Development and performance of SIAT bPET: a high-resolution and high-sensitivity MR-compatible brain PET scanner using dual-ended readout detectors.

PURPOSE: Positron emission tomography/magnetic resonance imaging (PET/MRI) is a powerful tool for brain imaging, but the spatial resolution of the PET scanners currently used for brain imaging can be further improved to enhance the quantitative accuracy of brain PET imaging. The purpose of this study is to develop an MR-compatible brain PET scanner that can simultaneously achieve a uniform high spatial resolution and high sensitivity by using dual-ended readout depth encoding detectors. METHODS: The MR-compatible brain PET scanner, named SIAT bPET, consists of 224 dual-ended readout detectors. Each detector contains a 26 × 26 lutetium yttrium oxyorthosilicate (LYSO) crystal array of 1.4 × 1.4 × 20 mm3 crystal size read out by two 10 × 10 silicon photomultiplier (SiPM) arrays from both ends. The scanner has a detector ring diameter of 376.8 mm and an axial field of view (FOV) of 329 mm. The performance of the scanner including spatial resolution, sensitivity, count rate, scatter fraction, and image quality was measured. Imaging studies of phantoms and the brain of a volunteer were performed. The mutual interferences of the PET insert and the uMR790 3 T MRI scanner were measured, and simultaneous PET/MRI imaging of the brain of a volunteer was performed. RESULTS: A spatial resolution of better than 1.5 mm with an average of 1.2 mm within the whole FOV was obtained. A sensitivity of 11.0% was achieved at the center FOV for an energy window of 350-750 keV. Except for the dedicated RF coil, which caused a ~ 30% reduction of the sensitivity of the PET scanner, the MRI sequences running had a negligible effect on the performance of the PET scanner. The reduction of the SNR and homogeneity of the MRI images was less than 2% as the PET scanner was inserted to the MRI scanner and powered-on. High quality PET and MRI images of a human brain were obtained from simultaneous PET/MRI scans. CONCLUSION: The SIAT bPET scanner achieved a spatial resolution and sensitivity better than all MR-compatible brain PET scanners developed up to date. It can be used either as a standalone brain PET scanner or a PET insert placed inside a commercial whole-body MRI scanner to perform simultaneous PET/MRI imaging.

Interaction of Interleukin 7 Receptor (IL7R) and IL6 Gene Polymorphisms with Smoking Associated with Susceptibility to Asthma in Chinese Han Adults.

BACKGROUND: the aim of this study was to investigate the relationship between the risk of asthma and multiple single nucleotide polymorphisms (SNPs) in interleukin 7 receptor (IL7R) and IL6 genes, as well as the gene- environment interactions. METHODS: This is a hospital- based case- control study. A total of 430 patients with asthma were continuously recruited. Four SNPs within IL7R and IL6 gene were genotyped by PCR based restriction fragment length polymorphism. The Hardy- Weinberg balance of all participants was tested by SNPstats. The best interaction combination of four SNPs in IL7R and IL6 genes and smoking was screened by generalized multifactor dimensionality reduction (GMDR). Logistic regression was used to test the association between four SNPs and asthma, and stratified analysis for rs1800795 gene-smoking interaction, synergy index (SI) was calculated. RESULTS: The rs1494558-G and rs1800795-C were associated with an increased risk of asthma, adjusted ORs (95% CI) was 1.81 (1.29-2.42) and 1.75 (1.20-2.28), respectively. GMDR indicated that the test accuracy for two-locus model involving rs1800795 and smoking was 0.5721, and the p = .011, the results providing evidence for rs1800795 gene-smoking interaction. The asthma risk was higher in smokers with GC or CC genotype than the sum of risks in subjects with smoking or GC or CC genotype alone, compared to the never smokers with GG genotype, the OR (95%CI) was 4.97 (3.01-7.24), and the synergy index (SI) was 1.68 (1.08-2.60). CONCLUSIONS: The rs1494558-G and rs1800795-C alleles, gene- environment interaction between rs1800795 and smoking were all associated with increased asthma risk.

Artificial Marker and MEMS IMU-Based Pose Estimation Method to Meet Multirotor UAV Landing Requirements.

The fully autonomous operation of multirotor unmanned air vehicles (UAVs) in many applications requires support of precision landing. Onboard camera and fiducial marker have been widely used for this critical phase due to its low cost and high effectiveness. This paper proposes a six-degrees-of-freedom (DoF) pose estimation solution for UAV landing based on an artificial marker and a micro-electromechanical system (MEMS) inertial measurement unit (IMU). The position and orientation of the landing maker are measured in advance. The absolute position and heading of the UAV are estimated by detecting the marker and extracting corner points with the onboard monocular camera. To achieve continuous and reliable positioning when the marker is occasionally shadowed, IMU data is fused by an extended Kalman filter (EKF). The error terms of the IMU sensor are modeled and estimated. Field experiments show that the positioning accuracy of the proposed system is at centimeter level, and the heading error is less than 0.1 degrees. Comparing to the marker-based approach, the roll and pitch angle errors decreased by 33% and 54% on average. Within five seconds of vision outage, the average drifts of the horizontal and vertical position were 0.41 and 0.09 m, respectively.

Prediction of subcellular location of apoptosis proteins by incorporating PsePSSM and DCCA coefficient based on LFDA dimensionality reduction.

BACKGROUND: Apoptosis is associated with some human diseases, including cancer, autoimmune disease, neurodegenerative disease and ischemic damage, etc. Apoptosis proteins subcellular localization information is very important for understanding the mechanism of programmed cell death and the development of drugs. Therefore, the prediction of subcellular localization of apoptosis protein is still a challenging task. RESULTS: In this paper, we propose a novel method for predicting apoptosis protein subcellular localization, called PsePSSM-DCCA-LFDA. Firstly, the protein sequences are extracted by combining pseudo-position specific scoring matrix (PsePSSM) and detrended cross-correlation analysis coefficient (DCCA coefficient), then the extracted feature information is reduced dimensionality by LFDA (local Fisher discriminant analysis). Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of the apoptosis proteins. The overall prediction accuracy of 99.7, 99.6 and 100% are achieved respectively on the three benchmark datasets by the most rigorous jackknife test, which is better than other state-of-the-art methods. CONCLUSION: The experimental results indicate that our method can significantly improve the prediction accuracy of subcellular localization of apoptosis proteins, which is quite high to be able to become a promising tool for further proteomics studies. The source code and all datasets are available at https://github.com/QUST-BSBRC/PsePSSM-DCCA-LFDA/ .

Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition.

Mitochondrion is important organelle of most eukaryotes and play an important role in participating in various life activities of cells. However, some functions of mitochondria can only be achieved in specific submitochondrial location, the study of submitochondrial locations will help to further understand the biological function of protein, which is a hotspot in proteomics research. In this paper, we propose a new method for protein submitochondrial locations prediction. Firstly, the features of protein sequence are extracted by combining Chou's pseudo-amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM). Then the extracted feature information is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict the protein submitochondrial locations. We obtained the ideal prediction results by jackknife test and compared with other prediction methods. The results indicate that the proposed method is significantly better than the existing research results, which can provide a new method to predict protein locations in other organelles. The source code and all datasets are available at https://github.com/QUST-BSBRC/PseAAC-PsePSSM-WD/ for academic use.

Evaluation of MIh Scoring System in Diagnosis of Obstructive Sleep Apnea Syndrome.

BACKGROUND The objective of the present study was to investigate whether the analysis of magnesium (Mg), high-sensitivity C-reactive protein (hsCRP), and ischemia-modified albumin (IMA) concentrations can be used as a non-invasive and convenient method for diagnosing obstructive sleep apnea syndrome (OSAS). MATERIAL AND METHODS After polysomnography, venous blood was collected from 33 patients with OSAS and 30 control individuals. Serum levels of Mg, hsCRP, and IMA were investigated. The relationship between these factors and apnea-hypopnea index (AHI) was analyzed using the Pearson correlation coefficient. The role of the factors was determined using a receiver operating characteristic (ROC) curve and multivariate logistic regression analysis. RESULTS The levels of hsCRP and IMA were significantly higher in patients with OSAS than in control subjects, while the levels of Mg were lower (P<0.05 for all). A significant correlation was noted between serum IMA (r=0.614; P<0.001) and hsCRP (r=0.453; P<0.001) levels and the AHI. The ROC showed that serum Mg (AUC=0.74(0.62-0.85)), hsCRP (AUC=0.77(0.65-0.87)), and IMA (AUC=0.78(0.66-0.87)) levels could be used as markers to diagnose OSAS. Moreover, our new model, MIh, which is obtained by multivariate analysis, yielded an AUC value of 0.93 (0.83-0.98). Continuous positive airway pressure (CPAP) treatment reversed the changes in the serum levels of Mg, hsCRP, and IMA. CONCLUSIONS Patients with OSAS show reduced serum Mg levels and elevated serum hsCRP and IMA levels. These observed alterations can be reversed by CPAP treatment. A novel model, named MIh, may be a promising tool for OSAS diagnosis.

Characterization of Large-Area SiPM Array for PET Applications.

The performance of an 8 × 8 array of 6.0 × 6.0 mm2 (active area) SiPMs was evaluated for PET applications using crystal arrays with different pitch sizes (3.4 mm, 1.5 mm, 1.35 mm and 1.2 mm) and custom designed five-channel front-end readout electronics (four channels for position information and one channel for timing information). The total area of this SiPM array is 57.4 × 57.4 mm2, and the pitch size is 7.2 mm. It was fabricated using enhanced blue sensitivity SiPMs (MicroFB-60035-SMT) with peak spectral sensitivity at 420 nm. The performance of the SiPM array was characterized by measuring flood histogram decoding quality, energy resolution, timing resolution and saturation at several bias voltages (from 25.0 V to 30.0 V in 0.5 V intervals) and two different temperatures (5 °C and 20 °C). Results show that the best flood histogram was obtained at a bias voltage of 28.0 V and 5 °C and an array of polished LSO crystals with a pitch as small as 1.2 mm can be resolved. No saturation was observed up to a bias voltage of 29.5 V during the experiments, due to adequate light sharing between SiPMs. Energy resolution and timing resolution at 5 °C ranged from 12.7 ± 0.8% to 14.6 ± 1.4 % and 1.58 ± 0.13 ns to 2.50 ± 0.44 ns, for crystal array pitch sizes of 3.4 mm and 1.2 mm respectively. Superior flood histogram quality, energy resolution and timing resolution were obtained with larger crystal array pitch sizes and at lower temperature. Based on our findings, we conclude that this large-area SiPM array can serve as a suitable photodetector for high-resolution small-animal PET or dedicated human brain PET scanners.

A Study of Position-Sensitive Solid-State Photomultiplier Signal Properties.

We present an analysis of the signal properties of a position-sensitive solid-state photomultiplier (PS-SSPM) that has an integrated resistive network for position sensing. Attractive features of PS-SSPMs are their large area and ability to resolve small scintillator crystals. However, the large area leads to a high detector capacitance, and in order to achieve high spatial resolution a large network resistor value is required. These inevitably create a low-pass filter that drastically slows what would be a fast micro-cell discharge pulse. Significant changes in the signal shape of the PS-SSPM cathode output as a function of position are observed, which result in a position-dependent time delay when using traditional time pick-off methods such as leading edge discrimination and constant fraction discrimination. The timing resolution and time delay, as a function of position, were characterized for two different PS-SSPM designs, a continuous 10 mm × 10 mm PS-SSPM and a tiled 2 × 2 array of 5 mm × 5 mm PS-SSPMs. After time delay correction, the block timing resolution, measured with a 6 × 6 array of 1.3 × 1.3 × 20 mm3 LSO crystals, was 8.6 ns and 8.5 ns, with the 10 mm PS-SSPM and 5 mm PS-SSPM respectively. The effect of crystal size on timing resolution was also studied, and contrary to expectation, a small improvement was measured when reducing the crystal size from 1.3 mm to 0.5 mm. Digital timing methods were studied and showed great promise for allowing accurate timing by implementation of a leading edge time pick-off. Position-dependent changes in signal shape on the anode side also are present, which complicates peak height data acquisition methods used for positioning. We studied the effect of trigger position on signal amplitude, flood histogram quality, and depth-of-interaction resolution in a dual-ended readout detector configuration. We conclude that detector timing and positioning can be significantly improved by implementation of digital timing methods and by accounting for changes in the shape of the signals from PS-SSPMs.

Identification Drug Targets for Oxaliplatin-Induced Cardiotoxicity without Affecting Cancer Treatment through Inter Variability Cross-Correlation Analysis (IVCCA).

The successful treatment of side effects of chemotherapy faces two major limitations: the need to avoid interfering with pathways essential for the cancer-destroying effects of the chemotherapy drug, and the need to avoid helping tumor progression through cancer promoting cellular pathways. To address these questions and identify new pathways and targets that satisfy these limitations, we have developed the bioinformatics tool Inter Variability Cross-Correlation Analysis (IVCCA). This tool calculates the cross-correlation of differentially expressed genes, analyzes their clusters, and compares them across a vast number of known pathways to identify the most relevant target(s). To demonstrate the utility of IVCCA, we applied this platform to RNA-seq data obtained from the hearts of the animal models with oxaliplatin-induced CTX. RNA-seq of the heart tissue from oxaliplatin treated mice identified 1744 differentially expressed genes with False Discovery Rate (FDR) less than 0.05 and fold change above 1.5 across nine samples. We compared the results against traditional gene enrichment analysis methods, revealing that IVCCA identified additional pathways potentially involved in CTX beyond those detected by conventional approaches. The newly identified pathways such as energy metabolism and several others represent promising target for therapeutic intervention against CTX, while preserving the efficacy of the chemotherapy treatment and avoiding tumor proliferation. Targeting these pathways is expected to mitigate the damaging effects of chemotherapy on cardiac tissues and improve patient outcomes by reducing the incidence of heart failure and other cardiovascular complications, ultimately enabling patients to complete their full course of chemotherapy with improved quality of life and survival rates.

A Simple Capacitive Charge-Division Readout for Position-Sensitive Solid-State Photomultiplier Arrays.

A capacitive charge-division readout method for reading out a 2 × 2 array of 5 mm × 5 mm position-sensitive solid-state photomultipliers (PS-SSPM) was designed and evaluated. Using this analog multiplexing method, the 20 signals (16 position, 4 timing) from the PS-SSPM array are reduced to 5 signals (4 position, 1 timing), allowing the PS-SSPM array to be treated as an individual large-area PS-SSPM module. A global positioning approach can now be used, instead of individual positioning for each PS-SSPM in the array, ensuring that the entire light signal is utilized. The signal-to-noise ratio (SNR) and flood histogram quality at different bias voltages (27.5 V to 32.0 V at 0.5 V intervals) and a fixed temperature of 0 °C were evaluated by coupling a 6 × 6 array of 1.3 mm × 1.3 mm × 20 mm polished LSO crystals to the center of the PS-SSPM array. The timing resolution was measured at a fixed bias voltage of 31.0 V and a fixed temperature of 0 °C. All the measurements were evaluated and compared using capacitors with different values and tolerances. Capacitor values ranged from 0.051 nf to 10 nf, and the capacitance tolerance ranged from 1% to 20%. The results show that better performance was achieved using capacitors with smaller values and better capacitance tolerance. Using 0.2 nf capacitors, the SNR, energy resolution and timing resolution were 24.3, 18.2% and 8.8 ns at a bias voltage 31.0 V, respectively. The flood histogram quality was also evaluated by using a 10 × 10 array of 1 mm × 1 mm × 10 mm polished LSO crystals and a 10 × 10 array of 0.7 mm × 0.7 mm × 20 mm unpolished LSO crystals to determine the smallest crystal size resolvable. These studies showed that the high spatial resolution of the PS-SSPM was preserved allowing for 0.7 mm crystals to be identified. These results show that the capacitive charge-division analog signal processing method can significantly reduce the number of electronic channels, from 20 to 5, while retaining the excellent performance of the detector.

Technical opportunities and challenges in developing total-body PET scanners for mice and rats.

Positron emission tomography (PET) is the most sensitive in vivo molecular imaging technique available. Small animal PET has been widely used in studying pharmaceutical biodistribution and disease progression over time by imaging a wide range of biological processes. However, it remains true that almost all small animal PET studies using mouse or rat as preclinical models are either limited by the spatial resolution or the sensitivity (especially for dynamic studies), or both, reducing the quantitative accuracy and quantitative precision of the results. Total-body small animal PET scanners, which have axial lengths longer than the nose-to-anus length of the mouse/rat and can provide high sensitivity across the entire body of mouse/rat, can realize new opportunities for small animal PET. This article aims to discuss the technical opportunities and challenges in developing total-body small animal PET scanners for mice and rats.

Influence of TPU/EVA Phase Morphology Evolution on Supercritical Carbon Dioxide Extrusion Foaming.

Ethylene-vinyl acetate copolymer (EVA) was added at different contents to the thermoplastic polyurethane (TPU) matrix to form a non-compatible blending system, and foaming materials with high pore density were prepared using the supercritical carbon dioxide extrusion method. The influence of the phase morphology and crystal morphology of the TPU/EVA blend on its foaming behavior was studied. The results show that EVA changed the phase morphology and crystal morphology of the blends, leading to the improved melt viscosity and crystallinity of the blend system. At the same time, interfacial nucleation increases the density of cells and decreases the cell thickness and size, which is beneficial for improving the foaming properties of the blends. For the EVA content of 10% (mass fraction), the cell size is small (105.29 µm) and the cell density is the highest (3.74 × 106 cells/cm3). Based on the TPU/EVA phase morphology and crystal morphology, it is found that the sea-island structure of the blend has better foaming properties than the bicontinuous structure.

DRG Explant Model: Elucidating Mechanisms of Oxaliplatin-Induced Peripheral Neuropathy and Identifying Potential Therapeutic Targets.

Oxaliplatin triggered chemotherapy induced peripheral neuropathy (CIPN) is a common and debilitating side effect of cancer treatment which limits the efficacy of chemotherapy and negatively impacts patients quality of life dramatically. For better understanding the mechanisms of CIPN and screen for potential therapeutic targets, it is critical to have reliable in vitro assays that effectively mirror the neuropathy in vivo . In this study, we established a dorsal root ganglia (DRG) explant model. This model displayed dose-dependent inhibition of neurite outgrowth in response to oxaliplatin, while oxalic acid exhibited no significant impact on the regrowth of DRG. The robustness of this assay was further demonstrated by the inhibition of OCT2 transporter, which facilitates oxaliplatin accumulation in neurons, fully restoring the neurite regrowth capacity. Using this model, we revealed that oxaliplatin triggered a substantial increase of oxidative stress in DRG. Notably, inhibition of TXNIP with verapamil significantly reduced oxidative stress level. Our results demonstrated the use of DRG explants as an efficient model to study the mechanisms of CIPN and screen for potential treatments.

Toward peripheral nerve mechanical characterization using Brillouin imaging spectroscopy.

Significance: Peripheral nerves are viscoelastic tissues with unique elastic characteristics. Imaging of peripheral nerve elasticity is important in medicine, particularly in the context of nerve injury and repair. Elasticity imaging techniques provide information about the mechanical properties of peripheral nerves, which can be useful in identifying areas of nerve damage or compression, as well as assessing the success of nerve repair procedures. Aim: We aim to assess the feasibility of Brillouin microspectroscopy for peripheral nerve imaging of elasticity, with the ultimate goal of developing a new diagnostic tool for peripheral nerve injury in vivo. Approach: Viscoelastic properties of the peripheral nerve were evaluated with Brillouin imaging spectroscopy. Results: An external stress exerted on the fixed nerve resulted in a Brillouin shift. Quantification of the shift enabled correlation of the Brillouin parameters with nerve elastic properties. Conclusions: Brillouin microscopy provides sufficient sensitivity to assess viscoelastic properties of peripheral nerves.

Oxaliplatin-induced cardiotoxicity in mice is connected to the changes in energy metabolism in the heart tissue.

Oxaliplatin is a platinum-based alkylating chemotherapeutic agent used for cancer treatment. At high cumulative dosage, the negative effect of oxaliplatin on the heart becomes evident and is linked to a growing number of clinical reports. The aim of this study was to determine how chronic oxaliplatin treatment causes the changes in energy-related metabolic activity in the heart that leads to cardiotoxicity and heart damage in mice. C57BL/6 male mice were treated with a human equivalent dosage of intraperitoneal oxaliplatin (0 and 10 mg/kg) once a week for eight weeks. During the treatment, mice were followed for physiological parameters, ECG, histology and RNA sequencing of the heart. We identified that oxaliplatin induces strong changes in the heart and affects the heart's energy-related metabolic profile. Histological post-mortem evaluation identified focal myocardial necrosis infiltrated with a small number of associated neutrophils. Accumulated doses of oxaliplatin led to significant changes in gene expression related to energy related metabolic pathways including fatty acid (FA) oxidation, amino acid metabolism, glycolysis, electron transport chain, and NAD synthesis pathway. At high accumulative doses of oxaliplatin, the heart shifts its metabolism from FAs to glycolysis and increases lactate production. It also leads to strong overexpression of genes in NAD synthesis pathways such as Nmrk2. Changes in gene expression associated with energy metabolic pathways can be used to develop diagnostic methods to detect oxaliplatin-induced cardiotoxicity early on as well as therapy to compensate for the energy deficit in the heart to prevent heart damage.

Performance of Dual-Ended Readout PET Detectors Based on BGO Arrays and BaSO4 Reflector.

In this paper, the performance of two dual-ended readout PET detectors based on 15 × 15 BGO arrays were compared. The crystal elements of one BGO array have polished lateral surfaces, while the crystal elements of the other BGO array have unpolished lateral surfaces. The two ends of the BGO elements are polished. The two BGO arrays both have a pitch size of 1.6 mm and thickness of 20 mm, and BaSO4 with a thickness of 80 µm was used as the reflector. Hamamatsu S14161-0305-08 SiPM arrays were used as photodetectors. All the measurements were performed at a bias voltage of 41.0 V and a temperature of 23.5 °C. The flood histograms show that all the crystal elements in the two BGO arrays were clearly resolved. The detector based on the BGO array with polished lateral surfaces provides an energy resolution of 16.9 ± 1.3%, timing resolution of 3.2 ± 0.2 ns, and DOI resolution of 18.4 ± 2.2 mm. In comparison, the detector based on the BGO array with unpolished lateral surfaces provides an energy resolution of 17.7 ± 2.0%, timing resolution of 3.5 ± 0.3 ns, and DOI resolution of 3.2 ± 0.2 mm.

A Privacy-Preserving Cross-Domain Healthcare Wearables Recommendation Algorithm Based on Domain-Dependent and Domain-Independent Feature Fusion.

Recently, recommender systems are applied to provide personalized recomendation for healthcare wearables. However, due to the sparsity problem, traditional recommendation algorithms are difficult to achieve desired performance. Considering that consumers often buy and rate other types of items on E-commerce platforms, we can leverage significant information in the auxiliary domains to improve the recommendation performance of healthcare wearables, which can be regarded as cross-domain recommendation. However, traditional cross-domain recommendation model cannot fully represent user's characteristics and fail to consider the leaks of original auxiliary domain ratings during the information transfer process. To overcome the two shortcomings, this paper proposes a Privacy-Preserving Cross-Domain Healthcare Wearables Recommendation algorithm (PPCDHWRec). Firstly, user's characteristics are divided into domain-dependent features and domain-independent features, which complement each other and fully depict the user's characteristics. Secondly, inspired by the latent factor model, we factorize the original rating information of each auxiliary domain by Funk-SVD and Orthogonal Nonnegative Matrix Tri-Factorization (ONMTF) model, to obtain user's domain-dependent and domain-independent features, respectively. Finally, the Factorization Machine algorithm is used to fuse the obtained user's features with the target domain information to provide the recommendation results. By hiding the item latent factors obtained in the factorization process, PPCDHWRec ensures that the original information cannot be inferred from the transferred user hidden vector. Hence, PPCDHWRec is a privacy-preserving recommendation model. Experiments on two groups of auxiliary domains, having high and low correlations with target domain, show the effectiveness of PPCDHWRec.

Identification of prognostic biomarkers related to the tumor microenvironment in thyroid carcinoma.

Thyroid Carcinoma (THCA) is the most common endocrine tumor that is mainly treated using surgery and radiotherapy. In addition, immunotherapy is a recently developed treatment option that has played an essential role in the management of several types of tumors. However, few reports exist on the use of immunotherapy to treat THCA. The study downloaded the miRNA, mRNA and lncRNA data for THCA patients from the TCGA database ( https://portal.gdc.cancer.gov/ ). Thereafter, the tumor samples were divided into cold and hot tumors, based on the immune score of the tumor microenvironment. Moreover, the differentially expressed lncRNAs and miRNAs were obtained. Finally, the study jointly constructed a ceRNA network through differential analysis of the mRNA data for cold and hot tumors. The study first assessed the level of immune infiltration in the THCA tumor microenvironment then divided the samples into cold and hot tumors, based on the immune score. Additionally, a total of 568 up-regulated and 412 down-regulated DEGs were screened by analyzing the differences between hot and cold tumors. Thereafter, the study examined the differentially expressed genes for lncRNA and miRNA. The results revealed 629 differentially expressed genes related to lncRNA and 114 associated with miRNA. Finally, a ceRNA network of the differentially expressed genes was constructed. The results showed a five-miRNA hubnet, i.e., hsa-mir-204, hsa-mir-128, hsa-mir-214, hsa-mir-150 and hsa-mir-338. The present study identified the immune-related mRNA, lncRNA and miRNA in THCA then constructed a ceRNA network. These results are therefore important as they provide more insights on the immune mechanisms in THCA. The findings also provides additional information for possible THCA immunotherapy.

Performance evaluation of dual-ended readout PET detectors based on BGO arrays with different reflector arrangements.

OBJECTIVE: Dual-ended readout depth-encoding detectors based on bismuth germanate (BGO) scintillation crystal arrays are good candidates for high-sensitivity small animal positron emission tomography used for very-low-dose imaging. In this paper, the performance of three dual-ended readout detectors based on 15 × 15 BGO arrays with three different reflector arrangements and 8 × 8 silicon photomultiplier arrays were evaluated and compared. APPROACH: The three BGO arrays, denoted wo-ILG (without internal light guide), wp-ILG (with partial internal light guide), and wf-ILG (with full internal light guide), share a pitch size of 1.6 mm and thickness of 20 mm. Toray E60 with a thickness of 50µm was used as inter-crystal reflector. All reflector lengths in the wo-ILG and wf-ILG BGO arrays were 20 and 18 mm, respectively; the reflectors in the wp-ILG BGO array were 18 mm at the central region of the array and 20 mm at the edge. By using 18 mm reflectors, part of the crystals in the wp-ILG and wf-ILG BGO arrays worked as internal light guides. MAIN RESULTS: The results showed that the detector based on the wo-ILG BGO array provided the best flood histogram. The energy, timing and DOI resolutions of the three detectors were similar. The energy resolutions full width at half maximum (FWHM value) based on the wo-ILG, wp-ILG and wf-ILG BGO arrays were 27.2 ± 3.9%, 28.7 ± 4.6%, and 29.5 ± 4.7%, respectively. The timing resolutions (FWHM value) were 4.7 ± 0.5 ns, 4.9 ± 0.5 ns, and 5.0 ± 0.6 ns, respectively. The DOI resolution (FWHM value) were 3.0 ± 0.2 mm, 2.9 ± 0.2 mm, and 3.0 ± 0.2 mm, respectively. Over all, the wo-ILG detector provided the best performance.

Energy and electron drift time measurements in a pixel CCI TlBr detector with 1.3 MeV prompt-gammas.

Assessing the position of the Bragg peak (BP) in hadron radiotherapy utilizing prompt-gamma imaging (PGI) presents many challenges in terms of detector physics. Gamma detectors with the capability of extracting the best energy, timing, and spatial information from each gamma interaction, as well as with high detection efficiency and count rate performance, are needed for this application. In this work we present the characterization of a pixel Cerenkov charge induction (CCI) thallium bromide (TlBr) detector in terms of energy and and electron drift time for its potential use in PGI. The CCI TlBr detector had dimensions of 4 × 4 × 5 mm3 and one of its electrodes was segmented in pixels with 1.7 mm pitch. A silicon photomultiplier (SiPM) was optically coupled to one of the faces of the TlBr slab to read out the Cerenkov light promptly emitted after the interaction of a gamma ray. The detector was operated stand-alone and the 1.275 prompt gammas from a 22Na radioactive source were used for the study. The electron drift time was obtained by combining the Cerenkov and charge induction signals and then used as a measure of the depth of interaction. The electron mobility in TlBr was estimated as ∼27 cm2 V-1 s-1. Energy resolutions between 3.4% and 4.0% at 1.275 MeV were obtained after depth-correction. These values improved to 3.0%-3.3% when events with drift times of 3-6 µs were selected. These results show the potential of pixel CCI TlBr detectors to resolve gamma interactions in the detector with mm-like accuracy in 3D and with excellent energy resolution. Previous studies with CCI TlBr devices have shown a timing resolution of <400 ps full width at half maximum when detecting 511 keV gamma rays, therefore, the timing accuracy is expected to improve with the increased energy of the gamma rays in PGI. While other important detector characteristics such as count rate capability remain to be studied, results from this work combined with other preliminary data show pixel CCI detectors can simultaneously provide excellent energy, timing, and spatial resolution performance and are a very promising option for PGI in hadron therapy.