Clinicopathologic analysis of nodal T-follicular helper cell lymphomas, a multicenter retrospective study from China.

Background: Nodal T-follicular helper cell lymphomas (nTFHLs) represent a new family of peripheral T-cell lymphomas (PTCLs), and comparative studies of their constituents are rare. Methods: This study retrospectively enrolled 10 patients with nTFHL-F and 30 patients with nTFHL-NOS diagnosed between December 2017 and October 2023 at six large comprehensive tertiary hospitals; 188 patients with nTFHL-AI were diagnosed during the same period at the First Affiliated Hospital of Zhengzhou University for comparison. Results: Compared with nTFHL-AI, nTFHL-NOS patients exhibited better clinical manifestations, lower TFH expression levels, and a lower Ki-67 index. However, no differences in clinicopathological features were observed between nTFHL-F and nTFHL-AI patients as well as nTFHL-NOS patients. According to the survival analysis, the median OS for patients with nTFHL-NOS, nTFHL-AI, and nTFHL-F were 14.2 months, 10 months, and 5 months, respectively, whereas the median TTP were 14 months, 5 months, and 3 months, respectively. Statistical analysis revealed differences in TTP among the three subtypes(P=0.0173). Among the population of patients receiving CHOP-like induction therapy, there were significant differences in the OS and TTP among the nTFHL-NOS, nTFHL-AI, and nTFHL-F patients (P=0.0134, P=0.0205). Both the GDPT and C-PET regimens significantly improved the ORR, OS, and PFS in nTFHL patients. Conclusion: There are significant differences in the clinical manifestations, pathology, and survival outcomes among the three subtypes of nTFHLs. However, further research with a larger sample size, and involving clinical pathology and molecular genetics is needed to determine the distinctive biological characteristics of these tumors.

Clinical and imaging features of lymphomatosis cerebri: analysis of 8 cases and systematic review of the literature.

Lymphomatosis cerebri (LC) is a rare type of primary central nervous system lymphoma with diffuse, nonenhancing infiltrative lesions and is often misdiagnosed. Our study aimed to investigate the clinical characteristics and prognosis of LC through analyzing patients from the literature and our own center, so as to improve early diagnosis and treatment. PubMed, Web of Science and our hospital databases were reviewed, and information on demographic, clinical, pathological, cerebrospinal fluid (CSF), neuroimaging and treatment options was extracted. Univariate survival analysis was conducted by generating survival curves and comparing them using the log-rank test. Multivariate analysis was performed using the Cox proportional hazards regression model to identify the prognostic predictors. A total of 81 patients (median age: 58 years; interquartile range, IQR: 50-66.5 years), 45 males and 36 females, were included. The most common symptoms were cognitive impairment (65.4%) and gait impairment (50.6%). Imaging studies indicated that all 81 patients had supratentorial structure involvement, and 93.8% (76/81) had bilateral hemisphere involvement. There were 53.3% (32/60) patients with CSF pleocytosis and 65% (39/60) patients with increased CSF protein levels. The median time of diagnosis was 4.8 months (IQR: 2.3-6.9 months). Compared with 4 (95% CI: 1.78-6.22) months for all 81 patients, the median OS was 20 (95% CI: 8.24-31.76) months for those who had chemotherapy plus radiotherapy. Multivariate Cox analysis revealed that chemoradiotherapy (HR: 0.12; 95% CI: 0.02-0.68) and higher CSF glucose level (HR: 0.01; 95% CI: 0.00-0.26) were inversely associated with death. The diagnosis of LC should be alerted when neuroimaging with bilateral hemispheric involvement and CSF abnormality with pleocytosis and increased protein. Once the diagnosis is confirmed, the combination of chemotherapy and radiotherapy can be considered if the patient's physical condition permits.Journal standard instruction requires an unstructured abstract. Kindly check and confirm.We have checked and confirmed that there is no problem.

Hydrologic-induced concentrated soil nutrients and improved plant growth increased carbon storage in a floodplain wetland over wet-dry alternating zones.

Hydrological gradient variations in wetlands have a vital impact on wetland carbon storage. However, the mechanisms by which hydrological gradient variations affect biomass and carbon storage by regulating the soil nutrient contents and plant diversity remain unclear. This study attempted to explore these influencing mechanisms by studying the relationships between hydrological gradient variations and carbon storage in wetlands. The results showed that the average nutrient content, plant biomass and soil carbon content values in the high-frequency wet-dry alternating zones (HFWA, zones where the frequency of water level occurs between -25 cm and 25 cm greater than 0.5) were 1.4 times, 2.3 times and 0.43 higher, respectively, than those in the low-frequency wet-dry alternating zones (LFWA, zones where the frequency of water level occurs between -25 cm and 25 cm less than 0.3). These results indicated that the HFWA zones had higher soil nutrients, higher plant dominance, higher biomass and higher soil carbon contents than the LFWA zones. The structural equation model revealed a significant positive correlation between wet-dry alternations and the soil nutrient-plant biomass-soil carbon relation in wetlands. Moreover, there was also a significant positive correlation between wet-dry alternations and the plant dominance-plant biomass-soil carbon relation in wetlands. This implied that the concentrated effect of HFWA on soil nutrients promotes plant growth, enhances plant dominance, promotes plant productivity, and enhances the capacities of plants to input carbon to the soil, thereby increasing the soil carbon content. This study closely linked wetland hydrological gradients, plant biodiversity and wetland carbon sequestration and profoundly revealed the mechanisms by which hydrological gradients in wetlands regulate the concentrations of nutrient elements, thereby affecting vegetation growth and carbon sequestration; these results could provide a new cognitive basis for understanding the coupling of carbon and water.

Differentiation of paediatric posterior fossa tumours by the multiregional and multiparametric MRI radiomics approach: a study on the selection of optimal multiple sequences and multiregions.

OBJECTIVE: To evaluate the diagnostic performance of a radiomics model based on multiregional and multiparametric MRI to classify paediatric posterior fossa tumours (PPFTs), explore the contribution of different MR sequences and tumour subregions in tumour classification, and examine whether contrast-enhanced T1 weighted (T1C) images have irreplaceable added value. METHODS: This retrospective study of 136 PPFTs extracted 11,958 multiregional (enhanced, non-enhanced, and total tumour) features from multiparametric MRI (T1- and T2 weighted, T1C, fluid-attenuated inversion recovery, and diffusion-weighted images). These features were subjected to fast correlation-based feature selection and classified by a support vector machine based on different tasks. Diagnostic performances of multiregional and multiparametric MRI features, different sequences, and different tumoral regions were evaluated using multiclass and one-vs-rest strategies. RESULTS: The established model achieved an overall area under the curve (AUC) of 0.977 in the validation cohort. The performance of PPFTs significantly improved after replacing T1C with apparent diffusion coefficient maps added into the plain scan sequences (AUC from 0.812 to 0.917). When oedema features were added to contrast-enhancing tumour volume, the performance did not significantly improve. CONCLUSION: The radiomics model built by multiregional and multiparametric MRI features allows for the excellent distinction of different PPFTs and provides valuable references for the rational adoption of MR sequences. ADVANCES IN KNOWLEDGE: This study emphasized that T1C has limited added value in predicting PPFTs and should be cautiously adopted. Selecting optimal MR sequences may help guide clinicians to better allocate acquisition sequences and reduce medical costs.

Accurate segmentation for different types of lung nodules on CT images using improved U-Net convolutional network.

ABSTRACT: Since lung nodules on computed tomography images can have different shapes, contours, textures or locations and may be attached to neighboring blood vessels or pleural surfaces, accurate segmentation is still challenging. In this study, we propose an accurate segmentation method based on an improved U-Net convolutional network for different types of lung nodules on computed tomography images.The first phase is to segment lung parenchyma and correct the lung contour by applying α-hull algorithm. The second phase is to extract image pairs of patches containing lung nodules in the center and the corresponding ground truth and build an improved U-Net network with introduction of batch normalization.A large number of experiments manifest that segmentation performance of Dice loss has superior results than mean square error and Binary_crossentropy loss. The α-hull algorithm and batch normalization can improve the segmentation performance effectively. Our best result for Dice similar coefficient (0.8623) is also more competitive than other state-of-the-art segmentation algorithms.In order to segment different types of lung nodules accurately, we propose an improved U-Net network, which can improve the segmentation accuracy effectively. Moreover, this work also has practical value in helping radiologists segment lung nodules and diagnose lung cancer.

Integrating ecosystem services modeling into effectiveness assessment of national protected areas in a typical arid region in China.

Protected areas (PAs) are essential for biodiversity conservation and for the delivery of ecosystem services (ESs). However, little is known about their effectiveness in providing ESs and contribution to species richness, especially in arid regions. Effectiveness evaluation is fundamental to understanding the extent of management enhancement required to fulfill conservation targets. In this study, we analyzed the supply of six ESs (water yield, nutrient retention, soil retention, sand fixation, carbon storage, and biodiversity richness) by landscapes in China's arid region of Xinjiang Uygur Autonomous Region (hereafter Xinjiang). The aim was to identify distribution of ESs hotspots and the extent of hotspots located within or outside national PAs. The results showed significant spatial heterogeneity and coverage differences in six types of ESs hotspots. Hotspots coverage of six ESs on average accounted for 10.45 % of the total area, distributed mainly in mountains and oases covered by vegetation and wetlands. Among these ESs hotspots, over 50 % fell within PAs. This suggested that although PAs delivered moderately well outcomes in preserving ESs and biodiversity in Xinjiang, conservation gaps needed to be addressed. Our study also revealed substantial differences in ESs supplied by different PAs, and serious deficiency existed in some PAs in protecting either biodiversity or key ESs outlined in their conservation objectives. Our study illustrated the priority areas for future conservation expansion and stressed the urgent shift toward broadening the goals of PAs from a dominant focus to ones that encompass multiple ESs for human well-being.

Magnetic resonance imaging reconstruction algorithm under complex convolutional neural network in diagnosis and prognosis of cerebral infarction.

This study was to explore the application value of magnetic resonance imaging (MRI) image reconstruction model based on complex convolutional neural network (CCNN) in the diagnosis and prognosis of cerebral infarction. Two image reconstruction methods, frequency domain reconstruction network (FDRN) and image domain reconstruction network (IDRN), were introduced based on the CCNN algorithm. In addition, they were integrated to form two new MRI image reconstruction models, namely D-FDRN and D-IDRN. The peak signal to noise ratio (PSNR) value and structural similarity index measure (SSIM) value of the image were compared and analyzed before and after the integration. The MRI images of patients with cerebral infarction in the dataset were undertaken as the data source, the average diffusion coefficient (DCavg) and apparent diffusion coefficient (ADC) values of different parts of the MRI image were measured, respectively. The correlation of the vein abnormality grading (VABG) to the infarct size and the degree of stenosis of the responsible vessel was analyzed in this study. The results showed that the PSNR and SSIM values of the MRI reconstructed image of the D-IDRN algorithm based on the CCNN algorithm in this study were higher than those of other algorithms. There was a positive correlation between the VABG and the infarct size (r = 0.48 and P = 0.002), and there was a positive correlation between the VABG the degree of stenosis of the responsible vessel (r = 0.58 and P < 0.0001). The ADC value of the central area of the infarct on the affected side was significantly greatly lower than that of the normal side (P < 0.01), and the DCavg value of the central area of the infarct was much lower in contrast to the normal side (P < 0.05). It indicated that an image reconstruction algorithm constructed in this study could improve the quality of MRI images. The ADC value and DCavg value changed in the infarct central area could be used as the basis for the diagnosis of cerebral infarction. If the vein was abnormal, the patient suffered from severe vascular stenosis, large infarction area, and poorer prognosis.

Differentiation Between Ependymoma and Medulloblastoma in Children with Radiomics Approach.

RATIONALE AND OBJECTIVES: Ependymoma (EP) and medulloblastoma (MB) of children are similar in age, location, manifestations and symptoms. Therefore, it is difficult to differentiate them through visual observation in clinical diagnosis. The aim of this study is to investigate the effectiveness of radiomics and machine-learning techniques on multimodal magnetic resonance imaging (MRI) in distinguish EP from MB. MATERIALS AND METHODS: Three dimensional (3D) tumors were semi-automatic segmented by radiologists from postcontrast T1-weighted images and apparent diffusion coefficient maps in 51 patients (24 EPs, 27 MBs). Then, we extracted radiomics features and further reduced them by three feature selection methods. For each feature selection method, 4 classifiers were adopted which yield 12 different models. After extensive crossvalidation, pairwise test were carried out in receiver operating characteristic curves to explore performance of these models. RESULTS: The radiomics model built with multivariable logistic regression as feature selection method and random forests as classifier had the best performance, area under the curve achieved 0.91 (95 % confidence interval 0.787-0.968). Five relevant features were highly correlated to discriminate EP and MB, which may used as imaging biomarkers to predict the kinds of tumors. CONCLUSION: The combination of radiomics and machine-learning approach on 3D multimodal MRI could well distinguish EP and MB of childhood, which assistant doctors in clinical diagnosis. Since there is no uniform model to obtained best performance for every specific data set, it is necessary to try different combination methods.

Capsaicin alleviates acetaminophen-induced acute liver injury in mice.

Overdose of N-acetyl-para-aminophenol (APAP) can induce acute liver injury (ALI). We evaluated the potential protective effect of 8-methyl-N-geranyl-6-nonamide (capsaicin (CAP)) in APAP-induced ALI in mice. ALI was induced by APAP (150 mg/kg, i.p.) administration; CAP pretreatment (1 mg/kg) was undertaken before APAP injection for 3 consecutive days. We found that CAP pretreatment attenuated ALI significantly; improve the oxidative stress-associated indicators (hepatic expression of malondialdehyde (MDA) superoxide dismutase (SOD) and glutathione (GSH)); downregulate expression of proinflammatory cytokines (interleukin (IL)-6, IL-1ß, tumor necrosis factor-α) through the high-mobility group box 1/toll-like receptor-4/nuclear factor-kappa B (HMGB1/TLR4/NF-κB) signaling pathway; alleviate hepatocyte apoptosis by inhibiting expression of B-cell lymphoma-2-associated X, caspase-3 and cleaved caspase-3. CAP pretreatment reduced expression of B-cell lymphoma-2, which served as a hepatotoxic factor rather than an anti-apoptotic protein in our mouse model. We propose that CAP can alleviate APAP-induced ALI by inhibiting the inflammatory response, attenuating oxidative stress, and reducing hepatocyte apoptosis.

[A method of calculating left ventricular functional parameter using gated SPECT myocardial imaging].

Based on the half sphere-cylinder myocardial model, a quantitative calculating method of gated SPECT myocardial infraction of the left ventricular functional parameters is proposed. To overcome the shortage of the ellipse model and other normal methods, this method uses the half sphere-cylinder myocardial model and its subarea. The experiment result shows that the data from normal men accord very well with those reported in domestic and international literature. The result from use in the case of left ventricular myocardial infarction is also satisfactory. Therefore, this method is of high value clinically.