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Abstract The prevalence of autism spectrum disorders (ASDs) differs substantially between males and females, suggesting that sex-related neurodevelopmental factors are central to ASD pathogenesis. Numerous studies have suggested that abnormal brain specialization patterns and poor regional cooperation contribute to ASD pathogenesis, but relatively little is known about the related sex differences. Therefore, this study examined sex differences in brain functional specialization and cooperation among children with ASD. The autonomy index (AI) and connectivity between functionally homotopic voxels (CFH) derived from resting-state functional magnetic resonance imaging (rs-fMRI) were compared between 58 male and 13 female children with ASD. In addition, correlations were examined between regional CFH values showing significant sex differences and symptom scores on the autism behavior checklist (ABC) and childhood autism rating scale (CARS). Male children with ASD demonstrated significantly greater CFH in the left fusiform gyrus (FG) and right opercular part of the inferior frontal gyrus (IFGoperc) than female children with ASD. In addition, the CFH value of the left FG in male children with ASD was negatively correlated with total ABC score and subscale scores for sensory and social abilities. In contrast, no sex differences were detected in brain specialization. These regional abnormalities in interhemispheric cooperation among male children with ASD may provide clues to the neural mechanisms underlying sex differences in ASD symptomatology and prevalence. Autism spectrum disorders, sex, resting-state functional magnetic resonance imaging, cerebral specialization, interhemispheric cooperation.

An adaptive motion planning method is proposed for the problems of complex kinematic solution, large configuration deviation of traditional multi-joint hyper-redundant robots. Firstly, an improved trajectory tracking algorithm is proposed for the task requirement of entering and leaving a narrow working space. By discrete target trajectory and segment fitting, the computational effort can be reduced, and the adaptive trajectory tracking control can be achieved. Then a bidirectional iterative tractor trajectory planning algorithm is proposed for the robot base fixed working condition. The target trajectory is obtained based on the end-traction method. By using the geometric property of the tractrix progressive convergence, the motion range of joints near the base is gradually reduced, the stability is improved, and the energy consumption is reduced. The adaptive trajectory control in the base fixed state is achieved through bi-directional iterative tractrix accelerated convergence. Finally, a simulation model containing 12 joints and (24+1） degrees of freedom is constructed， and the effectiveness of the adaptive motion planning method for the entire process of robot operation is verified.

Objective The risk of osteochondral fracture (OCF) after patellar dislocation has been shown to be related to patellofemoral anatomy, but its relationship to patellar morphology remains unknown. The aim of this study was to investigate the associations between patellar morphology and the risk of OCF after patellar dislocation. Methods A total of 140 patients with patellar dislocation between January 2018 and June 2023 were enrolled in this study and divided into two groups. Sixty‐five patellar dislocation patients with OCF were included in the OCF group, while 75 patellar dislocation patients without OCF were included in the non‐OCF group. Computed tomography was used to compare measurements of patellar morphology including Wiberg classification, patellar width and thickness, Wiberg angle, Wiberg index, facet ratio, lateral patellar facet angle, and patellar tilt angle. A logistic regression model was performed to evaluate the correlations between patellar morphology and the risk of OCF after patellar dislocation. Receiver operating characteristic curves were used to calculate the area under the curve (AUC) and determine the diagnostic values of patellar morphology for OCF after patellar dislocation. Subgroup analyses for gender and age were conducted to compare the differences in patellar morphology of PD patients. Results Wiberg angle was significantly lower in the OCF group (p = 0.017), while Wiberg index (p = 0.002) and facet ratio (p = 0.023) were significantly higher in the OCF group. According to the results of logistic regression analysis, Wiberg angle (odds ratio [OR] = 0.96, p = 0.022) and Wiberg index (OR = 1.105, p = 0.032) were the final relevant factors for the occurrence of OCF after patellar dislocation. The AUC was 0.622 (95% confidence interval [CI]: 0.529–0.714) for Wiberg angle, 0.65 (95% CI: 0.558–0.742) for Wiberg index, and 0.702 (95% CI: 0.615–0.788) for the combination of Wiberg angle plus Wiberg index. Conclusion Wiberg angle and Wiberg index were independent risk factors for the occurrence of osteochondral fracture after patellar dislocation. Moreover, Wiberg angle, Wiberg index, and the combination of Wiberg angle plus Wiberg index had good predictive diagnostic value for the occurrence of OCF after patellar dislocation.

[Objective] To improve the drying quality of pumpkins. [Methods] This study conducted experiments on hot air drying, vacuum drying, and combined hot air-vacuum drying, these drying characteristics were evaluated and compared based on unit energy consumption, rehydration ratio, and color difference indicators. Combining BP neural network model with genetic algorithm, combined with entropy weight and weighted scoring method, a multi-objective comprehensive optimization was carried out for the combined hot air-vacuum drying of pumpkins. [Results] Under the same conditions, the highest drying efficiency was hot air drying; And the findings revealed that at drying temperatures was 55 ℃, with a moisture content transition point of 30%, the combined drying method reduced the drying time by 52.63%, compared to vacuum drying. The lowest unit energy consumption was vacuum drying; The worst rehydration performance was hot air drying. The best color was vacuum drying. The optimal drying parameters determined by the genetic algorithm combined with a BP neural network model were a hot air drying temperature of 65 ℃, conversion point moisture content of 50%, and vacuum drying temperature of 56.050 9 ℃. Verification experiments demonstrated that the average relative errors between the genetic algorithm optimized values and the experimental values for unit energy consumption, rehydration ratio, and color difference were 2.5%, 5.53%, and 4.84%, respectively, all lower than 6%. [Conclusion] The combined hot air-vacuum drying of pumpkin integrates the advantages of both hot air drying and vacuum drying, and combined with BP neural network genetic algorithm model can optimize the process parameters for pumpkin hot air vacuum drying.

In this paper, a comprehensive study of wideband dielectric resonator antennas (DRAs) loaded with special dispersive materials is given in detail. The concept and theory for a new class of wideband and compact DRAs are introduced for the first time using the new material whose relative permittivity is inversely proportional to the frequency power of n (i.e., $\varepsilon _{r }$ (f) ${=} {k}$ / $f^{n}$ , k is a constant). Traditional DRAs are normally of limited bandwidth and unstable radiation patterns. The proposed new DRAs exhibit excellent advantages in bandwidth enhancement, size reduction, single-mode purity (predominantly supporting a single mode with minimal interference from other unwanted modes), and stable radiation patterns. The new dielectric resonator theory with wideband resonance characteristics is developed. Based on this, wideband and compact cylindrical and rectangular DRAs are designed and studied. The simulated and measured results demonstrate the merits of the proposed antennas. It is shown that without changing the structures, the percentage bandwidth of the proposed cylindrical DRA made of a dispersive material can be significantly increased to 120%, compared to the DRA using the traditional material with a constant permittivity (4%). The paper provides a new approach for making wideband and compact DRAs with stable radiation patterns for future wideband wireless communications and radar applications.

Abstract Background Extrachromosomal circular DNAs (eccDNAs) exist in human blood and somatic cells, and are essential for oncogene plasticity and drug resistance. However, the presence and impact of eccDNAs in type 2 diabetes mellitus (T2DM) remains inadequately understood. Methods We purified and sequenced the serum eccDNAs obtained from newly diagnosed T2DM patients and normal control (NC) subjects using Circle-sequencing. We validated the level of a novel circulating eccDNA named sorbin and SH3‐domain‐ containing‐1circle97206791–97208025 (SORBS1circle) in 106 newly diagnosed T2DM patients. The relationship between eccDNA SORBS1circle and clinical data was analyzed. Furthermore, we explored the source and expression level of eccDNA SORBS1circle in the high glucose and palmitate (HG/PA)-induced hepatocyte (HepG2 cell) insulin resistance model. Results A total of 22,543 and 19,195 eccDNAs were found in serum samples obtained from newly diagnosed T2DM patients and NC subjects, respectively. The T2DM patients had a greater distribution of eccDNA on chromosomes 1, 14, 16, 17, 18, 19, 20 and X. Additionally, 598 serum eccDNAs were found to be upregulated, while 856 eccDNAs were downregulated in T2DM patients compared with NC subjects. KEGG analysis demonstrated that the genes carried by eccDNAs were mainly associated with insulin resistance. Moreover, it was validated that the eccDNA SORBS1circle was significantly increased in serum of newly diagnosed T2DM patients (106 T2DM patients vs. 40 NC subjects). The serum eccDNA SORBS1circle content was positively correlated with the levels of glycosylated hemoglobin A1C (HbA1C) and homeostasis model assessment of insulin resistance (HOMA-IR) in T2DM patients. Intracellular eccDNA SORBS1circle expression was significantly enhanced in the high glucose and palmitate (HG/PA)-induced hepatocyte (HepG2 cell) insulin resistance model. Moreover, the upregulation of eccDNA SORBS1circle in the HG/PA-treated HepG2 cells was dependent on generation of apoptotic DNA fragmentation. Conclusions These results provide a preliminary understanding of the circulating eccDNA patterns at the early stage of T2DM and suggest that eccDNA SORBS1circle may be involved in the development of insulin resistance.

Abstract Because of its potent antioxidant effects, lycopene has been used in various industries including, but not limited to, food, medical, and cosmetic industries. Yarrowia lipolytica, a non-conventional yeast species, is a promising chassis due to its natural mevalonate (MVA) pathway, abundant precursor acetyl coenzyme A content, and oleaginous properties. Several gene editing tools have been developed for Y. lipolytica along with engineering strategies for tetraterpenoid production. In this study, we engineered Y. lipolytica following multi-level strategies for efficient lycopene accumulation. We first evaluated the performance of the key lycopene biosynthetic genes crtE, crtB, and crtI, expressed via ribosomal DNA (rDNA) mediated multicopy random integration in the HMG1- and GGS1-overexpressing background strain. Further improvement in lycopene production was achieved by overexpressing the key genes for MVA synthesis via non-homologous end joining (NHEJ) mediated multi-round iterative transformation. Efficient strategies in the MVA and lipid synthesis pathways were combined to improve lycopene production with a yield of 430.5 mg/L. This strain produced 121 mg/g dry cell weight of lycopene in a 5-L fed-batch fermentation system. Our findings demonstrated iterative gene integration mediated by 26S rDNA and NHEJ for the efficient production of lycopene in Y. lipolytica. These strategies can be applied to induce Y. lipolytica to produce other tetraterpenoids. Graphical Abstract

Abstract Nervonic acid, a natural fatty acid compound and also a core component of nerve fibers and nerve cells, has been widely used to prevent and treat related diseases of the brain nervous system. At present, fatty acids and their derivatives are mainly obtained by natural extraction or chemical synthesis which are limited by natural resources and production costs. In this study, the de novo synthetic pathway of nervonic acid was constructed in Yarrowia lipolytica by means of synthetic biology, and the yield of nervonic acid was further improved by metabolic engineering and fermentation optimization. Specially, heterologous elongases and desaturases derived from different organism were successfully expressed and evaluated for their potential for the production of nervonic acid in Y. lipolytica. Meanwhile, we overexpressed the genes involved in the lipid metabolism to increase the nervonic acid titer to 111.6 mg/L. In addition, the potential of adding oil as auxiliary carbon sources for nervonic acid production by the engineered Y. lipolytica was analyzed. The results indicated that supplementation with colleseed oil as an auxiliary carbon source can be beneficial for the nervonic acid productivity, which led to the highest concentration of 185.0 mg/L in this work. To summarize, this study describes that the Y. lipolytica can be used as a promising platform for the production of nervonic acid and other very long-chain fatty acids. Graphical Abstract

Sesamin (Ses) is a natural lignan abundantly present in sesame and sesame oil. Pyroptosis, a newly identified type of pro-inflammatory programmed necrosis, contributes to the development of non-alcoholic steatohepatitis (NASH) when hepatocyte pyroptosis is excessive. In this study, Ses treatment demonstrated an improvement in hepatic damage in mice with high-fat, high-cholesterol diet-induced NASH and palmitate (PA)-treated mouse primary hepatocytes. Notably, we discovered, for the first time, that Ses could alleviate hepatocyte pyroptosis both in vivo and in vitro. Furthermore, treatment with phorbol myristate acetate, a protein kinase Cδ (PKCδ) agonist, increased PKCδ phosphorylation and attenuated the protective effects of Ses against pyroptosis in PA-treated mouse primary hepatocytes. Mechanistically, Ses treatment alleviated hepatocyte pyroptosis in NASH, which was associated with the regulation of the PKCδ/nod-like receptor family CARD domain-containing protein 4/caspase-1 axis. This study introduces a novel concept and target, suggesting the potential use of functional factors in food to alleviate liver damage caused by NASH.

Taxadiene is an important precursor for the biosynthesis of highly effective anticancer drug paclitaxel, but its microbial biosynthesis yield is very low. In this study, we employed Yarrowia lipolytica as a microbial host to produce taxadiene. First, a “push–pull” strategy was adopted to increase taxadiene production by 234%. Then taxadiene synthase was fused with five solubilizing tags respectively, leading a maximum increase of 62.3% in taxadiene production when fused with SUMO. Subsequently, a multi-copy iterative integration method was used to further increase taxadiene titer, achieving the maximum titer of 23.7 mg/L in shake flask culture after three rounds of integration. Finally, the taxadiene titer was increased to 101.4 mg/L by optimization of the fed-batch fermentation conditions. This is the first report of taxadiene biosynthesis accomplished in Y. lipolytica, serving as a good example for the sustainable production of taxadiene and other terpenoids in this oleaginous yeast.

Injuries to pancreatic β-cells are intricately linked to the onset of diabetes mellitus (DM). Metformin (Met), one of the most widely prescribed medications for diabetes and metabolic disorders, has been extensively studied for its antioxidant, anti-aging, anti-glycation, and hepatoprotective activities. N6-methyladenosine (m6A) plays a crucial role in the regulation of β-cell growth and development, and its dysregulation is associated with metabolic disorders. This study aimed to elucidate the mechanistic basis of m6A involvement in the protective effects of Met against oxidative damage in pancreatic β-cells. Hydrogen peroxide (H2O2) was employed to induce β-cell damage. Remarkably, Met treatment effectively increased methylation levels and the expression of the methyltransferase METTL14, subsequently reducing H2O2-induced apoptosis. Knocking down METTL14 expression using siRNA significantly compromised cell viability. Conversely, targeted overexpression of METTL14 specifically in β-cells substantially enhanced their capacity to withstand H2O2-induced stress. Molecular evidence suggests that the anti-apoptotic properties of Met may be mediated through Bcl-xL and Bim proteins. In conclusion, our findings indicate that Met induces METTL14-mediated alterations in m6A methylation levels, thereby shielding β-cells from apoptosis and oxidative damage induced by oxidative stress.

Astaxanthin is a high value carotenoid with a broad range of commercial applications due to its superior antioxidant properties. In this study, β-carotene-producing Yarrowia lipolytica XK17 constructed in the lab was employed for astaxanthin biosynthesis. The catalytic effects of β-carotene ketolase CrtW and β-carotene hydroxylase CrtZ from various species were investigated. The PspCrtW from Paracoccus sp. and HpCrtZ# from Haematococcus pluvialis were confirmed to be the best combination in converting β-carotene. Several key bottlenecks in biomass and astaxanthin biosynthesis were effectively eliminated by optimizing the expression of the above enzymes and restoring uracil/leucine biosynthesis. In addition, the effects of astaxanthin biosynthesis on cell metabolism were investigated by integrated analysis of pathway modification and transcriptome information. After further optimization, strain DN30 was able to synthesize up to 730.3 mg/L astaxanthin in laboratory 5-L fermenter. This study provides a good metabolic strategy and a sustainable development platform for high-value carotenoid production.

Highlights 1. Effects of salinity, alkalinity and their combined impact were analysed with transcriptome and and proteomics methods in G. przewalskii. 2. The validity of transcriptome and proteome results in G. przewalskii was compared. 3. Hub genes in the adaptive responses to the combined impact of salinity and alkalinity were isolated. 4. Physiological regulation mechanisms regarding salinity, alkalinity, and salinity-alkalinity interactions were discussed.

Abstract Ansamitocin P-3 (AP-3) produced by Actinosynnema pretiosum is a potent antitumor agent. However, lack of efficient genome editing tools greatly hinders the AP-3 overproduction in A. pretiosum. To solve this problem, a tailor-made pCRISPR–Cas9apre system was developed from pCRISPR–Cas9 for increasing the accessibility of A. pretiosum to genetic engineering, by optimizing cas9 for the host codon preference and replacing pSG5 with pIJ101 replicon. Using pCRISPR–Cas9apre, five large-size gene clusters for putative competition pathway were individually deleted with homology-directed repair (HDR) and their effects on AP-3 yield were investigated. Especially, inactivation of T1PKS-15 increased AP-3 production by 27%, which was most likely due to the improved intracellular triacylglycerol (TAG) pool for essential precursor supply of AP-3 biosynthesis. To enhance a “glycolate” extender unit, two combined bidirectional promoters (BDPs) ermEp-kasOp and j23119p-kasOp were knocked into asm12-asm13 spacer in the center region of gene cluster, respectively, by pCRISPR–Cas9apre. It is shown that in the two engineered strains BDP-ek and BDP-jk, the gene transcription levels of asm13-17 were significantly upregulated to improve the methoxymalonyl-acyl carrier protein (MM-ACP) biosynthetic pathway and part of the post-PKS pathway. The AP-3 yields of BDP-ek and BDP-jk were finally increased by 30% and 50% compared to the parent strain L40. Both CRISPR–Cas9-mediated engineering strategies employed in this study contributed to the availability of AP-3 PKS extender units and paved the way for further metabolic engineering of ansamitocin overproduction. Graphical Abstract

The global market demand for natural astaxanthin is rapidly increasing owing to its safety, the potential health benefits, and the diverse applications in food and pharmaceutical industries. The major native producers of natural astaxanthin on industrial scale are the alga Haematococcus pluvialis and the yeast Xanthopyllomyces dendrorhous. However, the natural production via these native producers is facing challenges of limited yield and high cost of cultivation and extraction. Alternatively, astaxanthin production via metabolically engineered non-native microbial cell factories such as Escherichia coli, Saccharomyces cerevisiae and Yarrowia lipolytica is another promising strategy to overcome these limitations. In this review we summarize the recent scientific and biotechnological progresses on astaxanthin biosynthetic pathways, transcriptional regulations, the interrelation with lipid metabolism, engineering strategies as well as fermentation process control in major native and non-native astaxanthin producers. These progresses illuminate the prospects of producing astaxanthin by microbial cell factories on industrial scale.

Abstract Compared with the traditional environment, a connected environment in which multiple types of intelligent vehicles share roads will be more complicated. However, do changes in the traffic environment affect the driver's distraction level and distraction recognition? Relatively few studies have addressed these questions. This study constructs traditional and connected environments and conducts driving simulation experiments. Distracted driving data for 60 drivers were collected in each environment, and the one‐way repeated analysis of variance (ANOVA) method was used to select the distraction indices with significant differences as the input indices. An independent t‐test was applied to analyse changes in the distraction indices in the two environments. The results show that the distraction indices, including the standard deviation (SD) of the horizontal fixation angles, blink frequency, mean pupil diameter, mean saccade speed, SD of the steering wheel angle, mean speed and SD of the lane acceleration, differ in the two environments; therefore, the distraction recognition model in the traditional environment is no longer suitable for connected environments. A distraction state recognition model developed with a stacking‐based ensemble learning algorithm composed of a support vector machine (SVM), extreme gradient boosting (XGBoost), long short‐term memory (LSTM), and bi‐directional LSTM with an attention mechanism (AT‐Bi‐LSTM) was proposed for each environment. The recognition accuracy reaches 95.71% in the traditional environment, and the accuracy rate reaches 97.92% in the connected environment. Compared with traditional algorithms, the proposed approach yields greater recognition accuracy and can be applied in intelligent vehicle distraction early warning assistance systems to improve road safety.

ObjectivesSeveral studies have examined the effects of repetitive transcranial magnetic stimulation (rTMS) on associative memory (AM) but findings were inconsistent. Here, we aimed to test whether twice-daily rTMS could significantly improve AM.MethodsIn this single-blind, sham-controlled experiment, 40 participants were randomized to receive twice-daily sham or real rTMS sessions for five consecutive days (a total of 16,000 pulses). The stimulation target in left inferior parietal lobule (IPL) exhibiting peak functional connectivity to the left hippocampus was individually defined for each participant. Participants completed both a picture-cued word association task and Stroop test at baseline and 1 day after the final real or sham rTMS session. Effects of twice-daily rTMS on AM and Stroop test performance were compared using two-way repeated measures analysis of variance with main factors Group (real vs. sham) and Time (baseline vs. post-rTMS).ResultsThere was a significant Group × Time interaction effect. AM score was significantly enhanced in the twice-daily real group after rTMS, but this difference could not survive the post hoc analysis after multiple comparison correction. Further, AM improvement in the twice-daily real group was not superior to a previously reported once-daily rTMS group receiving 8,000 pulses. Then, we combined the twice- and once-daily real groups, and found a significant Group × Time interaction effect. Post hoc analysis indicated that the AM score was significantly enhanced in the real group after multiple comparisons correction.ConclusionOur prospective experiment did not show significant rTMS effect on AM, but this effect may become significant if more participants could be recruited as revealed by our retrospective analysis.

ObjectiveTwo subregions of the dorsolateral prefrontal cortex have been identified as effective repetitive transcranial magnetic stimulation (rTMS) targets for the “anxiosomatic” and “dysphoric” symptoms, respectively. We aimed to develop a convenient approach to locate these targets on the scalp.Materials and methodsIn a discovery experiment, the two personalized targets were precisely identified on 24 subjects using a neuronavigation system. Then, a localized approach was developed based on individual scalp landmarks. This “landmark-based approach” was replicated and validated in an independent cohort (N = 25). Reliability of the approach was tested by calculating the correlation of both the inter-rater and intra-rater results. Validity was tested by comparing the mean distance between the personalized and landmark-based targets to the TMS spatial resolution (i.e., 5 mm). We further conducted a total of 24 sham rTMS sessions to estimate the misplacement between the coil center and target during a 10-min stimulation without neuronavigation.ResultsThe parameters of the “landmark-based approach” in the discovery experiment were replicated well in an independent cohort. Using discovery parameters, we successfully identified the symptom-specific targets in the independent cohort. Specifically, the mean distance between the personalized and landmark-based targets on the cortex was not significantly larger than 5 mm. However, the personalized and landmark-based targets distance exceeded 5 mm in more than 50% of subjects. During the 10-min sham rTMS session, the average coil misplacement was significantly larger than 5 mm.ConclusionThe “landmark-based approach” can conveniently and reliably locate the two symptom-specific targets at group level. However, the accuracy was highly varied at individual level and further improvement is needed.

BackgroundTo investigate the dynamic changes of urine N6-methyladenosine (m6A) levels in patients with type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN) and evaluate the clinical significance.MethodsFirst, the levels of urine m6A were examined and compared among 62 patients with T2DM, 70 patients with DN, and 52 age- and gender-matched normal glucose tolerant subjects (NGT) by using a MethyIFIashTM Urine m6A Quantification Kit. Subsequently, we compared the concentrations of urine m6A between different stages of DN. Moreover, statistical analysis was performed to evaluate the association of urine m6A with DN.ResultsThe levels of m6A were significantly decreased in patients with DN [(16.10 ± 6.48) ng/ml], compared with NGT [(23.12 ± 7.52) ng/ml, P < 0.0001] and patients with T2DM [(20.39 ± 7.16) ng/ml, P < 0.0001]. Moreover, the concentrations of urine m6A were obviously reduced with the deterioration of DN. Pearson rank correlation and regression analyses revealed that m6A was significantly associated with DN (P < 0.05). The areas under the receiver operator characteristics curve (AUC) were 0.783 (95% CI, 0.699 – 0.867, P < 0.0001) for the DN and NGT groups, and 0.737 (95% CI, 0.639 – 0.835, P < 0.0001) for the macroalbuminuria and normoalbuminuria groups, and the optimal cutoff value for m6A to distinguish the DN from NGT and the macroalbuminuria from normoalbuminuria cases was 0.4687 (diagnostic sensitivity, 71%; diagnostic specificity, 76%) and 0.4494 (diagnostic sensitivity, 79%; diagnostic specificity, 66%), respectively.ConclusionsThe levels of urine m6A are significantly decreased in patients with DN and change with the deterioration of DN, which could serve as a prospective biomarker for the diagnosis of DN.

Methylglyoxal, a major precursor of advanced glycation end products, is elevated in the plasma of patients with type 2 diabetes mellitus. Islet β-cell function was recently shown to be regulated by N6-methyladenosine (m6A), an RNA modification consisting of methylation at the N6 position of adenosine. However, the role of m6A methylation modification in methylglyoxal-induced impairment of insulin secretion in pancreatic β cells has not been clarified. In this study, we showed that treatment of two β-cell lines, NIT-1 and β-TC-6, with methylglyoxal reduced m6A RNA content and methyltransferase-like 3 (METTL3) expression levels. We also showed that silencing of METTL3 inhibited glucose-stimulated insulin secretion (GSIS) from NIT-1 cells, whereas upregulation of METTL3 significantly reversed the methylglyoxal-induced decrease in GSIS. The methylglyoxal-induced decreases in m6A RNA levels and METTL3 expression were not altered by knockdown of the receptor for the advanced glycation end product but were further decreased by silencing of glyoxalase 1. Mechanistic investigations revealed that silencing of METTL3 reduced m6A levels, mRNA stability, and the mRNA and protein expression levels of musculoaponeurotic fibrosarcoma oncogene family A (MafA). Overexpression of MafA greatly improved the decrease in GSIS induced by METTL3 silencing; silencing of MafA blocked the reversal of the MG-induced decrease in GSIS caused by METTL3 overexpression. The current study demonstrated that METTL3 ameliorates MG-induced impairment of insulin secretion in pancreatic β cells by regulating MafA.

Fighting against the epidemic of Corona Virus Disease 2019 (COVID-19) has been successfully in this stage in China. The National Health Commission has proposed that rehabilitation medical institutions should provide assessment of pulmonary function and provide the management of respiratory rehabilitation for patients discharged with severe and critical COVID-19 infection. In response to this proposal, Hubei Provincial Hospital of Integrated Chinese and Western Medicine had established a COVID-19 Rehabilitation Department during the early stages of the pandemic and had been delivering clinical care according to National Rehabilitation Guidelines. According to clinical classification of the disease, the syndrome differentiation and treatment of traditional Chinese Medicine, we adopted personalized rehabilitation programme with integrated Chinese and western medicine, which include modern rehabilitation therapeutic techniques, such as positional therapy, breathing training and kinesiotherapy with the purpose of ameliorating respiratory and physical function, point massage, sandwiched moxibustion and other Chinese medicine treatments to regulate Qi (breathing) activities and repair Zang-fu viscera function, traditional Chinese exercises such as Tai Chi boxing and Baduanjin exercise with the effects of strenthening physical ability and improving physical and mental status. These Patients do benefit from this combined rehabilitation through clinical observation. Based on our clinical experience, we have formulated a standard protocol for patients with COVID-19 as a reference for rehabilitation professionals in application of traditional Chinese and western rehabilitation, with the aim of promoting universal function and quality of life for the patients.

Actinosynnema pretiosum is a well-known producer of maytansinoid antibiotic ansamitocin P-3 (AP-3). Growth of A. pretiosum in submerged culture was characterized by the formation of complex mycelial particles strongly affecting AP-3 production. However, the genetic determinants involved in mycelial morphology are poorly understood in this genus. Herein a continuum of morphological types of a morphologically stable variant was observed during submerged cultures. Expression analysis revealed that the ssgA_6663 and ftsZ_5883 genes are involved in mycelial aggregation and entanglement. Combing morphology observation and morphology engineering, ssgA_6663 was identified to be responsible for the mycelial intertwining during liquid culture. However, down-regulation of ssgA_6663 transcription was caused by inactivation of adpA_1075, gene coding for an AdpA-like protein. Additionally, the overexpression of adpA_1075 led to an 85% increase in AP-3 production. Electrophoretic mobility shift assays (EMSA) revealed that AdpA_1075 may bind the promoter regions of asm28 gene in asm gene cluster as well as the promoter regions of ssgA_6663. These results confirm that adpA_1075 plays a positive role in AP-3 biosynthesis and morphological differentiation.

It is very difficult to predict the Maximum Power Demand (MPD) of customers in high performance because of various factors. In this paper, the problem of MPD prediction is studied by using fused machine learning algorithms. Firstly, an improved grey relation analysis method is adopted to analyze relevant influencing factors. Secondly, a modified prediction algorithm based on an adaptive cubature Kalman filter combined with Fbprophet is proposed according to the characteristics of customers' MPD. Finally, the proposed algorithm of this paper is applied to predict MPD and cost is evaluated. Experiment results show that the improved MPD prediction algorithm can comprehensively consider the relevant factors, and has good performance in time series prediction.

A dual-band dual-polarized base station antenna for the fifth-generation (5G) mobile system is presented in this paper. The proposed antenna covers the frequency bands from 3.3 to 3.8 GHz (the lower band) and from 4.8 to 5.0 GHz (the upper band) with good isolation between its ports (≥ 20 dB). It consists of two double-oval-shaped dipoles, two double-oval-shaped feeding lines and a cavity reflector. In this design, parts of the dipole antenna structure are used as the feeding lines and it is found that using one arm of the dipole to feed the whole antenna can improve impedance matching. The dual-band performance is achieved by integrating a small oval-shaped loop within the large oval-shaped loop without increasing the size of the radiating patch. The size of the radiating patch is only 0.26λ0 × 0.26λ0 (λ0 is the free-space wavelength at 3.3 GHz). The cavity reflector improves the gain performance and reduces the overall size of the antenna, which is only 0.66 λ0 × 0.66λ0 × 0.2λ0. The antenna has an average realized gain of 7.56 dBi in the lower band and 7.42 dBi in the higher band. Meanwhile, for both bands, the radiation pattern is stable, and the half power beamwidth is within 65° ± 5°. Both simulated and measured results demonstrate that the antenna is a very good candidate for 5G mobile base stations.

Total radiated power (TRP) is commonly accepted as an important figure of merit (FoM) for evaluating the over-the-air (OTA) performance of wireless devices enabled by the emerging fifth generation (5G) mobile communication technology. The statistically homogeneous and isotropic electromagnetic (EM) environment created by a reverberation chamber (RC) makes it an accurate, efficient, and economic testing facility for TRP measurement. In this paper, an improved analytical uncertainty model which is based on the average Rician $K$ -factor ( $K_{avg}$ ) and the number of independent samples is proposed for TRP measurement using an RC. It has the flexibility to allow different stirring configurations in the calibration stage and the measurement stage, and gives insight into the measurement uncertainty without the tedious and inefficient empirical estimation processes. Estimators of $K_{avg}$ are modelled and analyzed. Specifically, the maximum likelihood estimator (MLE) of $K_{avg}$ is validated by the Monte Carlo simulation, and its unbiased correction is derived accordingly for improved uncertainty model accuracy. Extensive 9-Point estimation measurements are also conducted in order to evaluate the performance of the proposed analytical model.

Cellular interactions are a major driver of microbial communities and shown highly variable in strength. Here the authors construct synthetic consortia and mathematical models to elucidate the role of interaction variability in driving ecosystem succession.

Aiming at the problems of low-rate DDoS attack detection accuracy in cloud SDN network and the lack of unified framework for data plane and control plane low-rate DDoS attack detection and defense,a unified framework for low-rate DDoS attack detection was proposed.First of all,the validity of the data plane DDoS attacks in low rate was analyzed,on the basis of combining with low-rate of DDoS attacks in the aspect of communications,frequency characteristics,extract the mean value,maximum value,deviation degree and average deviation,survival time of ten dimensions characteristics of five aspects,to achieve the low-rate of DDoS attack detection based on bayesian networks,issued by the controller after the relevant strategies to block the attack flow.Finally,in OpenStack cloud environment,the detection rate of low-rate DDoS attack reaches 99.3% and the CPU occupation rate is 9.04%.It can effectively detect and defend low-rate DDoS attacks.

Diabetic cardiomyopathy (DCM) is a serious complication of diabetes mellitus (DM). One of the hallmarks of the DCM is enhanced oxidative stress in myocardium. The aim of this study was to research the underlying mechanisms involved in the effects of dapagliflozin (Dap) on myocardial oxidative stress both in streptozotocin-induced DCM rats and rat embryonic cardiac myoblasts H9C2 cells exposed to high glucose (33.0 mM). In in vivo studies, diabetic rats were given Dap (1 mg/ kg/ day) by gavage for eight weeks. Dap treatment obviously ameliorated cardiac dysfunction, and improved myocardial fibrosis, apoptosis and oxidase stress. In in vitro studies, Dap also attenuated the enhanced levels of reactive oxygen species and cell death in H9C2 cells incubated with high glucose. Mechanically, Dap administration remarkably reduced the expression of membrane-bound nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunits gp91phox and p22phox, suppressed the p67phox subunit translocation to membrane, and decreased the compensatory elevated copper, zinc superoxide dismutase (Cu/Zn-SOD) protein expression and total SOD activity both in vivo and in vitro. Collectively, our results indicated that Dap protects cardiac myocytes from damage caused by hyperglycemia through suppressing NADPH oxidase-mediated oxidative stress.

Driving behaviour is a complex and multidisciplinary research domain, and bad driving behaviours that threaten the safety of road users should be refrained. In order to better educate, manage, and restrain driver’s behaviours, from the perspective of human factors and psychology, the present study deconstructed driving behaviours based on theory of planned behaviour (TPB) into five categories: mistakes (Mis), lapses and slips (LaS), violations (Vio), driving experience (Exp), and safety attitude and awareness (SAA). According to today’s practical traffic rules and conditions in China, a driving behaviour questionnaire was built as an analysing tool and the survey data were collected in accordance with the demographic of Chinese drivers. Furthermore, a driving behaviour analysis model contains the aforementioned categories was established by using the structural equation model (SEM). Through the path analysis results among latent variables and manifested variables, it was found that Exp has an impact on Vio and LaS, and better SAA can inhibit Vio and Mis. In conclusion, the prime aim of improving road traffic safety is to reduce Vio by means of educating and improving the drivers’ Exp and SAA. Moreover, drivers’ LaS and Mis are transition processes which should be corrected timely and prevented from continuing to evolve into Vio.

Distracted driving is a dominant cause of traffic accidents. In addition, with the rapid development of intelligent vehicles, mixed traffic environments are expected to become more complicated with multiple types of intelligent vehicles sharing the road, thereby increasing the opportunities for distracted driving. However, the existing research on detecting driver distraction in mixed traffic environments is limited. Therefore, in this study, we analysed the effect of cognitive distraction on the driver physiological measures and driving performance in traditional and mixed traffic environments and compared the parameters extracted in the two environments. Sixty drivers were involved in the data collection, which included normal driving and two distracting tasks while driving in a simulator. Repeated-measures analysis of variance (ANOVA) was performed to examine the effect of cognitive distraction and traffic environments on all parameters. The results indicate that the effects of the pupil diameter, standard deviations (SDs) of the horizontal and vertical fixation angles, blink frequency, speed, SD of the lane positioning (SDLP), SD of the steering wheel angle (SDSWA), and steering entropy (SE) were significant. These findings provide a theoretical foundation for identifying the most appropriate parameters to detect cognitive distraction in traditional and mixed traffic environments to help reduce traffic accidents.

Distracted driving has become a growing traffic safety concern. With advances in autonomous driving and connected vehicle technology, a mixture of various types of intelligent vehicles will become normal in the near future, while more factors that may cause driver cognitive distraction are emerging. However, there are rarely studies on distracted driving in mixed traffic environments. To fill this gap, we conducted a natural driving experiment with three representative events at a nonsignalized intersection in a mixed traffic environment and proposed a novel method of identifying cognitive distraction based on bidirectional long short-term memory (Bi-LSTM) with attention mechanism. Forty participants were recruited for each event, who completed three different cognitive distraction experiments induced by three different secondary tasks in contrast with a normal driving process when passing a nonsignalized intersection. Related driving performance and eye movement data were collected to train and test the Bi-LSTM with attention mechanism model. Compared with the support vector machine (SVM) model, its recognition accuracy rate is 94.33%, which is 3.83% higher than that of the SVM in the total event, which has reasonable applicability for distraction recognition in a mixed traffic environment. Potential applications of this model include distraction alarm and autonomous driving assistance systems, which could avoid road traffic accidents.

An ionic liquid (IL) is used to make antennas for the first time. Unlike water, the proposed material has a large liquid range (-69.8 °C-350 °C), a relative permittivity of 3, an extremely low dielectric loss, and very stable thermophysical material properties. It can be used for liquid dielectric resonator antennas (DRAs) or as a loading material for performance enhancement. Importantly, the proposed liquid loading scheme is relatively simple and of low cost, but it can markedly improve the antenna performance. As design examples, a liquid-loaded wideband linearly polarized (LP) monopole antenna with an omnidirectional radiation pattern is first presented. Then, the LP antenna is modified to a wideband circularly polarized (CP) antenna with boresight radiation. These antenna examples demonstrate a frequency coverage of 1.25-5 GHz, a wide CP bandwidth, a relatively high gain (>4 dBi), high radiation efficiency >85%, and an electrical size of 0.42 λ0 x0.42λ0 x0.17λ0. The experimental results show that the liquid loading works well under a wide range of temperatures. It effectively reduces the antenna electrical size by 40% and improves the impedance matching by 5 dB. Therefore, the proposed liquid loading scheme can be applied to a variety of antenna/RF designs.

Abstract Background Ansamitocin P-3 (AP-3), produced by Actinosynnema pretiosum, has extraordinary antitumor activity and has been used as toxic “warhead” in antibody-conjugated drugs. However, AP-3 production is limited by its low yield and thus the high cost of fermentation. In this study, we aimed to reduce fermentation costs by utilizing the low-cost substrates and improve the AP-3 production, simultaneously. Result In this study, low-cost substrates used for ansamitocins production were selected via single-factor experiments and then the concentrations of these suitable carbon and nitrogen sources were optimized by response surface method (RSM). Cane molasses, glycerol, and cold-pressed soybean powder were determined to be the most suitable economical carbon and nitrogen sources for AP-3 accumulation. The AP-3 titer in shaking flasks reached 111.9 mg/L using the optimized medium containing cane molasses (63.22 g/L), glycerol (22.91 g/L), and cold-pressed soybean powder (3.29 g/L). In addition, appropriate supplementation with isobutanol, soybean oil, and vitamin B1 resulted in a marked enhancement in AP-3 production, to 141 mg/L. Meanwhile, the cost of this optimized fermentation medium was around 50% lower than those of two other high-yielding media. Conclusion Our findings provided practical and economically competitive cultivation conditions for the production of a value-added antitumor agent and may thus extend the applications of ansamitocin P-3.

This paper presents a quadruple-band indoor base station antenna for 2G/3G/4G/5G mobile communications, which covers multiple frequency bands of 0.8 - 0.96 GHz, 1.7 - 2.7 GHz, 3.3 - 3.8 GHz and 4.8 - 5.8 GHz and has a compact size with its overall dimensions of 204 × 175 × 39 mm3. The lower frequency bands over 0.8 - 0.96 GHz and 1.7 - 2.7 GHz are achieved through the combination of an asymmetrical dipole antenna and parasitic patches. A stepped-impedance feeding structure is used to improve the impedance matching of the dipole antenna over these two frequency bands. Meanwhile, the feeding structure also introduces an extra resonant frequency band of 3.3 - 3.8 GHz. By adding an additional small T-shaped patch, the higher resonant frequency band at 5 GHz is obtained. The parallel surrogate model-assisted hybrid differential evolution for antenna optimization (PSADEA) is employed to optimize the overall quadruple-band performance. We have fabricated and tested the final optimized antenna whose average gain is about 5.4 dBi at 0.8 - 0.96 GHz, 8.1 dBi at 1.7 - 2.7 GHz, 8.5 dBi at 3.3 - 3.8 GHz and 8.1 dBi at 4.8 - 5.0 GHz respectively. The proposed antenna has high efficiency and is of low cost and low profile, which makes it an excellent candidate for 2G/3G/4G/5G base station antenna systems.

This paper proposes a new design of a triple-band dual-polarized indoor base station antenna for mobile communication systems serving the 2G, 3G, 4G, and the new sub-6 GHz 5G applications. The design consists of two orthogonal dipole antennas to provide dual polarization. Each dipole consists of three different radiator types-elliptical dipole, bowtie dipole, and cat-ear shaped arms for different bands. The proposed antenna offers three broad bands with the fractional bandwidths of 31.3% (0.7-0.96 GHz), 55.3% (1.7-3 GHz), and 14% (3.3-3.8 GHz) which can be controlled independently. The design also offers stable radiation patterns within the desired frequency bands, high polarization purity and, a simple feeding structure with a compact size and low profile which make this new design an ideal candidate for indoor mobile base stations serving the 2G, 3G, 4G, and the new sub-6GHz 5G applications.

Abstract Background Yarrowia lipolytica is widely studied as a non-conventional model yeast owing to the high level of lipid accumulation. Therein, triacylglycerol (TAG) is a major component of liposome. In order to investigate the TAG biosynthesis mechanism at a systematic level, a novel genome-scale metabolic model of Y. lipolytica was reconstructed based on a previous model iYL619_PCP published by our lab and another model iYali4 published by Kerkhoven et al. Results The novel model iYL_2.0 contains 645 genes, 1083 metabolites, and 1471 reactions, which was validated more effective on simulations of specific growth rate. The precision of 29 carbon sources utilities reached up to 96.6% when simulated by iYL_2.0. In minimal growth medium, 111 genes were identified as essential for cell growth, whereas 66 essential genes were identified in yeast extract medium, which were verified by database of essential genes, suggesting a better prediction ability of iYL_2.0 in comparison with other existing models. In addition, potential metabolic engineering targets of improving TAG production were predicted by three in silico methods developed in-house, and the effects of amino acids supplementation were investigated based on model iYL_2.0. Conclusions The reconstructed model iYL_2.0 is a powerful platform for efficiently optimizing the metabolism of TAG and systematically understanding the physiological mechanism of Y. lipolytica.

Four new indolyl diketopiperazines, aspamides A–E (1–4) and two new diketopiperazines, aspamides F–G (5–6), along with 11 known diketopiperazines and intermediates were isolated from the solid culture of Aspergillus versicolor, which is an endophyte with the sea crab (Chiromantes haematocheir). Further chiral high-performance liquid chromatography resolution gave enantiomers (+)- and (−)-4, respectively. The structures and absolute configurations of compounds 1–6 were determined by the comprehensive analyses of nuclear magnetic resonance (NMR), high-resolution mass spectrometry (HR-MS), and electronic circular dichroism (ECD) calculation. All isolated compounds were selected for the virtual screening on the coronavirus 3-chymoretpsin-like protease (Mpro) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), and the docking scores of compounds 1–2, 5, 6, 8 and 17 were top among all screened molecules, may be helpful in fighting with Corona Virus Disease-19 (COVID-19) after further studies.

Genome-scale metabolic models embody a significant advantage of systems biology since their applications as metabolic flux simulation models enable predictions for the production of industrially-interesting metabolites. The biotechnological production of lycopene from Yarrowia lipolytica is an emerging scope that has not been fully scrutinized, especially for what concerns cultivation conditions of newly generated engineered strains. In this study, by combining flux balance analysis (FBA) and Plackett-Burman design, we screened chemicals for lycopene production from a metabolically engineered strain of Y. lipolytica. Lycopene concentrations of 126 and 242 mg/L were achieved correspondingly from the FBA-independent and the FBA-assisted designed media in fed-batch cultivation mode. Transcriptional studies revealed upregulations of heterologous genes in media designed according to FBA, thus implying the efficiency of model predictions. Our study will potentially support upgraded lycopene and other terpenoids production from existing or prospect bioengineered strains of Y. lipolytica and/or closely related yeast species.

Face representation and matching are two essential issues in face verification task. Various approaches have been proposed focusing on these two issues. However, few of them addressed the joint optimal solutions of these two issues in a unified framework. In this paper, we present a second-order face representation method for face pair and a unified face verification framework, in which the feature extractors and the subsequent binary classification model design can be selected flexibly. Our contributions can be summarized in the following aspects. First, a novel face-pair representation method that employs the second-order statistical property of the face pairs is proposed, which retains more information compared to the existing methods. Second, a flexible binary classification model, which differs from the conventionally used metric learning, is constructed based on the new face-pair representation. Finally, we verify that our proposed face-pair representation can benefit from large training datasets. All the experiments are carried out on Labeled Face in the Wild (LFW) to verify the algorithm’s effectiveness against challenging uncontrolled conditions.