Tumor-associated high endothelial venules mediate lymphocyte entry into tumors and predict response to PD-1 plus CTLA-4 combination immunotherapy

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The usefulness of measuring n-butyric acid concentration as a new indicator of blood decomposition in forensic autopsy

In forensic medicine, although various alcohols have been reported as indicators of decomposition in collected blood, no studies have examined short-chain fatty acids as indicators. In this study, the blood n-butyric acid concentration was quantified, and the association between n-butyric acid and decomposition was investigated to determine whether the detection of n-butyric acid could be a new indicator of decomposition. Among the forensic autopsies performed from 2016 to 2018 in our laboratory, the cases were divided into decomposed (n = 20) and non-decomposed (n = 20) groups based on macroscopic findings. Blood samples collected at the time of autopsy were derivatized with 3-nitrophenylhydrazine hydrochloride after solid-phase extraction. The n-butyric acid concentration was measured using liquid chromatography–tandem mass spectrometry. In addition, ethanol and n-propanol were measured using a gas chromatography-flame ionization detector. There was a significant difference (p < 0.01) in the concentrations of n-butyric acid between the decomposed and non-decomposed groups (0.343 ± 0.259 [0.030–0.973] and 0.003 ± 0.002 [0.001–0.007] mg/mL, respectively). In the decomposed group, n-butyric acid was detected at high concentrations, even in cases where n-propanol was low. These results suggest that n-butyric acid is more likely to be an indicator of blood decomposition than n-propanol.     

Contribution of different somatosensory afferent input to subcortical somatosensory evoked potentials in humans

ObjectivesTo investigate the subcortical somatosensory evoked potentials (SEPs) to electrical stimulation of either muscle or cutaneous afferents.MethodsSEPs were recorded in 6 patients suffering from Parkinson’s disease (PD) who underwent electrode implantation in the pedunculopontine (PPTg) nucleus area. We compared SEPs recorded from the scalp and from the intracranial electrode contacts to electrical stimuli applied to: 1) median nerve at the wrist, 2) abductor pollicis brevis motor point, and 3) distal phalanx of the thumb. Also the high-frequency oscillations (HFOs) were analysed.ResultsAfter median nerve and pure cutaneous (distant phalanx of the thumb) stimulation, a P1-N1 complex was recorded by the intracranial lead, while the scalp electrodes recorded the short-latency far-field responses (P14 and N18). On the contrary, motor point stimulation did not evoke any low-frequency component in the PPTg traces, nor the N18 potential on the scalp. HFOs were recorded to stimulation of all modalities by the PPTg electrode contacts.ConclusionsStimulus processing within the cuneate nucleus depends on modality, since only the cutaneous input activates the complex intranuclear network possibly generating the scalp N18 potential.SignificanceOur results shed light on the subcortical processing of the somatosensory input of different modalities.     

Enlarged high frequency oscillations of the median nerve somatosensory evoked potential and survival in amyotrophic lateral sclerosis

ObjectiveA large N20 and P25 of the median nerve somatosensory evoked potential (SEP) predicts short survival in amyotrophic lateral sclerosis (ALS). We investigated whether high frequency oscillations (HFOs) over N20 are enlarged and associated with survival in ALS.MethodsA total of 145 patients with ALS and 57 healthy subjects were studied. We recorded the median nerve SEP and measured the onset-to-peak amplitude of N20 (N20o-p), and peak-to-peak amplitude between N20 and P25 (N20p-P25p). We obtained early and late HFO potentials by filtering SEP between 500 and 1 kHz, and measured the peak-to-peak amplitude. We followed up patients until endpoints (death or tracheostomy) and analyzed the relationship between SEP or HFO amplitudes and survival using a Cox analysis.ResultsPatients showed larger N20o-p, N20p-P25p, and early and late HFO amplitudes than the control values. N20p-P25p was associated with survival periods (p = 0.0004), while early and late HFO amplitudes showed no significant association with survival (p = 0.4307, and p = 0.6858, respectively).ConclusionsThe HFO amplitude in ALS is increased, but does not predict survival.SignificanceThe enlarged HFOs in ALS might be a compensatory phenomenon to the hyperexcitability of the sensory cortex pyramidal neurons.     

A High Order Bound Preserving Finite Difference Linear Scheme for Incompressible Flows

We propose a high order finite difference linear scheme combined with a high order bound preserving maximum-principle-preserving (MPP) flux limiter to solve the incompressible flow system. For such problem with highly oscillatory structure but not strong shocks, our approach seems to be less dissipative and much less costly than a WENO type scheme, and has high resolution due to a Hermite reconstruction. Spurious numerical oscillations can be controlled by the weak MPP flux limiter. Numerical tests are performed for the Vlasov-Poisson system, the 2D guiding-center model and the incompressible Euler system. The comparison between the linear and WENO type schemes, with and without the MPP flux limiter, will demonstrate the good performance of our proposed approach.     

An ultrasonographic monitoring of skin condition in patients receiving radiotherapy for head and neck cancers

Radiodermatitis is one of the commonest side effects of radiotherapy. They are usually assessed by semi‐quantitative clinical scores, which are not validated and may be subject to inter‐observer variability. A few previous studies suggested that high‐frequency ultrasonography (HF‐USG) is useful in the assessment of the acute phase of radiation dermatitis in breast cancer patients. (a) To monitor skin changes by HF‐USG during the course of radiotherapy due to head and neck cancers, and (b) to determine whether there is any connection between skin sonograms and the skin scoring criteria. This prospective, observational study includes patients diagnosed with head and neck cancers, treated with radiotherapy or concomitant chemoradiation. The final analysis includes six patients. In every patient, the HF‐USG as well as dermatological assessment (target lesion score—TLS and CACE v. 4.0) were performed 4×: before, in the middle, day after, and 3 months after radiotherapy. There were significant differences between non‐irradiated skin thickness and thickness of skin with clinically obvious radiodermatitis (TLS grade 1‐4; P < .0001), as well as between irradiated, unchanged skin thickness (TLS grade 0) and thickness of skin with clinically obvious radiodermatitis (TLS grade 1‐4; P = .0002). There was no significant difference between non‐irradiated and irradiated, unchanged skin thickness (TLS grade 0; P = .9318). In four patients, we demonstrated subepidermal low echogenic band (SLEB). HF‐USG can be useful tool to noninvasive and objective assessment of skin changes during radiotherapy.     

How structural and functional MRI can inform dual-site tACS parameters: A case study in a clinical population and its pragmatic implications

BackgroundAbnormalities in frontoparietal network (FPN) were observed in many neuropsychiatric diseases including substance use disorders. A growing number of studies are using dual-site-tACS with frontoparietal synchronization to engage this network. However, a computational pathway to inform and optimize parameter space for frontoparietal synchronization is still lacking. In this case study, in a group of participants with methamphetamine use disorders, we proposed a computational pathway to extract optimal electrode montage while accounting for stimulation intensity using structural and functional MRI.MethodsSixty methamphetamine users completed an fMRI drug cue-reactivity task. Four main steps were taken to define electrode montage and adjust stimulation intensity using 4x1 high-definition (HD) electrodes for a dual-site-tACS; (1) Frontal seed was defined based on the maximum electric fields (EF) predicted by simulation of HD montage over DLPFC (F3/F4 in EEG 10–10), (2) frontal seed-to-whole brain context-dependent correlation was calculated to determine connected regions to frontal seeds, (3) center of connected cluster in parietal cortex was selected as a location for placing the second set of HD electrodes to shape the informed montage, (4) individualized head models were used to determine optimal stimulation intensity considering underlying brain structure. The informed montage was compared to montages with large electrodes and classic frontoparietal HD montages (F3-P3/F4-P4) in terms of tACS-induced EF and ROI-to-ROI task-based/resting-state connectivity.ResultsCompared to the large electrodes, HD frontoparietal montages allow for a finer control of the spatial peak fields in the main nodes of the FPN at the cost of lower maximum EF (large-pad/HD: max EF[V/m] = 0.37/0.11, number of cortical sub-regions that EF exceeds 50% of the max = 77/13). For defining stimulation targets based on EF patterns, using group-level head models compared to a single standard head model results in comparable but significantly different seed locations (6.43 mm Euclidean distance between the locations of the frontal maximum EF in standard-space). As expected, significant task-based/resting-state connections were only found between frontal-parietal locations in the informed montage. Cue-induced craving score was correlated with frontoparietal connectivity only in the informed montage (r = ?0.24). Stimulation intensity in the informed montage, and not in the classic HD montage, needs 40% reduction in the parietal site to reduce the disparity in EF between stimulation sites.ConclusionThis study provides some empirical insights to montage and dose selection in dual-site-tACS using individual brain structures and functions and proposes a computational pathway to use head models and functional MRI to define (1) optimum electrode montage for targeting FPN in a context of interest (drug-cue-reactivity) and (2) proper transcranial stimulation intensity.     

Differentiating autoimmune pancreatitis from pancreatic ductal adenocarcinoma with CT radiomics features

PurposeThe purpose of this study was to determine whether computed tomography (CT)-based machine learning of radiomics features could help distinguish autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC).Materials and MethodsEighty-nine patients with AIP (65 men, 24 women; mean age, 59.7 ± 13.9 [SD] years; range: 21–83 years) and 93 patients with PDAC (68 men, 25 women; mean age, 60.1 ± 12.3 [SD] years; range: 36–86 years) were retrospectively included. All patients had dedicated dual-phase pancreatic protocol CT between 2004 and 2018. Thin-slice images (0.75/0.5 mm thickness/increment) were compared with thick-slices images (3 or 5 mm thickness/increment). Pancreatic regions involved by PDAC or AIP (areas of enlargement, altered enhancement, effacement of pancreatic duct) as well as uninvolved parenchyma were segmented as three-dimensional volumes. Four hundred and thirty-one radiomics features were extracted and a random forest was used to distinguish AIP from PDAC. CT data of 60 AIP and 60 PDAC patients were used for training and those of 29 AIP and 33 PDAC independent patients were used for testing.ResultsThe pancreas was diffusely involved in 37 (37/89; 41.6%) patients with AIP and not diffusely in 52 (52/89; 58.4%) patients. Using machine learning, 95.2% (59/62; 95% confidence interval [CI]: 89.8–100%), 83.9% (52:67; 95% CI: 74.7–93.0%) and 77.4% (48/62; 95% CI: 67.0–87.8%) of the 62 test patients were correctly classified as either having PDAC or AIP with thin-slice venous phase, thin-slice arterial phase, and thick-slice venous phase CT, respectively. Three of the 29 patients with AIP (3/29; 10.3%) were incorrectly classified as having PDAC but all 33 patients with PDAC (33/33; 100%) were correctly classified with thin-slice venous phase with 89.7% sensitivity (26/29; 95% CI: 78.6–100%) and 100% specificity (33/33; 95% CI: 93–100%) for the diagnosis of AIP, 95.2% accuracy (59/62; 95% CI: 89.8–100%) and area under the curve of 0.975 (95% CI: 0.936–1.0).ConclusionsRadiomic features help differentiate AIP from PDAC with an overall accuracy of 95.2%.