Compressive sensing-based multi-focus line-scanning two-photon microscopy for fast 3D imaging.

Fast 3D volume imaging methods have been playing increasingly important roles in biological studies. In this article, we present the design and characterization of a multi-focus line-scanning two-photon microscope. Specifically, a digital micromirror device (DMD) is employed to generate a randomly distributed focus array on a plane (i.e., x-z) via binary holography. Next, a galvanometric mirror scans the focus array in a direction normal to the plane (i.e., y-axis) over the imaging volume. For sparse samples, e.g., neural networks in a brain, 1-3 foci are used together with compressive sensing algorithm to achieve a volume imaging rate of 15.5 volumes/sec over 77 × 120 × 40 µm3. High-resolution optical cross-sectional images on selected planes and regions can be generated by sequentially scanning the laser focus generated on the x-z plane with good imaging speeds (e.g., 107 frames/sec over 80 × 120 × 40 µm3). In the experiments, microbeads, pollens, and mouse brain slices have been imaged to characterize the point spread function and volume image rate and quality at different sampling ratios. The results show that the multi-focus line-scanning microscope presents a fast and versatile 3D imaging platform for deep tissue imaging and dynamic live animal studies.

Decreased cuticular penetration minimizes the impact of the pyrethroid insecticide λ-cyhalothrin on the insect predator Eocanthecona furcellata.

The use of broad-spectrum pesticides may reduce the biological control efficacy of predatory arthropods. Hence, the risks of pesticides to predators need to be evaluated. Here, we assessed the effects of a broad spectrum pyrethroid λ-cyhalothrin on a polyphagous predatory insect Eocanthecona furcellata via contact exposure route. The recommended application rate of λ-cyhalothrin was lower than the LR50 and HQ (in-field) was equal to 0.57, indicating the risk of λ-cyhalothrin to E. furcellata was low. Dried λ-cyhalothrin residue had no effect on the mortality, body weight, protein content of cuticle, or activities of major detoxification enzymes in E. furcellata. Residual of λ-cyhalothrin was only detected in the cuticle and legs of E. furcellata with a decreasing trend as time went by and no λ-cyhalothrin was detected inside the body. Additionally, a comparative transcriptome analysis was conducted to study global changes in gene expression in E. furcellata at different time points following exposure to λ-cyhalothrin-contaminated environment. A total of 57,839 unigenes with an average length of 1044 bp and an N50 of 1820 bp were obtained. In total, 118 and 109 differentially expressed genes (DEGs) at 12 h, and 60 h were identified between two groups. The DEGs were largely enriched in functional categories related to the structural constituent of cuticle. Accordingly, multiple cuticle protein-coding genes were up-regulated at 12 h after pesticide exposure. The present study stressed the importance of evaluating the compatibility between a specific pesticide (λ-cyhalothrin) and E. furcellata via simulating the releasing predators after insecticide application. The data could help optimize the pesticide use, optimizing the ecological services of E. furcellata as a BCA, and expanding its use into more areas of agriculture.

Predatory stink bug, Eocanthecona furcellata (Wolff) responses to oral exposure route of λ-cyhalothrin via sex-specific modulation manner.

The toxic effects of insecticides on predatory arthropods have closely related to their exposure routes. However, little is known about the effects of insecticide on reproductive parameters when the route of exposure occurs at a trophic level via prey intake. We therefore conducted current studies assessing whether Eocanthecona furcellata adults would be affected by feeding with λ-cyhalothrin-contaminated prey. Reproductive parameters, i.e. prolonged premating and preoviposition durations, reduced number of egg batches and egg amount, disturbed ovarian development, and suppressed expression of reproductive related genes were observed in E. furcellata females by feeding with treated prey. Moreover, reduced survival rate and altered carbohydrate metabolism parameters were detected in male bugs. Biochemical parameters, including MDA content, the activities of three antioxidant enzymes and three detoxification enzymes exhibited sex-specific responses after oral-exposure to λ-cyhalothrin in E. furcellata. The results indicate that the insecticide affects the fitness and leads to impairing reproductive potential via sex-specific modulation manner in predator insects. Taken together, our results provide a comprehensive assessment about detrimental impacts of λ-cyhalothrin-exposure on predators via prey intake, as well as a solid basis for further research to protect the predators from hazardous impacts of insecticides.

Broadband angular dispersion compensation for digital micromirror devices.

In this Letter, we present a compact broadband angular dispersion compensation method for digital micromirror devices (DMDs) and ultrashort pulse lasers, which effectively extends the conventional single-wavelength compensation design to a wide wavelength range of 300 nm. First, a parametric model was developed for the dispersion compensation unit, consisting of a transmission grating and a 4f telescope sub-unit, to guide the selection of components and parameter optimization for broadband applications. In the experiments, we designed a single slit-based metrology system to measure and quantify the compensated angular dispersion of a Ti:sapphire femtosecond laser with a pulse width of 75 fs. The results indicate that our method can reduce the angular dispersion to 0.04°, i.e., pulse widening less than 20 fs, over a wavelength range of 750-1050 nm. To demonstrate this, the DMD system was used as a multi-wavelength beam shaper to reconstruct a wavefront that contains the "CUHK" pattern and the results confirmed its ability to provide effective broadband angular dispersion compensation. This means the DMD can be used in different applications that employ a broadband light source, e.g., wavelength tunable femtosecond laser, attosecond laser, supercontinuum laser, and multi-color LED.

Thermal Emitting Strategy to Synthesize Atomically Dispersed Pt Metal Sites from Bulk Pt Metal.

Developing a facile route to access active and well-defined single atom sites catalysts has been a major area of focus for single atoms catalysts (SACs). Herein, we demonstrate a simple approach to generate atomically dispersed platinum via a thermal emitting method using bulk Pt metal as a precursor, significantly simplifying synthesis routes and minimizing synthesis costs. The ammonia produced by pyrolysis of Dicyandiamide can coordinate with platinum atoms by strong coordination effect. Then, the volatile Pt(NH3) x can be anchored onto the surface of defective graphene. The as-prepared Pt SAs/DG exhibits high activity for the electrochemical hydrogen evolution reaction and selective oxidation of various organosilanes. This viable thermal emitting strategy can also be applied to other single metal atoms, for example, gold and palladium. Our findings provide an enabling and versatile platform for facile accessing SACs toward many industrial important reactions.

Efficient and Robust Hydrogen Evolution: Phosphorus Nitride Imide Nanotubes as Supports for Anchoring Single Ruthenium Sites.

Amorphous phosphorus nitride imide nanotubes (HPN) are reported as a novel substrate to stabilize materials containing single-metal sites. Abundant dangling unsaturated P vacancies play a role in stabilization. Ruthenium single atoms (SAs) are successfully anchored by strong coordination interactions between the d orbitals of Ru and the lone pair electrons of N located in the HPN matrix. The atomic dispersion of Ru atoms can be distinguished by X-ray absorption fine structure measurements and spherical aberration correction electron microscopy. Importantly, Ru SAs@PN is an excellent electrocatalyst for the hydrogen evolution reaction (HER) in 0.5 m H2 SO4 , delivering a low overpotential of 24 mV at 10 mA cm-2 and a Tafel slope of 38 mV dec-1 . The catalyst exhibits robust stability in a constant current test at a large current density of 162 mA cm-2 for more than 24 hours, and is operative for 5000 cycles in a cyclic voltammetry test. Additionally, Ru SAs@PN presents a turnover frequency (TOF) of 1.67 H2 s-1 at 25 mV, and 4.29 H2 s-1 at 50 mV, in 0.5 m H2 SO4 solution, outperforming most of the reported hydrogen evolution catalysts. Density functional theory (DFT) calculations further demonstrate that the Gibbs free energy of adsorbed H* over the Ru SAs on PN is much closer to zero compared with the Ru/C and Ru SAs supported on carbon and C3 N4 , thus considerably facilitating the overall HER performance.

Sublethal effect of chlorpyrifos on predatory behavior and physiology of Eocanthecona furcellata (Hemiptera: Pentatomidae).

Insecticides have been known to reduce the predation efficacy of natural enemies. However, the mechanism of the sublethal effect of insecticides on the functional response of predators remains unclear. This study investigated the sublethal effects of the broad-spectrum insecticide chlorpyrifos on the predatory bug Eocanthecona furcellata (Wolff), which is a potential biological control agent against pests in integrated pest management (IPM) programs. After exposure to a sublethal concentration of chlorpyrifos, the predation capacity and the maximum predatory number of E. furcellata increased by 11.27 and 15.26%, respectively, with prey handling time decreased by 15.07%, and the searching efficiency increased by 5.88-12.61%. Additionally, the intraspecific interference effect was enhanced. Glutathione S-transferase (GST) activity was significantly decreased after 12- to 60-h treatment. At 12 h after treatment, the expression levels of GST gene (GST3), acetylcholinesterase gene (AChE), and cytochrome P450 monooxygenasegene (cyp6B1) were significantly up-regulated by 1.47-, 1.48-, and 2.05-fold, respectively, while GST gene (GST1) was significantly down-regulated by 16.67-fold. These results indicated that a sublethal chlorpyrifos concentration inhibited the GST activity and stimulated the predatory behavior of E. furcellata. The results will advance our understanding of the toxicological mechanism of predatory stink bug responses to insecticides and predict chlorpyrifos' effects on predators in an IPM program.

Identification and characterization of circadian clock genes in the head transcriptome of Conopomorpha sinensis Bradley.

Conopomorpha sinensis Bradley is the most detrimental pest to litchi and longan in China. Adult eclosion, locomotion, mating and oviposition of C. sinensis usually occur at night, regulated by a circadian rhythm. Nevertheless, our understanding of the linkages between adult circadian rhythms and clock genes remains inadequate. To address this gap, transcriptomic analysis was conducted on female and male heads (including antennae) of C. sinensis using the Illumina HiSeq 6000 platform to identify major circadian clock-related genes. The annotated sequences were analyzed by BLASTx, and candidate clock genes were classified based on conservation, predicted domain architectures, and phylogenetic analysis. The analysis revealed a higher conservation of these genes among the compared moths. Further, the expression profile analysis showed a significant spatiotemporal and circadian rhythmic accumulation of some clock genes during development. The candidate clock genes were predominantly expressed in the head, highlighting their crucial function in circadian rhythm regulation. Moreover, CsinPer, CsinTim1, and CsinCry1 displayed similar dynamic expressions with a peak expression level in the 4th age adults, suggesting their involvement in regulation of courtship and mating behaviors. The CsinPer and CsinTim1 mRNA oscillated strongly with a similar phase, containing a peak expression just before the female mating peak. This work will greatly contribute to understanding the circadian clock system of C. sinensis and provide valuable information for further studies of the molecular mechanisms involved in rhythmicity in fruit-boring pests.

Alpha oscillation mediates the interaction between suicide risk and symptom severity in Major Depressive Disorder.

Objective: The aim of our study was to explore the relationship between changes in neural oscillatory power in the EEG, the severity of depressive-anxiety symptoms, and the risk of suicide in MDD. Methods: 350 MDD patients' demographic and clinical data were collected, and their depressive and anxious symptoms were evaluated using HDRS-17 and HAMA-14, along with a suicide risk assessment using the Nurses' Global Assessment of Suicide Risk (NGASR). EEG data were captured, processed, and analyzed to study brain activity patterns related to MDD. The participants were divided based on suicide risk levels, and statistical analyses, including chi-square, t-tests, Pearson's correlations were used to explore the associations between brain activity, symptom severity, and suicide risk. Closely related variables were identified and ultimately the optimal model was screened using stepwise regression analysis with a forward strategy, and mediation effects were further used to determine the possible interactions between the variables in the regression model. Results: The regression model showed a significant effect of HDRS-17 and alpha power of Medial Occipital Cortex (MOC) on suicide risk, with elevated HDRS-17 increasing suicide risk and elevated alpha power decreasing suicide risk. Mediation effect analyses showed that MOC alpha power partially mediated the effect of depression level on suicide risk, and that an increase in depression severity may lead to a decrease in MOC alpha power, while a decrease in MOC alpha power may lead to an increase in suicide risk. Conclusion: The severity of depression directly increases suicide risk, whereas higher alpha power in the MOC serves as a protective factor, reducing this risk. Notably, MOC alpha power not only directly impacts suicide risk but also mediates the effects of both depression severity and anxiety levels on this risk. Limitations: The relatively small sample size of this study may limit the representativeness of the overall MDD patient population and the detailed analysis of different subgroups. This study did not delve into the relationship between the severity of cognitive symptoms in MDD patients and suicide risk.

Neural oscillation in bipolar disorder: a systematic review of resting-state electroencephalography studies.

Bipolar disorder (BD) is a severe psychiatric disease with high rates of misdiagnosis and underdiagnosis, resulting in a significant disease burden on both individuals and society. Abnormal neural oscillations have garnered significant attention as potential neurobiological markers of BD. However, untangling the mechanisms that subserve these baseline alternations requires measurement of their electrophysiological underpinnings. This systematic review investigates consistent abnormal resting-state EEG power of BD and conducted an initial exploration into how methodological approaches might impact the study outcomes. This review was conducted in Pubmed-Medline and Web-of-Science in March 2024 to summarize the oscillation changes in resting-state EEG (rsEEG) of BD. We focusing on rsEEG to report spectral power in different frequency bands. We identified 10 studies, in which neural oscillations was compared with healthy individuals (HCs). We found that BD patients had abnormal oscillations in delta, theta, beta, and gamma bands, predominantly characterized by increased power, indicating potential widespread neural dysfunction, involving multiple neural networks and cognitive processes. However, the outcomes regarding alpha oscillation in BD were more heterogeneous, which is thought to be potentially influenced by the disease severity and the diversity of samples. Furthermore, we conducted an initial exploration into how demographic and methodological elements might impact the study outcomes, underlining the importance of implementing standardized data collection methods. Key aspects we took into account included gender, age, medication usage, medical history, the method of frequency band segmentation, and situation of eye open/eye close during the recordings. Therefore, in the face of abnormal multiple oscillations in BD, we need to adopt a comprehensive research approach, consider the multidimensional attributes of the disease and the heterogeneity of samples, and pay attention to the standardized experimental design to improve the reliability and reproducibility of the research results.

Evidence for the Participation of Chemosensory Proteins in Response to Insecticide Challenge in Conopomorpha sinensis.

Chemosensory proteins (CSPs) are a type of efficient transporters that can bind various hydrophobic compounds. Previous research has shown that the expression levels of some insect CSPs were significantly increased after insecticide treatment. However, the role of CSPs in response to insecticide challenge is unclear. Conopomorpha sinensis is the most destructive borer pest of litchi (Litchi chinensis) and longan (Euphoria longan) in the Asia-Pacific region. Here, we studied the expression patterns and potential functions of 12 CSP genes (CsCSPs) from C. sinensis in response to λ-cyhalothrin exposure. The spatiotemporal distribution of CsCSPs suggested that they were predominantly expressed in the female abdomen, female legs, and male legs. The expression levels of CsCSPs were affected in a time-dependent manner after λ-cyhalothrin treatment in both sexes of C. sinensis adults. Compared to the control group, the expression levels of CsCSP1, CsCSP2, CsCSP9, and CsCSP12 in females were significantly increased by 2-4 times, while only one CsCSP, three CsCSPs, and two CsCSPs were significantly upregulated in males at three time points post-treatment. The sex-biased variance of CSP expression may be related to sex-specific detoxification enzymatic activities and survival rates of C. sinensis in response to insecticide challenge. Homology modeling and molecular docking analyses showed that the binding energy value of CsCSP1-12 to λ-cyhalothrin was negative and the binding energy between CsCSP9 and λ-cyhalothrin was the lowest (-11.35 kJ/mol). Combined with expression alterations of CsCSP1-12, the results indicate that CsCSP1, CsCSP2, CsCSP9, and CsCSP12 were involved in binding and ferrying of λ-cyhalothrin in C. sinensis.

Clinical characteristics of current COVID-19 rehabilitation outpatients in China.

To understand the clinical characteristics of omicron in COVID-19 Rehabilitation Clinic after the current shift of dynamic zeroing policy, we consecutively collected the patients' data who visited in COVID-19 Rehabilitation Clinic of a Grade-A tertiary hospital in Hangzhou, Zhejiang Province, from January 3 to January 10, 2023, analyzed related data and then compared the pneumonia between elderly and non-elderly groups. The results showed that 95.68% of the patients in COVID-19 Rehabilitation Clinic had symptoms, 70.10% had a dry cough, 12.36% had abnormal complete blood count or C-reactive protein, 19.35% had electrolyte disorder, and 2% had abnormal troponin or creatine kinase-MB. 40.45% of patients had abnormal lung CT findings, among them 86.49% of elderly patients had abnormal lung CT findings, and the utilization rate of glucocorticoids in COVID-19 Rehabilitation Clinic was only 5.98%, although people are all susceptible to getting the COVID-19 infection, the elderly are more prone to getting pneumonia, and the glucocorticoids utilization rate is relatively insufficient. It is needed to be stressed that Chinese medical staff should pay more attention to the elderly patients who are vulnerable to getting pneumonia during this period.

Functional characterization of chemosensory proteins in response to artificial light treatment in Thalassodes immissaria.

BACKGROUND: Chemosensory proteins (CSPs) play a vital role in the response to environmental stimuli in insects. However, the involvement of insect CSPs in the stress response to night-time environmental changes has not been examined. RESULTS: In the current study, four TiCSP genes were first cloned from Thalassodes immissaria by transcriptome and RACE-PCR techniques. TiCSPs had typical characteristics of insect CSPs, including a highly conserved four-cysteine motif and olfactory-specific protein D (OS-D) or OS-D superfamily domains. TiCSP1-4 were clustered classified within different clades in a phylogenetic analysis and were differentially expressed at all developmental stages. Under night-time artificial light stress, the expression levels of TiCSP1 in males were significantly decreased at 24 h, and those of TiCSP2 were decreased in both adult sexes at 48 h. In a molecular docking analysis, TiCSPs showed relatively higher binding affinities with sex pheromone components than with host plant volatile molecules. CONCLUSION: Taking the reduced expression levels of TiCSPs and binding affinities into account, TiCSP1 and TiCSP2 are involved in the stress response processes of T. immissaria under light treatment. Our study supplies basic data for the evaluation of the effects of light interference control technology - an emerging physical control measure on nontarget pests of lychee orchards. © 2023 Society of Chemical Industry.

Optical coherence tomography angiography metrics in diabetes: Focusing on diabetic retinopathy and carotid atherosclerosis.

BACKGROUND: To explore the value of Optical Coherence Tomography Angiography (OCTA) metrics in the early diagnosis of vascular complications in diabetes. METHODS: All participants underwent OCTA with a swept-source OCT device. Automated measurements of the foveal avascular zone (FAZ) area, vessel density (VD), and blood flow density (BFD) of both 3 × 3 and 6 × 6 windows were then obtained after a quality check. RESULTS: Diagnostic models based on multiple risk factors were developed separately for diabetic retinopathy and carotid atherosclerosis using random forest and multivariate logistic regression methods. The addition of specific OCTA metrics improved the diagnostic prediction of DR compared with the models of risk factors alone (Inner Retinal Blood Flow Density in 3 × 3 window, IRBFD; Brier score 0.124 vs. 0.149; AUC, 0.887 vs. 0.836) (Central Retinal Blood Flow Density in 3 × 3 window, CRBFD; Brier score 0.142 vs. 0.149; AUC, 0.851 vs. 0.836). Adding diabetic peripheral vascular disease (DPVD) indicator improved the prediction of carotid atherosclerosis (Brier score, 0.180 vs. 0.192; AUC, 0.802 vs. 0.781. The FAZ in the 3 × 3 window also achieved this effect when targeting only T2DM patients (AUC, 0.797 vs. 0.766; Brier score, 0.183 vs. 0.195). CONCLUSIONS: Focusing on IRBFD and CRBFD in the 3 × 3 window of OCTA allows for a more sensitive prediction of the occurrence of DR in diabetic patients. Meanwhile, the quantitative microvascular information provided by OCTA and the occurrence of DPVD may be crucial for diagnosing carotid atherosclerosis. For T2DM patients, we also propose the possibility of FAZ in the 3 × 3 window as a potential diagnostic indicator.

Multi-omics analysis reveals the molecular regulatory network underlying the prevention of Lactiplantibacillus plantarum against LPS-induced salpingitis in laying hens.

BACKGROUND: Salpingitis is one of the common diseases in laying hen production, which greatly decreases the economic outcome of laying hen farming. Lactiplantibacillus plantarum was effective in preventing local or systemic inflammation, however rare studies were reported on its prevention against salpingitis. This study aimed to investigate the preventive molecular regulatory network of microencapsulated Lactiplantibacillus plantarum (MLP) against salpingitis through multi-omics analysis, including microbiome, transcriptome and metabolome analyses. RESULTS: The results revealed that supplementation of MLP in diet significantly alleviated the inflammation and atrophy of uterus caused by lipopolysaccharide (LPS) in hens (P < 0.05). The concentrations of plasma IL-2 and IL-10 in hens of MLP-LPS group were higher than those in hens of LPS-stimulation group (CN-LPS group) (P < 0.05). The expression levels of TLR2, MYD88, NF-κB, COX2, and TNF-α were significantly decreased in the hens fed diet supplemented with MLP and suffered with LPS stimulation (MLP-LPS group) compared with those in the hens of CN-LPS group (P < 0.05). Differentially expressed genes (DEGs) induced by MLP were involved in inflammation, reproduction, and calcium ion transport. At the genus level, the MLP supplementation significantly increased the abundance of Phascolarctobacterium, whereas decreased the abundance of Candidatus_Saccharimonas in LPS challenged hens (P < 0.05). The metabolites altered by dietary supplementation with MLP were mainly involved in galactose, uronic acid, histidine, pyruvate and primary bile acid metabolism. Dietary supplementation with MLP inversely regulates LPS-induced differential metabolites such as LysoPA (24:0/0:0) (P < 0.05). CONCLUSIONS: In summary, dietary supplementation with microencapsulated Lactiplantibacillus plantarum prevented salpingitis by modulating the abundances of Candidatus_Saccharimonas, Phascolarctobacterium, Ruminococcus_torques_group and Eubacterium_hallii_group while downregulating the levels of plasma metabolites, p-tolyl sulfate, o-cresol and N-acetylhistamine and upregulating S-lactoylglutathione, simultaneously increasing the expressions of CPNE4, CNTN3 and ACAN genes in the uterus, and ultimately inhibiting oviducal inflammation.

Inferring Drug-Target Interactions Based on Random Walk and Convolutional Neural Network.

Computational strategies for identifying new drug-target interactions (DTIs) can guide the process of drug discovery, reduce the cost and time of drug development, and thus promote drug development. Most recently proposed methods predict DTIs via integration of heterogeneous data related to drugs and proteins. However, previous methods have failed to deeply integrate these heterogeneous data and learn deep feature representations of multiple original similarities and interactions related to drugs and proteins. We therefore constructed a heterogeneous network by integrating a variety of connection relationships about drugs and proteins, including drugs, proteins, and drug side effects, as well as their similarities, interactions, and associations. A DTI prediction method based on random walk and convolutional neural network was proposed and referred to as DTIPred. DTIPred not only takes advantage of various original features related to drugs and proteins, but also integrates the topological information of heterogeneous networks. The prediction model is composed of two sides and learns the deep feature representation of a drug-protein pair. On the left side, random walk with restart is applied to learn the topological vectors of drug and protein nodes. The topological representation is further learned by the constructed deep learning frame based on convolutional neural network. The right side of the model focuses on integrating multiple original similarities and interactions of drugs and proteins to learn the original representation of the drug-protein pair. The results of cross-validation experiments demonstrate that DTIPred achieves better prediction performance than several state-of-the-art methods. During the validation process, DTIPred can retrieve more actual drug-protein interactions within the top part of the predicted results, which may be more helpful to biologists. In addition, case studies on five drugs further demonstrate the ability of DTIPred to discover potential drug-protein interactions.

Effects of different probiotic fermented feeds on production performance and intestinal health of laying hens.

The aim of this study was to investigate the effects of different probiotic fermented diets on production performance and intestinal health of laying hens. A total of 360 healthy 22-wk-age Jingfen No. 6 layers were randomly divided into 4 treatments: basal diet (CON); supplemented with 6% Clostridium butyricum fermented feed (CB); supplemented with 6% Lactobacillus crispatus fermented feed (LC); supplemented with 6% Lactobacillus salivarius fermented feed (LS). The experiment lasted for 8 wk. The results showed that the levels of crude fiber, ß-glucan and pH of feed decreased significantly after fermentation (P < 0.05). Compared with CON group, the feed conversion ratio (FCR) was decreased significantly (P < 0.05), and albumen height and Haugh unit in LC group and LS group were increased significantly (P < 0.05). Fermented feed supplementation significantly improved villus height (VH) of the jejunum and the ratio of villus height to crypt depth (VH/CD) of the ileum (P < 0.05). Additionally, the VH and VH/CD of the duodenum were significantly increased in LS group (P < 0.05). Furthermore, the ACE and chao1 indexes in LS group were extremely significant higher than that in the other 3 groups (P < 0.05). In addition, compared with CON group, the abundance of Rikenellaceae and Methanobacteriaceae was significantly decreased at the family level in LC group and LS group (P < 0.05), while the abundance of Ruminocaceae was significantly higher (P < 0.05). Collectively, feeding Lactobacillus salivarius and Lactobacillus crispatus fermented feed improved the FCR, albumen height and Haugh unit of laying hens, and Lactobacillus salivarius fermented feed supplementation could improve intestinal health by ameliorating intestinal morphology, altering microbial composition and enhancing microbial community richness.

Medical image segmentation model based on triple gate MultiLayer perceptron.

To alleviate the social contradiction between limited medical resources and increasing medical needs, the medical image-assisted diagnosis based on deep learning has become the research focus in Wise Information Technology of med. Most of the existing medical segmentation models based on Convolution or Transformer have achieved relatively sound effects. However, the Convolution-based model with a limited receptive field cannot establish long-distance dependencies between features as the Network deepens. The Transformer-based model produces large computation overhead and cannot generalize the bias of local features and perceive the position feature of medical images, which are essential in medical image segmentation. To address those issues, we present Triple Gate MultiLayer Perceptron U-Net (TGMLP U-Net), a medical image segmentation model based on MLP, in which we design the Triple Gate MultiLayer Perceptron (TGMLP), composed of three parts. Firstly, considering encoding the position information of features, we propose the Triple MLP module based on MultiLayer Perceptron in this model. It uses linear projection to encode features from the high, wide, and channel dimensions, enabling the model to capture the long-distance dependence of features along the spatial dimension and the precise position information of features in three dimensions with less computational overhead. Then, we design the Local Priors and Global Perceptron module. The Global Perceptron divides the feature map into different partitions and conducts correlation modelling for each partition to establish the global dependency between partitions. The Local Priors uses multi-scale Convolution with high local feature extraction ability to explore further the relationship of context feature information within the structure. At last, we suggest a Gate-controlled Mechanism to effectively solves the problem that the dependence of position embeddings between Patches and within Patches in medical images cannot be well learned due to the relatively small number of samples in medical images segmentation data. Experimental results indicate that the proposed model outperforms other state-of-the-art models in most evaluation indicators, demonstrating its excellent performance in segmenting medical images.

Two new species of Chilocorus Leach, 1815 from Laos (ColeopteraCoccinellidaeChilocorini).

BACKGROUND: Chilocorus Leach, 1815 the largest genus of Chilocorini, contains more than 80 species, mainly preying on Coccoidea. Many species of Chilocorus are economically important as they are widely used as biological control agents. NEW INFORMATION: In this study, two new species of the genus Chilocorus Leach are described from Laos: C.toulakhomianus Li & Wang, sp. n. and C.vientianicus Li & Wang, sp. n. Diagnoses and detailed descriptions of the new species are given. Each species is illustrated in detail, including genitalia. Distribution maps are presented.

Prediction of Drug-Target Interactions Based on Network Representation Learning and Ensemble Learning.

Identifying interactions between drugs and target proteins is a critical step in the drug development process, as it helps identify new targets for drugs and accelerate drug development. The number of known drug-protein interactions (positive samples) is much lower than that of the unknown ones (negative samples), which forms a class imbalance. Most previous methods only utilised part of the negative samples to train the prediction model, so most of the information on negative samples was neglected. Therefore, a new method must be developed to predict candidate drug-related proteins and fully utilise negative samples to improve prediction performance. We present a method based on non-negative matrix factorisation and gradient boosting decision tree (GBDT), named NGDTP, to identify the candidate drug-protein interactions. NGDTP integrates multiple kinds of protein similarities, drugs-proteins interactions, and multiple kinds of drugs similarities at different levels, including target proteins of drugs, drug-related diseases, and side effects of drugs. We propose a network representation learning method based on matrix factorisation to learn low-dimensional vector representations of drug and protein nodes. On the basis of these low-dimensional node representations, a GBDT-based prediction model was constructed and it obtains the association scores through establishing multiple decision trees for a drug-protein pairs. NGDTP is an ensemble learning model that fully utilises all the negative samples to effectively alleviate the problem of class imbalance. NGDTP achieves superior prediction performance when it is compared with several state-of-the-art methods. The experimental results indicate that NGDTP also retrieves more actual drug-protein interactions in the top part of prediction result, which drew significant attention from the biologists. In addition, case studies on 10 drugs further confirmed the ability of the NGDTP to identify potential candidate proteins for drugs.