Self-Flipping Solar Seesaw Evaporators Leverage Scaling to De-Scale.

Salt scaling poses a significant obstacle to the practical implementation of solar-driven evaporation for desalination. Attempts to mitigate scaling by enhancing mass transfer often lead to a compromise in evaporation efficiency due to associated heat loss. In the present work, a novel seesaw evaporator with a Janus structure to harness scaling for periodic self-descaling is reported. The seesaw evaporators are facilely fabricated by delignifying balsa wood and subsequently single-sided spray-coating it with soot and polydimethylsiloxane (PDMS). This unique Janus structure enables the evaporator to float on the brine while ensuring an ample supply of solution for evaporation. During evaporation, salt ions are transported directionally toward the cocked end of the evaporator to form scaling, triggering the seesaw evaporator to flip once a threshold is reached. The accumulated salts re-dissolve back into the solution. By adjusting the tilt angle, the evaporator can achieve an impressive evaporation rate of up to 2.65 kg m-2  h-1 when evaporating an 8 wt.% NaCl solution. Remarkably, these evaporators maintain a stable evaporation rate during prolonged 120 h operation and produce ≈3.93-6.35 L m⁻2 ·day⁻¹ of freshwater from simulated brines when assembled into an evaporation device.

Predictive Value of CFIm25 Expression in Peripheral Blood Monocytes for Coronary Atherosclerosis.

Background: Cleavage factor Im25 (CFIm25) regulates cell function by affecting mRNA editing processes and plays diverse roles in various diseases. Studies have found that peripheral blood monocytes are valuable in diagnosing and prognosing coronary atherosclerosis. However, no studies have examined the predictive value of CFIm25 expression in peripheral blood monocytes for coronary atherosclerosis. Methods and Results: We collected the coronary angiography results of 267 patients and calculated the Gensini score to evaluate their degree of coronary atherosclerosis. We isolated peripheral blood monocytes and detected CFIm25 RNA expression. Based on their Gensini score, we divided the patients into negative (0, n = 46), mild lesion (≤ 8, n = 71), moderate lesion (8-23, n = 76), and severe lesion (≥ 23, n = 74) groups. Results showed that CFIm25 expression correlated negatively with the Gensini score and the number of involved coronary vessels. Univariate and multivariate binary logistic regression analyses showed that CFIm25 expression in peripheral blood monocytes was a protective factor for severe lesions, ≥ 50% stenosis, and three-vessel lesions. The areas under the receiver operating characteristic curve of CFIm25 expression for predicting lesions, severe lesions, ≥50% stenosis, and three-vessel lesions were 0.743, 0.735, 0.791, and 0.736, respectively. Conclusions: CFIm25 expression in peripheral blood monocytes correlates negatively with the degree of coronary atherosclerosis and helps predict the severity and number of coronary artery lesions.

Mutation (G275E) of nAChR subunit Foα6 associated with spinetoram resistance in Australian western flower thrips, Frankliniella occidentalis (Pergande).

Western flower thrips, Frankliniella occidentalis is an economically important agricultural pest. It causes damage by feeding and oviposition or indirectly by plant virus transmission. Australian F. occidentalis are resistant to many insecticides including spinosad and the related chemical spinetoram. Spinetoram resistance to F. occidentalis has been recently reported in three different Australian States, however, mechanisms conferring that resistance have not been investigated. To identify the mechanisms underlying resistance to spinetoram in F. occidentalis, we sequenced the genomic region of nicotinic acetylcholine receptor Foα6 in number of spinosad and spinetoram resistant field-populations. We found that a single nucleotide substitution (G to A) in exon 9 of the α6 subunit was present in resistant strains (G275E) and absent from susceptible. By examining field populations we consider the G275E mutation is the major cause of resistance to spinetoram in Australian F. occidentalis. We developed a real-time PCR diagnostic assay to quickly identify resistant alleles in field-populations. The method was used to test spinetoram resistant F. occidentalis collected from Australian cotton during the 2018-2019. Results show thrips tested carried the G275E mutation and the resistance allele was unusually widely distributed. The wide distribution of G275E mutation was not expected because spinetoram is not extensively used in Australian cotton. We speculate resistance may relate to extensive chemical use in crops nearby such as horticulture where thrips are often targeted for control. Our molecular diagnostic assay can provide timely and precise resistance frequency information that can support sustainable chemical use including spinetoram based IPM.

Improving Ponzi Scheme Contract Detection Using Multi-Channel TextCNN and Transformer.

With the development of blockchain technologies, many Ponzi schemes disguise themselves under the veil of smart contracts. The Ponzi scheme contracts cause serious financial losses, which has a bad effect on the blockchain. Existing Ponzi scheme contract detection studies have mainly focused on extracting hand-crafted features and training a machine learning classifier to detect Ponzi scheme contracts. However, the hand-crafted features cannot capture the structural and semantic feature of the source code. Therefore, in this study, we propose a Ponzi scheme contract detection method called MTCformer (Multi-channel Text Convolutional Neural Networks and Transofrmer). In order to reserve the structural information of the source code, the MTCformer first converts the Abstract Syntax Tree (AST) of the smart contract code to the specially formatted code token sequence via the Structure-Based Traversal (SBT) method. Then, the MTCformer uses multi-channel TextCNN (Text Convolutional Neural Networks) to learn local structural and semantic features from the code token sequence. Next, the MTCformer employs the Transformer to capture the long-range dependencies of code tokens. Finally, a fully connected neural network with a cost-sensitive loss function in the MTCformer is used for classification. The experimental results show that the MTCformer is superior to the state-of-the-art methods and its variants in Ponzi scheme contract detection.

Development of abamectin resistance in Tetranychus urticae in Australian cotton and the establishment of discriminating doses for T. lambi.

Since the 1980s Tetranychus urticae Koch has dominated Australian cotton due to its ability to develop resistance. Here we give screening data for a range of chemicals tested against T. urticae including abamectin, bifenthrin, diafenthiuron, etoxazole and propargite and speculate why abamectin resistance emerged without warning. Abamectin resistance was not detected in T. urticae in Australian cotton before season 2007-2008 when a few resistant individuals were detected in a single strain. Resistance was detected again in season 2010-2011 and continued to be detected in every subsequent season comprising 80% of strains tested in 2018-2019. We speculate the reason may relate to prophylactic abamectin use to prevent mite flare with Creontiades dilutes Stål mirid sprays. With the introduction of transgenic Bt-cotton, spraying significantly reduced and anecdotally Tetranychus lambi became more abundant. Although T. lambi may now be more common than T. urticae its response to chemical controls is completely unknown. Tetranychus lambi conspecific dose responses were established to support resistance monitoring against abamectin, diafenthiuron and propargite that generated discriminating dose (DD) estimates of 0.0007 g/L abamectin, 0.03 g/L diafenthiuron and 0.7 g/L propargite. These DD were used in season 2018-2019 but resistance was not detected against any product including abamectin. The reason why T. lambi may now dominate despite T. urticae being still resistant is speculated and thought related to the progressive reduction in insecticide use in Australian cotton and/or the changing weed complex in the transgenic cotton era.

Combining information from genome-wide association and multi-tissue gene expression studies to elucidate factors underlying genetic variation for residual feed intake in Australian Angus cattle.

BACKGROUND: Genome-wide association studies (GWAS) are extensively used to identify single nucleotide polymorphisms (SNP) underlying the genetic variation of complex traits. However, much uncertainly often still exists about the causal variants and genes at quantitative trait loci (QTL). The aim of this study was to identify QTL associated with residual feed intake (RFI) and genes in these regions whose expression is also associated with this trait. Angus cattle (2190 steers) with RFI records were genotyped and imputed to high density arrays (770 K) and used for a GWAS approach to identify QTL associated with RFI. RNA sequences from 126 Angus divergently selected for RFI were analyzed to identify the genes whose expression was significantly associated this trait with special attention to those genes residing in the QTL regions. RESULTS: The heritability for RFI estimated for this Angus population was 0.3. In a GWAS, we identified 78 SNPs associated with RFI on six QTL (on BTA1, BTA6, BTA14, BTA17, BTA20 and BTA26). The most significant SNP was found on chromosome BTA20 (rs42662073) and explained 4% of the genetic variance. The minor allele frequencies of significant SNPs ranged from 0.05 to 0.49. All regions, except on BTA17, showed a significant dominance effect. In 1 Mb windows surrounding the six significant QTL, we found 149 genes from which OAS2, STC2, SHOX, XKR4, and SGMS1 were the closest to the most significant QTL on BTA17, BTA20, BTA1, BTA14, and BTA26, respectively. In a 2 Mb windows around the six significant QTL, we identified 15 genes whose expression was significantly associated with RFI: BTA20) NEURL1B and CPEB4; BTA17) RITA1, CCDC42B, OAS2, RPL6, and ERP29; BTA26) A1CF, SGMS1, PAPSS2, and PTEN; BTA1) MFSD1 and RARRES1; BTA14) ATP6V1H and MRPL15. CONCLUSIONS: Our results showed six QTL regions associated with RFI in a beef Angus population where five of these QTL contained genes that have expression associated with this trait. Therefore, here we show that integrating information from gene expression and GWAS studies can help to better understand the genetic mechanisms that determine variation in complex traits.

Comparing allele specific expression and local expression quantitative trait loci and the influence of gene expression on complex trait variation in cattle.

BACKGROUND: The mutations changing the expression level of a gene, or expression quantitative trait loci (eQTL), can be identified by testing the association between genetic variants and gene expression in multiple individuals (eQTL mapping), or by comparing the expression of the alleles in a heterozygous individual (allele specific expression or ASE analysis). The aims of the study were to find and compare ASE and local eQTL in 4 bovine RNA-sequencing (RNA-Seq) datasets, validate them in an independent ASE study and investigate if they are associated with complex trait variation. RESULTS: We present a novel method for distinguishing between ASE driven by polymorphisms in cis and parent of origin effects. We found that single nucleotide polymorphisms (SNPs) driving ASE are also often local eQTL and therefore presumably cis eQTL. These SNPs often, but not always, affect gene expression in multiple tissues and, when they do, the allele increasing expression is usually the same. However, there were systematic differences between ASE and local eQTL and between tissues and breeds. We also found that SNPs significantly associated with gene expression (p < 0.001) were likely to influence some complex traits (p < 0.001), which means that some mutations influence variation in complex traits by changing the expression level of genes. CONCLUSION: We conclude that ASE detects phenomenon that overlap with local eQTL, but there are also systematic differences between the SNPs discovered by the two methods. Some mutations influencing complex traits are actually eQTL and can be discovered using RNA-Seq including eQTL in the genes CAST, CAPN1, LCORL and LEPROTL1.

Genome variants associated with RNA splicing variations in bovine are extensively shared between tissues.

BACKGROUND: Mammalian phenotypes are shaped by numerous genome variants, many of which may regulate gene transcription or RNA splicing. To identify variants with regulatory functions in cattle, an important economic and model species, we used sequence variants to map a type of expression quantitative trait loci (expression QTLs) that are associated with variations in the RNA splicing, i.e., sQTLs. To further the understanding of regulatory variants, sQTLs were compare with other two types of expression QTLs, 1) variants associated with variations in gene expression, i.e., geQTLs and 2) variants associated with variations in exon expression, i.e., eeQTLs, in different tissues. RESULTS: Using whole genome and RNA sequence data from four tissues of over 200 cattle, sQTLs identified using exon inclusion ratios were verified by matching their effects on adjacent intron excision ratios. sQTLs contained the highest percentage of variants that are within the intronic region of genes and contained the lowest percentage of variants that are within intergenic regions, compared to eeQTLs and geQTLs. Many geQTLs and sQTLs are also detected as eeQTLs. Many expression QTLs, including sQTLs, were significant in all four tissues and had a similar effect in each tissue. To verify such expression QTL sharing between tissues, variants surrounding (±1 Mb) the exon or gene were used to build local genomic relationship matrices (LGRM) and estimated genetic correlations between tissues. For many exons, the splicing and expression level was determined by the same cis additive genetic variance in different tissues. Thus, an effective but simple-to-implement meta-analysis combining information from three tissues is introduced to increase power to detect and validate sQTLs. sQTLs and eeQTLs together were more enriched for variants associated with cattle complex traits, compared to geQTLs. Several putative causal mutations were identified, including an sQTL at Chr6:87392580 within the 5th exon of kappa casein (CSN3) associated with milk production traits. CONCLUSIONS: Using novel analytical approaches, we report the first identification of numerous bovine sQTLs which are extensively shared between multiple tissue types. The significant overlaps between bovine sQTLs and complex traits QTL highlight the contribution of regulatory mutations to phenotypic variations.

Evaluation of Food Fineness by the Bionic Tongue Distributed Mechanical Testing Device.

In this study, to obtain a texture perception that is closer to the human sense, we designed eight bionic tongue indenters based on the law of the physiology of mandibular movements and tongue movements features, set up a bionic tongue distributed mechanical testing device, performed in vitro simulations to obtain the distributed mechanical information over the tongue surface, and preliminarily constructed a food fineness perception evaluation model. By capturing a large number of tongue movements during chewing, we analyzed and simulated four representative tongue movement states including the tiled state, sunken state, raised state, and overturned state of the tongue. By analyzing curvature parameters and the Gauss curvature of the tongue surface, we selected the regional circle of interest. With that, eight bionic tongue indenters with different curvatures over the tongue surface were designed. Together with an arrayed film pressure sensor, we set up a bionic tongue distributed mechanical testing device, which was used to do contact pressure experiments on three kinds of cookies-WZ Cookie, ZL Cookie and JSL Cookie-with different fineness texture characteristics. Based on the distributed mechanical information perceived by the surface of the bionic tongue indenter, we established a food fineness perception evaluation model by defining three indicators, including gradient, stress change rate and areal density. The correlation between the sensory assessment and model result was analyzed. The results showed that the average values of correlation coefficients among the three kinds of food with the eight bionic tongue indenters reached 0.887, 0.865, and 0.870, respectively, that is, a significant correlation was achieved. The results illustrate that the food fineness perception evaluation model is effective, and the bionic tongue distributed mechanical testing device has a good practical significance for obtaining food texture mouthfeel information.

Odor Fingerprint Analysis Using Feature Mining Method Based on Olfactory Sensory Evaluation.

In this paper, we aim to use odor fingerprint analysis to identify and detect various odors. We obtained the olfactory sensory evaluation of eight different brands of Chinese liquor by a lab-developed intelligent nose. From the respective combination of the time domain and frequency domain, we extract features to reflect the samples comprehensively. However, the extracted feature combined time domain and frequency domain will bring redundant information that affects performance. Therefore, we proposed data by Principal Component Analysis (PCA) and Variable Importance Projection (VIP) to delete redundant information to construct a more precise odor fingerprint. Then, Random Forest (RF) and Probabilistic Neural Network (PNN) were built based on the above. Results showed that the VIP-based models achieved better classification performance than PCA-based models. In addition, the peak performance (92.5%) of the VIP-RF model had a higher classification rate than the VIP-PNN model (90%). In conclusion, odor fingerprint analysis using a feature mining method based on the olfactory sensory evaluation can be applied to monitor product quality in the actual process of industrialization.

Characterization and Profiling of Liver microRNAs by RNA-sequencing in Cattle Divergently Selected for Residual Feed Intake.

MicroRNAs (miRNAs) are short non-coding RNAs that post-transcriptionally regulate expression of mRNAs in many biological pathways. Liver plays an important role in the feed efficiency of animals and high and low efficient cattle demonstrated different gene expression profiles by microarray. Here we report comprehensive miRNAs profiles by next-gen deep sequencing in Angus cattle divergently selected for residual feed intake (RFI) and identify miRNAs related to feed efficiency in beef cattle. Two microRNA libraries were constructed from pooled RNA extracted from livers of low and high RFI cattle, and sequenced by Illumina genome analyser. In total, 23,628,103 high quality short sequence reads were obtained and more than half of these reads were matched to the bovine genome (UMD 3.1). We identified 305 known bovine miRNAs. Bta-miR-143, bta-miR-30, bta-miR-122, bta-miR-378, and bta-let-7 were the top five most abundant miRNAs families expressed in liver, representing more than 63% of expressed miRNAs. We also identified 52 homologous miRNAs and 10 novel putative bovine-specific miRNAs, based on precursor sequence and the secondary structure and utilizing the miRBase (v. 21). We compared the miRNAs profile between high and low RFI animals and ranked the most differentially expressed bovine known miRNAs. Bovine miR-143 was the most abundant miRNA in the bovine liver and comprised 20% of total expressed mapped miRNAs. The most highly expressed miRNA in liver of mice and humans, miR-122, was the third most abundant in our cattle liver samples. We also identified 10 putative novel bovine-specific miRNA candidates. Differentially expressed miRNAs between high and low RFI cattle were identified with 18 miRNAs being up-regulated and 7 other miRNAs down-regulated in low RFI cattle. Our study has identified comprehensive miRNAs expressed in bovine liver. Some of the expressed miRNAs are novel in cattle. The differentially expressed miRNAs between high and low RFI give some insights into liver miRNAs regulating physiological pathways underlying variation in this measure of feed efficiency in bovines.

Manipulation of Omega-3 PUFAs in Lamb: Phenotypic and Genotypic Views.

A number of studies have shown that dietary omega-6 and omega-3 long-chain fatty acids can be incorporated into muscle tissue of ruminants despite the biohydrogenation of dietary fatty acids in the rumen. The main focus of this review is on eicosapentaenoic (20:5n-3) and docosahexaenoic (22:6n-3) fatty acids because health authorities around the world consider the sum of these fatty acids as the basis of classifying a food as a source or good source of omega-3 polyunsaturated fatty acids (PUFAs). A high proportion of polyunsaturated fatty acids are hydrogenated in the rumen, leading to a higher concentration of 18:0, but some escapes the rumen to be absorbed intact by the small intestine. Feeding strategies for ruminants have been successfully applied to increase the absorption of PUFAs in the small intestine and therefore to increase the levels of PUFAs in muscle tissue. Protected fats and algae are strong candidates to improve the nutritional value of red meat in ruminants in terms of health-claimable omega-3 fatty acids. Efforts to understand the genetic basis of fatty acid metabolism have been underway. The knowledge of the main genes which control the output of omega-3 fatty acids is still lacking, but gene expression studies have helped to explain the deposition of these acids in muscle, liver, and subcutaneous fat.

Integrated chassis control of active front steering and yaw stability control based on improved inverse nyquist array method.

An integrated chassis control (ICC) system with active front steering (AFS) and yaw stability control (YSC) is introduced in this paper. The proposed ICC algorithm uses the improved Inverse Nyquist Array (INA) method based on a 2-degree-of-freedom (DOF) planar vehicle reference model to decouple the plant dynamics under different frequency bands, and the change of velocity and cornering stiffness were considered to calculate the analytical solution in the precompensator design so that the INA based algorithm runs well and fast on the nonlinear vehicle system. The stability of the system is guaranteed by dynamic compensator together with a proposed PI feedback controller. After the response analysis of the system on frequency domain and time domain, simulations under step steering maneuver were carried out using a 2-DOF vehicle model and a 14-DOF vehicle model by Matlab/Simulink. The results show that the system is decoupled and the vehicle handling and stability performance are significantly improved by the proposed method.

Prevalence of Sarcoptes scabiei infection in pet dogs in southern China.

Little is known about the prevalence of Sarcoptes scabiei infection in pet dogs in China. In the present study, the prevalence of S. scabiei infection in pet dogs in Guangzhou, southern China, was investigated between January and December, 2009. A total of 3,977 pet dogs admitted to animal hospitals were examined for the presence of S. scabiei using a parasitological approach. The average prevalence of S. scabiei infection in pet dogs is 1.18% (95% confidence interval (CI): 0.85-1.52%). The prevalence of S. scabiei was higher in winter (1.42%; 95% CI: 0.29-2.55%), summer (1.39%; 95% CI: 0.83-1.96%), and autumn (1.1%; 95% CI: 0.53-1.68%) than in spring (0.63%; 95% CI: 0.02-1.25%). Furthermore, the prevalence of S. scabiei was the highest in Pekingese (21.88%; 95% CI: 7.55-36.2%), followed by Papillon (5.26%; 95% CI: 0-11.06%) and Bichon Frise (3.19%; 95% CI: 0-6.75%). The results of the present investigation indicate that S. scabiei infection is prevalent in pet dogs in Guangzhou, China, which provides relevant "baseline" data for conducting control strategies and measures against scabies in this region and elsewhere in China. To our knowledge, this is the first comprehensive report of S. scabiei prevalence in pet dogs in China.

A high-throughput multilocus-amplicon sequencing panel to monitor insecticide resistance in fall armyworm (FAW) Spodoptera frugiperda (Lepidoptera: Noctuidae).

BACKGROUND: Fall armyworm (FAW), Spodoptera frugiperda, is a highly polyphagous crop pest that has spread over the world rapidly and invaded Australia in 2020. Globally, FAW has been reported to be resistant to several insecticides permitted in Australia. Timely resistance diagnosis is critical for integrated pest management-based control of FAW in Australia. RESULTS: We developed a multi-amplicon panel by next-generation sequencing (multiamplicon-seq) to identify known insecticide resistance mutations in Australian FAW with high throughput and low cost. The panel included nine known mutations causing insecticide resistance in FAW and four gene mutations causing insecticide resistance in several insect species, not yet reported in FAW. We sequenced 36 plates (96-well) in one MiSeq flow cell with easy sequencing library preparation. We found that Australian FAW carried a very high proportion of the F290V mutation in the acetylcholinesterase (AChE) gene that causes resistance to organophosphate and carbamate insecticides. Furthermore, FAW has a GABA-activated chloride channel mutation, A301Q in the RDL gene. The sequencing-based platform provided evidence of a duplication in the AChE gene. Here several single nucleotide polymorphisms (SNPs) within the 476-bp amplicon of the AChE gene demonstrated 100% heterozygosity across samples and some individuals carried two haplotypes with the F290V mutation. CONCLUSION: Molecular surveillance by multiamplicon-seq will increase capacity for early detection and future resistance monitoring in highly dispersed Australian FAW. It can provide timely resistance information and has the potential to play an important role in the resistance management of FAW. © 2023 Society of Chemical Industry.

A novel mutation in mitochondrial cytochrome b conferring resistance to bifenazate in two-spotted spider mite Tetranychus urticae Koch (Acarina: Tetranychidae).

BACKGROUND: The two-spotted spider mite Tetranychus urticae causes significant damage to ornamental, cotton, sugarcane and horticultural crops in Australia. It has a long history of developing resistance to many acaricides including bifenazate. A mutation in the conserved cd1- and ef-helices of the Qo pocket of cytochrome b is recognized as the primary mechanism of bifenazate resistance. To investigate the resistance mechanisms against bifenazate in Australian two-spotted spider mite, we sequenced the complete mitochondrion genome of five mite strains including a susceptible and bifenazate-resistant strain. RESULTS: We identified a novel mutation D252N in the G126S background at cytochrome b being the cause of bifenazate resistance in a bifenazate-resistant strain, Bram. We validated the role of this mutation combination by reciprocal crosses between a bifenazate resistant and susceptible strain. By doing these crosses we confirmed the pattern of inheritance was maternal. Additionally, mitochondrial heteroplasmy was not observed by single mite genotyping of the mutations in cytb in a known bifenazate-resistant strain Bram. The phylogenetic analysis with the complete mitochondrion genome sequences revealed that Australian two-spotted spider mite strains are closely related to the green form of T. urticae found in China. CONCLUSIONS: The novel mutation D252N found in the cytochrome b in the G126S background was revealed to be the main cause of bifenazate resistance in the Australian T. urticae strain Bram. © 2024 Society of Chemical Industry.

Trends and hotspots in acupuncture treatment of rat models of stroke: a bibliometric analysis from 2004 to 2023.

Background: Acupuncture is a widely used clinical treatment method, and studies have confirmed its therapeutic effects on stroke patients. It can also reduce the burden on patients and society. Acupuncture treatment is a complementary and preventive treatment for stroke. However, there has yet to be a visual bibliometric analysis of the field of acupuncture for stroke rat models. This study explores future trends, research hotspots, and frontiers in acupuncture for stroke rat models over the past 20 years through investigation and visualization. Methods: We collected literature data on acupuncture treatment of stroke in rats from the Web of Science Core Collection (WOSCC) database from January 1, 2004, to December 31, 2023. Import into CiteSpace (version 6.2.R4) and RStudio for analysis by author, country/region, affiliation, annual publication, keywords, and journal visualization. Results: A total of 379 articles were retrieved, including articles from 16 countries, 258 research institutions, and 123 academic journals. The countries and institutions with the most publications were the People's Republic of China (338) and the Fujian University of Traditional Chinese Medicine (43). Tao, Jing had the highest number of co-citations (144). The keywords and co-citation clustering show the main research directions in the field, including "artery occlusion," "neural regeneration," "stimulation," "rapid tolerance," "receptor," "signaling pathway," "apoptosis," "oxidative stress," "inflammatory response," "endogenous neurogenesis," "tolerance of local cerebral ischemic tissues," "proliferation of reactive astrocytes" and "neuroprotective effect." The intervention combines classical acupuncture treatment and modern technology (electricity) with electroacupuncture as a new intervention modality. Conclusion: This study demonstrates the increasing research on acupuncture for treating stroke in rat models. The country/region with the most publications is the People's Republic of China. However, international cooperation still needs to be improved, and future researchers must strengthen international cooperation. In addition, in future studies, researchers should improve the overall quality of research results in this area and enhance research protocols.

Deep learning for colorectal cancer detection in contrast-enhanced CT without bowel preparation: a retrospective, multicentre study.

BACKGROUND: Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. However, colorectal cancers in contrast-enhanced CT without bowel preparation may elude detection by radiologists. We aimed to develop a deep learning (DL) model for accurate detection of colorectal cancer, and evaluate whether it could improve the detection performance of radiologists. METHODS: We developed a DL model using a manually annotated dataset (1196 cancer vs 1034 normal). The DL model was tested using an internal test set (98 vs 115), two external test sets (202 vs 265 in 1, and 252 vs 481 in 2), and a real-world test set (53 vs 1524). We compared the detection performance of the DL model with radiologists, and evaluated its capacity to enhance radiologists' detection performance. FINDINGS: In the four test sets, the DL model had the area under the receiver operating characteristic curves (AUCs) ranging between 0.957 and 0.994. In both the internal test set and external test set 1, the DL model yielded higher accuracy than that of radiologists (97.2% vs 86.0%, p < 0.0001; 94.9% vs 85.3%, p < 0.0001), and significantly improved the accuracy of radiologists (93.4% vs 86.0%, p < 0.0001; 93.6% vs 85.3%, p < 0.0001). In the real-world test set, the DL model delivered sensitivity comparable to that of radiologists who had been informed about clinical indications for most cancer cases (94.3% vs 96.2%, p > 0.99), and it detected 2 cases that had been missed by radiologists. INTERPRETATION: The developed DL model can accurately detect colorectal cancer and improve radiologists' detection performance, showing its potential as an effective computer-aided detection tool. FUNDING: This study was supported by National Science Fund for Distinguished Young Scholars of China (No. 81925023); Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (No. U22A20345); National Natural Science Foundation of China (No. 82072090 and No. 82371954); Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (No. 2022B1212010011); High-level Hospital Construction Project (No. DFJHBF202105).

Multi-treatment Effect Estimation from Biomedical Data.

Several biomedical applications contain multiple treatments from which we want to estimate the causal effect on a given outcome. Most existing Causal Inference methods, however, focus on single treatments. In this work, we propose a neural network that adopts a multi-task learning approach to estimate the effect of multiple treatments. We validated M3E2 in three synthetic benchmark datasets that mimic biomedical datasets. Our analysis showed that our method makes more accurate estimations than existing baselines.

Automatic 3D Teeth Reconstruction from Five Intra-oral Photos Using Parametric Teeth Model.

Orthodontic treatment is a lengthy process that requires regular in-person dental monitoring, making remote dental monitoring a viable alternative when face-to-face consultation is not possible. In this study, we propose an improved 3D teeth reconstruction framework that automatically restores the shape, arrangement, and dental occlusion of upper and lower teeth from five intra-oral photographs to aid orthodontists in visualizing the condition of patients in virtual consultations. The framework comprises a parametric model that leverages statistical shape modeling to describe the shape and arrangement of teeth, a modified U-net that extracts teeth contours from intra-oral images, and an iterative process that alternates between finding point correspondences and optimizing a compound loss function to fit the parametric teeth model to predicted teeth contours. We perform a five-fold cross-validation on a dataset of 95 orthodontic cases and report an average Chamfer distance of 1.0121 mm2 and an average Dice similarity coefficient of 0.7672 on all the test samples in the cross-validation, demonstrating a significant improvement compared with the previous work. Our teeth reconstruction framework provides a feasible solution for visualizing 3D teeth models in remote orthodontic consultations.