After heart transplantation, endomyocardial biopsy (EMBx) is used to monitor for acute rejection (AR). Unfortunately, EMBx is invasive, and its conventional histological interpretation has ...limitations. This is a validation study to assess the performance of a sensitive blood biomarker-percent donor-derived cell-free DNA (%ddcfDNA)-for detection of AR in cardiac transplant recipients.
This multicenter, prospective cohort study recruited heart transplant subjects and collected plasma samples contemporaneously with EMBx for %ddcfDNA measurement by shotgun sequencing. Histopathology data were collected to define AR, its 2 phenotypes (acute cellular rejection ACR and antibody-mediated rejection AMR), and controls without rejection. The primary analysis was to compare %ddcfDNA levels (median and interquartile range IQR) for AR, AMR, and ACR with controls and to determine %ddcfDNA test characteristics using receiver-operator characteristics analysis.
The study included 171 subjects with median posttransplant follow-up of 17.7 months (IQR, 12.1-23.6), with 1392 EMBx, and 1834 %ddcfDNA measures available for analysis. Median %ddcfDNA levels decayed after surgery to 0.13% (IQR, 0.03%-0.21%) by 28 days. Also, %ddcfDNA increased again with AR compared with control values (0.38% IQR, 0.31-0.83%, versus 0.03% IQR, 0.01-0.14%;
<0.001). The rise was detected 0.5 and 3.2 months before histopathologic diagnosis of ACR and AMR. The area under the receiver operator characteristic curve for AR was 0.92. A 0.25%ddcfDNA threshold had a negative predictive value for AR of 99% and would have safely eliminated 81% of EMBx. In addition, %ddcfDNA showed distinctive characteristics comparing AMR with ACR, including 5-fold higher levels (AMR ≥2, 1.68% IQR, 0.49-2.79% versus ACR grade ≥2R, 0.34% IQR, 0.28-0.72%), higher area under the receiver operator characteristic curve (0.95 versus 0.85), higher guanosine-cytosine content, and higher percentage of short ddcfDNA fragments.
We found that %ddcfDNA detected AR with a high area under the receiver operator characteristic curve and negative predictive value. Monitoring with ddcfDNA demonstrated excellent performance characteristics for both ACR and AMR and led to earlier detection than the EMBx-based monitoring. This study supports the use of %ddcfDNA to monitor for AR in patients with heart transplant and paves the way for a clinical utility study. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02423070.
This paper describes an all-digital PVT-variation tolerant true-random number generator (TRNG), fabricated in 45 nm high-k/metal-gate CMOS, targeted for on-die entropy generation in high-performance ...microprocessors. The TRNG harvests differential thermal-noise at the diffusion nodes of a pre-charged cross-coupled inverter pair to resolve out of metastability, generating one random bit/cycle. A self-calibrating 2-step tuning mechanism using coarse-grained configurable inverters and fine-grained programmable clock delay generators, along with an entropy-tracking feedback loop provide tolerance to 20% PVT variation-induced device mismatches, enabling lowest-reported energy-consumption of 2.9 pJ/bit with a dense layout occupying 4004 μm 2 , while achieving: (i) 2.4 Gbps random bit throughput, 7 mW total power consumption with 0.7 mW leakage power component, measured at 1.1 V, 50°C, (ii) random bitstreams that passes all NIST RNG tests with raw entropy/bit measured up to 0.9999999993, (iii) good distribution of 1's with 4-bit entropy of 3.97996 and high-entropy pattern probability of 0.066 (iv) wide operating supply voltage range with robust sub-threshold voltage performance of 14 Mbps, 5.6 μW, measured at 280 mV, 50°C, (v) 12 fine-grained high-entropy settings for the TRNG to dither in during steady-state operation, (vi) <;3% error while using an analytical ergodic Markov chain model for predicting pattern probabilities and (vii) 200x higher throughput and 9x higher energy-efficiency than previously reported implementations. Design modifications for robust operation in 22 nm high-volume manufacturing in the presence of 3σ process variations demonstrate scalability of the all-digital design to future technologies.
This paper describes a full-entropy 128-b key generation platform based on a 1024-b hybrid physically unclonable function (PUF) array, fabricated in 14-nm trigate high-k/metal-gate CMOS. ...Delay-hardened hybrid PUF cells use differential clock delay insertion to favor circuit evaluation in the desired direction while leveraging burn-in-induced aging for selective bit destabilization enabling quick identification and masking of unstable cells, and subsequent temporal-majority-voting with soft dark-bit masking to reduce PUF bit error by 3.9 times to 1.45% resulting in ~5 ppb failure probability. A stable full-entropy 128-b key is finally generated from the 1024 raw PUF bits using BCH error correction and AES-CBC-based entropy extraction. An all-digital design with compact PUF cell layout occupying 1.84 μm 2 achieves: 1) 4-fJ/b energy-efficiency with 3-μW leakage at 0.65 V, 70°C; 2) peak operating frequency of 1 GHz resulting in 1.2-μs key generation latency; 3) robust operation with stable key generation across 0.55-0.75 V, and 25°C-110°C; 4) 14 times separation between intra/inter-PUF hamming distances with 0.99993 entropy ensuring cryptographic quality randomness and uniqueness; 5) 48% higher PUF stability with long-term aging by leveraging transistor degradation to reinforce favorable cell bias; and 6) resiliency to power cycling attacks with common centroid clock routing measured from 49.5% hamming distance between array's evaluation and wake-up states.
This paper describes μRNG, an ultra-lightweight all-digital full-entropy true-random number generator (TRNG), fabricated in 14 nm high-k/metal-gate FinFET CMOS, targeted for on-die generation of ...cryptographic keys in energy-constrained IoT and wearable platforms. The μRNG combines the entropy of multiple independent sources to generate an output bitstream that is indistinguishable from an ideal unbiased entropy source. Three independent self-calibrating all-digital entropy sources, coupled with XOR feedback shift-register based correlation suppressors and an in-line compact Barak-Impagliazzo- Wigderson (BIW) extractor enable ultra-low energy consumption of 3 pJ/full-entropy bit with a dense layout occupying 1008 μm 2 , while achieving: (i) 162.5 Mbps full-entropy throughput at 1.3 GHz operation, with total power consumption of 1.5 mW and leakage power component of 90 μW, measured at 0.75 V, 25°C, (ii) mutually uncorrelated raw bitstreams from the three entropy sources with phi-coefficient cross-correlation <;0.003, (iii) extracted full-entropy bitstream that passes all 16 NIST RNG tests with measured Shannon entropy up to 0.9999999995, and lower-bound min-entropy H ∞ > 0.99, (iv) hysteresis-free extracted output for lags 1-1000, with ACF ~0 within 95% confidence bounds of a Gaussian distribution (μ = 0, σ 2 = 0.002), (v) wide operating supply voltage range of 300-950 mV with throughput scaling to 225 Mbps at 950 mV and robust subthreshold voltage performance of 400 Kbps, 4 μW, measured at 300 mV, 25°C, (vi) peak energy-efficiency of 323 Gbps/W at near-threshold voltage of 400 mV, with full-entropy throughput of 8.6 Mbps, total power consumption of 27 μW, (vii) 6.5× reduction in gate count and 5.4× lower energy consumption compared to conventional AES-based entropy extractors.
This paper describes a unified static/dynamic entropy generator based on a 512-b common entropy source (ES) array fabricated in 14-nm tri-gate CMOS with reconfigurable and adaptive post-processing ...circuits implemented on Arria 10 FPGA, targeted for flexible and secure privacy preserving mutual authentication on compact trusted mote platforms at the edge of internet of things. Several conditioning techniques that include temporal majority voting (TMV)-assisted ES array segregation with integrated bias tracking, three-way in-line self-calibration for tolerance to process-voltage-temperature variation, tri-level hierarchical Von Neumann (VN) extraction to maximize entropy harvesting, soft-dark bit masking for improving physically unclonable function (PUF) stability, and selective stress hardening to co-optimize the ES array for static-dynamic entropy with bias aware device aging enable simultaneous PUF and true random number generator (TRNG) operation with 1.48 and 0.56 Gb/s throughput, respectively, measured at 650 mV, 70 °C. The all-digital design with a compact layout footprint of 2114 <inline-formula> <tex-math notation="LaTeX">\mu \text{m}^{2} </tex-math></inline-formula> facilitates seamless integration in area constrained system-on-chips while achieving: 1) 25% area savings over conventional separate PUF and TRNG implementations; 2) cryptographic quality TRNG stream that passes all NIST randomness tests with 0.38 average p-value; 3) <inline-formula> <tex-math notation="LaTeX">1.6\times </tex-math></inline-formula> higher extractor performance at <inline-formula> <tex-math notation="LaTeX">9\times </tex-math></inline-formula> lower area with 750-gate hierarchical VN circuit over conventional light-weight entropy extractors; 4) 0.9996/0.99997 static/dynamic Shannon entropy indicating unbiased PUF/TRNG streams; 5) ultra-low energy consumption of 2.5 and 0.46 pJ/bit measured at 650 mV, 70 °C in TRNG and PUF modes; 6) 40% higher TRNG throughput with three-way self-calibration featuring coarse-grain column swap, fine-grain incremental ES substitution, and residual entropy recycling; 7) resistance to power injection attacks as measured by 64% higher performance over un-calibrated design in the presence 200-mV supply noise; 8) 2.8% PUF bit-error measured at 0.55-0.75 V, 25 °C-110 °C with 15-way TMV and soft dark-bit masking over a window of 100 cycles; 9) <inline-formula> <tex-math notation="LaTeX">14.8\times </tex-math></inline-formula> inter and intra-PUF hamming distance separation; and 10) 56% reduction in discarded ES cells with selective stress hardening to opportunistically reinforce/nullify pre-existing bias in PUF/TRNG candidate cells. To our knowledge, this is the first reported unified PUF-TRNG implementation enabling simultaneous generation of high-entropy chip-ID and encryption keys in real time.
As the COVID-19 pandemic has created shortages of vital personal protective equipment that threatens healthcare workers’ risk of exposure, a need for innovative new ways to protect healthcare workers ...has emerged. An aerosol containment box that covers the patient’s head and neck in bed provides a solution to protect clinicians during aerosol-generating procedures such as intubation. We collaborated with original designer HYL and modified the size to adapt to larger patients and operator mobility. We expand its applicability by allowing the use of different instruments. The container is outfitted with an ultra-low particulate air-equipped filtration vacuum device to create negative pressure within the chamber and actively remove floating droplet nuclei generated during a procedure. This barrier method will be a valuable and economical option to protect healthcare workers on the front line globally during this pandemic and beyond.
Neurological manifestations of coronavirus disease 2019 most commonly present in severe cases and range from mild complications, such as headache and dizziness, to severe complications, such as ...encephalopathy and acute cerebrovascular disease. Seizures, however, are an underreported neurological manifestation of this disease. We present three critically ill coronavirus disease 2019 patients with EEG monitoring who developed new-onset seizures and encephalopathy up to three-and-a-half weeks after symptom onset. There are several speculated etiologies for the development of new-onset seizures; however, the pathogenic mechanism remains unknown. Testing of coronavirus disease 2019 in the cerebrospinal fluid in addition to extensive research on neurological manifestations is warranted.
BACKGROUND—Right ventricular (RV) functional reserve affects functional capacity and prognosis in patients with pulmonary arterial hypertension (PAH). PAH associated with systemic sclerosis (SSc-PAH) ...has a substantially worse prognosis than idiopathic PAH (IPAH), even though many measures of resting RV function and pulmonary vascular load are similar. We therefore tested the hypothesis that RV functional reserve is depressed in SSc-PAH patients.
METHODS AND RESULTS—RV pressure-volume relations were prospectively measured in IPAH (n=9) and SSc-PAH (n=15) patients at rest and during incremental atrial pacing or supine bicycle ergometry. Systolic and lusitropic function increased at faster heart rates in IPAH patients, but were markedly blunted in SSc-PAH. The recirculation fraction, which indexes intracellular calcium recycling, was also depressed in SSc-PAH (0.32±0.05 versus 0.50±0.05; P=0.039). At matched exercise (25 W), SSc-PAH patients did not augment contractility (end-systolic elastance) whereas IPAH did (P<0.001). RV afterload assessed by effective arterial elastance rose similarly in both groups; thus, ventricular-vascular coupling declined in SSc-PAH. Both end-systolic and end-diastolic RV volumes increased in SSc-PAH patients to offset contractile deficits, whereas chamber dilation was absent in IPAH (+37±10% versus +1±8%, P=0.004, and +19±4% versus –1±6%, P<0.001, respectively). Exercise-associated RV dilation also strongly correlated with resting ventricular-vascular coupling in a larger cohort.
CONCLUSIONS—RV contractile reserve is depressed in SSc-PAH versus IPAH subjects, associated with reduced calcium recycling. During exercise, this results in ventricular-pulmonary vascular uncoupling and acute RV dilation. RV dilation during exercise can predict adverse ventricular-vascular coupling in PAH patients.
For over 2 decades preimplantation genetic testing (PGT) has been in clinical use to reduce the risk of miscarriage and genetic disease in patients with advanced maternal age and risk of transmitting ...disease. Recently developed methods of genome-wide genotyping and machine learning algorithms now offer the ability to genotype embryos for polygenic disease risk with accuracy equivalent to adults. In addition, contemporary studies on adults indicate the ability to predict polygenic disorders with risk equivalent to monogenic disorders. Existing biobanks provide opportunities to model the clinical utility of polygenic disease risk reduction among sibling adults. Here, we provide a mathematical model for the use of embryo screening to reduce the risk of type 1 diabetes. Results indicate a 45-72% reduced risk with blinded genetic selection of one sibling. The first clinical case of polygenic risk scoring in human preimplantation embryos from patients with a family history of complex disease is reported. In addition to these data, several common and accepted practices place PGT for polygenic disease risk in the applicable context of contemporary reproductive medicine. In addition, prediction of risk for PCOS, endometriosis, and aneuploidy are of particular interest and relevance to patients with infertility and represent an important focus of future research on polygenic risk scoring in embryos.
A binary neural network (BNN) chip explores the limits of energy efficiency and computational density for an all-digital deep neural network (DNN) inference accelerator. The chip intersperses data ...storage and computation using computation near memory (CNM) to reduce interconnect and data movement costs. It performs wide inner product operations to leverage parallelism inherent in DNN computations. The BNN chip leverages lightweight pipelining at a near-threshold voltage (NTV) to reduce the overhead of sequential elements. It employs optimized data access patterns to reduce memory accesses for convolutional operation with pooling layers. The combination of these techniques enables the BNN chip to achieve a peak energy efficiency of 617 TOPS/W. The digital BNN chip approaches the energy efficiency of analog in-memory techniques while also ensuring deterministic, scalable, and bit-accuracy operation. Moreover, the all-digital design leverages process scaling and does not require additional memory transistors or passive devices to attain a peak compute density of 418 TOPS/mm 2 and a memory density of 414 KB/mm 2 . The binary design is extended to enable bit-serial integer precision operation with a reconfigurable 1-b multiplication circuit and element-wise partial sum shift and accumulate. This technique allows for fine-grain mixed precision and retains energy efficiency by exploiting parallelism inherent in DNNs. The bit-serial binary operation allows for bit-accurate operation and high DNN accuracy that multibit analog compute-in-memory designs struggle to attain. It provides favorable energy tradeoffs compared with small-integer digital DNN accelerators.
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