Search

Table tennis involves quick and accurate motor responses during training and competition. Multiple studies have reported considerably faster visuomotor responses and expertise-related intrinsic brain activity changes among table tennis players compared with matched controls. However, the underlying neural mechanisms remain unclear. Herein, we performed static and dynamic resting-state functional magnetic resonance imaging (rs-fMRI) analyses of 20 table tennis players and 21 control subjects using 7T ultra-high field imaging. We calculated the static and dynamic amplitude of low-frequency fluctuations (ALFF) of the two groups. The results revealed that table tennis players exhibited decreased static ALFF in the left inferior temporal gyrus (lITG) compared with the control group. Voxel-wised static functional connectivity (sFC) and dynamic functional connectivity (dFC) analyses using lITG as the seed region afforded complementary and overlapping results. The table tennis players exhibited decreased sFC in the right middle temporal gyrus and left inferior parietal gyrus. Conversely, they displayed increased dFC from the lITG to prefrontal cortex, particularly the left middle frontal gyrus, left superior frontal gyrus-medial, and left superior frontal gyrus-dorsolateral. These findings suggest that table tennis players demonstrate altered visuomotor transformation and executive function pathways. Both pathways involve the lITG, which is a vital node in the ventral visual stream. These static and dynamic analyses provide complementary and overlapping results, which may help us better understand the neural mechanisms underlying the changes in intrinsic brain activity and network organization induced by long-term table tennis skill training.

The reference evapotranspiration (ET0) information is crucial for irrigation planning and water resource management. While the Penman-Monteith (PM) equation is widely recognized for ET0 calculation, its reliance on numerous meteorological parameters constrains its practical application. This study used 28 years of meteorological data from 18 stations in four geographic regions of Taiwan to evaluate the effectiveness of an artificial intelligence (AI) model for estimating PM-calculated ET0 using limited meteorological variables as input and compared it with traditional methods. The AI models were also employed for short-term ET0 forecasting with limited meteorological variables. The findings suggested that AI models performed better than their counterpart methods for ET0 estimation. The artificial neural network using temperature, solar radiation, and relative humidity as input variables performed best, with the correlation coefficient (r) ranging from 0.992 to 0.998, mean absolute error (MAE) ranging from 0.07 to 0.16 mm/day, and root mean square error (RMSE) ranging from 0.12 to 0.25 mm/day. For short-term ET0 forecasting, the long short-term memory model using temperature, solar radiation, and relative humidity as input variables was the best structure to forecast four-day-ahead ET0, with the r ranging from 0.608 to 0.756, MAE ranging from 1.05 to 1.28 mm/day, and RMSE ranging from 1.35 to 1.62 mm/day. The percentage error of this structure was within ± 5% for most meteorological stations over the one-year test period, underscoring the potential of the proposed models to deliver daily ET0 forecasts with acceptable accuracy. Finally, the proposed estimating and forecasting models were developed in regional and variable-limited scenarios, making them highly advantageous for practical applications. [ABSTRACT FROM AUTHOR]

Abstract Background Segmental zoster paresis (SZP) of limbs, characterized by focal weakness of extremity, is recognized as a rare complication of herpes zoster (HZ). The following study analyzes the clinical characteristics and data from electromyography and MRI scans in patients with motor weakness after zoster infection. Methods One thousand three hundred ninety-three patients from our database (Shandong Provincial Qianfoshan Hospital) suffering from HZ were retrospectively reviewed from June 2015 to July 2017. Patients who fulfilled the diagnostic criteria for SZP were included in the analysis. The clinical characteristics, as well as electromyography findings and MRI scans were analyzed. Results SZP was present in 0.57% of patients with HZ (8/1393). The average age of symptom onset in 8 SZP patients was 69 years old (SD: 13, range 47–87). The severity of muscle weakness ranged from mild to severe. The electrophysiological testing revealed the characteristics of axonopathy. Radiculopathy (2/8), plexopathy (2/8), radiculoplexopathy (3/8) and combined radiculopathy and mononeuropathy (1/8) were also identified. MRI revealed hyperintensity of the affected spinal dorsal horns, nerve roots or peripheral nerves. Conclusions SZP is associated with obvious limb weakness, nerve axons lesions and localization to nerve roots, plexus or peripheral nerves.

Purpose: To evaluate the capability of deep transfer learning (DTL) and fine-tuning methods in differentiating malignant from benign lesions in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods: The diagnostic efficiencies of the VGG19, ResNet50, and DenseNet201 models were tested under the same dataset. The model with the highest performance was selected and modified utilizing three fine-tuning strategies (S1-3). Fifty additional lesions were selected to form the validation set to verify the generalization abilities of these models. The accuracy (Ac) of the different models in the training and test sets, as well as the precision (Pr), recall rate (Rc), F1 score (), and area under the receiver operating characteristic curve (AUC), were primary performance indicators. Finally, the kappa test was used to compare the degree of agreement between the DTL models and pathological diagnosis in differentiating malignant from benign breast lesions. Results: The Pr, Rc, f1, and AUC of VGG19 (86.0%, 0.81, 0.81, and 0.81, respectively) were higher than those of DenseNet201 (70.0%, 0.61, 0.63, and 0.61, respectively) and ResNet50 (61.0%, 0.59, 0.59, and 0.59). After fine-tuning, the Pr, Rc, f1, and AUC of S1 (87.0%, 0.86, 0.86, and 0.86, respectively) were higher than those of VGG19. Notably, the degree of agreement between S1 and pathological diagnosis in differentiating malignant from benign breast lesions was 0.720 (κ = 0.720), which was higher than that of DenseNet201 (κ = 0.440), VGG19 (κ = 0.640), and ResNet50 (κ = 0.280). Conclusion: The VGG19 model is an effective method for identifying benign and malignant breast lesions on DCE-MRI, and its performance can be further improved via fine-tuning. Overall, our findings insinuate that this technique holds potential clinical application value. [ABSTRACT FROM AUTHOR]

OBJECTIVE:Prolactin (PRL) has been reported to be associated with increased bone turnover, and increased bone turnover is also a feature of skeletal fluorosis (SF). Autocrine/paracrine production of PRL is regulated by the extrapituitary promoter and a polymorphism in the extrapituitary PRL promoter at -1149 (rs1341239) is associated with disturbances of bone metabolism in other diseases. Here, we have investigated the possibility that the rs1341239 polymorphism is associated with SF, which results from the consumption of brick tea. DESIGN:We conducted a cross-sectional study in Sinkiang, Qinghai, Inner Mongolia in China. Demography survey questionnaires were completed and physical examination and X-ray diagnoses were used to diagnose SF. Brick tea water fluoride intake (IF) and urinary fluoride (UF) were tested by an F-ion selective electrode method. A Sequenom MassARRAY system was used to determine PRL gene polymorphisms. RESULTS:Subjects who were younger than 45 years of age and carried the T allele had a significantly decreased risk of SF [OR = 0.279 (95%CI, 0.094-0.824)] compared to those carrying the homozygous G allele. This phenomenon was only observed in Kazakh subjects [OR = 0.127 (95%CI, 0.025-0.646)]. Kazakh females who carried T alleles has a decreased risk of SF [OR = 0.410 (95%CI, 0.199-0.847)]. For Kazakh subjects which IF is less than 3.5 mg/d, a decreased risk of SF was observed among the participants who carried T alleles [OR = 0.118 (95%CI, 0.029-0.472)]. Overall, subjects with 1.6-3.2 mg/L UF and carried T alleles had a significantly decreased risk of SF [OR = 0.476 (95%CI, 0.237-0.955)] compared to homozygous G allele carriers. This phenomenon was only observed in Kazakh subjects [OR = 0.324 (95%CI, 0.114-0.923)]. CONCLUSIONS:Our results suggested that the PRL rs1341239 T allele decreases the risk of brick tea SF.

Phytochelatins (PCs) play an important role in detoxification of heavy metals in plants. PCs are synthesized from glutathione by phytochelatin synthase (PCS), a dipeptidyltransferase. Sesbania rostrata is a tropical legume plant that can tolerate high concentrations of Cd and Zn. In this study, the S. rostrata PCS gene (SrPCS) and cDNAs were isolated and characterized. Southern blot and sequence analysis revealed that a single copy of the SrPCS gene occurs in the S. rostrata genome, and produces four different SrPCS mRNAs and proteins, SrPCS1-SrPCS4, by alternative splicing of the SrPCS pre-mRNA. The SrPCS1 and SrPCS3 proteins conferred Cd tolerance when expressed in yeast cells, whereas the SrPCS2 and SrPCS4 proteins, which lack the catalytic triad and the N-terminal domains, did not. These results suggested that SrPCS1 and SrPCS3 have potential applications in genetic engineering of plants for enhancing heavy metal tolerance and phytoremediation of contaminated soils.

Lithium metal is considered as an ideal anode material for next-generation high energy density batteries with its high specific capacity and low electrode potential. However, the high activity of lithium metal can lead to a series of safety issues. For example, lithium metal will continuously react chemically with the electrolyte, forming unstable the solid electrolyte (SEI) films. In addition, lithium dendrites can be formed during cycling, which can puncture the SEI film and cause short circuits in the battery. These drawbacks greatly hinder the commercial application of lithium metal. To solve the above problems, it is important to understand the structure of SEI and the underlying mechanism of its formation as a guide for rational design. Quantum mechanics (QM) has been demonstrated as an effective tool to investigate the chemical reactions and microscopic atomic structures of SEI. However, QM is computationally too expensive to be used for large-scale and long-term theoretical simulations. Instead, the molecular mechanics (MM) method has much orders higher computational efficiency than QM, and can be used for large-scale and long-time theoretical simulations. However, the accuracy of MM is usually not guaranteed, especially for complex SEI. Therefore, a practical solution is to combine the advantages of both. In this work, we use the hybrid ab initio and reactive molecule dynamics (HAIRs) approach to describe chemical reactions with the accuracy of quantum chemistry and improve the computational efficiency by more than 10 times with mixing QM and MM. Using this method, we have investigated the interfacial reaction mechanism of two electrolyte solutions, 1 mol⋅-1 LiTFSI-DME (dimethoxyethane) and 1 mol⋅-1 LiTFSI-EC (ethylene carbonate) with the lithium metal anode. The simulation results show that TFSI anion prefers to be decomposed, while DME does not, thus, TFSI plays the vital role of protecting DME. However, in the LiTFSI-EC system, both TFSI anion and EC are decomposed, indicating that EC is less stable and not suitable to the formation of stable SEI. Thanks to the computational efficiency of the HAIRs method, we have completed the 1 ns simulation in a few days. Using the hardware, the above calculation would take at least one to two months if only the QM method was employed. Meanwhile the long HAIRs calculation shows that for the simulation of chemical reactions in SEI, at least 1 ns is essential. Instead, previous molecular dynamics (MD) simulations with a few ps, or tens of ps, are insufficient to fully capture the critical chemical reactions. The above simulation results provide reliable experience for the computational simulation study of SEI formation, and lay the theoretical foundation for the rational design of electrolytes and the development of high-performance electrolyte solution systems. [ABSTRACT FROM AUTHOR]