Elucidating causal relationships of diet-derived circulating antioxidants and the risk of osteoporosis: A Mendelian randomization study.

Background: Osteoporosis (OP) is typically diagnosed by evaluating bone mineral density (BMD), and it frequently results in fractures. Here, we investigated the causal relationships between diet-derived circulating antioxidants and the risk of OP using Mendelian randomization (MR). Methods: Published studies were used to identify instrumental variables related to absolute levels of circulating antioxidants like lycopene, retinol, ascorbate, and ß-carotene, as well as antioxidant metabolites such as ascorbate, retinol, α-tocopherol, and γ-tocopherol. Outcome variables included BMD (in femoral neck, lumbar spine, forearm, heel, total body, total body (age over 60), total body (age 45-60), total body (age 30-45), total body (age 15-30), and total body (age 0-15)), fractures (in arm, spine, leg, heel, and osteoporotic fractures), and OP. Inverse variance weighted or Wald ratio was chosen as the main method for MR analysis based on the number of single nucleotide polymorphisms (SNPs). Furthermore, we performed sensitivity analyses to confirm the reliability of the findings. Results: We found a causal relationship between absolute retinol levels and heel BMD (p = 7.6E-05). The results of fixed effects IVW showed a protective effect of absolute retinol levels against heel BMD, with per 0.1 ln-transformed retinol being associated with a 28% increase in heel BMD (OR: 1.28, 95% CI: 1.13-1.44). In addition, a sex-specific effect of the absolute circulating retinol levels on the heel BMD has been observed in men. No other significant causal relationship was found. Conclusion: There is a positive causal relationship between absolute retinol levels and heel BMD. The implications of our results should be taken into account in future studies and in the creation of public health policies and OP prevention tactics.

Service blockage on the downlink in large-scale satellite optical networks: a multi-downlink scheduling for routing selection.

Over years of space laser communication technology advances, satellite optical networks (SONs) have emerged as a pivotal component in 6 G networks. Satellite services are transmitted from the global view, undergoing transmission through SONs, and being downloaded to the targeted areas. However, the transmission capacity of satellites passing through the areas where users are concentrated may be insufficient to download services transmitted worldwide. This problem exists in various kinds of satellite networks and may cause a large amount of service congestion. In this paper, we propose a multi-downlink delivery routing selection (MDD-RS) strategy to study the total utilization of transmission capacity of SONs. We construct an integer linear programming (ILP) model to establish an optimal case study for minimal network capacity occupation. Also, we design an online option, MDD-RS heuristic algorithm, dynamically calculating path routes, considering bandwidth allocation and resource constraints. A comparative analysis against the conventional single-downlink scheme reveals superior performance of the MDD-RS heuristic algorithm, with a reduction in blocking probability of 0.129 and an improvement in bandwidth utilization of 0.032.

Autonomic end-to-end quality-of-service assurance over QKD-secured optical networks.

Quantum key distribution (QKD) provides future-proof security for data communications over optical networks. Currently, sophisticated QKD systems are developed and the scale of QKD-secured optical networks (QKD-ONs) becomes larger. Given the complex network conditions and dynamic end-to-end security services in QKD-ONs, autonomic management and control becomes a promising paradigm to support end-to-end quality-of-service (QoS) assurance in an efficient and stable way without requiring human intervention. Hence, to enable and utilize the autonomic functionalities over QKD-ONs for realizing the end-to-end QoS assurance becomes a challenge. This work enhances the software defined networking (SDN) technique to tackle this challenge because SDN can add programmability and flexibility for QKD-ON's management and control. A new architecture of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance is designed, where a knowledge engine with autonomic control loops is developed in the SDN controller. We present the autonomic end-to-end QoS assurance procedure, and the cross-layer collaborative QoS assurance (CLC-QA) strategy for implementing the autonomic functionalities in the network level over QKD-ONs. We also establish an experimental testbed of SDN-based QKD-ONs supporting autonomic end-to-end QoS assurance, and perform the numerical simulation to verify our proposed approaches. Experimental results demonstrate that our presented approaches can achieve the millisecond-level overall latency of 337 ms and 618 ms, during the first and second autonomic adjustment without human intervention in case of the autonomic QoS protection. Moreover, the CLC-QA strategy is evaluated under different traffic loads by being compared with the baseline strategy without cross-layer collaboration. It can improve 22.5% protection success ratio and save 5.7% average key consumption.

Identifying modifiable factors and their joint effect on brain health: an exposome-wide association study.

Considerable uncertainty remains regarding the associations of multiple factors with brain health. We aimed to conduct an exposome-wide association study on neurodegenerative disease and neuropsychiatry disorders using data of participants from the UK Biobank. Multivariable Cox regression models with the least absolute shrinkage and selection operator technique as well as principal component analyses were used to evaluate the exposures in relation to common disorders of central nervous system (CNS). Restricted cubic splines were conducted to explore potential nonlinear correlations. Then, weighted standardized scores were generated based on the coefficients to calculate the joint effects of risk factors. We also estimated the potential impact of eliminating the unfavorable profiles of risk domains on CNS disorders using population attributable fraction (PAF). Finally, sensitivity analyses were performed to reduce the risk of reverse causality. The current study discovered the significantly associated exposures fell into six primary exposome categories. The joint effects of identified risk factors demonstrated higher risks for common disorders of CNS (HR = 1.278 ~ 3.743, p < 2e-16). The PAF varied by exposome categories, with lifestyle and medical history contributing to majority of disease cases. In total, we estimated that up to 3.7 ~ 64.1% of disease cases could be prevented.This study yielded modifiable variables of different categories and assessed their joint effects on common disorders of CNS. Targeting the identified exposures might help formulate effective strategies for maintaining brain health.

Evaluation of a non-dispersive infrared spectrometer for quantifying organic and elemental carbon in diesel particulate matter.

Diesel particulate matter (DPM) is a common and well-known health hazard in the mining environment. The regulatory method for monitoring both the organic and elemental carbon (OC, EC) portions of DPM is a laboratory-based thermal-optical method with a typical turnaround time of one week. In order to evaluate exposure levels and take corrective action prior to overexposure, a portable real-time device capable of quantifying both OC and EC is needed. To that end, researchers from the National Institute for Occupational Safety and Health (NIOSH) designed and tested the feasibility of a device based on bandpass optical filters that target key infrared wavelengths associated with DPM and its spectroscopic baseline. The resulting device, referred to here as a non-dispersive infrared (NDIR) spectrometer could serve as the basis of a cost-effective, field-portable alternative to the laboratory thermal-optical method. The limits of quantification (LOD) indicate that the NDIR spectrometer can quantify EC, OC, and TC provided they are present at 20, 37, and 46 µg/m3 or more, respectively. In the event that the NDIR spectrometer is integrated with a sampler and filter tape the LOD is estimated to be reduced to 13, 7, and 10 µg/m3 for EC, OC, and TC, respectively. These LOD estimates assume a face velocity of 59 cm/s and a sampling time of 30 min.

Security enhanced routing and spectrum allocation against crosstalk attacks for confidential lightpath in elastic optical networks.

Elastic optical network (EON) is a critical transmission infrastructure for emerging new applications due to its spectral efficiency and flexibility. Nowadays, numerous confidential lightpaths (CLPs) are carried over EON to support security-sensitive users. However, they are vulnerable to crosstalk attacks at the optical layer, typically aimed at eavesdropping on the carried data or even disrupting connections. Due to the transparent nature of the optical signals, such attacks are difficult to detect and could last for a long time, resulting in data leakage even spreading throughout the network. This paper presents a novel routing and spectrum allocation (RSA) algorithm to protect CLPs from crosstalk attacks. We investigate intra-channel and inter-channel crosstalk attacks and develop a metric to quantify crosstalk leakage risks (CLRs). We first formulate an ILP model to plan CLPs with a minimum CLR. To solve the same problem for large-scale networks, we also propose a heuristic algorithm, i.e., crosstalk-attack-aware RSA. Results indicate that the proposed algorithm is capable of reducing CLR by 23%.

Association of peripheral immunity and cerebral small vessel disease in older adults without dementia: A longitudinal study.

This study explored the associations between peripheral immunity with cerebral small vessel diseases. Older adults without dementia from the Alzheimer's Disease Neuroimaging Initiative were investigated. Peripheral blood was obtained, and magnetic resonance imaging was performed to measure cerebral microbleeds (CMB), lacunar infarctions (LI), and white matter hyperintensities (WMH). Multivariable-adjusted regression models, linear mixed-effects models, and the Spearman correlations were used to evaluate the associations. At baseline, individuals with greater neutrophils (odds ratio [OR] =1.10, 95% confidence interval [CI] 1.00-1.20, p=0.042) and monocytes (OR=1.12, 95% CI 1.02-1.22, p=0.016) had higher WMH volume. On the contrary, a higher lymphocyte-to-monocyte ratio (LMR) was related to lower WMH volume (OR=0.91, 95% CI 0.82-1.00, p=0.041). Longitudinally, higher neutrophils (ρ=0.084, p=0.049) and NLR (ρ=0.111, p=0.009) predicted accelerated progression of WMH volume, while a greater LMR (ρ=-0.101, p=0.018) was linked to slower growth of WMH volume. Nevertheless, associations between peripheral immunity with CMB or LI were not observed at baseline and follow-up. Our study found that peripheral immune indexes could serve as convenient noninvasive biomarkers of WMH.

Increased serum extrachromosomal circular DNA SORBS1circle level is associated with insulin resistance in patients with newly diagnosed type 2 diabetes mellitus.

BACKGROUND: Extrachromosomal circular DNAs (eccDNAs) exist in human blood and somatic cells, and are essential for oncogene plasticity and drug resistance. However, the presence and impact of eccDNAs in type 2 diabetes mellitus (T2DM) remains inadequately understood. METHODS: We purified and sequenced the serum eccDNAs obtained from newly diagnosed T2DM patients and normal control (NC) subjects using Circle-sequencing. We validated the level of a novel circulating eccDNA named sorbin and SH3-domain- containing-1circle97206791-97208025 (SORBS1circle) in 106 newly diagnosed T2DM patients. The relationship between eccDNA SORBS1circle and clinical data was analyzed. Furthermore, we explored the source and expression level of eccDNA SORBS1circle in the high glucose and palmitate (HG/PA)-induced hepatocyte (HepG2 cell) insulin resistance model. RESULTS: A total of 22,543 and 19,195 eccDNAs were found in serum samples obtained from newly diagnosed T2DM patients and NC subjects, respectively. The T2DM patients had a greater distribution of eccDNA on chromosomes 1, 14, 16, 17, 18, 19, 20 and X. Additionally, 598 serum eccDNAs were found to be upregulated, while 856 eccDNAs were downregulated in T2DM patients compared with NC subjects. KEGG analysis demonstrated that the genes carried by eccDNAs were mainly associated with insulin resistance. Moreover, it was validated that the eccDNA SORBS1circle was significantly increased in serum of newly diagnosed T2DM patients (106 T2DM patients vs. 40 NC subjects). The serum eccDNA SORBS1circle content was positively correlated with the levels of glycosylated hemoglobin A1C (HbA1C) and homeostasis model assessment of insulin resistance (HOMA-IR) in T2DM patients. Intracellular eccDNA SORBS1circle expression was significantly enhanced in the high glucose and palmitate (HG/PA)-induced hepatocyte (HepG2 cell) insulin resistance model. Moreover, the upregulation of eccDNA SORBS1circle in the HG/PA-treated HepG2 cells was dependent on generation of apoptotic DNA fragmentation. CONCLUSIONS: These results provide a preliminary understanding of the circulating eccDNA patterns at the early stage of T2DM and suggest that eccDNA SORBS1circle may be involved in the development of insulin resistance.

Genetic architectures of cerebral ventricles and their overlap with neuropsychiatric traits.

The cerebral ventricles are recognized as windows into brain development and disease, yet their genetic architectures, underlying neural mechanisms and utility in maintaining brain health remain elusive. Here we aggregated genetic and neuroimaging data from 61,974 participants (age range, 9 to 98 years) in five cohorts to elucidate the genetic basis of ventricular morphology and examined their overlap with neuropsychiatric traits. Genome-wide association analysis in a discovery sample of 31,880 individuals identified 62 unique loci and 785 candidate genes associated with ventricular morphology. We replicated over 80% of loci in a well-matched cohort of lateral ventricular volume. Gene set analysis revealed enrichment of ventricular-trait-associated genes in biological processes and disease pathogenesis during both early brain development and degeneration. We explored the age-dependent genetic associations in cohorts of different age groups to investigate the possible roles of ventricular-trait-associated loci in neurodevelopmental and neurodegenerative processes. We describe the genetic overlap between ventricular and neuropsychiatric traits through comprehensive integrative approaches under correlative and causal assumptions. We propose the volume of the inferior lateral ventricles as a heritable endophenotype to predict the risk of Alzheimer's disease, which might be a consequence of prodromal Alzheimer's disease. Our study provides an advance in understanding the genetics of the cerebral ventricles and demonstrates the potential utility of ventricular measurements in tracking brain disorders and maintaining brain health across the lifespan.

Integrating key generation and distribution with the quantum noise stream cipher system without compromising the transmission performance.

We propose and experimentally demonstrate a secure quantum noise stream cipher transmission system that integrates key generation and distribution. At the stage of carrier phase recovery, the estimated phase noise is used to generate randomness keys without additional equipment. Based on direct sequence spread spectrum technology, we integrate the distributed keys with quantum noise stream cipher signals. The key distribution and encryption transmission can be completed simultaneously without occupying additional bandwidth or time slots. By changing the position of distributed keys in the encryption base, the BER performance of QAM/QNSC signals cannot be affected by the keys. Experimental results demonstrate that the 54.5 Mbps key distribution and 31 Gbps encryption transmission without OSNR penalty can be achieved simultaneously over a 120 km standard single-mode fiber.

Novel compound heterozygous pathogenic variants in the SLC3A1 gene in a Chinese family with cystinuria.

BACKGROUND: Cystinuria is an autosomal recessive disorder characterized by a cystine transport deficiency in the renal tubules due to mutations in two genes: SLC3A1 and SLC7A9. Cystinuria can be classified into three forms based on the genotype: type A, due to mutations in the SLC3A1 gene; type B, due to mutations in the SLC7A9 gene; and type AB, due to mutations in both genes. METHODS: We report a 12-year-old boy from central China with cystine stones. He was from a non-consanguineous family that had no known history of genetic disease. A physical examination showed normal development and neurological behaviors. Whole-exome and Sanger sequencing were used to identify and verify the suspected pathogenic variants. RESULTS: The compound heterozygous variants c.898_905del (p.Arg301AlafsTer6) is located in exon5 and c.1898_1899insAT (p.Asp634LeufsTer46) is located in exon10 of SLC3A1 (NM_000341.4) were deemed responsible for type A cystinuria family. The variant c.898_905del was reported in a Japanese patient in 2000, and the variant c.1898_1899insAT is novel. CONCLUSION: A novel pathogenic heterozygous variant pair of the SLC3A1 gene was identified in a Chinese boy with type A cystinuria, enriching the mutational spectrum of the SLC3A1 gene. We attempted to find a pattern for the association between the genotype of SLC3A1 variants and the manifestations of cystinuria in patients with different onset ages. Our findings have important implications for genetic counseling and the early clinical diagnosis of cystinuria.

Classification and Identification of Contaminants in Recyclable Containers Based on a Recursive Feature Elimination-Light Gradient Boosting Machine Algorithm Using an Electronic Nose.

Establishing an excellent recycling mechanism for containers is of great importance for environmental protection, so many technical approaches applied during the whole recycling stage have become popular research issues. Among them, classification is considered a key step, but this work is mostly achieved manually in practical applications. Due to the influence of human subjectivity, the classification accuracy often varies significantly. In order to overcome this shortcoming, this paper proposes an identification method based on a Recursive Feature Elimination-Light Gradient Boosting Machine (RFE-LightGBM) algorithm using electronic nose. Firstly, odor features were extracted, and feature datasets were then constructed based on the response data of the electronic nose to the detected gases. Afterwards, a principal component analysis (PCA) and the RFE-LightGBM algorithm were applied to reduce the dimensionality of the feature datasets, and the differences between these two methods were analyzed, respectively. Finally, the differences in the classification accuracies on the three datasets (the original feature dataset, PCA dimensionality reduction dataset, and RFE-LightGBM dimensionality reduction dataset) were discussed. The results showed that the highest classification accuracy of 95% could be obtained by using the RFE-LightGBM algorithm in the classification stage of recyclable containers, compared to the original feature dataset (88.38%) and PCA dimensionality reduction dataset (92.02%).

Advances in the pharmacological effects and molecular mechanisms of emodin in the treatment of metabolic diseases.

Rhubarb palmatum L., Polygonum multijiorum Thunb., and Polygonum cuspidatum Sieb. Et Zucc. are traditional Chinese medicines that have been used for thousands of years. They are formulated into various preparations and are widely used. Emodin is a traditional Chinese medicine monomer and the main active ingredient in Rhubarb palmatum L., Polygonum multijiorum Thunb., and Polygonum cuspidatum Sieb. Et Zucc. Modern research shows that it has a variety of pharmacological effects, including promoting lipid and glucose metabolism, osteogenesis, and anti-inflammatory and anti-autophagy effects. Research on the toxicity and pharmacokinetics of emodin can promote its clinical application. This review aims to provide a basis for further development and clinical research of emodin in the treatment of metabolic diseases. We performed a comprehensive summary of the pharmacology and molecular mechanisms of emodin in treating metabolic diseases by searching databases such as Web of Science, PubMed, ScienceDirect, and CNKI up to 2023. In addition, this review also analyzes the toxicity and pharmacokinetics of emodin. The results show that emodin mainly regulates AMPK, PPAR, and inflammation-related signaling pathways, and has a good therapeutic effect on obesity, hyperlipidemia, non-alcoholic fatty liver disease, diabetes and its complications, and osteoporosis. In addition, controlling toxic factors and improving bioavailability are of great significance for its clinical application.

Traffic-based adaptive bandwidth adjustment for flexible OTN connectivity in optical networks.

In conventional optical transport networks, the service form is the fixed bandwidth connectivity, which is not flexible for carrying bursting traffic. To support the time-varying traffic in an efficient way, researchers are studying the optical service units for building the more flexible optical transport network (OTN) connectivity, which is capable of dynamic hitless bandwidth adjustment. To better utilize the benefits of flexible connectivity, network operators need efficient algorithms to adjust the flexible connectivity bandwidth, especially in the network with a massive number of connections. In this paper, based on max-min fair bandwidth allocation criteria, we propose two traffic-based adaptive bandwidth adjustment algorithms to make bandwidth adjustment decisions, with the aim to improve bandwidth effectiveness. Simulation results show that the proposed algorithms can improve bandwidth utilization by up to 16%. Additionally, under high load conditions, it can reduce the loss in traffic bitrate by a maximum of 10%.

Effects of prepregnancy dietary patterns on infant birth weight: a prospective cohort study.

BACKGROUND: Maternal nutrition can have a profound effect on fetal growth, development, and subsequent infant birth weight. However, little is known regarding the influence of prepregnancy dietary patterns. OBJECTIVES: This study aimed to explore the effects between prepregnancy dietary patterns on birth weight. METHODS: This study included 911 singleton live-born infants from the Taicang and Wuqiang Mother-Child Cohort Study (TAWS). Baseline information and prepregnancy diet data were collected during early pregnancy. Newborn birth information was obtained from the Wuqiang County Hospital. Macrosomia, defined as a birth weight of ≥4000 g, and large for gestational age (LGA), defined as a birth weight higher than the 90th percentile for the same sex and gestational age, were the outcomes of interest. The dietary patterns were extracted using principal component analysis. Logistic regression models were used to investigate the association between prepregnancy dietary patterns (in tertiles) and macrosomia and LGA, and subgroup analysis was further explored by pre-pregnancy body mass index (BMI). RESULTS: Four dietary patterns were identified based on 15 food groups. These patterns were named as "cereals-vegetables-fruits," "vegetables-poultry-aquatic products," "milk-meat-eggs," and "nuts-aquatic products-snacks." After adjusting for sociodemographic characteristics, pregnancy complications, and other dietary patterns, greater adherence to the "cereals-vegetables-fruits" pattern before pregnancy was associated with a higher risk of macrosomia (adjusted OR = 2.220, 95% CI: 1.018, 4.843), while greater adherence to the "nuts-aquatic products-snacks" pattern was associated with a lower risk of macrosomia (adjusted OR = 0.357, 95% CI: 0.175, 0.725) compared to the lowest tertile. No significant association was observed between prepregnancy dietary patterns and LGA. However, after subgroup analysis of pre-pregnancy BMI, "cereals-vegetables-fruits" pattern was associated with an increased risk of LGA in overweight and obese mothers (adjusted OR = 2.353, 95% CI: 1.010, 5.480). CONCLUSIONS: An unbalanced pre-pregnancy diet increases the risk of macrosomia and LGA, especially in overweight or obese women before pre-pregnancy.

Channel power equalization based on joint optimization of EDFA and ROADM configuration in open optical network.

Deterioration of the signal-to-noise ratio (SNR) is an important challenge in ultra-long multi optical line system (OLS) optical transmission systems. The non-uniform gain and cascading of the Erbium-doped fiber amplifier (EDFA) lead to SNR deterioration in transmission systems. In this paper, we propose two channel power equalization methods based on joint optimization of EDFA and Reconfigurable optical add-drop multiplexer (ROADM) configurations: 1) reinforcement learning (RL)-based channel power equalization (RL-PE) and 2) covariance matrix adaptive evolution strategy (CMA-ES) channel power equalization (CMA-PE). The simulation results indicate that the power equalization effect was improved by 1.9 dB through the CMA-PE method, while the RL-PE method led to a 1.5 dB improvement in an ultra-long 80-channel 7-OLS transmission system.

Topology Abstraction-Based Routing Scheme for Secret-Key Provisioning in Hybrid GEO/LEO Quantum Satellite Networks.

Quantum key distribution (QKD) is a promising technique to resist the threat against quantum computers. However, the high loss of quantum signals over a long-distance optical fiber is an obstacle for QKD in the intercontinental domain. In this context, the quantum satellite network is preferred over the terrestrial quantum optical network. Due to the mobility of satellites, the satellite topology is dynamic in the quantum satellite network, which remains a challenge for routing. In hybrid geostationary-earth-orbit (GEO)/low-earth-orbit (LEO) quantum satellite networks, the lack of an efficient scheduling scheme for GEO/LEO satellites also limits the construction of quantum satellite networks. Therefore, this paper provides a topology abstraction-based routing scheme for secret-key provisioning, where the dynamic physical topology is translated into a quasi-static abstracted topology. This scheme contributes to saving the precious secret key resources. In order to improve the success probability of long-distance QKD requests, three novel resource-scheduling heuristic algorithms are proposed in hybrid GEO/LEO quantum satellite networks. Simulation results indicate that the proposed algorithms can improve the success probability of QKD requests by 47% compared to the benchmark.

Analysis of the encryption penalty in a QAM-based quantum noise stream cipher.

Quantum noise stream cipher based on quadrature-amplitude-modulation (QAM/QNSC) is a kind of physical layer encryption technology. However, the additional encryption penalty will significantly affect the practical deployment of QNSC, especially in the high capacity and long-haul transmission system. With our research, the encryption process of QAM/QNSC degrades the transmission performance of plaintext information. In this paper, we quantitatively analyze the encryption penalty of QAM/QNSC based on the proposed concept of effective minimum Euclidean distance. We calculate the theoretical signal-to-noise ratio sensitivity and encryption penalty of QAM/QNSC signals. A modified feedforward pilot-aided two-stage carrier phase recovery scheme is used to reduce the effect of laser phase noise and the encryption penalty. Experimental results achieve single-channel 205.9 Gbit/s 640km transmission with single carrier polarization-diversity-multiplexing 16-QAM/QNSC signal.

Machine-learning-based method for fiber-bending eavesdropping detection.

In this Letter, we present a scheme for detecting fiber-bending eavesdropping based on feature extraction and machine learning (ML). First, 5-dimensional features from the time-domain signal are extracted from the optical signal, and then a long short-term memory (LSTM) network is applied for eavesdropping and normal event classification. Experimental data are collected from a 60 km single-mode fiber transmission link with eavesdropping implemented by a clip-on coupler. Results show that the proposed scheme achieves a 95.83% detection accuracy. Furthermore, since the scheme focuses on the time-domain waveform of the received optical signal, additional devices and a special link design are not required.