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PURPOSE: Hip fractures among elderly patients are surgical emergencies. During COVID-19 pandemic time, many such patients could not be operated at early time because of the limitation of the medical resources, the risk of infection and redirection of medical attention to a severe infective health problem. METHODS: A search of electronic databases (PubMed, Medline, CINAHL, EMBASE and the Cochrane Central Register of Controlled Trials) with the keywords "COVID", "COVID-19″, "SARS-COV-2", "Corona", "pandemic", "hip fracture", "trochanteric fracture" and "neck femur fracture" revealed 64 studies evaluating treatment of hip fracture in elderly patients during COVID-19 pandemic time. The 30-day mortality rate, inpatient mortality rate, critical care/special care need, readmission rate and complications rate in both groups were evaluated. Data were analyzed using Review Manager (RevMan) V.5.3. RESULTS: After screening, 7 studies were identified that described the mortality and morbidity in hip fractures in both COVID-19 infected (COVID-19 +) and non-infected (COVID-19 -) patients. There were significantly increased risks of 30-day mortality (32.23% COVID-19 + death vs. 8.85% COVID-19 - death) and inpatient mortality (29.33% vs. 2.62%) among COVID-19 + patients with odds ratio (OR) of 4.84 (95% CI: 3.13-7.47, p

We present a 65-year-old female smoker who presented with acute bilateral blurred vision. Investigations led to an endobronchial ultrasound-guided fine-needle aspiration resulting in an early diagnosis of limited stage small cell lung cancer. Positive recoverin antibodies supported the diagnosis of cancer-associated retinopathy (CAR). CAR was the first manifestation of systemic malignancy in our patient and early diagnosis enabled curative intent systemic treatment with chemotherapy and radiotherapy. Ocular-specific treatment is required in CAR, although no standardised treatment exists. Current treatment options include steroids and immunosuppressive agents. Our patient was administered bilateral intravitreal dexamethasone implants, resulting in significant visual field and electroretinogram improvement at 8 weeks post-intervention. To our knowledge, this represents the first reported successful use of intravitreal dexamethasone implants as first-line therapy, in conjunction with chemoradiotherapy. Intravitreal dexamethasone implants therefore may provide an effective and safe treatment for CAR by reducing intraocular inflammation without systemic effects.

Infective endocarditis remains a dangerous condition and carries a mortality risk of approximately 20%. Splenic rupture is a rare complication of endocarditis. A 60-year-old woman with a history of atrial fibrillation, mitral valve repair and severe mitral regurgitation was admitted with a fall and abdominal pain. Emergency laparotomy was performed leading to a diagnosis of splenic rupture, for which splenectomy was performed. Four months later, the patient represented with symptoms of a transient ischaemic attack. Transthoracic and transoesophageal echocardiogram confirmed a large vegetation on the anterior mitral valve leaflet. Treatment with antibiotics and re-do mitral valve surgery was performed. The cause of the initial splenic rupture was felt to have been secondary to undiagnosed infective endocarditis. It is imperative to consider endocarditis in a case of spontaneous splenic rupture particularly in high-risk patients such as those with previous valve surgery.

In this paper, we describe the iterative participatory design of SOPHIE, an online virtual patient for feedback-based practice of sensitive patient-physician conversations, and discuss an initial qualitative evaluation of the system by professional end users. The design of SOPHIE was motivated from a computational linguistic analysis of the transcripts of 383 patient-physician conversations from an essential office visit of late stage cancer patients with their oncologists. We developed methods for the automatic detection of two behavioral paradigms, lecturing and positive language usage patterns (sentiment trajectory of conversation), that are shown to be significantly associated with patient prognosis understanding. These automated metrics associated with effective communication were incorporated into SOPHIE, and a pilot user study identified that SOPHIE was favorably reviewed by a user group of practicing physicians.

With the advent of wearable technologies, Human Body Communication (HBC) has emerged as a physically secure and power-efficient alternative to the otherwise ubiquitous Wireless Body Area Network (WBAN). Whereas the most investigated nodes of HBC have been Electric and Electro-quasistatic (EQS) Capacitive and Galvanic, recently Magnetic HBC (M-HBC) has been proposed as a viable alternative. Previous works have investigated M-HBC through an application point of view, without developing a fundamental working principle for the same. In this paper, for the first time, a ground up analysis has been performed to study the possible effects and contributions of the human body channel in M-HBC over a broad frequency range (1kHz to 10 GHz), by detailed electromagnetic simulations and supporting experiments. The results show that while M-HBC can be successfully operated as a body area network, the human body itself plays a minimal or negligible role in it's functionality. For frequencies less than about 30 MHz, in the domain of operation of Magneto-quasistatic (MQS) HBC, the human body is transparent to the quasistatic magnetic field. Conversely for higher frequencies, the conductive nature of human tissues end up attenuating Magnetic HBC fields due to Eddy currents induced in body tissues, eliminating the possibility of the body to support efficient waveguide modes. With this better understanding at hand, different modes of operations of MQS HBC have been outlined for both high impedance capacitive and 50 Ohm termination cases, and their performances have been compared with EQS HBC for similar sized devices, over varying distance between TX and RX. The resulting report presents the first fundamental understanding towards M-HBC operation and its contrast with EQS HBC, aiding HBC device designers to make educated design decisions, depending on mode of applications., Submitted to Transactions on Biomedical Engineering

Patients after heart transplantation are at increased risk for malignancy secondary to immunosuppression and oncogenic viral infections. Most common among children is posttransplant lymphoproliferative disorder (PTLD), occurring in 5% to 10% of patients. We used a national database to examine the incidence and risk factors for posttransplant malignancy.The United Network for Organ Sharing database was queried for pediatric (18 years) heart transplant recipients from October 1987 through November 2019. Freedom from malignancy after transplant was assessed with Kaplan-Meier analysis. Cox regression was performed to generate hazard ratios (HRs) and 95% CIs for risk of malignancy development.Of 8581 pediatric heart transplant recipients, malignancy developed in 8.1% over median follow-up time of 6.3 years, with PTLD compromising 86.4% of the diagnosed cancers. The incidence of PTLD development was 1.3% at 1 year and 4.5% at 5 years. Older age at the time of transplant was protective against the development of malignancy (HR, 0.98; 95% CI, 0.96-0.99; P.001), whereas a history of previous malignancy (HR, 1.9; 95% CI, 1.2-3.0; P = .007) and Ebstein-Barr virus (EBV) recipient-donor mismatch (HR, 1.7; 95% CI, 1.3-2.2; P.001) increased the risk. Induction therapy, used in 78.9% of the cohort, did not increase malignancy risk (P = .355) nor did use of maintenance tacrolimus (P = .912).PTLD occurred after 7% of pediatric heart transplants, with risk increased by younger age and EBV mismatch, highlighting the importance of PTLD monitoring in EBV-seronegative recipients. Induction therapy, used in most of the pediatric heart transplants, does not seem to increase posttransplant malignancy nor does tacrolimus, the most commonly used calcineurin inhibitor.

Accurate medical image segmentation of brain tumors is necessary for the diagnosing, monitoring, and treating disease. In recent years, with the gradual emergence of multi-sequence magnetic resonance imaging (MRI), multi-modal MRI diagnosis has played an increasingly important role in the early diagnosis of brain tumors by providing complementary information for a given lesion. Different MRI modalities vary significantly in context, as well as in coarse and fine information. As the manual identification of brain tumors is very complicated, it usually requires the lengthy consultation of multiple experts. The automatic segmentation of brain tumors from MRI images can thus greatly reduce the workload of doctors and buy more time for treating patients. In this paper, we propose a multi-modal brain tumor segmentation framework that adopts the hybrid fusion of modality-specific features using a self-supervised learning strategy. The algorithm is based on a fully convolutional neural network. Firstly, we propose a multi-input architecture that learns independent features from multi-modal data, and can be adapted to different numbers of multi-modal inputs. Compared with single-modal multi-channel networks, our model provides a better feature extractor for segmentation tasks, which learns cross-modal information from multi-modal data. Secondly, we propose a new feature fusion scheme, named hybrid attentional fusion. This scheme enables the network to learn the hybrid representation of multiple features and capture the correlation information between them through an attention mechanism. Unlike popular methods, such as feature map concatenation, this scheme focuses on the complementarity between multi-modal data, which can significantly improve the segmentation results of specific regions. Thirdly, we propose a self-supervised learning strategy for brain tumor segmentation tasks. Our experimental results demonstrate the effectiveness of the proposed model against other state-of-the-art multi-modal medical segmentation methods.

Variable annuities, the largest liability of U.S. life insurers, are investment products containing long-dated minimum return guarantees. I show that guarantees with similar economic risks are treated differently by regulation and these differences impact insurers’ hedging behavior. When the regulatory regime recognizes certain risks, insurers start to hedge these risks in a substantial way. For some guarantees, this involves hedging both interest rate and equity market risks. However, for others, it involves hedging only equity market risk. As the regulatory regime still does not recognize the interest rate risk of all guarantees, insurers remain exposed to substantial interest rate risk. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Mobile apps provide new opportunities to people with disabilities to act independently in the world. Motivated by this trend, researchers have conducted empirical studies by using the inaccessibility issue rate of each page (i.e., screen level) to represent the characteristics of mobile app accessibility. However, there still lacks an empirical investigation directly focusing on the issues themselves (i.e., issue level) to unveil more fine-grained findings, due to the lack of an effective issue detection method and a relatively comprehensive dataset of issues. To fill in this literature gap, we first propose an automated app page exploration tool, named Xbot, to facilitate app accessibility testing and automatically collect accessibility issues by leveraging the instrumentation technique and static program analysis. Owing to the relatively high activity coverage (around 80%) achieved by Xbot when exploring apps, Xbot achieves better performance on accessibility issue collection than existing testing tools such as Google Monkey. With Xbot, we are able to collect a relatively comprehensive accessibility issue dataset and finally collect 86,767 issues from 2,270 unique apps including both closed-source and open-source apps, based on which we further carry out an empirical study from the perspective of accessibility issues themselves to investigate novel characteristics of accessibility issues. Specifically, we extensively investigate these issues by checking 1) the overall severity of issues with multiple criteria, 2) the in-depth relation between issue types and app categories, GUI component types, 3) the frequent issue patterns quantitatively, and 4) the fixing status of accessibility issues.

In social networks, one of the most significant challenges is how to estimate the tweet popularity. Prior studies focus on leveraging different aspects of just a single tweet, while ignoring the impact of historical tweets. In this paper, we propose to leverage such historical information and rethink the problem of tweet popularity estimation. From historical information, there are two important factors that can be extracted: (1) user reputation feature, which can represent coarse-grained level of tweet popularity; (2) tweet related features, which can represent fine-grained level of tweet popularity. To incorporate these two factors from historical information, we design a novel deep neural architecture, a Bi-layered LSTM for tweet popUlarity Estimation, called DeepBlue. Specifically, we first propose a user-reputation aware mechanism to combine coarse-grained and fine-grained level estimation into a united LSTM model. We also design a content attention mechanism to consider different impacts of historical tweets in terms of content similarity. We then propose a time aware mechanism to address the time interval irregularity issue. Finally, we apply the Poisson regression model to obtain the overall loss for tweet popularity estimation. Extensive experiments demonstrate the superiority of our proposed approach to other state-of-the-arts in terms of MAE and SRC.

Young patients presenting with cryptogenic stroke should be investigated for cardiac and extra-cardiac sources of emboli. We present a patient who was investigated for a cardiac source of emboli, following multiple ischaemic strokes and migraine with aura over a period of 17 years. The events were initially thought to be related to a patent foramen ovale (PFO) on bubble contrast echocardiography, however, due to an unusual flow pattern to the left heart, she underwent a CT angiogram to exclude intrapulmonary shunting. This confirmed the presence of a moderate sized congenital pulmonary arteriovenous fistula in the left lung. Transcatheter occlusion of the vascular malformation has resolution of her symptoms. Bubble contrast echocardiography is routinely used to diagnose a PFO in these cases, but extreme caution is required during the procedure to differentiate the pattern of flow seen in patients with a pulmonary arteriovenous malformation.

An airport and its region have a mutual interaction. Thus, the airport's performance is crucial for its region. Moreover, airport's performance is influenced by air transport network. The measurement of the quality and capacity of the air transport network is multifaceted. The study assesses an airport's network in terms of its type, accessibility, and connectivity. It focusses on 12 Tier-II Indian cities having medium-hub international airports because of their huge growth potential and under-addressed assessment. Furthermore, it is in coherence with the current policies of boosting regional air connectivity. Specific analyses for Tier-II cities' airports is important as a comparison with the bigger metropolises will be skewed. This exploration puts special emphasis on their relationship with the Tier-I cities as the connectivity of Indian airports is majorly complementary than competitive. Measures used for assessment are concentration indices, graph theory-based connectivity and accessibility indices (shortest path length and quickest time length), and partial accessibility indicators (daily accessibility, potential indicator, location indicator, and network efficiency). Modifications and synthesis of partial indicators are also attempted. Annual data sets for the financial year 2017–18 and real-time data from 25–July 31, 2018 are used, and the analysis was carried out from April–August 2018. The study identifies future potential (hubs/feeders) among the Tier-II cities' airports and proposes to align policies accordingly. The results illustrate the need for more strong hubs in northern India and reveal the potential of Amritsar, Calicut, and Trichy of becoming future regional hubs.

Thyroid cancer is not among the top cancers in terms of diagnosis or mortality but it still ranks fifth among the cancers diagnosed in women. Infact, women are more likely to be diagnosed with thyroid cancer than the males. The burden of thyroid cancer has dramatically increased in last two decades in China and, in the United States, it is the most diagnosed cancer in young adults under the age of twenty-nine. All these factors make it worthwhile to fully understand the pathogenesis of thyroid cancer. Towards this end, microRNAs (miRNAs) have constantly emerged as the non-coding RNAs of interest in various thyroid cancer subtypes on which there have been numerous investigations over the last decade and half. This comprehensive review takes a look at the current knowledge on the topic with cataloging of miRNAs known so far, particularly related to their utility as epigenetic signatures of thyroid cancer progression and metastasis. Such information could be of immense use for the eventual development of miRNAs as therapeutic targets or even therapeutic agents for thyroid cancer therapy.

OBJECTIVE Brain arteriovenous malformations (bAVMs) most commonly present with rupture and intraparenchymal hemorrhage. In rare cases, the hemorrhage is large enough to cause clinical herniation or intractable intracranial hypertension. Patients in these cases require emergent surgical decompression as a life-saving measure. The surgeon must decide whether to perform concurrent or delayed resection of the bAVM. Theoretical benefits to concurrent resection include a favorable operative corridor created by the hematoma, avoiding a second surgery, and more rapid recovery and rehabilitation. The objective of this study was to compare the clinical and surgical outcomes of patients who had undergone concurrent emergent decompression and bAVM resection with those of patients who had undergone delayed bAVM resection. METHODS The authors conducted a 15-year retrospective review of consecutive patients who had undergone microsurgical resection of a ruptured bAVM at their institution. Patients presenting in clinical herniation or with intractable intracranial hypertension were included and grouped according to the timing of bAVM resection: concurrent with decompression (hyperacute group) or separate resection surgery after decompression (delayed group). Demographic and clinical characteristics were recorded. Groups were compared in terms of the primary outcomes of hospital and intensive care unit (ICU) lengths of stay (LOSs). Secondary outcomes included complete obliteration (CO), Glasgow Coma Scale score, and modified Rankin Scale score at discharge and at the most recent follow-up. RESULTS A total of 35/269 reviewed patients met study inclusion criteria; 18 underwent concurrent decompression and resection (hyperacute group) and 17 patients underwent emergent decompression only with later resection of the bAVM (delayed group). Hyperacute and delayed groups differed only in the proportion that underwent preresection endovascular embolization (16.7% vs 76.5%, respectively; p < 0.05). There was no significant difference between the hyperacute and delayed groups in hospital LOS (26.1 vs 33.2 days, respectively; p = 0.93) or ICU LOS (10.6 vs 16.1 days, respectively; p = 0.69). Rates of CO were also comparable (78% vs 88%, respectively; p > 0.99). Medical complications were similar in the two groups (33% hyperacute vs 41% delayed, p > 0.99). Short-term clinical outcomes were better for the delayed group based on mRS score at discharge (4.2 vs 3.2, p < 0.05); however, long-term outcomes were similar between the groups. CONCLUSIONS Ruptured bAVM rarely presents in clinical herniation requiring surgical decompression and hematoma evacuation. Concurrent surgical decompression and resection of a ruptured bAVM can be performed on low-grade lesions without compromising LOS or long-term functional outcome; however, the surgeon may encounter a more challenging surgical environment.

Background Chemotherapy is a first-line treatment for advanced and metastatic bladder cancer, but the unsatisfactory objective response rate to this treatment yields poor 5-year patient survival. Only PD-1/PD-L1-based immune checkpoint inhibitors, FGFR3 inhibitors and antibody-drug conjugates are approved by the FDA to be used in bladder cancer, mainly for platinum-refractory or platinum-ineligible locally advanced or metastatic urothelial carcinoma. Emerging studies indicate that the combination of targeted therapy and chemotherapy shows better efficacy than targeted therapy or chemotherapy alone. Newly identified targets in cancer cells and various functions of the tumour microenvironment have spawned novel agents and regimens, which give impetus to sensitizing chemotherapy in the bladder cancer setting. Aim of Review: This review aims to present the current evidence for potentiating the efficacy of chemotherapy in bladder cancer. We focus on combining chemotherapy with other treatments as follows: targeted therapy, including immunotherapy and antibody-drug conjugates in clinic; novel targeted drugs and nanoparticles in preclinical models and potential targets that may contribute to chemosensitivity in future clinical practice. The prospect of precision therapy is also discussed in bladder cancer. Key Scientific Concepts of Review: Combining chemotherapy drugs with immune checkpoint inhibitors, antibody-drug conjugates and VEGF inhibitors potentially elevates the response rate and survival. Novel targets, including cancer stem cells, DNA damage repair, antiapoptosis, drug metabolism and the tumour microenvironment, contribute to chemosensitization. Gene alteration-based drug selection and patient-derived xenograft- and organoid-based drug validation are the future for precision therapy.

Background The incidence of ischemic cerebrovascular disease is increasing in recent years and has been one of the leading causes of neurological dysfunction and death. Ginsenoside Rg1 has been found to protect against neuronal damage in many neurodegenerative diseases. However, the effect and mechanism by which Rg1 protects against cerebral ischemia-reperfusion injury (CIRI) are not fully understood. Here, we report the neuroprotective effects of Rg1 treatment on CIRI and its possible mechanisms in mice. Methods A bilateral common carotid artery ligation was used to establish a chronic CIRI model in mice. HT22 cells were treated with Rg1 after OGD/R to study its effect on [Ca2+]i. The open-field test and pole-climbing experiment were used to detect behavioral injury. The laser speckle blood flowmeter was used to measure brain blood flow. The Nissl and H&E staining were used to examine the neuronal damage. The Western blotting was used to examine MAP2, PSD95, Tau, p-Tau, NOX2, PLC, p-PLC, CN, NFAT1, and NLRP1 expression. Calcium imaging was used to test the level of [Ca2+]i. Results Rg1 treatment significantly improved cerebral blood flow, locomotion, and limb coordination, reduced ROS production, increased MAP2 and PSD95 expression, and decreased p-Tau, NOX2, p-PLC, CN, NFAT1, and NLRP1 expression. Calcium imaging results showed that Rg1 could inhibit calcium overload and resist the imbalance of calcium homeostasis after OGD/R in HT22 cells. Conclusion Rg1 plays a neuroprotective role in attenuating CIRI by inhibiting oxidative stress, calcium overload, and neuroinflammation.

Background Endoscopic thyroidectomy offers excellent cosmetic outcomes, but requires a period of time for surgeons to become proficient. We examined the learning curve for the first 100 cases experienced by a single surgeon using a video-assisted neck surgery (VANS) subclavian approach. Methods We retrospectively studied 100 patients (99 women, 1 man; mean age, 36.2 years) with both benign and malignant thyroid diseases treated between 2016 and 2020. Results Preoperative diagnosis was papillary thyroid carcinoma (PTC) in 36 cases and other (non-PTC) in 64 cases. All patients underwent lobectomy, with unilateral central node dissection added for patients with PTC. Mean operative time was 125 min for non-PTC cases and 129 min for PTC cases (p = 0.43), with blood loss of 33.8 ml and 7.6 ml, respectively (p = 0.01). Recurrent laryngeal nerve paralysis (RNP) was observed in 12 patients (12%) and hemorrhage in 2 patients (2%). Comparing the first 30 cases with the last 70 cases, no significant differences in operative time or blood loss were evident, although tumor size of non-PTC cases was significantly greater among later cases (32.4 mm vs. 39.5 mm, p = 0.039). RNP was significantly decreased in later cases (26.7% vs. 5.7%, p = 0.003). Multivariate analysis revealed tumor size as a significant risk factor for increased blood loss, and increased experience correlated significantly with the decrease in RNP. Conclusions In VANS, a certain surgical level was reached after experiencing 30 cases.

Using nationally representative household survey data administered by the U.S. Energy Information Administration, in this article, we attempt to analyze the aggregate behavior of households in terms of usage of appliances with explicit temperature control mechanism and the adoption of energy-efficient variants of other appliances. A multivariate probit analysis suggests that the households with larger size, higher income, and higher level of education are more likely to use smart thermostat to control temperature and purchase energy-efficient appliances. To identify the broad classes of household behavior, latent class analysis specifications are used. The optimal specification indicates that there are four broad classes of households. Consistent with the results of the multivariate probit specification, we find that the increased odds of belonging to the smart thermostat/energy-efficient appliance owner category of households over the no control/no energy-efficient appliance owner are related to variables, such as household type, size, and income. Therefore, targeting renters, apartment dwellers, and lower income households through appropriate household incentives and residential regulations are likely to improve outcomes in the adoption of efficient appliances and temperature control strategies.

Wearable inertial motion capture, a new type of motion capture technology, mainly estimates the human posture in 3-D space through multi-sensor data fusion. The available method for sensor fusion are usually aided by magnetometers to remove the drift error in yaw angle estimation, which in turn limits their application in the presence of complex magnetic field environment. In this paper, an extended Kalman filter data fusion method is proposed to fuse the 9-axis sensor data. Meanwhile, heuristic drift reduction (HDR) method is used to calibrate the accumulated error of heading angle. In addition, the position in 3-D space is estimated by foot-mounted Zero-Velocity-Update (ZUPT) technique. Combining 3-D attitude and position, a biomechanical model of the human body is established to track the motion of real human body. The extended Kalman filter (EKF) algorithm and position estimation methods are benchmarked against the golden standard, optical motion capture system, for various indoor experiments. In addition, various outdoor experiments are also conducted to verify the reliability of the proposed method. The results show that the proposed algorithm outperforms the available attitude estimation model in motion tracking and is feasible for 3-D human motion capture.

A noise-suppressing low-light image enhancement approach is proposed in this paper based on the extent of exposedness at each image pixel. To this end, a progressive, structure-aware exposedness estimation procedure is presented that quantifies local and global exposedness. These exposedness values are leveraged to produce a locally smooth pixel-level map that signifies the required degrees of enhancement at image pixels. This map is subsequently used in an enhancement function, which satisfies a few important properties, to generate the enhanced image. Before the enhancement, inherent noise in the low-light image is diminished employing a detail-preserving, low gradient magnitude suppression method. Subjective and quantitative analysis of results on a wide variety of natural and synthetically generated low-light images from standard databases using PSNR, iRSE, SSIM, and measures of perceptual quality, natural image statistics and brightness preservation suggests that our approach in general outperforms the state-of-the-art. Ablation studies and further experiments show the importance of a few components of our approach, and that our approach is computationally fast.

Analysis of electroencephalogram (EEG) is a crucial diagnostic criterion for many sleep disorders, of which sleep staging is an important component. Manual stage classification is a labor-intensive process and usually suffered from many subjective factors. Recently, more and more computer-aided techniques have been applied to this task, among which deep convolutional neural network has been performing well as an effective automatic classification model. Despite some comprehensive models have been developed to improve classification results, the accuracy for clinical applications has not been reached due to the lack of sufficient labeled data and the limitation of extracting latent discriminative EEG features. Therefore, we propose a novel hybrid manifold-deep convolutional neural network with hyperbolic attention. To overcome the shortage of labeled data, we update the semi-supervised training scheme as an optimal solution. In order to extract the latent feature representation, we introduce the manifold learning module and the hyperbolic module to extract more discriminative information. Eight subjects from the public dataset are utilized to evaluate our pipeline, and the model achieved 89% accuracy, 70% precision, 80% sensitivity, 72% f1-score and kappa coefficient of 78%, respectively. The proposed model demonstrates powerful ability in extracting feature representation and achieves promising results by using semi-supervised training scheme. Therefore, our approach shows strong potential for future clinical development.

Harnessing energy from the environment promotes the rapid development of micro-power generators and relevant power management modules of alternating current (AC) line-filtering to obtain a stabilized direct current (DC) output for storage and use. Micro-supercapacitors (MSCs) with miniaturized volume and high-frequency response are regarded as a critical component in filtering circuits for microscale power conversion. Here, we reported the fabrication of the wafer-sized planar MSCs (M-MSCs) based on 2D Ti3C2Tx MXene using a photolithography technique. The M-MSCs exhibited an areal capacitance of 153 μF cm−2 and a frequency characteristic (f0) of 5.6 kHz in aqueous electrolyte. Moreover, by employing suitable ionic liquid as electrolyte, the voltage window was expanded to 2 V and the f0 could be pushed to 6.6 kHz relying on the electrical double-layer mechanism and lower adsorption energy while maintaining quasi-rectangular cyclic voltammogram curves at 5000 V s−1. Furthermore, the integrated MSCs pack was constructed and exhibited excellent rectifying ability by filtering various high-frequency 5000 Hz AC signals with different waveforms into stable DC outputs. Such ultrahigh-rate and high-voltage M-MSCs module for kHz AC line-filtering would be potentially integrated with customizable electronics to realize on-chip rectifiers in high-density integrated circuit.

In this report, we present a case of successful long-term salvage of a patient with transfusion-related acute lung injury associated with acute respiratory distress syndrome immediately after a liver transplant. The patient was a 29-year-old man with end-stage liver disease due to sclerosing cholangitis who underwent liver transplant. After organ reperfusion, there was evidence of liver congestion, acidosis, coagulopathy, and acute kidney injury. He received 61 units of blood products. Continuous renal replacement therapy was initiated intraoperatively. On arrival to the intensive care unit, the patient was on high-dose pressors, and the patient developed respiratory failure and was immediately placed on veno-arterial extracorporeal membrane oxygenation via open femoral exposure. The patient presented with severe coagulopathy and early allograft dysfunction; therefore, no systemic heparin was administered and no thrombotic events occurred. He required extracorporeal membrane oxygenation support until posttransplant day 4, when resolution of the respiratory and cardiac dysfunction was noted. At 2 years after liver transplant, the patient has normal liver function, normal cognitive function, and stage V chronic kidney disease. We conclude that extracorporeal membrane oxygenation is a valuable therapeutic approach in patients with cardiorespiratory failure after liver transplant.

Galloway-Mowat syndrome is an autosomal recessive rare hereditary disorder with progressively worsening renal function, neurological and psychomotor abnormalities, microcephaly, facial dysmorphism, and thyroid, adrenal, and ovarian hypoplasia/agenesis. Here, we present the case of a 9-year-old girl who presented with late-onset steroid-resistant nephrotic syndrome with rapid worsening of renal function, microcephaly, hypertelorism, high-arched palate, delayed speech and developmental milestones, poor intellectual function, short stature, hypertension, and hypothyroidism. Magnetic resonance imaging brain was suggestive of cerebral and cerebellar atrophy, hypomyelination, and optic atrophy. Renal biopsy was suggestive of focal segmental glomerulosclerosis. Whole-genome exon sequencing revealed a homozygous mutation in the NUP85 gene. The clinicians should be aware of this rare syndrome and consider it as a possibility in any patient presenting with nephrotic syndrome, microcephaly, and neurological abnormality.

We examine how catastrophic innovation failure affects organizational and industry legitimacy in nascent sectors by analyzing the interactions between Virgin Galactic and stakeholders in the space community in the aftermath of the firm’s 2014 test flight crash. Following catastrophic innovation failure, we find that industry participants use their interpretations of the failure to either uphold or challenge the legitimacy of the firm while maintaining the legitimacy of the industry. These dynamics yield two interesting effects. First, we show that, in upholding the legitimacy of the industry, different industry participants rhetorically redraw the boundaries of the industry to selectively include players they consider legitimate and exclude those they view as illegitimate: detracting stakeholders constrain the boundaries of the industry by excluding the firm or excluding the firm and its segment, whereas the firm and supporting stakeholders amplify the boundaries of the industry by including firms in adjacent high-legitimacy sectors. Second, we show that, in assessing organizational legitimacy, the firm and its stakeholders differ in the way they approach distinctiveness between the identities of the industry and the firm. Detracting stakeholders differentiate the firm from the rest of the industry and isolate it, whereas the firm and supporting stakeholders reidentify the firm with the industry, embedding the firm within it. Overall, our findings illuminate the effects that catastrophic innovation failure has over high-order dynamics that affect the evolution of nascent industries.

In this study, we examine how changes in credit risk around CEO turnover announcements are affected by the nature of the succession (forced vs. voluntary), outgoing CEO’s legacy, and concentration of job titles. We find that firms whose incumbent is forced out experience a greater increase in credit default swap (CDS) spreads than firms with voluntary departures, especially when the influence of the outgoing CEO lingers or the CEO is powerful. These results provide new insights into sources of uncertainty around CEO turnovers and extend the literature on the determinants of CDS spreads around this corporate event.