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.

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.

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%).

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.

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%.

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.

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.

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.

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.

Renoprotection by Inhibiting Connexin 43 Expression in a Mouse Model of Obesity-Related Renal Injury.

Introduction: Our previous study conducted in an obesity-related renal injury rat model have established a connection between increased connexin 43 (Cx43) expression and renal injury. In this study, we investigated whether inhibiting Cx43 expression could provide renoprotection in a mouse model of obesity-related renal injury. Methods: Five-week-old C57BL/6J mice were fed with a high-fat diet for 12 weeks to establish an obesity-related renal injury model, then they were treated with Cx43 antisense oligodeoxynucleotide (AS) or scrambled oligodeoxynucleotide (SCR) by an implanted osmotic pump for 4 weeks. Finally, the glomerular filtration function, the histological change in the glomeruli, and the markers of podocyte injury (WT-1, Nephrin) and inflammatory infiltration of renal tissue (CD68, F4/80 and VCAM-1) were examined respectively. Results: The results showed that inhibiting Cx43 expression by AS in this mouse model of obesity-related renal injury can effectively improve glomerular filtration function, alleviate glomerular expansion and podocyte injury, and attenuate the inflammatory infiltration of renal tissue. Conclusion: Our results demonstrated that inhibiting Cx43 expression by AS could provide renoprotection for the mouse model of obesity-related renal injury.

Energy-efficient routing based on a genetic algorithm for satellite laser communication.

Low earth orbit satellite laser communication has become an important part of communications due to its large capacity and low latency. The lifetime of the satellite mainly depends on the recharge and discharge cycles of the battery. The low earth orbit satellites frequently recharge under sunlight and discharge in the shadow, which leads satellites to age quickly. This paper studies the energy-efficient routing problem for satellite laser communication and builds the satellite ageing model. Based on the model, we propose an energy-efficient routing scheme based on the genetic algorithm. Compared with shortest path routing, the proposed method improves the satellite lifetime by about 300%, and the performances of the network are only slightly degraded, the blocking ratio increases by only 1.2%, and the service delay increases by 1.3 ms.

Rapid Identification Method for CH4/CO/CH4-CO Gas Mixtures Based on Electronic Nose.

The inherent cross-sensitivity of semiconductor gas sensors makes them extremely challenging to accurately detect mixed gases. In order to solve this problem, this paper designed an electronic nose (E-nose) with seven gas sensors and proposed a rapid method for identifying CH4, CO, and their mixtures. Most reported methods for E-nose were based on analyzing the entire response process and employing complex algorithms, such as neural network, which result in long time-consuming processes for gas detection and identification. To overcome these shortcomings, this paper firstly proposes a way to shorten the gas detection time by analyzing only the start stage of the E-nose response instead of the entire response process. Subsequently, two polynomial fitting methods for extracting gas features are designed according to the characteristics of the E-nose response curves. Finally, in order to shorten the time consumption of calculation and reduce the complexity of the identification model, linear discriminant analysis (LDA) is introduced to reduce the dimensionality of the extracted feature datasets, and an XGBoost-based gas identification model is trained using the LDA optimized feature datasets. The experimental results show that the proposed method can shorten the gas detection time, obtain sufficient gas features, and achieve nearly 100% identification accuracy for CH4, CO, and their mixed gases.

Characteristics of Subjective Cognitive Decline Associated with Alzheimer's Disease Amyloid Pathology: Findings from The CABLE Study.

BACKGROUND: Subjective cognitive decline (SCD) is considered as a preclinical hallmark of Alzheimer's disease (AD). However, the characteristics of SCD associated with amyloid pathology remain unclear. OBJECTIVE: We aimed to explore the associations between SCD characteristics with amyloid pathology. METHODS: Using logistic regression analyses, we analyzed the associations between cerebrospinal fluid (CSF) amyloid pathology with AD risk factors, SCD-specific characteristics (onset of SCD within the last five years, age at onset ≥60 years, feelings of worse performance, informant confirmation of complaints, worries, other domains of cognition complaints), as well as subthreshold depressive and anxiety symptoms among individuals with SCD. RESULTS: A total of 535 SCD individuals with available CSF Aß42 information from the Chinese Alzheimer's Biomarker and LifestylE (CABLE) study (mean age of 63.5 years, range 40 to 88 years; 47.10% female) were enrolled. The characteristics of informant confirmation of complaints (OR, 95% CI = 2.00, 1.19-3.36), subthreshold depressive symptoms (OR, 95% CI = 2.31, 1.05-5.09), and subthreshold anxiety symptoms (OR, 95% CI = 2.22, 1.09-4.51) were found to be significantly associated with pathological amyloid in multivariate analyses when adjusting for age, sex, education, and APOE ɛ4. Besides, age and females were observed risks for amyloid pathology in subscale analyses. Nonetheless, we did not find any associations of other SCD-specific characteristics with amyloid pathology in this study. CONCLUSION: Our study suggested that informant confirmed complaints and subthreshold psychiatric symptoms might be critical for discriminating AD-related SCD from non-AD related SCD.