Association of lipid-lowering drugs with risk of sarcopenia: a drug target mendelian randomization study and meta-analysis.

BACKGROUND: Lipid-lowering drugs are widely used among the elderly, with some studies suggesting links to muscle-related symptoms. However, the causality remains uncertain. METHODS: Using the Mendelian randomization (MR) approach, we assessed the causal effects of genetically proxied reduced low-density lipoprotein cholesterol (LDL-C) through inhibitions of hydroxy-methyl-glutaryl-CoA reductase (HMGCR), proprotein convertase subtilisin/kexin type 9 (PCSK9), and Niemann-Pick C1-like 1 (NPC1L1) on sarcopenia-related traits, including low hand grip strength, appendicular lean mass, and usual walking pace. A meta-analysis was conducted to combine the causal estimates from different consortiums. RESULTS: Using LDL-C pooled data predominantly from UK Biobank, genetically proxied inhibition of HMGCR was associated with higher appendicular lean mass (beta = 0.087, P = 7.56 × 10- 5) and slower walking pace (OR = 0.918, P = 6.06 × 10- 9). In contrast, inhibition of PCSK9 may reduce appendicular lean mass (beta = -0.050, P = 1.40 × 10- 3), while inhibition of NPC1L1 showed no causal impact on sarcopenia-related traits. These results were validated using LDL-C data from Global Lipids Genetics Consortium, indicating that HMGCR inhibition may increase appendicular lean mass (beta = 0.066, P = 2.17 × 10- 3) and decelerate walking pace (OR = 0.932, P = 1.43 × 10- 6), whereas PCSK9 inhibition could decrease appendicular lean mass (beta = -0.048, P = 1.69 × 10- 6). Meta-analysis further supported the robustness of these causal associations. CONCLUSIONS: Genetically proxied HMGCR inhibition may increase muscle mass but compromise muscle function, PCSK9 inhibition could result in reduced muscle mass, while NPC1L1 inhibition is not associated with sarcopenia-related traits and this class of drugs may serve as viable alternatives to sarcopenia individuals or those at an elevated risk.

Effect of heat-reinforcing needling on hypoxia-inducible factor 1α and glycolysis activity in rabbits with cold syndrome of rheumatoid arthritis. / çƒ­è¡¥é’ˆæ³•å¯¹ç±»é£Žæ¹¿å ³èŠ‚ç‚Žå¯’è¯å®¶å ”è†å ³èŠ‚æ»‘è†œç»„ç»‡ç¼ºæ°§è¯±å¯¼å› å­1αå’Œç³–é µè§£æ´»æ€§çš„å½±å“.

OBJECTIVES: To observe the effect of heat-reinforcing needling (HRN) on synovial inflammation, hypoxia-inducible factor-1α (HIF-1α) and glycolytic activity in serum and synovial tissue in rabbits with cold syndrome of rheumatoid arthritis (RA), so as to explore its mechanisms underlying improvement of RA. METHODS: A total of 32 rabbits were randomly divided into normal, model, inhibitor and HRN groups, with 8 rabbits in each group. The RA with cold syndrome model was induced by injecting ovalbumin dry powder and Freund's complete adjuvant combined with cold freezing. Rabbits in the inhibitor group were intraperitoneally injected with 2-methoxyestradiol (2.5 mg/kg), rabbits in the HRN group were received HRN at bilateral "Zusanli" (ST36) for 30 min. The treatments were conducted once daily for 14 consecutive days. After the interventions, the knee circumference and pain threshold were measured. The contents of nicotinamide adenine dinucleotide phosphoric (NADPH), Hexokinase II (HK2) and 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase 3 (PFKFB3) in serum of rabbits were detected by ELISA. The pathological morphology of synovial tissue of the knee joints were observed by HE staining. The positive expressions of tumor necrosis factor (TNF-α), interleukin (IL)-1ß, IL-6 and IL-17 in synovial tissue of knee joint were detected by immunohistochemistry. The content of lactic acid in synovial tissue of rabbit knee joint was detected by spectrophotometry. The expression levels of HIF-1α, pyruvate kinase 2 (PKM2) and lactate dehydrogenase (LDHA) in synovial tissue of knee joint were detected by Western blot. RESULTS: After intervention, compared with the normal group, the knee circumference was significantly enlarged (P<0.05), the pain threshold was significantly decreased (P<0.05)；the synovial tissue of knee joints showed significant cell proliferation and inflammatory infiltration, the pathological score was significantly increased (P<0.05)；positive expressions of TNF-α, IL-1ß, IL-6 and IL-17, the content of lactic acid in synovial tissue, the contents of NADPH, HK2 and PFKFB3 in serum, and the protein expression levels of HIF-1α, PKM2 and LDHA in synovial tissue were increased (all P<0.05) in the model group. Compared with model group, the circumference of knee joint was significantly decreased (P<0.05), the pain threshold was significantly increased (P<0.05)；in synovial tissue, the pathological score was decreased (P<0.05)；the positive expressions of TNF-α, IL-1ß, IL-6 and IL-17 in synovial tissue were decreased (P<0.05), the lactic acid content in synovial tissue was decreased (P<0.05)；the contents of NADPH, HK2 and PFKFB3 in serum and the protein expression levels of HIF-1α, PKM2 and LDHA in synovial tissue were decreased (P<0.05) in inhibitor group and HRN group. Compared with the inhibitor group, the synovial pathological score was significantly increased (P<0.05), positive expressions of TNF-α, IL-1ß, IL-6 and IL-17, the content of lactic acid in synovial tissue, the contents of NADPH, HK2 and PFKFB3 in serum, and the protein expression levels of HIF-1α, PKM2 and LDHA in synovial tissue were increased (all P<0.05) in HRN group. CONCLUSIONS: HRN can increase the pain threshold, reduce the knee circumference and inhibit the inflammatory response in rabbits with cold syndrome of RA. The possible mechanism is related to the down-regulation of HIF-1α and glycolysis activity.

USP38 exacerbates pressure overload-induced left ventricular electrical remodeling.

BACKGROUND: Ubiquitin-specific protease 38 (USP38), belonging to the USP family, is recognized for its role in controlling protein degradation and diverse biological processes. Ventricular arrhythmias (VAs) following heart failure (HF) are closely linked to ventricular electrical remodeling, yet the specific mechanisms underlying VAs in HF remain inadequately explored. In this study, we examined the impact of USP38 on VAs in pressure overload-induced HF. METHODS: Cardiac-specific USP38 knockout mice, cardiac-specific USP38 transgenic mice and their matched control littermates developed HF induced by aortic banding (AB) surgery. After subjecting the mice to AB surgery for a duration of four weeks, comprehensive investigations were conducted, including pathological analysis and electrophysiological assessments, along with molecular analyses. RESULTS: We observed increased USP38 expression in the left ventricle of mice with HF. Electrocardiogram showed that the USP38 knockout shortened the QRS interval and QTc, while USP38 overexpression prolonged these parameters. USP38 knockout decreased the susceptibility of VAs by shortening action potential duration (APD) and prolonging effective refractory period (ERP). In addition, USP38 knockout increased ion channel and Cx43 expression in ventricle. On the contrary, the increased susceptibility of VAs and the decreased expression of ventricular ion channels and Cx43 were observed with USP38 overexpression. In both in vivo and in vitro experiments, USP38 knockout inhibited TBK1/AKT/CAMKII signaling, whereas USP38 overexpression activated this pathway. CONCLUSION: Our data indicates that USP38 increases susceptibility to VAs after HF through TBK1/AKT/CAMKII signaling pathway, Consequently, USP38 may emerge as a promising therapeutic target for managing VAs following HF.

Repairing distorted hologram data for sound field reconstruction.

This paper proposes a distorted hologram data repair approach for sound field reconstruction. In this approach, an equivalent source model is established by placing a set of equivalent sources near the hologram surface to represent the measured hologram pressures. Each hologram pressure is simultaneously assigned an indicator to describe whether its measurement is corrupted by errors or not. This model is then formulated within a modal framework by utilizing the modes generated through the singular value decomposition of the transfer matrix between the hologram and nearby equivalent source surfaces. Subsequently, the indicators and modal coefficients are assigned the 0-1 and Gaussian prior distributions, respectively, and their posterior distributions are derived using the Bayesian method. The means of the posterior distributions are calculated to discriminate corrupted measurements and repair distorted hologram pressures. Repaired hologram pressures are finally utilized for reconstructions using the equivalent source method. Results from both numerical simulations conducted under various parameter settings and two experiments demonstrate the effectiveness of the proposed approach in automatically discriminating all the corrupted measurements and accurately repairing the distorted hologram pressures. Furthermore, the accuracy of the reconstructions using the repaired hologram pressures is comparable to that achieved with the correctly measured pressures.

Causal effects of sedentary behaviours on the risk of migraine: A univariable and multivariable Mendelian randomization study.

BACKGROUND: Migraine is a common and burdensome neurological disorder. The causal relationship between sedentary behaviours (SBs) and migraine remains instinct. We aimed to evaluate the roles of SBs including watching TV, using computer and driving in the risk of migraine. METHODS: We conducted a univariable and multivariable Mendelian randomization (MR) study based on summary datasets of large genome-wide association studies. The inverse variance weighted method was utilized as the primary analytical tool. Cochran's Q, MR-Egger intercept test, MR pleiotropy residual sum and outlier and leave-one-out were conducted as sensitivity analysis. Additionally, we performed a meta-analysis to combine the causal estimates. RESULTS: In the discovery analysis, we identified causal associations between time spent watching TV and an increased risk of migraine (p = 0.015) and migraine without aura (MO) (p = 0.002). Such causalities with increasing risk of migraine (p = 0.005), and MO (p = 0.006) were further verified using summary datasets from another study in the replication analysis. There was no significant causal association found between time spent using computer, driving and migraine or its two subtypes. The meta-analysis and multivariable MR analysis also strongly supported the causal relationships between time spent watching TV and an increased risk of migraine (p = 0.0003 and p = 0.034), as well as MO (p < 0.0001 and p = 0.0004), respectively. These findings were robust under all sensitivity analysis. CONCLUSIONS: Our study suggested that time spent watching TV may be causally associated with an increased risk of migraine, particularly MO. Large-scale and well-designed cohort studies may be warranted for further validation. SIGNIFICANCE STATEMENT: This study represents the first attempt to investigate whether a causal relationship exists between SBs and migraine. Utilizing MR analysis helps mitigate reverse causation bias and confounding factors commonly encountered in observational cohorts, thereby enhancing the robustness of derived causal associations. Our MR analysis revealed that time spent watching TV may serve as a potential risk factor for migraine, particularly MO.

Real-time nearfield acoustic holography using particle velocity.

In this paper, a series of impulse response functions between acoustic quantities on the source plane and particle velocity on the hologram plane are derived. In virtue of these functions, real-time nearfield acoustic holography (RT-NAH) is extended from pressure-based to particle velocity. Pressure, normal velocity, acceleration, and displacement radiated from planar sources can be reconstructed by measuring time-dependent particle velocity signals on the hologram plane. A simulation of an excited aluminum plate is performed to evaluate the difference in accuracy between RT-NAHs based on pressure and based on particle velocity. This study also examines the impact of impulse response functions on the reconstruction results, allowing for detailed analysis of the reconstruction accuracy based on these functions. The simulation results demonstrate that using RT-NAH based on particle velocity obtains significantly higher-accuracy reconstruction results when reconstructing normal velocity and displacement and slightly more accurate reconstructed pressure and normal acceleration.

Abnormalities in spontaneous brain activity and functional connectivity are associated with cognitive impairments in children with type 1 diabetes mellitus.

BACKGROUND: It remains unclear whether alterations in brain function occur in the early stage of pediatric type 1 diabetes mellitus(T1DM). We aimed to examine changes in spontaneous brain activity and functional connectivity (FC) in children with T1DM using resting-state functional magnetic resonance imaging (rs-fMRI), and to pinpoint potential links between neural changes and cognitive performance. METHODS: In this study, 22 T1DM children and 21 age-, sex-matched healthy controls underwent rs-fMRI. The amplitude of low frequency fluctuations (ALFF) and seed-based FC analysis were performed to examine changes in intrinsic brain activity and functional networks in T1DM children. Partial correlation analyses were utilized to explore the correlations between ALFF values and clinical parameters. RESULTS: The ALFF values were significantly lower in the lingual gyrus (LG) and higher in the left medial superior frontal gyrus (MSFG) in T1DM children compared to controls. Subsequent FC analysis indicated that the LG had decreased FC with bilateral inferior occipital gyrus, and the left MSFG had decreased FC with right precentral gyrus, right inferior parietal gyrus and right postcentral gyrus in children with T1DM. The ALFF values of LG were positively correlated with full-scale intelligence quotient and age at disease onset in T1DM children, while the ALFF values of left MSFG were positively correlated with working memory scores. CONCLUSION: Our findings revealed abnormal spontaneous activity and FC in brain regions related to visual, memory, default mode network, and sensorimotor network in the early stage of T1DM children, which may aid in further understanding the mechanisms underlying T1DM-associated cognitive dysfunction.

[Cystic fibrosis primarily presenting with pseudo-Bartter syndrome: a report of three cases and literature review]. / 以假性Bartter综合征为主要表现的囊性纤维化患儿3ä¾‹å¹¶æ–‡çŒ®å¤ä¹ .

OBJECTIVES: To summarize the clinical characteristics and genetic variations in children with cystic fibrosis (CF) primarily presenting with pseudo-Bartter syndrome (CF-PBS), with the aim to enhance understanding of this disorder. METHODS: A retrospective analysis was performed on the clinical data of three children who were diagnosed with CF-PBS in Hunan Children's Hospital from January 2018 to August 2023, and a literature review was performed. RESULTS: All three children had the onset of the disease in infancy. Tests after admission showed hyponatremia, hypokalemia, hypochloremia, and metabolic alkalosis, and genetic testing showed the presence of compound heterozygous mutation in the CFTR gene. All three children were diagnosed with CF. Literature review obtained 33 Chinese children with CF-PBS, with an age of onset of 1-36 months and an age of diagnosis of 3-144 months. Among these children, there were 29 children with recurrent respiratory infection or persistent pneumonia (88%), 26 with malnutrition (79%), 23 with developmental retardation (70%), and 18 with pancreatitis or extrapancreatic insufficiency (55%). Genetic testing showed that c.2909G>A was the most common mutation site of the CFTR gene, with a frequency of allelic variation of 23% (15/66). CONCLUSIONS: CF may have no typical respiratory symptoms in the early stage. The possibility of CF-PBS should be considered for infants with recurrent hyponatremia, hypokalemia, hypochloremia, and metabolic alkalosis, especially those with malnutrition and developmental retardation. CFTR genetic testing should be performed as soon as possible to help with the diagnosis of CF.

[Identification of horn-derived animal medicines based on detection of keratin-derived characteristic peptides].

Due to the highly stable structure of keratin, the extraction and dissolution steps of animal medicines rich in keratin are complex, which seriously restricts the detection efficiency and flux. Therefore, this study simplified the pre-treatment steps of horn samples and optimized the detection methods of characteristic peptides to improve the efficiency of identifying the specificity of horn-derived animal medicines. For detection of the characteristic peptides in horn-derived animal medicines treated with/without iodoace-tamide(IAA), the ion pair conditions of the characteristic peptides were optimized, and the retention time, intensity and other data of the specific peptides were compared between the samples treated with/without IAA. Two pre-treatment methods, direct enzymatic hydrolysis and total protein extraction followed by enzymatic hydrolysis, were used to prepare horn-derived animal medicine samples. The effects of different methods on the detection of specific peptides in the samples of Saiga antelope horn, water buffalo horn, goat horn, and yak horn were compared regarding the retention time of specific peptides and ion intensity. The results indicated that after direct enzymatic hydrolysis, the specific peptides in the samples without IAA treatment can be detected. Compared with the characteristic peptides in the samples treated with IAA, their retention time shifted back and the mass spectrometry response slightly decreased. The specific peptides of the samples without IAA treatment had good specificity and did not affect the specificity identification of horn-derived animal medicines. Overall, the process of direct enzymatic hydrolysis can be used to treat horn samples, omitting the steps of protein extraction and dithiothreitol and IAA treatment, significantly improving the pre-treatment efficiency without affecting the specificity identification of horn-derived animal medicines. This study provides ideas for quality research and standard improvement of horn-derived animal medicines.

Machine learning models for diagnosis of essential tremor and dystonic tremor using grey matter morphological networks.

BACKGROUND: Essential tremor (ET) and dystonic tremor (DT) are the two most common tremor disorders, and misdiagnoses are very common due to similar tremor symptoms. In this study, we explore the structural network mechanisms of ET and DT using brain grey matter (GM) morphological networks and combine those with machine learning models. METHODS: 3D-T1 structural images of 75 ET patients, 71 DT patients, and 79 healthy controls (HCs) were acquired. We used voxel-based morphometry to obtain GM images and constructed GM morphological networks based on the Kullback-Leibler divergence-based similarity (KLS) method. We used the GM volumes, morphological relations, and global topological properties of GM-KLS morphological networks as input features. We employed three classifiers to perform the classification tasks. Moreover, we conducted correlation analysis between discriminative features and clinical characteristics. RESULTS: 16 morphological relations features and 1 global topological metric were identified as the discriminative features, and mainly involved the cerebello-thalamo-cortical circuits and the basal ganglia area. The Random Forest (RF) classifier achieved the best classification performance in the three-classification task, achieving a mean accuracy (mACC) of 78.7%, and was subsequently used for binary classification tasks. Specifically, the RF classifier demonstrated strong classification performance in distinguishing ET vs. HCs, ET vs. DT, and DT vs. HCs, with mACCs of 83.0 %, 95.2 %, and 89.3 %, respectively. Correlation analysis demonstrated that four discriminative features were significantly associated with the clinical characteristics. CONCLUSION: This study offers new insights into the structural network mechanisms of ET and DT. It demonstrates the effectiveness of combining GM-KLS morphological networks with machine learning models in distinguishing between ET, DT, and HCs.

A meta-analysis of the relationship between abnormal pretreatment EEG and epilepsy recurrence.

BACKGROUND: Researchers have studied the risk factors for epilepsy recurrence among patients who withdraw from antiseizure medication (ASM). These studies aimed to determine the optimal time for ASM withdrawal. EEG findings are one of the risk factors that has been studied. However, it remains unclear whether abnormal pretreatment EEG findings are a risk factor for recurrence after ASM withdrawal. We performed this meta-analysis to clarify this issue. METHODS: We retrieved literature from the PubMed and Embase databases, and used the NewcastleOttawa Scale to evaluate the methodological quality of the included studies. RevMan 5.3 software was used to analyse the data. RESULTS: In total,710 articles were retrieved from the databases. Ultimately, after screening, 11 articles involving 1686 patients with epilepsy were included. Compared with that for a normal EEG, the odds ratio (OR) for an abnormal EEG was 1.10 (P=0.50), with an I2 value of 32% (P=0.15). Subgroup analysis revealed that the children-to-adolescents subgroup had an OR of 1.21 (P=0.27), and the children-to-adults subgroup had an OR of 0.64 (P=0.14) for an abnormal EEG. A separate subgroup analysis revealed that the focal epilepsy subgroup had an OR of 1.30 (P=0.37), and the generalized epilepsy and focal epilepsy subgroup had an OR of 1.07 (P=0.67) for an abnormal EEG. CONCLUSIONS: The risk of epilepsy recurrence is not related to pretreatment EEG findings, regardless of age or epilepsy classification. The associations of pre- and posttreatment EEG alterations with epilepsy recurrence are controversial. Due to the limitations of our article, further research is needed.

The relationship between gastrointestinal symptoms in FGID patients and D-type personality and emotion regulation strategies.

This study examines the relationship between gastrointestinal symptoms in patients with functional gastrointestinal disorders (FGIDs) and type D personality traits, as well as emotion regulation strategies. Analyzing a diverse group of FGID patients, we uncover significant effects of gender and age on gastrointestinal symptoms. Negative Affectivity emerges as a key predictor, positively associated with symptom severity, whereas Social Inhibition correlates negatively with Abdominal Pain. Additionally, our findings suggest that the expressive suppression strategy predicts heightened gastrointestinal symptoms, whereas cognitive reappraisal predicts lower levels of certain symptoms. These findings provide valuable insights for precise diagnosis and tailored treatments of FGIDs. Further research is warranted to explore underlying mechanisms and inform evidence-based interventions.

Relationships among anxiety, depression, and health-related quality of life in adult epilepsy: A network analysis.

OBJECTIVE: Comorbid depression and anxiety in patients with epilepsy (PWE) are common and frequently under-treated, thus, causing poor health-related quality of life (HRQoL). However, little is known regarding the interconnections between anxious/depressive symptoms and the dimensions of HRQoL. Therefore, we conducted a network analysis to explore these relationships in detail among Chinese adult PWE. METHODS: A cohort of adult PWE was consecutively recruited from the First Affiliated Hospital of Chongqing Medical University. HRQoL, depression, and anxiety were measured with Quality of Life in Epilepsy Inventory-31, Neurological Disorders Depression Inventory for Epilepsy, and Generalized Anxiety Disorder 7-Item Scale, respectively. A regularized partial correlation network was constructed to investigate the interconnections between symptoms of anxiety/depression and the dimensions of HRQoL. We calculated expected influence (EI) and bridge expected influence (BEI) values to identify the most influential nodes. RESULTS: A total of 396 PWE were enrolled in this study, 78.1% of whom had focal onset epilepsy. The prevalence of anxiety and depression was 30.3% and 28.8%, respectively. The symptoms "frustrated" and "uncontrollable worry" had the highest EI values, whereas "emotional well-being", "seizure worry", "difficulty finding pleasure", and "nervousness or anxiety" had the highest BEI values. CONCLUSION: This study provides new insights into the relationships among anxiety, depression, and HRQoL. Critical central symptoms and bridge symptoms identified in the network might help to quickly identify PWE comorbid anxiety and depression in busy outpatient settings, thereby enabling early intervention and enhancing quality of life.

Investigating the Respiratory and Energy Metabolism Mechanisms behind ε-Poly-L-lysine Chitosan Coating's Improved Preservation Effectiveness on Tremella fuciformis.

Freshly harvested Tremella fuciformis contains high water content with an unprotected outer surface and exhibits high respiration rates, which renders it prone to moisture and nutrient loss, leading to decay during storage. Our research utilized ε-poly-L-lysine (ε-PL) and chitosan as a composite coating preservative on fresh T. fuciformis. The findings revealed that the ε-PL + chitosan composite coating preservative effectively delayed the development of diseases and reduced weight loss during storage compared to the control group. Furthermore, this treatment significantly decreased the respiration rate of T. fuciformis and the activity of respiratory metabolism-related enzymes, such as alternative oxidase (AOX), cytochrome c oxidase (CCO), succinic dehydrogenase (SDH), 6-phosphogluconate dehydrogenase, and glucose-6-phosphate dehydrogenase (6-PGDH and G-6-PDH). Additionally, the composite coating preservative also delayed the depletion of ATP and ADP and maintained higher levels of the energy charge while preserving low levels of AMP. It also sustained heightened activities of Mg2+-ATPase, Ca2+-ATPase, and H+-ATPase enzymes. These results demonstrate that utilizing the ε-PL + chitosan composite coating preservative can serve as a sufficiently safe and efficient method for prolonging the shelf life of post-harvest fresh T. fuciformis.

Genetic causal association between physical activities and epilepsy: A Mendelian randomization study.

BACKGROUND: Despite numerous investigations into the relationship between physical activities (PA) and epilepsy, the causal effects remain contentious. Thus, we conducted a two-sample Mendelian randomization (MR) study to assess the potential causality. METHODS: Single-nucleotide polymorphisms (SNPs) predisposed to self-reported moderate and vigorous physical activities (MPA and VPA) and overall acceleration average (OAA) calculated through wrist-worn accelerometers were selected as exposure instrumental variables. Five subtypes of epilepsy, including all epilepsy, focal epilepsy and generalized epilepsy (with or without each other), focal epilepsy-strict definition and generalized epilepsy-strict definition (without overlap), were chosen as the outcomes. The MR study utilized the inverse-variance weighted (IVW) method as the primary analytical tool, supplemented by MR-Egger, simple mode, weighted mode, and weighted median methods. Cochran's Q and MR-Egger intercept tests were employed to assess heterogeneity and pleiotropy, while MR pleiotropy residual sum and outlier and leave-one-out analyses were conducted to identify potential SNP outliers. RESULTS: The study indicated that OAA was genetically linked to a decreased risk of both focal epilepsy (OR = 0.812, 95% CI: 0.687-0.960, p = .015, IVW) and focal epilepsy-strict definition (OR = 0.732, 95% CI: 0.596-0.900, p = .003, IVW; OR = 0.749, 95% CI: 0.573-0.979, p = .035, Weighted median). Genetically predicted MPA and VPA did not exhibit a causal association with all epilepsy or its subtypes (p>.05). No evidence of heterogeneity, pleiotropy, or SNP outlier was observed. CONCLUSIONS: Our findings suggested that PA with accelerometer monitoring may potentially reduce the risk of focal epilepsy, while there is no evidence supporting causal association between self-reported MPA or VPA and either focal or generalized epilepsy.

Ubiquitin specific protease 38 aggravates pathological cardiac remodeling by stabilizing phospho-TBK1.

Chronic pressure overload can cause pathological cardiac remodeling and eventually heart failure. The ubiquitin specific protease (USP) family proteins play a prominent role in regulating substrate protein degradation and cardiac structural and functional homeostasis. Although USP38 is expressed in the heart, uncertainty exists regarding the function of USP38 in pathological cardiac remodeling. We constructed and generated cardiac specific USP38 knockout mice and cardiac specific USP38 overexpression mice to assess the role of USP38 in pathological cardiac remodeling. Furthermore, we used co-immunoprecipitation (Co-IP) assays and western blot analysis to identify the molecular interaction events. Here, we reported that the expression of USP38 is significantly elevated under a hypertrophic condition in vivo and in vitro. USP38 deletion significantly mitigates cardiomyocyte enlargement in vitro and hypertrophic effect induced by pressure overload, while overexpression of USP38 markedly aggravates cardiac hypertrophy and remodeling. Mechanistically, USP38 interacts with TANK-binding kinase 1 (TBK1) and removes K48-linked polyubiquitination of TBK1, stabilizing p-TBK1 and promoting the activation of its downstream mediators. Overexpression of TBK1 in the heart of cardiac specific USP38 knockout mice partially counteracts the benefit of USP38 deletion on pathological cardiac remodeling. The TBK1 inhibitor Amlexanox significantly alleviates pressure overload induced-cardiac hypertrophy and myocardial fibrosis in mice with USP38 overexpression. Our results demonstrate that USP38 serves as a positive regulator of pathological cardiac remodeling and suggest that targeting the USP38-TBK1 axis is a promising treatment strategy for hypertrophic heart failure.

Consequences of plateau pika disturbance on plant-soil carbon and nitrogen in alpine meadows.

The presence of burrowing mammals can have extensive effects on plants and soils, creating bare soil patches in alpine meadows and potentially altering plant-soil carbon (C) and nitrogen (N). This study focuses on the plateau pika (Ochotona curzoniae) to examine the responses of plant-soil C and N to a small burrowing mammal from quadrat scale to plot scale. The density of active burrow entrances in disturbed plots was used as an indicator of the disturbance intensity of plateau pikas. The study found that the below-ground biomass (BGB) and its C and N, as well as soil C and N concentrations were significantly lower in bare soil areas than in vegetated areas and undisturbed plots. This shows that the quadrat scale limited the estimation of the C and N sequestration potential. Therefore, further research on the plot scale found that the disturbance by plateau pika significantly reduced plant biomass and BGB carbon stock. However, plateau pika did not affect soil C and N stocks or ecosystem C and N stocks. These findings suggest the bare soil patches formed by plateau pika caused plant and soil heterogeneity but had a trade-off effect on plant-soil C and N stocks at the plot scale. Nevertheless, moderate disturbance intensity increased the C and N sequestration potential in grassland ecosystems. These results provide a possible way to estimate how disturbance by small burrowing mammals affects C and N cycling in grassland ecosystems while accurately assessing the effects of small burrowing mammal densities on C and N in grassland ecosystems.

Combined brain topological metrics with machine learning to distinguish essential tremor and tremor-dominant Parkinson's disease.

BACKGROUND: Essential tremor (ET) and Parkinson's disease (PD) are the two most prevalent movement disorders, sharing several overlapping tremor clinical features. Although growing evidence pointed out that changes in similar brain network nodes are associated with these two diseases, the brain network topological properties are still not very clear. OBJECTIVE: The combination of graph theory analysis with machine learning (ML) algorithms provides a promising way to reveal the topological pathogenesis in ET and tremor-dominant PD (tPD). METHODS: Topological metrics were extracted from Resting-state functional images of 86 ET patients, 86 tPD patients, and 86 age- and sex-matched healthy controls (HCs). Three steps were conducted to feature dimensionality reduction and four frequently used classifiers were adopted to discriminate ET, tPD, and HCs. RESULTS: A support vector machine classifier achieved the best classification performance of four classifiers for discriminating ET, tPD, and HCs with 89.0% mean accuracy (mACC) and was used for binary classification. Particularly, the binary classification performances among ET vs. tPD, ET vs. HCs, and tPD vs. HCs were with 94.2% mACC, 86.0% mACC, and 86.3% mACC, respectively. The most power discriminative features were mainly located in the default, frontal-parietal, cingulo-opercular, sensorimotor, and cerebellum networks. Correlation analysis results showed that 2 topological features negatively and 1 positively correlated with clinical characteristics. CONCLUSIONS: These results demonstrated that combining topological metrics with ML algorithms could not only achieve high classification accuracy for discrimination ET, tPD, and HCs but also help to reveal the potential brain topological network pathogenesis in ET and tPD.

Universal and Scalable Weakly-Supervised Domain Adaptation.

Domain adaptation leverages labeled data from a source domain to learn an accurate classifier for an unlabeled target domain. Since the data collected in practical applications usually contain noise, the weakly-supervised domain adaptation algorithm has attracted widespread attention from researchers that tolerates the source domain with label noises or/and features noises. Several weakly-supervised domain adaptation methods have been proposed to mitigate the difficulty of obtaining the high-quality source domains that are highly related to the target domain. However, these methods assume to obtain the accurate noise rate in advance to reduce the negative transfer caused by noises in source domain, which limits the application of these methods in the real world where the noise rate is unknown. Meanwhile, since source data usually comes from multiple domains, the naive application of single-source domain adaptation algorithms may lead to sub-optimal results. We hence propose a universal and scalable weakly-supervised domain adaptation method called PDCAS to ease restraints of such assumptions and make it more general. Specifically, PDCAS includes two stages: progressive distillation and domain alignment. In progressive distillation stage, we iteratively distill out potentially clean samples whose annotated labels are highly consistent with the prediction of model and correct labels for noisy source samples. This process is non-supervision by exploiting intrinsic similarity to measure and extract initial corrected samples. In domain alignment stage, we consider Class-Aligned Sampling which balances the samples for both source and target domains along with the global feature distributions to alleviate the shift of label distributions. Finally, we apply PDCAS in multi-source noisy scenario and propose a novel multi-source weakly-supervised domain adaptation method called MSPDCAS, which shows the scalability of our framework. Extensive experiments on Office-31 and Office-Home datasets demonstrate the effectiveness and robustness of our method compared to state-of-the-art methods.