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Internet addiction (IA) refers to excessive internet use that causes cognitive impairment or distress. Understanding the neurophysiological mechanisms underpinning IA is crucial for enabling an accurate diagnosis and informing treatment and prevention strategies. Despite the recent increase in studies examining the neurophysiological traits of IA, their findings often vary. To enhance the accuracy of identifying key neurophysiological characteristics of IA, this study used the phase lag index (PLI) and weighted PLI (WPLI) methods, which minimize volume conduction effects, to analyze the resting-state electroencephalography (EEG) functional connectivity. We further evaluated the reliability of the identified features for IA classification using various machine learning methods.
Methods
Ninety-two participants (42 with IA and 50 healthy controls (HCs)) were included. PLI and WPLI values for each participant were computed, and values exhibiting significant differences between the two groups were selected as features for the subsequent classification task.
Results
Support vector machine (SVM) achieved an 83% accuracy rate using PLI features and an improved 86% accuracy rate using WPLI features. t-test results showed analogous topographical patterns for both the WPLI and PLI. Numerous connections were identified within the delta and gamma frequency bands that exhibited significant differences between the two groups, with the IA group manifesting an elevated level of phase synchronization.
Conclusions
Functional connectivity analysis and machine learning algorithms can jointly distinguish participants with IA from HCs based on EEG data. PLI and WPLI have substantial potential as biomarkers for identifying the neurophysiological traits of IA.
As avionics systems become increasingly complex, traditional fault prediction methods are no longer sufficient to meet modern demands. This paper introduces four advanced fault prediction methods for avionics components, utilising a multi-step prediction strategy combined with a stacking regressor. By selecting various standard regression models as base regressors, these base regressors are first trained on the original data, and their predictions are subsequently used as input features for training a meta-regressor. Additionally, the Tree-structured Parzen Estimator (TPE) algorithm is employed for hyperparameter optimisation. The experimental results demonstrate that the proposed stacking regression methods exhibit superior accuracy in fault prediction compared to traditional single-model approaches.
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
Purple nutsedge (Cyperus rotundus L.) is one of the world’s resilient upland weeds, primarily spreading through its tubers. Its emergence in rice (Oryza sativa L.) fields has been increasing, likely due to changing paddy-farming practices. This study aimed to investigate how C. rotundus, an upland weed, can withstand soil flooding and become a problematic weed in rice fields. The first comparative analysis focused on the survival and recovery characteristics of growing and mature tubers of C. rotundus exposed to soil-flooding conditions. Notably, mature tubers exhibited significant survival and recovery abilities in these environments. Based on this observation, further investigation was carried out to explore the morphological structure, nonstructural carbohydrates, and respiratory mechanisms of mature tubers in response to prolonged soil flooding. Over time, the mature tubers did not form aerenchyma but instead gradually accumulated lignified sclerenchymal fibers, with lignin content also increasing. After 90 d, the lignified sclerenchymal fibers and lignin contents were 4.0 and 1.1 times higher than those in the no soil-flooding treatment. Concurrently, soluble sugar content decreased while starch content increased, providing energy storage, and alcohol dehydrogenase activity rose to support anaerobic respiration via alcohol fermentation. These results indicated that mature tubers survived in soil-flooding conditions by adopting a low-oxygen quiescence strategy, which involves morphological adaptations through the development of lignified sclerenchymal fibers, increased starch reserves for energy storage, and enhanced anaerobic respiration. This mechanism likely underpins the flooding tolerance of mature C. rotundus tubers, allowing them to endure unfavorable conditions and subsequently germinate and grow once flooding subsides. This study provides a preliminary explanation of the mechanism by which mature tubers of C. rotundus from the upland areas confer flooding tolerance, shedding light on the reasons behind this weed’s increasing presence in rice fields.
This study proposes a novel super-resolution (or SR) framework for generating high-resolution turbulent boundary layer (TBL) flow from low-resolution inputs. The framework combines a super-resolution generative adversarial neural network (SRGAN) with down-sampling modules (DMs), integrating the residual of the continuity equation into the loss function. The DMs selectively filter out components with excessive energy dissipation in low-resolution fields prior to the super-resolution process. The framework iteratively applies the SRGAN and DM procedure to fully capture the energy cascade of multi-scale flow structures, collectively termed the SRGAN-based energy cascade reconstruction framework (EC-SRGAN). Despite being trained solely on turbulent channel flow data (via ‘zero-shot transfer’), EC-SRGAN exhibits remarkable generalization in predicting TBL small-scale velocity fields, accurately reproducing wavenumber spectra compared to direct numerical simulation (DNS) results. Furthermore, a super-resolution core is trained at a specific super-resolution ratio. By leveraging this pretrained super-resolution core, EC-SRGAN efficiently reconstructs TBL fields at multiple super-resolution ratios from various levels of low-resolution inputs, showcasing strong flexibility. By learning turbulent scale invariance, EC-SRGAN demonstrates robustness across different TBL datasets. These results underscore the potential of EC-SRGAN for generating and predicting wall turbulence with high flexibility, offering promising applications in addressing diverse TBL-related challenges.
Despite observed ethnic differences in eating patterns and obesity, evidence in China is limited. This study examined ethnic differences in eating patterns and their associations with weight outcomes among multi-ethnic adults in West China. A cross-sectional survey collected self-reported data on demographics, eating behaviours, weight and height in 2021. Principal component analysis and multivariate regression were conducted to identify eating patterns and examine their associations with weight outcomes. In total, 4407 subjects aged ≥ 18 years were recruited across seven provinces in West China. Four eating patterns were identified: ‘meat-lover’ – characterised by frequent consumption of meat and dairy products, ‘indulgent’ – by frequent intakes of added salt, sugar, alcohol and pickled food, ‘diversified-eating’ – by frequently consuming food with diversified cooking methods and eating out and ‘nutri-health-concerned’ – by good food hygiene behaviours and reading food labels. Ethnic differences in eating patterns were observed. Compared with Han, Hui were less likely to exhibit meat-lover or diversified-eating patterns; Tibetans were less likely to have meat-lover or nutri-health-concerned patterns; Mongolians were more likely to have indulgent pattern. BMI was positively associated with meat-lover pattern in both genders (exp(β): 1·029; 95 % CI: 1·001, 1·058 for men; 1·018; 1·000, 1·036 for women) and negatively associated with nutri-health-concerned pattern in women (0·983; 0·966, 1·000). Mongolians were two times more likely to be overweight/obese than Han (OR: 3·126; 1·688, 5·790). Considerable ethnic differences existed in eating patterns in West China. Mongolians were more likely to be overweight/obese, which was associated with their indulgent eating patterns. Ethnic-specific healthy eating intervention programs are needed.
Aphids exhibit seasonally alternating asexual and sexual reproductive modes. Different morphs are produced throughout the life cycle. To evaluate morph-specific fitness during reproductive switching, holocyclic Sitobion avenae were induced continuously under short light conditions, and development and reproduction were compared in each morph. Seven morphs, including apterous and alate virginoparae, apterous and alate sexuparae, oviparae, males, and fundatrices, were produced during the life cycle. The greatest proportions of sexuparae, oviparae, males, and virginoparae were in the G1, G2, G3, and G4 generations, respectively. Regardless of asexual or sexual morphs, alate morphs exhibited a marked delay in age at maturity compared with that of apterous morphs. Among the alate morphs, males had the longest age at maturity, followed by sexuparae and virginoparae. Among the apterous morphs, sexuparae were older at maturity than the fundatrices, virginoparae, and oviparae. The nymphs of each morph had equal survival potentials. For the same wing morphs, apterous sexuparae and oviparae exhibited substantial delays in the pre-reproductive period and considerable reductions in fecundity, compared with those of apterous virginoparae and fundatrices, whereas alate sexuparae and alate virginoparae had similar fecundity. The seven morphs exhibited Deevey I survivorship throughout the life cycle. These results suggest that sexual production, particularly in males, has short-term development and reproduction costs. The coexistence of sexual and asexual morphs in sexuparae offspring may be regarded as an adaptive strategy for limiting the risk of low fitness in winter.
Breast cancer is a high-risk disease with a high mortality rate among women. Chemotherapy plays an important role in the treatment of breast cancer. However, chemotherapy eventually results in tumours that are resistant to drugs. In recent years, many studies have revealed that the activation of Wnt/β-catenin signalling is crucial for the emergence and growth of breast tumours as well as the development of drug resistance. Additionally, drugs that target this pathway can reverse drug resistance in breast cancer therapy. Traditional Chinese medicine has the properties of multi-target and tenderness. Therefore, integrating traditional Chinese medicine and modern medicine into chemotherapy provides a new strategy for reversing the drug resistance of breast tumours. This paper mainly reviews the possible mechanism of Wnt/β-catenin in promoting the process of breast tumour drug resistance, and the progress of alkaloids extracted from traditional Chinese medicine in the targeting of this pathway in order to reverse the drug resistance of breast cancer.
Straightplasma channels are widely used to guide relativistic intense laser pulses over several Rayleigh lengths for laser wakefield acceleration. Recently, a curved plasma channel with gradually varied curvature was suggested to guide a fresh intense laser pulse and merge it into a straight channel for staged wakefield acceleration [Phys. Rev. Lett. 120, 154801 (2018)]. In this work, we report the generation of such a curved plasma channel from a discharged capillary. Both longitudinal and transverse density distributions of the plasma inside the channel were diagnosed by analyzing the discharging spectroscopy. Effects of the gas-filling mode, back pressure and discharging voltage on the plasma density distribution inside the specially designed capillary are studied. Experiments show that a longitudinally uniform and transversely parabolic plasma channel with a maximum channel depth of 47.5 μm and length of 3 cm can be produced, which is temporally stable enough for laser guiding. Using such a plasma channel, a laser pulse with duration of 30 fs has been successfully guided along the channel with the propagation direction bent by 10.4°.
The purpose of this study was to analyse the clinical characteristics of patients with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) PCR re-positivity after recovering from coronavirus disease 2019 (COVID-19). Patients (n = 1391) from Guangzhou, China, who had recovered from COVID-19 were recruited between 7 September 2021 and 11 March 2022. Data on epidemiology, symptoms, laboratory test results and treatment were analysed. In this study, 42.7% of recovered patients had re-positive result. Most re-positive patients were asymptomatic, did not have severe comorbidities, and were not contagious. The re-positivity rate was 39%, 46%, 11% and 25% in patients who had received inactivated, mRNA, adenovirus vector and recombinant subunit vaccines, respectively. Seven independent risk factors for testing re-positive were identified, and a predictive model was constructed using these variables. The predictors of re-positivity were COVID-19 vaccination status, previous SARs-CoV-12 infection prior to the most recent episode, renal function, SARS-CoV-2 IgG and IgM antibody levels and white blood cell count. The predictive model could benefit the control of the spread of COVID-19.
According to Hamilton's rule, matrilineal-biased investment restrains men in matrilineal societies from maximising their inclusive fitness (the ‘matrilineal puzzle'). A recent hypothesis argues that when women breed communally and share household resources, a man should help his sisters' household, rather than his wife's household, as investment to the later but not the former would be diluted by other unrelated members (Wu et al., 2013). According to this hypothesis, a man is less likely to help on his wife's farm when there are more women reproducing in the wife's household, because on average he would be less related to his wife's household. We used a farm-work observational dataset, that we collected in the matrilineal Mosuo in southwest China, to test this hypothesis. As predicted, high levels of communal breeding by women in his wife's households do predict less effort spent by men on their wife's farm, and communal breeding in men's natal households do not affect whether men help on their natal farms. Thus, communal breeding by women dilutes the inclusive fitness benefits men receive from investment to their wife and children, and may drive the evolution of matrilineal-biased investment by men. These results can help solve the ‘matrilineal puzzle'.
In this study, we report the first complete mitochondrial genome of the tapeworm Nippotaenia mogurndae in the order Nippotaeniidea Yamaguti, 1939. This mitogenome, which is 14,307 base pairs (bp) long with an A + T content of 72.2%, consists of 12 protein-coding genes, 22 transfer RNA (tRNA) genes, two rRNA genes, and two non-coding regions. Most tRNAs have a conventional cloverleaf structure, but trnS1 and trnR lack dihydrouridine arms of tRNA. The two largest non-coding regions, NCR1 (220 bp) and NCR2 (817 bp), are located between trnY and trnS2 and between nad5 and trnG, respectively. Phylogenetic analyses of mitogenomic data indicate that N. mogurndae is closely related to tapeworms in the order Cyclophyllidea.
We present a self-biased three-stage GaN-based monolithic microwave integrated circuit low-noise amplifier (LNA) operating between 26 and 29 GHz for 5G mobile communications. The self-biasing circuit, common-source topology with inductive source feedback, and RLC negative feedback loops between gate and drain of the third transistor were implemented to achieve low noise, good port match, high stability, high gain, and compact size. Measurement results show that the LNA has a high and flat gain of 30.5 ± 0.4 dB with noise figure (NF) of 1.65–1.8 dB across the band. The three-stage topology also achieves high linearity, providing the 1 dB compression point output power (P1dB) of 21 dBm in the band. To our knowledge, this combination of NF, gain, and linearity performance represents the state of art of self-biased LNA in this frequency band.
This study aimed to investigate the relationship between depression in older nursing home residents and family caregivers’ (FCGs) depressive status and reasons for involvement with residents.
Design:
This study employed a cross-sectional design.
Setting:
Eight nursing homes in northern Taiwan.
Participants:
A total of 139 older resident–FCG pairs were recruited.
Measurements:
Depression was measured with the Geriatric Depression Scale-Short Form for nursing home residents and the Center for Epidemiologic Studies Depression Scale-Short Form for family members. Depression and demographic data were collected with face-to-face interviews. The meaning ascribed to caregivers’ nursing home visits was calibrated using the Family Meaning of Nursing-Home Visits scale. Multiple logistic regression was used to understand the factors related to residents’ depressive symptoms.
Results:
Depressive symptoms were present in 58.3% of the nursing home residents (n = 81). Depressive status of family members (Chi-square = 1.46, p = 0.23) or family’s visiting frequency (Chi-square = 1.64, p = 0.44) did not differ between residents with or without depressive symptoms. Factors associated with an increased risk of residents having depressive symptoms were age, self-perceived health status, and having a caregiver motivated to visit to assuage their guilt.
Conclusions:
Visiting a family member to assuage their guilt was the only caregiver variable associated with depressive symptoms for nursing home residents. This finding suggests that developing interventions to improve personal relationships between nursing home residents and family members might facilitate the emotional support of caregivers and psychological support for older nursing home residents in Taiwan.
Gut microbiome and dietary patterns have been suggested to be associated with depression/anxiety. However, limited effort has been made to explore the effects of possible interactions between diet and microbiome on the risks of depression and anxiety.
Methods
Using the latest genome-wide association studies findings in gut microbiome and dietary habits, polygenic risk scores (PRSs) analysis of gut microbiome and dietary habits was conducted in the UK Biobank cohort. Logistic/linear regression models were applied for evaluating the associations for gut microbiome-PRS, dietary habits-PRS, and their interactions with depression/anxiety status and Patient Health Questionnaire (PHQ-9)/Generalized Anxiety Disorder-7 (GAD-7) score by R software.
Results
We observed 51 common diet–gut microbiome interactions shared by both PHQ score and depression status, such as overall beef intake × genus Sporobacter [hurdle binary (HB)] (PPHQ = 7.88 × 10−4, Pdepression status = 5.86 × 10−4); carbohydrate × genus Lactococcus (HB) (PPHQ = 0.0295, Pdepression status = 0.0150). We detected 41 common diet–gut microbiome interactions shared by GAD score and anxiety status, such as sugar × genus Parasutterella (rank normal transformed) (PGAD = 5.15 × 10−3, Panxiety status = 0.0347); tablespoons of raw vegetables per day × family Coriobacteriaceae (HB) (PGAD = 6.02 × 10−4, Panxiety status = 0.0345). Some common significant interactions shared by depression and anxiety were identified, such as overall beef intake × genus Sporobacter (HB).
Conclusions
Our study results expanded our understanding of how to comprehensively consider the relationships for dietary habits–gut microbiome interactions with depression and anxiety.
We investigated the effects of botulinum toxin on gait in Parkinson’s disease (PD) patients with foot dystonia. Six patients underwent onabotulinum toxin A injection and were assessed by Burke–Fahn–Marsden Dystonia Rating Scale (BFMDRS), visual analog scale (VAS) of pain, Timed Up and Go (TUG), Berg Balance Test (BBT), and 3D gait analysis at baseline, 1 month, and 3 months. BFMDRS (p = 0.002), VAS (p = 0.024), TUG (p = 0.028), and BBT (p = 0.034) were improved. Foot pressures at Toe 1 (p = 0.028) and Midfoot (p = 0.018) were reduced, indicating botulinum toxin’s effects in alleviating the dystonia severity and pain and improving foot pressures during walking in PD.
The objective of this study was to analyze differences in birth weight and overweight/obesity in a Shanghai twin cohort. We also wanted to study their association and explore possible risk factors for the discordance of overweight/obesity within twins. This was an internal case–control study designed for twins. The 2012 Shanghai Twin Registration System baseline survey data of a total of 3417 twin pairs were statistically analyzed using SPSS22 software. Results show that the body mass index (BMI) of the Shanghai twin population increased with age. Twins with a high birth weight had a higher BMI and a higher rate of overweight and obesity; 0- to 6-year-old twins, male twins and dizygotic (DZ) twins had higher rates of overweight/obesity than other groups. The greater the discordant birth weight rate of twins, the more obvious the difference in BMI (p < .05). There was a significant difference in overweight/obesity between twins with a relative difference of birth weight ≥15% in DZ twins (p < .05). DZ twins, male twins and 0- to 6-year-old twins were more likely to be discordant in overweight/obese than others. The discordant birth weight within twins was not a risk factor for discordant overweight/obesity. However, attention should be paid to childhood obesity, and appropriate interventions should be made at the appropriate time. Genetics may play an important role in the occurrence and development of overweight/obesity. In conclusion, discordant growth and development in the uterus early in life may not lead to discordant weight development in the future.
Hypertension represents one of the most common pre-existing conditions and comorbidities in Coronavirus disease 2019 (COVID-19) patients. To explore whether hypertension serves as a risk factor for disease severity, a multi-centre, retrospective study was conducted in COVID-19 patients. A total of 498 consecutively hospitalised patients with lab-confirmed COVID-19 in China were enrolled in this cohort. Using logistic regression, we assessed the association between hypertension and the likelihood of severe illness with adjustment for confounders. We observed that more than 16% of the enrolled patients exhibited pre-existing hypertension on admission. More severe COVID-19 cases occurred in individuals with hypertension than those without hypertension (21% vs. 10%, P = 0.007). Hypertension associated with the increased risk of severe illness, which was not modified by other demographic factors, such as age, sex, hospital geological location and blood pressure levels on admission. More attention and treatment should be offered to patients with underlying hypertension, who usually are older, have more comorbidities and more susceptible to cardiac complications.
The FNDC5 gene encodes the fibronectin type III domain-containing protein 5 that is a membrane protein mainly expressed in skeletal muscle, and the FNDC5 rs3480 polymorphism may be associated with liver disease severity in non-alcoholic fatty liver disease (NAFLD). We investigated the influence of the FNDC5 rs3480 polymorphism on the relationship between sarcopenia and the histological severity of NAFLD. A total of 370 adult individuals with biopsy-proven NAFLD were studied. The association between the key exposure sarcopenia and the outcome liver histological severity was investigated by binary logistic regression. Stratified analyses were undertaken to examine the impact of FNDC5 rs3480 polymorphism on the association between sarcopenia and the severity of NAFLD histology. Patients with sarcopenia had more severe histological grades of steatosis and a higher prevalence of significant fibrosis and definite non-alcoholic steatohepatitis than those without sarcopenia. There was a significant association between sarcopenia and significant fibrosis (adjusted OR 2·79, 95 % CI 1·31, 5·95, P = 0·008), independent of established risk factors and potential confounders. Among patients with sarcopenia, significant fibrosis occurred more frequently in the rs3480 AA genotype carriers than in those carrying the FNDC5 rs3480 G genotype (43·8 v. 17·2 %, P = 0·031). In the association between sarcopenia and liver fibrosis, there was a significant interaction between the FNDC5 genotype and sarcopenia status (P value for interaction = 0·006). Sarcopenia is independently associated with significant liver fibrosis, and the FNDC5 rs3480 G variant influences the association between sarcopenia and liver fibrosis in patients with biopsy-proven NAFLD.