Correction: Sperm associated antigen 9 promotes oncogenic KSHV-encoded interferon regulatory factor-induced cellular transformation and angiogenesis by activating the JNK/VEGFA pathway.

[This corrects the article DOI: 10.1371/journal.ppat.1008730.].

HIV Services Uptake Among People Living with HIV in Jiangsu Province, China: A Cross-Sectional Study.

Healthcare disparities are common among people living with HIV (PLWH) in China and likely impact access to HIV services. This study aimed to assess the current status of access to HIV services among PLWH and explore the correlates of service uptake using baseline data from a prospective cohort study among PLWH in Jiangsu Province. Guided by Andersen's behavioral model, univariable and multivariable logistic regressions were conducted to identify factors associated with access to HIV services. Out of 8989 eligible PLWH included in this study, 46.4% perceived difficulty in seeing a healthcare professional for HIV treatment services in 2021-2022. PLWH aged 18-34 years (adjusted odds ratio [AOR] = 1.69, 95% CI 1.32-2.15), 35-39 years (AOR = 1.33, 95% CI 1.08-1.65), identified as a bisexual/other (AOR = 1.14, 95% CI 1.01-1.29), had a college and above education (AOR = 1.32, 95% CI 1.07-1.63), and perceived moderate (AOR = 1.70, 95% CI 1.51-1.91) and severe (AOR = 2.20, 95% CI 1.94-2.49) levels of HIV stigma were more likely to perceive difficulty in seeing healthcare professionals for HIV treatment in 2021-2022. Living in northern Jiangsu was also associated with increased odds of perceiving difficulty in seeing healthcare professionals for HIV treatment (AOR = 1.12, 95% CI 1.00-1.26). These findings underscore the need for innovative solutions to eliminate the practical barriers to HIV services utilization among PLWH who are bisexual, well-educated, and effective HIV-related stigma reduction interventions.

Development and validation of robust metabolism-related gene signature in the prognostic prediction of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumours worldwide. Given metabolic reprogramming in tumours was a crucial hallmark, several studies have demonstrated its value in the diagnostics and surveillance of malignant tumours. The present study aimed to identify a cluster of metabolism-related genes to construct a prediction model for the prognosis of HCC. Multiple cohorts of HCC cases (466 cases) from public datasets were included in the present analysis. (GEO cohort) After identifying a list of metabolism-related genes associated with prognosis, a risk score based on metabolism-related genes was formulated via the LASSO-Cox and LASSO-pcvl algorithms. According to the risk score, patients were stratified into low- and high-risk groups, and further analysis and validation were accordingly conducted. The results revealed that high-risk patients had a significantly worse 5-year overall survival (OS) than low-risk patients in the GEO cohort. (30.0% vs. 57.8%; hazard ratio [HR], 0.411; 95% confidence interval [95% CI], 0.302-0.651; p < 0.001) This observation was confirmed in the external TCGA-LIHC cohort. (34.5% vs. 54.4%; HR 0.452; 95% CI, 0.299-0.681; p < 0.001) To promote the predictive ability of the model, risk score, age, gender and tumour stage were integrated into a nomogram. According to the results of receiver operating characteristic curves and decision curves analysis, the nomogram score possessed a superior predictive ability than conventional factors, which indicate that the risk score combined with clinicopathological features was able to achieve a robust prediction for OS and improve the individualized clinical decision making of HCC patients. In conclusion, the metabolic genes related to OS were identified and developed a metabolism-based predictive model for HCC. Through a series of bioinformatics and statistical analyses, the predictive ability of the model was approved.

Ambient noise-based weakly supervised manhole localization methods over deployed fiber networks.

We present a manhole localization method based on distributed fiber optic sensing and weakly supervised machine learning techniques. For the first time to our knowledge, ambient environment data is used for underground cable mapping with the promise of enhancing operational efficiency and reducing field work. To effectively accommodate the weak informativeness of ambient data, a selective data sampling scheme and an attention-based deep multiple instance classification model are adopted, which only requires weakly annotated data. The proposed approach is validated on field data collected by a fiber sensing system over multiple existing fiber networks.

Three-Dimensional Printed Titanium Prosthesis for Mandibular Condyle Reconstruction After Extensive Resection of Chondrosarcoma: A 6-year Follow-Up.

Chondrosarcomas (CHS) are malignant mesenchymal tumors arising from cartilage. Chondrosarcomas arising in the temporomandibular joint are especially rare. Herein, the authors report an unusual case of a 50-year-old female who presented with a progressive swelling in the left preauricular region. Computed tomography and magnetic resonance imaging revealed an osteolytic and expansive lesion in the left condyle. The diagnosis tended to be a malignant tumor. A resection guide and 3-dimensional printed titanium prosthesis for condyle reconstruction were designed. Extended resection of the left condyle and reconstruction were performed. The pathologic diagnosis was consistent with CHS (grade II). There was no tumor recurrence or distant metastasis at the 6-year follow-up, and good occlusion and satisfactory function of the temporomandibular joint were regained.

Remote Blood Pressure Estimation via the Spatiotemporal Mapping of Facial Videos.

Blood pressure (BP) monitoring is vital in daily healthcare, especially for cardiovascular diseases. However, BP values are mainly acquired through a contact-sensing method, which is inconvenient and unfriendly for BP monitoring. This paper proposes an efficient end-to-end network for estimating BP values from a facial video to achieve remote BP estimation in daily life. The network first derives a spatiotemporal map of a facial video. Then, it regresses the BP ranges with a designed blood pressure classifier and simultaneously calculates the specific value with a blood pressure calculator in each BP range based on the spatiotemporal map. In addition, an innovative oversampling training strategy was developed to handle the problem of unbalanced data distribution. Finally, we trained the proposed blood pressure estimation network on a private dataset, MPM-BP, and tested it on a popular public dataset, MMSE-HR. As a result, the proposed network achieved a mean absolute error (MAE) and root mean square error (RMSE) of 12.35 mmHg and 16.55 mmHg on systolic BP estimations, and those for diastolic BP were 9.54 mmHg and 12.22 mmHg, which were better than the values obtained in recent works. It can be concluded that the proposed method has excellent potential for camera-based BP monitoring in the indoor scenarios in the real world.

Deep learning for Alzheimer's disease: Mapping large-scale histological tau protein for neuroimaging biomarker validation.

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical decline. Several tau PET tracers are available for neurodegenerative disease research, opening avenues for molecular diagnosis in vivo. However, few have been approved for clinical use. Understanding the neurobiological basis of PET signal validation remains problematic because it requires a large-scale, voxel-to-voxel correlation between PET and (immuno) histological signals. Large dimensionality of whole human brains, tissue deformation impacting co-registration, and computing requirements to process terabytes of information preclude proper validation. We developed a computational pipeline to identify and segment particles of interest in billion-pixel digital pathology images to generate quantitative, 3D density maps. The proposed convolutional neural network for immunohistochemistry samples, IHCNet, is at the pipeline's core. We have successfully processed and immunostained over 500 slides from two whole human brains with three phospho-tau antibodies (AT100, AT8, and MC1), spanning several terabytes of images. Our artificial neural network estimated tau inclusion from brain images, which performs with ROC AUC of 0.87, 0.85, and 0.91 for AT100, AT8, and MC1, respectively. Introspection studies further assessed the ability of our trained model to learn tau-related features. We present an end-to-end pipeline to create terabytes-large 3D tau inclusion density maps co-registered to MRI as a means to facilitate validation of PET tracers.

Sperm associated antigen 9 promotes oncogenic KSHV-encoded interferon regulatory factor-induced cellular transformation and angiogenesis by activating the JNK/VEGFA pathway.

Kaposi's sarcoma (KS), caused by Kaposi's sarcoma-associated herpesvirus (KSHV), is a highly angioproliferative disseminated tumor of endothelial cells commonly found in AIDS patients. We have recently shown that KSHV-encoded viral interferon regulatory factor 1 (vIRF1) mediates KSHV-induced cell motility (PLoS Pathog. 2019 Jan 30;15(1):e1007578). However, the role of vIRF1 in KSHV-induced cellular transformation and angiogenesis remains unknown. Here, we show that vIRF1 promotes angiogenesis by upregulating sperm associated antigen 9 (SPAG9) using two in vivo angiogenesis models including the chick chorioallantoic membrane assay (CAM) and the matrigel plug angiogenesis assay in mice. Mechanistically, vIRF1 interacts with transcription factor Lef1 to promote SPAG9 transcription. vIRF1-induced SPAG9 promotes the interaction of mitogen-activated protein kinase kinase 4 (MKK4) with JNK1/2 to increase their phosphorylation, resulting in enhanced VEGFA expression, angiogenesis, cell proliferation and migration. Finally, genetic deletion of ORF-K9 from KSHV genome abolishes KSHV-induced cellular transformation and impairs angiogenesis. Our results reveal that vIRF1 transcriptionally activates SPAG9 expression to promote angiogenesis and tumorigenesis via activating JNK/VEGFA signaling. These novel findings define the mechanism of KSHV induction of the SPAG9/JNK/VEGFA pathway and establish the scientific basis for targeting this pathway for treating KSHV-associated cancers.

vFLIP-regulated competing endogenous RNA (ceRNA) networks targeting lytic induction for KSHV-associated malignancies.

Kaposi's sarcoma-associated herpesvirus (KSHV) causes life-long latent infection and malignancies, including KS commonly found in AIDS patients. Lytic replication can be induced to kill tumor cells harboring latent KSHV, through viral cytopathic effects and the subsequent antiviral immune responses. Viral FLICE-inhibitory protein (vFLIP), encoded by KSHV ORF K13, inhibits KSHV lytic reactivation, implying that the competing endogenous RNA (ceRNA) networks regulated by vFLIP can be modulated to induce the lytic reactivation of latent KSHV, a promising strategy for KSHV-associated malignancies. Here, we performed whole-transcriptome sequencing to reveal the global landscape of noncoding RNAs and messenger RNAs (mRNAs) in iSLK-RGB-BAC16 cells and iSLK-RGB-K13 mutant cells. It showed that vFLIP regulated 227 differentially expressed (DE) long non-coding RNAs (lncRNAs), 57 DE circular RNAs (circRNAs), 20 DE microRNAs (miRNAs), and 1371 DE mRNAs. Enrichment analysis verified that riboflavin metabolism was simultaneously enriched in DE genes related to miRNAs, lncRNAs, and circRNAs. The upregulated hsa-miR-378i and hsa-miR-3654, and downregulated miR-4467, miR-3163, miR-4451, and miR-4257 were significantly enriched in the ceRNA complex network, which contained 9 upregulated and 7 downregulated circRNAs, 5 upregulated and 85 downregulated lncRNAs, 5 upregulated and 35 downregulated mRNAs. Finally, we constructed and validated two vFLIP-regulated ceRNA networks: circRNA hsa_circ_0070049/hsa-miR-378i/SPEG/FOXQ1 and lncRNA AL031123.1/hsa-miR-378i/SPEG/FOXQ1. Taken together, the two ceRNA networks may mediate KSHV reactivation. These novel findings refreshed the present understanding of ceRNA network in KSHV lytic induction and provided potential therapeutic targets for KSHV-associated malignancies.

A Distributed Anti-Jamming Algorithm Based on Actor-Critic Countering Intelligent Malicious Jamming for WSN.

In this paper, in order to solve the problem of wireless sensor networks' reliable transmission in intelligent malicious jamming, we propose a Distributed Anti-Jamming Algorithm (DAJA) based on an actor-critic algorithm for a multi-agent system. The Multi-Agent Markov Decision Process (MAMPD) is introduced to model the progress of wireless sensor networks' anti-jamming communication, and the multi-agent system learns the intelligent jamming from the external environment by using an actor-critic algorithm. On the basis of coping with the influence of external and internal factors effectively, each sensor in networks selects the appropriate channels for transmission and finally realizes the optimal transmission of the system overall in a unit time period. In the environment of probabilistic intelligent jamming with tracking properties set in this paper, the simulation shows that the algorithm proposed can outperform the algorithm based on joint Q-learning and the conventional scheme based on orthogonal frequency hopping in terms of transmission. In addition, the proposed algorithm completes two updates of strategy evaluation and action selection in one iteration, which means that the system has higher efficiency of action selection and better adaptability to the environment through the interaction with the external environment, resulting in the better performance of transmission and convergence.

The impact of COVID-19 pandemic on HIV care continuum in Jiangsu, China.

BACKGROUND: The COVID-19 pandemic seriously threatens general public health services globally. This study aimed to evaluate the impact of the COVID-19 pandemic on the HIV care continuum in Jiangsu province, China. METHODS: Data on newly diagnosed HIV persons for analysis were retrieved from Chinas' web-based Comprehensive Response Information Management System (CRIMS) for HIV/AIDS from 2016 to 2020. We recorded data for the first 3 months (January to March, 2020) of strictly implementing COVID-19 measures from publicly available disease databases of the Jiangsu provincial Health Committee. We used seasonal autoregressive integrated moving average (SARIMA) and exponential smoothing in forecasting the parameters. Subgroup differences were accessed using Chi-square tests. RESULTS: Compared to the estimated proportions, the HIV testing rates decreased by 49.0% (919,938) in the first three months of implementing COVID-19 measures. Of an estimated 1555 new HIV diagnosis expected in the same period, only 63.0% (980) new diagnoses were recorded. According to actual data recorded during the said period, 980 positively tested persons received confirmatory tests, of which 71.4% (700) were reportedly linked to care. And only 49.5% (235) out of the expected 475 newly diagnosed HIV persons received CD4 cell count testing. Meanwhile 91.6% (208) of newly diagnosed HIV persons who received CD4 count tests reportedly initiated antiretroviral therapy (ART) compared to the 227 expected. Compared to the same period from 2016 to 2019, PLWH less than 30 years old and migrants were more likely to be affected by the COVID-19 policies. CONCLUSIONS: The COVID-19 pandemic negatively impacted HIV healthcare systems in Jiangsu, China. Further measures that can counter the impact of the pandemic are needed to maintain the HIV care continuum.

Optical anisotropy of self-organized gold quasi-blazed nanostructures based on a broad ion beam.

To circumvent elaborate conventional lithographic methods for realizing metallic nanostructures, it is necessary to develop self-organized nanofabrication methods for suitable template structures and their optical characterization. We demonstrate the potential of ion bombardment with impurity co-deposition to fabricate terraced or quasi-blazed nanostructure templates. Self-organized terraced nanostructures on fused silica were fabricated using Ar+ ion bombardment with iron impurity co-deposition and subsequent Au shadow deposition. The aspect ratios are enhanced threefold, and the range of nanostructure period variation is significantly increased with respect to that of conventional nanostructures realized by pure ion bombardment. We reveal the key features of the method via atomic force microscopy and optical characterization. Variable-profile quasiperiodic nanostructures with periods of 100-450 nm, heights of 25-180 nm, and blaze angles of 10°-25° were fabricated over an area of 20×40mm2, and these exhibited tunable and broadening optical anisotropy across the nanostructured area. Thus, the proposed method is a viable technique for rapid, cost-effective, and deterministic fabrication of variable nanostructure templates for potential optical applications.

Patterns of tree species richness in Southwest China.

As a region known for its high species richness, southwest China plays an important role in preserving global biodiversity and ensuring ecological security in the Yangtze, Mekong, and Salween river basins. However, relatively few studies focus on the response of tree species richness to climate change in this part of China. This study determined the main tree species in southwest China using the Vegetation Map of China and the Flora of China. From simulations of 1970 to 2000 and three forecasts of future benign, moderate, and extreme climate warming anticipated during 2061 to 2080, this study used a maximum entropy model (MaxEnt) to simulate main tree species richness in southwest China. Regions with a peak species richness at intermediate elevations were typically dominated by complex mountainous terrain, such as in the Hengduan Mountains. Likewise, regions with the smallest richness were low-elevation areas, including the Sichuan Basin, and the high-elevation Sichuan-Tibet region. Annual precipitation, minimum temperature of the coldest month, temperature seasonality, and elevation were the most critical factors in estimating tree species richness in southwest China. During future 2061 to 2080 climate scenarios, tree species tended to migrate towards higher elevations as mean temperatures increased. For climate change scenarios RCP2.6-2070 (benign) and RCP4.5-2070 (moderate), the main tree species richness in the study area changed little. During the RCP8.5-2070 extreme scenario, tree species richness decreased. This study provides useful guidance to plan and implement measures to conserve biodiversity.

The association between fasting blood glucose trajectory and cancer risk in Chinese population without diabetes.

To examine the associations between fasting blood glucose (FBG) trajectories, the changes in FBG over time and the risk of cancer, particularly for gastrointestinal cancer, we enrolled 69,742 participants without diabetes from the Kailuan cohort. FBG trajectories (2006-2010) were modeled by group-based trajectory modeling, and five trajectories were identified: low-increasing (n = 6,275), moderate-stable (n = 44,120), moderate-increasing (n = 10,149), elevated-decreasing (n = 5,244) and elevated-stable (n = 3,954). A total of 1,364 cancer cases were accumulated between 2010 and 2015, including 472 gastrointestinal cancer cases. We used Cox proportional hazards regression models to evaluate the associations between FBG trajectory patterns and the risk of cancer. We further assessed the associations while carefully controlling for initial body mass index (BMI) in 2006 and for changes in BMI during 2006-2010. Relative to the moderate-stable group, we found a higher hazard ratio (HR) for overall cancer in the low-increasing group (HR = 1.26, 95% confidence interval (CI) 1.06-1.50); and for gastrointestinal cancer in the elevated-stable group (HR = 1.66, 95% CI 1.22-2.26). Moreover, among participants with an initial BMI ≥25 kg/m2 , a positive association with the low-increasing group was observed for both overall cancer and gastrointestinal cancer (HR = 1.54, 95% CI 1.17-2.04; HR = 1.65, 95% CI 1.02-2.66; respectively); among participants with a stable BMI (4.40% loss-5.15% gain), a positive association with the elevated-stable group was observed both for overall cancer and gastrointestinal cancer (HR = 1.43, 95% CI 1.10-1.87; HR = 1.95, 95% CI 1.33-2.86; respectively). Our study observed that FBG trajectories were associated with cancer risk among participants without diabetes, and BMI may modify the associations.

Independent and joint associations of blood lipids and lipoproteins with lung cancer risk in Chinese males: A prospective cohort study.

To investigate the independent and joint associations of blood lipids and lipoproteins with lung cancer risk in Chinese males, a prospective cohort study was conducted. A total of 109,798 males with baseline information on total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and non-HDL were prospectively observed from 2006 to 2015 for cancer incidence. Cox proportional hazards models and restricted cubic spline (RCS) analysis were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). During a 9-year follow-up, a total of 986 lung cancer cases were identified. Multivariable analyses showed that both males with low TC (HRQ1vs.Q2 = 1.27, 95%CI: 1.02-1.60) and males with high TC (HRQ5vs.Q2 = 1.30, 95%CI: 1.04-1.63) had an increased lung cancer risk, and the U-shaped association was also revealed in the RCS analysis (poverall = 0.013, pnonlinear = 0.006). Furthermore, both low TG (HRQ1vs.Q2 = 1.24, 95%CI: 0.99-1.54) and high TG (HRQ5vs.Q2 = 1.27, 95%CI: 1.01-1.59) were associated with increased lung cancer risk, while low LDL-C (HRQ1vs.Q2 = 1.38, 95%CI: 1.11-1.72) was associated with increased lung cancer risk. When TC, TG and LDL-C were considered jointly, the number of abnormal indicators was linearly associated with an increased risk of lung cancer (ptrend < 0.001), as subjects with three abnormal indicators had a twofold higher risk of developing lung cancer (HR = 2.02, 95%CI: 1.62-2.54). Notably, these associations were statistically significant among never smokers, never drinkers and overweight/obese males. These findings suggest that dyslipidemia may potentially be a modifiable risk factor that has key scientific and clinical significance for lung cancer prevention.

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodologies to identify a T2DM-related perfusion pattern and possible relationship between the pattern and cognitive performance/disease severity. PURPOSE: To develop a machine-learning pipeline to investigate the method's discriminative value between T2DM patients and normal controls, the T2DM-related network pattern, and association of the pattern with cognitive performance/disease severity. STUDY TYPE: A cross-sectional study and prospective longitudinal study with a 2-year time interval. POPULATION: Seventy-three subjects (41 T2DM patients and 32 controls) aged 50-85 years old at baseline, and 42 subjects (19 T2DM and 23 controls) aged 53-88 years old at 2-year follow-up. FIELD STRENGTH/SEQUENCE: 3T pseudocontinuous arterial spin-labeling MRI. ASSESSMENT: Machine-learning-based pipeline (principal component analysis, feature selection, and logistic regression classifier) to generate the T2DM-related network pattern and the individual scores associated with the pattern. STATISTICAL TESTS: Linear regression analysis with gray matter volume and education years as covariates. RESULTS: The machine-learning-based method is superior to the widely used univariate group comparison method with increased test accuracy, test area under the curve, test positive predictive value, adjusted McFadden's R square of 4%, 12%, 7%, and 24%, respectively. The pattern-related individual scores are associated with diabetes severity variables, mobility, and cognitive performance at baseline (P < 0.05, |r| > 0.3). More important, the longitudinal change of individual pattern scores is associated with the longitudinal change of HbA1c (P = 0.0053, r = 0.64), and baseline cholesterol (P = 0.037, r = 0.51). DATA CONCLUSION: The individual perfusion diabetes pattern score is a highly promising perfusion imaging biomarker for tracing the disease progression of individual T2DM patients. Further validation is needed from a larger study. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:834-844.

Identification and characterization of high methane-emitting abandoned oil and gas wells.

Recent measurements of methane emissions from abandoned oil/gas wells show that these wells can be a substantial source of methane to the atmosphere, particularly from a small proportion of high-emitting wells. However, identifying high emitters remains a challenge. We couple 163 well measurements of methane flow rates; ethane, propane, and n-butane concentrations; isotopes of methane; and noble gas concentrations from 88 wells in Pennsylvania with synthesized data from historical documents, field investigations, and state databases. Using our databases, we (i) improve estimates of the number of abandoned wells in Pennsylvania; (ii) characterize key attributes that accompany high emitters, including depth, type, plugging status, and coal area designation; and (iii) estimate attribute-specific and overall methane emissions from abandoned wells. High emitters are best predicted as unplugged gas wells and plugged/vented gas wells in coal areas and appear to be unrelated to the presence of underground natural gas storage areas or unconventional oil/gas production. Repeat measurements over 2 years show that flow rates of high emitters are sustained through time. Our attribute-based methane emission data and our comprehensive estimate of 470,000-750,000 abandoned wells in Pennsylvania result in estimated state-wide emissions of 0.04-0.07 Mt (1012 g) CH4 per year. This estimate represents 5-8% of annual anthropogenic methane emissions in Pennsylvania. Our methodology combining new field measurements with data mining of previously unavailable well attributes and numbers of wells can be used to improve methane emission estimates and prioritize cost-effective mitigation strategies for Pennsylvania and beyond.

Acoustic Indoor Localization System Integrating TDMA+FDMA Transmission Scheme and Positioning Correction Technique.

This paper presents a novel audio indoor localization system. In the proposed system, four speakers placed at known positions transmit chirp signals according to the time-division multiple access (TDMA) plus frequency-division multiple access (FDMA) transmission scheme. A smartphone receives the signal via a built-in microphone and calculates the time differences of arrival (TDOAs). Using TDOA measurements, the position is estimated by the shrinking-circle method. In particular, to reduce the positioning error in moving conditions, a TDOA correction method based on Doppler shifts is proposed. The performance of the proposed system was evaluated in real-world experiments using a 10.971 m × 5.684 m positioning area. The results of the static-target positioning experiment showed that the TDMA+FDMA transmission scheme has more advantages in improving the update rate of the positioning system than the TDMA-only transmission scheme. The results of the moving-target positioning experiment under three different speeds demonstrated that the positioning errors were reduced by about 10 cm when the Doppler-shift-based TDOA correction method was adopted. This research provides a possible framework for the realization of a TDOA-chirp-based acoustic indoor positioning system with high positioning accuracy and update rate.

Sleep duration and the risk of cancer: a systematic review and meta-analysis including dose-response relationship.

BACKGROUND: The effect of sleep duration on cancer risk remains controversial. We aimed to quantify the available evidence on this relationship using categorical and dose-response meta-analyses. METHODS: Population-based cohort studies and case-control studies with at least three categories of sleep duration were identified by searching PubMed, EMBASE, and the Cochrane Library database up to July 2017. RESULTS: Sixty-five studies from 25 articles were included, involving 1,550,524 participants and 86,201 cancer cases. The categorical meta-analysis revealed that neither short nor long sleep duration was associated with increased cancer risk (short: odds ratio [OR] = 1.01, 95% confidence intervals [CI] = 0.97-1.05; long: OR = 1.02, 95% CI = 0.97-1.07). Subgroup analysis revealed that short sleep duration was associated with cancer risk among Asians (OR = 1.36; 95% CI: 1.02-1.80) and long sleep duration significantly increased the risk of colorectal cancer (OR = 1.21; 95% CI: 1.08-1.34). The dose-response meta-analysis showed no significant relationship between sleep duration and cancer risk. When treated as two linear piecewise functions with a cut point of 7 h, similar nonsignificant associations were found (per 1-h reduction: OR = 1.02, 95% CI = 0.98-1.07; per 1-h increment: OR = 1.003, 95% CI = 0.97-1.03). CONCLUSION: Categorical meta-analysis indicated that short sleep duration increased cancer risk in Asians and long sleep duration increased the risk of colorectal cancer, but these findings were not consistent in the dose-response meta-analysis. Long-term randomized controlled trials and well-designed prospective studies are needed to establish causality and to elucidate the mechanism underlying the association between sleep duration and cancer risk.

Fast Electrochemical and Plasmonic Detection Reveals Multitime Scale Conformational Gating of Electron Transfer in Cytochrome c.

Conformational fluctuations play a central role in the electron transfer reactions of molecules. Because the fluctuations can be extremely fast in kinetics and small in amplitude, a technique with fast temporal resolution and high conformational sensitivity is needed to follow the transient electron transfer processes. Here we report on an electrochemically controlled plasmonic detection technique capable of monitoring conformational changes in redox molecules with ns response time. Using the technique, we study the electron transfer reaction and the associated conformational gating of a redox protein (cytochrome c). The study reveals that the conformational gating takes place over a broad range of time scales, from microsecond to millisecond.