Different correlation between depressive symptoms and sleep duration on weekdays/weekends among adolescents in Taiyuan, North China.

OBJECTIVE: In Chinese adolescents, the co-occurrence of depressive symptoms and short sleep duration constitute a serious public health issue. This study investigates the association between depressive symptoms and sleep duration of Chinese adolescents on weekdays as well as weekends. METHODS: A multistage random cluster selection was utilized to select 2660 adolescents in Taiyuan, China. The survey contents included demographic characteristics, sleep duration, and depressive symptoms. RESULTS: About 41.95 % of students reported depressive symptoms with an average sleep duration of 7.71 ± 0.90 h. After adjusting for covariates, depressive symptoms were found to be positively correlated with sleep duration <6 h (OR = 1.88, 95 % CI: 1.20, 2.95) and 6 ~ h (OR = 1.61, 95 % CI: 1.18, 2.20) on weekdays, and sleep duration <6 h (OR = 2.10, 95 % CI: 1.17, 3.79) and 6 ~ hours (OR = 1.74, 95 % CI: 1.16, 2.62) on weekends compared with a sleep duration of 8 ~ hours. Only on weekdays, sleep duration of 7 ~ hours was positively correlated with depressive symptoms (OR = 1.39, 95%CI: 1.05, 1.84). On weekends, it was not associated with depressive symptoms (OR = 1.06, 95%CI: 0.82, 1.39). In subgroup analyses, female students (OR = 2.88, 1.97, 1.50) and middle school students (OR = 3.50, 2.07, 1.50) were more likely to experience depressive symptoms on weekdays with a sleep duration of <6 h, 6 ~ hours and 7 ~ hours. LIMITATIONS: Sleep duration and depressive symptoms were self-reported measures. CONCLUSION: The study highlights that short sleep duration (< 7 h) increases the risk of depressive symptoms among adolescents regardless of weekdays or weekends. Just on weekdays, the sleep duration of 7 ~ hours was a risk factor for depressive symptoms. Further, gender, grade, and the only-child played significant modification effects between depressive symptoms and sleep duration. To conclude, this study will assist in the effective promotion of the education of adolescents' sleep health.

Knockdown of miR-361-5p promotes the induced activation of SHF-stem cells through FOXM1 mediated Wnt/ß-catenin pathway in cashmere goats.

The inducing activation event of secondary hair follicle (SHF)-stem cells is considered a key biological process in the SHF regeneration, and the morphogenesis of cashmere fiber in cashmere goats. The miR-361-5p was essentially implicated in the induced activation of SHF-stem cells of cashmere goats, but its functional mechanisms are unclear. Here, we confirmed miR-361-5p was significantly downregulated in anagen SHF bugle of cashmere goats compared with that at telogen, and miR-361-5p expression was significantly lower in SHF-stem cells after activation than its counterpart before activation. Further, we found that miR-361-5p could negatively regulate the induced activation event of SHF-stem cells in cashmere goats. Mechanistically, through dual-luciferase reporter assays, miR-361-5p specifically bound with FOXM1 mRNA in SHF-stem cells of cashmere goats and negatively regulated the expression of FOXM1 gene. Also, through overexpression/knockdown analysis of FOXM1 gene, our results indicated that FOXM1 upregulated the expression of Wnt/ß-catenin pathway related genes in SHF-stem cells. Moreover, based on TOP/FOP-flash Wnt report assays, the knockdown of miR-361-5p promotes the Wnt/ß-catenin pathway activation through upregulating the FOXM1 expression in SHF-stem cells. Finally, we demonstrated that miR-361-5p negatively regulated the induced activation of SHF-stem cells through FOXM1 mediated Wnt/ß-catenin pathway in cashmere goats.

Deciphering the impact of greenhouse pesticides on hepatic metabolism profile: Toxicity experiments on HepG2 cells using chlorpyrifos and emamectin benzoate.

Epidemiological evidence on the health effects of pesticide exposure among greenhouse workers is limited, and the mechanisms are lacking. Building upon our team's previous population study, we selected two pesticides, CPF and EB, with high detection rates, based on the theoretical foundation that the liver serves as a detoxifying organ, we constructed a toxicity model using HepG2 cells to investigate the impact of individual or combined pesticide exposure on the hepatic metabolism profile, attempting to identify targeted biomarkers. Our results showed that CPF and EB could significantly affect the survival rate of HepG2 cells and disrupt their metabolic profile. There were 117 metabolites interfered by CPF exposure, which mainly affected ABC transporter, biosynthesis of amino acids, center carbon metabolism in cancer, fatty acid biosynthesis and other pathways, 95 metabolites interfered by EB exposure, which mainly affected center carbon metabolism in cancer, HIF-1 signaling pathway, valine, leucine and isoleucine biosynthesis, fatty acid biosynthesis and other pathways. The cross analysis and further biological experiments confirmed that CPF and EB pesticide exposure may affect the HIF-1 signaling pathway and valine, leucine and isoleucine biosynthesis in HepG2 cells, providing reliable experimental evidence for the prevention and treatment of liver damage in greenhouse workers.

CircERCC6 Positively Regulates the Induced Activation of SHF Stem Cells in Cashmere Goats via the miR-412-3p/BNC2 Axis in an m6A-Dependent Manner.

The cashmere, a kind of nature protein fiber, is one of the main use of cashmere goats. The induced activation of secondary hair follicle (SHF) stem cells by the dermal papilla cell-derived signals is a key biological process for the morphogenesis and growth of cashmere fiber in cashmere goats. Previously, the circRNA-ERCC6 (circERCC6) was identified from cashmere goat SHFs; however, its biological significance is unclear in the SHF physiology process of cashmere goats. In this study, we found that circERCC6 exhibited significantly higher expression at anagen SHF bulge compared with the counterpart of telogen and harbored three m6A modified sites (named m6A-685, m6A-862, and m6A-995) through methylation immunoprecipitation using a real-time quantitative polymerase chain reaction (Me-RIP-qPCR) technique. The knockdown experiments of circERCC6 in SHF stem cells showed that circERCC6 positively regulates the induced activation of SHF stem cells in cashmere goats. Through a dual-luciferase reporter assay, we demonstrated that m6A-modified circERCC6 (m6A-circERCC6) sponged miR-412-3p to upregulate the expression of BNC2 mRNA in SHFstem cells. Through m6A-deficient mutant assay in circERCC6 knockdown SHF stem cells, we further showed that m6A modification within circERCC6 is required to mediate the miR-412-3p/BNC2 axis to finally promote the proper induced activation of SHF stem cells in cashmere goats.

XGBoost-SHAP-based interpretable diagnostic framework for alzheimer's disease.

BACKGROUND: Due to the class imbalance issue faced when Alzheimer's disease (AD) develops from normal cognition (NC) to mild cognitive impairment (MCI), present clinical practice is met with challenges regarding the auxiliary diagnosis of AD using machine learning (ML). This leads to low diagnosis performance. We aimed to construct an interpretable framework, extreme gradient boosting-Shapley additive explanations (XGBoost-SHAP), to handle the imbalance among different AD progression statuses at the algorithmic level. We also sought to achieve multiclassification of NC, MCI, and AD. METHODS: We obtained patient data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, including clinical information, neuropsychological test results, neuroimaging-derived biomarkers, and APOE-ε4 gene statuses. First, three feature selection algorithms were applied, and they were then included in the XGBoost algorithm. Due to the imbalance among the three classes, we changed the sample weight distribution to achieve multiclassification of NC, MCI, and AD. Then, the SHAP method was linked to XGBoost to form an interpretable framework. This framework utilized attribution ideas that quantified the impacts of model predictions into numerical values and analysed them based on their directions and sizes. Subsequently, the top 10 features (optimal subset) were used to simplify the clinical decision-making process, and their performance was compared with that of a random forest (RF), Bagging, AdaBoost, and a naive Bayes (NB) classifier. Finally, the National Alzheimer's Coordinating Center (NACC) dataset was employed to assess the impact path consistency of the features within the optimal subset. RESULTS: Compared to the RF, Bagging, AdaBoost, NB and XGBoost (unweighted), the interpretable framework had higher classification performance with accuracy improvements of 0.74%, 0.74%, 1.46%, 13.18%, and 0.83%, respectively. The framework achieved high sensitivity (81.21%/74.85%), specificity (92.18%/89.86%), accuracy (87.57%/80.52%), area under the receiver operating characteristic curve (AUC) (0.91/0.88), positive clinical utility index (0.71/0.56), and negative clinical utility index (0.75/0.68) on the ADNI and NACC datasets, respectively. In the ADNI dataset, the top 10 features were found to have varying associations with the risk of AD onset based on their SHAP values. Specifically, the higher SHAP values of CDRSB, ADAS13, ADAS11, ventricle volume, ADASQ4, and FAQ were associated with higher risks of AD onset. Conversely, the higher SHAP values of LDELTOTAL, mPACCdigit, RAVLT_immediate, and MMSE were associated with lower risks of AD onset. Similar results were found for the NACC dataset. CONCLUSIONS: The proposed interpretable framework contributes to achieving excellent performance in imbalanced AD multiclassification tasks and provides scientific guidance (optimal subset) for clinical decision-making, thereby facilitating disease management and offering new research ideas for optimizing AD prevention and treatment programs.

Landmark Model-based Individual Dynamic Prediction of Conversion from Mild Cognitive Impairment to Alzheimer's Disease using Cognitive Screening.

BACKGROUND: Identifying individuals with mild cognitive impairment (MCI) who are at increased risk of Alzheimer's Disease (AD) in cognitive screening is important for early diagnosis and prevention of AD. OBJECTIVE: This study aimed at proposing a screening strategy based on landmark models to provide dynamic predictive probabilities of MCI-to-AD conversion according to longitudinal neurocognitive tests. METHODS: Participants were 312 individuals who had MCI at baseline. The longitudinal neurocognitive tests were the Mini-Mental State Examination, Alzheimer Disease Assessment Scale-Cognitive 13 items, Rey Auditory Verbal Learning Test immediate, learning, and forgetting, and Functional Assessment Questionnaire. We constructed three types of landmark models and selected the optimal landmark model to dynamically predict 2-year probabilities of conversion. The dataset was randomly divided into training set and validation set at a ratio of 7:3. RESULTS: The FAQ, RAVLT-immediate, and RAVLT-forgetting were significant longitudinal neurocognitive tests for MCI-to-AD conversion in all three landmark models. We considered Model 3 as the final landmark model (C-index = 0.894, Brier score = 0.040) and selected Model 3c (FAQ and RAVLT-forgetting as neurocognitive tests) as the optimal landmark model (C-index = 0.898, Brier score = 0.027). CONCLUSION: Our study shows that the optimal landmark model with a combination FAQ and RAVLTforgetting is feasible to identify the risk of MCI-to-AD conversion, which can be implemented in cognitive screening.

Evaluating the effect of gestational diabetes mellitus on macrosomia based on the characteristics of oral glucose tolerance test.

BACKGROUND: GDM is always treated as a homogenous disease ignoring the different metabolic characteristics in oral glucose tolerance test (OGTT). We assessed the effect of GDM on macrosomia based on the different characteristics of OGTT. METHODS: We retrospectively divided 998 GDM pregnant women into 7 groups, Group A1: abnormal OGTT0h; Group A2: abnormal OGTT1h; Group A3: abnormal OGTT2h; Group B1: abnormal OGTT0h+1h; Group B2: abnormal OGTT0h+2h; Group B3: abnormal OGTT1h+2h; Group C: abnormal OGTT0h+1h+2h. RESULTS: The incidence of macrosomia in group C (21.92%) was higher than other groups. The OR of OGTT0h+1h+2h was significant (OGTT1h: OR = 1.577, 95% CI: 0.791, 3.145; OGTT2h: OR = 1.151, 95% CI: 0.572, 2.313; OGTT0h+1h: OR = 1.346, 95% CI: 0.584, 3.101; OGTT0h+2h: OR = 1.327, 95% CI: 0.517, 3.409; OGTT1h+2h: OR = 0.771, 95% CI: 0.256, 2.322; OGTT0h+1h+2h: OR = 4.164, 95% CI: 2.095, 8.278) when comparing with OGTT0h. Subgroup analysis showed abnormal OGTT0h+1h+2h might contribute more to macrosomia in pre-pregnancy BMI ≥ 24 kg/m2 than those with BMI < 24 kg/m2. CONCLUSION: The effect of abnormal OGTT0h+1h+2h on macrosomia was significantly greater than other OGTT characteristics, especially for those with pre-pregnancy BMI ≥ 24 kg/m2. Individualized management of GDM based on OGTT characteristics and pre-pregnancy BMI might be needed.

Photonic super-resolution millimeter-wave joint radar-communication system using self-coherent detection.

A millimeter-wave (MMW) joint radar-communication (JRC) system with super-resolution is proposed and experimentally demonstrated, using optical heterodyne upconversion and self-coherent detection downconversion techniques. The point lies in the designed coherent dual-band constant envelope linear frequency modulation-orthogonal frequency division multiplexing (LFM-OFDM) signal with opposite phase modulation indexes for the JRC system. Then the self-coherent detection, as a simple and low-cost means, is accordingly facilitated for both de-chirping of MMW radar and frequency downconversion reception of MMW communication, which circumvents costly high-speed mixers along with MMW local oscillators and, more significantly, achieves the real-time decomposition of radar and communication information. Furthermore, a super-resolution radar range profile is realized through the coherent fusion processing of dual-band JRC signals. In experiments, a dual-band LFM-OFDM JRC signal centered at 54 GHz and 61 GHz is generated. The two bands feature an identical instantaneous bandwidth of 2 GHz and carry an OFDM signal of 1 Gbaud, which helps to achieve a 6-Gbit/s data rate for communication and a 1.76-cm range resolution for radar.

Discovery and Functional Analysis of Secondary Hair Follicle miRNAs during Annual Cashmere Growth.

Secondary hair follicles (SHFs) produce the thermoregulatory cashmere of goats. MicroRNAs (miRNAs) play indispensable roles in hair follicle formation and growth. However, most studies examining miRNAs related to cashmere have been performed on goat skin. It remains unclear which miRNAs are highly expressed in SHFs or how miRNAs affect cashmere growth. In the present study, we isolated the SHFs under a dissecting microscope and analyzed the miRNA signatures during annual cashmere growth. Small-RNA sequencing followed by genome-wide expression analysis revealed that early anagen is a crucial phase for miRNA regulation of the cashmere growth, as revealed by two predominant groups of miRNAs. Although they exhibited opposite expression patterns, both groups demonstrated sharp changes of expression when in transit from early anagen to mid-anagen. In addition, we identified 96 miRNA signatures that were differentially expressed between different phases among 376 miRNAs. Functional analysis of the predicted target genes of highly expressed or differentially expressed miRNAs indicated that these miRNAs were involved in signal pathways associated with SHF development, regeneration, and regression. Furthermore, miR-143-3p was preferentially expressed in SHFs and Itga6 was identified as one of targets. The dual-luciferase and in situ hybridization assay demonstrated that miR-143-3p directly repressed the expression of Itga6, suggesting a possible novel role for miR-143-3p in cashmere growth.

Analysis of m6A methylation in skin tissues of different sex Liaoning cashmere goats.

N6-methyladenosine (m6A) is the most frequent internal modification of mRNA and lncRNA in eukaryotes. We used two high-throughput sequencing method, m6A-seq and RNA-seq to identify pivotal m6A-modified genes in cashmere fineness and fiber growth. 8062 m6A peaks were detected by m6A-seq, including 2157 upregulated and 6445 downregulated. Furthermore, by comparing m6A-modified genes of the male Liaoning Cashmere Goat (M-LCG) and female Liaoning Cashmere Goat (F-LCG) skin tissues, we get 862 differentially expressed m6A-modified genes. To identify differently expressed m6A genes associated with cashmere fineness, 11 genes were selected for validation using real time fluorescent quantitative PCR in M-LCG and F-LCG. This study provides an acadamic basis on the molecular regulation mechanism of m6A modification in cashmere growth process.

CircRNA-1967 participates in the differentiation of goat SHF-SCs into hair follicle lineage by sponging miR-93-3p to enhance LEF1 expression.

Circular RNAs (circRNAs), a novel class of non-coding RNAs, can interact with miRNAs through a sequence-driven sponge mechanism, thereby regulating the expression of their downstream target genes. CircRNA-1967 was found in secondary hair follicles (SHFs) of cashmere goats, but its functions are not clear. Here, we showed that both circRNA-1967 and its host gene BNC2 had significantly higher expression in SHF bulge at anagen than those at telogen of cashmere goats. Also, circRNA-1967 participates in the differentiation of SHF stem cells (SHF-SCs) into hair follicle lineage in cashmere goats. RNA pull-down assay verified that circRNA-1967 interacts with miR-93-3p. We also indicated that circRNA-1967 promoted LEF1 expression in SHF-SCs of cashmere goats. By dual-luciferase reporter analysis, we found that circRNA-1967 up-regulated LEF1 expression through the miR-93-3p-mediated pathway. The results from this study demonstrated that circRNA-1967 participated in the differentiation of goat SHF-SCs into hair follicle lineage by sponging miR-93-3p to enhance LEF1 expression. Our founding might constitute a novel pathway for revealing the potential mechanism of the differentiation of SHF-SCs into hair follicle lineage in cashmere goats. Also, these results provided a valuable basis for further enhancing the intrinsic regeneration of cashmere goat SHFs with the formation and growth of cashmere fibers.

The role of the gut microbiota in depressive-like behavior induced by chlorpyrifos in mice.

Chlorpyrifos (CPF) is associated with depression, cognitive dysfunction, and other neurological disorders. Increasing evidence has suggested that the gut microbiota plays a vital role in regulating the development of depression. However, it is unknown whether gut microbiota is associated with CPF-related depression. This study aimed to explore the effect of CPF on depressive-like behavior in mice and investigated the role of gut microbiota in this behavior. In our study, we selected fifty male C57BL/6 J mice for the model and subjected them to CPF poisoning by gavage for 14 days. The depressive-like behaviors of mice were assessed by the open field test (OFT), sucrose preference test (SPT), and forced swimming test (FST). Furthermore, we selected the high-dose group (CPF10) with obvious changes in depressive-like behaviors for the hippocampus and colon histopathological analysis, examined the changes in the gut microbiota by 16 S rRNA sequencing, screened the different microbiota among groups by linear discriminant analysis effect size (LEfSe), analyzed the correlation between intestinal bacteria and depression-like behavior indicators by Spearman analysis, and evaluated the predictive ability of different bacteria to CPF-induced depressive-like behavior using the receiver operator characteristic (ROC) curve. The results showed that CPF caused depressive-like behaviors with pathological changes in the hippocampus and colon. CPF induced changes in gut microbiota, including 49 differential bacteria. Among the top 10 abundant bacteria, Actinobacteria and Deferribacteres were increased, and Cyanobacteria, Patescibacteria and Verrucomicrobia were decreased at the phylum level. Muribaculum, Ruminococcaceae.UCG.014 and uncultured Bacteroides bacterium were decreased at the genus level. Correlation analysis demonstrated that 18 differentially abundant bacteria were correlated with CPF-induced depression. ROC curves revealed that Deferribacteres, Mucispirillum, Rikenella and GCA900066575 are potential biomarkers for depression caused by CPF. These findings will provide an experimental basis for the neurological health of the pesticide-exposed population.

N6-Methyladenosine modification (m6A) of circRNA-ZNF638 contributes to the induced activation of SHF stem cells through miR-361-5p/Wnt5a axis in cashmere goats.

OBJECTIVE: The objective of this study was to investigate the effects of N6-Methyladenosine modification-circRNA-zinc finger protein 638 (m6A-circRNA-ZNF638) on the induced activation of secondary hair follicle (SHF) stem cells with its potential mechanisms in cashmere goats. METHODS: The m6A modification of ZNF638 was analyzed using methylation immunoprecipitation with real-time quantitative polymerase chain reaction technique in SHF stem cells. The effects of circRNA-ZNF638 on the induced activation of SHF stem cells in m6A dependence were evaluated through the overexpression of circRNA-ZNF638/its m6Adeficient mutants in circRNA-ZNF638 knockdown SHF stem cells. The competitive binding of miR-361-5p to circRNA-ZNF638/Wnt5a 3'- untranslated region was analyzed through Dual-luciferase reporter assay. RESULTS: The m6A-circRNA-ZNF638 had significantly higher transcription at anagen SHF bulge of cashmere goats compared with that at telogen, as well as it positively regulated the induced activation of SHF-stem cells in cashmere goats. Mechanismly, m6A-circRNA-ZNF638 sponged miR-361-5p to heighten the transcriptional expression of Wnt5a gene in SHFstem cells. We further demonstrated that the internal m6A modification within circRNAZNF638 is required for mediating the miR-361-5p/Wnt5a pathway to regulate the induced activation of SHF stem cells through an introducing of m6A-deficient mutant of circRNAZNF638. CONCLUSION: The circRNA-ZNF638 contributes the proper induced activation of SHF-stem cells in cashmere goats in m6A-dependent manner through miR-361-5p/Wnt5a axis.

Estimating Bidirectional Transitions and Identifying Predictors of Mild Cognitive Impairment.

BACKGROUND AND OBJECTIVES: Various resources exist for treating mild cognitive impairment (MCI) or dementia separately as terminal events or for focusing solely on a 1-way path from MCI to dementia without taking into account heterogeneous transitions. Little is known about the trajectory of reversion from MCI to normal cognition (NC) or near-NC and patterns of postreversion, which refers to cognitive trajectories of patients who have reversed from MCI to NC. Our objectives were to (1) quantitatively predict bidirectional transitions of MCI (reversion and progression), (2) explore patterns of future cognitive trajectories for postreversion, and (3) estimate the effects of demographic characteristics, APOE, cognition, daily activity ability, depression, and neuropsychiatric symptoms on transition probabilities. METHODS: We constructed a retrospective cohort by reviewing patients with an MCI diagnosis at study entry and at least 2 follow-up visits between June 2005 and February 2021. Defining NC or near-NC and MCI as transient states and dementia as an absorbing state, we used continuous-time multistate Markov models to estimate instantaneous transition intensity between states, transition probabilities from one state to another at any given time during follow-up, and hazard ratios of reversion-related variables. RESULTS: Among 24,220 observations from 6,651 participants, there were 2,729 transitions to dementia and 1,785 reversions. As for postreversion, there were 630 and 73 transitions of progression to MCI and dementia, respectively. The transition intensity of progression to MCI for postreversion was 0.317 (2.48-fold greater than that for MCI progression or reversion). For postreversion participants, the probability of progressing to dementia increased by 2% yearly. Participants who progressed to MCI were likely to reverse again (probability of 40% over 15 years). Age, independence level, APOE, cognition, daily activity ability, depression, and neuropsychiatric symptoms were significant predictors of bidirectional transitions. DISCUSSION: The nature of bidirectional transitions cannot be ignored in multidimensional MCI research. We found that postreversion participants remained at an increased risk of progression to MCI or dementia over the longer term and experienced recurrent reversions. Our findings may serve as a valuable reference for future research and enable health care professionals to better develop proactive management plans and targeted interventions.

The mediating effects of depression, anxiety, and rapid eye movement sleep behavior disorder on the association between dopaminergic replacement therapy and impulse control disorders in Parkinson's disease.

OBJECTIVES: This study aims to longitudinally explore whether and how rapid eye movement sleep behavior disorder (RBD), depression, and anxiety mediate the association between dopaminergic replacement therapy (DRT) and impulse control disorders (ICDs) in patients with Parkinson's disease (PD). METHODS: Subjects were selected from the Parkinson's Progression Markers Initiative. After excluding missing data, 268, 223, 218, 238, and 219 patients with PD diagnosed at 12, 24, 36, 48, and 60 months prior, respectively, were included. We used the Questionnaire for Impulsive-Compulsive Disorders, RBD Screening Questionnaire, Geriatric Depression Scale, and State-Trait-Anxiety Inventory to assess ICBs, RBD, depression, and anxiety, respectively. We constructed three causal mediation analysis models to infer potential contingent pathways from DRT to ICD mediated by depression, anxiety, and RBD separately. RESULTS: DRT was associated with an increased risk of PD incidence. Aggravation of ICDs was partly explained by improvements in depression (the average causal mediation effect accounted for 8.0% of the total effect) and RBD (the average causal mediation effect of RBD accounted for 16.4% of the total effect). This suggested that anxiety (the average causal mediation effect accounted for 12.7% of the total effect) plays a mediating role. CONCLUSIONS: Focusing on changes in RBD, depression, and anxiety associated with hyperdopaminergic status should be an essential part of strategies to prevent ICDs in patients with Parkinson's disease.

Digitized radio-over-fiber transmission based on probabilistic quantization codeword shaping.

To improve the receiver sensitivity of the digitized radio-over-fiber (DRoF) transmission system, a vector quantization scheme based on probabilistic quantization codeword shaping (PQCS) is proposed. The PQCS performs quantization bits (QBs) rematching on the original codebook to optimize the proportion distribution of level '0' and level '2' in 4-Pulse Amplitude Modulation (PAM-4) for improving system sensitivity. A 16-Quadrature Amplitude Modulation (16-QAM) DRoF transmission system using intensity-modulation/direct-detection is employed to experimentally verify the proposed scheme. The experimental results indicate that, compared to the traditional vector quantization scheme, the PQCS method offers 1.45 dB shaping gain for system sensitivity at a bit error rate (BER) of 5 × 10-4. Nevertheless, the error vector magnitude (EVM) can be obtained below 2% when 6 and 7 QBs are adopted for 64-QAM and 256-QAM, respectively.

Millimeter-wave joint radar and communication system based on photonic frequency-multiplying constant envelope LFM-OFDM.

The joint radar and communication (JRC) system providing both large-capacity transmission and high-resolution ranging will play a pivotal role in the next-generation wireless networks (e.g., 6G and beyond) and defense applications. Here, we propose and experimentally demonstrate a novel photonics-assisted millimeter-wave (mm-wave) JRC system with a multi-Gbit/s data rate for communication function and centimeter-level range resolution for radar function. The key is the design of the intermediate-frequency (IF) JRC signal through the angle modulation of the linear frequency modulation (LFM) radar carrier using orthogonal frequency division multiplexing (OFDM) communication signal, inspired by the idea of constant-envelope OFDM (CE-OFDM). This IF angle-modulated waveform facilitates the broadband photonic frequency (phase)-multiplying scheme to generate mm-wave JRC signal with multiplied instantaneous bandwidth and phase modulation index for high-resolution LFM radar and noise-robust CE-OFDM communication. It is with fixed low power-to-average power ratio to render robustness against the nonlinear distortions. In proof-of-concept experiments, a 60-GHz JRC signal with an instantaneous bandwidth over 10-GHz is synthesized through a CE-LFM-OFDM signal encoded with a 2-GBaud 16-QAM OFDM signal. Consequently, a 1.5-cm range resolution of two-dimension imaging and an 8-Gbit/s data rate are achieved for both radar and communication functions, respectively. Furthermore, the proposed JRC system is able to achieve higher radar range resolution and better anti-noise communication, when using higher-order photonic frequency multiplying.

RoF distributed antenna architecture and reinforcement learning empowered real-time EMI immunity for highly reliable railway communication: publisher's note.

The publisher's note contains a correction to [Opt. Express2932333 (2021)10.1364/OE.438439]. The article was corrected on 17 June 2022.

Longitudinal Mediating Effect of Depression on the Relationship between Excessive Daytime Sleepiness and Activities of Daily Living in Parkinson's Disease.

OBJECTIVES: Whether depression affects activities of daily living (ADLs) in patients with Parkinson's disease (PD) via excessive daytime sleepiness (EDS) remains unclear; moreover, few longitudinal studies have been conducted. METHODS: We recruited 421 patients from the Parkinson's Progression Markers Initiative. We constructed a latent growth mediation model to explore the longitudinal mediating effect of depression on the relationship between EDS and ADLs. RESULTS: EDS (p < .001) and depression scores (p < .001) both increased, and ADL scores (p < .001) decreased. Moreover, EDS was positively correlated with depression, whereas an increase in EDS significantly reduced ADLs. The initial value (95% confidence interval [CI]: 0.026, 0.154) and the rate of change (95% CI: 0.138, 0.514) of self-reported depression measured using the Geriatric Depression Scale(GDS) partially mediated the association between EDS and ADL score. CONCLUSIONS: The indirect effect of the longitudinal changes of depression on the relationship between EDS and ADLs highlights the importance of depression changes in PD patients with EDS. CLINICAL IMPLICATIONS: Depression should be considered a mediator by clinicians; preventing the worsening of depression is essential for improving ADLs in patients with PD, especially those with EDS.

A Stacking Framework for Multi-Classification of Alzheimer's Disease Using Neuroimaging and Clinical Features.

BACKGROUND: Alzheimer's disease (AD) is a severe health problem. Challenges still remain in early diagnosis. OBJECTIVE: The objective of this study was to build a Stacking framework for multi-classification of AD by a combination of neuroimaging and clinical features to improve the performance. METHODS: The data we used were from the Alzheimer's Disease Neuroimaging Initiative database with a total of 493 subjects, including 125 normal control (NC), 121 early mild cognitive impairment, 109 late mild cognitive impairment (LMCI), and 138 AD. We selected structural magnetic resonance imaging (sMRI) feature by voting strategy. The imaging feature, demographic information, Mini-Mental State Examination, and Alzheimer's Disease Assessment Scale-Cognitive Subscale were combined together as classification features. We proposed a two-layer Stacking ensemble framework to classify four types of people. The first layer represented support vector machine, random forest, adaptive boosting, and gradient boosting decision tree; the second layer was a logistic regression classifier. Additionally, we analyzed performance of only sMRI feature and combined features and compared the proposed model with four base classifiers. RESULTS: The Stacking model combined with sMRI and non-imaging features outshined four base classifiers with an average accuracy of 86.96%. Compared with using sMRI data alone, sMRI combined with non-imaging features significantly improved diagnostic accuracy, especially in NC versus LMCI. CONCLUSION: The Stacking framework we used can improve performance in diagnosis of AD using combined features.