Association of midlife air pollution exposures and residential road proximity with incident dementia: The Atherosclerosis Risk in Communities (ARIC) study.

BACKGROUND: Increasing evidence links higher air pollution exposures to increased risk of cognitive impairment. While midlife risk factors are often most strongly linked to dementia risk, few studies have considered associations between midlife roadway proximity or ambient air pollution exposure and incident dementia decades later, in late life. OBJECTIVES: Our objective was to determine if midlife exposures to ambient air pollution or roadway proximity are associated with increased risk of dementia in the Atherosclerosis Risk in Communities (ARIC) study over up to 29 years of follow-up. METHODS: Our eligible sample included Black and White ARIC participants without dementia at Visit 2 (1990-1992). Participants were followed through Visit 7 (2018-2019), with dementia status and onset date defined based on formal dementia ascertainment at study visits, informant interviews, and surveillance efforts. We used adjusted Weibull survival models to assess the associations of midlife ambient air pollution and road proximity with incident dementia. RESULTS: The median age at baseline (1990-1992, Visit 2) of the 12,700 eligible ARIC participants was 57.0 years; 56.0% were female, 24.2% were Black, and 78.9% had at least a high school education. Over up to 29 years of follow-up, 2511 (19.8%) persons developed dementia. No associations were found between ambient air pollutants and proximity to major roadways with risk of incident dementia. In exploratory analyses, living closer to roadways in midlife increased dementia risk in individuals younger at baseline and those without midlife hypertension, and there was evidence of increased risk of dementia with increased midlife exposure to NOx, several PM2.5 components, and trace metals among those with diabetes in midlife. CONCLUSIONS: Midlife exposure to ambient air pollution and midlife roadway proximity was not associated with dementia risk over decades of follow-up. Further investigation to explore potential for greater susceptibility among specific subgroups identified here is needed.

Encephalitis-like episodes with cortical edema and enhancement in patients with neuronal intranuclear inclusion disease.

OBJECTIVES: Neuronal intranuclear inclusion disease (NIID) exhibited significant clinical heterogeneities. However, the clinical features, radiographic changes, and prognosis of patients with encephalitis-like NIID have yet to be systematically elucidated. METHODS: Clinical data including medical history, physical examination, and laboratory examinations were collected and analyzed. Skin and sural nerve biopsies were conducted on the patient. Repeat-primed PCR (RP-PCR) and fluorescence amplicon length PCR (AL-PCR) were used to detect the expansion of CGG repeat. We also reviewed the clinical and genetic data of NIID patients with cortical enhancement. RESULTS: A 54-year-old woman presented with encephalitis-like NIID, characterized by severe headache and agitative psychiatric symptoms. The brain MRI showed cortical swelling in the temporo-occipital lobes and significant enhancement of the cortical surface and dura, but without hyperintensities along the corticomedullary junction on diffusion-weighted image (DWI). A biopsy of the sural nerve revealed a demyelinating pathological change. The intranuclear inclusions were detected in nerve and skin tissues using the p62 antibody and electron microscopy. RP-PCR and AL-PCR unveiled the pathogenic expansion of CGG repeats in the NOTCH2NLC gene. A review of the literature indicated that nine out of the 16 patients with cortical lesions and linear enhancement exhibited encephalitis-like NIID. CONCLUSION: This study indicated that patients with encephalitis-like NIID typically exhibited headache and excitatory psychiatric symptoms, often accompanied by cortical edema and enhancement of posterior lobes, and responded well to glucocorticoid treatment. Furthermore, some patients may not exhibit hyperintensities along the corticomedullary junction on DWI, potentially leading to misdiagnosis.

Design of Path-Planning System for Interventional Thermal Ablation of Liver Tumors Based on CT Images.

OBJECTIVE: Aiming at the shortcomings of artificial surgical path planning for the thermal ablation of liver tumors, such as the time-consuming and labor-consuming process, and relying heavily on doctors' puncture experience, an automatic path-planning system for thermal ablation of liver tumors based on CT images is designed and implemented. METHODS: The system mainly includes three modules: image segmentation and three-dimensional reconstruction, automatic surgical path planning, and image information management. Through organ segmentation and three- dimensional reconstruction based on CT images, the personalized abdominal spatial anatomical structure of patients is obtained, which is convenient for surgical path planning. The weighted summation method based on clinical constraints and the concept of Pareto optimality are used to solve the multi-objective optimization problem, screen the optimal needle entry path, and realize the automatic planning of the thermal ablation path. The image information database was established to store the information related to the surgical path. RESULTS: In the discussion with clinicians, more than 78% of the paths generated by the planning system were considered to be effective, and the efficiency of system path planning is higher than doctors' planning efficiency. CONCLUSION: After improvement, the system can be used for the planning of the thermal ablation path of a liver tumor and has certain clinical application value.

Noisy image segmentation based on synchronous dynamics of coupled photonic spiking neurons.

The collective dynamics in neural networks is essential for information processing and has attracted much interest on the application in artificial intelligence. Synchronization is one of the most dominant phenomenon in the collective dynamics of neural network. Here, we propose to use the spiking dynamics and collective synchronization of coupled photonic spiking neurons for noisy image segmentation. Based on the synchronization mechanism and synchronization control, the noised pattern segmentation is demonstrated numerically. This work provides insight into the possible application based on the collective dynamics of large-scale photonic networks and opens a way for ultra-high speed image processing.

Neuromorphic convolution with a spiking DFB-SA laser neuron based on rate coding.

We propose a neuromorphic convolution system using a photonic integrated distributed feedback laser with a saturable absorber (DFB-SA) as a photonic spiking neuron. The experiments reveal that the DFB-SA laser can encode different stimulus intensities at different frequencies, similar to biological neurons. Based on this property, optical inputs are encoded into rectangular pulses of varying intensities and injected into the DFB-SA laser, enabling the convolution results to be represented by the firing rate of the photonic spiking neuron. Both experimental and numerical results show that the binary convolution is successfully achieved based on the rate-encoding properties of a single DFB-SA laser neuron. Furthermore, we numerically predict 4-channel quadratic convolution and accomplish MNIST handwritten digit classification using a spiking DFB-SA laser neuron model with rate coding. This work provides a novel approach for convolution computation, indicating the potential of integrating DFB-SA laser into future photonics spiking neural networks.

Development and validation of the chemotherapy-induced peripheral neuropathy integrated assessment - oxaliplatin subscale: a prospective cohort study.

BACKGROUND: Current chemotherapy-induced peripheral neuropathy (CIPN) assessment tools mostly have poor sensitivity and weak anti-interference, so that it is sometimes difficult to provide substantive guidance for clinical intervention. This study aimed to develop an assessment tool dedicated for oxaliplatin to address these limitations. METHODS: This study screened 445 OIPN-related literatures for producing a symptom list, and developed the questionnaire module through expert supplement, item generation, content correlation analysis, pre-testing, and item improvement. The validation phase used a Chinese population-based prospective cohort study from June 2021 to July 2022. Patients were requested to complete the tested questionnaire, QLQ-CIPN20 and the CTCAE grading one day before cycles 2-6 of chemotherapy. Cronbach's α coefficient and intraclass correlation coefficient (ICC) were calculated for the internal consistency and stability analysis, respectively. Exploratory factor analysis was conducted to investigate the construct validity. The correlations among the tested questionnaire, QLQ-CIPN20 and CTCAE were compared for the criterion validity analysis. Wilcoxon signed-rank sum test was utilized to compare the sensitivity between the tested questionnaire and QLQ-CIPN20. RESULT: A 20-item CIPN assessment tool named chemotherapy-induced peripheral neuropathy integrated assessment - oxaliplatin subscale (CIPNIA-OS) was developed. The validation phase included 186 patients. Cronbach's α coefficient of CIPNIA-OS was 0.764 (> 0.7), and ICC was 0.997 (between 0.9 and 1). The structure of CIPNIA-OS containing seven factors was examined. The correlation coefficient between CIPNIA-OS and CTCAE was 0.661 (95%CI 0.623 to 0.695), which was significantly higher than that between QLQ-CIPN20 and CTCAE (0.417, 95%CI 0.363 to 0.469, p < 0.01). Besides, the total score of CIPNIA-OS was mostly higher than QLQ-CIPN20, with an average difference of 2.189 (CI 95% 2.056 to 2.322), and the difference gradually expanded with the progress of chemotherapy (p < 0.05). CONCLUSION: This study developed an original CIPN questionnaire which was dedicated for OIPN assessment. It was a comprehensive tool that covered acute OIPN symptoms and integrated features from several proven CIPN assessment tools. The validation results supported that CIPNIA-OS had satisfactory reliability, stability, construct, criterion validity, and was more accuracy and sensitive than QLQ-CIPN20 in the evaluation of OIPN.

Evidence mapping of clinical practice guidelines recommendations and quality for depression in children and adolescents.

This study systematically reviewed the clinical practice guidelines (CPGs) for depression in children and adolescents and assessed the quality and recommendation consistency of those CPGs. Evidence mapping was presented to illustrate the research trends and identify gaps to guide future research. Literature on CPGs for depression was systematically collected from PubMed, Embase, Web of Science, guideline databases, and psychiatric association/ society websites. The basic information, recommendations, methodological quality, and reporting quality of CPGs were extracted, and the supporting evidence strength for the included CPGs was analyzed in Excel. Four appraisers independently assessed the eligible CPGs using AGREE II instrument and the RIGHT checklist. All recommendations from the CPGs were summarized and analyzed, and the evidence mapping bubble charts were plotted in Excel. After excluding 15,184 records, 12 depression CPGs were eventually proved eligible, six of which were of high quality and six medium quality. A total of 39 major recommendations were summarized, 35 of which were supported by high-quality CPGs. Although direct comparisons are challenging due to differences in grading schemes and research quality, most CPGs share many pivotal recommendations that can help guide clinical practice. However, the evidence for some clinical problems is still lacking. Thus, more research is necessary on the screening and treatment of children and adolescents to put forward more evidence-based and high-quality recommendations.

Spatiotemporal trends and ecological determinants of cardiovascular mortality among 2844 counties in mainland China, 2006-2020: a Bayesian modeling study of national mortality registries.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death in China. No previous study has reported CVD mortality at county-level, and little was known about the nonmedical ecological factors of CVD mortality at such small scale in mainland China. Understanding the spatiotemporal variations of CVD mortality and examining its nonmedical ecological factors would be of great importance to tailor local public health policies. METHODS: By using national mortality registration data in China, this study used hierarchical spatiotemporal Bayesian model to demonstrate spatiotemporal distribution of CVD mortality in 2844 counties during 2006 to 2020 and investigate how nonmedical ecological determinants have affected CVD mortality inequities from the spatial perspectives. RESULTS: During 2006-2020, the age-standardized mortality rate (ASMR) of CVD decreased from 284.77 per 100,000 in 2006 to 241.34 per 100,000 in 2020. Among 2844 counties, 1144 (40.22%) were hot spots counties with a higher CVD mortality risk compared to the national average and located mostly in northeast, north central, and westernmost regions; on the contrary, 1551 (54.53%) were cold spots counties and located mostly in south and southeast coastal counties. CVD mortality risk decreased from 2006 to 2020 was larger in counties where CVD mortality rate had been higher in 2006 in most of the counties, vice versa. Nationwide, nighttime light intensity (NTL) was the major influencing factor of CVD mortality, a higher NTL appeared to be negatively associated with a lower CVD mortality, with one unit increase in NTL, and the CVD mortality risk will decrease 11% (relative risk of NTL was estimated as 0.89 with 95% confidence interval of 0.83-0.94). CONCLUSIONS: Substantial between-county discrepancies of CVD mortality distribution were observed during past 15 years in mainland China. Nonmedical ecological determinants were estimated to significantly explain the overall and local spatiotemporal patterns of this CVD mortality risk. Targeted considerations are needed to integrate primary care with clinical care through intensifying further strategies to narrow unequally distribution of CVD mortality at local scale. The approach to county-level analysis with small area models has the potential to provide novel insights into Chinese disease-specific mortality burden.

Different Agglomeration Processes Induced by the Varied Interaction of Fe-Fe Analogues with Differently Charged Surfactants.

The catalytic activity of Prussian blue analogues (PBAs) is mainly tuned via the control of material sizes and morphologies. However, the shapes and sizes of many PBAs are difficult to control. In this work, a facile approach is demonstrated using differently charged surfactants to tune the catalytic activity of PBAs. Fe-Fe PBAs prepared with non-ionic P123, cationic cetyltrimethylammonium bromide, and anionic sodium dodecyl sulfate are chosen to study the effect of surfactant charges on the catalytic activity. The transesterification of propylene carbonate to dimethyl carbonate by methanol is selected as a model reaction. Owing to the different agglomeration processes of PB particles after modified with differently charged surfactants, significantly varied shapes and sizes were observed. Accordingly, the catalytic activity is greatly varied by adding surfactants. The different catalytic activities may arise from the different behaviors of agglomeration of PB particles after surfactant modification as well as the material size and shape changes. Besides, apparent activation energies for PBs adding different surfactants were derived. Finally, the agglomeration mechanism of PB particles in the presence of differently charged surfactants was proposed.

EGLP-1 lowers body weight better than exendin-4 by reducing food intake and increasing basal energy expenditure in diet-induced obese mice.

It is well known that GLP-1 activates GLP-1R to reduce body weight by inhibiting eating. GLP-1 is cleaved by the neutral endopeptidase (NEP) 24.11 into a pentapeptide GLP-1 (32-36) amide, which increases basal energy expenditure and inhibits weight gain in obese mice. It is well known that GLP-1 analogs can reduce weight by suppressing eating. However, there are few reports of reducing weight through the dual effects of inhibiting eating and increasing basic energy. Here, we report the peptide EGLP-1, a GLP-1 analogue, which can reduce food intake and increase basal energy expenditure. In C2C12 myotubes, EGLP-1 can increase both phosphorylation of acetyl CoA carboxylase (ACC) and the ratio between phosphorylation of ACC and the total expression of ACC (pACC/ACC). In diet-induced obese mice, EGLP-1 is more effective than exendin-4 in reducing body weight, reducing fat mass and improving hepatic steatosis. At the same time, EGLP-1 can improve hyperglycemia, reduce food intake, and improve insulin resistance, just like exendin-4. In addition, EGLP-1, not exendin-4, can improve physiological parameters associated with lipid metabolism and increase oxygen consumption by increasing uncoupling proteins 3 (UCP3) expression and pACC/ACC ratio in skeletal muscle. Taken together, this data showed that EGLP-1 is able to reduce body weight by reducing food intake and increasing basal energy expenditure, suggesting it may be more effective in treating diabetic and non-diabetic overweight or obese people than pure GLP-1R agonist exendin-4.

Experimental implementation of spike-based neuromorphic XOR operation based on polarization-mode competition in a single VCSOA.

We experimentally and numerically propose an approach for implementing spike-based neuromorphic exclusive OR (XOR) operation using a single vertical-cavity semiconductor optical amplifier (VCSOA). XOR operation is realized based on the neuron-like inhibitory dynamics of the VCSOA subject to dual-polarized pulsed optical injections. The inhibitory dynamics based on the polarization-mode competition effect are analyzed, and the inhibitory response can be obtained in a suitable range of wavelength detuning. Here, all input and output bits are represented by spikes that are compatible with the photonic spiking neural network. The experimental and numerical results show that XOR operation can be realized in two polarization modes by adjusting the time offset in the inhibitory window and setting defined reference thresholds. In addition, the influences of delay time and input intensity ratio on XOR operation are studied experimentally. This scheme is energy efficient because VCSOA neuromorphic photonics computing and information processing.

Intelligent Diagnosis Based on Double-Optimized Artificial Hydrocarbon Networks for Mechanical Faults of In-Wheel Motor.

To avoid the potential safety hazards of electric vehicles caused by the mechanical fault deterioration of the in-wheel motor (IWM), this paper proposes an intelligent diagnosis based on double-optimized artificial hydrocarbon networks (AHNs) to identify the mechanical faults of IWM, which employs a K-means clustering and AdaBoost algorithm to solve the lower accuracy and poorer stability of traditional AHNs. Firstly, K-means clustering is used to improve the interval updating method of any adjacent AHNs molecules, and then simplify the complexity of the AHNs model. Secondly, the AdaBoost algorithm is utilized to adaptively distribute the weights for multiple weak models, then reconstitute the network structure of the AHNs. Finally, double-optimized AHNs are used to build an intelligent diagnosis system, where two cases of bearing datasets from Paderborn University and a self-made IWM test stand are processed to validate the better performance of the proposed method, especially in multiple rotating speeds and the load conditions of the IWM. The double-optimized AHNs provide a higher accuracy for identifying the mechanical faults of the IWM than the traditional AHNs, K-means-based AHNs (K-AHNs), support vector machine (SVM), and particle swarm optimization-based SVM (PSO-SVM).

Acoustic environments of intensive care units during the COVID-19 pandemic.

This study aims to investigate the typical noise levels and noise sources in an intensive care unit (ICU) during the COVID-19 pandemic. Acoustic experiments were conducted over 24 hrs in patient wards and at nurse stations in four Chinese hospitals. From the measurements, noise levels and sources were analysed in terms of the A-weighted equivalent sound pressure levels (L Aeq) and A-weighted maximum Fast time-weighted sound pressure levels (L AFmax) over three different time periods during the day (i.e. day, evening and night). Overall, noise levels (L Aeq) for 24 hrs in all hospitals exceeded the World Health Organisation's (WHO) guide levels, varying from 51.1 to 60.3 dBA. The highest maximum noise level reached 104.2 dBA. The single-bedded wards (side rooms) were quieter than multi-bedded wards, and night time noise levels were quieter than daytime and evening across all hospitals. It was observed that the most dominant noise sources were talking/voices, door-closing, footsteps, and general activities (e.g. noise from cleaning equipment and cutlery sound). Footsteps became an unexpected dominant noise source during the pandemic because of the staff's disposable shoe covers which made footsteps noisier. Patient alarms and coughing varied significantly between patients. Talking/voices produced the highest maximum median values of the sound exposure level (SEL) and the maximum noise level at all sites. Noise levels in all the patient rooms were more than the WHO guidelines. The pandemic control guidelines had little impact on the noise levels in the ICUs.

Nervous system diseases are associated with the severity and mortality of patients with COVID-19: a systematic review and meta-analysis.

Coronavirus disease 2019 (COVID-19) has become a global pandemic. Previous studies showed that comorbidities in patients with COVID-19 are risk factors for adverse outcomes. This study aimed to clarify the association between nervous system diseases and severity or mortality in patients with COVID-19. We performed a systematic literature search of four electronic databases and included studies reporting the prevalence of nervous system diseases in COVID-19 patients with severe and non-severe disease or among survivors and non-survivors. The included studies were pooled into a meta-analysis to calculate the odds ratio (OR) with 95% confidence intervals (95%CI). We included 69 studies involving 17 879 patients. The nervous system diseases were associated with COVID-19 severity (OR = 3.19, 95%CI: 2.37 to 4.30, P < 0.001) and mortality (OR = 3.75, 95%CI: 2.68 to 5.25, P < 0.001). Specifically, compared with the patients without cerebrovascular disease, patients with cerebrovascular disease infected with COVID-19 had a higher risk of severity (OR = 3.10, 95%CI: 2.21 to 4.36, P < 0.001) and mortality (OR = 3.45, 95% CI: 2.46 to 4.84, P < 0.001). Stroke was associated with severe COVID-19 disease (OR = 1.95, 95%CI: 1.11 to 3.42, P = 0.020). No significant differences were found for the prevalence of epilepsy (OR = 1.00, 95%CI: 0.42 to 2.35, P = 0.994) and dementia (OR = 2.39, 95%CI: 0.55 to 10.48, P = 0.247) between non-severe and severe COVID-19 patients. There was no significant association between stroke (OR = 1.79, 95%CI: 0.76 to 4.23, P = 0.185), epilepsy (OR = 2.08, 95%CI: 0.08 to 50.91, P = 0.654) and COVID-19 mortality. In conclusion, nervous system diseases and cerebrovascular disease were associated with severity and mortality of patients with COVID-19. There might be confounding factors that influence the relationship between nervous system diseases and COVID-19 severity as well as mortality.

Prevalence and Treatment of Diabetes in China, 2013-2018.

Importance: Recent data on prevalence, awareness, treatment, and risk factors of diabetes in China is necessary for interventional efforts. Objective: To estimate trends in prevalence, awareness, treatment, and risk factors of diabetes in China based on national data. Design, Setting, and Participants: Cross-sectional nationally representative survey data collected in adults aged 18 years or older in mainland China from 170 287 participants in the 2013-2014 years and 173 642 participants in the 2018-2019 years. Exposures: Fasting plasma glucose and hemoglobin A1c levels were measured for all participants. A 2-hour oral glucose tolerance test was conducted for all participants without diagnosed diabetes. Main Outcomes and Measures: Primary outcomes were diabetes and prediabetes defined according to American Diabetes Association criteria. Secondary outcomes were awareness, treatment, and control of diabetes and prevalence of risk factors. A hemoglobin A1c level of less than 7.0% (53 mmol/mol) among treated patients with diabetes was considered adequate glycemic control. Results: In 2013, the median age was 55.8 years (IQR, 46.4-65.2 years) and the weighted proportion of women was 50.0%; in 2018, the median age was 51.3 years (IQR, 42.1-61.6 years), and the weighted proportion of women was 49.5%. The estimated prevalence of diabetes increased from 10.9% (95% CI, 10.4%-11.5%) in 2013 to 12.4% (95% CI, 11.8%-13.0%) in 2018 (P < .001). The estimated prevalence of prediabetes was 35.7% (95% CI, 34.2%-37.3%) in 2013 and 38.1% (95% CI, 36.4%-39.7%) in 2018 (P = .07). In 2018, among adults with diabetes, 36.7% (95% CI, 34.7%-38.6%) reported being aware of their condition, and 32.9% (95% CI, 30.9%-34.8%) reported being treated; 50.1% (95% CI, 47.5%-52.6%) of patients receiving treatment were controlled adequately. These rates did not change significantly from 2013. From 2013 to 2018, low physical activity, high intake of red meat, overweight, and obesity significantly increased in prevalence. Conclusions and Relevance: In this survey study, the estimated diabetes prevalence was high and increased from 2013 to 2018. There was no significant improvement in the estimated prevalence of adequate treatment.

Time-delay signature concealment of chaos and ultrafast decision making in mutually coupled semiconductor lasers with a phase-modulated Sagnac loop.

We propose and experimentally demonstrate the generation of dual-channels chaos with time delay signature (TDS) concealment by introducing a phase-modulated Sagnac loop in mutually coupled semiconductor lasers (MCSL). Furthermore, we demonstrate the utilization of the dual-channels chaos to solve multi-armed bandit (MAB) problem in reinforcement learning. The experimental results agree well with the numerical simulations. For the purpose of comparison, the MCSL with a conventional Sagnac loop is also considered. It is found that the TDS of dual-channels chaotic signals can be better concealed in our proposed system. Besides, the proposed system allows for a better decision making performance in MAB problem. Moreover, compared with the one-channel chaotic system, the proposed dual-channels chaotic system achieves ultrafast decision making in parallel, and thus, is highly valuable for further improving the security of communication systems and the performance of photonic intelligence.

All-optical neuromorphic XOR operation with inhibitory dynamics of a single photonic spiking neuron based on a VCSEL-SA.

We propose a simple hardware architecture for solving exclusive OR (XOR) tasks in a single step by using a single photonic spiking neuron based on vertical-cavity surface-emitting lasers with an embedded saturable absorber (VCSEL-SA) subject to dual-polarized pulsed optical injection. We model the inhibitory photonic spiking neuron by extending the Yamada model and spin-flip model to incorporate the two polarization-resolved modes and the saturable absorber. It is shown that, by carefully adjusting the temporal difference according to the inhibitory window, the XOR operation can be realized in a single photonic spiking neuron, which is interesting and valuable for the photonic neuromorphic computing and information processing.

Population-Based Surveillance for Birth Defects Potentially Related to Zika Virus Infection - 22 States and Territories, January 2016-June 2017.

Zika virus infection during pregnancy can cause congenital brain and eye abnormalities and is associated with neurodevelopmental abnormalities (1-3). In areas of the United States that experienced local Zika virus transmission, the prevalence of birth defects potentially related to Zika virus infection during pregnancy increased in the second half of 2016 compared with the first half (4). To update the previous report, CDC analyzed population-based surveillance data from 22 states and territories to estimate the prevalence of birth defects potentially related to Zika virus infection, regardless of laboratory evidence of or exposure to Zika virus, among pregnancies completed during January 1, 2016-June 30, 2017. Jurisdictions were categorized as those 1) with widespread local transmission of Zika virus; 2) with limited local transmission of Zika virus; and 3) without local transmission of Zika virus. Among 2,004,630 live births, 3,359 infants and fetuses with birth defects potentially related to Zika virus infection during pregnancy were identified (1.7 per 1,000 live births, 95% confidence interval [CI] = 1.6-1.7). In areas with widespread local Zika virus transmission, the prevalence of birth defects potentially related to Zika virus infection during pregnancy was significantly higher during the quarters comprising July 2016-March 2017 (July-September 2016 = 3.0; October-December 2016 = 4.0; and January-March 2017 = 5.6 per 1,000 live births) compared with the reference period (January-March 2016) (1.3 per 1,000). These findings suggest a fourfold increase (prevalence ratio [PR] = 4.1, 95% CI = 2.1-8.4) in birth defects potentially related to Zika virus in widespread local transmission areas during January-March 2017 compared with that during January-March 2016, with the highest prevalence (7.0 per 1,000 live births) in February 2017. Population-based birth defects surveillance is critical for identifying infants and fetuses with birth defects potentially related to Zika virus regardless of whether Zika virus testing was conducted, especially given the high prevalence of asymptomatic disease. These data can be used to inform follow-up care and services as well as strengthen surveillance.

Mechanosensing in liver regeneration.

Liver is highly regenerative as it can restore its function and size even after 70% partial hepatectomy. During liver regeneration, the mechanical and chemical environment of liver is altered with accumulation of various growth factors and remodeling of extracellular environment. Cells can sense the changes in their cellular environment through various chemo and mechanosensors present on their surfaces. These changes are then transduced by initiation of multiple signaling pathways. Traditional view of liver regeneration describes the process as a cascade of chemical signaling pathways. In this review, we describe the role of mechanical forces and mechanosensing in regulating liver regeneration with focus on the role of altered shear and extracellular matrix environment following injury. These mechanosensing mechanisms either generate molecular signals that further activate downstream signaling pathways such as YAP or directly transduce mechanical signals by regulating actomyosin cytoskeleton. These signals travel to the decision center such as nucleus to switch cell fate and activate functions needed in liver regeneration, e.g. proliferation of various hepatic cell types, differentiation of hepatic stem cells, extracellular matrix remodeling and termination signals that regulate the regenerated liver size. Different mechanical and chemical signals coordinate intracellular chemical signaling pathways leading to robust liver regeneration.

Pharmacological Effects of EGLP-1, a Novel Analog of Glucagon-Like Peptide-1, on Carbohydrate and Lipid Metabolism.

BACKGROUND/AIMS: Abnormal glucose metabolism and lipid metabolism are two key issues in Type 1 diabetes mellitus (T1DM). Insulin can control carbohydrate metabolism adequately, but cannot regulate lipid metabolism well in patients with T1DM. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have cured type 2 diabetes mellitus in clinical trials and have improved T1DM glycemic control in preclinical studies. However, previous studies have not reported whether GLP-1 can lower the serum concentration of non-esterified fatty acids (NEFAs). In this study, we examine whether GLP-1 can affect serum NEFA levels. METHODS: The bioactivity of EGLP-1 (a novel GLP-1 analog) in vitro was analyzed in CG-HEK293 cells and with high-performance liquid chromatography. An intraperitoneal glucose tolerance test (IPGTT) was used to analyze the acute and sustained hypoglycemic effects of EGLP-1 in normal C57BL/6J mice. Streptozotocin-induced hyperglycemic mice were used to study the effects of EGLP-1 on blood glucose and NEFAs as well as its mechanism. RESULTS: EGLP-1 activated GLP-1R and resisted dipeptidyl peptidase-IV digestion in vitro. Additionally, EGLP-1 had an insulinotropic action in vivo that lasted for approximately 6 h. In Streptozotocin-induced hyperglycemic mice, EGLP-1 improved hyperglycemia, inhibited food intake, and increased ß-cell area. Serum physiological indexes showed that insulin and C-peptide levels were increased, while NEFA and triacylglycerol concentrations were decreased. Western blot analysis revealed that EGLP-1 significantly reduced phosphorylated-hormone sensitive lipase (pHSL) levels in white adipose tissue. CONCLUSIONS: EGLP-1 can improve hyperglycemia by increasing islet ß-cell area and improving ß-cell function, possibly due to reduced NEFA content in serum by lowering pHSL levels.