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We propose an acoustic-mechanical metasurface with simultaneous sound absorption and vibration reduction functionalities. This acoustic-mechanical feature results from a nonlocal coupling effect in the designed composite meta-structure. A nonlocal meta-mesh is designed at the acoustic-mechanical interface and embedded in the metasurface array to connect adjacent unit cells, which can make a nonlocal coupling effect. This effect can improve the acoustic property, which strengthens sound absorption by 58.6 %, and the mechanical interface strengthens vibration acceleration reduction by 88.45 %. The resulting nonlocal acoustic-mechanical metasurface achieves an average absorption coefficient of higher than 0.9 within 267–638 Hz, and a vibration level difference of 18.75 dB within 490–920 Hz. The sample has an ultra-thin thickness of 8.5 cm (λ/14 for the lowest working frequency) and is lightweight (305.1 g), whose weight reduction reaches 42.8 % compared with conventional designs with similar functionalities. Our proposed design strategy will be enlightened for multi-functional acoustic-mechanical coupling meta-device.

Industrial microbes have become the core of biological manufacturing, which utilized as the cell factory for production of plenty of chemicals, fuels and medicine. However, the challenge that the extreme stress conditions exist in production is unavoidable for cell factory. Consequently, to enhance robustness of the chassis cell lays the foundation for development of bio-manufacturing. Currently, the researches on cell tolerance covered various aspects, involving reshaping regulatory network, cell membrane modification and other stress response. In fact, the strategies employed to improve cell robustness could be summarized into two directions, irrational engineering and rational engineering. In this review, the metabolic engineering technologies on enhancement of microbe tolerance to industrial conditions are summarized. Meanwhile, the novel thoughts emerged with the development of biological instruments and synthetic biology are discussed.

Aquatic animals are an important source of food for humans, yet little is known about their potential to transfer zoonotic viruses. Multiple recent cases of SARS-CoV-2 from cold-chain aquatic food and environmental samples has evoked worldwide concerns, and even though these cases pale in comparison to poultry and livestock. To investigate the potential threat of food from aquatic animals, we map their transcriptomes to the genomes of human respiratory- and intestine-related viruses. Analyses only find an influenza virus sequence in a salmon (Salmo salar) skin transcriptome. BLAST and phylogenetic analyses identify this sequence as influenza A, and this likely owes to contamination from a worker. Thus, when prepared properly, aquatic animals can provide great nutritional benefits to humans while posing minimal health risks.

The four-switch buck-boost (FSBB) converter usually adopts a pseudo-continuous conduction mode (PCCM) soft switching (ZVS) control strategy, but there is a problem with the low efficiency of FSBB converters under light loads. Firstly, the constraints that the control variables of the FSBB converter need to satisfy are analyzed, and it is pointed out that the fixed frequency constraint is not necessary. Then, the switching frequency is used to control the degree of freedom, and the quantitative relationship between the FSBB converter loss and the switching frequency is obtained. Finally, for different input voltages and loads, the switching frequency corresponding to the minimum power loss is calculated offline. By optimizing the switching frequency, the light-load efficiency of the FSBB converter is improved. A prototype with an input voltage range of 210 V–330 V, an output voltage of 270 V, and an output power of 3 kW was developed. The loss was reduced by 15% at 20% load, and the peak efficiency of the converter reached 99.23%. The experimental results verified the effectiveness of the proposed control strategy.

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Abstract To investigate the effects and potential mechanisms of human umbilical cord mesenchymal stem cells, exosomes, and their conditioned media on lipid storage in oleic acid (OA) and palmitic acid (PA) treated hepatocytes and high-fat methionine- choline deficient diet (HFMRCD) induced non-alcoholic steatohepatitis (NASH) mice. AML12 cells were stimulated with OA and PA to establish the lipid storage cell model. HucMSCs, exosomes, and culture medium were then co-cultured. At the same time, C57BL/6 mice were fed an HFMRCD for 6 or 8 weeks to establish a NASH mouse model. The effect of HucMSCs, exosomes, and culture medium on lipid droplet repair of hepatocytes or NASH mice was then assessed. The weight of hepatocytes or liver tissue, Oil Red O, hematoxylin–eosin staining, Masson staining, Western blot, and qPCR were used to detect the related IL-6, TNF-α, TGF-β1 andEI24/AMPK/mTOR pathway expression in hepatocytes and liver tissue. Compared with the model group, the effect of HucMSCs-Ex on inhibiting the accumulation of lipid droplets was more obvious at the cell level. In vivo study showed that HucMSCs-Ex reduces activity scores in NASH mice and improves liver tissue morphology by reducing vacuolar degeneration, fat deposition, and collagen deposition of liver tissue. Western blot and qPCR results showed that inflammatory factors and AMPK/mTOR or EI24-related autophagy pathways were altered before and after treatment. HucMSCs, HucMSC-Ex, and CM can promote autophagy in hepatocytes or NASH mice through the AMPK/mTOR or EI24-related autophagy pathway and alleviate injury associated with lipid deposition, collagen deposition or inflammation, reversing the progression of NASH.

Abrupt dietary change can disrupt the intestinal balance in felines. This study aimed to assess the impact of heat-treated Bifidobacterium longum CECT-7384 combined with Fibersol-2 on the intestinal health of adult cats before and after dietary change. We selected 24 British shorthair cats, dividing them into two groups. From day 1 to day 14, the control group received a lower protein (33%) concentration (LPF) diet, while the treated group received the same LPF diet supplemented with 0.16% functional additives, consisting of Bifidobacterium longum CECT-7384 combined with Fibersol-2. Subsequently, from day 15 to day 28, the control group transitioned to a higher protein (40%) concentration (HPF) diet, while the treated group received the same HPF diet supplemented with 0.16% functional additives. Blood and fresh feces were collected on day 0, 14, 17, 21, and 28 of the experiment. The results suggest that the use of heat-treated Bifidobacterium longum CECT-7384 combined with Fibersol-2 may improve gastrointestinal function in cats by reducing serum LPS levels and fecal pH, while increasing fecal sIgA levels. In addition, the functional additive regulates the fecal microbiota and its function, promoting intestinal homeostasis and colonization with beneficial bacteria such as Blautia. Furthermore, on day 28, there was a significant difference in fecal microbiota beta diversity between the two groups. In summary, the addition of heat-treated Bifidobacterium longum CECT-7384 combined with Fibersol-2 contributes to improving the intestinal health of adult cats affected by abrupt dietary change.

Abstract Dopamine is high-value compound of pharmaceutical interest, but its industrial scale production mostly focuses on chemical synthesis, possessing environment pollution. Bio-manufacturing has caused much attention for its environmental characteristic. Resting cells were employed to as biocatalysts with extraordinary advantages like offering stable surroundings, the inherent presence of expensive cofactors. In this study, whole-cell bioconversion was employed to convert dopa to dopamine. To increase the titer and yield of dopamine production through whole-cell catalysis, three kinds of aromatic amino acid transport protein, AroP, PheP and TyrP, were selected to be co-expressed. The effects of the concentration of L-dopa, pyridoxal-5’- phosphate (PLP), reaction temperature and pH were characterized for improvement of bioconversion. Under optimal conditions, dopamine titer reached 1.44 g/L with molar yield of 46.3%, which is 6.62 times than that of initial conditions. The catalysis productivity of recombinant E. coli co-expressed L-dopa decarboxylase(DDC) and AroP was further enhanced by repeated cell recycling, which maintained over 50% of its initial ability with eight consecutive catalyses. This study was the first to successfully bioconversion of dopamine by whole-cell catalysis. This research provided reference for whole-cell catalysis which is hindered by cell membrane.

Objective: The three-dimensional morphological structures of periodontal ligaments (PDLs) are important data for periodontal, orthodontic, prosthodontic, and implant interventions. This study aimed to employ a deep learning (DL) algorithm to segment the PDL automatically in cone-beam computed tomography (CBCT). Method: This was a retrospective study. We randomly selected 389 patients and 1734 axial CBCT images from the CBCT database, and designed a fully automatic PDL segmentation computer-aided model based on instance segmentation Mask R-CNN network. The labels of the model training were ‘teeth’ and ‘alveolar bone’, and the ‘PDL’ is defined as the region where the ‘teeth’ and ‘alveolar bone’ overlap. The model’s segmentation performance was evaluated using CBCT data from eight patients outside the database. Results: Qualitative evaluation indicates that the PDL segmentation accuracy of incisors, canines, premolars, wisdom teeth, and implants reached 100%. The segmentation accuracy of molars was 96.4%. Quantitative evaluation indicates that the mIoU and mDSC of PDL segmentation were 0.667 ± 0.015 (>0.6) and 0.799 ± 0.015 (>0.7) respectively. Conclusion: This study analysed a unique approach to AI-driven automatic segmentation of PDLs on CBCT imaging, possibly enabling chair-side measurements of PDLs to facilitate periodontists, orthodontists, prosthodontists, and implantologists in more efficient and accurate diagnosis and treatment planning.

IntroductionIn the context of digital transformation of education, online training is one of the important ways for teachers to improve their professionalism and promote the quality of education. However, studies have shown that teachers’ online training suffers from insufficient learning engagement and other problems, so it is crucial to explore the factors influencing teachers’ learning engagement and their mechanisms of action in the context of online training.MethodsTaking 589 teachers who participated in online training as the research subjects, the study used the methods of survey research and statistical analysis to explore the influence mechanism of teachers’ academic emotions and motivational beliefs on online learning engagement based on the dual perspectives of control value theory and expectancy-value theory.ResultsThe study found that: (1) positive-high arousal academic emotions, training self-efficacy, and training task value significantly and positively predicted online learning engagement, respectively; (2) negative-high arousal and negative-low arousal academic emotions significantly and negatively predicted online learning engagement; (3) training self-efficacy and training task value mediated the relationship between positive-high arousal academic emotions, negative-high arousal academic emotions, negative-low arousal academic emotions and online learning engagement, respectively.DiscussionThe study concluded that by creating an immersive learning environment based on the educational meta universe, personalized and precise training based on big data and adaptive technologies, and establishing a multi-dimensional and three-dimensional online learning support service system, which can effectively improve teachers’ online learning engagement and enhance their online training quality and effectiveness.

Abstract Background Polyamide (nylon) is an important material, which has aroused plenty of attention from all aspects. PA 5.4 is one kind of nylon with excellent property, which consists of cadaverine and succinic acid. Due to the environmental pollution, bio-production of cadaverine and succinic acid has been more attractive due to the less pollution and environmental friendliness. Microbes, like Escherichia coli, has been employed as cell factory to produce cadaverine and succinic acid. However, the accumulation of cadaverine will cause severe damage on cells resulting in inhibition on cell growth and cadaverine production. Herein, a novel two stage co-production of succinic acid and cadaverine was designed based on an efficient thermos-regulated switch to avoid the inhibitory brought by cadaverine. Results The fermentation process was divided into two phase, one for cell growth and lysine production and the other for cadaverine and succinic acid synthesis. The genes of ldhA and ackA were deleted to construct succinic acid pathway in cadaverine producer strain. Then, a thermal switch system based on pR/pL promoter and CI857 was established and optimized. The fermentation conditions were investigated that the optimal temperature for the first stage was determined as 33 ℃ and the optimal temperature for the second stage was 39 ℃. Additionally, the time to shifting temperature was identified as the fermentation anaphase. For further enhance cadaverine and succinic acid production, a scale-up fermentation in 5 L bioreactor was operated. As a result, the titer, yield and productivity of cadaverine was 55.58 g/L, 0.38 g/g glucose and 1.74 g/(L·h), respectively. 28.39 g/L of succinic acid was also obtained with yield of 0.19 g/g glucose. Conclusion The succinic acid metabolic pathway was constructed into cadaverine producer strain to realize the co-production of succinic acid and cadaverine. This study provided a novel craft for industrial co-production of cadaverine and succinic acid.

Abstract Tumor lysis syndrome (TLS) is a common and fatal complication of childhood hematologic malignancies, especially acute lymphoblastic leukemia (ALL). The clinical features, therapeutic regimens, and outcomes of TLS have not been comprehensively analyzed in Chinese children with ALL. A total of 5537 children with ALL were recruited from the Chinese Children’s Cancer Group, including 79 diagnosed with TLS. The clinical characteristics, treatment regimens, and survival of TLS patients were analyzed. Age distribution of children with TLS was remarkably different from those without TLS. White blood cells (WBC) count ≥ 50 × 109/L was associated with a higher risk of TLS [odds ratio (OR) = 2.6, 95% CI = 1.6–4.5]. The incidence of T-ALL in TLS children was significantly higher than that in non-TLS controls (OR = 4.7, 95% CI = 2.6–8.8). Hyperphosphatemia and hypocalcemia were more common in TLS children with hyperleukocytosis (OR = 2.6, 95% CI = 1.0–6.9 and OR = 5.4, 95% CI = 2.0–14.2, respectively). Significant differences in levels of potassium (P = 0.004), calcium (P

This paper proposes a novel trajectory planning algorithm to design an end-effector motion profile along a specified path. An optimization model based on the whale optimization algorithm (WOA) is established for time-optimal asymmetrical S-curve velocity scheduling. Trajectories designed by end-effector limits may violate kinematic constraints due to the non-linear relationship between the operation and joint space of redundant manipulators. A constraints conversion approach is proposed to update end-effector limits. The path can be divided into segments at the minimum of the updated limitations. On each path segment, the jerk-limited S-shaped velocity profile is generated within the updated limitations. The proposed method aims to generate end-effector trajectory by kinematic constraints which are imposed on joints, resulting in efficient robot motion performance. The WOA-based asymmetrical S-curve velocity scheduling algorithm can be automatically adjusted for different path lengths and start/end velocities, allowing flexibility in finding the time-optimal solution under complex constraints. Simulations and experiments on a redundant manipulator prove the effect and superiority of the proposed method.

Handedness influences differences in lateralization of language areas as well as dominance of motor and somatosensory cortices. However, differences in whole-brain functional connectivity (i.e., functional connectomes) due to handedness have been relatively understudied beyond pre-specified networks of interest. Here, we compared functional connectomes of left- and right-handed individuals at the whole brain level. We explored differences in functional connectivity of previously established regions of interest, and showed differences between primarily left- and primarily right-handed individuals in the motor, somatosensory, and language areas using functional connectivity. We then proceeded to investigate these differences in the whole brain and found that the functional connectivity of left- and right-handed individuals are not specific to networks of interest, but extend across every region of the brain. In particular, we found that connections between and within the cerebellum show distinct patterns of connectivity. To put these effects into context, we show that the effect sizes associated with handedness differences account for a similar amount of individual differences in the connectome as sex differences. Together these results shed light on regions of the brain beyond those traditionally explored that contribute to differences in the functional organization of left- and right-handed individuals and underscore that handedness effects are neurobiologically meaningful in addition to being statistically significant.

Acoustic insulation in ventilated structures is an important problem in acoustic engineering with many potential practical applications, such as the noise control for ventilating ducts of buildings, vehicles, or air conditioners. Acoustic metamaterial is a good candidate for the design of acoustic insulation for ventilated channel (AIVC) because the structural design with hard boundary has longer lifetime than conventional sound-absorbing cotton. In this paper, an AIVC with an open region and narrow channels of different lengths is proposed. We numerically and experimentally demonstrate its acoustic insulation larger than 20 dB (T < 0.01) within approximately 500–1,200 Hz with a subwavelength channel length of λ/6. The parameter dependence and air flow effect are numerically studied. Our findings show an alternative design of AIVC that may have applications in noise control and architectural acoustics.

Objective(s): Endometritis is the inflammation of the uterine lining that is associated with infertility. It affects milk production and reproductive performance and leads to huge economic losses in dairy cows. Dimethyl itaconate (DI), a promising chemical agent, has recently been proved to have multiple health-promoting effects. However, the effects of DI on endometritis remain to be unknown. Materials and Methods: In this study, we assessed the anti-inflammatory effects of DI on Lipopolysaccharide (LPS)-induced endometritis in mice. The endometritis was induced by LPS treatment for 24 hr, and DI was given 24 hr before induction of LPS.Results: As a result, DI administered mice significantly suffered less impairment of uterine tissue and less recruitment of inflammatory cells than LPS administered mice. In addition, DI markedly inhibited uterine myeloperoxidase (MPO) activity and pro-inflammatory cytokines of tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6) induced by LPS. Moreover, LPS-induced toll-like receptor 4/ nuclear factor-kappa B (TLR4/NF-κB) activation was suppressed by DI. In addition, the expressions of nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase (HO-1) were upregulated by DI.Conclusion: These findings suggest that DI has anti-inflammatory functions in the LPS-induced mice and may be a therapeutic agent against endometritis.

Based on the granular-solid-hydrodynamic theory, the constitutive model considering the thermo-hydro-mechanical (THM) coupled action is established, and the dilatancy property of sandy soil under coupled high mechanical pressure and temperature is simulated. The relationship between the energy dissipation and the macroscopic stress-strain changes at the grain level of saturated sandy soil is connected by defining the transfer coefficient and the energy function, without considering the concepts of yield surface and hardening parameters in classical plastic mechanics. Additionally, the changes in temperature, relative density and confining pressure during the shearing process cause particle rolling, slipping and friction. The energy dissipation in this process is described by defining the concept of particle entropy and particle temperature. In the calculation, the isotropic compression test, drained and undrained shear test of sandy soil under high stress are simulated respectively. The validity of the model is proved by comparing with the test results. Meanwhile, the stress-strain relationship and pore pressure variation law of sandy soil under different temperatures are predicted. The results show that the effect of temperature on shear strength is limited, and the pore pressure will gradually increase and become stable with the increase of temperature. Thus, this work establishes the soil THM coupled model from the perspective of micro energy dissipation, which can provide new theoretical support for the prediction of natural disasters such as landslides and debris flow.

Functional connectivity (FC) estimated from functional magnetic resonance imaging (fMRI) signals is important in understanding neural representation and information processing in cortical networks. However, due to a lack of ”ground truth” FC pattern, the reliability and robustness of FC estimates are usually examined in downstream FC analysis tasks, such as performing participant’s identification (also known as ”fingerprinting”). In this paper, we propose to learn FC via a smooth graph learning framework. In particular, we treat each time frame of the fMRI time series as a graph signal on an underlying functional brain graph, and estimate the smooth graph functional connectivity (SGFC) by learning the weighted graph adjacency matrix based on graph signal smoothness assumption. We demonstrate that our approach gives rise to a natural and sparse graph representation of FC from which reliable graph measures can be extracted. Reliability of SGFC is evaluated in the context of fingerprinting and compared to correlation FC (CFC). SGFC achieves higher fingerprinting accuracy across several different experiment settings; the improvement is even more significant when a shorter fMRI scanning length is used for FC estimation. In addition to being reliable, we also validate the cognitive relevance of SGFC by using it to predict fluid intelligence. Finally, in evaluating topological measures of the sparse graph, SGFC reveals a more small-world and modular structure compared to CFC. Together, our results suggest that the smooth graph learning framework produces a naturally sparse, reliable, and cognitive-relevant representation of functional connectivity.

The uniqueness and stability of the adolescent and adult functional connectome has been demonstrated to be high (80–95 % identification) using connectome-based identification (ID) or “fingerprinting”. However, it is unclear to what extent individuals exhibit similar distinctiveness and stability in infancy, a developmental period of rapid and unparalleled brain development. In this study, we examined connectome-based ID rates within and across the first year of life using a longitudinal infant dataset at 1.5 month and 9 months of age. We also calculated the test–retest reliability of individual connections across the first year of life using the intraclass correlation coefficient (ICC). Overall, we found substantially lower infant ID rates than have been reported in adult and adolescent populations. Within-session ID rates were moderate and significant (ID = 48.94–70.83 %). Between-session ID rates were very low and not significant, with task-to-task connectomes resulting in the highest between-session ID rate (ID = 26.6 %). Similarly, average edge-level test-retest reliability was higher within-session than between-session (mean within-session ICC = 0.17, mean between-session ICC = 0.10). These findings suggest a lack of uniqueness and stability in functional connectomes across the first year of life consistent with the unparalleled changes in brain functional organization during this critical period.

Urban water and power supply networks with interdependent characteristics are essential components of urban infrastructures and play an important role in maintaining the daily operations and post-disaster recovery of cities. The aim of this study is to provide a method for researchers of resilient cities to build virtual water and power supply networks according to their basic physical mechanisms so that they can complete the risk or resilience evaluation of benchmark cities when some confidential infrastructure information is difficult to obtain. The innovation is that a new design framework for urban virtual water and power networks with interdependent characteristics combined with geographic information is suggested based on the perspective of practical engineering. After giving an overview of the framework, this paper presents the planning and design of the water and power supply networks as well as the interdependence between them in detail. Then the water and power supply networks of a virtual city called Virtual Shangcheng City are established, which verify the feasibility and practicality of the approach. This framework can establish virtual water and power supply networks with interdependent characteristics that conform to actual engineering and urban geographic information characteristics. Moreover, it can provide an effective modeling method for water and power supply networks in the absence of data for urban resilience and disaster risk studies.

Abstract Introduction Working memory is a critical cognitive ability that affects our daily functioning and relates to many cognitive processes and clinical conditions. Episodic memory is vital because it enables individuals to form and maintain their self‐identities. Our study analyzes the extent to which whole‐brain functional connectivity observed during completion of an N‐back memory task, a common measure of working memory, can predict both working memory and episodic memory. Methods We used connectome‐based predictive models (CPMs) to predict 502 Human Connectome Project (HCP) participants' in‐scanner 2‐back memory test scores and out‐of‐scanner working memory test (List Sorting) and episodic memory test (Picture Sequence and Penn Word) scores based on functional magnetic resonance imaging (fMRI) data collected both during rest and N‐back task performance. We also analyzed the functional brain connections that contributed to prediction for each of these models. Results Functional connectivity observed during N‐back task performance predicted out‐of‐scanner List Sorting scores and to a lesser extent out‐of‐scanner Picture Sequence scores, but did not predict out‐of‐scanner Penn Word scores. Additionally, the functional connections predicting 2‐back scores overlapped to a greater degree with those predicting List Sorting scores than with those predicting Picture Sequence or Penn Word scores. Functional connections with the insula, including connections between insular and parietal regions, predicted scores across the 2‐back, List Sorting, and Picture Sequence tasks. Conclusions Our findings validate functional connectivity observed during the N‐back task as a measure of working memory, which generalizes to predict episodic memory to a lesser extent. By building on our understanding of the predictive power of N‐back task functional connectivity, this work enhances our knowledge of relationships between working memory and episodic memory.

Background: The association between immune checkpoint inhibitors (ICIs) and Stevens-Johnsons syndrome (SJS) /toxic epidermal necrolysis (TEN) is unclear. We assessed the risk of SJS and TEN related to ICIs, via a systematic analysis of SJS/TEN cases reported in clinical trials and the FDA Adverse Event Reporting System (FAERS). Methods: We explored ICIs related SJS/TEN events in randomized control trials available in ClinicalTrials.gov and electronic databases (Pubmed, Embase, the Cochrane Central Register of Controlled Trials) up to 12 January 2021. Meta-analysis was performed by using Peto odds ratios (ORs) with 95% CIs. In a separate retrospective pharmacovigilance study of FAERs, cases of ICIs related SJS/TEN were extracted between the first quarter (Q1) of 2004 and Q4 of 2020. Disproportionality was analyzed using the proportional reports reporting odds ratio (ROR) and information components (IC). PROSPERO registration number: CRD42021232399. Findings: A total of 20 RCTs (11597 patients) were included. ICIs were associated with an increased risk of SJS/TEN (OR= 4.33, 95%CI:1.90–9.87). FAERS pharmacovigilance data identified 411 cases of SJS (n = 253) or TEN (n = 184) related to ICIs therapy. ICIs were significantly associated with SJS/TEN (n = 411; ROR=2.88, 95%CI:2.61–3.17; IC=1.49, 95%CI:1.35–1.65). The median onset time of SJS/TEN was 25.5 days (SJS:21.5 days; TEN:32 days) (n = 190), 97.5% of patients discontinued use of ICIs when suffering from SJS/TEN (n = 201). Of 305 cases that reported outcomes, 113 (37%) resulted in death (SJS:19.9%, TEN:61.6%). Interpretation: These data suggest that ICIs were significantly associated with increased risk of SJS/TEN.

Summary: Functional connectivity (FC) calculated from task fMRI data better reveals brain-phenotype relationships than rest-based FC, but how tasks have this effect is unknown. In over 700 individuals performing seven tasks, we use psychophysiological interaction (PPI) and predictive modeling analyses to demonstrate that task-induced changes in FC successfully predict phenotype, and these changes are not simply driven by task activation. Activation, however, is useful for prediction only if the in-scanner task is related to the predicted phenotype. To further characterize these predictive FC changes, we develop and apply an inter-subject PPI analysis. We find that moderate, but not high, task-induced consistency of the blood-oxygen-level-dependent (BOLD) signal across individuals is useful for prediction. Together, these findings demonstrate that in-scanner tasks have distributed, phenotypically relevant effects on brain functional organization, and they offer a framework to leverage both task activation and FC to reveal the neural bases of complex human traits, symptoms, and behaviors.

Artemisia selengensis straw is an agricultural residue with great potential as a renewable resource because it is rich in lignocellulose. In this study, A. selengensis straw was used as a source of hemicelluloses (ASH) and cellulose nanocrystals (ASCNC) to produce biodegradable films. Different content levels of ASCNC were used as additives to improve composite films with ASH and polyvinyl alcohol (PVA). Various mechanical and hydrophobic properties of the films were analyzed. The composite films enhanced by ASCNC exhibited greater strength and were more effective as a barrier to water vapor when compared to that of the control ASH/PVA film. The tensile strength of the composite film was increased 80.1% to 36.21 MPa with ASCNC loading exceeding 9%, and the water vapor transmission rate decreased 15.45% when 12% ASCNC was added. Furthermore, the ASCNC-enhanced ASH/PVA composite film reduced a greater amount of light transmission than the control film.

Aggressive behavior has negative effects on animal welfare and growth performance in pigs. The dopamine receptor D2 (DRD2) has a critical neuromodulator role in the dopamine signal pathway within the brain to control behavior. A functional single-nucleotide polymorphism (SNP), rs1110730503, in the promoter region of the porcine DRD2 gene was identified, which affects aggressive behavior in pigs. A chromatin immunoprecipitation (ChIP) assay was used to identify the interactions between interferon regulatory factor 1 (IRF1) and IRF2 with the DRD2 gene. The overexpression or knockdown of these two transcription factors in porcine kidney-15 (PK15) and porcine neuronal cells (PNCs) indicate that the binding of IRF1 to DRD2 promotes the transcription of the DRD2 gene, but the binding of IRF2 to the DRD2 gene inhibits its transcription. Furthermore, IRF1 and IRF2 are functionally antagonistic to each other. The downregulation of DRD2 or upregulation of IRF2 increased the apoptosis rate of porcine neuroglial cells. Taken together, we found that transcriptional factors IRF1 and IRF2 have vital roles in regulating the transcription of the DRD2 gene, and rs1110730503 (−915A/T) is a functional SNP that influences IRF2 binding to the promoter of the DRD2 gene. These findings will provide further insight towards controlling aggressive behavior in pigs.

Decoding or predicting cognitive traits from brain activity is an exciting prospect. Here, the authors show that task-based functional connectivity better predicts intelligence-related measures than rest-based connectivity, suggesting that cognitive tasks amplify individual differences in trait-relevant circuitry.

Steroid hormone levels are associated with estrous behavior, which affects timely mating and reproductive efficiency in pigs. 17β-hydroxysteroid dehydrogenase type 14 (HSD17B14) modulates steroid synthesis and metabolism. To identify the functional single nucleotide polymorphisms (SNPs) in the porcine HSD17B14 gene, ear tissues from Large White and Mi gilts were collected to extract genomic DNA. Variable lengths of truncated promoter of HSD17B14 gene were used to determine the promoter activity by a dual luciferase reporter system. The vector HSD17B14Phe or HSD17B14Val was transfected into porcine granulosa cells (GCs). The core promoter region was identified between −72 bp and −218 bp. Six of seven SNPs had significant differences of allele frequency between Large White and Mi gilts. The plasmids with the wild genotype AA of rs329427898 maintained a smaller fraction of promoter activity compared with the plasmids with the mutant genotype GG, while the plasmids with wild the genotype TT of rs319864566 had a greater promoter activity than the plasmids with the mutant genotype CC. A missense mutation (Phe73Val) caused changes in the structural dynamics and function of the HSD17B14 protein. The highly expressed HSD17B14Val degraded less estradiol into estrone, while the relatively lowly expressed HSD17B14Phe degraded more estradiol into estrone, suggesting the protein activity of HSD17B14Phe was greater than that of HSD17B14Val. Moreover, the HSD17B14Phe group has a greater apoptosis rate of porcine GCs. The HSD17B14 gene could been used as a candidate molecular marker for estrus behavior in pigs.

Pigs are animals that live in groups and have social hierarchies within the group. After mixing, they can re-establish social hierarchies within several days through fighting. Dominance hierarchical indices, such as I&SI, Elo rating, and Glicko rating, have been used to analyze social hierarchies of some social animals but not pigs. I&SI index involves iterative calculations that first minimize the number of inconsistencies (I) in a dominance matrix, and then minimize the strength of those inconsistencies (SI). Elo rating and Glicko rating indices are based on the sequence in which interactions occur, and continuously update ratings by looking at interactions sequentially. To study the temporal dynamics of social hierarchy formation and maintenance in weaned pigs after mixing, a total of 102 pigs (47 females and 55 barrows) were selected by similar body weight and mixed in 10 pens (10 or 11 females or barrows per pen). Their behavior was recorded and observed for 72 h after mixing. Results showed that hierarchical indices I&SI, Elo rating, and Glicko rating were associated with each other (|r| = 0.681 ~ 0.942, p < 0.001). I&SI was associated with logarithms of frequency of active attack (|r| = 0.65, p < 0.05) and tended to associated with logarithms of frequency of standoff (|r| = 0.48, p < 0.1). Elo rating, and Glicko rating were associated with the logarithms of duration of being bullied (|r| = 0.393~0.401, p < 0.05). In addition, Glicko rating tended to be associated with the logarithms of duration of active attack and frequency of active attack (|r| = 0.416~0.439, p < 0.1). Multiple linear regression analyses of logarithms of dyadic behavior indicators for three hierarchical indices indicated the same effects. The time (hours) to achieve social stability of pigs after mixing was lower for females than barrows (23.06 ± 4.15 vs. 40.55 ± 4.71 h; p < 0.001). The most dominant pig (the first ranked) in each pen quickly appeared within a few hours after mixing and remained stable. Overall, our study demonstrated that the ranks calculated by the three dominance hierarchical indices: I&SI, Elo rating, and Glicko rating, were consistent and partially associated with part of the dyadic behavioral indicators in weaned pigs after mixing.

Understanding the genetic background underlying the expression of behavioral traits has the potential to fasten the genetic progress for reduced aggressive behavior of pigs. The monoamine oxidase A (MAOA) gene is known as the “warrior” gene, as it has been previously linked to aggressive behavior in humans and livestock animals. To identify single nucleotide polymorphisms in porcine MAOA gene associated with aggressive behavior of pigs, a total of 500 weaned pigs were selected and mixed in 51 pens. In each pen, two aggressive and two docile pigs (a total of 204 pigs) were selected based on their composite aggressive score (CAS). Ear tissue was sampled to extract genomic DNA. Constructs containing variable lengths of truncated porcine MAOA promoter were used to determine the promoter activity by a dual luciferase reporter system. The core promoter region was located at −679 bp to −400 bp. A total of nine single nucleotide polymorphisms (SNPs) in MAOA gene were genotyped, of which six SNPs had significant differences (p < 0.05) in allele frequency between the aggressive and docile pigs. Linkage disequilibrium and association analyses showed that the pigs inherited the wild genotypes showed more aggressive behavior (p < 0.05) than pigs with the mutant genotypes of the four linked SNPs, rs321936011, rs331624976, rs346245147, and rs346324437. In addition, pigs of GCAA haplotype were more (p < 0.05) aggressive than the pigs with GCGA or ATGG haplotype. The construct containing the wild genotype GG of rs321936011 had lower (p = 0.031) promoter activity compared to the mutant genotype AA. These results suggest that the four linked SNPs in MAOA gene could be considered as a molecular marker for behavioral trait selection in pigs.

The detection range of a semi-active laser guidance system can deviate significantly from the design value over a wide ambient temperature range. In this paper, a mathematical model of the detection range of a semi-active laser guidance system is built and the main factors affecting the detection range are analyzed. The parameter responsivity, which shows significant change, is found by applying the ambient temperature stress to the four-quadrant PIN detector and its signal processing chain. The relationship between the maximum detection range and ambient temperature is established based on a given signal-to-noise ratio, which is necessary for reliable detection. The target temperature and tolerance are setup for real-time temperature compensation for the four-quadrant PIN detector. The ambient temperature stress is applied to the system under compensation to verify the effect of compensation. The experimental results show that the ratio of the maximum variation of the detection range to the design point is 6.9% after the compensation is implemented when the ambient temperature changes from −40 °C to 60 °C, which is improved by 13.2% compared to that without compensation.

17β-estradiol (E2) is a natural endocrine disruptor that is frequently detected in surface and groundwater sources, thereby threatening ecosystems and human health. The newly isolated E2-degrading strain Sphingomonas colocasiae C3-2 can degrade E2 through both the 4,5-seco pathway and the 9,10-seco pathway; the former is the primary pathway supporting the growth of this strain and the latter is a branching pathway. The novel gene cluster ean was found to be responsible for E2 degradation through the 4,5-seco pathway, where E2 is converted to estrone (E1) by EanA, which belongs to the short-chain dehydrogenases/reductases (SDR) superfamily. A three-component oxygenase system (including the P450 monooxygenase EanB1, the small iron-sulfur protein ferredoxin EanB2, and the ferredoxin reductase EanB3) was responsible for hydroxylating E1 to 4-hydroxyestrone (4-OH-E1). The enzymatic assay showed that the proportion of the three components is critical for its function. The dioxygenase EanC catalyzes ring A cleavage of 4-OH-E1, and the oxidoreductase EanD is responsible for the decarboxylation of the ring A-cleavage product of 4-OH-E1. EanR, a TetR family transcriptional regulator, acts as a transcriptional repressor of the ean cluster. The ean cluster was also found in other reported E2-degrading sphingomonads. In addition, the novel two-component monooxygenase EanE1E2 can open ring B of 4-OH-E1 via the 9,10-seco pathway, but its encoding genes are not located within the ean cluster. These results refine research on genes involved in E2 degradation and enrich the understanding of the cleavages of ring A and ring B of E2. [ABSTRACT FROM AUTHOR]