Search

Background and ObjectivesFemale patients tend to have greater disability and worse long-term outcomes after stroke than male patients. To date, the biological basis of sex difference in ischemic stroke remains unclear. We aimed to 1) assess sex differences in clinical manifestation and outcomes of acute ischemic stroke and 2) investigate whether the sex disparity is due to different infarct locations or different impacts of infarct in the same location.MethodsThis MRI-based multicenter study included 6,464 consecutive patients with acute ischemic stroke (ResultsMean (SD) age was 67.5 (12.6) years, and 2,641 (40.9%) were female patients. Percentage infarct volumes on diffusion-weighted MRI did not differ between female patients and male patients (median 0.14% vs. 0.14%, P=0.35). However, female patients showed higher stroke severity (NIHSS-score, median 4 vs. 3, P2) than male patients (adjusted-absolute-difference 4.5%; 95%-CI 2.0–7.0; PDiscussionFemale patients have more frequent middle cerebral artery disease and striatocapsular motor-pathway involvement with acute ischemic stroke, along with left parieto-occipital cortical infarcts showing greater severity for equivalent infarct volumes than in male patients. This leads to more severe initial neurological symptoms, higher susceptibility to neurological worsening, and less 3-month functional independence, when compared with male patients.

BackgroundThere is limited information on the delivery of acute stroke therapies and secondary preventive measures and clinical outcomes over time in young adults with acute ischemic stroke (AIS). This study investigated whether advances in these treatments improved outcomes in this population.MethodsUsing a prospective multicenter stroke registry in Korea, young adults (aged 18–50 years) with AIS hospitalized between 2008 and 2019 were identified. The observation period was divided into four epochs: 2008–2010, 2011–2013, 2014–2016, and 2017–2019. Secular trends for patient characteristics, treatments, and outcomes were analyzed.ResultsA total of 7,050 eligible patients (mean age 43.1; men 71.9%) were registered. The mean age decreased from 43.6 to 42.9 years (Ptrend=0.01). Current smoking decreased, whereas obesity increased. Other risk factors remained unchanged. Intravenous thrombolysis and mechanical thrombectomy rates increased over time from 2008–2010 to 2017–2019 (9.5% to 13.8% and 3.2% to 9.2%, respectively; Ptrend’strendtrend’strend=0.04), but was not significant after adjusting for warfarin use.ConclusionImprovements in the delivery of acute stroke treatments did not necessarily lead to better outcomes in young adults with AIS over the past decade, indicating a need for further improvement.

BACKGROUND Assessment of activities of daily living (ADLs) and instrumental activities of daily living (iADLs) is key to determining severity of dementia and care needs among older adults. However, such information is often only documented in free-text clinical notes within the electronic health record (EHR) and can be challenging to find. OBJECTIVE To develop and validate machine learning models to determine status of ADL and iADL impairments based on clinical notes. METHODS This cross-sectional study leveraged EHR clinical notes from Mass General Brigham’s Research Patient Data Repository linked with Medicare fee-for-service claims data from 2007-2017 to identify individuals aged 65 and older with at least one diagnosis of dementia. Notes for encounters both 180 days before and after the first date of dementia diagnosis were randomly sampled. Models were trained and validated using note sentences filtered by expert-curated keywords (filtered cohort) and further evaluated using unfiltered sentences (unfiltered cohort). Models’ performance was compared using area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC). RESULTS The study included 10,000 key-term filtered sentences representing 441 subjects (283 [64.17%] women, mean [SD] age 82.7 [7.9] years), and 1,000 unfiltered sentences representing 80 subjects (56 [70%] women, mean [SD] age 82.8 [7.5] years). AUROC was high for the best-performing ADL and iADL models on both cohorts (>0.97). For ADL impairment identification, the random forest model achieved the best AUPRC (0.89; 95% CI, 0.86-0.91) on the filtered cohort; the SVM model achieved the highest AUPRC (0.82; 95% CI, 0.75-0.89) for the unfiltered cohort. For iADL impairment, the Bio+Clinical BERT model had the highest AUPRC (0.76 filtered; 95% CI, 0.68-0.82; 0.58 unfiltered; 95% CI, 0.001-1.0). Compared with a keyword-search approach on the unfiltered cohort, machine learning reduced false positive rates from 4.5% to 0.2% for ADL and 1.8% to 0.1% for iADL. CONCLUSIONS In this study, we demonstrated the ability of machine learning models to accurately identify ADL and iADL impairment based on free-text clinical notes, which could be useful in determining the severity of dementia.

The stemness of bone marrow mesenchymal stem cells (BMSCs) is maintained by hypoxia. The oxygen level increases from vessel-free cartilage to hypoxic bone marrow and, furthermore, to vascularized bone, which might direct the chondrogenesis to osteogenesis and regenerate the skeletal system. Hence, oxygen was diffused from relatively low to high levels throughout a three-dimensional chip. When we cultured BMSCs in the chip and implanted them into the rabbit defect models of low-oxygen cartilage and high-oxygen calvaria bone, (i) the low oxygen level (base) promoted stemness and chondrogenesis of BMSCs with robust antioxidative potential; (ii) the middle level (two times ≥ low) pushed BMSCs to quiescence; and (iii) the high level (four times ≥ low) promoted osteogenesis by disturbing the redox balance and stemness. Last, endochondral or intramembranous osteogenesis upon transition from low to high oxygen in vivo suggests a developmental mechanism–driven solution to promote chondrogenesis to osteogenesis in the skeletal system by regulating the oxygen environment.

Background Severe hypoglycemia is associated with adverse clinical outcomes. We evaluated the risk of severe hypoglycemia in older adults initiating newer glucose-lowering medications overall and across strata of known indicators of high hypoglycemia risk. Methods We conducted a comparative-effectiveness cohort study of older adults aged >65 years with type 2 diabetes initiating sodium-glucose cotransporter 2 inhibitors (SGLT2i) versus dipeptidyl peptidase-4 inhibitors (DPP-4i) or SGLT2i versus glucagon-like peptide-1 receptor agonists (GLP-1RA) using Medicare claims (3/2013–12/2018) and Medicare-linked-electronic health records. We identified severe hypoglycemia requiring emergency or inpatient visits using validated algorithms. After 1:1 propensity score matching, we estimated hazard ratios (HR) and rate differences (RD) per 1,000 person-years. Analyses were stratified by baseline insulin, sulfonylurea, cardiovascular disease (CVD), chronic kidney disease (CKD), and frailty. Results Over a median follow-up of 7 (interquartile range: 4–16) months, SGLT2i was associated with a reduced risk of hypoglycemia versus DPP-4i (HR 0.75 [0.68, 0.83]; RD −3.21 [−4.29, −2.12]), and versus GLP-1RA (HR 0.90 [0.82, 0.98]; RD −1.33 [−2.44, −0.23]). RD for SGLT2i versus DPP-4i was larger in patients using baseline insulin than in those not, although HRs were similar. In patients using baseline sulfonylurea, the risk of hypoglycemia was lower in SGLT2i versus DPP-4i (HR 0.57 [0.49, 0.65], RD −6.80 [−8.43, −5.16]), while the association was near-null in those without baseline sulfonylurea. Results stratified by baseline CVD, CKD and frailty were similar to the overall cohort findings. Findings for the GLP-1RA comparison were similar. Conclusions SGLT2i was associated with a lower hypoglycemia risk versus incretin-based medications, with larger associations in patients using baseline insulin or sulfonylurea.

The high-temperature resilience of quantum-dot (QD) laser materials is exploited to realize a broad spectral bandwidth emitter in the near infrared. For an InAs/GaAs-based QD-superluminescent light emitting diode (SLEDs), we introduced a 2000 μm long, 5 μm width ridge waveguide that is tilted by 7° and composed of eight multi-sections. With increased temperature operation over 160 °C, the spectral bandwidth is dramatically increased by thermally excited carrier transition in ES1 and ES2. Additionally, the positive net-modal gain is demonstrated at the high operating temperatures, and this is exploited in the QD-SLEDs operating at 180 °C, which exhibit a −3 dB linewidth of 270 nm and a power of 0.34 mW. The simplicity of this approach, utilizing heat alone, is contrasted with other approaches for the extremely broad spectral bandwidth emitter.

Background A claims-based frailty index (CFI) allows measurement of frailty on a population scale. Our objective was to examine the association of changes in CFI over 12 months with mortality and Medicare costs. Methods We used a 5% sample of fee-for-service Medicare beneficiaries. We estimated CFI (range: 0–1; nonfrail [0.015–0.045), or large increase (>0.045). We used Cox proportional hazards model to estimate hazard ratio (HR) for mortality adjusting for age, sex, and 2015 CFI value and compared total Medicare costs from January 1, 2016 to December 31, 2016. Results The study population included 995 664 beneficiaries (mean age 77 years, 56.8% female). In nonfrail (n = 906 046), HR (95% confidence interval [CI]) ranged from 0.71 (0.67–0.75) for a large decrease to 2.75 (2.68–2.33) for a large increase. In moderate-to-severely frail beneficiaries (n = 16 527), the corresponding HR (95% CI) ranged from 0.63 (0.57–0.70) to 1.21 (1.06–1.38). The mean total Medicare cost per member per year (standard deviation) was from $12 149 ($83 508) in nonfrail beneficiaries to $61 155 ($345 904) in moderate-to-severely frail beneficiaries. Conclusions One-year changes in CFI are associated with elevated mortality risk and health care costs across all levels of frailty.

In this study, we investigated the impact of intrinsic output conductance (goi) on the short-circuit current-gain cut-off frequency (fT) in InxGa1-xAs/In0.52Al0.48As quantum-well (QW) high-electron-mobility transistors. At its core, we attempted to extract values of fT using a simplified small-signal model (SSM) of the HEMTs and to derive an analytical formula for fT in terms of extrinsic model parameters that are related with intrinsic model parameters of a general SSM. We projected how fT was influenced by goi in HEMTs, emphasizing that the improvement in electrostatic integrity would also be of critical importance to fully benefit from scaling down Lg.

Myelin water imaging (MWI) using MRI has been introduced as a method to quantify the integrity of myelin in vivo. However, the investigation of its potential to probe myelin changes has been limited.To determine the myelin change using MWI in the corticospinal tract (CST) during the rehabilitation of stroke patients.Longitudinal.A total of 24 stroke patients within 6 months from the onset (64.3 ± 16.1 years, 14 women, 10 men) and 10 healthy volunteers (27.0 ± 2.2 years, 2 women, 8 men).Three-dimensional multiecho gradient echo sequence and diffusion-weighted echoplanar imaging sequence at 3 T.The changes of myelin water fraction (MWF) and fractional anisotropy (FA) during rehabilitation were analyzed in the CST and other regions using tractography software and region of interest drawings by the radiologist.A paired t-test was performed to investigate the change of MRI metrics during rehabilitation. In addition, an independent two-sample t-test was performed to investigate the effects of different rehabilitation protocols. A P-value0.05 was considered significant.In the CST, MWF significantly changed from 5.83 ± 0.91% to 6.23 ± 0.97% after rehabilitation while changes of FA (0.442 ± 0.038 to 0.443 ± 0.035) were not significant (P = 0.656). The rate of change in MWF and FA, which were 6.69% and 0.439% respectively, were significantly different. Other regions did not show significant changes (range of MWF change: -3.44% to -1.61%, range of FA change: -1.39% to 0.79%, and range of P-value: 0.144-0.761). Further analysis showed that those with additional robot-assisted rehabilitation had a significantly larger MWF change than those with conventional rehabilitation only (rate of change: 11.2% vs. 3.2%).The feasibility of using MWI to monitor myelin content was demonstrated by showing the MWF changes during rehabilitation.2 TECHNICAL EFFICACY STAGE: 2.

The directional structure of a solution-derived bismuth aluminum gallium tin oxide film is achieved by a brush coating method. This structure is used for spontaneous and uniform liquid crystal alignment.

A 10-year-old intact male Shih Tzu dog presented with hematuria. Double-contrast cystography revealed a polypoid filling defect at the apex of the urinary bladder. Ultrasonography revealed a heterogeneously hypoechoic intramural mass with minimal vascular flow beneath the submucosal layer. After partial cystectomy, a well-demarcated bladder leiomyosarcoma was diagnosed on histopathology. The patient was alive and well without any clinical signs, recurrence, or metastasis at the 29-month follow-up after the surgical removal of the bladder mass. Leiomyosarcoma should be considered as a differential diagnosis if mass-like lesions are observed in the urinary bladder, although this type of malignancy is rare in canines. Histopathological confirmation is important for predicting prognosis and determining further medical plans.

Renewable energies, such as solar and wind energy, play a critical role in achieving rapid decarbonization to limit global warming by replacing fossil energy. However, lack of knowledge on renewable energy potentials in developing countries is a barrier in making adequate policies to promote these energies. Thus, we have carried out a spatial and economic analysis of solar and wind energy potential at the provincial level for the first time in Nepal. Our analysis is built upon the spatial energy modeling based on technical, geographical, and economic suitability criteria, utilizing open-source geographical information system platforms. A significant amount of renewable energy could be harnessed in Nepal, i.e., up to about 47,628 MW and 1,686 MW from solar and wind energy, respectively. Similarly, Nepal has a co-location potential of about 890 and 267 MW of solar and wind energy. Karnali and Gandaki provinces have the highest solar and wind energy potential due to a large share of suitable locations with good resource quality. We estimate the 10th percentile of Levelized cost of electricity generation of 91 USD/MWh for solar and 46 USD/MWh for wind. Our findings are helpful for the formulation of resource-specific policies of Nepal at a sub-national level.

We present a genetic algorithm based energy-aware convolutional neural network (CNN) quantization framework (EGQ) for processing-in-memory (PIM) architectures. EGQ predicts layer-wise dynamic energy consumption based on the number of ADC access. Also, EGQ automatically optimizes layer-wise weight/activation bitwidth that can reduce total dynamic energy with negligible accuracy loss. As EGQ requires basic CNN model information such as weight/activation dimensions to predict the dynamic energy, various models can be compressed by EGQ. We analyse the effectiveness of EGQ on the area, dynamic energy, and energy efficiency of PIM architectures for VGG-19, ResNet-18, and ResNet-50 using NeuroSim. We observe EGQ is an effective approach for the CNN models to reduce the dynamic energy in various PIM designs with SRAM, RRAM, and FeFET technologies. EGQ achieves 6.1 bit of average weight bitwidth and 6.3 bit of average activation bitwidth in ResNet-18, that improves energy efficiency by 6.5× than the 16-bit model. For ResNet-18 with CIFAR-10, 2.5 bit and 3.9 bit of average weight and activation bitwidth are achieved. Both results show the negligible accuracy loss of 2%.