Design and Implementation of a Hybrid Optical Camera Communication System for Indoor Applications.

Optical wireless communication is a promising emerging technology that addresses the limitations of radio-frequency-based wireless technologies. This study presents a new hybrid modulation method for optical camera communication (OCC), which integrates two waveforms transmitted from a single transmitter light-emitting diode (LED) and receives data through two rolling shutter camera devices on the receiver side. Then, a smart camera with a high-resolution image sensor captures the high-frequency signal, and a low-resolution image sensor from a smartphone camera captures the low-frequency signal. Based on this hybrid scheme, two data streams are transmitted from a single LED, which reduces the cost of the indoor OCC device compared with transmitting two signals from two different LEDs. In the proposed scheme, rolling-shutter orthogonal frequency-division multiplexing is used for the high-frequency signals, and M-ary frequency-shift keying is used for the low-frequency signals in the time domain. This proposed scheme is compatible with smartphone and USB cameras. By controlling the OCC parameters, the hybrid scheme can be implemented with high performance for a communication distance of 10 m.

Autistic-like behavior and cerebellar dysfunction in Bmal1 mutant mice ameliorated by mTORC1 inhibition.

Although circadian and sleep disorders are frequently associated with autism spectrum disorders (ASD), it remains elusive whether clock gene disruption can lead to autistic-like phenotypes in animals. The essential clock gene Bmal1 has been associated with human sociability and its missense mutations are identified in ASD. Here we report that global Bmal1 deletion led to significant social impairments, excessive stereotyped and repetitive behaviors, as well as motor learning disabilities in mice, all of which resemble core behavioral deficits in ASD. Furthermore, aberrant cell density and immature morphology of dendritic spines were identified in the cerebellar Purkinje cells (PCs) of Bmal1 knockout (KO) mice. Electrophysiological recordings uncovered enhanced excitatory and inhibitory synaptic transmission and reduced firing rates in the PCs of Bmal1 KO mice. Differential expression of ASD- and ataxia-associated genes (Ntng2, Mfrp, Nr4a2, Thbs1, Atxn1, and Atxn3) and dysregulated pathways of translational control, including hyperactivated mammalian target of rapamycin complex 1 (mTORC1) signaling, were identified in the cerebellum of Bmal1 KO mice. Interestingly, the antidiabetic drug metformin reversed mTORC1 hyperactivation and alleviated major behavioral and PC deficits in Bmal1 KO mice. Importantly, conditional Bmal1 deletion only in cerebellar PCs was sufficient to recapitulate autistic-like behavioral and cellular changes akin to those identified in Bmal1 KO mice. Together, these results unveil a previously unidentified role for Bmal1 disruption in cerebellar dysfunction and autistic-like behaviors. Our findings provide experimental evidence supporting a putative role for dysregulation of circadian clock gene expression in the pathogenesis of ASD.

Long-Time Oxygen and Superoxide Localization in Arabidopsis thaliana Cryptochrome.

Cryptochromes are proteins that are highly conserved across species and in many instances bind the flavin adenine dinucleotide (FAD) cofactor within their photolyase-homology region (PHR) domain. The FAD cofactor has multiple redox states that help catalyze reactions, and absorbs photons at about 450 nm, a feature linked to the light-related functions of cryptochrome proteins. Reactive oxygen species (ROS) are produced from redox reactions involving molecular oxygen and are involved in a myriad of biological processes. Superoxide O2•- is an exemplary ROS that may be formed through electron transfer from FAD to O2, generating an electron radical pair. Although the formation of a superoxide-FAD radical pair has been speculated, it is still unclear if the required process steps could be realized in cryptochrome. Here, we present results from molecular dynamics (MD) simulations of oxygen interacting with the PHR domain of Arabidopsis thaliana cryptochrome 1 (AtCRY1). Using MD simulation trajectories, oxygen binding locations are characterized through both the O2-FAD intermolecular distance and the local protein environment. Oxygen unbinding times are characterized through replica simulations of the bound oxygen. Simulations reveal that oxygen molecules can localize at certain sites within the cryptochrome protein for tens of nanoseconds, and superoxide molecules can localize for significantly longer. This relatively long-duration molecule binding suggests the possibility of an electron-transfer reaction leading to superoxide formation. Estimates of electron-transfer rates using the Marcus theory are performed for the identified potential binding sites. Molecular oxygen binding results are compared with recent results demonstrating long-time oxygen binding within the electron-transfer flavoprotein (ETF), another FAD binding protein.

AI-based classification of three common malignant tumors in neuro-oncology: A multi-institutional comparison of machine learning and deep learning methods.

PURPOSE: To determine if machine learning (ML) or deep learning (DL) pipelines perform better in AI-based three-class classification of glioblastoma (GBM), intracranial metastatic disease (IMD) and primary CNS lymphoma (PCNSL). METHODOLOGY: Retrospective analysis included 502 cases for training (208 GBM, 67 PCNSL and 227 IMD), with external validation on 86 cases (27:27:32). Multiparametric MRI images (T1W, T2W, FLAIR, DWI and T1-CE) were co-registered, resampled, denoised and intensity normalized, followed by semiautomatic 3D segmentation of the enhancing tumor (ET) and peritumoral region (PTR). Model performance was assessed using several ML pipelines and 3D-convolutional neural networks (3D-CNN) using sequence specific masks, as well as combination of masks. All pipelines were trained and evaluated with 5-fold nested cross-validation on internal data followed by external validation using multi-class AUC. RESULTS: Two ML models achieved similar performance on test set, one using T2-ET and T2-PTR masks (AUC: 0.885, 95% CI: [0.816, 0.935] and another using T1-CE-ET and FLAIR-PTR mask (AUC: 0.878, CI: [0.804, 0.930]). The best performing DL models achieved an AUC of 0.854, (CI [0.774, 0.914]) on external data using T1-CE-ET and T2-PTR masks, followed by model derived from T1-CE-ET, ADC-ET and FLAIR-PTR masks (AUC: 0.851, CI [0.772, 0.909]). CONCLUSION: Both ML and DL derived pipelines achieved similar performance. T1-CE mask was used in three of the top four overall models. Additionally, all four models had some mask derived from PTR, either T2WI or FLAIR.

Microplastic accumulation in bivalves collected from different coastal areas of Vietnam and an assessment of potential risks.

Microplastic (MP) pollution is an emerging problem in many areas around the world and in coastal areas of Vietnam, requiring more studies dedicated to the accumulation of this pollutant in the food chain as well as its potential risk to human health. This study investigated MP levels in tissues of five common bivalve species collected from aquaculture areas along the coast of Vietnam. MPs were found in all bivalve samples, with average values of 10.84 ± 2.61 items/individual or 2.40 ± 1.34 items/g wet weight. Impacts of feeding habits of bivalves showed influences on MP abundance in the samples. Fibers were the dominant shape of MPs recorded, most of which accumulated in the gills and digestive glands of all bivalve samples, with the majority falling within the size range of 300-2000 µm. MPs found in all studied species had relatively similar chemical compositions, mainly composed of polypropylene (PP) and polyethylene (PE). In this study, a diverse diet consisting of different bivalve species and detailed data on the consumption rate of these species were used to assess the human health risk of MPs dedicated to the coastal communities of Vietnam. The results suggested a significant part of MP uptake by human could be via bivalve consumption, in which removing viscera and proper depuration should be applied prior to eating, thereby reducing the risk.

Circadian activities of the brain MNK-eIF4E signalling axis contribute to diurnal rhythms of some cognitive functions.

Although it is well recognized that the circadian timing system profoundly influences cognitive performance, the underlying molecular mechanisms remain poorly defined. Our previous work has found that the mitogen-activated protein kinase-interacting kinase (MNK)-eukaryotic translation initiation factor 4E (eIF4E) axis, a conserved cellular signalling pathway regulating mRNA translation, modulates the function of the suprachiasmatic nucleus (SCN), the master circadian clock. Here, with the use of a combination of genetic, biochemical and behavioural approaches, we investigated the distribution and temporal regulation of eIF4E phosphorylation in the brain and its role in regulating the diurnal oscillations of some aspects of cognition in mice. We found that activities of the MNK-eIF4E axis, as indicated by the level of eIF4E phosphorylation at Ser209, exhibited significant circadian oscillations in a variety of brain regions, including but not limited to the prefrontal cortex, the hippocampus, the amygdala and the cerebellum. Phosphorylated eIF4E was enriched in neurons but not in astrocytes or microglia. Mice lacking eIF4E phosphorylation (eIF4ES209A/S209A ) or the MNKs (Mnk1-/-,2-/- ), the kinases that phosphorylate eIF4E, exhibited impaired diurnal variations of novel object recognition, object location memory, Barnes maze learning and ambulatory activities. Together, these results suggest that circadian activities of the MNK-eIF4E axis contribute to the diurnal rhythms of some cognitive functions, highlighting a role for rhythmic translational control in circadian regulation of cognitive performance.

Long-Time Oxygen Localization in Electron Transfer Flavoprotein.

Reactive oxygen species (ROS) exert a wide range of biological effects from beneficial regulatory function to deleterious oxidative stress. The electron transfer flavoprotein (ETF) is ubiquitous to life and is associated with aerobic metabolism and ROS production due to its location in the mitochondria. Quantifying oxygen localization within the ETF complex is critical for understanding the potential for electron transfer and radical pair formation between flavin adenine dinucleotide (FAD) cofactor and superoxide during ROS formation. Our study employed all-atom molecular dynamics simulations and identified several novel, long-lived oxygen binding sites within the ETF complex that appear near the FAD cofactor. Site locations, the local electrostatic environment, and characteristic oxygen binding times for each site were evaluated to establish factors that may lead to possible charge transfer reactions and superoxide formation within the ETF complex. The study revealed that some oxygen binding sites are naturally linked to protein domain features, suggesting opportunities to engineer and control ROS production and subsequent dynamics.

Haploinsufficiency of a Circadian Clock Gene Bmal1 (Arntl or Mop3) Causes Brain-Wide mTOR Hyperactivation and Autism-like Behavioral Phenotypes in Mice.

Approximately 50-80% of children with autism spectrum disorders (ASDs) exhibit sleep problems, but the contribution of circadian clock dysfunction to the development of ASDs remains largely unknown. The essential clock gene Bmal1 (Arntl or Mop3) has been associated with human sociability, and its missense mutation is found in ASD. Our recent study found that Bmal1-null mice exhibit a variety of autism-like phenotypes. Here, we further investigated whether an incomplete loss of Bmal1 function could cause significant autism-like behavioral changes in mice. Our results demonstrated that heterozygous Bmal1 deletion (Bmal1+/-) reduced the Bmal1 protein levels by ~50-75%. Reduced Bmal1 expression led to decreased levels of clock proteins, including Per1, Per2, Cry 1, and Clock but increased mTOR activities in the brain. Accordingly, Bmal1+/- mice exhibited aberrant ultrasonic vocalizations during maternal separation, deficits in sociability and social novelty, excessive repetitive behaviors, impairments in motor coordination, as well as increased anxiety-like behavior. The novel object recognition memory remained intact. Together, these results demonstrate that haploinsufficiency of Bmal1 can cause autism-like behavioral changes in mice, akin to those identified in Bmal1-null mice. This study provides further experimental evidence supporting a potential role for disrupted clock gene expression in the development of ASD.

Radiomics-based differentiation between glioblastoma and primary central nervous system lymphoma: a comparison of diagnostic performance across different MRI sequences and machine learning techniques.

OBJECTIVES: Despite the robust diagnostic performance of MRI-based radiomic features for differentiating between glioblastoma (GBM) and primary central nervous system lymphoma (PCNSL) reported on prior studies, the best sequence or a combination of sequences and model performance across various machine learning pipelines remain undefined. Herein, we compare the diagnostic performance of multiple radiomics-based models to differentiate GBM from PCNSL. METHODS: Our retrospective study included 94 patients (34 with PCNSL and 60 with GBM). Model performance was assessed using various MRI sequences across 45 possible model and feature selection combinations for nine different sequence permutations. Predictive performance was assessed using fivefold repeated cross-validation with five repeats. The best and worst performing models were compared to assess differences in performance. RESULTS: The predictive performance, both using individual and a combination of sequences, was fairly robust across multiple top performing models (AUC: 0.961-0.977) but did show considerable variation between the best and worst performing models. The top performing individual sequences had comparable performance to multiparametric models. The best prediction model in our study used a combination of ADC, FLAIR, and T1-CE achieving the highest AUC of 0.977, while the second ranked model used T1-CE and ADC, achieving a cross-validated AUC of 0.975. CONCLUSION: Radiomics-based predictive accuracy can vary considerably, based on the model and feature selection methods as well as the combination of sequences used. Also, models derived from limited sequences show performance comparable to those derived from all five sequences. KEY POINTS: • Radiomics-based diagnostic performance of various machine learning models for differentiating glioblastoma and PCNSL varies considerably. • ML models using limited or multiple MRI sequences can provide comparable performance, based on the chosen model. • Embedded feature selection models perform better than models using a priori feature reduction.

A model for global surgical training and capacity development: the Children's of Alabama-Viet Nam pediatric neurosurgery partnership.

INTRODUCTION: Training capable and competent neurosurgeons to work in underserved regions of the world is an essential component of building global neurosurgical capacity. One strategy for achieving this goal is establishing longitudinal partnerships between institutions in low- and middle-income countries (LMICs) and their counterparts in high-income countries (HICs) utilizing a multi-component model. We describe the initial experience of the Children's of Alabama (COA) Global Surgery Program partnership with multiple Vietnamese neurosurgical centers. METHODS: The training model developed by the COA Global Surgery Program utilizes three complementary and interdependent methods to expand neurosurgical capacity: in-country training, out-of-country training, and ongoing support and mentorship. Multiple Vietnamese hospital systems have participated in the partnership, including three hospitals in Hanoi and one hospital in Ho Chi Minh City. RESULTS: During the 7 years of the partnership, the COA and Viet Nam teams have collaborated on expanding pediatric neurosurgical care in numerous areas of clinical need including five subspecialized areas of pediatric neurosurgery: cerebrovascular, epilepsy, neuroendoscopy for hydrocephalus management, craniofacial, and neuro-oncology. CONCLUSION: Long-term partnerships between academic departments in LMICs and HICs focused on education and training are playing an increasingly important role in scaling up global surgical capacity. We believe that our multi-faceted approach consisting of in-country targeted hands-on training, out-of-country fellowship training at the mentor institution, and ongoing mentorship using telecollaboration and Internet-based tools is a viable and generalizable model for enhancing surgical capacity globally.

Confinement effects on the solar thermal heating process of TiN nanoparticle solutions.

We propose a theoretical approach to describe quantitatively the heating process in aqueous solutions of dispersed TiN nanoparticles under solar illumination. The temperature gradients of the solution with different concentrations of the TiN nanoparticles are calculated when confinement effects of the container on the solar absorption are taken into account. We find that the average penetration of solar radiation into the solution is significantly reduced upon increasing the nanoparticle concentration. At high concentrations, our numerical results show that photons are localized near the surface of the solution. Moreover, the heat energy balance equation at the vapor-liquid interface is used to describe the solar steam generation. The theoretical time dependence of temperature rise and vaporization weight losses is consistent with experiments. Our calculations give strong evidence that the substantially localized heating near the vapor-liquid interface is the main reason for the more efficient steam generation process by floating plasmonic membranes when compared to randomly dispersed nanoparticles. The validated theoretical model suggests that our approach can be applied towards new predictions and other experimental data descriptions.

Photography Trilateration Indoor Localization with Image Sensor Communication.

Localization has become an important aspect in a wide range of mobile services with the integration of the Internet of things and service on demand. Numerous mechanisms have been proposed for localization, most of which are based on the estimation of distances. Depending on the channel modeling, each mechanism has its advantages and limitations on deployment, exhibiting different performances in terms of error rates and implementation. With the development of technology, these limitations are rapidly overcome with hybrid systems and enhancement schemes. The successful approach depends on the achievement of a low error rate and its controllability by the integration of deployed products. In this study, we propose and analyze a new distance estimation technique employing photography and image sensor communications, also named optical camera communications (OCC). It represents one of the most important steps in the implemented trilateration localization scheme with real architectures and conditions of deployment which is the second our contribution for this article. With the advantages of the image sensor hardware integration in smart mobile devices, this technology has great potential in localization-based optical wireless communication.

Reduced effects of age on dopamine D2 receptor levels in physically active adults.

Physical activity has been shown to ameliorate dopaminergic degeneration in non-human animal models. However, the effects of regular physical activity on normal age-related changes in dopamine function in humans are unknown. Here we present cross-sectional data from forty-four healthy human subjects between 23 and 80 years old, showing that typical age-related dopamine D2 receptor loss, assessed with PET [18F]fallypride, was significantly reduced in physically active adults compared to less active adults.

A comparison of symptoms and quality of life between medial flap and coblation turbinator of inferior turbinate reduction in endoscopic septoturbinoplasty: an analysis of 108 cases.

Introduction: The combination of septoplasty and turbinoplasty is a common surgical and accepted intervention to correct the nasal obstruction. The coblation submucosal reduction turbinator is a new surgical device, and it started to be used recently. On the other hand, the medial flap inferior turbinoplasty is not a conservative technique, but it provides a reliable and robust reduction. Objective: This study aims to compare the symptoms as well as health-related quality of life (HQOL) in 55 patients who underwent septoplasty with concomitent medial flap inferior turbinoplasty (group 1), 53 patients who patients underwent septoplasty with concomitent coblation turbinator (group 2). Patients and methods: The authors performed a prospective, randomized study of 108 patients who consulted the otorhinolaryngology department at the university hospital for surgery of septoturbinoplasty. Results: Preoperatively, the two patient groups had quite similar symptoms and health-related quality of life, and the anterior width of the inferior turbinate showed significant differences between the contralateral and deviated sides but not the posterior part. The significant difference (P<0.05) was noted for postoperatively improved symptom scores on visual analogue scale (VAS), nasal obstruction septoplasty effectiveness (NOSE) and better HQOL [Sino-Nasal Outcome Test-22 (SNOT-22)] in all patient groups. In addition, the NOSE and SNOT-22 scores in group 2 had significantly greater improvement than group 1 (P<0.05). Conclusions: Septoturbinoplasty treatment of septum deviation and inferior turbinate hypertrophy led to less symptoms as well as better HQOL for all two patient groups. Therefore, these techniques were an effective intervention for turbinate reduction, and they are equally efficient in the long term.

Antimicrobial Resistance Patterns of Common Gram-Negative Microorganisms Isolated from Patients with Lower Respiratory Tract Infections in a Teaching Hospital in Vietnam.

This cross-sectional study investigated the antimicrobial resistance (AMR) patterns of gram-negative pathogens isolated from 4,789 hospitalized patients with lower respiratory tract infections (LRTIs). Of the collected specimens, 1,325 (27.7%) tested positive for gram-negative bacteria. Acinetobacter baumannii (38.6%), Pseudomonas aeruginosa (33.5%), Klebsiella pneumoniae (18.7%), Escherichia coli (5.6%), and Klebsiella aerogenes (3.5%) were the most prevalent isolates. AMR analysis revealed high resistance rates (79.9%-100%) of A. baumannii isolates to multiple classes of antibiotics except amikacin, trimethoprim/sulfamethoxazole, and colistin. P. aeruginosa displayed low resistance to colistin (< 10%) but high resistance to other antibiotics. K. pneumoniae displayed high resistance rates of 90.0%-100.0% to most penicillins, whereas resistance rates were notably lower for colistin (7.1%) and amikacin (16.7%). K. aerogenes exhibited high resistance to various antibiotics and sensitivity to amikacin (95.1%), ampicillin (100.0%), and colistin (100.0%). E. coli isolates exhibited resistance to ampicillin (96.9%) and maximum sensitivity to several antibiotics. Our study identified significant AMR trends and highlighted the prevalence of multidrug-resistant strains (93.6% for K. aerogenes and 69.1%-92.4% for other isolates). These findings emphasize the urgent need for appropriate antibiotic management practices to combat AMR in gram-negative pathogens associated with LRTIs.

Transferable Force Field for Gallium Nitride Crystal Growth from the Melt Using On-The-Fly Active Learning.

Atomic-scale simulations of reactive processes have been stymied by two factors: the lack of a suitable semiempirical force field on one hand and the impractically large computational burden of using ab initio molecular dynamics on the other hand. In this paper, we use an "on-the-fly" active learning technique to develop a nonparameterized force field that, in essence, exhibits the accuracy of density functional theory and the speed of a classical molecular dynamics simulation. We developed a force field capable of capturing the crystallization of gallium nitride (GaN) during a novel additive manufacturing process featuring the reaction of liquid Ga and gaseous nitrogen precursors to grow crystalline GaN thin films. We show that this machine learning model is capable of producing a single force field that can model solid, liquid, and gas phases involved in the process. We verified our computational predictions against a range of experimental measurements relevant to each phase and against ab initio calculations, showing that this nonparametric force field produces properties with excellent accuracy as well as exhibits computationally tractable efficiency. The force field is capable of allowing us to simulate the solid-liquid coexistence interface and the crystallization of GaN from the melt. The development of this transferable force field opens the opportunity to simulate the liquid-phase epitaxial growth more accurately than before to analyze reaction and diffusion processes and ultimately to establish a growth model of the additive manufacturing process to create the gallium nitride thin films.

Advances in long-acting slow effective release antiretroviral therapies for treatment and prevention of HIV infection.

Adherence to daily oral antiretroviral therapy (ART) is a barrier to both treatment and prevention of human immunodeficiency virus (HIV) infection. To overcome limitations of life-long daily regimen adherence, long-acting (LA) injectable antiretroviral (ARV) drugs, nanoformulations, implants, vaginal rings, microarray patches, and ultra-long-acting (ULA) prodrugs are now available or in development. These medicines enable persons who are or at risk for HIV infection to be treated with simplified ART regimens. First-generation LA cabotegravir, rilpivirine, and lenacapavir injectables and a dapivirine vaginal ring are now in use. However, each remains limited by existing dosing intervals, ease of administration, or difficulties in finding drug partners. ULA ART regimens provide an answer, but to date, such next-generation formulations remain in development. Establishing the niche will require affirmation of extended dosing, improved access, reduced injection volumes, improved pharmacokinetic profiles, selections of combination treatments, and synchronization of healthcare support. Based on such needs, this review highlights recent pharmacological advances and a future treatment perspective. While first-generation LA ARTs are available for HIV care, they remain far from ideal in meeting patient needs. ULA medicines, now in advanced preclinical development, may close gaps toward broader usage and treatment options.

Improving the photoelectrochemical water splitting performance of CuO photocathodes using a protective CuBi2O4 layer.

A heterojunction photocathode of CuO and CuBi2O4 grown on an FTO substrate (FTO/CuO/CuBi2O4) was synthesized using hydrothermal method followed by spin coating and annealing to overcome the bottlenecks encountered by CuO in photoelectrochemical (PEC) water splitting application. The synthesis methods, morphological, structural properties, and composition of each sample under each synthesis condition are discussed in detail. The photocathode with 15 coating layers annealed at 450 °C exhibited the best PEC performance. Moreover, its current density reached 1.23 mA/cm2 under an applied voltage of - 0.6 V versus Ag/AgCl in a neutral electrolyte. Additionally, it exhibited higher stability than the bare CuO thin film. The bonding of CuBi2O4 on CuO resulted in close contact between the two semiconductors, helping the semiconductors support each other to increase the PEC efficiency of the photocathode. CuO acted as the electron-generating layer, and the CuBi2O4 layer helped minimize photocorrosion as well as transport the carriers to the electrode/electrolyte interface to accomplish the hydrogen evolution reaction.

Selective detection of HBV pre-genomic RNA in chronic hepatitis B patients using a novel RT-PCR assay.

In chronic hepatitis B (CHB) patients, quantification of HBV pgRNA in plasma has the potential to provide information on disease prognosis and liver injury or histopathology. However, current methods for detecting HBV pgRNA present technical difficulties due to the co-existence of HBV DNA in plasma samples. We have successfully established a novel one-step RT-PCR assay that allows selective quantification of HBV pgRNA. Two cohorts of participants were recruited for assay validation, including treatment-naïve patients with CHB and HBeAg-positive CHB patients who were treated with Tenofovir and monitored for 6 months to assess the predictive value of baseline HBV RNA for HBeAg seroclearance. Statistical analysis was performed using MedCalc version 20.019 software. The novel selective one-step RT-PCR assay for detecting HBV pgRNA was validated with a limit of detection of 100 copies/mL. The assay was able to selectively measure HBV pgRNA even in the presence of excess HBV rcDNA. In treatment-naïve CHB patients, HBV pgRNA levels were significantly lower than HBV DNA concentration. Serum HBV DNA levels and HBeAg status were positively associated with HBV pgRNA. Baseline serum HBV pgRNA levels were found to be strong predictors of HBeAg seroclearance after 6 months of Tenofovir treatment. The study presents a novel RT-PCR assay that allows accurate measurement of plasma HBV pgRNA in chronic hepatitis B patients, even in the presence of excess HBV DNA. The assay is highly selective and represents a significant advancement with potential for further breakthroughs in understanding the clinical significance of HBV pgRNA.

Differentiation Between Glioblastoma and Metastatic Disease on Conventional MRI Imaging Using 3D-Convolutional Neural Networks: Model Development and Validation.

RATIONALE AND OBJECTIVES: Imaging-based differentiation between glioblastoma (GB) and brain metastases (BM) remains challenging. Our aim was to evaluate the performance of 3D-convolutional neural networks (CNN) to address this binary classification problem. MATERIALS AND METHODS: T1-CE, T2WI, and FLAIR 3D-segmented masks of 307 patients (157 GB and 150 BM) were generated post resampling, co-registration normalization and semi-automated 3D-segmentation and used for internal model development. Subsequent external validation was performed on 59 cases (27 GB and 32 BM) from another institution. Four different mask-sequence combinations were evaluated using area under the curve (AUC), precision, recall and F1-scores. Diagnostic performance of a neuroradiologist and a general radiologist, both without and with the model output available, was also assessed. RESULTS: 3D-model using the T1-CE tumor mask (TM) showed the highest performance [AUC 0.93 (95% CI 0.858-0.995)] on the external test set, followed closely by the model using T1-CE TM and FLAIR mask of peri-tumoral region (PTR) [AUC of 0.91 (95% CI 0.834-0.986)]. Models using T2WI masks showed robust performance on the internal dataset but lower performance on the external set. Both neuroradiologist and general radiologist showed improved performance with model output provided [AUC increased from 0.89 to 0.968 (p = 0.06) and from 0.78 to 0.965 (p = 0.007) respectively], the latter being statistically significant. CONCLUSION: 3D-CNNs showed robust performance for differentiating GB from BMs, with T1-CE TM, either alone or combined with FLAIR-PTR masks. Availability of model output significantly improved the accuracy of the general radiologist.