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Purpose: This study aims to identify key genes regulating tumor infiltrating plasma cells (PC) and provide new insights for innovative immunotherapy. Methods: Key genes related to PC were identified using machine learning in lung adenocarcinoma (LUAD) patients. A prognostic model called PC scores was developed using TCGA data and validated with GEO cohorts. We assessed the molecular background, immune features, and drug sensitivity of the high PC scores group. Real-time PCR was utilized to assess the expression of hub genes in both localized LUAD patients and LUAD cell lines. Results: We constructed PC scores based on seventeen PC-related hub genes (ELOVL6, MFI2, FURIN, DOK1, ERO1LB, CLEC7A, ZNF431, KIAA1324, NUCB2, TXNDC11, ICAM3, CR2, CLIC6, CARNS1, P2RY13, KLF15, and SLC24A4). Higher age, TNM stage, and PC scores independently predicted shorter overall survival. The AUC value of PC scores for one year, three years, and five years of overall survival were 0.713, 0.716, and 0.690, separately. The nomogram model that integrated age, stage, and PC scores showed significantly higher predictive value than stage alone (P < 0.01). High PC scores group exhibited an immune suppressing microenvironment with lower B, CD8 + T, CD4 + T, and dendritic cell infiltration. Docetaxel, gefitinib, and erlotinib had lower IC50 in high PC groups (P < 0.001). After validation through the local cohort and in vitro experiments, we ultimately confirmed three key potential targets: MFI2, KLF15, and CLEC7A. Conclusion: We proposed a prediction mode which can effectively identify high-risk LUAD patients and found three novel genes closely correlated with PC tumor infiltration. [ABSTRACT FROM AUTHOR]

Background: Artery of Percheron (AOP) as main feeder artery of arteriovenous malformation (AVM) is extremely rare. Two cases of thalamic AVM fed by AOP have been reported to date and only one AVM been removed by microsurgery when attempt of intervention embolization failed. Midbrain AVM fed by AOP has not been reported yet. Case presentation: Here, we presented the first successful embolized case of midbrain AVM supplied by the AOP in a 10-year-old boy, who suffered dual oculomotor nerve palsy and secondary hemorrhage before embolization. During endovascular embolization, selective angiography by 1.2 Fr. Magic microcatheter showed an intranidal aneurysm located on the distal AOP. Two injections of a 1:4 ratio mixture of NBCA-MS completely occlude the nidus and intranidal aneurysm with no complications occurred. The child recovered well and the oculomotor deficits improved. Conclusion: This case highlighted that AOP is a clinically significant branch associated with AVM in midbrain and thalamus. Moreover, intervention embolization of midbrain AVM fed by AOP is a considerable therapeutic strategy. [ABSTRACT FROM AUTHOR]

In this article, an Improved Particle Swarm Optimization (IPSO) is proposed for solving global optimization and hyperparameter optimization. This improvement is proposed to reduce the probability of particles falling into local optimum and alleviate premature convergence and the imbalance between the exploitation and exploration of the Particle Swarm Optimization (PSO). The IPSO benefits from a new search policy named group-based update policy. The initial population of IPSO is grouped by the k-means to form a multisubpopulation, which increases the intragroup learning mechanism of particles and effectively enhances the balance between the exploitation and exploration. The performance of IPSO is evaluated on six representative test functions and one engineering problem. In all experiments, IPSO is compared with PSO and one other state-of-the-art metaheuristics. The results are also analyzed qualitatively and quantitatively. The experimental results show that IPSO is very competitive and often better than other algorithms in the experiments. The results of IPSO on the hyperparameter optimization problem demonstrate its efficiency and robustness. [ABSTRACT FROM AUTHOR]

This paper introduces a new metaheuristic algorithm called bacteria phototaxis optimizer (BPO). It is designed to solving optimization issues. Inspired by the bacteria phototaxis under the control of photosensory proteins in nature, and based on the basic law of bacterial colony growth and evolution, we have designed the photosensory protein concentration, phototaxis motion and growth operators. These three operators exhibit a highly adaptive and information interaction mechanism. The goal is to simulate the phototaxis process of bacteria and form a complete model of BPO. At the same time, BPO is compared with eight most representative as well as newly generated metaheuristics. Its performance is verified by using 23 well-known benchmark functions with three different types. Additionally, we have conducted several evaluation processes, such as qualitative and quantitative analysis as well as parametric and nonparametric tests. Finally, five classical engineering design problems are used to further test the effectiveness of the algorithm in solving constrained problems. The aforementioned experimental results show that compared with other algorithms, BPO has better accuracy, convergence, and robustness and shows strong competitiveness and optimization performance. [ABSTRACT FROM AUTHOR]

Objective: Bone marrow mesenchymal stem cell (BMSC)-derived extracellular vesicles (EVs) have been demonstrated as a potential therapeutic agent in acute kidney injury (AKI). However, little is known about the mechanisms of action of BMSC-derived EVs in AKI. Based on this, our research was designed to investigate the mechanism behind BMSC-derived EVs controlling inflammation and pyroptosis during AKI. Methods: Peripheral blood from AKI patients was used for detection of microRNA (miR)-223-3p, HDAC2, and SNRK expression. An AKI rat model was established, and HK-2 cell injury was induced by lipopolysaccharide (LPS) to establish a cellular model. Co-culture with BMSC-derived EVs and/or gain- and loss-of-function assays were conducted in LPS-treated HK-2 to evaluate the functions of BMSCs-EVs, miR-223-3p, HDAC2, and SNRK. AKI rats were simultaneously injected with EVs and short hairpin RNAs targeting SNRK. The interactions among miR-223-3p, HDAC2, and SNRK were evaluated by RIP, ChIP, and dual-luciferase gene reporter assays. Results: Patients with AKI had low miR-223-3p and SNRK expression and high HDAC2 expression in peripheral blood. Mechanistically, miR-223-3p targeted HDAC2 to accelerate SNRK transcription. In LPS-treated HK-2 cells, BMSCs-EVs overexpressing miR-223-3p increased cell viability and diminished cell apoptosis, KIM-1, LDH, IL-1β, IL-6, TNF-α, NLRP3, ASC, cleaved caspase-1, and IL-18 expression, and GSDMD cleavage, which was nullified by HDAC2 overexpression or SNRK silencing. In AKI rats, BMSCs-EV-shuttled miR-223-3p reduced CRE and BUN levels, apoptosis, inflammation, and pyroptosis, which was abrogated by SNRK silencing. Conclusion: Conclusively, BMSC-derived EV-encapsulated miR-223-3p mitigated AKI-induced inflammation and pyroptosis by targeting HDAC2 and promoting SNRK transcription. [ABSTRACT FROM AUTHOR]

Fluorescence plays an important role in determining the color appearance of fluorescing minerals. This paper discusses the color mechanism in the red spinel and the color effects from the light source as well as the background on the spinel color. Excitation-Emission Matrices (EEMs) fluorescence spectroscopy was utilized to characterize the fluorescence of natural Cr-doped magnesia-alumina spinel from Myanmar. EMP, LA-ICP-MS, and optical spectroscopy were applied to study the spinel's chemical compositions and color mechanism. X-Rite Ci-7800 spectrophotometer, which is useful to measure colors for fluorescing minerals, was employed to acquire color data of spinel in daylight and incandescent light. The results indicated the higher value of Cr/Fe makes pinkish-red spinel has a much stronger red fluorescence effect than dark-red spinel. The two narrow absorption bands at ~ 25,500 cm−1 (with a broad absorption band at ~ 24,100 cm−1) and ~ 18,570 cm−1 in the optical absorption spectrum are assigned to spin-allowed electronic d-d transitions 4A2g → 4T1g(F) and 4A2g → 4T2g(F) in Cr3+ at the M site. The EEMs spectra of the pinkish-red spinels show twin emissions at 706 nm excited both by ~ 380 nm and ~ 535 nm radiations, which is the key to the bright neon red color in pinkish-red spinel. The colorimetry study suggests the strong red fluorescence produced by < 460 nm radiation contributes more than 10% lightness and chroma in pinkish-red spinel under daylight. The lightness and the chroma of the spinels grow with the decrease of the background grayscale. The differentiation of spinel colors in dark conditions is lower than that in a bright environment. [ABSTRACT FROM AUTHOR]

Traditional thresholding methods are widely used to extract objects of interest from image backgrounds in various practical applications. However, these methods often face challenges in complex scenes due to poor uniformity, noise, and low contrast. To overcome these limitations, this paper proposes a peak-weaken Otsu method (PWOTSU) that improves the segmentation performance of the Otsu method for automatically extracting objects in complex scenes. The proposed approach uses a set of cross parameters as weights for the Otsu criterion function to adaptively weaken the between-class variance at the peak of the histogram. This ensures that an appropriate threshold value is always obtained for images with different types of histogram distribution. The improved criterion function has the advantage of obtaining a more accurate threshold value without the need for additional parameters, making it easily applicable to various practical applications. Experimental results demonstrate that the proposed method effectively improves the segmentation accuracy and robustness compared to the standard Otsu method and its modifications, as evidenced by qualitative and quantitative evaluations. [ABSTRACT FROM AUTHOR]

Compressed ghost imaging method can effectively reduce the number of measurements required for ghost imaging reconstruction. The non-negative characteristics of measurement matrix in compressed ghost imaging method is inconsistent with the requirements of the measurement matrix in traditional compressed sensing theory, leading to low quality reconstruction. Aiming at the point, this paper proposes a singular value decomposition compressed ghost imaging method to improve the reconstruction quality of ghost imaging. First, the singular value decomposition is performed on the measurement matrix, and then the optimized measurement matrix and measurements are obtained, finally the reconstruction of the image is completed by the reconstruction algorithm. Numerical simulation experiments verify the superiority of our proposed singular value decomposition compressed ghost imaging method. [ABSTRACT FROM AUTHOR]

Graph convolutional network (GCN) has led to state-of-the-art performance for structured data. The superior performance would be partly due to the convolutional operations that operate over local neighborhoods. However, the distant long-range dependencies in data are still challenging to capture since it requires deep stacks of convolutional operations. Moreover, missing links in structured data might further hurt the performance. This paper introduces non-locality augmented graph convolution blocks into GCN to capture long-range or even disconnected dependencies. Specifically, we propose a dictionary-based non-locality encoding approach in which the non-local information is encoded by both graph convolution and dictionary-based implicit convolution. Unlike previous non-local approaches, our non-local block does not rely on the exhaustive computation of the relationship of data pairs. Thus, it is suitable for GCN, which typically models a large number of data samples. What's more, the proposed non-local blocks could be embedded into arbitrarily GCN architectures. We demonstrate the efficacy of our non-local block on four benchmark datasets. [ABSTRACT FROM AUTHOR]

Gold nanoparticles/785 porous silicon photonic crystals (Au NPs/785 PSi PhCs) were used as substrates in combination with a low-concentration serum surface-enhanced Raman spectroscopy (SERS) detection scheme to obtain spectral signals from healthy individuals and cervical cancer patients. The best principal component scores were selected by principal component analysis (PCA) combined with linear discriminant analysis (LDA) and support vector machine (SVM) to analyze the spectral differences distinguishing healthy and cervical cancer patients. The accuracy of the two models was 97.9% and 96.9%, respectively. SERS technique based on Au NPs/785 PSi PhCs has great potential to improve the screening of cervical cancer. [ABSTRACT FROM AUTHOR]

Pore fluids control the diagenetic processes and storage spaces of deep clastic rock reservoirs and have become a major area of interest within the fields of sedimentology and petroleum geology. This paper aims to relate the diagenetic processes of the Oligocene Zhuhai sandstones in the Baiyun Sag to pore fluids varying with burial depth. The types and distribution patterns of authigenic minerals are investigated through analysis of petrographic, mineralogical, and geochemical features to illustrate the origin and flow patterns of pore fluids and their influences on reservoir diagenesis. Strong cementation of eogenetic carbonate cement near the sandstone–mudstone interface was a consequence of material migration from adjacent mudstones on a large scale. The pore fluids were mainly affected by microbial methanogenesis and carbonate mineral dissolution in adjacent mudstones during eogenesis. The pore fluids were diffusively transported in a relatively open geochemical system within a local range. Support for this model is provided by the heavier stable isotopic values present in eogenetic calcite and dolomite. Feldspar dissolution during early mesogenesis was spatially accompanied by the precipitation of authigenic quartz and ferroan carbonate cement. Pore fluids in this period were rich in organic acids and CO2, and their migration mechanism was diffusive transport. The obviously lighter carbon and oxygen isotopic compositions of the ferroan calcite support this inference. During late mesogenesis, the input of deep hydrothermal fluid might have been partly responsible for the precipitation of ankerite, barite and authigenic albite. Oil charging may have inhibited carbonate cementation and compaction, accordingly preserving porosity, and together with authigenic kaolinite, might have promoted the transition of the reservoir from water wet to oil wet to the benefit of oil entrapment. The findings reported here shed new light on the evaluation and prediction of sandstone reservoirs that have experienced multiple periods of fluid flow. [ABSTRACT FROM AUTHOR]

Kruppel like factor 15 (KLF15), a transcriptional factor belonging to the Kruppel-like factor (KLF) family of genes, has recently been reported as a tumor suppressor gene in breast cancer. However, the specific mechanisms by which KLF15 inhibits BrCa have not been elucidated. Here we investigated the role and mechanism of KLF15 in triple-negative breast cancer (TNBC). KLF15 expression and methylation were detected by RT-qPCR, RT-PCR and methylation-specific PCR in breast cancer cell lines and tissues. The effects of KLF15 on TNBC cell functions were examined via various cellular function assays. The specific anti-tumor mechanisms of KLF15 were further investigated by RNA sequence, RT-qPCR, Western blotting, luciferase assay, ChIP, and bioinformatics analysis. As the results showed that KLF15 is significantly downregulated in breast cancer cell lines and tissues, which promoter methylation of KLF15 partially contributes to. Exogenous expression of KLF15 induced apoptosis and G2/M phase cell cycle arrest, suppressed cell proliferation, metastasis and in vivo tumorigenesis of TNBC cells. Mechanism studies revealed that KLF15 targeted and downregulated C–C motif chemokine ligand 2 (CCL2) and CCL7. Moreover, transcriptome and metabolome analysis revealed that KLF15 is involved in key anti-tumor regulatory and metabolic pathways in TNBC. In conclusion, KLF15 suppresses cell growth and metastasis in TNBC by downregulating CCL2 and CCL7. KLF15 may be a prognostic biomarker in TNBC. [ABSTRACT FROM AUTHOR]

The finite element model was established to predict the thermal and stress fields in selective laser melting of Ti55531 alloy. The temperature distribution, melt pool dimension, and solidification parameters on the different scanning speeds were evaluated and analyzed. The results show that the temperature and dimension of the melt pool decrease as the scanning speed increases. The maximum cooling rate and solidification rate are about 1.38 × 104 ℃/s and 0.95 mm/s, respectively, obtained at scanning speed of 1000 mm/s, while the minimum cooling rate and solidification rate are approximately 5.80 × 103 ℃/s and 0.2 mm/s, respectively, obtained at scanning speed of 200 mm/s. Relatively high scanning speed improves the instability of the solid/liquid interface and is beneficial for obtaining fine grains. In addition, the thermal stress exhibits a tendency to increase with the laser moves forward, and the residual stress increases sharply mainly during the cooling period. The maximum residual stress reached 878 MPa with a scanning speed of 1000 mm/s. The simulations and experiment results exhibit good agreement. A surface heat source with Gaussian distribution was used to realize the numerical simulation of SLM under different scanning speeds, which provides a good reference for the optimization of deposition parameters of Ti55531 alloy and the production of good-quality deposited components in the future. [ABSTRACT FROM AUTHOR]

The non-negativity of the measurement matrix in the traditional compressed ghost imaging system and iterative optimization process leads to low imaging quality and slow reconstruction speed. This paper proposes a singular value decomposition compressed ghost imaging method based on deep unfolding. The measurement matrix and training data pairs are generated through numerical simulation to reduces the cost of data acquisition. This paper adds a preprocessing layer to the network, which performs singular value decomposition on the measurement matrix to simultaneously obtain an optimized semi-orthogonal measurement matrix and optimized measurements. Then, iterative shrinking threshold algorithm network (ISTA-Net +) is used to learn the mapping between the measurements to the original signal from the training data set. Finally, the trained deep neural network can achieve non-iterative real-time reconstruction of high-quality images from low sampling rate measurements. Numerical experiments demonstrate that our proposed method has good reconstruction performance and good anti-noise performance at low sampling rates. [ABSTRACT FROM AUTHOR]

The chemical composition and influencing factors of the colour of 95 yellow to light blue iron-bearing beryl are studied through Electron Microprobe Analysis (EMPA), Energy-dispersive X-ray fluorescence (ED-XRF) spectroscopy, Fourier transform infrared (FTIR) spectroscopy, ultraviolet–visible (UV–vis) spectroscopy and X-Rite SP62 spectrophotometer. The intensities of the three characteristic hydroxyl stretching bands of the beryl from 3500 cm−1 to 3800 cm−1 prove they are low to medium levels of alkali bearing natural beryl. The wide absorption edge of 320 ~ 465 nm caused by the ultra-violet charge transfer from O2− to Fe3+ and the 650 nm absorption band in E//c-polarization caused by the intervalence charge transfer between Fe2+ and Fe3+ are the main factors affecting the colour of beryl. By applying CIE D65 standard light source and N9 Munsell neutral background as testing conditions, the colour parameters of 82 gem-quality beryl are tested. According to the results, iron-containing beryl colours are classified into yellow, yellowish-green, bluish-green, greenish-blue, and blue by the K-means cluster analysis method. The blue tone has a greater influence on the hue of beryl, while the yellow tone has a greater influence on the chroma. Iron content is higher in yellow and blue beryl. With the increase of iron content, the lightness of beryl decreased and the chroma increased. [ABSTRACT FROM AUTHOR]

Breast cancer is the leading cause of cancer death in female. Until now, advanced breast cancer is still lack effective treatment strategies and reliable prognostic markers. In the present article, we introduced the physiologic and pathologic functions and regulation mechanisms of ZBTB28, a tumor suppressor gene, in breast cancer. ZBTB28 is frequently silenced in breast cancer due to promoter CpG methylation, and its expression is positively correlated with breast cancer patient survival. The antineoplastic effect of ZBTB28 in breast cancer was elucidated through a series of in vitro and in vivo measurements, including cell proliferation, apoptosis, cell cycle, epithelial mesenchymal transition (EMT), and growth of xenografts. Furthermore, ZBTB28 can directly regulate IFNAR to activate interferon-stimulated genes and potentiate macrophage activation. Ectopic ZBTB28 expression in breast cancer cells was sufficient to downregulate CD24 and CD47 to promote phagocytosis of macrophages, demonstrating that ZBTB28 was beneficial for the combination treatment of anti-CD24 and anti-CD47. Collectively, our results reveal a mode of action of ZBTB28 as a tumor suppressor gene and suggest that ZBTB28 is an important regulator of macrophage phagocytosis in breast cancer, holding promise for the development of novel therapy strategies for breast cancer patients. [ABSTRACT FROM AUTHOR]

This study is nationwide multicenter epidemiological research, aimed at investigating the distribution changes and seasonal patterns of various airborne allergens among preschool children with allergic rhinitis (AR) in different regions of China, and analyzing the clinical correlation between sensitization to various airborne allergens and AR symptoms in children. Information on children was collected through standard questionnaires, and total IgE (tIgE) and specific IgE (sIgE) for 11 inhalant allergens were tested. The results showed that dust mites are the primary allergens for preschool AR children (39%). Among pollen allergens, Amb a had the highest positivity rate (8.1%), followed by Art v (7.8%). The sensitization rates for two mites peaked in May (46.9% and 40.6%). Art v peaked in August (21.5%), while Amb a had peaks in May (12.7%) and August (17.8%). The sensitization peaks for various tree pollens mainly occurred in August. In the Eastern monsoon region, the sensitization rate to mites was significantly higher than in the Northwest arid and semi-arid regions; whereas, for pollen allergens, the sensitization rates to Amb a, Pla a, Pin a, Pop d, and Bet v were significantly higher in the Northwest arid and semi-arid regions than in the Eastern monsoon region. The correlation among various tree pollens, specifically between Pla a, Pin r, Pop d, and Bet v was strong (0.63 ~ 0.79), with a cross-overlapping percentage of 53.9%. Children with multiple pollen sensitizations had higher cumulative nasal symptom scores than those negative for pollen (P < 0.01). Children with only pollen sensitization had higher cumulative rhinitis symptom scores than the all-negative group (P < 0.0001) and the mite-only sensitization group [P < 0.05], while the mite-only sensitization group also had higher scores than the all-negative group [P < 0.05], and the group sensitized to both pollen and mites had lower scores than the pollen-only group [P < 0.05]. This study indicates that sensitization to mites and grass pollens exhibits significant regional differences, with grass pollen allergies primarily occurring in autumn, sensitization to pollens in general exhibits a pronounced seasonal pattern. Moreover, pollen sensitization aggravates nasal and ocular symptoms in AR children. [ABSTRACT FROM AUTHOR]

Highlights: This review introduces the potential of 2D electronics for post-Moore era and discusses their current progress in digital circuits, analog circuits, heterogeneous integration, sensing circuits, artificial intelligence chips, and quantum chips in sequence. A comprehensive analysis of the current trends and challenges encountered in the development of 2D materials is summarized. An in-depth roadmap outlining the future development of 2D electronics is presented, and the most accessible and promising avenues for 2D electronics are suggested. Due to the constraints imposed by physical effects and performance degradation, silicon-based chip technology is facing certain limitations in sustaining the advancement of Moore's law. Two-dimensional (2D) materials have emerged as highly promising candidates for the post-Moore era, offering significant potential in domains such as integrated circuits and next-generation computing. Here, in this review, the progress of 2D semiconductors in process engineering and various electronic applications are summarized. A careful introduction of material synthesis, transistor engineering focused on device configuration, dielectric engineering, contact engineering, and material integration are given first. Then 2D transistors for certain electronic applications including digital and analog circuits, heterogeneous integration chips, and sensing circuits are discussed. Moreover, several promising applications (artificial intelligence chips and quantum chips) based on specific mechanism devices are introduced. Finally, the challenges for 2D materials encountered in achieving circuit-level or system-level applications are analyzed, and potential development pathways or roadmaps are further speculated and outlooked. [ABSTRACT FROM AUTHOR]

Accurately predicting prognosis subcutaneous leiomyosarcoma (LMS) is crucial for guiding treatment decisions in patients. The objective of this study was to develop prediction models for cancer-specific survival (CSS) in patients with subcutaneous LMS. The collected cases of diagnosed subcutaneous LMS were randomly divided into a training cohort and a validation cohort at a 6:4 ratio based on tumor location and histological code. The X-tile program was utilized to determine the optimal cutoff points for age index. Univariate and Cox multivariate regression analyses were conducted to identify independent risk factors for subcutaneous LMS patients. Nomograms were constructed to predict CSS, and their performance was assessed using C-index and calibration plots. Additionally, a decision tree model was established using recursive partitioning analysis to determine the total score for CSS prediction in subcutaneous LMS patients based on the nomogram model. A total of 1793 patients with subcutaneous LMS were found. X-tile software divides all patients into ≤ 61 years old, 61–82 years old, and ≥ 82 years old. The most important anatomical sites were the limbs (including the upper and lower limbs, 48.0%). Only 6.2% of patients received chemotherapy, while 44% had a history of radiotherapy and 92.9% underwent surgery. The independent risk factors for patients with subcutaneous LMS were age, summary stage, grade, and surgery. CSS was significantly decreased in patients with distant metastases, which showed the highest independent risk predictor (HR 4.325, 95% CI 3.010–6.214, p < 0.001). The nomogram prediction model of LMS was constructed based on four risk factors. The C-index for this model was 0.802 [95% CI 0.781–0.823] and 0.798 [95% CI 0.768–0.829]. The training cohort's 3-, 5-, and 10-year AUCs for CSS in patients with subcutaneous LMS were 0.833, 0.830, and 0.859, and the validation cohort's AUC for predicting CSS rate were 0.849, 0.830, and 0.803, respectively. Recursive segmentation analysis divided patients into 4 risk subgroups according to the total score in the nomogram, including low-risk group < 145, intermediate-low-risk group ≥ 145 < 176, intermediate-high-risk group ≥ 176 < 196, and high-risk group ≥ 196; The probability of the four risk subgroups is 9.1%, 34%, 49%, and 79% respectively. In this retrospective study, a novel nomogram or corresponding risk classification system for patients with subcutaneous LMS were developed, which may assist clinicians in identifying high-risk patients and in guiding the clinical decision. [ABSTRACT FROM AUTHOR]

Surface-enhanced Raman scattering (SERS), as a rapid, reliable and non-destructive spectral detection technology, has made a series of breakthrough achievements in screening and pre-diagnosis of various cancerous tumors. In this paper, high-performance gold nanoparticles/785 porous silicon photonic crystals (Au NPs/785 PSi PhCs) active SERS substrates were specially designed for serum testing, and realized highly sensitive detection of serum from healthy people, patients with cervical cancer and breast cancer. Based on the SERS spectra of the three groups of serum, the significant differences between the healthy group and cancer group at 1030 cm−1 and 1051 cm−1 were analyzed, and the similar but different serum SERS spectra of cervical cancer and breast cancer patients were compared. In addition, the spectral difference detected by SERS technology combined with a multivariate statistical algorithm was used to distinguish three kinds of serum. The serum SERS spectral sensitive bands were extracted by recursive weighted partial least squares (rPLS), and the three classification diagnosis models were established by combining orthogonal partial least squares discriminant analysis (OPLS-DA), linear discriminant analysis (LDA) and principal component analysis support vector machine (PCA-SVM) for synchronous classification and discrimination of the three groups of serum. The diagnostic results showed that the overall screening accuracy of three models were 93.28%, 97.77% and 94.78%, respectively. These above results confirmed that the Au NPs/785 PSi PhCs can realize super-sensitive detection of serum, and the established diagnostic model has great potential for pre-diagnosis and simultaneous screening of cervical cancer and breast cancer. [ABSTRACT FROM AUTHOR]

Purpose: In previous studies, short-chain fatty acids (SCFAs) have been found to regulate gut microbiota and change gut barrier status, and the potential positive effects of SCFAs on inflammatory bowel disease (IBD), type 1 diabetes mellitus (T1D), and non-alcoholic fatty liver disease (NAFLD) have also been found, but the role of SCFAs in these three diseases is not clear. This review aims to summarize existing evidence on the effects of SCFAs on IBD, T1D, and NHFLD, and correlates them with gut barrier and gut microbiota (gut microbiota barrier). Methods: A literature search in PubMed, Web of Science, Springer, and Wiley Online Library up to October 2020 was conducted for all relevant studies published. Results: This is a retrospective review of 150 applied research articles or reviews. The destruction of gut barrier may promote the development of IBD, T1D, and NAFLD. SCFAs seem to maintain the gut barrier by promoting the growth of intestinal epithelial cells, strengthening the intestinal tight connection, and regulating the activities of gut microbiota and immune cells, which might result possible beneficial effects on the above three diseases at a certain dose. Conclusions: Influencing gut barrier health may be a bridge for SCFAs (especially butyrate) to have positive effects on IBD, T1D, and NAFLD. It is expected that this article can provide new ideas for the subsequent research on the treatment of diseases by SCFAs and help SCFAs be better applied to precise and personalized treatment. [ABSTRACT FROM AUTHOR]

Auricularia is a genus of edible jelly fungi whose highly plastic fruiting bodies lack differentiation between stalks and caps, making accurate identification of similar species difficult. Auricularia villosula (A. villosula) is a wild edible mushroom that is also used in traditional Chinese medicine. Here, we sequenced and assembled its mitochondrial genome using Illumina short reads. The complete sequence is 230,069 bp in length with a GC content of 30.1%. It harbors 41 genes (25 tRNA, 2 rRNA, and 14 protein-coding): 2 on the N strand (−) and 29 on the J strand (+). Analysis of nucleotide composition revealed positive GC (0.027) and AT (0.002) skews. The mitochondrial genome included a very large intergenic region (22,840 bp) between cytochrome b (CytB) and tRNATyr, lacked overlapping nucleotides between genes, and used non-standard start codons for some genes. Phylogenetic analysis revealed that A. villosula was distant from other species of Polyporales, Agaricales, and Russulales. The A. villosula mitogenome sequence will be useful for future taxonomic and genetic studies. [ABSTRACT FROM AUTHOR]

Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease with limited therapeutic targets or clinical outcome predictors. This study aimed to gain more insights into the underlying immunological pathways and prognostic biomarkers of SLE. Integrated analyses of RNA-seq data from 64 SLE and 62 healthy controls, examining 27 immune cell types to explore the key pathways and driver genes in SLE pathogenesis. Single-cell RNA sequencing data from the skin and kidney were used to determine the association of COX5A expression with organ damage. The associations of COX5A with SLE phenotypes were further evaluated in two independent cohorts, and receiver operating characteristic (ROC) curves were constructed to assess the value of COX5A as a biomarker for disease activity and organ damage in SLE. We found that oxidative phosphorylation (OXPHOS) is the most significantly altered metabolic pathway in SLE, especially in effector T cells. Notably, we identified an OXPHOS-related enzyme, COX5A, whose expression was significantly higher in effector T cells than in naïve T cells and showed associations with disease activity, organ damage, and steroid treatment of SLE. Furthermore, ROC curves showed that COX5A is a robust biomarker for disease activity, kidney involvement, and new-onset skin lesions, with the area under the curve (AUC) values of 0.880, 0.801, and 0.805, respectively. Our results identified the OXPHOS signature as a prominent feature in SLE T cells, and COX5A as a potential candidate biomarker for disease activity and organ damage in SLE. [ABSTRACT FROM AUTHOR]

H3 K27M-mutant diffuse midline glioma (H3 K27M-mt DMG) is a rare, highly invasive tumor with a poor prognosis. The prognostic factors of H3 K27M-mt DMG have not been fully identified, and there is no clinical prediction model for it. This study aimed to develop and validate a prognostic model for predicting the probability of survival in patients with H3 K27M-mt DMG. Patients diagnosed with H3 K27M-mt DMG in the West China Hospital from January 2016 to August 2021 were included. Cox proportional hazard regression was used for survival assessment, with adjustment for known prognostic factors. The final model was established using the patient data of our center as the training cohort and data from other centers for external independent verification. One hundred and five patients were ultimately included in the training cohort, and 43 cases from another institution were used as the validation cohort. The factors influencing survival probability in the prediction model included age, preoperative KPS score, radiotherapy and Ki-67 expression level. The adjusted consistency indices of the Cox regression model in internal bootstrap validation at 6, 12, and 18 months were 0.776, 0.766, and 0.764, respectively. The calibration chart showed high consistency between the predicted and observed results. The discrimination in external verification was 0.785, and the calibration curve showed good calibration ability. We identified the risk factors that affect the prognosis of H3 K27M-mt DMG patients and then established and validated a diagnostic model for predicting the survival probability of these patients. [ABSTRACT FROM AUTHOR]

The high enhancement activity of litchi-like gold nanoparticles (Au NPs) is prepared in deep eutectic solvent (DES), and the prepared Au NPs as SERS active substrate exhibits excellent sensitivity when rhodamine 6G (R6G) is used as a probe molecule for detection. The enhancement factor (EF) is calculated to be about 1.8 × 1012, and the minimum detected concentration is outstanding in R6G aqueous solution at 10−12 M. In addition, the microtrace determination of penicillin G sodium (PG) in camel milk powder produced in Xinjiang was successfully achieved by using the prepared Au NPs. This work provides an environmentally friendly, simple, and rapid method to prepare efficient and sensitive surface-enhanced Raman scattering (SERS) materials. Meanwhile, it also uncovers a new possibility for the development of various nanoparticles with SERS prepared using DES as reactive solutions. [ABSTRACT FROM AUTHOR]

Footprint data have large intra-class variances and small inter-class variances; therefore, the key to the footprint recognition problem is to mine and learn the discriminative local details in the footprint images. In this paper, an algorithm based on a multi-scale confusion and filling mechanism is proposed to address the problem of footprint recognition from the perspective of fine-grained image recognition. Firstly, the pressure footprint image is divided evenly into several sub-regions, and the score of each sub-region is calculated by a joint confidence function. Secondly, using the filling mechanism of the Region Filling Module, the region with the lowest score in the split image is filled with a higher one for data enhancement. Then, the filled image is confused once using the Multi-Scale Region Confusion Module, and the regions with high confidence score are confused again to obtain an image with multi-scale information. Finally, the footprint features of the filled image and the confused image are extracted by the backbone network and optimized by the joint loss function to carry out the task of footprint recognition. Comprehensive experiments show that the proposed algorithm achieves 89.3%, 93.4% and 86.5% on three benchmark dataset including CUB-200-2011, Aircraft and Stanford Dogs. Meanwhile, it obtains 97.8% on the footprint dataset. [ABSTRACT FROM AUTHOR]

The concentration of guest elements (dopants) into host materials play an important role in changing their intrinsic electrical and optical properties. The existence of hetero-element induce defect in crystal structure, affecting conductivity. In the current work, we report Cu2+ ion into hematite in the defectronics point of view and their photoelectrochemical properties. Crystal distortion in the structure of hematite is observed as the amount of dopant increases. Among 1, 3 and 5 mol% of Cu2+ doped hematite, the existence of 1 mol% of Cu2+ ion into hematite crystal structure produce photocurrent value of 0.15 mA/cm2, IPCE value of ~ 4.7% and EIS value of ~ 2000 Ω/cm2 as best performances. However, further increasing dopants increases the number of interstitial defects, which cause the deformation of intrinsic lattice structure. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to develop and validate a predictive model for osteoporotic vertebral fractures (OVFs) risk by integrating demographic, bone mineral density (BMD), CT imaging, and deep learning radiomics features from CT images.A total of 169 osteoporosis-diagnosed patients from three hospitals were randomly split into OVFs (n = 77) and Non-OVFs (n = 92) groups for training (n = 135) and test (n = 34). Demographic data, BMD, and CT imaging details were collected. Deep transfer learning (DTL) using ResNet-50 and radiomics features were fused, with the best model chosen via logistic regression. Cox proportional hazards models identified clinical factors. Three models were constructed: clinical, radiomics-DTL, and fusion (clinical-radiomics-DTL). Performance was assessed using AUC, C-index, Kaplan–Meier, and calibration curves. The best model was depicted as a nomogram, and clinical utility was evaluated using decision curve analysis (DCA).BMD, CT values of paravertebral muscles (PVM), and paravertebral muscles' cross-sectional area (CSA) significantly differed between OVFs and Non-OVFs groups (P < 0.05). No significant differences were found between training and test cohort. Multivariate Cox models identified BMD, CT values of PVM, and CSAPS reduction as independent OVFs risk factors (P < 0.05). The fusion model exhibited the highest predictive performance (C-index: 0.839 in training, 0.795 in test). DCA confirmed the nomogram's utility in OVFs risk prediction.This study presents a robust predictive model for OVFs risk, integrating BMD, CT data, and radiomics-DTL features, offering high sensitivity and specificity. The model's visualizations can inform OVFs prevention and treatment strategies.Methods: This study aimed to develop and validate a predictive model for osteoporotic vertebral fractures (OVFs) risk by integrating demographic, bone mineral density (BMD), CT imaging, and deep learning radiomics features from CT images.A total of 169 osteoporosis-diagnosed patients from three hospitals were randomly split into OVFs (n = 77) and Non-OVFs (n = 92) groups for training (n = 135) and test (n = 34). Demographic data, BMD, and CT imaging details were collected. Deep transfer learning (DTL) using ResNet-50 and radiomics features were fused, with the best model chosen via logistic regression. Cox proportional hazards models identified clinical factors. Three models were constructed: clinical, radiomics-DTL, and fusion (clinical-radiomics-DTL). Performance was assessed using AUC, C-index, Kaplan–Meier, and calibration curves. The best model was depicted as a nomogram, and clinical utility was evaluated using decision curve analysis (DCA).BMD, CT values of paravertebral muscles (PVM), and paravertebral muscles' cross-sectional area (CSA) significantly differed between OVFs and Non-OVFs groups (P < 0.05). No significant differences were found between training and test cohort. Multivariate Cox models identified BMD, CT values of PVM, and CSAPS reduction as independent OVFs risk factors (P < 0.05). The fusion model exhibited the highest predictive performance (C-index: 0.839 in training, 0.795 in test). DCA confirmed the nomogram's utility in OVFs risk prediction.This study presents a robust predictive model for OVFs risk, integrating BMD, CT data, and radiomics-DTL features, offering high sensitivity and specificity. The model's visualizations can inform OVFs prevention and treatment strategies.Results: This study aimed to develop and validate a predictive model for osteoporotic vertebral fractures (OVFs) risk by integrating demographic, bone mineral density (BMD), CT imaging, and deep learning radiomics features from CT images.A total of 169 osteoporosis-diagnosed patients from three hospitals were randomly split into OVFs (n = 77) and Non-OVFs (n = 92) groups for training (n = 135) and test (n = 34). Demographic data, BMD, and CT imaging details were collected. Deep transfer learning (DTL) using ResNet-50 and radiomics features were fused, with the best model chosen via logistic regression. Cox proportional hazards models identified clinical factors. Three models were constructed: clinical, radiomics-DTL, and fusion (clinical-radiomics-DTL). Performance was assessed using AUC, C-index, Kaplan–Meier, and calibration curves. The best model was depicted as a nomogram, and clinical utility was evaluated using decision curve analysis (DCA).BMD, CT values of paravertebral muscles (PVM), and paravertebral muscles' cross-sectional area (CSA) significantly differed between OVFs and Non-OVFs groups (P < 0.05). No significant differences were found between training and test cohort. Multivariate Cox models identified BMD, CT values of PVM, and CSAPS reduction as independent OVFs risk factors (P < 0.05). The fusion model exhibited the highest predictive performance (C-index: 0.839 in training, 0.795 in test). DCA confirmed the nomogram's utility in OVFs risk prediction.This study presents a robust predictive model for OVFs risk, integrating BMD, CT data, and radiomics-DTL features, offering high sensitivity and specificity. The model's visualizations can inform OVFs prevention and treatment strategies.Conclusion: This study aimed to develop and validate a predictive model for osteoporotic vertebral fractures (OVFs) risk by integrating demographic, bone mineral density (BMD), CT imaging, and deep learning radiomics features from CT images.A total of 169 osteoporosis-diagnosed patients from three hospitals were randomly split into OVFs (n = 77) and Non-OVFs (n = 92) groups for training (n = 135) and test (n = 34). Demographic data, BMD, and CT imaging details were collected. Deep transfer learning (DTL) using ResNet-50 and radiomics features were fused, with the best model chosen via logistic regression. Cox proportional hazards models identified clinical factors. Three models were constructed: clinical, radiomics-DTL, and fusion (clinical-radiomics-DTL). Performance was assessed using AUC, C-index, Kaplan–Meier, and calibration curves. The best model was depicted as a nomogram, and clinical utility was evaluated using decision curve analysis (DCA).BMD, CT values of paravertebral muscles (PVM), and paravertebral muscles' cross-sectional area (CSA) significantly differed between OVFs and Non-OVFs groups (P < 0.05). No significant differences were found between training and test cohort. Multivariate Cox models identified BMD, CT values of PVM, and CSAPS reduction as independent OVFs risk factors (P < 0.05). The fusion model exhibited the highest predictive performance (C-index: 0.839 in training, 0.795 in test). DCA confirmed the nomogram's utility in OVFs risk prediction.This study presents a robust predictive model for OVFs risk, integrating BMD, CT data, and radiomics-DTL features, offering high sensitivity and specificity. The model's visualizations can inform OVFs prevention and treatment strategies. [ABSTRACT FROM AUTHOR]

Background: Acute kidney injury (AKI) is common and it is associated with poor clinical outcomes in premature and low birth weight neonates. This systematic review and meta-analysis was performed to summarize the literature and evaluate the prevalence, risk factors, and mortality of premature and low birth weight neonates with AKI. Methods: A systematic search in PubMed, Embase, and the Cochrane Library was performed. Studies on the prevalence, risk factors, diagnosis, and outcomes of acute kidney injury in preterm neonates and neonates with low birth weight were included and analyzed. Results: Fifty articles of 10,744 patients were included in this study. The overall rate of AKI from the pooled results of all patients was 25% (95% CI 20–30%) with heterogeneity among studies (I2 = 97%; P < 0.01). Patients with AKI had significantly higher rate of mortality than patients without AKI (odds ratio (OR) = 7.13; 95% CI 5.91–8.60; P < 0.01). Conclusions: AKI was prevalent and was associated with high mortality rate among preterm and low birth weight neonates. [ABSTRACT FROM AUTHOR]

Background: We aimed to examine the associations between depressive symptoms and physical activity parameters (e.g., intensity, frequency, and duration) among Chinese school-aged children.Participants in this study were extracted from the Tongji Mental Health Cohort Study. The baseline survey was conducted in June 2020 involving 2588 school-aged children from two primary schools in Hubei Province, China. A total of 2435 children were followed up successfully in December 2020. The Children’s Depression Inventory Short Form (CDI-S) was applied to evaluate depressive symptoms among school-aged children. The Physical Activity Rating Scale-3 (PARS-3) was adopted to estimate children’s physical activity parameters including the intensity, frequency, and duration. Generalized estimation equation models were used to explore the longitudinal associations between physical activity and depressive symptoms among school-aged children.Engaging in moderate levels of physical activity (OR, 0.800; 95%CI, 0.692–0.924) or high levels of physical activity (OR, 0.808; 95%CI, 0.689–0.947) in the baseline survey was associated with a reduced risk of developing depressive symptoms in the follow-up survey compared with children engaging in low levels of physical activity. Stratified analyses revealed that the associations between physical activity and depressive symptoms exhibited a significant correlation among boys and children in the older age group (11–12 years). Our findings showed that engaging in physical activity more than once a week, with each session lasting 20 min or longer, was related to significant reductions in depressive symptoms by 43.8% and 22.3%, respectively.Self-reported physical activity is positively associated with improved mental health among Chinese school-aged children, especially when considering parameters such as frequency and duration. The association between vigorous-intensity physical activity and depressive symptoms in children should be cautiously interpreted. Future research should continue to explore the effects of vigorous-intensity physical activity on depressive symptoms in children.Method: We aimed to examine the associations between depressive symptoms and physical activity parameters (e.g., intensity, frequency, and duration) among Chinese school-aged children.Participants in this study were extracted from the Tongji Mental Health Cohort Study. The baseline survey was conducted in June 2020 involving 2588 school-aged children from two primary schools in Hubei Province, China. A total of 2435 children were followed up successfully in December 2020. The Children’s Depression Inventory Short Form (CDI-S) was applied to evaluate depressive symptoms among school-aged children. The Physical Activity Rating Scale-3 (PARS-3) was adopted to estimate children’s physical activity parameters including the intensity, frequency, and duration. Generalized estimation equation models were used to explore the longitudinal associations between physical activity and depressive symptoms among school-aged children.Engaging in moderate levels of physical activity (OR, 0.800; 95%CI, 0.692–0.924) or high levels of physical activity (OR, 0.808; 95%CI, 0.689–0.947) in the baseline survey was associated with a reduced risk of developing depressive symptoms in the follow-up survey compared with children engaging in low levels of physical activity. Stratified analyses revealed that the associations between physical activity and depressive symptoms exhibited a significant correlation among boys and children in the older age group (11–12 years). Our findings showed that engaging in physical activity more than once a week, with each session lasting 20 min or longer, was related to significant reductions in depressive symptoms by 43.8% and 22.3%, respectively.Self-reported physical activity is positively associated with improved mental health among Chinese school-aged children, especially when considering parameters such as frequency and duration. The association between vigorous-intensity physical activity and depressive symptoms in children should be cautiously interpreted. Future research should continue to explore the effects of vigorous-intensity physical activity on depressive symptoms in children.Results: We aimed to examine the associations between depressive symptoms and physical activity parameters (e.g., intensity, frequency, and duration) among Chinese school-aged children.Participants in this study were extracted from the Tongji Mental Health Cohort Study. The baseline survey was conducted in June 2020 involving 2588 school-aged children from two primary schools in Hubei Province, China. A total of 2435 children were followed up successfully in December 2020. The Children’s Depression Inventory Short Form (CDI-S) was applied to evaluate depressive symptoms among school-aged children. The Physical Activity Rating Scale-3 (PARS-3) was adopted to estimate children’s physical activity parameters including the intensity, frequency, and duration. Generalized estimation equation models were used to explore the longitudinal associations between physical activity and depressive symptoms among school-aged children.Engaging in moderate levels of physical activity (OR, 0.800; 95%CI, 0.692–0.924) or high levels of physical activity (OR, 0.808; 95%CI, 0.689–0.947) in the baseline survey was associated with a reduced risk of developing depressive symptoms in the follow-up survey compared with children engaging in low levels of physical activity. Stratified analyses revealed that the associations between physical activity and depressive symptoms exhibited a significant correlation among boys and children in the older age group (11–12 years). Our findings showed that engaging in physical activity more than once a week, with each session lasting 20 min or longer, was related to significant reductions in depressive symptoms by 43.8% and 22.3%, respectively.Self-reported physical activity is positively associated with improved mental health among Chinese school-aged children, especially when considering parameters such as frequency and duration. The association between vigorous-intensity physical activity and depressive symptoms in children should be cautiously interpreted. Future research should continue to explore the effects of vigorous-intensity physical activity on depressive symptoms in children.Conclusion: We aimed to examine the associations between depressive symptoms and physical activity parameters (e.g., intensity, frequency, and duration) among Chinese school-aged children.Participants in this study were extracted from the Tongji Mental Health Cohort Study. The baseline survey was conducted in June 2020 involving 2588 school-aged children from two primary schools in Hubei Province, China. A total of 2435 children were followed up successfully in December 2020. The Children’s Depression Inventory Short Form (CDI-S) was applied to evaluate depressive symptoms among school-aged children. The Physical Activity Rating Scale-3 (PARS-3) was adopted to estimate children’s physical activity parameters including the intensity, frequency, and duration. Generalized estimation equation models were used to explore the longitudinal associations between physical activity and depressive symptoms among school-aged children.Engaging in moderate levels of physical activity (OR, 0.800; 95%CI, 0.692–0.924) or high levels of physical activity (OR, 0.808; 95%CI, 0.689–0.947) in the baseline survey was associated with a reduced risk of developing depressive symptoms in the follow-up survey compared with children engaging in low levels of physical activity. Stratified analyses revealed that the associations between physical activity and depressive symptoms exhibited a significant correlation among boys and children in the older age group (11–12 years). Our findings showed that engaging in physical activity more than once a week, with each session lasting 20 min or longer, was related to significant reductions in depressive symptoms by 43.8% and 22.3%, respectively.Self-reported physical activity is positively associated with improved mental health among Chinese school-aged children, especially when considering parameters such as frequency and duration. The association between vigorous-intensity physical activity and depressive symptoms in children should be cautiously interpreted. Future research should continue to explore the effects of vigorous-intensity physical activity on depressive symptoms in children. [ABSTRACT FROM AUTHOR]

RNA N6-methyladenosine (m6A) modifications are essential in plants. Here, we show that transgenic expression of the human RNA demethylase FTO in rice caused a more than threefold increase in grain yield under greenhouse conditions. In field trials, transgenic expression of FTO in rice and potato caused ~50% increases in yield and biomass. We demonstrate that the presence of FTO stimulates root meristem cell proliferation and tiller bud formation and promotes photosynthetic efficiency and drought tolerance but has no effect on mature cell size, shoot meristem cell proliferation, root diameter, plant height or ploidy. FTO mediates substantial m6A demethylation (around 7% of demethylation in poly(A) RNA and around 35% decrease of m6A in non-ribosomal nuclear RNA) in plant RNA, inducing chromatin openness and transcriptional activation. Therefore, modulation of plant RNA m6A methylation is a promising strategy to dramatically improve plant growth and crop yield. Rice and potato plants are more productive after epitranscriptome engineering. [ABSTRACT FROM AUTHOR]

Early detection of cervical lesions, accurate diagnosis of cervical lesions, and timely and effective therapy can effectively avoid the occurrence of cervical cancer or improve the survival rate of patients. In this paper, the spectra of tissue sections of cervical inflammation (n = 60), CIN (cervical intraepithelial neoplasia) I (n = 30), CIN II (n = 30), CIN III (n = 30), cervical squamous cell carcinoma (n = 30), and cervical adenocarcinoma (n = 30) were collected by a confocal Raman micro-spectrometer (LabRAM HR Evolution, Horiba France SAS, Villeneuve d'Ascq, France). The Raman spectra of six kinds of cervical tissues were analyzed, the dominant Raman peaks of different kinds of tissues were summarized, and the differences in chemical composition between the six tissue samples were compared. An independent sample t test (p ≤ 0.05) was used to analyze the difference of average relative intensity of Raman spectra of six types of cervical tissues. The difference of relative intensity of Raman spectra of six kinds of tissues can reflect the difference of biochemical components in six kinds of tissues and the characteristic of biochemical components in different kinds of tissues. The classification models of cervical inflammation, CIN I, CIN II, CIN III, cervical squamous cell carcinoma, and cervical adenocarcinoma were established by using a support vector machine (SVM) algorithm. Six types of cervical tissues were classified and identified with an overall diagnostic accuracy of 85.7%. This study laid a foundation for the application of Raman spectroscopy in the clinical diagnosis of cervical precancerous lesions and cervical cancer. [ABSTRACT FROM AUTHOR]

Purpose: Chemotherapeutic adjuvants, such as oxaliplatin (OXA) and 5-fluorouracil (5-FU), that enhance the immune system, are being assessed as strategies to improve durable response rates when used in combination with immune checkpoint inhibitor (ICI) monotherapy in cancer patients. In this study, we explored granzyme B (GZB), released by tumor-associated immune cells, as a PET imaging-based stratification marker for successful combination therapy using a fluorine-18 (18F)-labelled GZB peptide ([18F]AlF-mNOTA-GZP). Methods: Using the immunocompetent CT26 syngeneic mouse model of colon cancer, we assessed the potential for [18F]AlF-mNOTA-GZP to stratify OXA/5-FU and ICI combination therapy response via GZB PET. In vivo tumor uptake of [18F]AlF-mNOTA-GZP in different treatment arms was quantified by PET, and linked to differences in tumor-associated immune cell populations defined by using multicolour flow cytometry. Results: [18F]AlF-mNOTA-GZP tumor uptake was able to clearly differentiate treatment responders from non-responders when stratified based on changes in tumor volume. Furthermore, [18F]AlF-mNOTA-GZP showed positive associations with changes in tumor-associated lymphocytes expressing GZB, namely GZB+ CD8+ T cells and GZB+ NK+ cells. Conclusions: [18F]AlF-mNOTA-GZP tumor uptake, driven by changes in immune cell populations expressing GZB, is able to stratify tumor response to chemotherapeutics combined with ICIs. Our results show that, while the immunomodulatory mode of action of the chemotherapies may be different, the ultimate mechanism of tumor lysis through release of Granzyme B is an accurate biomarker for treatment response. [ABSTRACT FROM AUTHOR]

Background: In rice, panicle apical abortion is a common phenomenon that usually results in a decreased number of branches and grains per panicle, and consequently a reduced grain yield. A better understanding of the molecular mechanism of panicle abortion is thus critical for maintaining and increasing rice production. Results: We reported a new rice mutant panicle apical abortion 3 (paa3), which exhibited severe abortion of spikelet development on the upper part of the branches as well as decreased grain size over the whole panicle. Using mapping-based clone, the PAA3 was characterized as the LOC_ Os04g56160 gene, encoding an H+-ATPase. The PAA3 was expressed highly in the stem and panicle, and its protein was localized in the plasma membrane. Our data further showed that PAA3 played an important role in maintaining normal panicle development by participating in the removal of reactive oxygen species (ROS) in rice. Conclusions: Our studies suggested that PAA3 might function to remove ROS, the accumulation of which leads to programmed cell death, and ultimately panicle apical abortion and decreased seed size in the paa3 panicle. [ABSTRACT FROM AUTHOR]