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Although fasciculation on muscle ultrasonography (MUS) is useful in diagnosing amyotrophic lateral sclerosis (ALS), its applicability to early diagnosis remains unclear. We aimed to develop and validate diagnostic models especially beneficial to early-stage ALS via machine learning.We investigated 100 patients with ALS, including 50 with early-stage ALS within 9 months from onset, and 100 without ALS. Fifteen muscles were bilaterally observed for 10 s each and the presence of fasciculations was recorded. Hierarchical clustering and nominal logistic regression, neural network, or ensemble learning were applied to the training cohort comprising the early-stage ALS to develop MUS-based diagnostic models, and they were tested in the validation cohort comprising the later-stage ALS.Fasciculations on MUS in the brainstem or thoracic region had high specificity but limited sensitivities and predictive profiles for diagnosis of ALS. A machine learning-based model comprising eight muscles in the four body regions had a high sensitivity (recall), specificity, and positive predictive value (precision) for both early- and later-stage ALS patients.We developed and validated MUS-fasciculation-based diagnostic models for early- and later-stage ALS.Fasciculation detected in relevant muscles on MUS can contribute to the diagnosis of ALS from the early stage.

Transthyretin amyloidosis (ATTR) variant is a life-threatening hereditary disease predominantly affecting the peripheral nervous system and heart. Tafamidis, which prevents the deposition of amyloid by stabilizing transthyretin, is available for the treatment of neuropathy and cardiomyopathy of ATTR. However, whether tafamidis could eliminate established amyloid deposits and improve cardiac function remains unknown. We reported a case of regression of left ventricular hypertrophy after tafamidis therapy in a patient with an ATTR variant. J. Med. Invest. 69 : 320-322, August, 2022.

Recently, the biallelic expansion of an AAGGG repeat in RFC1 was reported as a cause of cerebellar ataxia with neuropathy and vestibular areflexia syndrome. This mutation has also been reported in more selected nervous disorders, including pure sensory axonal polyneuropathy. Thus, the multisystem disorders caused by this mutation are now considered RFC1-related spectrum disorders. Here, we review the previous reports about RFC1-related spectrum disorders from the aspect of neuropathy.

This paper analyzes the behavior of a firm facing an ambiguous technology shock and the effects of the attitude toward ambiguity on optimal capital investment using the smooth ambiguity model of Klibanoffet al. (2005). Although it seems intuitive that an increase in ambiguity aversion always reduces the optimal capital investment, this is not necessarily true because the shape of the production function plays a key role in determining the effect. Under some conditions, we show that the optimal amount of capital investment increases (decreases) in ambiguity aversion if the production function is substitute (complement), and that this result is counterintuitive when the production function is substitute. Furthermore, our main results hold if we assume the alpha-maxmin preferences in Ghirardato et al. (2004).

ObjectiveAutosomal recessive spinocerebellar ataxia type 9 (SCAR9) has received attention due to its potential response to coenzyme Q10 (CoQ10) supplementation; however, the response has so far been limited and variable.MethodsWe report a SCAR9 patient with severe hypophosphatemia who responded well to CoQ10 and phosphate repletion.ResultsA 70-year-old man (the offspring of a consanguineous marriage) presented with cerebellar ataxia and intense fatigue after exercise. Whole-exome sequencing identified a novel homozygous deletion mutation (NM_020247.5:c.1218_1219del) inCOQ8A. We thus diagnosed him with SCAR9. Supplementation of CoQ10 alleviated his symptoms, with the Scale for the Assessment and Rating of Ataxia (SARA) dropping from 16 to 14. During the course of the disease, he demonstrated continuous hypophosphatemia caused by renal phosphate wasting. Gait dysfunction due to weakness and eye movement was partially alleviated, and SARA dropped from 17 to 13 after phosphate repletion.DiscussionPhosphate repletion should be considered for patients with severe hypophosphatemia without any apparent subjective symptoms. In this case, phosphate repletion could have improved myopathy leading to partial improvement in the patient's symptoms. Further analyses regarding the association between COQ8A mutation and phosphate wasting are required to elucidate the detailed pathogenesis.Classification of EvidenceThis provides Class IV evidence. This is a single observational study without controls.

The diagnosis of amyotrophic lateral sclerosis (ALS) requires both upper and lower motor neuron signs. However, quite a few patients with ALS lack the upper motor neuron sign during the disease. This study sought to investigate whether metabolites, including glutamate (Glu), N-acetyl aspartate (NAA), and gamma aminobutyric acid (GABA), in the supplementary motor area (SMA) measured by magnetic resonance spectroscopy (MRS), could be a surrogate biomarker for ALS. Twenty-five patients with ALS and 12 controls underwent 3.0-T MR scanning, which measured Glu, NAA, and GABA. Finally, receiver operating characteristic (ROC) curves were created and the area under curve (AUC) was calculated to assess the diagnostic power. Logistic regression analysis revealed the usefulness of both Glu and NAA for the differentiation of ALS from controls (Glu, P = 0.009; NAA, P = 0.033). The ratio of Glu to NAA or GABA was significantly increased in patients with ALS (Glu/NAA, P = 0.027; Glu/GABA, P = 0.003). Both the AUCs were more than 0.7, with high specificity but low sensitivity. The present findings might indicate that both the Glu/NAA and the Glu/GABA ratios in the SMA could be potential biomarkers for the diagnosis of ALS.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder affecting the upper and lower motor neurons causing progressive weakness. It eventually involves the diaphragm which leads to respiratory paralysis and subsequently death. Phrenic nerve (PN) conduction studies and diaphragm ultrasound has been studied and correlated with pulmonary function tests in ALS patients. However, PN ultrasonography has not been employed in ALS. This study aims to sonographically evaluate the morphologic appearance of the PN of ALS patients. Thirty-eight ALS patients and 28 normal controls referred to the neurophysiology laboratory of two institutions were retrospectively included in the study. Baseline demographic and clinical variables such as disease duration, ALS Functional Rating Scale-Revised score, and ALS region of onset were collected. Ultrasound was used to evaluate the PN cross-sectional area (CSA) of ALS and control subjects. The mean PN CSA of ALS patients were 1.08 ± 0.39 mm on the right and 1.02 ± 0.34 mm on the left. The PN CSA of ALS patients were significantly decreased compared to controls (p value

Serum neurofilament light chain (NfL) and chitinase 3-like 1 (CHI3L1, also called YKL-40) concentrations are attractive candidate biomarkers for neurodegenerative disorders, which include amyotrophic lateral sclerosis (ALS) and parkinsonian disorders. We aimed to assess the diagnostic power of serum NfL and CHI3L1 concentrations with regard to the early diagnosis of ALS and Parkinson's disease (PD). We studied 157 individuals, which included 41 healthy controls, 8 patients with ALS mimics, 18 patients initially diagnosed with ALS (ID-ALS), 32 patients late-diagnosed with ALS (LD-ALS), 29 patients with PD, 12 patients with PD mimics, and 17 patients initially diagnosed with atypical parkinsonian disorders (ID-APDs) at the initial stage of diagnosis. Electrochemiluminescence was used to measure the concentrations of serum NfL and CHI3L1, the diagnostic performance of which was assessed using the area under the receiver operating curves (AUCs). The AUCs of serum NfL were 0.90 for discriminating ALS mimics from LD-ALS at the initial stage of diagnosis and 0.89 for discriminating ALS mimics from ALS (LD/ID-ALS). The AUCs of serum NfL were 0.76 for discriminating PD from PD mimics at the initial stage of diagnosis, and 0.80 for discriminating PD from APD. No significant difference existed in serum CHI3L1 concentrations between individuals with suspected ALS or parkinsonism (p = 0.14, and p = 0.44, respectively). Serum NfL had excellent and almost good diagnostic performances for patients with ALS and PD, respectively, at the initial stage of diagnosis, whereas no significant difference existed in serum CHI3L1 between any groups.

Accumulated medical information is necessary to determine comorbidity risk between a primary disease and secondary diseases. However, medical decisions often must be made without conclusive evidence because individuals do not have sufficient information. By introducing ambiguity regarding comorbidities, we describe situations in which individuals face a set of plausible comorbidity risks that determines the correlations between primary and secondary diseases. This study examines the conditions under which the willingness to pay for health improvement is larger with comorbidity ambiguity than without it. This study also examines the effect of changes in ambiguity and ambiguity aversion on the willingness to pay.

Objective Given the recent advent in machine learning and artificial intelligence on medical data analysis, we hypothesized that the deep learning algorithm can classify resting needle electromyography (n-EMG) discharges. Methods Six clinically observed resting n-EMG signals were used as a dataset. The data were converted to Mel-spectrogram. Data augmentation was then applied to the training data. Deep learning algorithms were applied to assess the accuracies of correct classification, with or without the use of pre-trained weights for deep-learning networks. Results While the original data yielded the accuracy up to 0.86 on the test dataset, data-augmentation up to 200,000 training images showed significant increase in the accuracy to 1.0. The use of pre-trained weights (fine tuning) showed greater accuracy than “training from scratch”. Conclusions Resting n-EMG signals were successfully classified by deep-learning algorithm, especially with the use of data augmentation and transfer learning techniques. Significance Computer-aided signal identification of clinical n-EMG testing might be possible by deep-learning algorithms.

COL4A1-related disorders are characterized by a higher incidence of cerebral hemorrhage than other hereditary cerebral small vessel diseases. Accumulating data have shown broad phenotypic variations, and extracerebral hemorrhages have been linked to these disorders. Moreover, the coexistence of neural tumors has been described. Here, we report a Japanese family with a novel COL4A1 variant, including a patient with recurrent epistaxis and glioblastoma.

Background Transection‐induced axonal retrograde degeneration, in contrast to Wallerian degeneration, has not been widely recognized in clinical practice. Aims of the Study To assess a potential of corticospinal tractography for detecting axonal retrograde degeneration. Methods We assessed the corticospinal tractography of a 74‐year‐old woman with monoplegia of the lower limb due to a unilateral thoracic spinal cord tumor. Results The tractography revealed integrity reduction of the corticospinal tract in the cerebra contralateral to the spinal cord tumor. Conclusions The present report supports that magnetic resonance tractography has the potential for detecting this under‐recognized phenomenon., To assess a potential of corticospinal tractography for detecting axonal retrograde degeneration, an under‐recognized phenomenon, we performed the cerebral corticospinal tractography of a 74‐year‐old woman with monoplegia of the lower limb due to a unilateral thoracic spinal cord tumor. The tractography revealed integrity reduction of the corticospinal tract in the cerebra contralateral to the spinal cord tumor. The present report supports that magnetic resonance tractography has the potential for detecting this under‐recognized phenomenon.

This paper considers the optimal demand for insurance in the presence of state dependent background uncertainty, that is, the uncertainty is dependent on the states which are clarified by the realization of the loss. First, we consider a situation in which the state dependent background risk is ordered by the stochastic dominance relation. When the background risk conditional on the loss state is worse (better) than the no-loss state, we determine the condition in which the insurance demand is higher (lower) compared with the state independent background risk. Second, we consider a situation in which the uncertainty is different between the loss and the no-loss state. When ambiguity is introduced into the loss (no-loss) state, introducing ambiguity is higher (lower) compared with the risk case. Last, we discuss resolving the insurance demand puzzles by the different recognition of state dependent background uncertainty.

It is observed that stock price fluctuations are slowly in upward phases like bubble, but fast in downward phases like its burst. This paper provides a new theoretical explanation of this phenomenon, especially why stock price drops sharply, based on the timing of stock sales. Investors tend to be more risk averse when the timing of decision making is closer for the present. This tendency can explain that the timing of stock sales is different according to risk aversion. When investors become excessive risk averse, they tend to sell stocks more in the present. This result is consistent with asymmetric patterns of stock price fluctuation when investors are moderate risk averse in normal economic conditions, but excessive risk averse in abnormal economic condition like the fear of financial crises.

Cognitive decline affects the clinical course in patients with Parkinson’s disease (PD) and contributes to a poor prognosis. However, little is known about the underlying network-level abnormalities associated with each cognitive domain. We aimed to identify the networks related to each cognitive domain in PD using resting-state functional magnetic resonance imaging (MRI). Forty patients with PD and 15 normal controls were enrolled. All subjects underwent MRI and the Mini-Mental State Examination. Furthermore, the cognitive function of patients with PD was assessed using the Montreal Cognitive Assessment (MoCA). We used independent component analysis of the resting-state functional MRI for functional segmentation, followed by reconstruction to identify each domain-related network, to predict scores in PD using multiple regression models. Six networks were identified, as follows: the visuospatial-executive-domain-related network (R2 = 0.54, p &lt, 0.001), naming-domain-related network (R2 = 0.39, p &lt, 0.001), attention-domain-related network (R2 = 0.86, p &lt, 0.001), language-domain-related network (R2 = 0.64, p &lt, 0.001), abstraction-related network (R2 = 0.10, p &lt, 0.05), and orientation-domain-related network (R2 = 0.64, p &lt, 0.001). Cerebellar lobule VII was involved in the visuospatial-executive-domain-related and attention-domain-related networks. These two domains are involved in the first three listed nonamnestic cognitive impairment in the diagnostic criteria for PD with dementia (PDD). Furthermore, Brodmann area 10 contributed most frequently to each domain-related network. Collectively, these findings suggest that cerebellar lobule VII may play a key role in cognitive impairment in nonamnestic types of PDD.

Mouse embryonic fibroblasts lacking D-3-phosphoglycerate dehydrogenase (Phgdh), which catalyzes the first step of de novo synthesis of l-serine, are particularly sensitive to depletion of extracellular L-serine. In these cells, depletion of l-serine leads to a rapid reduction of intracellular L-serine, cell growth arrest, and altered expression of a wide variety of genes. However, it remains unclear whether reduced availability of extracellular l-serine elicits such responses in other cell types expressing Phgdh. Here, we show in the mouse hepatoma cell line Hepa1-6 that extracellular l-serine depletion transiently induced transcriptional activation of Atf4-target genes, including cation transport regulator-like protein 1 (Chac1). Expression levels of these genes returned to normal 24 h after l-serine depletion, and were suppressed by the addition of l-serine or glycine in the medium. Extracellular l-serine depletion caused a reduction of extracellular and intracellular glycine levels but maintained intracellular l-serine levels in the cells. Further, Phgdh and serine hydroxymethyltransferase 2 (Shmt2) were upregulated after l-serine depletion. These results led us to conclude that the Atf4-mediated gene expression program is activated by extracellular l-serine depletion in Hepa1-6 cells expressing Phgdh, but is antagonized by the subsequent upregulation of l-serine synthesis, mainly from autonomous glycine consumption.

Some people have optimistic expectations regarding their accident probability, and thus, refrain from purchasing adequate insurance. This study investigates how insurance firms use advertisements to lower the ratio of optimistic individuals in the market. The main results are as follows: first, the optimal level of advertisements is maximized when the insurance premium is moderate. Second, the maximum level of advertisement varies according to the degree of optimism, which is measured by the difference between accurate and optimistic accident probabilities. Third, the advertisement decision is affected by the free-rider problem, and the equilibrium number of insurance firms with advertisement is always larger than that of firms without advertisement in a competitive insurance market.

This study examines how basis ambiguity influences the demand for index insurance. Ambiguity is introduced into the statistical relationship between the loss and the index because they are more difficult to guess than the occurrence of the loss and the index individually. Basis ambiguity lowers the demand for index insurance and increases the threshold to hold the index insurance. This is a possible explanation for the very low demand and participation in index insurance. Further, we consider how changes in ambiguity and ambiguity aversion influence the demand.

This study considers how changes in wealth affect insurance demand when individuals suffer disutility from regret. Anticipated regret stems from a comparison between the ex-post maximum and actual wealth. We consider a situation wherein individuals maximize their expected utility incorporating anticipated regret. The wealth effect on insurance demand can be classified into the risk and the regret effects. These effects are determined by the properties of the utility function and the regret function. We show that insurance can be normal when individuals place weight on anticipated regret, even though the utility function exhibit decreasing absolute risk aversion. This result indicates that regret theory is a possible explanation to the wealth effect puzzle, in which insurance is normal from empirical observation, but it should be inferior by theoretical prediction under expected utility theory.

This study considers a pure exchange economy with insurance against ambiguous loss. Ambiguity preferences are represented by the dual theory of the smooth ambiguity model from Iwaki and Osaki (2014). The economic premium principle of Bühlmann (1980, 1984) is extended to ambiguity. We also perform some comparative statics and present sufficient conditions under which an increase in ambiguity aversion increases insurance demand and insurance premiums. Contrary to the result in Tsanakas and Christofides (2006), the optimal demand for insurance is not always comonotonic, because our model permits an economy comprising both ambiguity averse and ambiguity loving agents.