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Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.

Although randomised controlled trials are considered the gold standard in clinical research, they are not always feasible due to limitations in the study population, challenges in obtaining evidence, high costs and ethical considerations. As a result, single-arm trial designs have emerged as one of the methods to address these issues. Single-arm trials are commonly applied to study advanced-stage cancer, rare diseases, emerging infectious diseases, new treatment methods and medical devices. Single-arm trials have certain ethical advantages over randomised controlled trials, such as providing equitable treatment, respecting patient preferences, addressing rare diseases and timely management of adverse events. While single-arm trials do not adhere to the principles of randomisation and blinding in terms of scientific rigour, they still incorporate principles of control, balance and replication, making the design scientifically reasonable. Compared with randomised controlled trials, single-arm trials require fewer sample sizes and have shorter trial durations, which can help save costs. Compared with cohort studies, single-arm trials involve intervention measures and reduce external interference, resulting in higher levels of evidence. However, single-arm trials also have limitations. Without a parallel control group, there may be biases in interpreting the results. In addition, single-arm trials cannot meet the requirements of randomisation and blinding, thereby limiting their evidence capacity compared with randomised controlled trials. Therefore, researchers consider using single-arm trials as a trial design method only when randomised controlled trials are not feasible.

Litter input plays important roles in controlling soil aggregation and aggregate carbon (C) content. However, the effects of litter input on soil aggregate C turnover in different forest types remain unclear. We examined the changes of aggregate mass proportion, and the litter-derived and native C content among soil aggregates after three years of aboveground and root litter input, using C isotope tracing in a natural forest, a Chinese fir ( ) plantation, and a masson pine ( ) plantation in southeastern China. Belowground root litter rather than aboveground litter input enhanced soil aggregation. Litter input increased total C content across all aggregates, and the effects were no different between aboveground litter and belowground root litter input except for the >2 mm fraction. Belowground root litter input led to less native C content across three forest types. However, belowground root litter input resulted in more formation of litter-derived C than aboveground litter input under masson pine plantations, but not for both natural forest and Chinese fire plantation, suggesting a different effect of litter input on the litter-derived C formation among forest types. In addition, forest type affected soil aggregation and aggregate C turnover, and the differences in litter quantity and litter C:N ratio can explain the changes in soil aggregation and aggregate C turnover among forest types. Our results imply that belowground root litter input plays a more important role in controlling soil aggregation and aggregate C turnover than aboveground litter, and the impact on newly litter-derived C formation depends on forest type.

HighlightsPlasma-assisted phosphorization has been used to prepare defect-rich metal phosphides.The p-NiCoP/NCF@CC shows high activities and excellent stability for the hydrogen evolution reaction and the oxygen evolution reaction.The p-NiCoP/NCF@CC shows great potential for overall water splitting.This work reports the use of defect engineering and carbon supporting to achieve metal-doped phosphides with high activities and stabilities for the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) in alkaline media. Specifically, the nitrogen-doped carbon nanofiber-supported Ni-doped CoP3 with rich P defects (Pv·) on the carbon cloth (p-NiCoP/NCFs@CC) is synthesized through a plasma-assisted phosphorization method. The p-NiCoP/NCFs@CC is an efficient and stable catalyst for the HER and the OER. It only needs overpotentials of 107 and 306 mV to drive 100 mA cm−2 for the HER and the OER, respectively. Its catalytic activities are higher than those of other catalysts reported recently. The high activities of the p-NiCoP/NCFs@CC mainly arise from its peculiar structural features. The density functional theory calculation indicates that the Pv· richness, the Ni doping, and the carbon supporting can optimize the adsorption of the H atoms at the catalyst surface and promote the strong electronic couplings between the carbon nanofiber-supported p-NiCoP with the surface oxide layer formed during the OER process. This gives the p-NiCoP/NCFs@CC with the high activities for the HER and the OER. When used in alkaline water electrolyzers, the p-NiCoP/NCFs@CC shows the superior activity and excellent stability for overall water splitting.

Renal epithelioid angiomyolipoma (EAML) is frequently misdiagnosed due to nonspecific imaging findings. This study aimed to explore the radiographic characteristics of EAML, with the goal of enhancing the accuracy of preoperative diagnoses. A total of 27 patients with histopathologically confirmed renal EAML were included in the study. We retrospectively reviewed the radiographic features and analyzed the differences between tumors with a cut-off diameter of 40 mm. The majority of the lesions were isolated (25/27, 92.59%) and were predominantly found in females (18/27, 66.67%). ‌CT images revealed that most lesions were hyperdense, with fat detected in 13 cases. Small lesions were more likely to exhibit rapid wash-in and wash-out enhancement ( p  = 0.04), whereas abnormal vessels were more commonly found in large lesions. Tumors with higher risk stratification tended to show persistent or delayed enhancement on CT images. The imaging manifestations of renal EAML are diverse. After enhancement, small lesions are more likely to display rapid wash-in and wash-out patterns on CT images, whereas large lesions are more likely to exhibit abnormal vessels within or surrounding the tumor.

Host–guest binding, despite the relatively simple structural and chemical features of individual components, still poses a challenge in computational modelling. The extreme underperformance of standard end-point methods in host–guest binding makes them practically useless. In the current work, we explore a potentially promising modification of the three-trajectory realization. The alteration couples the binding-induced structural reorganization into free energy estimation and suffers from dramatic fluctuations in internal energies in protein–ligand situations. Fortunately, the relatively small size of host–guest systems minimizes the magnitude of internal fluctuations and makes the three-trajectory realization practically suitable. Due to the incorporation of intra-molecular interactions in free energy estimation, a strong dependence on the force field parameters could be incurred. Thus, a term-specific investigation of transferable GAFF derivatives is presented, and noticeable differences in many aspects are identified between commonly applied GAFF and GAFF2. These force-field differences lead to different dynamic behaviors of the macrocyclic host, which ultimately would influence the end-point sampling and binding thermodynamics. Therefore, the three-trajectory end-point free energy calculations are performed with both GAFF versions. Additionally, due to the noticeable differences between host dynamics under GAFF and GAFF2, we add additional benchmarks of the single-trajectory end-point calculations. When only the ranks of binding affinities are pursued, the three-trajectory realization performs very well, comparable to and even better than the regressed PBSA_E scoring function and the dielectric constant-variable regime. With the GAFF parameter set, the TIP3P water in explicit solvent sampling and either PB or GB implicit solvent model in free energy estimation, the predictive power of the three-trajectory realization in ranking calculations surpasses all existing end-point methods on this dataset. We further combine the three-trajectory realization with another promising modified end-point regime of varying the interior dielectric constant. The combined regime does not incur sizable improvements for ranks and deviations from experiment exhibit non-monotonic variations.

Background Previous data have reported that Sentrin/SUMO-specific protease 6 (SENP6) is involved in ischaemic brain injury and induces neuronal apoptosis after cerebral ischaemia, but the role of SENP6 in microglia-induced neuroinflammation and its underlying mechanism remain poorly understood. This research systematically explored the function and potential mechanism of SENP6 in microglia-induced neuroinflammation after ischaemic stroke. Results We first identified an increased protein level of SENP6 in microglia after cerebral ischaemia. Then, we demonstrated that SENP6 promoted detrimental microglial phenotype polarization. Specifically, SENP6-mediated de-SUMOylation of ANXA1 targeted the IκB kinase (IKK) complex and selectively inhibited the autophagic degradation of IKKα in an NBR1-dependent manner, activating the NF-κB pathway and enhancing proinflammatory cytokine expression. In addition, downregulation of SENP6 in microglia effectively reduced cocultured neuronal damage induced by ischaemic stroke. More importantly, we employed an AAV-based technique to specifically knockdown SENP6 in microglia/macrophages, and in vivo experiments showed that SENP6 inhibition in microglia/macrophages notably lessened brain ischaemic infarct size, decreased neurological deficit scores, and ameliorated motor and cognitive function in mice subjected to cerebral ischaemia surgery. Conclusion We demonstrated a previously unidentified mechanism by which SENP6-mediated ANXA1 de-SUMOylation regulates microglial polarization and our results strongly indicated that in microglia, inhibition of SENP6 may be a crucial beneficial therapeutic strategy for ischaemic stroke. Graphical Abstract

A transfer learning-based end-to-end speech recognition approach is presented in two levels in our framework. Firstly, a feature extraction approach combining multilingual deep neural network (DNN) training with matrix factorization algorithm is introduced to extract high-level features. Secondly, the advantage of connectionist temporal classification (CTC) is transferred to the target attention-based model through a joint CTC-attention model composed of shallow recurrent neural networks (RNNs) on top of the proposed features. The experimental results show that the proposed transfer learning approach achieved the best performance among all end-to-end methods and could be comparable to the state-of-the-art speech recognition system for TIMIT when further jointly decoded with a RNN language model.

Objective Bleomycin is an important chemotherapeutic drug that activates premature senescence to decrease the tumorigenic process. We aimed to investigate the role of phosphatase and tensin homolog deleted on chromosome ten (PTEN) in bleomycin-induced premature senescence in lung cancer cells. Methods Human lung cancer A549 cells were incubated in the presence of different concentrations of bleomycin for 5 days. A lentivirus vector was used to silence the PTEN gene, followed by stimulation with bleomycin (1 µg/mL). Changes were evaluated by senescence-associated β-galactosidase staining, reverse transcription-polymerase chain reaction, and western blot. Results Treatment with bleomycin induced premature senescence. PTEN expression was decreased and key downstream molecules in the phosphoinositide 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway were gradually activated following bleomycin treatment. Silencing PTEN reduced autophagy and accelerated senescence of A549 cells. Autophagy levels were also increased and senescence markers were reduced after inhibiting mTOR. Conclusions Downregulation of PTEN mediates bleomycin-induced premature senescence in lung cancer cells by suppressing autophagy via the PI3K/Akt/mTOR pathway. These findings provide new insights into the potential role of PTEN as a molecular target for cancer chemotherapy.

Background It has been reported that co-rumination and transition shocks significantly influence effective communication in clinical practice. However, previous research has not sufficiently explored the specific relationships between these two characteristics and their gender differences among nursing interns. Objective The objective of this study was to evaluate the states of co-rumination and transition shock among current nursing interns during clinical placements, as well as to determine whether gender differences affect these two traits and how exploiting such differences can improve nurses’ co-rumination. Methods A cross-sectional study design was adopted. We gathered data from a convenient sample of 505 nursing interns from a grade A tertiary hospital in Anhui, China. This study included Data collected using the Co-Rumination Questionnaire (CRQ-9) and Transition Shock Scale for Undergraduate Nursing Students (UNSTS). The data were analyzed using an independent samples t-test, Pearson correlation, and hierarchical multiple linear regression. Results There was no significant difference in UNSTS scores between male and female nursing interns, but male nursing interns had lower CRQ-9 scores ( P  < 0.05). This study found that Transition Shock was the most critical factor influencing Co-Rumination variation for male and female nursing interns during clinical practice through hierarchical multiple regression analysis. Conclusions Gender differences are reflected not only in the level of co-rumination but also in the relationships between co-rumination and transition shock. Nursing educators should be aware of how gender differences can affect these two traits; this is particularly important for improving the mental health problems of nursing interns based on students’ aptitudes.