Cumulative consumption of tea is associated with lower risk of liver cancer: Updated results from the Shanghai Women's Health Study.

Prospective epidemiological studies have provided limited evidence for an association between tea consumption and liver cancer risk. Based on a population-based prospective cohort study in middle-aged Chinese women, we investigated the association between tea consumption and the risk of primary liver cancer. Detailed information on tea drinking habits and other potential confounders was obtained at the baseline interview. Incident liver cancer cases were identified through record linkage with the population-based cancer registry and verified through home visits and review of medical charts by medical experts. Multiple aspects of tea drinking habits including starting age, duration, intensity and cumulative consumption of any type of tea and green tea were considered. Multivariable-adjusted hazard ratios (aHRs) and their 95% confidence intervals (CIs) were derived from the Cox regression models. After a median follow-up time of 18.12 (interquartile range = 1.59) years, 253 incident liver cancer cases were identified from 71 841 cohort members. Compared with never tea drinkers, the risk of liver cancer for participants who have consumed over 30 kg of dried tea leaves cumulatively was 0.56 (95% CI: 0.32-0.97). For those who drank green tea only, the aHR was 0.54 (95% CI: 0.30-0.98). This updated study suggested an inverse association between cumulative consumption of tea, especially green tea and the risk of primary liver cancer.

Cross-sectional relationships between general and central adiposity and plasma amino acids in Chinese adults.

Adiposity is an important determinant of blood metabolites, but little is known about the variations of blood amino acids according to general and central adiposity status among Chinese population. This study included 187 females and 322 males who were cancer-free subjects randomly selected from two cohorts in Shanghai, China. Participants' plasma concentrations of amino acids were measured by ultra-performance liquid chromatography coupled to tandem mass spectrometry. Linear regression models were used to examine the cross-sectional correlations between general and central adiposity and amino acid levels. A total of 35 amino acids in plasma were measured in this study. In females, alanine, aspartic acid and pyroglutamic acid were positively correlated with general adiposity. In males, glutamic acid, aspartic acid, valine and pyroglutamic acid showed positive correlations, and glutamine, serine and glycine showed negative correlations with both general and central adiposity; phenylalanine, isoleucine and leucine were positively correlated and N-phenylacetylglutamine was negatively correlated with general adiposity; asparagine was negatively correlated with central adiposity. In summary, general adiposity and central adiposity were correlated with the concentrations of specific plasma amino acids among cancer-free female and male adults in China. Adiposity-metabolite characteristics and relationships should be considered when studying blood biomarkers for adiposity-related health outcomes.

Detector Processor for a 5G Base Station.

Nonlinear soft bit detection is essential for the uplink receivers of 5G base stations, especially for users around the cell edge. However, its throughput and computing complexity are always challenges for both research and industry. A low-cost and low-power parallel implementation of a soft-output detector based on sorted QR decomposition (SQRD) and the K-best breadth-first search algorithm is thus proposed to reduce computational complexity and latency. In addition, to save area and reduce latency, two improvement methods are used: (1) reduce the computing cost by saturating and truncating large values during PED computing and (2) reduce the sorting cost by using the binary bit sorting method for a reduced sample set with finite accuracy. Furthermore, a pipelined VLSI architecture is designed using 28-nm digital CMOS technology offered by Semiconductor Manufacturing International Corporation (SMIC). It can achieve a peak throughput of 6400 Mbps while consuming 153 K gates (including all flip-flops) for SMIC's 28-nm technology and running at 800 MHz, a 32% cost reduction compared with the published reference design.

An ASIP for Neural Network Inference on Embedded Devices with 99% PE Utilization and 100% Memory Hidden under Low Silicon Cost.

The computation efficiency and flexibility of the accelerator hinder deep neural network (DNN) implementation in embedded applications. Although there are many publications on deep neural network (DNN) processors, there is still much room for deep optimization to further improve results. Multiple dimensions must be simultaneously considered when designing a DNN processor to reach the performance limit of the architecture, including architecture decision, flexibility, energy efficiency, and silicon cost minimization. Flexibility is defined as the ability to support as many multiple networks as possible and to easily adjust the scale. For energy efficiency, there are huge opportunities for power efficiency optimization, which involves access minimization and memory latency minimization based on on-chip memory minimization. Therefore, this work focused on low-power and low-latency data access with minimized silicon cost. This research was implemented based on an ASIP (application specific instruction set processor) in which an ISA was based on the caffe2 inference operator and the hardware design was based on a single instruction multiple data (SIMD) architecture. The scalability and system performance of our SoC extension scheme were demonstrated. The VLIW was used to execute multiple instructions in parallel. All costs for data access time were thus eliminated for the convolution layer. Finally, the processor was synthesized based on TSMC 65 nm technology with a 200 MHz clock, and the Soc extension scheme was analyzed in an experimental model. Our design was tested on several typical neural networks, achieving 196 GOPS at 200 MHz and 241 GOPS/W on the VGG16Net and AlexNet.

An Uplink Channel Estimator Using a Dedicated Instruction Set for 5G Small Cells.

As 5G small cells gradually become the main force of 5G indoor deployment, it is necessary to study channel estimators for 5G small base stations, but there has been limited research on high-performance channel estimators in recent years. This study implemented a low-delay, low-overhead, relatively universal channel estimation module by dedicated instruction set acceleration including reference signal estimation, Wiener, 1st order, and 2nd order interpolations in frequency and time domains. The instruction level acceleration is on our vector processor, yet is suitable for other commercial and academic vector processors. Through instruction acceleration, compared with the existing general vector processing instruction sets, the processor performance of the LS estimation module and Wiener filter interpolation in the frequency domain is improved by 50% and 37.5%, respectively. The BER VS SNR measure of time-frequency Wiener filter interpolation achieves 4 db compared with linear interpolation, meaning our instruction level acceleration can be an optimum solution.

Dietary fat intake and liver cancer incidence: A population-based cohort study in Chinese men.

To date, limited studies have focused on the association between dietary fat and liver cancer risk, especially in China. Our study aims to evaluate the association between dietary fat intake and liver cancer incidence risk in men. Dietary fat intake was obtained through a validated food frequency questionnaire in a Chinese prospective cohort. The Cox regression model was utilized to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). After exclusion, 59 998 recruitments were finally analyzed with a total follow-up time of 714 339 person-years, 431 incident liver cancer cases were newly identified among them. The adjusted HRs (95% CIs) for the highest vs lowest quartile of total fat, saturated fat, monounsaturated fat (MUFA), and polyunsaturated fat (PUFA) were 1.33 (1.01-1.75), 1.50 (1.13-1.97), 1.26 (0.96-1.65), and 1.41 (1.07-1.86), and the corresponding P-trend values were .008, .005, .034, and .005, respectively. In the secondary analysis among participants tested for hepatitis B virus, we found that higher intakes of saturated fat and PUFA were also associated with increased liver cancer risks. Besides, high risks of per standard deviation alterations of the total fat, saturated fat and MUFA were detected in liver cancer, and these results were similar to those concluded from the full-cohort analysis. In conclusion, dietary intakes of total fat, saturated fat, PUFA, and probably MUFA might increase liver cancer risks. Our study provides suggestive advice to public administration on dietary suggestions, and related measures taken from managing dietary fat intake might reduce liver cancer incidence.

Low-Latency QC-LDPC Encoder Design for 5G NR.

In order to meet the low latency and high throughput requirements of data transmission in 5th generation (5G) New Radio (NR), it is necessary to minimize the low power encoding hardware latency on transmitter and achieve lower base station power consumption within a fixed transmission time interval (TTI). This paper investigates parallel design and implementation of 5G quasi-cyclic low-density parity-check (QC-LDPC) codes encoder. The designed QC-LDPC encoder employs a multi-channel parallel structure to obtain multiple parity check bits and thus reduce encoding latency significantly. The proposed encoder maps high parallelism encoding algorithms to a configurable circuit architecture, achieving flexibility and support for all 5G NR code length and code rate. The experimental results show that under the 800 MHz system frequency, the achieved data throughput ranges from 62 to 257.9 Gbps, and the maximum code length encoding time under base graph 1 (BG1) is only 33.75 ns, which is the critical encoding time of our proposed encoder. Finally, our proposed encoder was synthesized on SMIC 28 nm CMOS technology; the result confirmed the effectiveness and feasibility of our design.

Personal Characteristics Effects on Validation of Self-reported Type 2 Diabetes From a Cross-sectional Survey Among Chinese Adults.

BACKGROUND: The objective was to evaluate the effects of personal characteristics on the validation of self-reported type 2 diabetes among Chinese adults in urban Shanghai. METHODS: During 2015 through 2016, 4,322 participants were recruited in this validation study. We considered the criteria of diabetes verification to use the laboratory assays of fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), or self-reported use of diabetic medication. RESULTS: When taking diabetic medication or FPG ≥7.0 mmol/L was as identified diabetes, the measurements of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Kappa value of self-reported diabetes were 72.0%, 99.2%, 95.1%, 93.9%, and 0.78, respectively. If an additional HbA1c test was used for 708 subjects (aged <65 years), slightly lower values of sensitivity, NPV, and Kappa were observed. More potential diabetes cases were found compared to only using FPG. Subjects who were female, older, or had a family history of diabetes had sensitivity over 75% and excellent Kappa over 0.8, while the sensitivity and Kappa of opposite groups had poorer values. Specificity, PPV, and NPV were similar among groups with different demographic or disease characteristics. The prevalence of type 2 diabetes was 19.3% in the study (14.1% diagnosed diabetes, 5.2% undiagnosed diabetes). About 26.2% of subjects were pre-diabetic. Additional HbA1c test indicated an increased prevalence of undiagnosed diabetes and pre-diabetes. CONCLUSIONS: Findings support self-reported diabetes is sufficiently valid to be used in large-scale, population-based epidemiologic studies. Participants with different characteristics may have different indicators in terms of validation, such as age, gender, and family history of diabetes in first-degree relatives.

An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer.

For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power.

A Magnetic-Balanced Inductive Link for the Simultaneous Uplink Data and Power Telemetry.

When using the conventional two-coil inductive link for the simultaneous wireless power and data transmissions in implantable biomedical sensor devices, the strong power carrier could overwhelm the uplink data signal and even saturate the external uplink receiver. To address this problem, we propose a new magnetic-balanced inductive link for our implantable glaucoma treatment device. In this inductive link, an extra coil is specially added for the uplink receiving. The strong power carrier interference is minimized to approach zero by balanced canceling of the magnetic field of the external power coil. The implant coil is shared by the wireless power harvesting and the uplink data transmitting. Two carriers (i.e., 2-MHz power carrier and 500-kHz uplink carrier) are used for the wireless power transmission and the uplink data transmission separately. In the experiments, the prototype of this link achieves as high as 65.72 dB improvement of the signal-to-interference ratio (SIR) compared with the conventional two-coil inductive link. Benefiting from the significant improvement of SIR, the implant transmitter costs only 0.2 mW of power carrying 50 kbps of binary phase shift keying data and gets a bit error rate of 1 × 10 - 7 , even though the coupling coefficient is as low as 0.005. At the same time, 5 mW is delivered to the load with maximum power transfer efficiency of 58.8%. This magnetic-balanced inductive link is useful for small-sized biomedical sensor devices, which require transmitting data and power simultaneously under ultra-weak coupling.

An NFC on Two-Coil WPT Link for Implantable Biomedical Sensors under Ultra-Weak Coupling.

The inductive link is widely used in implantable biomedical sensor systems to achieve near-field communication (NFC) and wireless power transfer (WPT). However, it is tough to achieve reliable NFC on an inductive WPT link when the coupling coefficient is ultra-low (0.01 typically), since the NFC signal (especially for the uplink from the in-body part to the out-body part) could be too weak to be detected. Traditional load shift keying (LSK) requires strong coupling to pass the load modulation information to the power source. Instead of using LSK, we propose a dual-carrier NFC scheme for the weak-coupled inductive link; using binary phase shift keying (BPSK) modulation, its downlink data are modulated on the power carrier (2 MHz), while its uplink data are modulated on another carrier (125 kHz). The two carriers are transferred through the same coil pair. To overcome the strong interference of the power carrier, dedicated circuits are introduced. In addition, to minimize the power transfer efficiency decrease caused by adding NFC, we optimize the inductive link circuit parameters and approach the receiver sensitivity limit. In the prototype experiments, even though the coupling coefficient is as low as 0.008, the in-body transmitter costs only 0.61 mW power carrying 10 kbps of data, and achieves a 1 × 10 - 7 bit error rate under the strong interference of WPT. This dual-carrier NFC scheme could be useful for small-sized implantable biomedical sensor applications.

PaCHNOC: Packet and Circuit Hybrid Switching NoC for Real-Time Parallel Stream Signal Processing.

Real-time heterogeneous parallel embedded digital signal processor (DSP) systems process multiple data streams in parallel in a stringent time interval. This type of system on chip (SoC) requires the network on chip (NoC) to establish multiple symbiotic parallel data transmission paths with ultra-low transmission latency in real time. Our early NoC research PCCNOC meets this need. The PCCNOC uses packet routing to establish and lock a transmission circuit, so that PCCNOC is perfectly suitable for ultra-low latency and high-bandwidth transmission of long data packets. However, a parallel multi-data stream DSP system also needs to transmit roughly the same number of short data packets for job configuration and job execution status reports. While transferring short data packets, the link establishment routing delay of short data packets becomes relatively obvious. Our further research, thus, introduced PaCHNOC, a hybrid NoC in which long data packets are transmitted through a circuit established and locked by routing, and short data packets are attached to the routing packet and the transmission is completed during the routing process, thus avoiding the PCCNOC setup delay. Simulation shows that PaCHNOC performs well in supporting real-time heterogeneous parallel embedded DSP systems and achieves overall latency reduction 65% compared with related works. Finally, we used PaCHNOC in the baseband subsystem of a real 5G base station, which proved that our research is the best NoC for baseband subsystem of 5G base stations, which reduce 31% comprehensive latency in comparison to related works.

Parallel PWMs based fully digital transmitter with wide carrier frequency range.

The carrier-frequency (CF) and intermediate-frequency (IF) pulse-width modulators (PWMs) based on delay lines are proposed, where baseband signals are conveyed by both positions and pulse widths or densities of the carrier clock. By combining IF-PWM and precorrected CF-PWM, a fully digital transmitter with unit-delay autocalibration is implemented in 180 nm CMOS for high reconfiguration. The proposed architecture achieves wide CF range of 2 M-1 GHz, high power efficiency of 70%, and low error vector magnitude (EVM) of 3%, with spectrum purity of 20 dB optimized in comparison to the existing designs.

PCCNoC: Packet Connected Circuit as Network on Chip for High Throughput and Low Latency SoCs.

Hundreds of processor cores or modules are integrated into a single chip. The traditional bus or crossbar is challenged by bandwidth, scalability, and silicon area, and cannot meet the requirements of high end applications. Network-on-chip (NoC) has become a very promising interconnection structure because of its good scalability, predictable interconnect length and delay, high bandwidth, and reusability. However, the most available packet routing NoC may not be the perfect solution for high-end heterogeneous multi-core real-time systems-on-chip (SoC) because of the excessive latency and cache cost overhead. Moreover, circuit switching is limited by the scale, connectivity flexibility, and excessive overhead of fully connected systems. To solve the above problems and to meet the need for low latency, high throughput, and flexibility, this paper proposes PCCNoC (Packet Connected Circuit NoC), a low-latency and low-overhead NoC based on both packet switching (setting-up circuit) and circuit switching (data transmission on circuit), which offers flexible routing and zero overhead of data transmission latency, making it suitable for high-end heterogeneous multi-core real-time SoC at various system scales. Compared with typically available packet switched NoC, our PCCoC sees 242% improved performance and 97% latency reduction while keeping the silicon cost relatively low.

Biochemical and structural characterization of Haemophilus influenzae nitroreductase in metabolizing nitroimidazoles.

Nitroheterocycle antibiotics, particularly 5-nitroimidazoles, are frequently used for treating anaerobic infections. The antimicrobial activities of these drugs heavily rely on the in vivo bioactivation, mainly mediated by widely distributed bacterial nitroreductases (NTRs). However, the bioactivation can also lead to severe toxicities and drug resistance. Mechanistic understanding of NTR-mediated 5-nitroimidazole metabolism can potentially aid addressing these issues. Here, we report the metabolism of structurally diverse nitroimidazole drug molecules by a NTR from a human pathogen Haemophilus influenzae (HiNfsB). Our detailed bioinformatic analysis uncovered that HiNfsB represents a group of unexplored oxygen-insensitive NTRs. Biochemical characterization of the recombinant enzyme revealed that HiNfsB effectively metabolizes ten clinically used nitroimidazoles. Furthermore, HiNfsB generated not only canonical nitroreduction metabolites but also stable, novel dimeric products from three nitroimidazoles, whose structures were proposed based on the results of high resolution MS and tandem MS analysis. X-ray structural analysis of the enzyme coupled with site-directed mutagenesis identified four active site residues important to its catalysis and broad substrate scope. Finally, transient expression of HiNfsB sensitized an E. coli mutant strain to 5-nitroimidazoles under anaerobic conditions. Together, these results advance our understanding of the metabolism of nitroimidazole antibiotics mediated by a new NTR group and reinforce the research on the natural antibiotic resistome for addressing the antibiotic resistance crisis.

Dietary glycemic index, glycemic load, and cause-specific mortality: two population-based prospective cohort studies.

BACKGROUND: Epidemiological studies on the relationship between dietary glycemic index (GI), glycemic load (GL) and all-cause and cause-specific mortality yielded conflict results. We aimed to assess these associations in Chinese. METHODS: We conducted this study based on two prospective cohort studies in Shanghai. Dietary information was collected using validated cohort-specific food frequency questionnaires. We used Cox regression model to estimate the hazard ratios (HR) for mortality associated with GI and GL. RESULTS: After median follow-up periods of 12.8 years for 59,770 men and 18.2 years for 74,735 women, 8,711 deaths in men and 10,501 deaths in women were documented. After we controlled the potential confounders, dietary GI, GL, and carbohydrate intake were associated with a higher risk of cardiovascular disease (CVD) mortality (P values for trend = 0.025, 0.001, and 0.001). Dietary GI was associated with lower risk of total and cause-specific mortality in men in the second quartile (Q) (all-cause mortality: HR Q2 vs. Q1 = 0.89, 95%CI: 0.84, 0.95). Dietary GL was associated with lower risk of cancer mortality but higher risk of CVD mortality in men. In women, dietary GI was associated with mortality due to all-cause (HRMax Q4 vs. Q1 = 1.10, 95%CI: 1.04, 1.06), cancer (HRMax Q4 vs. Q1 = 1.12, 95%CI: 1.02, 1.23), and CVD (HRMax Q4 vs. Q1 = 1.10, 95%CI: 1.00, 1.22). CONCLUSIONS: The present study indicates that diet with higher GI and GL was associated with an increased risk of CVD mortality in Chinese adults. The association may vary for men and women, which need further investigating in other Asian populations.

Dose-response relationship between fat distribution and liver cancer incidence: A prospective cohort study in Chinese men.

BACKGROUND: Based on a prospective cohort study in middle-aged Chinese men, the current study characterized the dose-response relationships between fat distribution measurements and the incidence of primary liver cancer. METHODS: Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated by Cox regression models for the association between waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), a body shape index (ABSI), and body roundness index (BRI) with liver cancer incidence. Dose-response curves were characterized using a restricted cubic spline function. RESULTS: After a mean follow-up time of 11.9 (SD = 2.4) years, 440 liver cancer cases were identified from 60,625 participants. WC, WHtR, ABSI, and BRI were found to be associated with an increased risk of liver cancer at a given level of body mass index (BMI), with multivariable-adjusted HRs of 1.19 (95% CI: 1.01-1.41), 1.26 (95% CI: 1.02-1.50), 1.12 (95% CI: 1.05-1.23) and 1.28 (95% CI: 1.08-1.53) for per SD increment, respectively. Dose-response curves suggested that the risk increased rapidly above the median levels of WC, WHtR, and BRI. For ABSI, the risk decreased from the minimum level to about the 35th percentile and increased slowly thereafter. CONCLUSIONS: The current study suggested an association between abdominal obesity in middle age and increased risk of primary liver cancer at a given level of BMI. WHtR and BRI were better predictors of liver cancer risk compared with WC and ABSI.

Biocatalytic synthesis of peptidic natural products and related analogues.

Peptidic natural products (PNPs) represent a rich source of lead compounds for the discovery and development of therapeutic agents for the treatment of a variety of diseases. However, the chemical synthesis of PNPs with diverse modifications for drug research is often faced with significant challenges, including the unavailability of constituent nonproteinogenic amino acids, inefficient cyclization protocols, and poor compatibility with other functional groups. Advances in the understanding of PNP biosynthesis and biocatalysis provide a promising, sustainable alternative for the synthesis of these compounds and their analogues. Here we discuss current progress in using native and engineered biosynthetic enzymes for the production of both ribosomally and nonribosomally synthesized peptides. In addition, we highlight new in vitro and in vivo approaches for the generation and screening of PNP libraries.

Metabolite profiling reveals organ-specific flavone accumulation in Scutellaria and identifies a scutellarin isomer isoscutellarein 8-O-ß-glucuronopyranoside.

Scutellaria is a genus of plants containing multiple species with well-documented medicinal effects. S. baicalensis and S. barbata are among the best-studied Scutellaria species, and previous works have established flavones to be the primary source of their bioactivity. Recent genomic and biochemical studies with S. baicalensis and S. barbata have advanced our understanding of flavone biosynthesis in Scutellaria. However, as over several hundreds of Scutellaria species occur throughout the world, flavone biosynthesis in most species remains poorly understood. In this study, we analyzed organ-specific flavone profiles of seven Scutellaria species, including S. baicalensis, S. barbata, and two species native to the Americas (S. wrightii to Texas and S. racemosa to Central and South America). We found that the roots of almost all these species produce only 4'-deoxyflavones, while 4'-hydroxyflavones are accumulated exclusively in their aerial parts. On the other hand, S. racemosa and S. wrightii also accumulated high levels of 4'-deoxyflavones in their aerial parts, different with the flavone profiles of S. baicalensis and S. barbata. Furthermore, our metabolomics and NMR study identified the accumulation of isoscutellarein 8-O-ß-glucuronopyranoside, a rare 4'-hydroxyflavone, in the stems and leaves of several Scutellaria species including S. baicalensis and S. barbata, but not in S. racemosa and S. wrightii. Distinctive organ-specific metabolite profiles among Scutellaria species indicate the selectivity and diverse physiological roles of flavones.

Visible-light-promoted 3,5-dimethoxyphenyl glycoside activation and glycosylation.

A new glycosylation method promoted by visible light with 3,5-dimethoxyphenyl glycoside as the donor was developed. This protocol delivers both O-glycosides and N-glycosides in moderate to excellent yields using a wide range of O-nucleophiles and nucleobases as the glycosyl acceptors.