Not exclusively the activity, but the sweet spot: a dehydrogenase point mutation synergistically boosts activity, substrate tolerance, thermal stability and yield.

Catalytic activity is undoubtedly a key focus in enzyme engineering. The complicated reaction conditions hinder some enzymes from industrialization even though they have relatively promising activity. This has occurred to some dehydrogenases. Hydroxysteroid dehydrogenases (HSDHs) specifically catalyze the conversion between hydroxyl and keto groups, and hold immense potential in the synthesis of steroid medicines. We underscored the importance of 7α-HSDH activity, and analyzed the overall robustness and underlying mechanisms. Employing a high-throughput screening approach, we comprehensively assessed a mutation library, and obtained a mutant with enhanced enzymatic activity and overall stability/tolerance. The superior mutant (I201M) was identified to harbor improved thermal stability, substrate susceptibility, cofactor affinity, as well as the yield. This mutant displayed a 1.88-fold increase in enzymatic activity, a 1.37-fold improvement in substrate tolerance, and a 1.45-fold increase in thermal stability when compared with the wild type (WT) enzyme. The I201M mutant showed a 2.25-fold increase in the kcat/KM ratio (indicative of a stronger binding affinity for the cofactor). This mutant did not exhibit the highest enzyme activity compared with all the tested mutants, but these improved characteristics contributed synergistically to the highest yield. When a substrate at 100 mM was present, the 24 h yield by I201M reached 89.7%, significantly higher than the 61.2% yield elicited by the WT enzyme. This is the first report revealing enhancement of the catalytic efficiency, cofactor affinity, substrate tolerance, and thermal stability of NAD(H)-dependent 7α-HSDH through a single-point mutation. The mutated enzyme reached the highest enzymatic activity of 7α-HSDH ever reported. High enzymatic activity is undoubtedly crucial for enabling the industrialization of an enzyme. Our findings demonstrated that, when compared with other mutants boasting even higher enzymatic activity, mutants with excellent overall robustness were superior for industrial applications. This principle was exemplified by highly active enzymes such as 7α-HSDH.

Characteristic analysis of epileptic brain network based on attention mechanism.

Constructing an efficient and accurate epilepsy detection system is an urgent research task. In this paper, we developed an EEG-based multi-frequency multilayer brain network (MMBN) and an attentional mechanism based convolutional neural network (AM-CNN) model to study epilepsy detection. Specifically, based on the multi-frequency characteristics of the brain, we first use wavelet packet decomposition and reconstruction methods to divide the original EEG signals into eight frequency bands, and then construct MMBN through correlation analysis between brain regions, where each layer corresponds to a specific frequency band. The time, frequency and channel related information of EEG signals are mapped into the multilayer network topology. On this basis, a multi-branch AM-CNN model is designed, which completely matches the multilayer structure of the proposed brain network. The experimental results on public CHB-MIT datasets show that eight frequency bands divided in this work are all helpful for epilepsy detection, and the fusion of multi-frequency information can effectively decode the epileptic brain state, achieving accurate detection of epilepsy with an average accuracy of 99.75%, sensitivity of 99.43%, and specificity of 99.83%. All of these provide reliable technical solutions for EEG-based neurological disease detection, especially for epilepsy detection.

Facile Strategy for Efficient Charge Separation and High Photoactivity of Mixed-Linker MOFs.

Two new sets of UiO-Zr metal-organic framework (MOF) bearing mixed linkers BDC-(SCH3)2 and BDC-(SOCH3)2 that have different band gaps and edges were prepared through post oxidation and direct methods, namely, UiO-66-(SCH3)2-xh (x = 4, 9, 12 oxidation hours) and UiO-66-(SOCH3)x(SCH3)2-x (x = 0, 0.4, 0.6, 2), respectively. These composites with stoichiometric components were fully characterized via proton nuclear magnetic resonance (1H NMR) spectroscopy, powder X-ray diffraction (PXRD), transmission electron microscopy (TEM), Fourier-transform infrared (FT-IR) spectra, Brunauer-Emmett-Teller (BET), photo electrochemical measurements, and femtosecond transient absorption (fs-TA) spectroscopy. The structure, electronic property, and photoresponsive and catalytic ability as the functions of the molar ratio of linkers and the synthetic protocol were first investigated. The mixed-linker UiO-66-(SCH3)2-xh and UiO-66-(SOCH3)x(SCH3)2-x exhibited improved performances as compared to the UiO-66-(SCH3)2 and UiO-66-(SOCH3)2 possessing neat linkers only. Their photo response and catalytic activity varied with different linker ratios. For UiO-66-(SCH3)2-xh, the performance increased with the increasing linker BDC-(SOCH3)2 ratio upon oxidation but reached the highest as the BDC-(SOCH3)2 being of 24.4% in UiO-66-(SCH3)2-9h. In comparison, the best photocurrent (80.74 uA/cm-2) and the highest H2 generation rate (2018.8 µmol g-1 h-1) (λ > 400 nm) in UiO-66-(SCH3)2-9h are about twice those of UiO-66-(SOCH3)0.4(SCH3)1.6 obtained by direct synthesis, although the linker BDC-(SOCH3)2 ratio of those two composites is almost the same (24.4% vs 23.9%). Recorded shorter lifetime and higher charge separation efficiency of the former than those of the latter suggest the postsynthetic protocol as the efficient method for achieving the mixed-liner-MOF-based photocatalyst with high performance. A new type-II tailored homojunction is proposed in these mixed-linker MOFs for their efficient charge separation and improved activity.

Diffusion weighted imaging for the differential diagnosis of benign vs. malignant ovarian neoplasms.

In order to assess the diagnostic accuracy of diffusion weighted imaging (DWI) in differentiating between benign and malignant ovarian neoplasms, a systemic meta-analysis was conducted. Relevant studies were retrieved from scientific literature databases, including the PubMed, Wiley, EBSCO, Ovid, Web of Science, Wanfang, China National Knowledge Infrastructure and VIP databases. Following a multi-step screening and study selection process, the relevant data was extracted for use in the present study. Statistical analyses were performed using Meta-disc software version 1.4 and STATA statistical software version 12.0. A total of 285 articles were retrieved from the database searches. Following a careful screening process, 10 case-control studies were selected for the present meta-analysis. The 10 studies investigated the efficacy of DWI in diagnosing ovarian neoplasms, and included a combined total of 1,159 subjects, of which 559 patients had malignant lesions and 600 had benign lesions. The results showed that the pooled sensitivity, pooled specificity, pooled positive likelihood ratio, pooled negative likelihood ratio, pooled diagnostic odds ratio (DOR) and area under the curve of the summary receiver operating characteristics curve of DWI for differentiating between benign and malignant ovarian neoplasms were 0.93, 0.89, 7.58, 0.10, 85.33 and 0.95, respectively. A subgroup analysis based on ethnicity revealed no significant difference between Asians and Caucasians. Another subgroup analysis by magnetic resonance imaging (MRI) type showed that the DORs for GE Healthcare Life Sciences and Siemens AG machines were 100.76 [95% confidence interval (CI), 65.28-155.53] and 30.85 (95% CI, 10.40-91.53), respectively; this indicates that the diagnostic efficiency of the GE Healthcare Life Sciences MRI is superior compared with the Siemens AG MRI. The DWI demonstrated an excellent diagnostic performance in discriminating between benign and malignant ovarian neoplasms, and predicted the surgical outcome in ovarian neoplasms.