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Ceramides, formed by the dehydration of long-chain fatty acids with phytosphingosine and its derivatives, are widely used in skincare, cosmetics, and pharmaceuticals. Due to the exceedingly low concentration of phytosphingosine in plant seeds, relying on the extraction method is highly challenging. Currently, the primary method for obtaining phytosphingosine is the deacetylation of tetraacetyl phytosphingosine (TAPS) derived from fermentation. Wickerhamomyces ciferrii, an unconventional yeast from the pods of Dipteryx odorata, is the only known microorganism capable of naturally secreting TAPS, which is of great industrial value. In recent years, research and applications focused on modifying W. ciferrii for TAPS overproduction have increased rapidly. This review first describes the discovery history, applications, microbial synthesis pathway of TAPS. Research progress in using haploid breeding, mutagenesis breeding, and metabolic engineering to improve TAPS production is then summarized. In addition, the future prospects of TAPS production using the W. ciferrii platform are discussed in light of the current progress, challenges, and trends in this field. Finally, guidelines for future researches are also emphasized.

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Geranylgeraniol (GGOH) is a crucial component in fragrances and essential oils, and a valuable precursor of vitamin E. It is primarily extracted from the oleoresin of Bixa orellana, but is challenged by long plant growth cycles, severe environmental pollution, and low extraction efficiency. Chemically synthesized GGOH typically comprises a mix of isomers, making the separation process both challenging and costly. Advancements in synthetic biology have enabled the construction of microbial cell factories for GGOH production. In this study, Yarrowia lipolytica was engineered to efficiently synthesize GGOH by expressing heterologous phosphatase genes, enhancing precursor supplies of farnesyl diphosphate, geranylgeranyl pyrophosphate, and acetyl-CoA, and downregulating the squalene synthesis pathway by promoter engineering. Additionally, optimizing fermentation conditions and reducing reactive oxygen species significantly increased the GGOH titer to 3346.47 mg/L in a shake flask. To the best of our knowledge, this is the highest reported GGOH titer in shaking flasks to date, setting a new benchmark for terpenoid production.

Assuntos

Diterpenos , Engenharia Metabólica , Yarrowia , Yarrowia/genética , Yarrowia/metabolismo , Diterpenos/metabolismo , Diterpenos/química , Diterpenos/síntese química , Fosfatos de Poli-Isoprenil/metabolismo , Fermentação , Proteínas Fúngicas/genética , Proteínas Fúngicas/metabolismo , Sesquiterpenos

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Degenerative scoliosis (DS), encompassing conditions like spondylolisthesis and spinal stenosis, is a common type of spinal deformity. Lumbar interbody fusion (LIF) stands as a conventional surgical intervention for this ailment, aiming at decompression, restoration of intervertebral height, and stabilization of motion segments. Despite its widespread use, the precise mechanism underlying spinal fusion remains elusive. In this review, our focus lies on endochondral ossification for spinal fusion, a process involving vertebral development and bone healing. Endochondral ossification is the key step for the successful vertebral fusion. Endochondral ossification can persist in hypoxic conditions and promote the parallel development of angiogenesis and osteogenesis, which corresponds to the fusion process of new bone formation in the hypoxic region between the vertebrae. The ideal material for interbody fusion cages should have the following characteristics: (1) Good biocompatibility; (2) Stable chemical properties; (3) Biomechanical properties similar to bone tissue; (4) Promotion of bone fusion; (5) Favorable for imaging observation; (6) Biodegradability. Utilizing cartilage-derived bone-like constructs holds promise in promoting bony fusion post-operation, thus warranting exploration in the context of spinal fusion procedures.

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Southern root-knot nematodes are among the most pernicious phytoparasites; they are responsible for substantial yield losses in agricultural crops worldwide. The limited availability of nematicides for the prevention and control of plant-parasitic nematodes necessitates the urgent development of novel nematicides. Natural products have always been a key source for the discovery of pesticides. Waltherione A, an alkaloid, exhibits potent nematocidal activity. In this study, we designed and synthesized a series of quinoline and quinolone derivatives from Waltherione A, leveraging a strategy of structural simplification. Bioassays have revealed that the quinoline derivatives exhibit better activity than quinolone derivatives in terms of both nematocidal and fungicidal activities. Notably, compound D1 demonstrated strong nematocidal activity, with a 72 h LC50 of 23.06 µg/mL, and it effectively controlled the infection of root-knot nematodes on cucumbers. The structure-activity relationship suggests that the quinoline moiety is essential for the nematocidal efficacy of Waltherione A. Additionally, compound D1 exhibited broad-spectrum fungicidal activity, with an EC50 of 2.98 µg/mL against Botrytis cinerea. At a concentration of 200 µg/mL, it significantly inhibited the occurrence of B. cinerea on tomato fruits, with an inhibitory effect of 96.65%, which is slightly better than the positive control (90.30%).

Assuntos

Antinematódeos , Antinematódeos/farmacologia , Antinematódeos/síntese química , Antinematódeos/química , Relação Estrutura-Atividade , Animais , Desenho de Fármacos , Doenças das Plantas/parasitologia , Doenças das Plantas/microbiologia , Doenças das Plantas/prevenção & controle , Cucumis sativus/parasitologia , Cucumis sativus/microbiologia , Fungicidas Industriais/farmacologia , Fungicidas Industriais/síntese química , Fungicidas Industriais/química , Quinolinas/química , Quinolinas/farmacologia , Quinolinas/síntese química , Nematoides/efeitos dos fármacos , Tylenchoidea/efeitos dos fármacos , Botrytis/efeitos dos fármacos , Quinolonas/farmacologia , Quinolonas/química , Quinolonas/síntese química , Estrutura Molecular

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Softening and subsequent deformation are significant challenges in additive manufacturing of thermal-curable thermosets. This study proposes an approach to address these issues, involving the preparation of thermosetting composite powders with distinct curing temperatures, the utilization of cold spray additive manufacturing (CSAM) for sample fabrication, and the implementation of stepwise curing for each component. To validate the feasibility of this approach, two single-component thermosetting powders P1 and P2 and their composite powder C were subjected to CSAM and stepwise curing. From the sample morphology observation and deposition/curing mechanism investigation based on thermomechanical analysis and differential scanning calorimetry, it is found that severe plastic deformation occurs during the CSAM process, accompanied by heat generation, leading to local melting to promote a good bond at the contact surface of the particles and form small pores. During the progressive curing, the samples printed using C demonstrate superior deformation resistance compared with those using P1 and P2, and the curing time is reduced from 16.7 h to 1.5 h, due to the sequential curing reactions of P1 and P2 components in composite C, allowing the uncured P2 and cured P1 to alternately remain solid for providing structural support and minimizing deformation.

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BACKGROUND: Endoscopic instrument segmentation is essential for ensuring the safety of robotic-assisted spinal endoscopic surgeries. However, due to the narrow operative region, intricate surrounding tissues, and limited visibility, achieving instrument segmentation within the endoscopic view remains challenging. PURPOSE: This work aims to devise a method to segment surgical instruments in endoscopic video. By designing an endoscopic image classification model, features of frames before and after the video are extracted to achieve continuous and precise segmentation of instruments in endoscopic videos. METHODS: Deep learning techniques serve as the algorithmic core for constructing the convolutional neural network proposed in this study. The method comprises dual stages: image classification and instrument segmentation. MobileViT is employed for image classification, enabling the extraction of key features of different instruments and generating classification results. DeepLabv3+ is utilized for instrument segmentation. By training on distinct instruments separately, corresponding model parameters are obtained. Lastly, a flag caching mechanism along with a blur detection module is designed to effectively utilize the image features in consecutive frames. By incorporating specific parameters into the segmentation model, better segmentation of surgical instruments can be achieved in endoscopic videos. RESULTS: The classification and segmentation models are evaluated on an endoscopic image dataset. In the dataset used for instrument segmentation, the training set consists of 7456 images, the validation set consists of 829 images, and the test set consists of 921 images. In the dataset used for image classification, the training set consists of 2400 images and the validation set consists of 600 images. The image classification model achieves an accuracy of 70% on the validation set. For the segmentation model, experiments are conducted on two common surgical instruments, and the mean Intersection over Union (mIoU) exceeds 98%. Furthermore, the proposed video segmentation method is tested using videos collected during surgeries, validating the effectiveness of the flag caching mechanism and blur detection module. CONCLUSIONS: Experimental results on the dataset demonstrate that the dual-stage video processing method excels in performing instrument segmentation tasks under endoscopic conditions. This advancement is significant for enhancing the intelligence level of robotic-assisted spinal endoscopic surgeries.

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Background: The incidence rate of thyroid nodules has reached 65%, but only 5-15% of these modules are malignant. Therefore, accurately determining the benign and malignant nature of thyroid nodules can prevent unnecessary treatment. We aimed to develop a deep-learning (DL) radiomics model based on ultrasound (US), explore its diagnostic efficacy for benign and malignant thyroid nodules, and verify whether it improved the diagnostic level of physicians. Methods: We retrospectively included 1,076 thyroid nodules from 817 patients at three institutions. The radiomics and DL features of the US images were extracted and used to construct radiomics signature (Rad_sig) and deep-learning signature (DL_sig). A Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used for feature selection. Clinical US semantic signature (C_US_sig) was constructed based on clinical information and US semantic features. Next, a combined model was constructed based on the above three signatures in the form of a nomogram. The model was constructed using a development set (institution 1: 719 nodules), and the model was evaluated using two external validation sets (institution 2: 74 nodules, and institution 3: 283 nodules). The performance of the model was assessed using decision curve analysis (DCA) and calibration curves. Furthermore, the C_US_sigs of junior physicians, senior physicians, and expers were constructed. The DL radiomics model was used to assist the physicians with different levels of experience in the interpretation of thyroid nodules. Results: In the development and validation sets, the combined model showed the highest performance, with areas under the curve (AUCs) of 0.947, 0.917, and 0.929, respectively. The DCA results showed that the comprehensive nomogram had the best clinical utility. The calibration curves indicated good calibration for all models. The AUCs for distinguishing between benign and malignant thyroid nodules by junior physicians, senior physicians, and experts were 0.714-0.752, 0.740-0.824, and 0.891-0.908, respectively; however, with the assistance of DL radiomics, the AUCs reached 0.858-0.923, 0.888-0.944, and 0.912-0.919, respectively. Conclusions: The nomogram based on DL radiomics had high diagnostic efficacy for thyroid nodules, and DL radiomics could assist physicians with different levels of experience to improve their diagnostic level.

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Endoscopy holds a pivotal role in the early detection and treatment of diverse diseases, with artificial intelligence (AI)-assisted methods increasingly gaining prominence in disease screening. Among them, the depth estimation from endoscopic sequences is crucial for a spectrum of AI-assisted surgical techniques. However, the development of endoscopic depth estimation algorithms presents a formidable challenge due to the unique environmental intricacies and constraints within the dataset. This paper proposes a self-supervised depth estimation network to comprehensively explore the brightness changes in endoscopic images, and fuse different features at multiple levels to achieve an accurate prediction of endoscopic depth. First, a FlowNet is designed to evaluate the brightness changes of adjacent frames by calculating the multi-scale structural similarity. Second, a feature fusion module is presented to capture multi-scale contextual information. Experiments show that the average accuracy of the algorithm is 97.03% in the Stereo Correspondence and Reconstruction of Endoscopic Data (SCARED dataset). Based on the training parameters of the SCARED dataset, the algorithm achieves superior performance on the other two datasets (EndoSLAM and KVASIR dataset), indicating that the algorithm has good generalization performance.

RESUMO

Background: The aim of this study is to develop a predictive model utilizing deep learning and machine learning techniques that will inform clinical decision-making by predicting the 1-year postoperative recovery of patients with lumbar disk herniation. Methods: The clinical data of 470 inpatients who underwent tubular microdiscectomy (TMD) between January 2018 and January 2021 were retrospectively analyzed as variables. The dataset was randomly divided into a training set (n = 329) and a test set (n = 141) using a 10-fold cross-validation technique. Various deep learning and machine learning algorithms including Random Forests, Extreme Gradient Boosting, Support Vector Machines, Extra Trees, K-Nearest Neighbors, Logistic Regression, Light Gradient Boosting Machine, and MLP (Artificial Neural Networks) were employed to develop predictive models for the recovery of patients with lumbar disk herniation 1 year after surgery. The cure rate score of lumbar JOA score 1 year after TMD was used as an outcome indicator. The primary evaluation metric was the area under the receiver operating characteristic curve (AUC), with additional measures including decision curve analysis (DCA), accuracy, sensitivity, specificity, and others. Results: The heat map of the correlation matrix revealed low inter-feature correlation. The predictive model employing both machine learning and deep learning algorithms was constructed using 15 variables after feature engineering. Among the eight algorithms utilized, the MLP algorithm demonstrated the best performance. Conclusion: Our study findings demonstrate that the MLP algorithm provides superior predictive performance for the recovery of patients with lumbar disk herniation 1 year after surgery.

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Arsenic (As)-bearing Fe(III) precipitate groundwater treatment sludge has traditionally been viewed by the water sector as a disposal issue rather than a resource opportunity, partly due to assumptions of the low value of As. However, As has now been classified as a Critical Raw Material (CRM) in many regions, providing new incentives to recover As and other useful components of the sludge, such as phosphate (P) and the reactive hydrous ferric oxide (HFO) sorbent. Here, we investigate alkali extraction to separate As from a variety of field and synthetic As-bearing HFO sludges, which is a critical first step to enable sludge upcycling. We found that As extraction was most effective using NaOH, with the As extraction efficiency increasing up to >99% with increasing NaOH concentrations (0.01, 0.1, and 1 M). Extraction with Na2CO3 and Ca(OH)2 was ineffective (<5%). Extraction time (hour, day, week) played a secondary role in As release but tended to be important at lower NaOH concentrations. Little difference in As extraction efficiency was observed for several key variables, including sludge aging time (50 days) and cosorbed oxyanions (e.g., Si, P). However, the presence of ∼10 mass% calcite decreased As release from field and synthetic sludges considerably (<70% As extracted). Concomitant with As release, alkali extraction promoted crystallization of poorly ordered HFO and decreased particle specific surface area, with structural modifications increasing with NaOH concentration and extraction time. Taken together, these results provide essential information to inform and optimize the design of resource recovery methods for As-bearing treatment sludge.

Assuntos

Álcalis , Arsênio , Água Subterrânea , Esgotos , Esgotos/química , Água Subterrânea/química , Álcalis/química , Poluentes Químicos da Água/química , Purificação da Água/métodos , Compostos Férricos/química

RESUMO

Traditional metal-plastic dissimilar welding methods directly heat the metal workpiece, which may cause potential thermal damage to the metal workpiece. Ultrasonic extruded weld-riveting (UEWR) is a relatively new method for dissimilar joining of carbon fiber-reinforced thermoplastic (CFRTP) and metal. In this method, the CFRTP workpiece is melted using the ultrasonic effect and is squeezed into prefabricated holes in the metal workpiece to form a rivet structure. In this method, the metal workpiece is not directly heated, and potential high-temperature losses can be avoided. This paper investigates the process characterizations of UERW of AZ31B magnesium alloy to carbon fiber-reinforced PA66. The process parameters are optimized by the Taguchi method. The joint formation process is analyzed based on the fiber distribution in the cross-sections of joints. The effects of welding parameters on the joint microstructure and fracture surface morphology are discussed. The results show that a stepped amplitude strategy (40 µm amplitude in the first stage and 56 µm amplitude in the second stage) could balance the joint strength and joint appearance. Insufficient (welding energy < 2600 J or amplitude-A < 50%) or excessive (welding energy > 2800 J or amplitude-A > 50%) welding parameters lead to the formation of porous defects. Three fracture modes are identified according to the fracture surface analysis. The maximum tensile shear strength of joints at the optimal parameters is about 56.5 ± 6.2 MPa.

RESUMO

Hepatitis B virus (HBV) can be completely suppressed after antiviral treatment; however, some patients with chronic hepatitis B (CHB) exhibit elevated alanine aminotransferase (ALT) levels and sustained disease progression. This study provides novel insights into the mechanism and potential predictive biomarkers of persistently elevated ALT (PeALT) in patients with CHB after complete viral inhibition. Patients having CHB with undetectable HBV DNA at least 12 months after antiviral treatment were enrolled from a prospective, observational cohort. Patients with PeALT and persistently normal ALT (PnALT) were matched 1:1 using propensity score matching. Correlations between plasma metabolites and the risk of elevated ALT were examined using multivariate logistic regression. A mouse model of carbon tetrachloride-induced liver injury was established to validate the effect of key differential metabolites on liver injury. Of the 1238 patients with CHB who achieved complete viral suppression, 40 (3.23%) had PeALT levels during follow-up (median follow-up: 2.42 years). Additionally, 40 patients with PnALT levels were matched as controls. Ser-Phe-Ala, Lys-Ala-Leu-Glu, 3-methylhippuric acid, 3-methylxanthine, and 7-methylxanthine were identified as critical differential metabolites between the two groups and independently associated with PeALT risk. Ser-Phe-Ala and Lys-Ala-Leu-Glu levels could be used to discriminate patients with PeALT from those with PnALT. Furthermore, N-acetyl- l-methionine (NALM) demonstrated the strongest negative correlation with ALT levels. NALM supplementation alleviated liver injury and hepatic necrosis induced by carbon tetrachloride in mice. Changes in circulating metabolites may contribute to PeALT levels in patients with CHB who have achieved complete viral suppression after antiviral treatment.

Assuntos

Alanina Transaminase , Antivirais , Biomarcadores , Hepatite B Crônica , Humanos , Hepatite B Crônica/tratamento farmacológico , Hepatite B Crônica/sangue , Hepatite B Crônica/virologia , Masculino , Feminino , Alanina Transaminase/sangue , Antivirais/uso terapêutico , Adulto , Estudos Prospectivos , Pessoa de Meia-Idade , Biomarcadores/sangue , Animais , Camundongos , Vírus da Hepatite B , Resposta Viral Sustentada , DNA Viral/sangue , Modelos Animais de Doenças , Fígado/patologia , Fígado/virologia , Carga Viral

RESUMO

Effective crosslinking among food constituents has the potential to enhance their overall quality. Distarch phosphate (DSP), a common food additive employed as a thickening agent, bears a pre-crosslinked oligosaccharide (PCO) moiety within its molecular structure. Once this moiety is released, its double reducing end has the potential to undergo crosslinking with amino-rich macromolecules through Maillard reaction. In this study, hydrolyzed distarch phosphate (HDSP) was synthesized, and spectroscopic analysis verified the presence of PCO within HDSP. Preliminary validation experiment showed that HDSP could crosslink chitosan to form a hydrogel and significant browning was also observed during the process. Furthermore, rehydrated sea cucumber (RSC) crosslinked with HDSP exhibited a more intact appearance, higher mechanical strength, better color profile, and increased water-holding capacity. This series of results have confirmed that HDSP is capable to crosslink amino-rich macromolecules and form more stable three-dimensional network.

Assuntos

Fosfatos , Pepinos-do-Mar , Animais , Pepinos-do-Mar/química , Hidrólise , Fosfatos/química , Aditivos Alimentares/química , Reagentes de Ligações Cruzadas/química , Reação de Maillard , Oligossacarídeos/química

RESUMO

Perovskite solar cells (PSCs) have shown great potential for reducing costs and improving power conversion efficiency (PCE). One effective method to achieve the latter is to use an all-inorganic charge transport layer (ICTL). However, traditional methods for crystallizing inorganic layers often result in the formation of a powder instead of a continuous film. To address this issue, we designed a dual-layer inorganic electron transport layer (IETL). This dual-layer structure consists of a layer of SnO2 nanocrystals (SnO2 NCs) deposited via a solution process and a dense SnO2 layer deposited through atomic layer deposition (ALD SnO2) to fill the cracks and gaps between the SnO2 NCs. PSCs having these dual-layer SnO2 ETLs achieved a high efficiency of 23.0%. This efficiency surpasses the recorded performance of ICTLs deposited on the perovskite. Furthermore, the PCE is comparable to that achieved with a C60 ETL. Moreover, the high-density structure of the ALD SnO2 layer inhibits the vertical migration of ions, resulting in improved thermal stability. After continuous heating at 85 °C in 10% humidity for 1000 h, the PCE of the dual-layer SnO2 structure decreased by 18%, whereas that of the C60/BCP structure decreased by 36%. The integration of dual-layer SnO2 into PSCs represents a significant advancement in achieving high-performance, commercially viable inverted monolithic PSCs or tandem solar cells.

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Background: Neck pain has become very common in China and has greatly affected individuals, families, and society in general. In this study, we aimed to report on the rates and trends of the prevalence, incidence, and years lived with disability (YLDs) caused by neck pain in the general population of China from 1990 to 2019. Methods: We used data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) study to estimate the number and age standardised rates per 100 000 population of neck pain point prevalence, annual incidence, and YLDs in 33 provinces/municipalities/autonomous regions of China, stratified by age, sex, and sociodemographic index (SDI) from 1990 to 2019. We then compared these estimates with other G20 countries. Results: There were 6.80 × 107 patients with neck pain in 2019, presenting an increase from 3.79 × 107 in 1990. Likewise, the national age-standardised point prevalence increased slightly from 3.53% in 1990 to 3.57% in 2019. The YLDs increased by 78.08%, from 3814 × 103 in 1990 to 6792 × 103 in 2019. The age-standardised YLDs rate increased 1.50% from 352.84 in 1990 to 358.10 in 2019. The point prevalence of neck pain in 2019 was higher in females compared with males. These estimates were all above the global average level and increased more rapidly among G20 countries from 1990 to 2019. We generally observed a positive association between age-standardised YLD rates for neck pain and SDI, suggesting the burden is higher at higher sociodemographic indices. Conclusions: Neck pain is a serious public health problem in the general population in China, especially in its central and western regions, with an overall increasing trend in the last three decades. This is possibly related to changes of people's lifestyles and work patterns due to improvements in societal well-being and technology. Raising awareness of risk factors for neck pain in the general population and establishing effective preventive and treatment strategies could help reduce the future burden of neck disorders.

Assuntos

Pessoas com Deficiência , Carga Global da Doença , Masculino , Feminino , Humanos , Cervicalgia/epidemiologia , Prevalência , Incidência , China/epidemiologia , Saúde Global

RESUMO

The employment of dinuclear Au(I) catalysts in photomediated modern organic transformations has attracted significant attention over the past decade, which commonly demonstrates unique catalytic performance compared with the corresponding mononuclear gold complexes. Nevertheless, detailed mechanisms of dinuclear gold catalysis remain ambiguous, and further mechanistic understanding is highly desirable. Herein, computational studies were carried out to gain mechanistic insights into the photoinduced dinuclear gold-catalyzed divergent dechloroalkylation of gem-dichloroalkanes. Computational results suggest that a proton transfer from the additive, Hantzsch ester (HE), to the base, guanidine, could lead to an ionic pair complex, which is ready to undergo excitation under blue light irradiation to result in the corresponding triplet excited state. Then, the excited complex might undergo oxidative quenching with the dinuclear gold photocatalyst [AuI-AuI]2+, via a single-electron-transfer (SET) step to afford an unusual [Au1/2-Au1/2]+ dinuclear species. The corresponding mononuclear gold catalyst, [AuI]+, however, is not ready to enable the analogous step to give a [Au0] species, which might account for the unique characteristics of dinuclear gold catalysis. Subsequently, the formed [Au1/2-Au1/2]+ intermediate could trigger a Cl-atom transfer from dichloromethane in an inner-sphere manner to furnish a critical chloromethyl radical. Next, the resulting chloromethyl radical could attack the alkenyl moiety of substrates to generate the corresponding alkyl radicals. Then, three possible mechanistic pathways were explored to rationalize the substrate-dependent divergent transformations in this protocol. The main factors responsible for the diversified transformations were discussed.

RESUMO

Extended reality (XR) technology refers to any situation where real-world objects are enhanced with computer technology, including virtual reality, augmented reality, and mixed reality. Augmented reality and mixed reality technologies have been widely applied in orthopedic clinical practice, including in teaching, preoperative planning, intraoperative navigation, and surgical outcome evaluation. The primary goal of this narrative review is to summarize the effectiveness and superiority of XR-technology-assisted intraoperative navigation in the fields of trauma, joint, spine, and bone tumor surgery, as well as to discuss the current shortcomings in intraoperative navigation applications. We reviewed titles of more than 200 studies obtained from PubMed with the following search terms: extended reality, mixed reality, augmented reality, virtual reality, intraoperative navigation, and orthopedic surgery; of those 200 studies, 69 related papers were selected for abstract review. Finally, the full text of 55 studies was analyzed and reviewed. They were classified into four groups-trauma, joint, spine, and bone tumor surgery-according to their content. Most of studies that we reviewed showed that XR-technology-assisted intraoperative navigation can effectively improve the accuracy of implant placement, such as that of screws and prostheses, reduce postoperative complications caused by inaccurate implantation, facilitate the achievement of tumor-free surgical margins, shorten the surgical duration, reduce radiation exposure for patients and surgeons, minimize further damage caused by the need for visual exposure during surgery, and provide richer and more efficient intraoperative communication, thereby facilitating academic exchange, medical assistance, and the implementation of remote healthcare.

RESUMO

Surface electromyogram (sEMG)-based gesture recognition has emerged as a promising avenue for developing intelligent prostheses for upper limb amputees. However, the temporal variations in sEMG have rendered recognition models less efficient than anticipated. By using cross-session calibration and increasing the amount of training data, it is possible to reduce these variations. The impact of varying the amount of calibration and training data on gesture recognition performance for amputees is still unknown. To assess these effects, we present four datasets for the evaluation of calibration data and examine the impact of the amount of training data on benchmark performance. Two amputees who had undergone amputations years prior were recruited, and seven sessions of data were collected for analysis from each of them. Ninapro DB6, a publicly available database containing data from ten healthy subjects across ten sessions, was also included in this study. The experimental results show that the calibration data improved the average accuracy by 3.03%, 6.16%, and 9.73% for the two subjects and Ninapro DB6, respectively, compared to the baseline results. Moreover, it was discovered that increasing the number of training sessions was more effective in improving accuracy than increasing the number of trials. Three potential strategies are proposed in light of these findings to enhance cross-session models further. We consider these findings to be of the utmost importance for the commercialization of intelligent prostheses, as they demonstrate the criticality of gathering calibration and cross-session training data, while also offering effective strategies to maximize the utilization of the entire dataset.

Assuntos

Amputados , Membros Artificiais , Humanos , Eletromiografia/métodos , Calibragem , Reconhecimento Automatizado de Padrão/métodos , Extremidade Superior , Algoritmos

RESUMO

The interactions between microbes and plants are governed by complex chemical signals, which can forcefully affect plant growth and development. Here, to understand how microbes influence Houttuynia cordata Thunb. plant growth and its secondary metabolite through chemical signals, we established the interaction between single bacteria and a plant. We inoculated H. cordata seedlings with bacteria isolated from their roots. The results showed that the total fresh weight, the total dry weight, and the number of lateral roots per seedling in the P. fluorescens-inoculated seedlings were 174%, 172% and 227% higher than in the control seedlings. Pseudomonas fluorescens had a significant promotional effect of the volatile contents compared to control, with ß-myrcene increasing by 192%, 2-undecanone by 203%, decanol by 304%, ß-caryophyllene by 197%, α-pinene by 281%, bornyl acetate by 157%, γ-terpinene by 239% and 3-tetradecane by 328% in P. fluorescens-inoculated H. cordata seedlings. the contents of chlorogenic acid, rutin, quercitin, and afzelin were 284%, 154%, 137%, and 213% higher than in control seedlings, respectively. Our study provided basic data to assess the linkages between endophytic bacteria, plant phenotype and metabolites of H. cordata to provide an insight into P. fluorescens use as biological fertilizer, promoting the synthesis of medicinal plant compounds.

Assuntos

Medicamentos de Ervas Chinesas , Houttuynia , Plantas Medicinais , Pseudomonas fluorescens , Houttuynia/química , Extratos Vegetais , Plantas Medicinais/química , Medicamentos de Ervas Chinesas/química

RESUMO

Punicic acid is a conjugated linolenic acid with various biological activities including antiobesity, antioxidant, anticancer, and anti-inflammatory effects. It is often used as a nutraceutical, dietary additive, and animal feed. Currently, punicic acid is primarily extracted from pomegranate seed oil, but it is restricted due to the extended growth cycle, climatic limitations, and low recovery level. There have also been reports on the chemical synthesis of punicic acid, but it resulted in a mixture of structurally similar isomers, requiring additional purification/separation steps. In this study, a comprehensive strategy for the production of punicic acid in Yarrowia lipolytica was implemented by pushing the supply of linoleic acid precursors in a high-oleic oil strain, expressing multiple copies of the fatty acid conjugase gene from Punica granatum, engineering the acyl-editing pathway to improve the phosphatidylcholine pool, and promoting the assembly of punicic acid in the form of triglycerides. The optimal strain with high oil production capacity and a significantly increased punicic acid ratio accumulated 3072.72 mg/L punicic acid, accounting for 6.19% of total fatty acids in fed-batch fermentation, providing a viable, sustainable, and green approach for punicic acid production to substitute plant extraction and chemical synthesis production.

Assuntos

Lythraceae , Punica granatum , Yarrowia , Animais , Yarrowia/genética , Yarrowia/metabolismo , Óleos de Plantas/metabolismo , Lythraceae/genética , Lythraceae/metabolismo , Ácidos Graxos/metabolismo , Ácidos Linolênicos , Engenharia Metabólica