Neurogenesis dynamics in the olfactory bulb:deciphering circuitry organization, function, and adaptive plasticity

Adult neurogenesis persists after birth in the subventricular zone, with new neurons migrating to the granule cell layer and glomerular layers of the olfactory bulb, where they integrate into existing circuitry as inhibitory interneurons. The generation of these new neurons in the olfactory bulb supports both structural and functional plasticity, aiding in circuit remodeling triggered by memory and learning processes. However, the presence of these neurons, coupled with the cellular diversity within the olfactory bulb, presents an ongoing challenge in understanding its network organization and function. Moreover,the continuous integration of new neurons in the olfactory bulb plays a pivotal role in regulating olfactory information processing. This adaptive process responds to changes in epithelial composition and contributes to the formation of olfactory memories by modulating cellular connectivity within the olfactory bulb and interacting intricately with higher-order brain regions. The role of adult neurogenesis in olfactory bulb functions remains a topic of debate. Nevertheless, the functionality of the olfactory bulb is intricately linked to the organization of granule cells around mitral and tufted cells. This organizational pattern significantly impacts output, network behavior, and synaptic plasticity, which are crucial for olfactory perception and memory. Additionally, this organization is further shaped by axon terminals originating from cortical and subcortical regions. Despite the crucial role of olfactory bulb in brain functions and behaviors related to olfaction, these complex and highly interconnected processes have not been comprehensively studied as a whole. Therefore, this manuscript aims to discuss our current understanding and explore how neural plasticity and olfactory neurogenesis contribute to enhancing the adaptability of the olfactory system. These mechanisms are thought to support olfactory learning and memory, potentially through increased complexity and restructuring of neural network structures, as well as the addition of new granule granule cells that aid in olfactory adaptation. Additionally, the manuscript underscores the importance of employing precise methodologies to elucidate the specific roles of adult neurogenesis amidst conflicting data and varying experimental paradigms. Understanding these processes is essential for gaining insights into the complexities of olfactory function and behavior.

“Adapted Physical Activity”理念在普通高校特殊群体学生体育教育中的阐释

通过对adapted physical activity(APA)理念的本质、概念,实施的条件,发展背景,在特殊群体学生体育教育中的体现及实现,特殊群体学生体育教师的培养体系等方面进行解释和分析,逐步了解和认识到adapted physical activity(APA)理念在特殊群体学生体育教育中作用和价值,以及实现的途径和方法。

Heterosis in locally adapted sorghum genotypes and potential of hybrids for increased productivity in contrasting environments in Ethiopia

Increased productivity in sorghum has been achieved in the developed world using hybrids.Despite their yield advantage,introduced hybrids have not been adopted in Ethiopia due to the lack of adaptive traits,their short plant stature and small grain size.This study was conducted to investigate hybrid performance and the magnitude of heterosis of locally adapted genotypes in addition to introduced hybrids in three contrasting environments in Ethiopia.In total,139 hybrids,derived from introduced seed parents crossed with locally adapted genotypes and introduced R lines,were evaluated.Overall,the hybrids matured earlier than the adapted parents,but had higher grain yield,plant height,grain number and grain weight in all environments.The lowland adapted hybrids displayed a mean better parent heterosis(BPH) of19%,equating to 1160 kg ha-1and a 29% mean increase in grain yield,in addition to increased plant height and grain weight,in comparison to the hybrids derived from the introduced R lines.The mean BPH for grain yield for the highland adapted hybrids was 16% in the highland and 52%in the intermediate environment equating to 698 kg ha-1and 2031 kg ha-1,respectively,in addition to increased grain weight.The magnitude of heterosis observed for each hybrid group was related to the genetic distance between the parental lines.The majority of hybrids also showed superiority over the standard check varieties.In general,hybrids from locally adapted genotypes were superior in grain yield,plant height and grain weight compared to the high parents and introduced hybrids indicating the potential for hybrids to increase productivity while addressing farmers' required traits.

Realization of Orthogonal Wavelets Adapted to Fabric Texture for Defect Detection

The wavelet adapted to the fabric texture can be developed from the orthogonal and normal series which are selected randomly by means of Monte Carlo method and op timized by adding certain constraint conditions.Then the fabric image can be decomposed into the subimages by the adaptive wavelet transform and the horizontal and vertical texture information will be perfectly contained in the subimages. Therefore this method can be effectively used for the automatic inspection of the fabric defects.

A Finite Difference Scheme on a Priori Adapted Meshes for a Singularly Perturbed Parabolic Convection-Diffusion Equation

A boundary value problem is considered for a singularly perturbed parabolic convection-diffusion equation; we construct a finite difference scheme on α priori （sequentially） adapted meshes and study its convergence. The scheme on α priori adapted meshes is constructed using a majorant function for the singular component of the discrete solution, which allows us to find α priori a subdomain where the computed solution requires a further improvement. This subdomain is defined by the perturbation parameter ε, the step-size of a uniform mesh in χ, and also by the required accuracy of the discrete solution and the prescribed number of refinement iterations K for improving the solution. To solve the discrete problems aimed at the improvement of the solution, we use uniform meshes on the subdomains. The error of the numerical solution depends weakly on the parameter ε. The scheme converges almost ε-uniformly, precisely, under the condition N^-1 = o （ε^v）, where N denotes the number of nodes in the spatial mesh, and the value v = v（K） can be chosen arbitrarily small for suitable K.

Stealth Adapted Viruses: A Bridge between Molecular Virology and Clinical Psychiatry

Cytopathic “stealth-adapted” viruses bypass the cellular immune defense mechanisms because of molecular deletion or mutation of critical antigen coding genes. They, therefore, do not provoke the inflammatory reaction typical of infections with the conventional viruses from which stealth adapted viruses are derived. Stealth adapted viruses establish persistent, systemic virus infections, which commonly involve the brain. The brain damage can cause major mood and cognitive disorders, fatigue, seizures and various manifestations of an impaired autonomic nervous system. Symptoms can also result from: 1) induced autoimmunity, 2) antibody formation against virus antigens, 3) virus-induced cellular damage to non-brain tissues and 4) induced heightened overall immune reactivity, such that normally unrecognized components of the virus begin to become targeted by the cellular immune system. This last mechanism is relevant to the reported neurological and psychiatric adverse effects of vaccination in certain individuals. It is also appropriate to consider the infectious component of stealth adapted virus infections since family members and others may be at risk for becoming infected.

Rewriting and the Original Work——An analysis of the adapted version of Outlaws of the Marsh

Outlaws of the Marsh is familiar to both Chinese and Westerners. Through the long history it can still gain a remarkable statusin literature. This paper aims to analysis the adapted version of its translation and try to give some inspiration on translation practice.

Significantly improved oxidation of bio-based furans into furan carboxylic acids using substrate-adapted whole cells

Furan carboxylic acids are important building blocks in polymer and fine chemical industries. In this work, a simple substrate adaptation strategy was applied to improve the catalytic performances of Comamonas testosteroni SC1588 cells for the synthesis of various furan carboxylic acids. It was found that biocatalytic synthesis of 5-hydroxymethyl-2-furancarboxylic acid(HMFCA) was substantially promoted by adding histidine and increasing cell concentrations. HMFCA was produced in a quantitative yield from200 m M HMF in 24 h. Besides, the HMFCA yields of 71%–81% were achieved with the substrate concentrations up to 250–300 m M. It was firstly found that 4-tert-butylcatechol(TBC), as the stabilizer present in HMF, exerted a significantly detrimental effect on whole-cell catalytic synthesis of HMFCA at high substrate concentrations(more than 130 m M). In addition, a variety of furan carboxylic acids such as2-furoic acid, 5-methyl-2-furancarboxylic acid and 5-methoxymethyl-2-furancarboxylic acid were synthesized with the yields up to 98%.

A study on liver mitochondria respiration and protein synthesis in cold adapted rats

Mitochondria were isolated from normal and cold adapted rat livers.The respiratory func-tion of mitochondria in rat livers,including ADP:O ratio(P/O)and the respiratory control ratio(RCR),was determined by oxygen electrode method,The protein synthesis in mitochondria wasstudied by observing the incorporation of[~3H]-Leucine into mitochondria.Polyacrylamide gelelectrophoresis was carried out to detect the changes of the inner membrane proteins.It was shownthat the P/O and RCR decreased in cold adapted rats in the 2nd and 4th weeks and returned tothe control level in the 6th week,the protein synthesis of mitochondria decreased significantly incold adapted rats in 1,2 and 4 weeks;the electrophoretic pattern of the inner membrane proteinsin mitochondria from cold adapted rat livers revealed some new bands.

Breathing adapted radiation therapy for leukemia relapse in the breast: A case report

BACKGROUND Infiltration of the breast by leukemic cells is uncommon but may manifest as an oncological emergency requiring prompt management.Extramedullary relapse of T-cell acute lymphoblastic leukemia(T-ALL)within the breast is exceedingly rare and there is paucity of data in the literature regarding this entity.No consensus exists on management of isolated extramedullary breast relapses of T-ALL.Herein,we report a case of isolated extramedullary breast relapse of T-ALL treated with breathing adapted radiation therapy(BART)using the active breathing control(ABC)system.CASE SUMMARY The patient was a 33-year-old female with diagnosis of T-ALL.She received intensive systemic chemotherapy that resulted in complete remission of her disease,and then underwent allogeneic hematopoietic stem cell transplantation.After a 15 mo period without symptoms and signs of progression,the patient presented with palpable masses in both breasts.She complained from severe pain and swelling of the breasts.Imaging workup showed bilateral breast lesions,and diagnosis of breast infiltration by leukemic cells was confirmed after immunohistopathological evaluation.The patient suffering from severe pain,discomfort,and swelling of both breasts due to leukemic infiltration was referred to the Radiation Oncology Department for symptomatic palliation.Whole breast irradiation was delivered to both breasts of the patient with BART using the ABC system.The patient had complete resolution of her symptoms after treatment with BART.CONCLUSION BART with the ABC system resulted in complete resolution of the patient’s symptoms due to leukemic infiltration of both breasts with T-ALL.This contemporary treatment technique should be preferred for radiotherapeutic management of patients with leukemic infiltration of the breasts to achieve effective symptomatic palliation.

A Novel Clutter Suppression Algorithm for Low-Slow-Small Targets Detecting Based on Sparse Adaptive Filtering

Passive detection of low-slow-small(LSS)targets is easily interfered by direct signal and multipath clutter,and the traditional clutter suppression method has the contradiction between step size and convergence rate.In this paper,a frequency domain clutter suppression algorithm based on sparse adaptive filtering is proposed.The pulse compression operation between the error signal and the input reference signal is added to the cost function as a sparsity constraint,and the criterion for filter weight updating is improved to obtain a purer echo signal.At the same time,the step size and penalty factor are brought into the adaptive iteration process,and the input data is used to drive the adaptive changes of parameters such as step size.The proposed algorithm has a small amount of calculation,which improves the robustness to parameters such as step size,reduces the weight error of the filter and has a good clutter suppression performance.

Diabetic retinopathy identification based on multi-sourcefree domain adaptation

AIM:To address the challenges of data labeling difficulties,data privacy,and necessary large amount of labeled data for deep learning methods in diabetic retinopathy(DR)identification,the aim of this study is to develop a source-free domain adaptation(SFDA)method for efficient and effective DR identification from unlabeled data.METHODS:A multi-SFDA method was proposed for DR identification.This method integrates multiple source models,which are trained from the same source domain,to generate synthetic pseudo labels for the unlabeled target domain.Besides,a softmax-consistence minimization term is utilized to minimize the intra-class distances between the source and target domains and maximize the inter-class distances.Validation is performed using three color fundus photograph datasets(APTOS2019,DDR,and EyePACS).RESULTS:The proposed model was evaluated and provided promising results with respectively 0.8917 and 0.9795 F1-scores on referable and normal/abnormal DR identification tasks.It demonstrated effective DR identification through minimizing intra-class distances and maximizing inter-class distances between source and target domains.CONCLUSION:The multi-SFDA method provides an effective approach to overcome the challenges in DR identification.The method not only addresses difficulties in data labeling and privacy issues,but also reduces the need for large amounts of labeled data required by deep learning methods,making it a practical tool for early detection and preservation of vision in diabetic patients.

Propagation of Low Temperature-Adapted Hepatitis A Virus in BSC-1 Cell Culture

Hepatitis A virus, HM-175 strain, adapted to low temperature was cultivated in BSC-1 cell culture.Replication of the virus was detected by radioimmunoassay(RIA), radioimmunofocus assay (RIFA) and dot blot hybridization. The results showed that, of the 7 low temperature-adapted(LTA) strains studied, strain E, F and D gave the highest titer in BSC-1 cell culture. This culture system was proved to be suitable for the study of the characteristic of temperature mutants of HAV.

Thermostable ethanol tolerant xylanase from a cold-adapted marine species Acinetobacter johnsonii

A xylanase-producing bacterium, isolated from deep sea sediments, was identified as the cold-adapted marine species Acinetobacter Johnsonii. A cold-adapted marine species Acinetobacter Johnsonii could grow at 4 ℃. The optimum temperature and pH of xylanase from a cold-adapted marine species Acinetobacter Johnsonii were 55 ℃ and pH 6.0. Xylanase from a cold-adapted marine species Acinetobacter Johnsonii remained at 80% activity after incubation for 1 h at 65 ℃. The xylanase activity was 1.2-fold higher in 4% ethanol solution than in ethanol free solution. Gibbs free energy of denaturation, ΔG, was higher in 4% ethanol solution than in ethanol free solution. Thermostable ethanol tolerant xylanase was valuable for bioethanol production by simultaneous saccharification and fermentation process with xylan as a carbon source.

Underwater four-quadrant dual-beam circumferential scanning laser fuze using nonlinear adaptive backscatter filter based on pauseable SAF-LMS algorithm

The phenomenon of a target echo peak overlapping with the backscattered echo peak significantly undermines the detection range and precision of underwater laser fuzes.To overcome this issue,we propose a four-quadrant dual-beam circumferential scanning laser fuze to distinguish various interference signals and provide more real-time data for the backscatter filtering algorithm.This enhances the algorithm loading capability of the fuze.In order to address the problem of insufficient filtering capacity in existing linear backscatter filtering algorithms,we develop a nonlinear backscattering adaptive filter based on the spline adaptive filter least mean square(SAF-LMS)algorithm.We also designed an algorithm pause module to retain the original trend of the target echo peak,improving the time discrimination accuracy and anti-interference capability of the fuze.Finally,experiments are conducted with varying signal-to-noise ratios of the original underwater target echo signals.The experimental results show that the average signal-to-noise ratio before and after filtering can be improved by more than31 d B,with an increase of up to 76%in extreme detection distance.

An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.

Extracellular enzymatic activities of cold-adapted bacteria from polar oceans and effect of temperature and salinity on cell growth

The potential of 324 bacteria isolated from different habitats in polar oceans to produce a variety of extracellular enzymatic activities at low temperature was investigated. By plate assay, lipase, protease, amylase, gelatinase, agarase, chitinase or cellulase were detected. Lipases were generally present by bacteria living in polar oceans. Protease-producing bacteria held the second highest proportion in culturable isolates. Strains producing amylase kept a relative stable proportion of around 30% in different polar marine habitats. All 50 Arctic sea-ice bacteria producing proteases were cold-adapted strains, however, only 20% were psychrophilic. 98% of them could grow at 3% NaCl, and 56% could grow without NaCl. On the other hand, 98% of these sea-ice bacteria produced extracellular proteases with optimum temperature at or higher than 35℃, well above the upper temperature limit of cell growth. Extracellular enzymes including amylase, agarase, cellulase and lipase released by bacteria from seawater or sediment in polar oceans, most expressed maximum activities between 25 and 35℃. Among extracellular enzymes released by bacterial strain BSw20308, protease expressed maximum activity at 40℃, higher than 35℃ of polysaccharide hydrolases and 25℃ of lipase.

Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.

Robust adaptive leaderless consensus of unknown non-minimum phase linear multi-agent systems subject to disturbances and/or unmodeled dynamics

This article investigates the problem of robust adaptive leaderless consensus for heterogeneous uncertain nonminimumphase linear multi-agent systems over directed communication graphs. Each agent is assumed tobe of unknown nominal dynamics and also subject to external disturbances and/or unmodeled dynamics. Anovel distributed robust adaptive control strategy is proposed. It is shown that the robust adaptive leaderlessconsensus problem is solved with the proposed control strategy under some sufficient conditions. Two examplesare provided to demonstrate the efficacy of the proposed control strategy.

Splitting of Gaussian Models via Adapted BML Method Pertaining to Cry-Based Diagnostic System

In this paper,we make use of the boosting method to introduce a new learning algorithm for Gaussian Mixture Models (GMMs) called adapted Boosted Mixture Learning (BML). The method possesses the ability to rectify the existing problems in other conventional techniques for estimating the GMM parameters, due in part to a new mixing-up strategy to increase the number of Gaussian components. The discriminative splitting idea is employed for Gaussian mixture densities followed by learning via the introduced method. Then, the GMM classifier was applied to distinguish between healthy infants and those that present a selected set of medical conditions. Each group includes both full-term and premature infants. Cry-pattern for each pathological condition is created by using the adapted BML method and 13-dimensional Mel-Frequency Cepstral Coefficients (MFCCs) feature vector. The test results demonstrate that the introduced method for training GMMs has a better performance than the traditional method based upon random splitting and EM-based re-estimation as a reference system in multi-pathological classification task.