Trimethylamine from Subtropical Forests Rival Total Farmland Emissions in China.

Many types of living plants release gaseous trimethylamine (TMA), making it a potentially important contributor to new particle formation (NPF) in remote areas. However, a panoramic view of the importance of forest biogenic TMA at the regional scale is lacking. Here, we pioneered nationwide mobile measurements of TMA across a transect of contiguous farmland in eastern China and a transect of subtropical forests in southern China. In contrast to the farmland route, TMA concentrations measured during the subtropical forest route correlated significantly with isoprene, suggesting potential TMA emissions from leaves. Our high time-resolved concentrations obtained from a weak photo-oxidizing atmosphere reflected freshly emitted TMA, indicating the highest emission intensity from irrigated dryland (set as the baseline of 10), followed by paddy field (7.1), subtropical evergreen forests (5.9), and subtropical broadleaf and mixed forests (4.3). Extrapolating their proportions roughly to China, subtropical forests alone, which constitute half of the total forest area, account for nearly 70% of the TMA emissions from the nation's total farmland. Our estimates, despite the uncertainties, take the first step toward large-scale assessment of forest biogenic amines, highlighting the need for observational and modeling studies to consider this hitherto overlooked source of TMA.

Differentiation of Meningiomas and Gliomas by Amide Proton Transfer Imaging: A Preliminary Study of Brain Tumour Infiltration.

Background: Gliomas are more malignant and invasive than meningiomas. Objective: To distinguish meningiomas from low-grade/high-grade gliomas (LGGs/HGGs) using amide proton transfer imaging (APT) combined with conventional magnetic resonance imaging (MRI) and to explore the application of APT in evaluating brain tumour invasiveness. Materials and Methods: The imaging data of 50 brain tumors confirmed by pathology in patients who underwent APT scanning in our centre were retrospectively analysed. Of these tumors, 25 were meningiomas, 10 were LGGs, and 15 were HGGs. The extent of the tumour-induced range was measured on APT images, T2-weighted imaging (T2WI), and MRI enhancement; additionally, and the degree of enhancement was graded. Ratios (RAPT/T2 and RAPT/E) were obtained by dividing the range of changes observed by APT by the range of changes observed via T2WI and MR enhancement, respectively, and APTmean values were measured. The Mann-Whitney U test was used to compare the above measured values with the pathological results obtained for gliomas and meningiomas, the Kruskal-Wallis test was used to compare LGGs, HGGs and meningiomas, and Dunn's test was used for pairwise comparisons. In addition, receiver operating characteristic (ROC) curves were drawn. Results: The Mann-Whitney U test showed that APTmean (p=0.005), RAPT/T2 (p<0.001), and RAPT/E (p<0.001) values were statistically significant in the identification of meningioma and glioma. The Kruskal-Wallis test showed that the parameters APTmean, RAPT/T2, RAPT/E and the degree of enhancement are statistically significant. Dunn's test revealed that RAPT/T2 (p=0.004) and RAPT/E (p=0.008) could be used for the identification of LGGs and meningiomas. APTmean (p<0.001), RAPT/T2 (p<0.001), and RAPT/E (p<0.001) could be used for the identification of HGGs and meningiomas. APTmean (p<0.001) was statistically significant in the comparison of LGGs and HGGs. ROC curves showed that RAPT/T2 (area under the curve (AUC)=0.947) and RAPT/E (AUC=0.919) could be used to distinguish gliomas from meningiomas. Conclusion: APT can be used for the differential diagnosis of meningioma and glioma, but APTmean values can only be used for the differential diagnosis of HGGs and meningiomas or HGGs and LGGs. Gliomas exhibit more obvious changes than meningiomas in APT images of brain tissue; this outcome may be caused by brain infiltration.

Rosette-forming glioneuronal tumours: two case reports and a review of the literature.

Rosette-forming glioneuronal tumour (RGNT) is a rare central nervous system (CNS) neoplasm that typically arises in the fourth ventricle. It is even more uncommon to arise outside the midline. In this paper, we report two cases of RGNT: one located in the fourth ventricle (a typical site), and the other in the right cerebellar hemisphere (a rare site). Both cases were misdiagnosed on imaging, and the results were inconsistent with the pathological diagnosis. The aim of the article is to deepen medical practitioners' understanding of RGNT by learning from these two cases, summarising cases located in the cerebellar hemispheres and systematically reviewing RGNT.

MR imaging features of Lhermitte-Duclos disease: Case reports and literature review.

RATIONALE: Lhermitte-Duclos disease (LDD) is a rare tumor of the nervous system with a typical "tiger striped'" sign, but its features on functional magnetic resonance imaging (fMRI) are still inconclusive. PATIENT CONCERNS: To explore the characteristics of LDDs using fMRI. DIAGNOSES: We report 3 cases of pathologically confirmed LDDs. INTERVENTIONS: Three patients underwent brain tumor surgery. OUTCOMES: All the patients had a good prognosis. LESSONS: Magnetic resonance spectroscopy and susceptibility-weighted imaging combined with conventional MRI can be used to better diagnose LDDs. Perfusion-weighted imaging is not specific for distinguishing cerebellar tumors. The combined application of fMRI and conventional MRI can improve the accuracy of LDD diagnoses.

Transient partial regression of intracranial germ cell tumor in adult thalamus: A case report.

Background: Intracranial germ cell tumors (GCTs) are a relatively rare malignancy in clinical practice. Natural regression of this tumor is also uncommon. We describe a rare case of an intracranial GCT in the thalamus of an adult that showed spontaneous regression and recurrence after steroid therapy. Case description: A 38-year-old male patient's MRI of the head suggested space-occupying masses in the left thalamus and midbrain. MRI examination revealed demyelination or granulomatous lesions. After high dose steroid treatment, the symptoms improved. The lesions were significantly reduced on repeat MRI, and oral steroid therapy was continued after discharge. The patient's symptoms deteriorated 1 month prior to a re-examination with head MRI, which revealed that the mass within the intracranial space was larger than on the previous image. He revisited the Department of Neurosurgery of our hospital and underwent left thalamic/pontine mass resection on October 16, 2019, and the pathological results showed that the tumor was a GCT. Conclusion: Intracranial GCTs are rare in the adult thalamus but should be considered in the differential diagnosis. The intracranial GCT regression seen in this case may be a short-lived phenomenon arising from complex immune responses caused by the intervention.

Differential diagnosis of central lymphoma and high-grade glioma: dynamic contrast-enhanced histogram.

BACKGROUND: In clinical diagnosis, some central nervous system lymphomas (CNSL) are difficult to distinguish from high-grade gliomas (HGG). PURPOSE: To evaluate the diagnostic efficacy of the histogram analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) in the identification of CNSL and HGG. MATERIAL AND METHODS: In all, 43 patients diagnosed with HGG (n = 28) and CNSL (n = 15) by histopathology underwent DCE-MRI scanning. Differences in histogram parameters based on DCE-MRI between HGG and CNSL were analyzed by Mann-Whitney U test. In addition, receiver operating characteristic (ROC) analysis was performed. Short-term follow-up of patients was performed using Kaplan-Meier analysis to explore the survival rates of HGG and CNSL. RESULTS: For the ROC curve analysis, we demonstrate that the 10th percentile of Ktrans (area under the curve [AUC] = 0.912, sensitivity = 86.7%, specificity = 92.9%), Kep (AUC = 0.940, sensitivity = 93.3%, specificity = 79.6%), Ve (AUC = 0.907, sensitivity = 86.7%, specificity = 89.3%), and AUC (AUC = 0.904, sensitivity = 86.7%, specificity = 92.9%) were significantly different between the CNSL and HGG groups (P < 0.001), with high diagnostic efficiency. Table 2 shows that the histogram features based on AUC maps (10th, 25th, median, 75th, 90th, and mean) were always significantly higher in the CNSL group than in the HGG group (P < 0.001). There was no significant difference in Vp or in the 75th, 90th and mean of Ktrans, Kep, and Ve between the CNSL and HGG groups (P > 0.05). CONCLUSION: A histogram analysis of DCE-MRI identified significant differences between HGG and CNSL, and this will help in the clinical differential diagnosis of these conditions.

DSC and DCE Histogram Analyses of Glioma Biomarkers, Including IDH, MGMT, and TERT, on Differentiation and Survival.

RATIONALE AND OBJECTIVES: The World Health Organization 2016 classification of central nervous system tumors added the molecular classification of gliomas and has guiding significance for the operation and prognosis of glioma patients. At present, the perfusion technique plays an important role in judging the malignant degree of glioma. To evaluate the performance of dynamic susceptibility contrast (DSC)- and dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) histogram analyses in discriminating the states of molecular biomarkers and survival in glioma patients. MATERIALS AND METHODS: Forty-three glioma patients who underwent DCE- and DSC-MRI were enrolled. Relevant molecular test results, including those on isocitrate dehydrogenase (IDH), O6-methylguanine-DNA methyltransferase (MGMT) and telomere reverse transcriptase (TERT), were collected. The mean relative cerebral blood volume of DSC-MRI and histogram parameters derived from DCE-MRI (volume transfer coefficient (Ktrans), fractional volume of the extravascular extracellular space (Ve), fractional blood plasma volume (Vp), rate constant between the extravascular extracellular space and blood plasma (Kep) and area under the curve (AUC)) were calculated. Differences in each parameter between gliomas with different expression states (IDH, MGMT, and TERT) were evaluated. The diagnostic efficiency of each parameter was analyzed. The overall survival of all patients was assessed. RESULTS: The 10th percentile AUC (AUC = 0.830, sensitivity = 0.78, specificity = 0.80), the 90th percentile Ve (AUC = 0.816, sensitivity = 0.84, specificity = 0.79), and the mean Kep (AUC = 0.818, sensitivity = 0.76, specificity = 0.78) provided the highest differential efficiency for IDH, MGMT, and TERT, respectively. Kaplan-Meier curves showed a significant difference between subjects with a 10th percentile AUC higher or lower than 0.028 (log-rank = 7.535; p = 0.006) for IDH and between subjects with different 90th percentile Ve values (log-rank = 6.532; p = 0.011) for MGMT. CONCLUSION: Histogram DCE-MRI demonstrates good diagnostic performance in identifying different molecular types and for the prognostic assessment of glioma.