Milletdb: a multi-omics database to accelerate the research of functional genomics and molecular breeding of millets.

Millets are a class of nutrient-rich coarse cereals with high resistance to abiotic stress; thus, they guarantee food security for people living in areas with extreme climatic conditions and provide stress-related genetic resources for other crops. However, no platform is available to provide a comprehensive and systematic multi-omics analysis for millets, which seriously hinders the mining of stress-related genes and the molecular breeding of millets. Here, a free, web-accessible, user-friendly millets multi-omics database platform (Milletdb, http://milletdb.novogene.com) has been developed. The Milletdb contains six millets and their one related species genomes, graph-based pan-genomics of pearl millet, and stress-related multi-omics data, which enable Milletdb to be the most complete millets multi-omics database available. We stored GWAS (genome-wide association study) results of 20 yield-related trait data obtained under three environmental conditions [field (no stress), early drought and late drought] for 2 years in the database, allowing users to identify stress-related genes that support yield improvement. Milletdb can simplify the functional genomics analysis of millets by providing users with 20 different tools (e.g., 'Gene mapping', 'Co-expression', 'KEGG/GO Enrichment' analysis, etc.). On the Milletdb platform, a gene PMA1G03779.1 was identified through 'GWAS', which has the potential to modulate yield and respond to different environmental stresses. Using the tools provided by Milletdb, we found that the stress-related PLATZs TFs (transcription factors) family expands in 87.5% of millet accessions and contributes to vegetative growth and abiotic stress responses. Milletdb can effectively serve researchers in the mining of key genes, genome editing and molecular breeding of millets.

Comparison of 14 respiratory pathogens among hospitalized children during and after the COVID-19 outbreak in Chaoshan area.

BACKGROUND: Since January 2020, measures has been adopted in the Chaoshan area to limit the spread of COVID-19. Restrictions were removed after August 2020. At the same time, children returned to school. We previously reported the changes of 14 main respiratory pathogens in hospitalized children before and during the COVID-19 outbreak in Chaoshan area. However, the changes of respiratory pathogen spectrum in hospitalized children after the epidemic are still unknown, which will be elucidated in this study. METHODS: There are 6201 children hospitalized with respiratory tract infection were enrolled in the study, which were divided into two groups: 2533 from outbreak group (1 January 2020-31 December 2020), and 3668 from post-outbreak group (1 January 2021-31 December 2021). Pharyngeal swab samples were collected. 14 respiratory tract pathogens were detected by liquid chip technology. RESULTS: The positive rate of pathogen detection is significantly lower in the outbreak group (65.42%, 1657/2533) than that in the post-outbreak group (70.39%, 2582/3668; χ2 = 17.15, P < 0.05). The Influenza A virus (FluA) detection rate was 1.9% (49) in 2020, but 0% (0) in 2021. The detection rates of Bordetella pertussis (BP) decreased from 1.4% (35) in 2020 to 0.5% (17) in 2021. In contrast, the detection rates of  Influenza B virus (FluB), Cytomegalovirus (CMV), Haemophilus influenzae (HI), Streptococcus pneumoniae (SP) increased from 0.3% (8), 24.7% (626), 2.0% (50) and 19.4% (491) in 2020 to 3.3% (121), 27.9% (1025), 4.6% (169), 22.8% (836) in 2021, respectively (P < 0.01). CONCLUSIONS: The detection rates of pathogens such as FluA, FluB, CMV, HI, SP, BP were statistically different between 2020 and 2021. From 2020 to 2021, the positive rates of Flu, CMV, HI and SP increased, while the positive rates of FluA and BP decreased. After the COVID-19 prevention and control measures are gradually relaxed, the positive rate of respiratory pathogens in children aged from 6 months to 6 years will increase.

Toe-lift test: a novel, simple and noninvasive in vivo method for contractile evaluation of tibialis anterior muscle.

Tibialis anterior (TA) muscle has frequently been used for scientific experiments, particularly for muscle contractile assays, because of its anatomical advantages. However, classical evaluation methods for the TA muscle, such as EMG and force transducer, require experimental skills to acquire reliable results. Furthermore, because sacrificing experimental animals is usually indispensable for both methods, sequential observations cannot be performed. Therefore, developing a simple, objective, and animal friendly evaluation system was warranted. In this article, we introduce a novel, simple, and noninvasive in vivo evaluation method for the TA muscle called the toe-lift test (TLT), which is not only easy to perform but also capable of detecting contractile strength precisely. Because the TLT does not require experimental animal sacrifice, performing assessments over time, such as in sequential observation, is possible. This novel method represents a solution to the need for a simple, noninvasive, and effective method for TA muscle contractile evaluation.

Research on the drought tolerance mechanism of Pennisetum glaucum (L.) in the root during the seedling stage.

BACKGROUND: Drought is one of the major environmental stresses resulting in a huge reduction in crop growth and biomass production. Pearl millet (Pennisetum glaucum L.) has excellent drought tolerance, and it could be used as a model plant to study drought resistance. The root is a very crucial part of plant that plays important roles in plant growth and development, which makes it a focus of research. RESULTS: In this study, we explored the mechanism of drought tolerance of pearl millet by comparing physiological and transcriptomic data under normal condition and drought treatment at three time points (1 h, 3 h and 7 h) in the root during the seedling stage. The relative electrical conductivity went up from 1 h to 7 h in both control and drought treatment groups while the content of malondialdehyde decreased. A total of 2004, 1538 and 605 differentially expressed genes were found at 1 h, 3 h and 7 h respectively and 12 genes showed up-regulation at all time points. Some of these differentially expressed genes were significantly enriched into 'metabolic processes', 'MAPK signaling pathway' and 'plant hormone signal transduction' such as the ABA signal transduction pathway in GO and KEGG enrichment analysis. CONCLUSIONS: Pearl millet was found to have a quick drought response, which may occur before 1 h that contributes to its tolerance against drought stress. These results can provide a theoretical basis to enhance the drought resistance in other plant species.

Muscle type from which satellite cells are derived plays a role in their damage response.

The aim of this study was to evaluate the response of satellite cells to muscular atrophies which possess different pathological characteristics and which were induced by distinct damages. Right lower limbs of rats were exposed to denervation or disuse and later its tibialis anterior (TA) or soleus (SOL) muscles were analyzed. After confirming their functional impairments indicated by common but distinct pathological and electrophysiological characteristics, the quantitative polymerase chain reaction analysis of Pax7 and Pax3 expressions and the number of Pax7+ve and Pax3+ve cells were analyzed sequentially at day 0, day 7, and day 14. TA muscles of both denervation- and disuse-induced atrophy models showed persisted low level of Pax7 expression from day 7 (0.91 ± 0.23 and 0.31 ± 0.07, P = 0.06, n = 6) through day 14 (1.09 ± 0.15 and 0.4 ± 0.09 [P < 0.05]). On the other hand, significant elevations were observed in Pax3 expression in both atrophy models (2.73 ± 0.46 and 2.75 ± 0.26 [P < 0.05]) at day 7. Similar to TA muscle, resembled pattern of Pax7 and Pax3 expression changes were observed between the SOL muscles of denervation- and disused-atrophy models. These trends were further confirmed by the changes in Pax7+ve and Pax3+ve cell numbers of TA and SOL muscles in both atrophy models. Despite the distinct pathological findings, similar patterns in the changes of Pax3 and Pax7 expressions and the changes of Pax7+ve and Pax3+ve cell numbers were observed between the denervation- and disuse-induced atrophy models and this commonality was admitted among the muscle type. Therefore, we claim that the muscle regeneration orchestrated by satellite cells was governed by the muscle type in which satellite cells reside.

Metal-free oxysulfonylation and aminosulfonylation of alkenyl oximes: synthesis of sulfonylated isoxazolines and cyclic nitrones.

Intramolecular oxysulfonylation of alkenyl oximes was reported. Using iodine as the catalyst, TBHP as the oxidant, and sulfonyl hydrazides as the sulfonyl radical source, a variety of sulfonylated isoxazolines were obtained in moderate to excellent yields. Cyclic nitrones could also be readily obtained under the same conditions.

Iodine-mediated aminosulfonylation of alkenyl sulfonamides with sulfonyl hydrazides: synthesis of sulfonylmethyl piperidines, pyrrolidines and pyrazolines.

An aminosulfonylation of alkenyl sulfonamides was reported. Using iodine as the catalyst, TBHP as the oxidant, and sulfonyl hydrazides as the sulfonyl radical sources, a variety of sulfonylmethyl piperidines, pyrrolidines and pyrazolines were obtained in moderate to excellent yields.

Realizing Efficient EMG-Based Prosthetic Control Strategy.

As an integral part of the body, the limb poses dexterous and fine motor grasping and sensing capabilities that enable humans to effectively communicate with their environment during activities of daily living (ADL). Hence, limb loss severely limits individuals' ability especially when they need to perform tasks requiring their limb functions during ADL, thus leading to decreased quality of life. To effectively restore limb functions in amputees, the advanced prostheses that are controlled by electromyography (EMG) signal have been widely investigated and used. Since EMG signals reflect neural activity, they would contain information on the muscle activation related to limb motions. Pattern recognition-based myoelectric control is an important branch of the EMG-based prosthetic control. And the EMG-based prosthetic control theoretically supports multiple degrees of freedom movements  that allows amputees to intuitively manipulate the device. This chapter focuses on EMG-based prosthetic control strategy that involves utilizing intelligent computational technique to decode upper limb movement intentions from which control commands are derived. Additionally, different techniques/methods for improving the overall performance of EMG-based prostheses control strategy were introduced and discussed in this chapter.

A transient protective effect of low-level laser irradiation against disuse-induced atrophy of rats.

Satellite cells, a population of skeletal muscular stem cells, are generally recognized as the main and, possibly, the sole source of postnatal muscle regeneration. Previous studies have revealed the potential of low-level laser (LLL) irradiation in promoting satellite cell proliferation, which, thereby, boosts the recovery of skeletal muscle from atrophy. The purpose of this study is to investigate the beneficial effect of LLL on disuse-induced atrophy. The optimal irradiation condition of LLL (808 nm) enhancing the proliferation of Pax7+ve cells, isolated from tibialis anterior (TA) muscle, was examined and applied on TA muscle of disuse-induced atrophy model of the rats accordingly. Healthy rats were used as the control. On one hand, transiently, LLL was able to postpone the progression of atrophy for 1 week through a reduction of apoptosis in Pax7-veMyoD+ve (myocyte) population. Simultaneously, a significant enhancement was observed in Pax7+veMyoD+ve population; however, most of the increased cells underwent apoptosis since the second week, which suggested an impaired maturation of the population. On the other hand, in normal control rats with LLL irradiation, a significant increase in Pax7+veMyoD+ve cells and a significant decrease of apoptosis were observed. As a result, a strengthened muscle contraction was observed. Our data showed the capability of LLL in postponing the progression of disuse-induced atrophy for the first time. Furthermore, the result of normal rats with LLL irradiation showed the effectiveness of LLL to strengthen muscle contraction in healthy control.

A Convolution Component-Based Method with Attention Mechanism for Travel-Time Prediction.

Deep learning approaches have been recently applied to traffic prediction because of their ability to extract features of traffic data. While convolutional neural networks may improve the predictive accuracy by transiting traffic data to images and extracting features in the images, the convolutional results can be improved by using the global-level representation that is a direct way to extract features. The time intervals are not considered as aspects of convolutional neural networks for traffic prediction. The attention mechanism may adaptively select a sequence of regions and only process the selected regions to better extract features when aspects are considered. In this paper, we propose the attention mechanism over the convolutional result for traffic prediction. The proposed method is based on multiple links. The time interval is considered as the aspect of attention mechanism. Based on the dataset provided by Highways England, the experimental results show that the proposed method can achieve better accuracy than the baseline methods.

An LSTM-Based Method with Attention Mechanism for Travel Time Prediction.

Traffic prediction is based on modeling the complex non-linear spatiotemporal traffic dynamics in road network. In recent years, Long Short-Term Memory has been applied to traffic prediction, achieving better performance. The existing Long Short-Term Memory methods for traffic prediction have two drawbacks: they do not use the departure time through the links for traffic prediction, and the way of modeling long-term dependence in time series is not direct in terms of traffic prediction. Attention mechanism is implemented by constructing a neural network according to its task and has recently demonstrated success in a wide range of tasks. In this paper, we propose an Long Short-Term Memory-based method with attention mechanism for travel time prediction. We present the proposed model in a tree structure. The proposed model substitutes a tree structure with attention mechanism for the unfold way of standard Long Short-Term Memory to construct the depth of Long Short-Term Memory and modeling long-term dependence. The attention mechanism is over the output layer of each Long Short-Term Memory unit. The departure time is used as the aspect of the attention mechanism and the attention mechanism integrates departure time into the proposed model. We use AdaGrad method for training the proposed model. Based on the datasets provided by Highways England, the experimental results show that the proposed model can achieve better accuracy than the Long Short-Term Memory and other baseline methods. The case study suggests that the departure time is effectively employed by using attention mechanism.

Adaptable interaction between aquaporin-1 and band 3 reveals a potential role of water channel in blood CO2 transport.

Human CO2 respiration requires rapid conversion between CO2 and HCO3- Carbonic anhydrase II facilitates this reversible reaction inside red blood cells, and band 3 [anion exchanger 1 (AE1)] provides a passage for HCO3- flux across the cell membrane. These 2 proteins are core components of the CO2 transport metabolon. Intracellular H2O is necessary for CO2/HCO3- conversion. However, abundantly expressed aquaporin 1 (AQP1) in erythrocytes is thought not to be part of band 3 complexes or the CO2 transport metabolon. To solve this conundrum, we used Förster resonance energy transfer (FRET) measured by fluorescence lifetime imaging (FLIM-FRET) and identified interaction between aquaporin-1 and band 3 at a distance of 8 nm, within the range of dipole-dipole interaction. Notably, their interaction was adaptable to membrane tonicity changes. This suggests that the function of AQP1 in tonicity response could be coupled or correlated to its function in band 3-mediated CO2/HCO3- exchange. By demonstrating AQP1 as a mobile component of the CO2 transport metabolon, our results uncover a potential role of water channel in blood CO2 transport and respiration.-Hsu, K., Lee, T.-Y., Periasamy, A., Kao, F.-J., Li, L.-T., Lin, C.-Y., Lin, H.-J., Lin, M. Adaptable interaction between aquaporin-1 and band 3 reveals a potential role of water channel in blood CO2 transport.

Energy-Aware Computation Offloading of IoT Sensors in Cloudlet-Based Mobile Edge Computing.

Mobile edge computing is proposed as a promising computing paradigm to relieve the excessive burden of data centers and mobile networks, which is induced by the rapid growth of Internet of Things (IoT). This work introduces the cloud-assisted multi-cloudlet framework to provision scalable services in cloudlet-based mobile edge computing. Due to the constrained computation resources of cloudlets and limited communication resources of wireless access points (APs), IoT sensors with identical computation offloading decisions interact with each other. To optimize the processing delay and energy consumption of computation tasks, theoretic analysis of the computation offloading decision problem of IoT sensors is presented in this paper. In more detail, the computation offloading decision problem of IoT sensors is formulated as a computation offloading game and the condition of Nash equilibrium is derived by introducing the tool of a potential game. By exploiting the finite improvement property of the game, the Computation Offloading Decision (COD) algorithm is designed to provide decentralized computation offloading strategies for IoT sensors. Simulation results demonstrate that the COD algorithm can significantly reduce the system cost compared with the random-selection algorithm and the cloud-first algorithm. Furthermore, the COD algorithm can scale well with increasing IoT sensors.

Autocrine parathyroid hormone-like hormone promotes intrahepatic cholangiocarcinoma cell proliferation via increased ERK/JNK-ATF2-cyclinD1 signaling.

BACKGROUND AND AIMS: Intrahepatic cholangiocarcinoma (ICC) is an aggressive tumor with a high fatality rate. It was recently found that parathyroid hormone-like hormone (PTHLH) was frequently overexpressed in ICC compared with non-tumor tissue. This study aimed to elucidate the underlying mechanisms of PTHLH in ICC development. METHODS: The CCK-8 assay, colony formation assays, flow cytometry and a xenograft model were used to examine the role of PTHLH in ICC cells proliferation. Immunohistochemistry (IHC) and western blot assays were used to detect target proteins. Luciferase reporter, chromatin immunoprecipitation (ChIP) and DNA pull-down assays were used to verify the transcription regulation of activating transcription factor-2 (ATF2). RESULTS: PTHLH was significantly upregulated in ICC compared with adjacent and normal tissues. Upregulation of PTHLH indicated a poor pathological differentiation and intrahepatic metastasis. Functional study demonstrated that PTHLH silencing markedly suppressed ICC cells growth, while specific overexpression of PTHLH has the opposite effect. Mechanistically, secreted PTHLH could promote ICC cell growth by activating extracellular signal-related kinase (ERK) and c-Jun N-terminal kinase (JNK) signaling pathways, and subsequently upregulated ATF2 and cyclinD1 expression. Further study found that the promoter activity of PTHLH were negatively regulated by ATF2, indicating that a negative feedback loop exists. CONCLUSIONS: Our findings demonstrated that the ICC-secreted PTHLH plays a characteristic growth-promoting role through activating the canonical ERK/JNK-ATF2-cyclinD1 signaling pathways in ICC development. We identified a negative feedback loop formed by ATF2 and PTHLH. In this study, we explored the therapeutic implication for ICC patients.

Trust Model of Wireless Sensor Networks and Its Application in Data Fusion.

In order to ensure the reliability and credibility of the data in wireless sensor networks (WSNs), this paper proposes a trust evaluation model and data fusion mechanism based on trust. First of all, it gives the model structure. Then, the calculation rules of trust are given. In the trust evaluation model, comprehensive trust consists of three parts: behavior trust, data trust, and historical trust. Data trust can be calculated by processing the sensor data. Based on the behavior of nodes in sensing and forwarding, the behavior trust is obtained. The initial value of historical trust is set to the maximum and updated with comprehensive trust. Comprehensive trust can be obtained by weighted calculation, and then the model is used to construct the trust list and guide the process of data fusion. Using the trust model, simulation results indicate that energy consumption can be reduced by an average of 15%. The detection rate of abnormal nodes is at least 10% higher than that of the lightweight and dependable trust system (LDTS) model. Therefore, this model has good performance in ensuring the reliability and credibility of the data. Moreover, the energy consumption of transmitting was greatly reduced.

A PetriNet-Based Approach for Supporting Traceability in Cyber-Physical Manufacturing Systems.

With the growing popularity of complex dynamic activities in manufacturing processes, traceability of the entire life of every product has drawn significant attention especially for food, clinical materials, and similar items. This paper studies the traceability issue in cyber-physical manufacturing systems from a theoretical viewpoint. Petri net models are generalized for formulating dynamic manufacturing processes, based on which a detailed approach for enabling traceability analysis is presented. Models as well as algorithms are carefully designed, which can trace back the lifecycle of a possibly contaminated item. A practical prototype system for supporting traceability is designed, and a real-life case study of a quality control system for bee products is presented to validate the effectiveness of the approach.

Comparative genomics of grass EST libraries reveals previously uncharacterized splicing events in crop plants.

BACKGROUND: Crop plants such as rice, maize and sorghum play economically-important roles as main sources of food, fuel, and animal feed. However, current genome annotations of crop plants still suffer false-positive predictions; a more comprehensive registry of alternative splicing (AS) events is also in demand. Comparative genomics of crop plants is largely unexplored. RESULTS: We performed a large-scale comparative analysis (ExonFinder) of the expressed sequence tag (EST) library from nine grass plants against three crop genomes (rice, maize, and sorghum) and identified 2,879 previously-unannotated exons (i.e., novel exons) in the three crops. We validated 81% of the tested exons by RT-PCR-sequencing, supporting the effectiveness of our in silico strategy. Evolutionary analysis reveals that the novel exons, comparing with their flanking annotated ones, are generally under weaker selection pressure at the protein level, but under stronger pressure at the RNA level, suggesting that most of the novel exons also represent novel alternatively spliced variants (ASVs). However, we also observed the consistency of evolutionary rates between certain novel exons and their flanking exons, which provided further evidence of their co-occurrence in the transcripts, suggesting that previously-annotated isoforms might be subject to erroneous predictions. Our validation showed that 54% of the tested genes expressed the newly-identified isoforms that contained the novel exons, rather than the previously-annotated isoforms that excluded them. The consistent results were steadily observed across cultivated (Oryza sativa and O. glaberrima) and wild (O. rufipogon and O. nivara) rice species, asserting the necessity of our curation of the crop genome annotations. Our comparative analyses also inferred the common ancestral transcriptome of grass plants and gain- and loss-of-ASV events. CONCLUSIONS: We have reannotated the rice, maize, and sorghum genomes, and showed that evolutionary rates might serve as an indicator for determining whether the identified exons were alternatively spliced. This study not only presents an effective in silico strategy for the improvement of plant annotations, but also provides further insights into the role of AS events in the evolution and domestication of crop plants. ExonFinder and the novel exons/ASVs identified are publicly accessible at http://exonfinder.sourceforge.net/ .

Determination of Phenolic Compounds in Environmental Water by HPLC Combination with On-Line Solid-Phase Extraction Using Molecularly Imprinted Polymers.

A novel molecularly imprinted polymer (MIP) was synthesized using halloysite nanotubes (HNT) as matrix, ß-cyclodextrin (ß-CD) and methyl propyl acid (MAA) as functional monomers, and 2,4,6-TCP as template molecule by graft copolymerization. Infrared spectroscopy and transmission electron microscopy (TEM) were used to characterize the as-synthesized imprinted polymer. The selective recognizability of the MIP towards four phenolic analogs were determined and the recognition coefficients for 2,4,6-TCP, 2,6-DCP, 4-CP and phenol were found to be 2.17, 1.85, 2.02 and 1.36, respectively. Using as the packing material of solid-phase extraction, the imprinted polymer has been applied to on-line extraction of the four phenolic compounds in environmental water. The corresponding analytical methods to determine these four phenolic compounds have been developed. Good linear relationships were obtained over the range of 0.05-5.0 mg x L(-1). The average recoveries for spiked samples were in the range of 74.8-97.2%, and the detection limits for 2,4,6-TCP, 2,6-DCP, p-chlorophenol, phenol were 0.19, 0.20, 0.75, 0.73 mg x L(-1), respectively. The method is rapid, accurate and high selectivity. It was feasible for the determination of trace level phenolic compounds in environmental samples.

Respiratory virus infections among children in South China.

Acute respiratory tract infection is an important cause of morbidity and mortality with a worldwide disease burden. This study aimed to determine the prevalence and clinical characteristics of children with viral-induced acute respiratory tract infection, in Southern China. Nasopharyngeal aspirate samples from 1,980 pediatric patients with suspected acute respiratory tract infection, and 82 samples from healthy subject controls were collected for routine examination at the Second Affiliated Hospital of Shantou University Medical College, from October 2007 to August 2011. Specimens were tested by multiplex polymerase chain reaction (mPCR). At least one or more viruses were detected from 1,087 samples (54.9%). These included laboratory confirmations for 446 respiratory syncytial virus (RSV), 386 influenza virus A (FluA), 315 human rhinovirus (HRV), 135 human bocavirus (HBoV), 119 Parainfluenza virus 3 (PIV3), 82 Parainfluenza virus 1 (PIV1), 66 adenovirus (ADV), 53 WU polyomavirus (WUPyV), 52 human metapneumovirus (hMPV), and 29 influenza virus B (FluB) samples. Samples from healthy subjects were negative for any virus. Of the patients with positive specimens, 107 (9.8%) were admitted to pediatric intensive care unit (PICU). Co-infection with at least two of the viral pathogens under study was observed in 325 of the 1,980 patients (16.4% of the total number of cases). These findings may help in the diagnosis of viral infections of the respiratory tract in children, and help to consider current and potential therapeutic approaches for the treatment of acute respiratory tract infection, and further respiratory complications.

A rotary transformer cross-subject model for continuous estimation of finger joints kinematics and a transfer learning approach for new subjects.

Introduction: Surface Electromyographic (sEMG) signals are widely utilized for estimating finger kinematics continuously in human-machine interfaces (HMI), and deep learning approaches are crucial in constructing the models. At present, most models are extracted on specific subjects and do not have cross-subject generalizability. Considering the erratic nature of sEMG signals, a model trained on a specific subject cannot be directly applied to other subjects. Therefore, in this study, we proposed a cross-subject model based on the Rotary Transformer (RoFormer) to extract features of multiple subjects for continuous estimation kinematics and extend it to new subjects by adversarial transfer learning (ATL) approach. Methods: We utilized the new subject's training data and an ATL approach to calibrate the cross-subject model. To improve the performance of the classic transformer network, we compare the impact of different position embeddings on model performance, including learnable absolute position embedding, Sinusoidal absolute position embedding, and Rotary Position Embedding (RoPE), and eventually selected RoPE. We conducted experiments on 10 randomly selected subjects from the NinaproDB2 dataset, using Pearson correlation coefficient (CC), normalized root mean square error (NRMSE), and coefficient of determination (R2) as performance metrics. Results: The proposed model was compared with four other models including LSTM, TCN, Transformer, and CNN-Attention. The results demonstrated that both in cross-subject and subject-specific cases the performance of RoFormer was significantly better than the other four models. Additionally, the ATL approach improves the generalization performance of the cross-subject model better than the fine-tuning (FT) transfer learning approach. Discussion: The findings indicate that the proposed RoFormer-based method with an ATL approach has the potential for practical applications in robot hand control and other HMI settings. The model's superior performance suggests its suitability for continuous estimation of finger kinematics across different subjects, addressing the limitations of subject-specific models.