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Item does not contain fulltext There has been increasing interest in using neuroimaging measures to predict psychiatric disorders. However, predictions usually rely on large brain networks and large disorder heterogeneity. Thus, they lack both anatomical and behavioural specificity, preventing the advancement of targeted interventions. Here we address both challenges. First, using resting-state functional magnetic resonance imaging, we parcellated the amygdala, a region implicated in mood disorders, into seven nuclei. Next, a questionnaire factor analysis provided subclinical mental health dimensions frequently altered in anxious-depressive individuals, such as negative emotions and sleep problems. Finally, for each behavioural dimension, we identified the most predictive resting-state functional connectivity between individual amygdala nuclei and highly specific regions of interest, such as the dorsal raphe nucleus in the brainstem or medial frontal cortical regions. Connectivity in circumscribed amygdala networks predicted behaviours in an independent dataset. Our results reveal specific relations between mental health dimensions and connectivity in precise subcortical networks. 18 p.

Reconstructing visual experiences from human brain activity offers a unique way to understand how the brain represents the world, and to interpret the connection between computer vision models and our visual system. While deep generative models have recently been employed for this task, reconstructing realistic images with high semantic fidelity is still a challenging problem. Here, we propose a new method based on a diffusion model (DM) to reconstruct images from human brain activity obtained via functional magnetic resonance imaging (fMRI). More specifically, we rely on a latent diffusion model (LDM) termed Stable Diffusion. This model reduces the computational cost of DMs, while preserving their high generative performance. We also characterize the inner mechanisms of the LDM by studying how its different components (such as the latent vector of image Z, conditioning inputs C, and different elements of the denoising U-Net) relate to distinct brain functions. We show that our proposed method can reconstruct high-resolution images with high fidelity in straightforward fashion, without the need for any additional training and fine-tuning of complex deep-learning models. We also provide a quantitative interpretation of different LDM components from a neuroscientific perspective. Overall, our study proposes a promising method for reconstructing images from human brain activity, and provides a new framework for understanding DMs. Please check out our webpage at https://sites.google.com/view/stablediffusion-with-brain/

This study presents a model predictive-based current control for permanent magnet synchronous motors (PMSMs). In the authors' proposed approach, a reference voltage to an inverter can be strictly treated as a discrete voltage vector so that the output saturation of the inverter is avoided. Various constraints can be also taken into consideration in their approach. Designing the band of frequency is incorporated into a single objective function. The effectiveness of the proposed method is verified through simulations and experiments.

Choices rely on a transformation of sensory inputs into motor responses. Using invasive single neuron recordings, the evolution of a choice process has been tracked by projecting population neural responses into state spaces. Here, we develop an approach that allows us to recover similar trajectories on a millisecond timescale in non-invasive human recordings. We selectively suppress activity related to three task-axes, relevant and irrelevant sensory inputs and response direction, in magnetoencephalography data acquired during context-dependent choices. Recordings from premotor cortex show a progression from processing sensory input to processing the response. In contrast to previous macaque recordings, information related to choice-irrelevant features is represented more weakly than choice-relevant sensory information. To test whether this mechanistic difference between species is caused by extensive over-training common in non-human primate studies, we trained humans on >20,000 trials of the task. Choice-irrelevant features were still weaker than relevant features in premotor cortex after over-training.

Geospatial Information Authority of Japan has a VLBI antenna (ISHIOKA) and an IGS station (ISHI) at the Ishioka Geodetic Observing Station. The Ishioka VLBI antenna has participated in the IVS sessions and IGS station ISHI has continuously provided the GNSS data.We conducted co-location surveys in November 2018 and September 2020 to determine a local tie vector between the Ishioka VLBI antenna and the IGS station ISHI. In the surveys, we determined the position of ISHI w.r.t. four surrounding reference pillars by angle/distance measurements and leveling. To determine the position of the VLBI antenna reference point w.r.t. the pillars, we adopted the “inside method” (Munekane, 2019), where the position of the VLBI reference point is determined by observing mirror installed inside the AZ cabin from the fixed point inside the cabin; its position is determined by angle/distance measurements from the pillars. We plan to finish the calculation early this year and submit the results to IERS ITRS Center so as to contribute to the ITRF2020.In this presentation, we will outline the inside method and compare the results in 2018 and 2020.

There has been increasing interest in using neuroimaging measures to predict psychiatric disorders. However, predictions usually rely on large numbers of brain connections and large disorder heterogeneity, thus lacking both anatomical and behavioural specificity, preventing the advancement of targeted interventions. Here, we address both challenges. First, using resting-state functional MRI, we parcellated the amygdala, a region implicated in mood disorders but difficult to image with high fidelity, into seven nuclei. Next, a questionnaire factor analysis provided four sub-clinical latent behaviours frequently found in anxious-depressive individuals, such as negative emotions and sleep problems. Finally, for each latent behaviour, we identified the most predictive connections between individual amygdala nuclei and highly specific regions of interest e.g. dorsal raphe nucleus in the brainstem or medial prefrontal cortical regions. A small number of distinct connections predicted behaviours, providing unprecedented levels of specificity, in humans, for relating mental well-being to precise anatomical connections.

There has been increasing interest in using neuroimaging measures to predict psychiatric disorders. However, predictions usually rely on large brain networks and large disorder heterogeneity. Thus, they lack both anatomical and behavioural specificity, preventing the advancement of targeted interventions. Here we address both challenges. First, using resting-state functional magnetic resonance imaging, we parcellated the amygdala, a region implicated in mood disorders, into seven nuclei. Next, a questionnaire factor analysis provided subclinical mental health dimensions frequently altered in anxious-depressive individuals, such as negative emotions and sleep problems. Finally, for each behavioural dimension, we identified the most predictive resting-state functional connectivity between individual amygdala nuclei and highly specific regions of interest, such as the dorsal raphe nucleus in the brainstem or medial frontal cortical regions. Connectivity in circumscribed amygdala networks predicted behaviours in an independent dataset. Our results reveal specific relations between mental health dimensions and connectivity in precise subcortical networks.

Choices rely on a transformation of sensory inputs into motor responses. Using invasive single neuron recordings, the evolution of a choice process has been tracked by projecting population neural responses into state spaces. Here we develop an approach that allows us to recover state space trajectories on a millisecond timescale in non-invasive human recordings. We selectively suppress activity related to relevant and irrelevant sensory inputs and response direction in magnetoencephalography data acquired during context-dependent choices. Recordings from premotor cortex show a smooth progression from sensory input encoding to response encoding. In contrast to previous macaque recordings, information related to choice-irrelevant features is represented more weakly than choice-relevant sensory information. To test whether this mechanistic difference between species is caused by extensive overtraining common in non-human primate studies, we trained humans on >20,000 trials of the task. Choice-irrelevant features were still weaker than relevant features in premotor cortex after overtraining.

This paper discusses unified criteria for the local buckling of multi-walled carbon nanotubes in both compression and bending deformations from a standpoint of atomic simulations. Defective and non-defective five-walled carbon nanotubes are subjected to compression and bending deformation by the molecular dynamics method using the adaptive intermolecular reactive empirical bond order potential. The atomic elastic stiffness of each atom, B ij α , is then evaluated during the deformations to discuss the onset of local buckling. The B ij α corresponds to the second-order derivatives of the atomic energy, i.e., the gradient of the local stress–strain surfaces in six-dimensional strain space. If B ij α has a negative eigenvalue, a local unstable path will exist in the direction of the strain. Under compression, the smallest eigenvalues, λ ( 1 ) α , of the B ij α for all atoms changes to a negative value long before buckling occurs, while the second-smallest eigenvalues, λ ( 2 ) α , of the B ij α of some atoms change to a negative value just prior to buckling. Under bending deformation, the change in the positivity of λ ( 2 ) α corresponds to a rippling deformation on the side of compressive bending stresses. A variation in the location of defects in the carbon nanotubes affects the peak stresses under compression and the peak moments under a bending deformation. However, for all models, local buckling occurs from the dense region of atoms whose λ ( 2 ) α 0 in some outer layers. This suggests that the atomic elastic stiffness is capable of acting as an evaluation criterion for local buckling in multi-walled carbon nanotubes.

This study re-examines the racial salary gap of National Basketball Association players by constructing a long unbalanced panel covering the 1985-1986 to 2015-2016 seasons. Contrary to the results of previous studies, we find that non-white players are paid equally to white players with similar characteristics in the 1980s and 1990s, but that white players started to be paid about 20 percent more than non-white players in the last 10 years. Our results are robust to all specification checks, such as quantile regressions, controlling sample selection, different contract types, and player nationality. We find that neither employer preference nor income gap of white and black residents explains this increasing salary gap.

An increasing number of functional magnetic resonance imaging (fMRI) studies have revealed potential neural substrates of individual differences in diverse types of brain function and dysfunction. Although most previous studies have inherently focused on state-specific characterizations of brain networks and their functions, several recent studies reported on the potential state-unspecific nature of functional brain networks, such as global similarities across different experimental conditions or states, including both task and resting states. However, no previous studies have carried out direct, systematic characterizations of state-unspecific brain networks, or their functional implications. Here, we quantitatively identified several modes of state-unspecific individual variations in whole-brain functional connectivity patterns, called "Common Neural Modes" (CNMs), from a large-scale fMRI database including eight task/resting states. Furthermore, we tested how CNMs accounted for variability in individual cognitive measures. The results revealed that three CNMs were robustly extracted under various dimensions of features used. Each of these CNMs was preferentially correlated with different aspects of representative cognitive measures, reflecting stable individual traits. Importantly, the association between CNMs and cognitive measures emerged from brain connectivity data alone ("unsupervised"), whereas previous related studies have explicitly used both connectivity and cognitive measures to build their prediction models ("supervised"). The three CNMs were also able to predict several life outcomes, including income and life satisfaction, and achieved the highest level of performance when combined with a conventional cognitive measure. Our findings highlight the importance of state-unspecific brain networks in characterizing fundamental individual variation.

Recent functional magnetic resonance imaging (fMRI) studies have increasingly revealed potential neural substrates of individual differences in diverse types of brain function and dysfunction. Although most previous studies have been inherently limited to state-specific characterizations of related brain networks and their functions, several recent studies have examined the potential state-unspecific nature of functional brain networks, such as their global similarities across different experimental conditions (i.e., states) including both task and rest. However, no previous studies have carried out direct, systematic characterizations of state-unspecific brain networks, or their functional implications. Here, we quantitatively identified several modes of state-unspecific individual variation in whole-brain functional connectivity patterns, called “Common Neural Modes (CNMs)”, from a large fMRI dataset including eight task/rest states, obtained from the Human Connectome Project. Furthermore, we tested how CNMs account for variability in individual behavioral measures. The results revealed that three CNMs were robustly extracted under various different preprocessing conditions. Each of these CNMs was significantly correlated with different aspects of behavioral measures of both fluid and crystalized intelligence. The three CNMs were also able to predict several life outcomes, such as income and life satisfaction, achieving the highest performance when combined with behavioral intelligence measures as inputs. Our findings highlight the importance of state-unspecific brain networks to characterize fundamental individual variation.

Anxiety is one of the most common mental states of humans. Although it drives us to avoid frightening situations and to achieve our goals, it may also impose significant suffering and burden if it becomes extreme. Because we experience anxiety in a variety of forms, previous studies investigated neural substrates of anxiety in a variety of ways. These studies revealed that individuals with high state, trait, or pathological anxiety showed altered neural substrates. However, no studies have directly investigated whether the different dimensions of anxiety share a common neural substrate, despite its theoretical and practical importance. Here, we investigated a brain network of anxiety shared by different dimensions of anxiety in a unified analytical framework using functional magnetic resonance imaging (fMRI). We analyzed different datasets in a single scale, which was defined by an anxiety-related brain network derived from whole brain. We first conducted the anxiety provocation task with healthy participants who tended to feel anxiety related to obsessive-compulsive disorder (OCD) in their daily life. We found a common state anxiety brain network across participants (1585 trials obtained from 10 participants). Then, using the resting-state fMRI in combination with the participants' behavioral trait anxiety scale scores (879 participants from the Human Connectome Project), we demonstrated that trait anxiety shared the same brain network as state anxiety. Furthermore, the brain network between common to state and trait anxiety could detect patients with OCD, which is characterized by pathological anxiety-driven behaviors (174 participants from multi-site datasets). Our findings provide direct evidence that different dimensions of anxiety have a substantial biological inter-relationship. Our results also provide a biologically defined dimension of anxiety, which may promote further investigation of various human characteristics, including psychiatric disorders, from the perspective of anxiety.

The group transfer polymerization (GTP) with N-(trimethylsilyl)bis(trifluoromethanesulfonyl)imide (Me3SiNTf2) and 1-methoxy-1-triisopropylsiloxy-2-methyl-1-propene (iPr-SKA) has been studied using methyl acrylate (MA), ethyl acrylate (EA), n-butyl acrylate (nBA), 2-ethylhexyl acrylate (EHA), cyclohexyl acrylate (cHA), dicyclopentanyl acrylate (dcPA), tert-butyl acrylate (tBA), 2-methoxyethyl acrylate (MEA), 2-(2-ethoxyethoxy)ethyl acrylate (EEA), 2-(dimethylamino)ethyl acrylate (DMAEA), allyl acrylate (AlA), propargyl acrylate (PgA), 2-(triisopropylsiloxy)ethyl acrylate (TIPS-HEA), and triisopropylsilyl acrylate (TIPSA). Except for tBA and DMAEA, the GTPs of all other monomers described above proceeded rapidly in a living manner and produced well-defined homo acrylate polymers. The living nature of the GTPs of such acrylate monomers was further applied to the postpolymerizations of MA, EA, nBA, and MEA and also to the sequential GTPs of diverse acrylate monomers for preparing di- and multiblock acrylate p...

Anxiety is one of the most common mental states of humans. Although it drives us to avoid frightening situations and to achieve our goals, it may also impose significant suffering and burden if it becomes extreme. Because we experience anxiety in a variety of forms, previous studies investigated neural substrates of anxiety in a variety of ways. These studies revealed that individuals with high state, trait, or pathological anxiety showed altered neural substrates. However, no studies have directly investigated whether the different dimensions of anxiety share a common neural substrate, despite its theoretical and practical importance. Here, we investigated a neural network of anxiety shared by different dimensions of anxiety in a unified analytical framework using functional magnetic resonance imaging (fMRI). We analyzed different datasets in a single scale, which was defined by an anxiety-related neural network derived from whole brain. Through the fMRI task for provoking anxiety, we found a common neural network of state anxiety across participants (1,638 trials obtained from 10 participants). Then, using the resting-state fMRI in combination with the participants’ trait anxiety scale (879 participants from the Human Connectome Project), we demonstrated that trait anxiety also shared the same neural network as state anxiety. Furthermore, the common neural network between state and trait anxiety could detect patients with obsessive-compulsive disorder, which is characterized by pathological anxiety-driven behaviors (174 participants from multi-site datasets). Our findings provide direct evidence that different dimensions of anxiety are not completely independent but have a substantial biological inter-relationship. Our results also provide a biologically defined dimension of anxiety, which may promote further investigation of various human characteristics, including psychiatric disorders, from the perspective of anxiety.

Axial compressive simulations are performed on defective and non-defective multiwalledcarbon nanotubes (MWCNTs) using the molecular dynamics method, and the effectof defects upon the buckling behavior is discussed. In our previous study, changes in atomicstresses in MWCNTs with three layers were evaluated until buckling occurred. That studysuggested that the transition from homogeneous stress distributions to inhomogeneous onesplays an important role in the occurrence of buckling in MWCNTs, though the critical stressesor strains relating to buckling are dependent upon the structure and location of defects. In thepresent study, the atomic elastic stiffness of each atom, Bij , is evaluated to discuss the onsetof local buckling in MWCNTs with five layers. The det(Bij) of all atoms is found to change toa negative value long before buckling occurs, while the second smallest eigenvalues of Bij forsome atoms change to a negative value just prior to buckling. The existence of dense regions ofatoms that have two negative eigenvalues of Bij are found to vary as a function of the defectlocation, and to correspond with onset points of local buckling.

Background and Aim: Ultrathin transnasal endoscopy, used extensively in Japan, is considered to have inferior image quality and suction performance, and questionable diagnostic performance. So the aim of the present study was to compare the diagnostic performance of white light (WL) examination and non-magnified narrow-band imaging (NBI) examination in screening for esophageal disorders with ultrathin transnasal endoscopy. Methods: A prospective case study of 105 consecutive patients screened for upper gastrointestinal disorders at a single clinic in Tokyo Medical University Hospital. All subjects were diagnosed using WL, NBI and Lugol-staining examinations. Areas ≥ 5 mm clearly not a Lugol-staining lesion were defined as esophageal disorders and the rates of detection of the two examination methods (WL vs NBI) were compared. Results: For WL examination, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy (concordance rate) for esophageal disorders were 19.6%, 98.1%, 90.9%, 55.4%, and 59.2%, respectively, versus 60.8% 96.2%, 93.9%, 71.4%, and 78.6% for NBI. Conclusion: A useful level of diagnostic performance for esophageal disorders can be achieved with non-magnified narrow-band NBI ultrathin transnasal endoscopy.

Background and Aims: Helicobacter pylori infection rates are reported to be high in people over the age of 40 years, but are decreasing in younger age groups. A negative correlation has been reported between H. pylori infection and reflux esophagitis (RE). Methods: The subjects were 418 patients who underwent esophagogastroduodenoscopy and measurement of serum immunoglobulin G H. pylori antibodies examined as part of their routine health checks. Their mean age was 39.2 ± 8.3 years (range 22–58). We analyzed the RE findings (Los Angeles classification: A, B, C, D). Results: The total H. pylori infection rate was 33.7% (141/418). By age group, infection rates were 15.7% in the 20–29 years group, 28.0% in the 30–39 group, 34.3% in the 40–49 group and 69.1% in the 50–59 group. The proportion of H. pylori-negative subjects with RE was 23.5% (20–29, 22.9%; 30–39, 31.7%; 40–49, 32.4%; 50–59, 41.7%), significantly higher than that (12.1%) in H. pylori-positive subjects (20–29, 0%; 30–39, 16.7%; 40–49, 12.2%; 50–59, 10.5%). The severity of RE increased with advancing age in H. pylori-positive subjects, but not in H. pylori-negative subjects. Conclusion: In this study, higher rates of RE were seen in H. pylori-negative subjects. It may be, however, that the presence of H. pylori infection influences the progression of RE.

Background: We used transnasal ultrathin esophagogastroduodenoscopy (UT-EGD) to simultaneously perform realtime esophageal manometry and observe esophageal peristalsis. Methods: The subjects were 22 healthy volunteers and 10 patients with proton-pump inhibitor (PPI) dependent gastroesophageal reflux disease (GERD). We induced the primary peristaltic wave associated with swallowing and observed it endoscopically in the lower esophagus, at the same time measuring the intraesophageal pressure using a manometry catheter. Results: The mean primary peristaltic amplitude associated with swallowing was 65.6 ± 47.4 mmHg in the volunteer group, and 28.0 ± 25.6 mmHg in the GERD group. Although peristalsis was observed endoscopically in the GERD group, in some cases incomplete peristalsis left a small but definite lumen and in these subjects, the primary peristaltic wave was almost flat. Conclusions: The use of an ultrathin transnasal endoscope makes possible simultaneous manometry and endoscopic observation of the esophagus. This combination should prove useful in the evaluation of esophageal peristaltic function, such as in the diagnosing of GERD.

胃軸捻転症の成人発症例は稀である.今回,われわれは成人の横隔膜弛緩症が誘因となった胃軸捻転症を合併した胃癌に対し,外科的治療を行った1例を経験したので報告する.症例は69歳,男性,健診にて施行した上部消化管造影にて異常陰影を指摘され,当院を受診した.胃内視鏡検査にて胃癌と診断され当院入院となった.胸部単純X線写真,上部消化管造影にて横隔膜弛緩症を伴う胃軸捻転症(間膜軸性)と診断,開腹手術を施行した.手術は幽門側胃切除, D-2郭清, Billroth-I法再建および横隔膜縫縮術(重層形成法)を行った.術後5年を経過したが再発を認めず,経過良好である.

Objective: An important issue in cancer therapy is to investigate the mechanism for cellular sensitivity to anticancer agents such as cisplatin. Cisplatin is one of the DNA-damaging agents and several factors including p53 are related to the sensitivity to cisplatin in cancer. Protein kinase C (PKC) δ is known as a positive regulator for cisplatin-induced cell death. In our present study, we examined whether overexpression of PKCδ and p53 increases the sensitivity of the human gastric cancer cell line, MKN28, which has a mutation of p53 gene, to cisplatin. Methods: Cell viability and DNA content were measured in MKN28 with adenovirus-mediated expression of PKCδ and p53 after exposure to cisplatin. In addition, the active form of caspase-3 was detected by Western blotting. Results: Overexpression of exogenous PKCδ did not induce cell death in MKN28 but inhibited cell growth at 1 µg/ml cisplatin as compared to that by cisplatin alone. Moreover, overexpression of both wild-type p53 and exogenous PKCδ in MKN28 increased cisplatin-induced cell death in MKN28. Conclusion: These results suggest that PKCδ, in cooperation with p53, possibly regulates cisplatin-induced caspase-3-mediated cell death in gastric cancer.

症例は40歳の女性で, 主訴は嚥下困難であった. 近医にて胃食道接合部の胃粘膜下腫瘍と診断された. 超音波内視鏡検査にて食道胃接合部直下に存在する胃壁第4層由来の胃嚢胞と診断した. 自験例は嚥下困難があり悪性が否定できず噴門側胃切除, 空腸間置再建術を施行した. 病理組織学的所見から嚢胞壁の内側には幼若な繊毛円柱上皮を認め, また核は基底部と中央部に多列に存在しており食道原基由来の組織の迷入が示唆された. 胃に発生した嚢胞性病変は胃嚢胞, enterogenous cyst, 消化管重複症などとさまざまに報告されている. 我々は内壁が幼若な繊毛円柱上皮で構成された胃嚢胞の1例を経験したので報告した.

食道癌は頭頸部癌との重複が多いことが知られているが，その原因についてはいまだ十分に解明されていない。今回われわれは，喫煙量(Brinkman index: BI)，飲酒量(sake index: SI)，human papilloma virus (HPV)，癌関連遺伝子(p53，pRb，p16)，アルデヒド脱水素酵素(ALDH2)が食道癌と頭頸部癌との重複癌の発生に関与しているかどうかを食道癌単独症例と比較検討した。その結果，BI，SI，食道内多発癌は重複癌症例で有意に多かった(p