Li2ZnCu3 modified Cu current collector to regulate Li deposition.

Rationally designing a current collector that can maintain low lithium (Li) porosity and smooth morphology while enduring high-loading Li deposition is crucial for realizing the high energy density of Li metal batteries, but it is still challengeable. Herein, a Li2ZnCu3 alloy-modified Cu foil is reported as a stable current collector to fulfill the stable high-loading Li deposition. Benefiting from the in-situ alloying, the generated numerous Li2ZnCu3@Cu heterojunctions induce a homogeneous Li nucleation and dense growth even at an ultrahigh capacity of 12 mAh cm-2. Such a spatial structure endows the overall Li2ZnCu3@Cu electrode with the manipulated steric hindrance and outmost surface electric potential to suppress the side reactions during Li stripping and plating. The resultant Li||Li2ZnCu3@Cu asymmetric cell preserves an ultrahigh average Coulombic efficiency of 99.2% at 3 mA cm-2/6 mAh cm-2 over 200 cycles. Moreover, the Li-Li2ZnCu3@Cu||LiFePO4 cell maintains a cycling stability of 87.5% after 300 cycles. After coupling with the LiCoO2 cathode (4 mAh cm-2), the cell exhibits a high energy density of 407.4 Wh kg-1 with remarkable cycling reversibility at an N/P ratio of 3. All these findings present a doable way to realize the high-capacity, dendrite-free, and dense Li deposition for high-performance Li metal batteries.

IL-17 in plasma and bronchoalveolar lavage fluid in non-neutropenic patients with invasive pulmonary aspergillosis.

Background: The purpose of this study was to investigate the diagnostic value of IL-17 detection in bronchoalveolar lavage fluid (BALF) and plasma samples from nonneutropenic patients with invasive pulmonary aspergillosis. Methods: We retrospectively collected data on non-neutropenic patients who were suspected to have IPA admitted to the Third Affiliated Hospital of Soochow University between March 2020 to January 2023. IL-17 and GM were measured using enzyme-linked immunosorbent assays. Results: A total of 281 patients were enrolled in this study, of which 62 had proven or probable IPA and the remaining 219 patients were controls. The plasma and BALF IL-17 levels were significantly higher in the IPA group compared with the control group. The plasma GM, plasma IL17, BALF GM, and BALF IL17 assays had sensitivities of 56.5%, 72.6%, 68.7%, and 81.2%, respectively, and specificities of 87.7%, 69.4%, 91.9%, and 72.6%, respectively. The sensitivity of IL17 in plasma and BALF was higher than that of GM. Plasma GM in combination with IL-17 increases the sensitivity but does not decrease the diagnostic specificity of GM testing. The diagnostic sensitivity and specificity of BALF GM combined with IL-17 for IPA in non-neutropenic patients were greater than 80% and there was a significant increase in sensitivity compared with BALF GM. Conclusions: Plasma and BALF IL-17 levels were significantly higher in non-neutropenic patients with IPA. The sensitivity of plasma and BLAF IL-17 for diagnosing IPA in non-neutropenic patients was superior to that of GM. Combined detection of lavage fluid GM and IL17 significantly improves the diagnosis of IPA in non-neutropenic patients. The combined detection of GM and IL-17 in plasma also contributes to the diagnosis of IPA in patients who cannot tolerate invasive procedures.

tRNA-m1A methylation controls the infection of Magnaporthe oryzae by supporting ergosterol biosynthesis.

Ergosterols are essential components of fungal plasma membranes. Inhibitors targeting ergosterol biosynthesis (ERG) genes are critical for controlling fungal pathogens, including Magnaporthe oryzae, the fungus that causes rice blast. However, the translational mechanisms governing ERG gene expression remain largely unexplored. Here, we show that the Trm6/Trm61 complex catalyzes dynamic N1-methyladenosine at position 58 (m1A58) in 51 transfer RNAs (tRNAs) of M. oryzae, significantly influencing translation at both the initiation and elongation stages. Notably, tRNA m1A58 promotes elongation speed at most cognate codons mainly by enhancing eEF1-tRNA binding rather than affecting tRNA abundance or charging. The absence of m1A58 leads to substantial decreases in the translation of ERG genes, ergosterol production, and, consequently, fungal virulence. Simultaneously targeting the Trm6/Trm61 complex and the ergosterol biosynthesis pathway markedly improves rice blast control. Our findings demonstrate an important role of m1A58-mediated translational regulation in ergosterol production and fungal infection, offering a potential strategy for fungicide development.

SbPL1CE8 from Segatella bryantii combines with SbGH28GH105 in a multi-enzyme cascade for pectic biomass utilization.

Pectinases are useful biocatalysts for pectic biomass processing and are extensively used in the food/feed, textile and papermaking industries. Two pectinase genes, a pectate lyase (SbPL1CE8) and a polygalacturonase (SbGH28GH105) were isolated from Segatella bryantii and functionally characterized. Recombinant rSbPL1CE8 was most active against polygalacturonic acid (PGA) and pectin with a 60 % degree of esterification, with kcat/Km values of 721.18 ± 64.77 and 327.02 ± 22.44 mL/s/mg, respectively. Truncated rSbPL1 acted as a mesophilic alkaline pectate lyase, which was highly resistant to inactivation by methanol and ethanol. The rSbPL1CE8 exclusively digested PGA and pectin into unsaturated digalacturonate (uG2), which was further converted into galacturonic acid by rSbGH28GH105. The rSbPL1CE8 was highly effective for saccharification of waste materials from Zea mays, Oryza sativa and Arachis hypogaea processing, and for ramie fiber degumming. This novel pectate lyase has great potential for application in industrial pectic biomass processing.

Genome wide-scale CRISPR-Cas9 knockout screens identify a fitness score for optimized risk stratification in colorectal cancer.

BACKGROUND: The molecular complexity of colorectal cancer poses a significant challenge to the clinical implementation of accurate risk stratification. There is still an urgent need to find better biomarkers to enhance established risk stratification and guide risk-adapted treatment decisions. METHODS: we systematically analyzed cancer dependencies of 17 colorectal cancer cells and 513 other cancer cells based on genome-scale CRISPR-Cas9 knockout screens to identify colorectal cancer-specific fitness genes. A regression model was built using colorectal cancer-specific fitness genes, which was validated in other three independent cohorts. 30 published gene expression signatures were also retrieved. FINDINGS: We defined a total of 1828 genes that were colorectal cancer-specific fitness genes and identified a 22 colorectal cancer-specific fitness gene (CFG22) score. A high CFG22 score represented unfavorable recurrence and mortality rates, which was validated in three independent cohorts. Combined with age, and TNM stage, the CFG22 model can provide guidance for the prognosis of colorectal cancer patients. Analysis of genomic abnormalities and infiltrating immune cells in the CFG22 risk stratification revealed molecular pathological difference between the subgroups. Besides, drug analysis found that CFG22 high patients were more sensitive to clofibrate. INTERPRETATION: The CFG22 model provided a powerful auxiliary prediction tool for identifying colorectal cancer patients with high recurrence risk and poor prognosis, optimizing precise treatment and improving clinical efficacy.

Maternal intervention with a combination of galacto-oligosaccharides and hyocholic acids during late gestation and lactation increased the reproductive performance, colostrum composition, antioxidant and altered intestinal microflora in sows.

Introduction: This study was conducted to evaluate the effects of dietary galacto-oligosaccharides (GOS) and hyocholic acids (HCA) during late gestation and lactation on reproductive performance, colostrum quality, antioxidant capacity and gut microbiota in multiparous sows. Methods: A total of 60 healthy multiparous cross-bred sows (Landrace × Yorkshire) were randomly fed 4 groups diets as follows: the basal diets (CTRL group), or the basal diets containing only 600 mg/kg GOS (GOS group), 600 mg/kg GOS + 100 mg/kg HCA (GOS + Low HCA group), and 600 mg/kg + 200 mg/kg HCA (GOS + High HCA group) from d 85 of gestation to weaning. Multiple parameters of sows were determined. Results: There was a trend of shortening the labor process of sows (p = 0.07) in the GOS group and GOS + Low/High HCA group. Compared with the CTRL group, the GOS + Low/High HCA group increased the average piglets weight at birth (p < 0.05), and increased the IgA concentration of colostrum (p < 0.05). In addition, serum triglyceride (TG) concentration was lower (p < 0.05), and serum total antioxidant capacity (T-AOC) was higher (p < 0.05) in the GOS and GOS + Low/High HCA groups than in the CTRL group at farrowing. Serum catalase (CAT) activities was higher in the GOS and GOS + High HCA groups than in the CTRL group at farrowing. The 16S rRNA analysis showed that GOS combination with high-dose HCA shaped the composition of gut microbiota in different reproductive stages (d 107 of gestation, G107; d 0 of lactation, L0; d 7 of lactation, L7). At the phylum level, the relative abundance of Bacteroidota and Desulfobacterota in G107, Bacteroidota, and Proteobacteria in L0, and Planctomycetota in L7 was increased in GOS + High HCA group (p < 0.05). Spearman correlation analysis showed that Streptococcus was positively correlated with the serum TG but negatively correlated with the average piglets weight at birth (p < 0.05). Conclusion: This investigation demonstrated that the administration of galacto-oligosaccharides (GOS) in conjunction with hyocholic acids (HCA), to sows with nutrient restrictions during late gestation and lactation, further improved their antioxidant capacity and milk quality. The observed beneficial effects of GOS + HCA supplementation could potentially be linked to an improvement in gut microbiota disorders of the sows.

Discovery of LC-MI-3: A Potent and Orally Bioavailable Degrader of Interleukin-1 Receptor-Associated Kinase 4 for the Treatment of Inflammatory Diseases.

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a promising therapeutic target in inflammation-related diseases. However, the inhibition of IRAK4 kinase activity may lead to moderate anti-inflammatory efficacy owing to the dual role of IRAK4 as an active kinase and a scaffolding protein. Herein, we report the design, synthesis, and biological evaluation of an efficient and selective IRAK4 proteolysis-targeting chimeric molecule that eliminates IRAK4 scaffolding functions. The most potent compound, LC-MI-3, effectively degraded cellular IRAK4, with a half-maximal degradation concentration of 47.3 nM. LC-MI-3 effectively inhibited the activation of downstream nuclear factor-κB signaling and exerted more potent pharmacological effects than traditional kinase inhibitors. Furthermore, LC-MI-3 exerted significant therapeutic effects in lipopolysaccharide- and Escherichia coli-induced acute and chronic inflammatory skin models compared with kinase inhibitors in vivo. Therefore, LC-MI-3 is a candidate IRAK4 degrader in alternative targeting strategies and advanced drug development.

Arterial Smooth Muscle Cell AKAP150 Mediates Exercise-Induced Repression of CaV1.2 Channel Function in Cerebral Arteries of Hypertensive Rats.

BACKGROUND: Hypertension is a major, prevalent risk factor for the development and progression of cerebrovascular disease. Regular exercise has been recommended as an excellent choice for the large population of individuals with mild-to-moderate elevations in blood pressure, but the mechanisms that underlie its vascular-protective and antihypertensive effects remain unknown. Here, we describe a mechanism by which myocyte AKAP150 (A-kinase anchoring protein 150) inhibition induced by exercise training alleviates voltage-dependent L-type Ca2+ channel (CaV1.2) activity and restores cerebral arterial function in hypertension. METHODS: Spontaneously hypertensive rats and newly generated smooth muscle-specific AKAP150 knockin mice were used to assess the role of myocyte AKAP150/CaV1.2 channel in regulating cerebral artery function after exercise intervention. RESULTS: Activation of the AKAP150/PKCα (protein kinase Cα) signaling increased CaV1.2 activity and Ca2+ influx of cerebral arterial myocyte, thus enhancing vascular tone in spontaneously hypertensive rats. Smooth muscle-specific AKAP150 knockin mice were hypertensive with higher CaV1.2 channel activity and increased vascular tone. Furthermore, treatment of Ang II (angiotensin II) resulted in a more pronounced increase in blood pressure in smooth muscle-specific AKAP150 knockin mice. Exercise training significantly reduced arterial myocyte AKAP150 expression and alleviated CaV1.2 channel activity, thus restoring cerebral arterial function in spontaneously hypertensive rats and smooth muscle-specific AKAP150 knockin mice. AT1R (AT1 receptor) and AKAP150 were interacted closely in arterial myocytes. Exercise decreased the circulating Ang II and Ang II-involved AT1R-AKAP150 association in myocytes of hypertension. CONCLUSIONS: The current study demonstrates that aerobic exercise ameliorates CaV1.2 channel function via inhibiting myocyte AKAP150, which contributes to reduced cerebral arterial tone in hypertension.

Swimming Exercise Protocol and Care Methods for Pregnant Rats.

The developmental origins of health and disease concept highlights the impact of early environments on chronic non-communicable diseases like diabetes, cardiovascular disease, and cancer. Studies using animal models have investigated how maternal factors such as undernutrition, overnutrition, obesity, and exposure to chemicals or hypoxia affect fetal development and offspring health, leading to issues like low birth weight, high blood pressure, dyslipidemia, and insulin resistance. Given the increasing prevalence of overweight and obesity among reproductive-age women, effective interventions are critical. Maternal exercise during pregnancy has emerged as a key intervention, benefiting both mother and offspring and reducing the risk of disease. This study compares the differences of three exercise models on pregnant rats: voluntary wheel running, motorized treadmills, and swimming. Swimming is the most beneficial option due to its safe and controlled intensity levels. This protocol details the rat breeding methods, swimming training during pregnancy, and post-breeding nursing protocols. This model, suitable for various rat and mouse species, is useful for studying the benefits of maternal exercise on offspring health and intergenerational wellness.

Using machine learning to enlarge the measurement range and promote the compactness of the optical fiber torsion sensor based on the Sagnac interferometer.

The support vector regression (SVR) algorithm is presented to demodulate the torsion angle of an optical fiber torsion sensor based on the Sagnac interferometer with the panda fiber. Experimental results demonstrate that with the aid of SVR algorithm, the information in the transmission spectrum of the sensor can be used fully to realize the regression prediction of the directional torsion angle. The full torsion angle ranges from -360° to 360° can be predicted with a mean absolute error (MAE) of 2.24° and determination coefficient (R2) of 0.9996. The impact of the angle sampling interval and wavelength resolution of the spectrometer on the prediction accuracy of the directional torsion angle and the suitability of the SVR algorithm for compact optical fiber sensor and other optical fiber torsion sensors based on the Sagnac interferometer are discussed. Moreover, the multi-objective SVR algorithm is used to eliminate the interference of strain during torsion angle measurement. The SVR algorithm can efficiently enlarge the measurement range of the torsion angle and break through the challenge of demodulating sensing signal for compact fiber torsion sensor. Compared to the prediction accuracy of common machine learning algorithms of artificial neural network (ANN) algorithm, random forest (RF) algorithm, and K-nearest neighbor (KNN) algorithm, the SVR algorithm has the advantages of higher measurement accuracy and shorter testing time.

Age at menarche and idiopathic pulmonary fibrosis: a two-sample mendelian randomization study.

BACKGROUND: Sex difference in the incidence rate of idiopathic pulmonary fibrosis (IPF) indicates that estrogen has a certain protective effect on the disease. Nevertheless, there is a dearth of study investigating the association between factors pertaining to endogenous estrogen exposure level, such as age at menarche (AAM) in women, and IPF. Our study intended to employ Mendelian randomization (MR) method to elucidate the causal association between AAM and IPF. METHODS: Our study utilized AAM as a measure of endogenous estrogen exposure and investigated its causal effect on the risk of IPF through MR. We employed the inverse variance weighted (IVW) method to assess the causal relationship between AAM and IPF risk, with supplementary analyses conducted using the weighted median estimator (WME) and MR-Egger method. Several sensitivity analyses were performed to assess the dependability of MR estimates. RESULTS: A total of 9 selected single nucleotide polymorphisms (SNPs) significantly associated with AAM were selected as instrumental variables. The IVW method showed that genetically later AAM was associated with an increased risk of IPF (odds ratio [OR] = 1.0014, 95%confidence interval [CI] = 1.0005-1.0023, p = 0.001). The median weighting method and the MR-Egger method obtained similar estimates, and no heterogeneity or pleiotropy was found, indicating that the results were robust. CONCLUSIONS: Our MR study suggested a causal relationship between a later onset of menarche and a heightened susceptibility to IPF.

Value of rapid on-site evaluation combined with interventional pulmonology techniques in the diagnosis of pulmonary cryptococcosis.

OBJECTIVES: The aim of this study is to evaluate the diagnostic value of rapid on-site evaluation (ROSE) combined with computed tomography-guided percutaneous needle biopsy (CT-PNB) or radial endobronchial ultrasound-guided transbronchial lung biopsy (EBUS-TBLB) for pulmonary cryptococcosis (PC). METHODS: Clinical data of 33 patients diagnosed with PC at the Third Affiliated Hospital of Soochow University between February 2018 and June 2023 were retrospectively analysed. Patients were divided into the CT-PNB and EBUS-TBLB groups based on the intervention method, and the diagnostic positivity rate and incidence of complications were compared between the two groups. RESULTS: Compared with the final diagnosis, the positive diagnostic rates of ROSE, histopathology and serum CrAg of all patients were 81.8% (27/33), 72.7% (24/33) and 63.6% (21/33), respectively. The average turnaround times of the three methods were 0.1 (0.1-0.2) h, 96.0 (48.0-120.0) h and 7.8 (4.5-13.6) h, respectively (P < 0.001). The coincidence rate between histopathology and ROSE was 84.8% with a kappa value of 0.574. The positive diagnostic rate for PC was significantly higher in the CT-PNB group than in the EBUS-TBLB group (92.9% vs. 57.9%), and the difference was statistically significant (P < 0.05). Combined with the ROSE results, the positive diagnostic rate in the EBUS-TBLB group increased to 84.2% (16/19). CONCLUSION: ROSE has commendable accuracy and timeliness, and CT-PNB offers further advantages in this regard. ROSE enhances the diagnostic efficiency of EBUS-TBLB for PC and is safe and effective.

Hierarchical Li electrochemistry using alloy-type anode for high-energy-density Li metal batteries.

Exploiting thin Li metal anode is essential for high-energy-density battery, but is severely plagued by the poor processability of Li, as well as the uncontrollable Li plating/stripping behaviors and Li/electrolyte interface. Herein, a thickness/capacity-adjustable thin alloy-type Li/LiZn@Cu anode is fabricated for high-energy-density Li metal batteries. The as-formed lithophilic LiZn alloy in Li/LiZn@Cu anode can effectively regulate Li plating/stripping and stabilize the Li/electrolyte interface to deliver the hierarchical Li electrochemistry. Upon charging, the Li/LiZn@Cu anode firstly acts as Li source for homogeneous Li extraction. At the end of charging, the de-alloy of LiZn nanostructures further supplements the Li extraction, actually playing the Li compensation role in battery cycling. While upon discharging, the LiZn alloy forms just at the beginning, thereby regulating the following Li homogeneous deposition. The reversibility of such an interesting process is undoubtedly verified from the electrochemistry and in-situ XRD characterization. This work sheds light on the facile fabrication of practical Li metal anodes and useful Li compensation materials for high-energy-density Li metal batteries.

Li ions traffic controller on thin lithium metal anode: Regulating deposition, optimizing and protecting solid electrolyte interphase.

The performance of thin lithium metal anodes is affected due to issues that weaken the electrode-electrolyte interphase. In this work, a coating layer serving as a Li+ traffic controller based on hexadecyl trimethyl ammonium bis(trifluoromethanesulphonyl)imide ([CTA][TFSI]) and poly (vinylidene difluoride co-hexafluoropropylene) (P(VDF-HFP)) is used to stabilize the thin lithium metal interface. The CTA+ ions in the coating layer can effectively regulate the distribution of Li+ concentration to promote uniform deposition of lithium. The anion of [CTA][TFSI] can optimize solid electrolyte interphase (SEI) with inorganic-rich components, which improve the ionic conductivity and reaction kinetics. Furthermore, the flexible polymer skeleton can fortify the fragile SEI, facilitating the consistent operation of the battery. Due to these improvements, a thin Li metal anode (4 mAh cm-2) with a coating layer in a Li||Li symmetric cell demonstrates a lifespan of 600 h at 1 mA cm-2 and 1 mAh cm-2. Notably, full cells with an ultra-low negative electrode/positive electrode = 1 (N/P = 1) demonstrate a stable performance over 200 cycles and 90 cycles at 0.5C and 1C (1C = 170 mA g-1), respectively.

Quorum sensing-induced transition from colloidal waves to Turing-like patterns in chemorepulsive active colloids.

The study of active systems, especially in the presence of a chemical background field, is garnering significant attention. Traditionally, the self-propelled velocity of active colloids was assumed to be constant, independent of the local density of colloids. In this work, we introduce a chemotactic active system that features quorum sensing (QS), wherein particles act as chemorepellents. Interestingly, these particles lose their activity in regions of high local particle density. Our findings reveal that QS leads to a transition from an oscillatory colloidal wave to a Turing-like pattern, with the observation of an intermediate state. With the variation of the sensing threshold, both the mean oscillation frequency of the system and the number of clusters exhibit non-monotonic dependence. Furthermore, the QS-induced pattern differs markedly from systems without QS, primarily due to the competitive interplay between diffusion and chemotaxis. The dynamics of this phenomenon are explained using a coarse-grained mean field model.

Correlation analysis of regional carbon emission intensity and green industry development-A case study of Chengdu-Chongqing region.

Industrial structure markedly affects the level of carbon emissions generated in a region. It is imperative to study the industrial structure of the Chengdu-Chongqing region to obtain information to achieve regional high-quality development by promoting low-carbon development. We selected 16 cities in Chengdu-Chongqing area as the research object in this study. The total carbon emissions (CE), carbon intensity (CI) and per capita carbon emissions (PCE) were calculated for each city. The green industry development (GI) evaluation indexes were then extracted, and the comprehensive evaluation value was determined using the entropy weight-TOPSIS model (EWM-TOPSIS). The green industry development was used as the core explanatory variable to construct a system representing the dynamic relationship between green industry development and carbon intensity using the quantile regression (QR) model. The results of the study showed that: (1) the total carbon emissions of Chengdu-Chongqing region increased whereas the carbon intensity decreased from 2010 to 2020. (2) The green industry development evaluation results showed that Chengdu-Chongqing had unevenly distributed green industry development during the study period, and Chengdu and Chongqing cities had higher green industry development values than other cities. (3) The green industry development of the region had a significant negative effect on carbon intensity at low quantile and a significant positive effect on carbon intensity at high quantile. Energy supply (ES) was positively correlated with the carbon intensity of the region at 1 % level of significance, whereas urbanization rate (U) and power consumption (PEC) were negatively correlated with the carbon intensity at 1 % level of significance. We comprehensively evaluated the development of green industry and introduced it as a core explanatory variable into the quantile regression model to explore the relationship between regional carbon emission intensity and industrial development. The results provide a reference for designing strategies to promote high-quality development in the cities in the Chengdu-Chongqing region.

High sensitivity twist sensor based on suspended core fiber Sagnac interferometer with temperature calibration.

A high sensitivity optical fiber twist sensor based on Suspend Core Fiber Sagnac Interference (SCFSI) is proposed and experimentally demonstrated. By filling the air hole of the Suspend Core Fiber (SCF) with alcohol, the twist sensitivity of the twist sensor is greatly improved to 8.37 nm/°. Moreover, the valid angle measurement range of the sensor can be expanded by utilizing the combination of intensity demodulation and wavelength demodulation. The sensor not only has high twist angle sensitivity but also exhibits a capability of temperature calibration. Since the wavelength shifts of the interference fringes of Mach-Zehnder Interferometer (MZI) formed in the suspend core of SCF appears insensitive to twist angle, the parasitic interference formed by MZI can be used for temperature calibration. Due to compact structure, easy fabrication and low temperature cross sensitivity, the proposed sensor has a great potential for structural health monitoring, such as buildings, towers, bridges, and many other infrastructures.

Artificial Intelligence Aided Lipase Production and Engineering for Enzymatic Performance Improvement.

With the development of artificial intelligence (AI), tailoring methods for enzyme engineering have been widely expanded. Additional protocols based on optimized network models have been used to predict and optimize lipase production as well as properties, namely, catalytic activity, stability, and substrate specificity. Here, different network models and algorithms for the prediction and reforming of lipase, focusing on its modification methods and cases based on AI, are reviewed in terms of both their advantages and disadvantages. Different neural networks coupled with various algorithms are usually applied to predict the maximum yield of lipase by optimizing the external cultivations for lipase production, while one part is used to predict the molecule variations affecting the properties of lipase. However, few studies have directly utilized AI to engineer lipase by affecting the structure of the enzyme, and a set of research gaps needs to be explored. Additionally, future perspectives of AI application in enzymes, including lipase engineering, are deduced to help the redesign of enzymes and the reform of new functional biocatalysts. This review provides a new horizon for developing effective and innovative AI tools for lipase production and engineering and facilitating lipase applications in the food industry and biomass conversion.

Genome-wide identification and expression analysis of the NRT genes in Ginkgo biloba under nitrate treatment reveal the potential roles during calluses browning.

Nitrate is a primary nitrogen source for plant growth, and previous studies have indicated a correlation between nitrogen and browning. Nitrate transporters (NRTs) are crucial in nitrate allocation. Here, we utilized a genome-wide approach to identify and analyze the expression pattern of 74 potential GbNRTs under nitrate treatments during calluses browning in Ginkgo, including 68 NITRATE TRANSPORTER 1 (NRT1)/PEPTIDE TRANSPORTER (PTR) (NPF), 4 NRT2 and 2 NRT3. Conserved domains, motifs, phylogeny, and cis-acting elements (CREs) were analyzed to demonstrate the evolutionary conservation and functional diversity of GbNRTs. Our analysis showed that the NPF family was divided into eight branches, with the GbNPF2 and GbNPF6 subfamilies split into three groups. Each GbNRT contained 108-214 CREs of 19-36 types, especially with binding sites of auxin and transcription factors v-myb avian myeloblastosis viral oncogene homolog (MYB) and basic helix-loop-helix (bHLH). The E1X1X2E2R motif had significant variations in GbNPFs, indicating changes in the potential dynamic proton transporting ability. The expression profiles of GbNRTs indicated that they may function in regulating nitrate uptake and modulating the signaling of auxin and polyphenols biosynthesis, thereby affecting browning in Ginkgo callus induction. These findings provide a better understanding of the role of NRTs during NO3- uptake and utilization in vitro culture, which is crucial to prevent browning and develop an efficient regeneration and suspension production system in Ginkgo.

Machine-learning-assisted omnidirectional bending sensor based on a cascaded asymmetric dual-core PCF sensor.

An omnidirectional bending sensor comprising cascaded asymmetric dual-core photonic crystal fibers (ADCPCFs) is designed and demonstrated experimentally. Upon cascading and splicing two ADCPCFs at a lateral rotation angle, the transmission spectrum of the sensor becomes highly dependent on the bending direction. Machine learning (ML) is employed to predict the curvature and bending orientation of the bending sensor for the first time, to the best of our knowledge. The experimental results demonstrate that the ADCPCF sensor used in combination with machine learning can predict the curvature and omnidirectional bending orientation within 360° without requiring any post-processing fabrication steps. The prediction accuracy is 99.85% with a mean absolute error (MAE) of 2.7° for bending direction measurement and 98.08% with an MAE of 0.03 m-1 for the curvature measurement. This promising strategy utilizes the global features (full spectra) in combination with machine learning to overcome the dependence of the sensor on high-quality transmission spectra, the wavelength range, and a special wavelength dip in the conventional dip tracking method. This excellent omnidirectional bending sensor has large potential for structural health monitoring, robotic arms, medical instruments, and wearable devices.