CFAP47 is a novel causative gene implicated in X-linked polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is a well-described condition in which ~80% of cases have a genetic explanation, while the genetic basis of sporadic cystic kidney disease in adults remains unclear in ~30% of cases. This study aimed to identify novel genes associated with polycystic kidney disease (PKD) in patients with sporadic cystic kidney disease in which a clear genetic change was not identified in established genes. A next-generation sequencing panel analyzed known genes related to renal cysts in 118 sporadic cases, followed by whole-genome sequencing on 47 unrelated individuals without identified candidate variants. Three male patients were found to have rare missense variants in the X-linked gene Cilia And Flagella Associated Protein 47 (CFAP47). CFAP47 was expressed in primary cilia of human renal tubules, and knockout mice exhibited vacuolation of tubular cells and tubular dilation, providing evidence that CFAP47 is a causative gene involved in cyst formation. This discovery of CFAP47 as a newly identified gene associated with PKD, displaying X-linked inheritance, emphasizes the need for further cases to understand the role of CFAP47 in PKD.

Cytokine Release Syndrome with Relative Adrenal Insufficiency Induced by Ipilimumab and Nivolumab Combination Therapy for Clear Cell Renal Cell Carcinoma.

Combination therapy with ipilimumab and nivolumab is indicated for many types of cancers; however, several patients experience immune-related adverse events (irAEs). We herein report a case of cytokine release syndrome (CRS) in a 63-year-old woman with stage IV left clear cell renal cell carcinoma. Our patient developed CRS while taking prednisolone, 43 days after the start of ipilimumab and nivolumab administration. The patient was treated with steroid pulse therapy, which improved the symptoms of shock and respiratory failure. Increased vascular permeability and relative adrenal insufficiency are considered to be the main pathogeneses. The early administration of high-dose steroids is crucial as a replacement for corticosteroids.

Genetic insights into Tietz albinism-deafness syndrome: A new dominant-negative mutation in MITF.

Tietz albinism-deafness syndrome (TADS) is a rare and severe manifestation of Waardenburg syndrome that is primarily linked to mutations in MITF. In this report, we present a case of TADS resulting from a novel c.637G>C mutation in MITF (p.Glu213Gln; GenBank Accession number: NM_000248). A 3-year-old girl presented with congenital generalized hypopigmentation of the hair, skin, and irides along with complete sensorineural hearing loss. Histopathological and electron microscopy investigations indicated that this variant did not alter the number of melanocytes in the skin but significantly impaired melanosome maturation within melanocytes. Comprehensive melanin analysis revealed marked reductions in both eumelanin (EM) and pheomelanin (PM) rather than changes in the EM-to-PM ratio observed in oculocutaneous albinism. We conducted an electrophoretic mobility shift assay to investigate the binding capability of the identified variant to DNA sequences containing the E-box motif along with other known variants (p.Arg217del and p.Glu213Asp). Remarkably, all three variants exhibited dominant-negative effects, thus providing novel insights into the pathogenesis of TADS. This study sheds light on the genetic mechanisms underlying TADS and offers a deeper understanding of this rare condition and its associated mutations in MITF.

Bright Fluorescent p-Phenylene-bridged Triarylmethyl Highly Stable Diradical.

Two units of highly stable luminescent triarylmethyl radical, (3,5-dichloro-4-pyridyl)bis(2,4,6-trichlorophenyl)methyl radical (PyBTM), were bridged by p-phenylene linker. The photoluminescence quantum yield (PLQY) of PyBTM-PhPyBTM was at most 0.4 % in various organic solvents. Adding two mesityl groups on the terminals did not improve the PLQY. In the MesPyBTM-PhPyBTM-Mes, the mesityl group did not worked as an electron donor unlike the previously reported monoradical MesPyBTM. However, adding two n-hexyl groups on the bridging p-phenylene did greatly improve it, and the PLQY of the PyBTM-(Hex2Ph)PyBTM was 7 % in dichloromethane and acetone, and 12 % in poly(methyl methacrylate) (PMMA) film. Twisting p-phenylene linker by hexyl groups hindered the π-conjugation and suppressed the non-radiative decay of the excited state.

A Robust Approach Assisted by Signal Quality Assessment for Fetal Heart Rate Estimation from Doppler Ultrasound Signal.

Fetal heart rate (FHR) monitoring, typically using Doppler ultrasound (DUS) signals, is an important technique for assessing fetal health. In this work, we develop a robust DUS-based FHR estimation approach complemented by DUS signal quality assessment (SQA) based on unsupervised representation learning in response to the drawbacks of previous DUS-based FHR estimation and DUS SQA methods. We improve the existing FHR estimation algorithm based on the autocorrelation function (ACF), which is the most widely used method for estimating FHR from DUS signals. Short-time Fourier transform (STFT) serves as a signal pre-processing technique that allows the extraction of both temporal and spectral information. In addition, we utilize double ACF calculations, employing the first one to determine an appropriate window size and the second one to estimate the FHR within changing windows. This approach enhances the robustness and adaptability of the algorithm. Furthermore, we tackle the challenge of low-quality signals impacting FHR estimation by introducing a DUS SQA method based on unsupervised representation learning. We employ a variational autoencoder (VAE) to train representations of pre-processed fetal DUS data and aggregate them into a signal quality index (SQI) using a self-organizing map (SOM). By incorporating the SQI and Kalman filter (KF), we refine the estimated FHRs, minimizing errors in the estimation process. Experimental results demonstrate that our proposed approach outperforms conventional methods in terms of accuracy and robustness.

Single-Element Dual-Interferometer for Precision Inertial Sensing: Sub-Picometer Structural Stability and Performance as a Reference for Laser Frequency Stabilization.

Future GRACE-like geodesy missions could benefit from adopting accelerometer technology akin to that of the LISA Pathfinder, which employed laser interferometric readout at the sub-picometer level in addition to the conventional capacitive sensing, which is at best at the level of 100 pm. Improving accelerometer performance holds great potential to enhance the scientific output of forthcoming missions, carrying invaluable implications for research in climate, water resource management, and disaster risk reduction. To reach sub-picometer displacement sensing precision in the millihertz range, laser interferometers rely on suppression of laser-frequency noise by several orders of magnitude. Many optical frequency stabilization methods are available with varying levels of complexity, size, and performance. In this paper, we describe the performance of a Mach-Zehnder interferometer based on a compact monolithic optic. The setup consists of a commercial fiber injector, a custom-designed pentaprism used to split and recombine the laser beam, and two photoreceivers placed at the complementary output ports of the interferometer. The structural stability of the prism is transferred to the laser frequency via amplification, integration, and feedback of the balanced-detection signal, achieving a fractional frequency instability better than 6 parts in 1013, corresponding to an interferometer pathlength stability better than 1pm/Hz. The prism was designed to host a second interferometer to interrogate the position of a test mass. This optical scheme has been dubbed "single-element dual-interferometer" or SEDI.

Detection and isolation of a new member of Burkholderiaceae-related endofungal bacteria from Saksenaea boninensis sp. nov., a new thermotolerant fungus in Mucorales.

Thermotolerance in Mucorales (Mucoromycotina) is one of the factors to be opportunistic pathogens, causing mucormycosis. Among thermotolerant mucoralean fungi, Burkholderiaceae-related endobacteria (BRE) are rarely found and the known range of hosts is limited to Rhizopus spp. The phylogenetic divergence of BRE has recently expanded in other fungal groups such as Mortierellaceae spp. (Mortierellomycotina); however, it remains unexplored in Mucorales. Here, we found a thermotolerant mucoralean fungus obtained from a litter sample collected from Haha-jima Island in the Ogasawara (Bonin) Islands, Japan. The fungus was morphologically, phylogenetically, and physiologically characterized and proposed as a new species, Saksenaea boninensis sp. nov. Besides the fungal taxonomy, we also found the presence of BRE in isolates of this species by diagnostic PCR amplification of the 16S rRNA gene from mycelia, fluorescence microscopic observations, and isolation of the bacterium in pure culture. Phylogenetic analysis of the 16S rRNA gene of BRE revealed that it is distinct from all known BRE. The discovery of a culturable BRE lineage in the genus Saksenaea will add new insight into the evolutional origin of mucoralean fungus-BRE associations and emphasize the need to pay more attention to endofungal bacteria potentially associated with isolates of thermotolerant mucoralean fungi causing mucormycosis.

Retroperitoneal hematoma: A rare complication of percutaneous pedicle screw in an osteoporotic patient.

Background: Percutaneous pedicle screw (PPS) placement is an established technique for minimally invasive surgery. However, life-threatening hematomas may occur in osteoporotic patients undergoing percutaneous screw placement. Case Description: An 80-year-old female with an osteoporotic T10 chance fracture developed a life-threatening hematoma following a T8-L3 posterior fusion performed with PPS. Prompt angiography diagnosed a life-threatening hematoma attributed to laceration of the left third lumbar artery occurring following pedicle screw (PS) placement into an osteoporotically fractured left L3 transverse process. This was immediately and successfully embolized. Conclusion: An 80-year-old female with multiple lumbar osteoporotic fractures developed a life-threatening hematoma during a T8-L3 PS fusion. When the lumbar computed tomography angiography diagnosed a laceration of the left L3 lumbar artery, immediate transarterial embolization proved life-saving.

Benign endobronchial lipoma causing repeated pneumonia.

Endobronchial lipomas are rare; nonetheless, physicians should consider them as a differential diagnosis in patients with repeated pneumonia. Computed tomography and bronchoscopy are recommended for diagnosis. In this case, the patient's cough was ameliorated after undergoing a right basal segmentectomy.

Solar-pumped fiber laser using a solid-state luminescent solar collector.

We have developed a fully planar solar-pumped fiber laser using a solid-state luminescent solar collector (LSC). This laser does not use any focusing device, such as a lens or mirror; thus, it can lase without tracking the sun. Our developed device with an aperture of 30 cm emits 15 mW, corresponding to an optical-to-optical conversion efficiency of 0.023% and a collection efficiency of 0.21 W/m2. A 12-fold improvement over a previously developed liquid LSC is achieved by combining the total internal reflection of the solid-state LSC with dielectric multilayer mirrors. The observed laser power is in good agreement with that predicted via numerical simulation, demonstrating the effectiveness of our proposed method.

Pneumocystis pneumonia diagnosed by repeated measurements of ß-D-glucan levels.

ß-D-glucan is extensively employed as a supplementary diagnostic tool for Pneumocystis pneumonia (PCP) and typically yields positive results in most cases. We present a case of a 73-year-old woman with a history of rheumatoid arthritis, who was receiving biological agents and was admitted due to pneumonia. Initially, the ß-D-glucan test was negative. However, as the disease progressed, it eventually turned positive, leading to the diagnosis of PCP. The patient was treated with corticosteroids and trimethoprim-sulfamethoxazole, resulting in pneumonia resolution. Our findings suggest that repeated assessment of ß-D-glucan levels holds diagnostic value in patients without human immunodeficiency virus infection.

Factors affecting severity of pressure ulcers: Impact of number of medications.

Polypharmacy, which refers to the situation of a patient taking more medications than is clinically necessary, has become a major problem in recent years. Although the effects of medications on pressure ulcers have been reported, there are no reports on the impact of the total number of medications on pressure ulcers. The purpose of this study was to investigate the effect of number of medications on the severity of pressure ulcers. Participants included 94 patients who were admitted to Chiba University Hospital with pressure ulcers between April 2013 and March 2021. Univariate analysis identified ulcer depth, weight loss and anticoagulant use to be factors that contributed to the severity of pressure ulcers. Multiple regression analysis was performed for six variables, namely, the number of medications, ulcer depth, weight loss and anticoagulant use, as well as diabetes status and total serum protein level, which have been reported to be associated with pressure ulcers in previous studies. The following independent risk factors were identified: weight loss (ß 0.207, 95% confidence interval [CI] 0.700-3.193; p = 0.003), anticoagulant use (ß 0.161, 95% CI 0.271-3.088; p = 0.020) and ulcer depth (ß 0.719, 95% CI 7.172-10.329; p < 0.001). The number of medications was not a significant factor. This study revealed that the number of medications a patient is taking does not affect the severity of pressure ulcers. The findings should provide useful information for the management of pressure ulcers.

Ultrafast Subpicosecond Magnetization of a 2D Ferromagnet.

Strong spin-charge interactions in several ferromagnets are expected to lead to subpicosecond (sub-ps) magnetization of the magnetic materials through control of the carrier characteristics via electrical means, which is essential for ultrafast spin-based electronic devices. Thus far, ultrafast control of magnetization has been realized by optically pumping a large number of carriers into the d or f orbitals of a ferromagnet; however, it is extremely challenging to implement by electrical gating. This work demonstrates a new method for sub-ps magnetization manipulation called wavefunction engineering, in which only the spatial distribution (wavefunction) of s (or p) electrons is controlled and no change is required in the total carrier density. Using a ferromagnetic semiconductor (FMS) (In,Fe)As quantum well (QW), instant enhancement, as fast as 600 fs, of the magnetization is observed upon irradiating a femtosecond (fs) laser pulse. Theoretical analysis shows that the instant enhancement of the magnetization is induced when the 2D electron wavefunctions (WFs) in the FMS QW are rapidly moved by a photo-Dember electric field formed by an asymmetric distribution of the photocarriers. Because this WF engineering method can be equivalently implemented by applying a gate electric field, these results open a new way to realize ultrafast magnetic storage and spin-based information processing in present electronic systems.

Unsupervised Learning-Based Non-Invasive Fetal ECG Muti-Level Signal Quality Assessment.

OBJECTIVE: To monitor fetal health and growth, fetal heart rate is a critical indicator. The non-invasive fetal electrocardiogram is a widely employed measurement for fetal heart rate estimation, which is extracted from the electrodes placed on the surface of the maternal abdomen. The qualities of the fetal ECG recordings, however, are frequently affected by the noises from various interference sources. In general, the fetal heart rate estimates are unreliable when low-quality fetal ECG signals are used for fetal heart rate estimation, which makes accurate fetal heart rate estimation a challenging task. So, the signal quality assessment for the fetal ECG records is an essential step before fetal heart rate estimation. In other words, some low-quality fetal ECG signal segments are supposed to be detected and removed by utilizing signal quality assessment, so as to improve the accuracy of fetal heart rate estimation. A few supervised learning-based fetal ECG signal quality assessment approaches have been introduced and shown to accurately classify high- and low-quality fetal ECG signal segments, but large fetal ECG datasets with quality annotation are required in these methods. Yet, the labeled fetal ECG datasets are limited. Proposed methods: An unsupervised learning-based multi-level fetal ECG signal quality assessment approach is proposed in this paper for identifying three levels of fetal ECG signal quality. We extracted some features associated with signal quality, including entropy-based features, statistical features, and ECG signal quality indices. Additionally, an autoencoder-based feature is calculated, which is related to the reconstruction error of the spectrograms generated from fetal ECG signal segments. The high-, medium-, and low-quality fetal ECG signal segments are classified by inputting these features into a self-organizing map. MAIN RESULTS: The experimental results showed that our proposal achieved a weighted average F1-score of 90% in three-level fetal ECG signal quality classification. Moreover, with the acceptable removal of detected low-quality signal segments, the errors of fetal heart rate estimation were reduced to a certain extent.

A Denoising Method Using Deep Image Prior to Human-Target Detection Using MIMO FMCW Radar.

A Multiple-Input Multiple-Output (MIMO) Frequency-Modulated Continuous Wave (FMCW) radar can provide a range-angle map that expresses the signal power against each range and angle. It is possible to estimate object locations by detecting the signal power that exceeds a threshold using an algorithm, such as Constant False Alarm Rate (CFAR). However, noise and multipath components often exist over the range-angle map, which could produce false alarms for an undesired location depending on the threshold setting. In other words, the threshold setting is sensitive in noisy range-angle maps. Therefore, if the noise is reduced, the threshold can be easily set to reduce the number of false alarms. In this paper, we propose a method that improves the CFAR threshold tolerance by denoising a range-angle map using Deep Image Prior (DIP). DIP is an unsupervised deep-learning technique that enables image denoising. In the proposed method, DIP is applied to the range-angle map calculated by the Curve-Length (CL) method, and then the object location is detected over the denoised range-angle map based on Cell-Averaging CFAR (CA-CFAR), which is a typical threshold setting algorithm. Through the experiments to estimate human locations in indoor environments, we confirmed that the proposed method with DIP reduced the number of false alarms and estimated the human location accurately while improving the tolerance of the threshold setting, compared to the method without DIP.

Spatiotemporal Pavlovian head-fixed reversal learning task for mice.

Our world is full of uncertainty. Animals, including humans, need to behave flexibly to adjust to ever-changing environments. Reversal learning tasks have been used to assess behavioral flexibility in many species. However, there are some limitations in the traditional free-moving methodology, including (1) sessions to train the animals, (2) within-session number of trials associated with reversals, (3) factors of physical movement unrelated to the task in the maze or operant box, and (4) incompatibility with techniques, such as two-photon imaging. Therefore, to address these limitations, we established a novel spatiotemporal Pavlovian head-fixed reversal learning task for mice. Six experimentally naive adult C57BL/6J mice were used in this study. First, we trained head-fixed mice on a fixed-time schedule task. Sucrose solution was delivered every 10 s with a single drinking spout placed within the licking distance of the mice. After the mice showed anticipatory licking toward the timing of sucrose solution delivery, we began training the mice on the fixed-time schedule reversal learning task with two licking spouts. In this task, sucrose solution was delivered through one of the two drinking spouts. The rewarding spout was switched every 10 trials. Mice quickly learned to switch anticipatory licking to the rewarding side of the spouts, suggesting that they learned this head-fixed reversal learning task. Using the head-fixed experimental design, behavioral measures can be simplified by eliminating the complex behavioral sequences observed in free-moving animals. This novel head-fixed reversal learning task is a useful assay for studying the neurobiological mechanism of behavioral flexibility that is impaired in various psychopathological conditions.

Non-contact Blood Pressure Estimation Method Based on Blood Pressure Category Classification.

In recent years, non-contact Blood Pressure (BP) measurement has been attracting attention for measuring our health status in daily life. A Doppler radar can observe pulse waves caused by chest wall displacement due to heartbeat. BP can be estimated by constructing a BP estimation model using BP-related features obtained from the pulse wave. However, compared to when modeling for each subject, the BP esti-mation accuracy deteriorates significantly when modeling with multiple subjects including the testing subject. To deal with this limitation, BP category classification has been introduced into PhotoPlethysmoGraphy (PPG)-based BP estimation. In this paper, we develop a Doppler radar-based BP estimation method based on BP category classification. In the proposed method, the pulse waves extracted from a Doppler radar are classified into three categories, "Low BP", "Normal BP", and "High BP" by k-Nearest Neighbor (kNN) based on the features that correlate with BP. The SBP estimation model is trained for each BP category. After the BP category classification, SBP is then estimated by using the model corresponding to the classified BP category. The experimental results showed that the proposed method with BP category classification estimated SBP accurately, compared to without BP category classification.

Arterial Blood Pressure Estimation Method from Electrocardiogram Signals using U-Net.

Previous works proposed deep learning models to estimate blood pressure from electrocardiogram (ECG) signals. However, they can only estimate max, min, and mean arterial blood pressures and cannot estimate arterial blood pressure (ABP). This paper presents the ABP estimation method from ECG signals using the deep learning model of U-Net. Through the performance evaluation with signals of about 185 hours, we observed that the proposed method estimated ABP with high accuracy. Furthermore, the accuracies of the calculated max, min, and mean ABPs were comparable to those in the previous works, even though our method also estimated ABP. In the end, we discussed the subject-overfitting problem and future work toward practical use of daily blood pressure monitoring.