Sensitive Cancer Hypoxia Detection via a Dual-Locking Fluorescence Response System Using Two Hypoxia Indicators.

Hypoxia is intricately associated with various diseases, including ischemia, vascular disorders, and cancer. Particularly in cancer cells, hypoxia promotes tumor growth, cell proliferation, migration, and invasion and enhances treatment resistance, making its detection crucial for cancer diagnosis and therapy. However, methods for detecting hypoxia are limited, often relying on single-detection systems. In this study, we developed a dual-lock-based fluorescent probe that selectively exhibits strong green fluorescence under hypoxic conditions due to simultaneous activity of nitroreductases (NTRs) and hydrogen sulfide (H2S), with a high signal-to-background ratio. The biocompatibility and photophysical properties of the probes were thoroughly investigated through both extracellular and intracellular experimental analyses. Among the synthesized naphthalimide-based probes, the dual-detection probe DNNC demonstrated excellent selectivity and sensitivity to the simultaneous activity of NTR/H2S compared to other single-detection probes. The performance of DNNC was applied to various organ-derived cancer cells and tumor tissue models such as HeLa cell sparoids, enabling spatiotemporal confocal fluorescence imaging and quantitative analysis of hypoxic levels in cancer. Our development of DNNC is expected to significantly advance cancer diagnosis and treatment by molecularly detecting hypoxia associated with cancer aggressiveness, therapy resistance, and unfavorable prognosis.

Dual-Emissive Detection of ATP and Hypochlorite Ions for Monitoring Inflammation-Driven Liver Injury In Vitro and In Vivo.

Reactive oxygen species play a pivotal role in liver disease, contributing to severe liver damage and chronic inflammation. In liver injury driven by inflammation, adenosine-5'-triphosphate (ATP) and hypochlorite ion (ClO-) emerge as novel biomarkers, reflecting mitochondrial dysfunction and amplified oxidative stress, respectively. However, the dynamic fluctuations of ATP and ClO- in hepatocytes and mouse livers remain unclear, and multidetection techniques for these biomarkers are yet to be developed. This study presents RATP-NClO, a dual-channel fluorescent bioprobe capable of synchronously detecting ATP and ClO- ions. RATP-NClO exhibits excellent selectivity and sensitivity for ATP and ClO- ions, demonstrating a dual-channel fluorescence response in a murine hepatocyte cell line. Upon intravenous administration, RATP-NClO reveals synchronized ATP depletion and ClO- amplification in the livers of mice with experimental metabolic dysfunction-associated steatohepatitis (MASH). Through a comprehensive analysis of the principal mechanism of the developed bioprobe and the verification of its reliable detection ability in both in vitro and in vivo settings, we propose it as a unique tool for monitoring changes in intracellular ATP and ClO- level. These findings underscore its potential for practical image-based monitoring and functional phenotyping of MASH pathogenesis.

Quantitative phenotyping of verbal and non-verbal cognitive impairment using diffusion-weighted MRI connectome: Preliminary study of the crowding effect in children with left hemispheric epilepsy.

The "crowding" effect (CE), wherein verbal functions are preserved presumably at the expense of nonverbal functions, which diminish following inter-hemispheric transfer of language functions, is recognized as a specific aspect of functional reorganization, offering an insight about neural plasticity in children with neural insult to the dominant hemisphere. CE is hypothesized as a marker for language preservation or improvement after left-hemispheric injury, yet it remains challenging to fully discern it in preoperative evaluation. We present a novel DWI connectome (DWIC) approach to predict the presence of CE in 24 drug-resistant epilepsy (DRE) patients with a left-hemispheric focus and 29 young healthy controls. Psychometry-driven DWIC analysis was applied to create verbal and non-verbal modular networks. Local efficiency (LE) was assessed at individual regions of the two networks and its Z-score was compared to predict the presence of CE. Compared with a traditional organization (TO) group, wherein verbal functions are adversely affected, while non-verbal functions are preserved, the CE group showed significantly higher Z-scores in verbal network and significantly lower Z-scores in non-verbal network, corresponding to network reorganization in CE. A larger number of antiseizure drugs was significantly associated with more decreased Z-score in the right non-verbal network of the CE group and left verbal network of the TO group. These findings hold great potential to identify DRE patients whose verbal/language skills may over time be preserved due to effective inter-hemispheric reorganization and identify those whose verbal/language impairments may persist due to lack of inter-hemispheric reorganization.

Favorable clinical efficacy of cytotoxic chemotherapy in patients with progressive desmoid tumors: a retrospective real-world study.

BACKGROUND: The real-world evidence about the efficacy of cytotoxic chemotherapy in desmoid tumors is still limited. We investigated the efficacy of chemotherapy in the treatment of recurrent or progressive desmoid tumors. METHODS: The patients with desmoid tumors who had received cytotoxic chemotherapy between November 2007 and June 2020 in two tertiary hospitals in Korea were reviewed. RESULTS: A total of 25 patients were included in the analysis. The most common primary tumor site was the intra-abdominal or pelvic cavity (56%), followed by the trunk and abdominal wall (24%), extremities (16%), and head and neck (4%). Sixty percent of the patients had familial adenomatous polyposis and 76% received doxorubicin plus dacarbazine. The objective response rate and disease control rate was 64% (95% confidence interval [CI]: 40.7-82.8) and 96% (95% CI: 77.2-99.9), respectively. With the median follow-up time of 55 months (95% CI: 41.0-68.2), the 3-year PFS rate was 65% (95% CI: 41.1-80.5), and the 3-year OS rate was 89% (95% CI: 63.8-97.3). Grade 3 or 4 hematologic adverse events were reported in 14 patients, all of which were manageable. CONCLUSION: Our real-world evidence suggests that doxorubicin-based cytotoxic chemotherapy can be an effective treatment option for recurrent and progressive desmoid tumors with respect to favorable clinical outcomes.

Initial updosing phase of oral immunotherapy improves quality of life and psychological burden in parents of children with food allergy.

Background: Oral immunotherapy (OIT) can impose psychological burdens on patients and their parents due to the necessary preparations and repeated adverse reactions. Objective: To investigate changes in quality of life (QoL) and psychological burden in parents of children receiving OIT for food allergy (FA). Methods: Children aged 3-13 years with FA were enrolled. Parents were asked to fill out the Korean versions of the Food Allergy Quality of Life-Parental Burden (FAQL-PB), the Korean versions of the Food Allergy Quality of Life-Parental Form (K-FAQLQ-PF), the Korean versions of the Beck Anxiety Inventory (K-BAI), and the Korean version of the Patient Health Questionnaire-9 (PHQ-9) for depression before OIT (T1), after 2 months of updosing (T2), and after the end of the updosing phase (T3). Results: A total of 111 parents were enrolled. The total FAQL-PB scores were decreased at T2 and T3 compared with those at T1 (all p < 0.001). Greater improvement in the total FAQL-PB score at T2 was noted in parents with a higher parental burden (FAQL-PB score ≥ 74 points) at baseline than in those with a lower parental burden (p = 0.001). Among the K-FAQLQ-PF domains, "food anxiety" scores were decreased at T2 and T3 compared with those at T1 (p = 0.049 and p = 0.030, respectively), whereas there was no change in "social and dietary limitation" and "emotional impact" scores between T1 and T2 and between T1 and T3. However, no differences were observed in K-BAI and PHQ-9 scores between T1 and T2 and between T1 and T3. Conclusion: Our results suggest that OIT improves parental burden and QoL in parents of children with FA.

Home-based up-dosing of wheat oral immunotherapy: Real-world effectiveness and predictive factor analysis.

BACKGROUND: Wheat allergy is one of the most prevalent allergens in Korea, decreasing quality of life and causing nutritional repercussions. OBJECTIVE: We aimed to investigate the efficacy and safety of the home-based wheat oral immunotherapy (OIT) using wheat noodles in children with a wheat allergy. METHODS: We conducted a retrospective study involving 72 children aged 3 to 17 years diagnosed with a wheat allergy. Patients received wheat OIT using wheat noodles (n = 50) and were compared with a historical control group (n = 22). Baseline characteristics, adverse events, and immunological changes were assessed. Predictors of successful desensitization were identified using logistic regression analysis. RESULTS: Among 50 patients completing the up-dosing phase, 82.0% achieved desensitization to 2,400 mg of wheat protein, compared to 4.5% in the control group (p < 0.001). During the up-dosing period, the median number of adverse reactions per person was 2, and anaphylaxis occurred in 30.0% (15/50). However, there were no life-threatening adverse events. In multivariable analysis, the presence of asthma (adjusted odds ratio [aOR], 8.88; 95% confidence interval [CI], 1.10-71.97; p = 0.041) and a higher ratio of specific IgE (sIgE) to ω-5-gliadin and total IgE (aOR 19.09, 95%CI 1.21-300.80, p = 0.036) were significantly associated with treatment outcomes of wheat OIT. CONCLUSION: Our study showed the safety and efficacy of home-based wheat OIT using boiled noodles in Korean children with wheat allergies. Careful consideration is warranted for patients with elevated baseline sIgE to ω-5-gliadin to total IgE ratio and a history of asthma.

Ulnar neuropathy at the elbow: associations of pre-operative DTI parameters with clinical outcomes after cubital tunnel decompression.

OBJECTIVES: To evaluate whether DTI parameters of the ulnar nerve at the elbow are associated with clinical outcomes in patients receiving cubital tunnel decompression (CTD) surgery for ulnar neuropathy. METHODS: This retrospective study included 21 patients with cubital tunnel syndrome who received CTD surgery between January 2019 and November 2020. All patients underwent pre-operative elbow MRI, including DTI. Region-of-interest analysis was performed on the ulnar nerve at three levels around the elbow: above (level 1), cubital tunnel (level 2), and below (level 3). Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were calculated on three sections at each level. Clinical data on symptom improvement in respect to pain and tingling sensation after CTD were recorded. Logistic regression analysis was used to compare DTI parameters of the nerve at three levels and the entire nerve course between patients with and without symptom improvement after CTD. RESULTS: After CTD, 16 patients showed improvement in symptoms, but five did not. ROC analysis of DTI parameters showed that AUCs of FA, AD, and MD were higher at level 1 than at levels 2 and 3, with FA showing the highest AUC (level 1: FA, 0.7104 [95% CI, 0.5206-0.9002] vs AD, 0.6521 [95% CI, 0.4900-0.8142] vs MD, 0.6153 [95% CI, 0.4187-0.8119]). CONCLUSION: In patients who underwent CTD surgery for ulnar neuropathy at the elbow, the DTI parameters of FA, AD, and MD above the cubital tunnel level were associated with clinical outcomes, with FA showing the strongest associations. KEY POINTS: • After CTD surgery for ulnar neuropathy at the elbow, persistent symptoms may be observed, depending on symptom severity. • DTI parameters of the ulnar nerve at the elbow showed differences in their capacity for discriminating between patients with and without symptom improvement following CTD surgery, with this capacity depending on the nerve level at the elbow. • FA, AD, and MD measured above the cubital tunnel on pre-operative DTI may be associated with surgical outcomes, with FA showing the strongest association (AUC at level 1, 0.7104 [95% CI, 0.5206-0.9002]).

Naming-related spectral responses predict neuropsychological outcome after epilepsy surgery.

This prospective study determined the use of intracranially recorded spectral responses during naming tasks in predicting neuropsychological performance following epilepsy surgery. We recruited 65 patients with drug-resistant focal epilepsy who underwent preoperative neuropsychological assessment and intracranial EEG recording. The Clinical Evaluation of Language Fundamentals evaluated the baseline and postoperative language function. During extra-operative intracranial EEG recording, we assigned patients to undergo auditory and picture naming tasks. Time-frequency analysis determined the spatiotemporal characteristics of naming-related amplitude modulations, including high gamma augmentation at 70-110 Hz. We surgically removed the presumed epileptogenic zone based on the intracranial EEG and MRI abnormalities while maximally preserving the eloquent areas defined by electrical stimulation mapping. The multivariate regression model incorporating auditory naming-related high gamma augmentation predicted the postoperative changes in Core Language Score with r2 of 0.37 and in Expressive Language Index with r2 of 0.32. Independently of the effects of epilepsy and neuroimaging profiles, higher high gamma augmentation at the resected language-dominant hemispheric area predicted a more severe postoperative decline in Core Language Score and Expressive Language Index. Conversely, the model incorporating picture naming-related high gamma augmentation predicted the change in Receptive Language Index with an r2 of 0.50. Higher high gamma augmentation independently predicted a more severe postoperative decline in Receptive Language Index. Ancillary regression analysis indicated that naming-related low gamma augmentation and alpha/beta attenuation likewise independently predicted a more severe Core Language Score decline. The machine learning-based prediction model suggested that naming-related high gamma augmentation, among all spectral responses used as predictors, most strongly contributed to the improved prediction of patients showing a >5-point Core Language Score decline (reflecting the lower 25th percentile among patients). We generated the model-based atlas visualizing sites, which, if resected, would lead to such a language decline. With a 5-fold cross-validation procedure, the auditory naming-based model predicted patients who had such a postoperative language decline with an accuracy of 0.80. The model indicated that virtual resection of an electrical stimulation mapping-defined language site would have increased the relative risk of the Core Language Score decline by 5.28 (95% confidence interval: 3.47-8.02). Especially, that of an electrical stimulation mapping-defined receptive language site would have maximized it to 15.90 (95% confidence interval: 9.59-26.33). In summary, naming-related spectral responses predict neuropsychological outcomes after epilepsy surgery. We have provided our prediction model as an open-source material, which will indicate the postoperative language function of future patients and facilitate external validation at tertiary epilepsy centres.

Developmental organization of neural dynamics supporting auditory perception.

PURPOSE: A prominent view of language acquisition involves learning to ignore irrelevant auditory signals through functional reorganization, enabling more efficient processing of relevant information. Yet, few studies have characterized the neural spatiotemporal dynamics supporting rapid detection and subsequent disregard of irrelevant auditory information, in the developing brain. To address this unknown, the present study modeled the developmental acquisition of cost-efficient neural dynamics for auditory processing, using intracranial electrocorticographic responses measured in individuals receiving standard-of-care treatment for drug-resistant, focal epilepsy. We also provided evidence demonstrating the maturation of an anterior-to-posterior functional division within the superior-temporal gyrus (STG), which is known to exist in the adult STG. METHODS: We studied 32 patients undergoing extraoperative electrocorticography (age range: eight months to 28 years) and analyzed 2,039 intracranial electrode sites outside the seizure onset zone, interictal spike-generating areas, and MRI lesions. Patients were given forward (normal) speech sounds, backward-played speech sounds, and signal-correlated noises during a task-free condition. We then quantified sound processing-related neural costs at given time windows using high-gamma amplitude at 70-110 Hz and animated the group-level high-gamma dynamics on a spatially normalized three-dimensional brain surface. Finally, we determined if age independently contributed to high-gamma dynamics across brain regions and time windows. RESULTS: Group-level analysis of noise-related neural costs in the STG revealed developmental enhancement of early high-gamma augmentation and diminution of delayed augmentation. Analysis of speech-related high-gamma activity demonstrated an anterior-to-posterior functional parcellation in the STG. The left anterior STG showed sustained augmentation throughout stimulus presentation, whereas the left posterior STG showed transient augmentation after stimulus onset. We found a double dissociation between the locations and developmental changes in speech sound-related high-gamma dynamics. Early left anterior STG high-gamma augmentation (i.e., within 200 ms post-stimulus onset) showed developmental enhancement, whereas delayed left posterior STG high-gamma augmentation declined with development. CONCLUSIONS: Our observations support the model that, with age, the human STG refines neural dynamics to rapidly detect and subsequently disregard uninformative acoustic noises. Our study also supports the notion that the anterior-to-posterior functional division within the left STG is gradually strengthened for efficient speech-sound perception after birth.

Diffusion tractography predicts propagated high-frequency activity during epileptic spasms.

OBJECTIVE: To determine the structural networks that constrain propagation of ictal oscillations during epileptic spasm events, and compare the observed propagation patterns across patients with successful or unsuccessful surgical outcomes. METHODS: Subdural electrode recordings of 18 young patients (age 1-11 years) were analyzed during epileptic spasm events to determine ictal networks and quantify the amplitude and onset time of ictal oscillations across the cortical surface. Corresponding structural networks were generated with diffusion magnetic resonance imaging (MRI) tractography by seeding the cortical region associated with the earliest average oscillation onset time, and white matter pathways connecting active electrode regions within the ictal network were isolated. Properties of this structural network were used to predict oscillation onset times and amplitudes, and this relationship was compared across patients who did and did not achieve seizure freedom following resective surgery. RESULTS: Onset propagation patterns were relatively consistent across each patient's spasm events. An electrode's average ictal oscillation onset latency was most significantly associated with the length of direct corticocortical tracts connecting to the area with the earliest average oscillation onset (p < .001, model R2  = .54). Moreover, patients demonstrating a faster propagation of ictal oscillation signals within the corticocortical network were more likely to have seizure recurrence following resective surgery (p = .039). In addition, ictal oscillation amplitude was associated with connecting tractography length and weighted fractional anisotropy (FA) measures along these pathways (p = .002/.030, model R2  = .31/.25). Characteristics of analogous corticothalamic pathways did not show significant associations with ictal oscillation onset latency or amplitude. SIGNIFICANCE: Spatiotemporal propagation patterns of high-frequency activity in epileptic spasms align with length and FA measures from onset-originating corticocortical pathways. Considering the data in this individualized framework may help inform surgical decision-making and expectations of surgical outcomes.

Neonatal encephalopathy prediction of poor outcome with diffusion-weighted imaging connectome and fixel-based analysis.

BACKGROUND: Better biomarkers of eventual outcome are needed for neonatal encephalopathy. To identify the most potent neonatal imaging marker associated with 2-year outcomes, we retrospectively performed diffusion-weighted imaging connectome (DWIC) and fixel-based analysis (FBA) on magnetic resonance imaging (MRI) obtained in the first 4 weeks of life in term neonatal encephalopathy newborns. METHODS: Diffusion tractography was available in 15 out of 24 babies with MRI, five each with normal, abnormal motor outcome, or death. All 15 except one underwent hypothermia as initial treatment. In abnormal motor and death groups, DWIC found 19 white matter pathways with severely disrupted fiber orientation distributions. RESULTS: Using random forest classification, these disruptions predicted the follow-up outcomes with 89-99% accuracy. These pathways showed reduced integrity in abnormal motor and death vs. normal tone groups (p < 10-6). Using ranked supervised multi-view canonical correlation and depicting just three of the five dimensions of the analysis, the abnormal motor and death were clearly differentiated from each other and the normal tone group. CONCLUSIONS: This study suggests that a machine-learning model for prediction using early DWIC and FBA could be a possible way of developing biomarkers in large MRI datasets having clinical outcomes. IMPACT: Early connectome and FBA of clinically acquired DWI provide a new noninvasive imaging tool to predict the long-term motor outcomes after birth, based on the severity of white matter injury. Disrupted white matter connectivity as a novel neonatal marker achieves high accuracy of 89-99% to predict 2-year motor outcomes using conventional machine-learning classification. The proposed neonatal marker may allow better prognostication that is important to elucidate neural repair mechanisms and evaluate treatment modalities in neonatal encephalopathy.

Differentiating between benign and malignant ampullary strictures: a prediction model using a nomogram based on CT imaging and clinical findings.

OBJECTIVES: To construct a predictive nomogram for differentiating malignant from benign ampullary strictures using contrast-enhanced computed tomography (CT) findings combined with clinical findings. METHODS: In this retrospective study, 152 patients with ampullary stricture (98 benign and 54 malignant) who underwent contrast-enhanced CT were included. Various imaging findings of the ampulla, bile duct, main pancreatic duct, and periampullary area were evaluated and clinical findings including the presence of jaundice, carbohydrate antigen 19-9 level, and history of cholecystectomy were collected. Among them, statistically significant findings were identified using univariable and multivariable logistic regression analyses. A nomogram was constructed to differentiate benign and malignant ampullary strictures and was internally validated. RESULTS: Multivariable analysis revealed that jaundice (odds ratio [OR]: 17.33, p < 0.001), presence of an ampullary mass (OR: 24.40, p < 0.001), non-similar enhancement of the ampulla to the duodenum (OR: 31.96, p = 0.003), and proportional dilatation of the bile duct (OR: 7.98, p = 0.001) were independent significant factors for predicting the malignant ampullary stricture, and were used to construct a nomogram. Among them, non-similar enhancement of the ampulla to the duodenum showed the highest OR and predictor point on the nomogram. The calibration plots showed excellent agreement between the predicted probabilities and the actual rates of malignant ampullary strictures, on internal validation. CONCLUSIONS: Combination of clinical and imaging findings could aid in predicting malignant ampullary strictures using significant findings of jaundice, presence of ampullary mass, non-similar enhancement of the ampulla to the duodenum, and proportional dilatation of the bile duct. KEY POINTS: • The presence of jaundice, ampullary mass, non-similar enhancement of the ampulla, and proportional bile duct dilatation were significant findings for predicting malignant ampullary strictures. • Non-similar enhancement of the ampulla to the duodenum was a significant feature with the highest odds ratio for differentiating benign and malignant ampullary strictures. • The nomogram constructed using contrast-enhanced computed tomography imaging and clinical findings could aid in predicting malignant ampullary strictures.

Deep learning image reconstruction algorithm for abdominal multidetector CT at different tube voltages: assessment of image quality and radiation dose in a phantom study.

OBJECTIVES: To compare the image quality and radiation dose of a deep learning image reconstruction (DLIR) algorithm compared with iterative reconstruction (IR) and filtered back projection (FBP) at different tube voltages and tube currents. MATERIALS AND METHODS: A customized body phantom was scanned at different tube voltages (120, 100, and 80 kVp) with different tube currents (200, 100, and 60 mA). The CT datasets were reconstructed with FBP, hybrid IR (30% and 50%), and DLIR (low, medium, and high levels). The reference image was set as an image taken with FBP at 120 kVp/200 mA. The image noise, contrast-to-noise ratio (CNR), sharpness, artifacts, and overall image quality were assessed in each scan both qualitatively and quantitatively. The radiation dose was also evaluated with the volume CT dose index (CTDIvol) for each dose scan. RESULTS: In qualitative and quantitative analyses, compared with reference images, low-dose CT with DLIR significantly reduced the noise and artifacts and improved the overall image quality, even with decreased sharpness (p < 0.05). Despite the reduction of image sharpness, low-dose CT with DLIR could maintain the image quality comparable to routine-dose CT with FBP, especially when using the medium strength level. CONCLUSION: The new DLIR algorithm reduced noise and artifacts and improved overall image quality, compared to FBP and hybrid IR. Despite reduced image sharpness in CT images of DLIR algorithms, low-dose CT with DLIR seems to have an overall greater potential for dose optimization. KEY POINTS: • Using deep learning image reconstruction (DLIR) algorithms, image quality was maintained even with a radiation dose reduced by approximately 70%. • DLIR algorithms yielded lower image noise, higher contrast-to-noise ratios, and higher overall image quality than FBP and hybrid IR, both subjectively and objectively. • DLIR algorithms can provide a better image quality, much better than FBP and even better than hybrid IR, while facilitating a reduction in radiation dose.

Image quality and acquisition time assessments for phase oversampling in compressed sensing sensitivity encoding: Comparison with conventional SENSE.

This study compared sensitivity encoding (SENSE) and compressed sensing sensitivity encoding (CS-SENSE) for phase oversampling distance and assessed its impact on image quality and image acquisition time. The experiment was performed with a large diameter phantom using 16-channel anterior body coils. All imaging data were divided into three groups according to the parallel imaging technique and oversampling distances: groups A (SENSE with phase oversampling distance of 150 mm), B (CS-SENSE with phase oversampling distance of 100 mm), and C (CS-SENSE with phase oversampling distance of 75 mm). No statistically significant differences were observed among groups A, B, and C regarding both T2 and T1 turbo spin-echo (TSE) sequences using an acceleration factor (AF) of 2 (p = 0.301 and 0.289, respectively). In comparison with AF 2 of group A, the scan time of AF 2 of groups B and C was reduced by 11.2% and 23.5% (T2 TSE) and 15.8% and 22.7% (T1 TSE), respectively, while providing comparable image quality. Significant image noise and aliasing artifact were more evident at AF ≥ $ \ge $ 2 in group A compared with groups B and C. CS-SENSE with a less phase oversampling distance can reduce image acquisition time without image quality degradation compared with that of SENSE, despite the increase in aliasing artifact as the AF increased in both CS-SENSE and SENSE.

Naphthalimide-4-(4-nitrophenyl)thiosemicarbazide: A Fluorescent Probe for Simultaneous Monitoring of Viscosity and Nitric Oxide in Living Cells.

Intracellular viscosity is a physicochemical factor that determines the outcomes of various biological processes, while nitric oxide (NO) is an essential signaling molecule that controls many cellular processes, including oxidative stress. Anticipating that both may be interrelated with a variety of pathologies, their simultaneous measurement would be highly valuable for the investigation of the pathological condition of cells. However, the development of a sensor for such simultaneous detection has not been attempted yet. Herein, we present the synthesis of naphthalimide-4-(4-nitrophenyl)thiosemicarbazide, probe 1, and its application to living cells under conditions of lipopolysaccharide or nystatin treatment, adopted as oxidative stress and altered intracellular viscosity models, respectively. The probe showed increased fluorescence in response to elevation of viscosity and NO levels at 470 and 550 nm, respectively, in the solution studies. When the probe was used for a confocal microscopic study of HeLa cells under stressed conditions, simultaneous monitoring of viscosity and NO level elevations was possible through fluorescence imaging using band-pass filters of 420-475 and 505-600 nm, respectively, upon excitation at a wavelength of 405 nm. Interestingly, both the cellular viscosity and NO levels increased together under lipopolysaccharide or nystatin treatment. Therefore, we suggest that probe 1 is a fluorescent chemical probe that enables the monitoring of alterations in intracellular viscosity and NO levels in living cells, which would be valuable in studies of various cellular damage models.

Deep reasoning neural network analysis to predict language deficits from psychometry-driven DWI connectome of young children with persistent language concerns.

This study investigated whether current state-of-the-art deep reasoning network analysis on psychometry-driven diffusion tractography connectome can accurately predict expressive and receptive language scores in a cohort of young children with persistent language concerns (n = 31, age: 4.25 ± 2.38 years). A dilated convolutional neural network combined with a relational network (dilated CNN + RN) was trained to reason the nonlinear relationship between "dilated CNN features of language network" and "clinically acquired language score". Three-fold cross-validation was then used to compare the Pearson correlation and mean absolute error (MAE) between dilated CNN + RN-predicted and actual language scores. The dilated CNN + RN outperformed other methods providing the most significant correlation between predicted and actual scores (i.e., Pearson's R/p-value: 1.00/<.001 and .99/<.001 for expressive and receptive language scores, respectively) and yielding MAE: 0.28 and 0.28 for the same scores. The strength of the relationship suggests elevated probability in the prediction of both expressive and receptive language scores (i.e., 1.00 and 1.00, respectively). Specifically, sparse connectivity not only within the right precentral gyrus but also involving the right caudate had the strongest relationship between deficit in both the expressive and receptive language domains. Subsequent subgroup analyses inferred that the effectiveness of the dilated CNN + RN-based prediction of language score(s) was independent of time interval (between MRI and language assessment) and age of MRI, suggesting that the dilated CNN + RN using psychometry-driven diffusion tractography connectome may be useful for prediction of the presence of language disorder, and possibly provide a better understanding of the neurological mechanisms of language deficits in young children.

Multi-arterial phase MRI depicts inconsistent arterial phase hyperenhancement (APHE) subtypes in liver observations of patients at risk for hepatocellular carcinoma.

OBJECTIVES: According to LI-RADS, a major discriminating feature between hepatocellular carcinoma (HCC) and non-HCC malignancies is the subtype of arterial phase hyperenhancement (APHE). The aim of this study was to investigate whether APHE subtypes are consistent across multi-arterial phase (mHAP) MRI acquisitions while evaluating reader agreement. Secondarily, we investigated factors that may affect reader agreement for APHE subtype. METHODS: In this retrospective study, consecutive patients with liver cirrhosis and focal observations who underwent mHAP were included. Five radiologists reviewed MR images in 2 reading sessions. In reading session 1, individual AP series were reviewed and scored for presence of APHE and subtype. In reading session 2, readers scored observations' major and ancillary features and LI-RADS category in the complete MRI examination. Reader agreement was calculated using Fleiss' kappa for binary outcomes and Kendall's coefficient of concordance for LI-RADS categories. Univariate mixed effects logistic regressions were performed to investigate factors affecting agreement. RESULTS: In total, 61 patients with 77 focal observations were analyzed. Of observations unanimously scored as having APHE, 27.7% showed both rim and nonrim subtypes on mHAP. Inter-reader agreement for APHE subtype ranged from 0.49 (95% CI: 0.33, 0.64) to 0.57 (95% CI: 0.40, 0.74) between reading sessions. Observation size had a trend level effect on rim APHE agreement (p = 0.052). CONCLUSION: Approximately 1/3 of observations demonstrated inconsistent APHE subtype during mHAP acquisition. Small lesions were particularly challenging. Further guidance on APHE subtype classification, especially when applied to mHAP, could be a focus of LI-RADS refinement. KEY POINTS: • In a cohort of patients at risk for HCC, 28% of the observations showed inconsistent arterial phase hyperenhancement (APHE) subtypes (rim and nonrim) on multi-arterial phase imaging according to the majority score of 5 independent readers. • Inconsistent APHE subtypes may challenge reliable imaging diagnosis, i.e., LI-RADS categorization, of focal liver observations in patients at risk for HCC.

CNN color-coded difference maps accurately display longitudinal changes in liver MRI-PDFF.

OBJECTIVES: To assess the feasibility of a CNN-based liver registration algorithm to generate difference maps for visual display of spatiotemporal changes in liver PDFF, without needing manual annotations. METHODS: This retrospective exploratory study included 25 patients with suspected or confirmed NAFLD, who underwent PDFF-MRI at two time points at our institution. PDFF difference maps were generated by applying a CNN-based liver registration algorithm, then subtracting follow-up from baseline PDFF maps. The difference maps were post-processed by smoothing (5 cm2 round kernel) and applying a categorical color scale. Two fellowship-trained abdominal radiologists and one radiology resident independently reviewed difference maps to visually determine segmental PDFF change. Their visual assessment was compared with manual ROI-based measurements of each Couinaud segment and whole liver PDFF using intraclass correlation (ICC) and Bland-Altman analysis. Inter-reader agreement for visual assessment was calculated (ICC). RESULTS: The mean patient age was 49 years (12 males). Baseline and follow-up PDFF ranged from 2.0 to 35.3% and 3.5 to 32.0%, respectively. PDFF changes ranged from - 20.4 to 14.1%. ICCs against the manual reference exceeded 0.95 for each reader, except for segment 2 (2 readers ICC = 0.86-0.91) and segment 4a (reader 3 ICC = 0.94). Bland-Altman limits of agreement were within 5% across all three readers. Inter-reader agreement for visually assessed PDFF change (whole liver and segmental) was excellent (ICCs > 0.96), except for segment 2 (ICC = 0.93). CONCLUSIONS: Visual assessment of liver segmental PDFF changes using a CNN-generated difference map strongly agreed with manual estimates performed by an expert reader and yielded high inter-reader agreement. KEY POINTS: • Visual assessment of longitudinal changes in quantitative liver MRI can be performed using a CNN-generated difference map and yields strong agreement with manual estimates performed by expert readers.

Peripheral nerve sheath tumor: differentiation of malignant from benign tumors with conventional and diffusion-weighted MRI.

OBJECTIVES: To evaluate potential of conventional MRI and diffusion-weighted imaging (DWI) for differentiating malignant from benign peripheral nerve sheath tumors (PNSTs). METHODS: Eighty-seven cases of malignant or benign PNSTs in the trunk or extremities that underwent conventional MRI with contrast enhancement, DWI, and pathologic confirmation between Sep. 2014 and Dec. 2017 were identified. Of these, 55 tumors of uncertain nature on MRI were included. Tumor size, signal, and morphology were reviewed on conventional MRI, and apparent diffusion coefficient (ADC) values of solid enhancing portions were measured from DWI. Patient demographics, MRI features, and ADC values were compared between benign and malignant tumors, and robust imaging findings for malignant peripheral nerve sheath tumors (MPNSTs) were identified using multivariable models. RESULTS: A total of 55 uncertain tumors consisted of 18 malignant and 37 benign PNSTs. On MRI, tumor size, margin, perilesional edema, and presence of split fat, fascicular, and target signs were significantly different between groups (p < 0.05), as were mean and minimum ADC values (p = 0.002, p < 0.0001). Most inter-reader agreement was moderate to excellent (κ value, 0.45-1.0). The mean ADC value and absence of a split fat sign were identified as being associated with MPNSTs (odds ratios = 13.19 and 25.67 for reader 1; 49.05 and 117.91 for reader 2, respectively). The C-indices obtained by combining these two findings were 0.90 and 0.95, respectively. CONCLUSIONS: Benign and malignant PNSTs showed different features on MRI and DWI. A combination of mean ADC value and absence of split fat was excellent for discriminating malignant from benign PNSTs. KEY POINTS: • It is important to distinguish between malignant peripheral nerve sheath tumors (MPNSTs) and benign peripheral nerve sheath tumors (BPNSTs) to ensure an appropriate treatment plan. • On conventional MRI and diffusion-weighted imaging (DWI), MPNSTs and BPNSTs showed significant differences in tumor size, margin, presence of perilesional edema, and absence of split fat, fascicular, and target signs. • Absence of a split fat sign and mean apparent diffusion coefficient (ADC) values were robust imaging findings distinguishing MPNSTs from BPNSTs, with a C-index of > 0.9.

Prediction of baseline expressive and receptive language function in children with focal epilepsy using diffusion tractography-based deep learning network.

PURPOSE: Focal epilepsy is a risk factor for language impairment in children. We investigated whether the current state-of-the-art deep learning network on diffusion tractography connectome can accurately predict expressive and receptive language scores of children with epilepsy. METHODS: We studied 37 children with a diagnosis of drug-resistant focal epilepsy (age: 11.8 ±â€¯3.1 years) using 3 T MRI and diffusion tractography connectome: G = (S, Ω), where S is an adjacency matrix of edges representing the connectivity strength (number of white-matter tract streamlines) between each pair of brain regions, and Ω reflects a set of brain regions. A convolutional neural network (CNN) was trained to learn the nonlinear relationship between 'S (input)' and 'language score (output)'. Repeated hold-out validation was then employed to measure the Pearson correlation and mean absolute error (MAE) between CNN-predicted and actual language scores. RESULTS: We found that CNN-predicted and actual scores were significantly correlated (i.e., Pearson's R/p-value: 0.82/<0.001 and 0.75/<0.001), yielding MAE: 7.77 and 7.40 for expressive and receptive scores, respectively. Specifically, sparse connectivity not only within the left cortico-cortical network but also involving the right subcortical structures was predictive of language impairment of expressive or receptive domain. Subsequent subgroup analyses inferred that the effectiveness of diffusion tractography-based prediction of language outcome was independent of clinical variables. Intrinsic diffusion tractography connectome properties may be useful for predicting the severity of baseline language dysfunction and possibly provide a better understanding of the biological mechanisms of epilepsy-related language impairment in children.