAP1 expression, of which the high level was indeed associated with resistance to multiple drugs, but some effective drugs still identified based on high TAP1 expression. According to the analysis of various databases, the role of TAP1 in ccRCC was explored, especially in relationship of TAP1 with tumor microenvironment. These results indicate that TAP1 can serve as a potential target for treatment of ccRCC.

BackgroundRenal cancer is one of the most lethal cancers because of its atypical symptoms and metastatic potential. The metabolism of amino acids and their derivatives is essential for cancer cell survival and proliferation. Thus, the construction of the amino acid metabolism-related risk signature might enhance the accuracy of the prognostic model and shed light on the treatments of renal cancers.MethodsRNA expression and clinical data were downloaded from Santa Cruz (UCSC) Xena, GEO, and ArrayExpress databases. The “DESeq2” package identified the differentially expressed genes. Univariate COX analysis selected prognostic genes related to the metabolism of amino acids. Patients were divided into two clusters using the “ConsensusClusterPlus” package, and the CIBERSORT, ESTIMATE methods were explored to assess the immune infiltrations. The LASSO regression analysis constructed a risk model which was evaluated the prediction accuracy in two independent cohorts. The genomic alterations and drug sensitivity of 18-LASSO-genes were assessed. The differentially expressed genes between two clusters were used to perform functional enrichment analysis and weighted gene co-expression network analysis (WGCNA). Furthermore, external validation of TMEM72 expression was conducted in the FUSCC cohort containing 33 ccRCC patients.ResultsThe amino acid metabolism-related genes had significant correlations with prognosis. The patients in Cluster A demonstrated better survival, lower Treg cell proportion, higher ESTIMATE scores, and higher cuproptosis-related gene expressions. Amino acid metabolism-related genes with prognostic values were used to construct a risk model and patients in the low risk group were associated with improved outcomes. The Area Under Curve of the risk model was 0.801, 0.777, and 0.767 at the first, second, and third year respectively. The external validation cohort confirmed the stable prognostic value of the risk model. WGCNA identified four gene modules correlated with immune cell infiltrations and cuproptosis. We found that TMEM72 was downregulated in tumors by using TCGA, GEO datasets (p

Measurement(s) environmental pressure Technology Type(s) digital curation Sample Characteristic - Location China Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.15656622

Slight crack of cottonseed is a critical factor influencing the germination rate of cotton due to foamed acid or water entering cottonseed through testa. However, it is very difficult to detect cottonseed with slight crack using common non-destructive detection methods, such as machine vision, optical spectroscopy, and thermal imaging, because slight crack has little effect on morphology, chemical substances or temperature. By contrast, the acoustic method shows a sensitivity to fine structure defects and demonstrates potential application in seed detection. This paper presents a novel method to detect slightly cracked cottonseed using air-coupled ultrasound with a light-weight vision transformer (ViT) and a sound-to-image encoding method. The echo signal of air-coupled ultrasound from cottonseed is obtained by non-contact and non-destructive methods. The intrinsic mode functions (IMFs) of ultrasound signal are obtained as the sound features using variational mode decomposition (VMD) approach. Then the sound features are converted into colorful images by a color encoding method. This method uses different colored lines to represent the changes of different values of IMFs according to the specified encoding period. A light-weight MobileViT method is utilized to identify the slightly cracked cottonseeds using encoding colorful images corresponding to cottonseeds. The experimental results show an average overall recognition accuracy of 90.7% for slightly cracked cottonseed from normal cottonseed, which indicates that the proposed method is reliable to applications in detection task of cottonseed with slight crack.

Sarcomatoid differentiation is a highly aggressive pathological characteristic of renal cell carcinoma (RCC) and is characterized by susceptibility to progression and extremely poor prognosis. In this study, we included all genomic alteration events that led to a loss of protein function of MTAP and CDKN2A, and enrolled 5,307 RCC patients with genomic sequencing data from Western and Chinese cohorts. Notably, MTAP/CDKN2AMUT occurred in the Chinese population ~2 times more frequently than in the Western cohort and showed significant co-mutation trends. We found significantly higher proportions of sarcomatoid-positive patients with MTAPMUT or CDKN2AMUT compared with MTAP/CDKN2A wild-type (WT) patients (P

Bladder cancer is one of the most common genitourinary malignant cancers worldwide. Cell death processes, including apoptosis, ferroptosis, and necrosis, provide novel clinical and immunological insights promoting the management of precision medicine. Therefore, this study aimed to evaluate the transcriptomic profile of signatures in cell death pathways with significant prognostic implications in patients with bladder cancer from multiple independent cohorts (n = 1999). First, genes involved in apoptosis (n = 19), ferroptosis (n = 31), and necrosis (n = 6) were analyzed to evaluate the prognostic implications in bladder cancer. Significant genes were included to establish the cell-death index (CDI) of 36 genes that distinguished patients according to high and low risks. Survival analysis using the Kaplan-Meier curves clustered patients based on overall survival (18.8 vs. 96.7 months; hazard model [HR] = 3.12, P

While electromagnetic forming of aluminum alloy sheet has gained several advantages, the uneven radial deformation of the sheet is still one of the main drawback of this technology that calls for reliable and cost-effective solution. Aiming at this point, this paper presents an electromagnetic bulging system equipped with a new magnetic field shaper placed between the driving coil and the object sheet to modulate the distribution of the induced eddy current in the sheet, and hence regulating the distribution of the electromagnetic force to achieve more uniform deformation. A finite element electromagnetic-structure 2D coupling model simulating this process is developed and the effects of workpiece geometry and deformation speed on the circuit, magnetic field and structure field are considered. The coupling between the electric circuit and magnetic field; magnetic field and workpiece deformation is realized to simulate the actual system of thin plate electromagnetic bulging. The performance of the proposed system is compared with that of the traditional system through investigating the profiles of the induced eddy current, electromagnetic force and forming effect. Simulation results show that the uniformity of sheet metal forming is improved by using the proposed magnetic field shaper, and the maximum uniform deformation area is increasing from 32.1 mm to 73.8 mm, which stimulates more industrial applications of sheet metal electromagnetic forming.

AbstractPurpose This study aims to identify potential prognostic biomarkers of bladder cancer (BCa) based on large-scale multi-omics data and investigate the role of SRC in improving predictive outcomes for BCa patients and those receiving immune checkpoint therapies (ICTs).Methods Large-scale multi-comic data were enrolled from the Cancer Proteome Atlas, the Cancer Genome Atlas and gene expression omnibus based on machining-learning methods. Immune infiltration, survival and other statistical analyses were implemented using R software in cancers (n = 12,452). The predictive value of SRC was performed in 81 BCa patients receiving ICT from aa validation cohort (n = 81).Results Landscape of novel candidate prognostic protein signatures of BCa patients was identified. Differential BECLIN, EGFR, PKCALPHA, ANNEXIN1, AXL and SRC expression significantly correlated with the outcomes for BCa patients from multiply cohorts (n = 906). Notably, risk score of the integrated prognosis-related proteins (IPRPs) model exhibited high diagnostic accuracy and consistent predictive ability (AUC = 0.714). Besides, we tested the clinical relevance of baseline SRC protein and mRNA expression in two independent confirmatory cohorts (n = 566) and the prognostic value in pan-cancers. Then, we found that elevated SRC expression contributed to immunosuppressive microenvironment mediated by immune checkpoint molecules of BCa and other cancers. Next, we validated SRC expression as a potential biomarker in predicting response to ICT in 81 BCa patient from FUSCC cohort, and found that expression of SRC in the baseline tumour tissues correlated with improved survival benefits, but predicts worse ICT response.Conclusion This study first performed the large-scale multi-omics analysis, distinguished the IPRPs (BECLIN, EGFR, PKCALPHA, SRC, ANNEXIN1 and AXL) and revealed novel prediction model, outperforming the currently traditional prognostic indicators for anticipating BCa progression and better clinical strategies. Additionally, this study provided insight into the importance of biomarker SRC for better prognosis, which may inversely improve predictive outcomes for patients receiving ICT and enable patient selection for future clinical treatment.

The aged seeds have a significant influence on seed vigor and corn growth. Therefore, it is vital for the planting industry to identify aged seeds. In this study, hyperspectral reflectance imaging (1,000–2,000 nm) was employed for identifying aged maize seeds using seeds harvested in different years. The average spectra of the embryo side, endosperm side, and both sides were extracted. The support vector machine (SVM) algorithm was used to develop classification models based on full spectra to evaluate the potential of hyperspectral imaging for maize seed detection and using the principal component analysis (PCA) and ANOVA to reduce data dimensionality and extract feature wavelengths. The classification models achieved perfect performance using full spectra with an accuracy of 100% for the prediction set. The performance of models established with the first three principal components was similar to full spectrum models, but that of PCA loading models was worse. Compared to other spectra, the two-band ratio (1,987 nm/1,079 nm) selected by ANOVA from embryo-side spectra achieved a better classification accuracy of 95% for the prediction set. The image texture features, including histogram statistics (HS) and gray-level co-occurrence matrix (GLCM), were extracted from the two-band ratio image to establish fusion models. The results demonstrated that the two-band ratio selected from embryo-side spectra combined with image texture features achieved the classification of maize seeds harvested in different years with an accuracy of 97.5% for the prediction set. The overall results indicated that combining the two wavelengths with image texture features could detect aged maize seeds effectively. The proposed method was conducive to the development of multi-spectral detection equipment.

Nondestructive determination the internal quality of thick-skin fruits has always been a challenge. In order to investigate the prediction ability of full transmittance mode on the soluble solid content (SSC) in thick-skin fruits, the full transmittance spectra of citrus were collected using a visible/near infrared (Vis/NIR) portable spectrograph (550–1100 nm). Three obvious absorption peaks were found at 710, 810 and 915 nm in the original spectra curve. Four spectral preprocessing methods including Smoothing, multiplicative scatter correction (MSC), standard normal variate (SNV) and first derivative were employed to improve the quality of the original spectra. Subsequently, the effective wavelengths of SSC were selected from the original and pretreated spectra with the algorithms of successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS) and genetic algorithm (GA). Finally, the prediction models of SSC were established based on the full wavelengths and effective wavelengths. Results showed that SPA performed the best performance on eliminating the useless information variable and optimizing the number of effective variables. The optimal prediction model was established based on 10 characteristic variables selected from the spectra pretreated by SNV with the algorithm of SPA, with the correlation coefficient, root mean square error, and residual predictive deviation for prediction set being 0.9165, 0.5684°Brix and 2.5120, respectively. Overall, the full transmittance mode was feasible to predict the internal quality of thick-skin fruits, like citrus. Additionally, the combination of spectral preprocessing with a variable selection algorithm was effective for developing the reliable prediction model. The conclusions of this study also provide an alternative method for fast and real-time detection of the internal quality of thick-skin fruits using Vis/NIR spectroscopy.

Seed vigor is one of the essential contents of agricultural research. The decline of seed vigor is described as an inevitable process. Recent studies have shown that the oxidative damage caused by reactive oxygen species (ROS) is the main reason for the destruction of various chemicals in seeds and eventually evolves into seed death. The traditional vigor tests, such as the seed germination test and TTC staining, are commonly used to assess seed vigor. However, these methods often need a large number of experimental samples, which will bring a waste of seed resources. At present, many new methods that are fast and nondestructive to seeds, such as vibrational spectroscopic techniques, have been used to test seed vigor and have achieved convincing results. This paper is aimed at analyzing the microchanges of seed-vigor decline, summarizing the performance of current seed-vigor test methods, and hoping to provide a new idea for the nondestructive testing of a single seed vigor by combining the physiological alterations of seeds with chemometrics algorithms.

Background: The tumor microenvironment affects the occurrence and development of cancers, including clear cell renal cell carcinoma (ccRCC). However, how the immune contexture interacts with the cancer phenotype remains unclear.Methods: We identified and evaluated immunophenotyping clusters in ccRCC using machine-learning algorithms. Analyses for functional enrichment, DNA variation, immune cell distribution, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies were performed and validated.Results: Three immunophenotyping clusters with gradual levels of immune infiltration were identified. The intermediate and high immune infiltration clusters (Clusters B and C) were associated with a worse prognosis for ccRCC patients. Tumors in the immune-hot Clusters B and C showed pro-tumorigenic immune infiltration, and these patients showed significantly worse survival compared with patients in the immune-cold Cluster A in the training and testing cohorts (n = 422). In addition to distinct immune cell infiltrations of immunophenotyping, we detected significant differences in DNA variation among clusters, suggesting a high degree of genetic heterogeneity. Furthermore, expressions of multiple immune checkpoint molecules were significantly increased. Clusters B and C predicted favorable outcomes in 64 ccRCC patients receiving immune checkpoint therapies from the FUSCC cohort. In 360 ccRCC patients from the FUSCC validation cohort, Clusters B and C significantly predicted worse prognosis compared with Cluster A. After immunophenotyping of ccRCC was confirmed, significantly increased tertiary lymphatic structures, aggressive phenotype, elevated glycolysis and PD-L1 expression, higher abundance of CD8+ T cells, and TCRn cell infiltration were found in the immune-hot Clusters B and C.Conclusion: This study described immunophenotyping clusters that improved the prognostic accuracy of the immune contexture in the ccRCC microenvironment. Our discovery of the novel independent prognostic indicators in ccRCC highlights the relationship between tumor phenotype and immune microenvironment.

The tumor microenvironment (TME) affects the biologic malignancy of clear cell renal cell carcinoma (ccRCC). The influence of the 5-methylcytosine (m5C) epigenetic modification on the TME is unknown. We comprehensively assessed m5C modification patterns of 860 ccRCC samples (training, testing, and real-world validation cohorts) based on 17 m5C regulators and systematically integrated the modification patterns with TME cell-infiltrating characterizations. Our results identified distinct m5C modification clusters with gradual levels of immune cell infiltration. The distinct m5C modification patterns differ in clinicopathological features, genetic heterogeneity, patient prognosis, and treatment responses of ccRCC. An elevated m5C score, characterized by malignant biologic processes of tumor cells and suppression of immunity response, implies an immune-desert TME phenotype and is associated with dismal prognosis of ccRCC. Activation of exhausted T cells and effective immune infiltration were observed in the low m5C score cluster, reflecting a noninflamed and immune-excluded TME phenotype with favorable survival and better responses to immunotherapy. Together, these findings provide insights into the regulation mechanisms of DNA m5C methylation modification patterns on the tumor immune microenvironment. Comprehensive assessment of tumor m5C modification patterns may enhance our understanding of TME cell-infiltrating characterizations and help establish precision immunotherapy strategies for individual ccRCC patients.

Interferon-gamma (IFN-γ) has a complex role in modulating the tumor microenvironment (TME) during renal cell carcinoma (RCC) development. To define the role of IFN-γ response genes in RCC progression, we characterized the differential gene expression, prognostic implications, and DNA variation profiles of selected IFN-γ response signatures, which exhibited a significant hazard ratio for the overall survival (OS) and progression-free survival (PFS) of papillary, chromophobia, and clear cell RCC (ccRCC) patients (n = 944). Prognostic nomograms were constructed to predict the outcomes for ccRCC patients, highlighting the prognostic implications of RANBP2-type and C3HC4-type zinc finger containing 1 (RBCK1). Interestingly, large-scale pan-cancer samples (n = 12,521) and three single-cell RNA datasets revealed that RBCK1 showed markedly differential expression between cancer and normal tissues and significantly correlated with tumor-infiltrating immune cells, tumor purity, and immune checkpoint molecules, such as PD-L1, CTLA-4, LAG-3, and TIGIT in pan-cancer samples. Notably, the TIDE score was significantly higher in the RBCK1high group compared with the RBCK1low group in both ccRCC and RCC cohorts. Besides, immunohistochemistry staining showed significantly elevated RBCK1 expression in tumors (n = 50) compared with kidney samples (n = 40) from a real-world cohort, Fudan University Shanghai Cancer Center (FUSCC, Shanghai). After RBCK1 expression was confirmed in ccRCC, we found a significantly decreased number of infiltrating CD4+ T cells, CD4+ FOXP3+ Treg cells, M1 macrophages, and CD56bight/dim NK cells in the immune-cold RBCK1high group. In addition to the distinct heterogeneous immune microenvironment, the increased expression of RBCK1 predicted a prominently worse prognosis than the RBCK1low group for 232 ccRCC patients in the FUSCC proteomic cohort. Furthermore, after transfected with siRNA in human ccRCC cells, extraordinarily decreased cell proliferation, migration capacities, and prominently elevated apoptosis tumor cell proportion were found in the siRNA groups compared with the negative control group. In conclusion, this study identified IFN-γ response clusters, which might be used to improve the prognostic accuracy of immune contexture in the ccRCC microenvironment. Immune-cold RBCK1high patients have pro-tumorigenic immune infiltration and significantly worse outcomes than RBCK1low patients based on results from multi-omics to real-world data. Our discovery of novel independent prognostic indicators for RCC highlights the association between tumor alterations and immune phenotype.

BackgroundThis study aims to establish an N6-methyladenosine (m6A) RNA methylation regulators-mediated methylation model and explore its role in predicting prognostic accuracy of immune contexture and characterizations of clear cell renal cell carcinoma (ccRCC).MethodsThe m6A modification subclasses (m6AMS) were identified by unsupervised cluster analysis and three clusters were determined by consensus clustering algorithm in a discovering cohort. Testing and real-world validation cohorts were used to identify predictive responses for immune checkpoint therapies (ICTs) of m6AMS.ResultsPrognostic implications landscape of m6A regulators in cancers and its differential expression levels in ccRCC patients were identified. Based on discovering cohort, ccRCC were automatically divided into three m6AMS, and cluster 3 showed significant worse survival than cluster 1/2. Importantly, it was found that the immune checkpoint molecules expression was significantly elevated in cluster 3. Besides, m6A scoreLow group (cluster 1&2) have significantly elevated TIDE score compared with m6A scoreHigh group (cluster 3). There was conspicuous tertiary lymphoid tissue, aggressive phenotype, elevated glycolysis, expression of PD-L1, abundance of CD8+ T cells, CD4+ FOXP3+ Treg cells and TCRn immune cells infiltration in the high m6A score group. Interestingly, there are significantly increased patients with clinical benefit in m6A scoreHigh group in 368 patients receiving ICTs from testing IMvigor210 (n = 292) and validation FUSCC (n = 55) cohorts.ConclusionOur discovery highlights the relationship between tumor epigenetic heterogeneity and immune contexture. Immune-rejection cluster 3 has pro-tumorigenic immune infiltration, and shows significant clinical benefits for ccRCC patients receiving ICTs, enabling patient selection for future clinical treatment.

The basic optical properties of fruit tissues are significant and helpful to be known when they are utilized for internal quality detection. The integrating sphere (IS) system was established to measure diffuse reflectance spectra (R') of peel-flesh layer, absorption coefficient (μα) and reduced scattering coefficient (μ's) of flesh layer of `Ya' pear tissues using inverse adding-doubling (IAD) method in 900-1700 nm. Aiming at studying the relationship between soluble solids content (SSC) and optical properties (μα and μ's), partial least square (PLS) regression was employed to establish calibration models based on three wavelength regions. Results showed that better correlations were found using reflectance and μα spectra than using scattering ones with full wavelengths in 900-1350 nm. Moreover, reflectance spectra (rp = 0.8911, RMSEP = 0.4965 °Brix) with 27 effective wavelength (EWs) and μα spectra (rp = 0.8641, RMSEP = 0.5506 °Brix) with 14 EWs both performed satisfactory results using competitive adaptive reweighted sampling (CARS). Good result (rp = 0.8856, RMSEP = 0.5081 °Brix) could also be found by the combination of reflectance and μα spectra with 38 EWs. Results of independent validation test showed that EWs of μα spectra was more promising in pear SSC prediction even though the model stability was not as good as these obtained by reflectance. Therefore, more research needs to be done to improve the stability and accuracy of the IS system. This study illustrated the availability for multiple index quality attributes detection of fruit tissues by detecting reflectance and optical properties information using IS system.

BackgroundMyasthenia gravis (MG) is the most common paraneoplastic syndromes of thymoma and closely related to thymus abnormalities. Timely detecting of the risk of MG would benefit clinical management and treatment decision for patients with thymoma. Herein, we developed a 3D DenseNet deep learning (DL) model based on preoperative computed tomography (CT) as a non-invasive method to detect MG in thymoma patients.MethodsA large cohort of 230 thymoma patients in a hospital affiliated with a medical school were enrolled. 182 thymoma patients (81 with MG, 101 without MG) were used for training and model building. 48 cases from another hospital were used for external validation. A 3D-DenseNet-DL model and five radiomic models were performed to detect MG in thymoma patients. A comprehensive analysis by integrating machine learning and semantic CT image features, named 3D-DenseNet-DL-based multi-model, was also performed to establish a more effective prediction model.FindingsBy elaborately comparing the prediction efficacy, the 3D-DenseNet-DL effectively identified MG patients and was superior to other five radiomic models, with a mean area under ROC curve (AUC), accuracy, sensitivity, and specificity of 0.734, 0.724, 0.787, and 0.672, respectively. The effectiveness of the 3D-DenseNet-DL-based multi-model was further improved as evidenced by the following metrics: AUC 0.766, accuracy 0.790, sensitivity 0.739, and specificity 0.801. External verification results confirmed the feasibility of this DL-based multi-model with metrics: AUC 0.730, accuracy 0.732, sensitivity 0.700, and specificity 0.690, respectively.InterpretationOur 3D-DenseNet-DL model can effectively detect MG in patients with thymoma based on preoperative CT imaging. This model may serve as a supplement to the conventional diagnostic criteria for identifying thymoma associated MG.

Purpose: Lipid metabolism reprogramming is a major pathway in tumor evolution. This study investigated fatty acid synthase (FASN) mRNA expression in anthropometric adipose tissue and elucidated the prognostic value and potential mechanism of clear cell renal cell carcinoma (ccRCC).Materials and Methods: Transcription profiles were obtained from 533 ccRCC samples in The Cancer Genome Atlas (TCGA) cohorts. Real-time quantitative PCR (RT-qPCR) and immunohistochemistry were performed to detect FASN expression in 380 paired ccRCC and normal tissues from the Fudan University Shanghai Cancer Center (FUSCC). Visceral adipose tissue (VAT) and subcutaneous adipose tissue were at the level of the umbilicus as measured by magnetic resonance imaging (MRI). Non-targeted metabolomics and in vitro experiments were used to reveal the biological functions of FASN.Results: Increased FASN expression was significantly relevant to advanced T, N, and American Joint Committee on Cancer (AJCC) stages (p < 0.01) and significantly correlated to poor progression-free survival (PFS) and overall survival (OS) of 913 ccRCC patients in FUSCC and TCGA cohorts. Pearson's correlation coefficient indicated that FASN amplification was positively correlated to VAT% (r = 0.772, p < 0.001), which significantly correlated to poor PFS (HR = 2.066, p = 0.028) and OS (HR = 2.773, p = 0.023) in the FUSCC cohort. Transient inhibition or overexpression of FASN significantly regulated A498 and 786O cell proliferation and migration by regulating epithelial–mesenchymal transition. Inhibition of FASN led to a higher apoptotic rate and decreased lipid droplet formation compared with normal control in ccRCC cells. Non-targeted metabolomics showed that decreased de novo lipogenesis might be required to sustain an elevation of glycolytic activity in 786O cells by regulating galactinol, dl-lactate, N-acetylaspartylglutamate, and sucrose, thereby participating in carcinogenesis and progression of ccRCC.Conclusion: This study demonstrated that FASN expression is positively related to aggressive cell proliferation, migration, apoptosis, and lipid droplet formation and regulates metabolic disorders of the ccRCC microenvironment. Additionally, elevated FASN mRNA expression is significantly correlated to the abdominal obesity distribution, especially VAT%, which is a significant predictor of a poor prognosis for ccRCC patients.

Maize is susceptible to mold infection during growth and storage due to its large embryo and high moisture content. Therefore, it is essential to distinguish the moldy sample from healthy groups to prevent the spread of mold and avoid huger economic losses. Catalase is a metabolite in the growth of microorganisms; hence, all maize samples were accurately divided into four moldy grades (health, mild, moderate, and severe levels) by determining their catalase activity. The visible and shortwave near-infrared (Vis-SWNIR) and longwave near-infrared (LWNIR) hyperspectral images were investigated to jointly identify the moldy levels of maize. Spectra and texture information of each maize sample were extracted and used to build the classification models of maize with different moldy levels in pixel-level fusion and feature-level fusion. The result showed that the feature-level fusion of spectral and texture within Vis-SWNIR and LWNIR regions achieved the best results, overall prediction accuracy reached 95.00% for each moldy level, all healthy maize was correctly classified, and none of the moldy samples were misclassified as healthy level. This study illustrated that two hyperspectral image systems, with complementary spectral ranges, combined with feature selection and data fusion strategies, could be used synergistically to improve the classification accuracy of maize with different moldy levels.

Electroacupuncture (EA) is widely recognized as clinical treatment of spinal cord injury (SCI). The purpose of this study is to elucidate whether and how the PI3K/AKT/mTOR signaling pathway plays any role in EA treating SCI. Rats were randomly divided into four equal groups: Control Group, Sham-operation Group, Model Group, and EA Group, then further randomly divided into the following subgroups: 1-day (n=12), 1-day rapamycin (n=6), 14-day (n=18), and 28-day (n=18). A rat model of SCI was established by a modified Allen’s weight-drop method. In the EA Group, rats were stimulated on Dazhui (GV14) and Mingmen (GV4) for 20 min by sterilized stainless steel needles. In the EA Group, the Basso, Beattie, and Bresnahan locomotor rating scale showed obvious improved locomotor function, and hematoxylin-eosin staining and magnetic resonance imaging showed that the histological morphology change of injured spinal cord tissue was obviously alleviated. Also, blocking spinal mTOR by injection of rapamycin showed that mTOR existed in the injured spinal cord, and EA could significantly activate mTOR in SCI rats. And immunohistochemistry and western blot analysis on the PI3K/AKT/mTOR signaling pathway showed that levels of PI3K, AKT, mTOR, and p70S6K in the injured spinal cord tissue were greatly increased in the EA Group, while the levels of PTEN and caspase 3 were decreased. The present study suggests that EA could affect cell growth, apoptosis, and autophagy through the PI3K/AKT/mTOR signaling pathway.

Objective The purpose of this study was to explore the composition of tumor-infiltrating immune cells (TIIC) and prognostic significance of tumor-infiltrating mast cells (TIMC) in adrenocortical carcinoma (ACC). Methods The gene expression profiles of ACC were downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GSE90713, GSE12368). The abundance of TIICs in ACC samples was calculated by CIBERSORT algorithm and immunohistochemistry was used to identify mast cells of 39 tumor samples from Fudan University Shanghai Cancer Center (FUSCC). Differentially expressed genes (DEGs) were analyzed by LIMMA package using R software. Survival analysis was analyzed by Kaplan-Meier method and Cox regression models. Results The abundance of mast cells (p = .008) was positively correlated with ACC patients’ outcome in TCGA cohort and was also positively correlated with both overall survival (p

Aflatoxin B1 (AFB1) is a very strong carcinogen, maize kernels are easily infected by this toxin during storage. Rapid and accurate identification of AFB1 is of great significance to ensure food safety. In this study, a novel method for classification of AFB1 in single maize kernels was developed. Four groups of maize kernel samples with different AFB1 concentrations (10, 20, 50, and 100 ppb) were prepared by artificial inoculation of toxin. In addition, one group of maize kernel samples without AFB1 were prepared as control, each group with 70 samples. The visible and short wave near-infrared (Vis-SWNIR) region (500–1000 nm) and long wave near-infrared (LWNIR) region (1000–2000 nm) hyperspectral images of all samples were obtained respectively, and the hyperspectral images in 500–2000 nm range was obtained after spectral pretreatment and fusion. Kennard-Stone algorithm was used to divide the samples into calibration set or prediction set. Competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA) were used to roughly select the characteristic wavelengths of the calibration set samples, and 25 and 26 effective wavelengths were obtained respectively. Based on the roughly selected wavelengths, a method of fine selection of the characteristic wavelengths was proposed by using the gray-value difference of image (GDI), and a few number of characteristic wavelengths were further selected. Under the LDA classification model, 10 characteristic wavelengths were selected to test the prediction set and the independent verification samples, and the ideal result were obtained with an accuracy of 94.46% and 91.11%, respectively. This study provides a new approach for AFB1 concentration classification of single maize kernels.

To reduce food waste, many behavioural intervention experiments have been conducted worldwide, but their effectiveness remains unclear. To assess their impacts, we present a meta-analysis based on 58 studies, selected after screening 1143 papers, which were conducted between 2011 and 2021 covering 26 533 participants. We confirm that behavioural interventions have a moderate effect ( $z$ = 0.22) on food waste reduction, with education programs having the most significant impact and informational feedback having the least. We also show that interventions in elementary and middle school settings marginally improve the overall effect size ( P < 0.1), and controlled experiments exhibit a higher effect size compared to pre-post experiments in education interventions ( P < 0.05). Finally, we present a roadmap to guide future research in the next decade to further improve our understanding on the effects of behavioural interventions to reduce food waste.