Improving the efficiency of CRISPR-Cas12a-based genome editing with site-specific covalent Cas12a-crRNA conjugates.

The CRISPR-Cas12a system shows unique features compared with widely used Cas9, making it an attractive and potentially more precise alternative. However, the adoption of this system has been hindered by its relatively low editing efficiency. Guided by physical chemical principles, we covalently conjugated 5' terminal modified CRISPR RNA (crRNA) to a site-specifically modified Cas12a through biorthogonal chemical reaction. The genome editing efficiency of the resulting conjugated Cas12a complex (cCas12a) was substantially higher than that of the wild-type complex. We also demonstrated that cCas12a could be used for precise gene knockin and multiplex gene editing in a chimeric antigen receptor T cell preparation with efficiency much higher than that of the wild-type system. Overall, our findings indicate that covalently linking Cas nuclease and crRNA is an effective approach to improve the Cas12a-based genome editing system and could potentially provide an insight into engineering other Cas family members with low efficiency as well.

Tracking endogenous proteins based on RNA editing-mediated genetic code expansion.

Protein labeling approaches are important to study proteins in living cells, and genome editing tools make it possible to tag endogenous proteins to address the concerns associated with overexpression. Here we established RNA editing-mediated noncanonical amino acids (ncAAs) protein tagging (RENAPT) to site-specifically label endogenous proteins with ncAAs in living cells. RENAPT labels protein in a temporary and nonheritable manner and is not restricted by protospacer adjacent motif sequence. Using a fluorescent ncAA or ncAA with a bio-orthogonal reaction handle for subsequent dye labeling, we demonstrated that a variety of endogenous proteins can be imaged at their specific subcellular locations. In addition, two proteins can be tagged individually and simultaneously using two different ncAAs. Furthermore, endogenous ion channels and neuron-specific proteins can be real-time labeled in primary neurons. Thus, RENAPT presents a promising platform with broad applicability for tagging endogenous proteins in living cells to study their localization and functions.

Computation-Guided Discovery of Diazole Monosubstituted Tetrazines as Optimal Bioorthogonal Tools.

Monosubstituted tetrazines are important bioorthogonal reactive tools due to their rapid ligation with trans-cyclooctene. However, their application is limited by the reactivity-stability paradox in biological environments. In this study, we demonstrated that steric effects are crucial in resolving this paradox through theoretical methods and developed a simple synthetic route to validate our computational findings, leading to the discovery of 1,3-azole-4-yl and 1,2-azole-3-yl monosubstituted tetrazines as superior bioorthogonal tools. These new tetrazines surpass previous tetrazines in terms of high reactivities and elevated stabilities. The most stable tetrazine exhibits a reasonable stability (71% remaining after 24 h incubation in cell culture medium) and an exceptionally high reactivity (k2 > 104 M-1 s-1 toward trans-cyclooctene). Due to its good stability in biological systems, a noncanonical amino acid containing such a tetrazine side chain was genetically encoded into proteins site-specifically via an expanded genetic code. The encoded protein can be efficiently labeled using cyclopropane-fused trans-cyclooctene dyes in living mammalian cells with an ultrafast reaction rate exceeding 107 M-1 s-1, making it one of the fastest protein labeling reactions reported to date. Additionally, we showed its superiority through in vivo reactions in living mice, achieving an efficient local anchoring of proteins. These tetrazines are expected to be optimal bioorthogonal reactive tools within living systems.

Characterization and stress-responsive regulation of CmPHT1 genes involved in phosphate uptake and transport in Melon (Cucumis melo L.).

BACKGROUND: Phosphorus (P) deficiency, a major nutrient stress, greatly hinders plant growth. Phosphate (Pi) uptake in plant roots relies on PHT1 family transporters. However, melon (Cucumis melo L.) lacks comprehensive identification and characterization of PHT1 genes, particularly their response patterns under diverse stresses. RESULTS: This study identified and analyzed seven putative CmPHT1 genes on chromosomes 3, 4, 5, 6, and 7 using the melon genome. Phylogenetic analysis revealed shared motifs, domain compositions, and evolutionary relationships among genes with close histories. Exon number varied from 1 to 3. Collinearity analysis suggested segmental and tandem duplications as the primary mechanisms for CmPHT1 gene family expansion. CmPHT1;4 and CmPHT1;5 emerged as a tandemly duplicated pair. Analysis of cis-elements in CmPHT1 promoters identified 14 functional categories, including putative PHR1-binding sites (P1BS) in CmPHT1;4, CmPHT1;6, and CmPHT1;7. We identified that three WRKY transcription factors regulated CmPHT1;5 expression by binding to its W-box element. Notably, CmPHT1 promoters harbored cis-elements responsive to hormones and abiotic factors. Different stresses regulated CmPHT1 expression differently, suggesting that the adjusted expression patterns might contribute to plant adaptation. CONCLUSIONS: This study unveils the characteristics, evolutionary diversity, and stress responsiveness of CmPHT1 genes in melon. These findings lay the foundation for in-depth investigations into their functional mechanisms in Cucurbitaceae crops.

Comprehensive review: Effects of climate change and greenhouse gases emission relevance to environmental stress on horticultural crops and management.

Global climate change exerts a significant impact on sustainable horticultural crop production and quality. Rising Global temperatures have compelled the agricultural community to adjust planting and harvesting schedules, often necessitating earlier crop cultivation. Notably, climate change introduces a suite of ominous factors, such as greenhouse gas emissions (CGHs), including elevated temperature, increased carbon dioxide (CO2) concentrations, nitrous oxide (N2O) and methane (CH4) ozone depletion (O3), and deforestation, all of which intensify environmental stresses on crops. Consequently, climate change stands poised to adversely affect crop yields and livestock production. Therefore, the primary objective of the review article is to furnish a comprehensive overview of the multifaceted factors influencing horticulture production, encompassing fruits, vegetables, and plantation crops with a particular emphasis on greenhouse gas emissions and environmental stressors such as high temperature, drought, salinity, and emission of CO2. Additionally, this review will explore the implementation of novel horticultural crop varieties and greenhouse technology that can contribute to mitigating the adverse impact of climate change on agricultural crops.

A model selection criterion for clustered survival analysis with informative cluster size.

We propose a model selection criterion for correlated survival data when the cluster size is informative to the outcome. This approach, called Resampling Cluster Survival Information Criterion (RCSIC), uses the Cox proportional hazards model that is weighted with the inverse of the cluster size. The RCSIC based on the within-cluster resampling idea takes into account the possible variability of the within-cluster subsampling and the possible informativeness of cluster sizes. The RCSIC allows for easy execution for the within-cluster resampling idea without a large number of resamples of the data. In contrast with the traditional model selection method in survival analysis, the RCSIC has an additional penalization for the within-cluster subsampling variability. Our simulations show the satisfactory results where the RCSIC provides a more robust power for variable selection in terms of clustered survival analysis, regardless of whether informative cluster size exists or not. Applying the RCSIC method to a periodontal disease studies, we identify the tooth loss in patients associated with the risk factors, Age, Filled Tooth, Molar, Crown, Decayed Tooth, and Smoking Status, respectively.

Integrated Analysis of the Transcriptome and Metabolome of Brassica rapa Revealed Regulatory Mechanism under Heat Stress.

Affected by global warming; heat stress is the main limiting factor for crop growth and development. Brassica rapa prefers cool weather, and heat stress has a significant negative impact on its growth, development, and metabolism. Understanding the regulatory patterns of heat-resistant and heat-sensitive varieties under heat stress can help deepen understanding of plant heat tolerance mechanisms. In this study, an integrative analysis of transcriptome and metabolome was performed on the heat-tolerant ('WYM') and heat-sensitive ('AJH') lines of Brassica rapa to reveal the regulatory networks correlated to heat tolerance and to identify key regulatory genes. Heat stress was applied to two Brassica rapa cultivars, and the leaves were analyzed at the transcriptional and metabolic levels. The results suggest that the heat shock protein (HSP) family, plant hormone transduction, chlorophyll degradation, photosynthetic pathway, and reactive oxygen species (ROS) metabolism play an outstanding role in the adaptation mechanism of plant heat tolerance. Our discovery lays the foundation for future breeding of horticultural crops for heat resistance.

K33-Linked Polyubiquitination of Coronin 7 by Cul3-KLHL20 Ubiquitin E3 Ligase Regulates Protein Trafficking.

Ubiquitin chains are formed as structurally distinct polymers via different linkages, and several chain types including K33-linkage remain uncharacterized. Here, we describe a role for K33-polyubiquitination in protein trafficking. We show that the Cullin 3 (Cul3) substrate adaptor KLHL20 is localized to the trans-Golgi network (TGN) and is important for post-Golgi trafficking by promoting the biogenesis of TGN-derived transport carriers. The Cul3-KLHL20 ubiquitin E3 ligase catalyzes a nondegradable, K33-linked polyubiquitination on coronin 7 (Crn7), which facilitates Crn7 targeting to TGN through a ubiquitin-dependent interaction with Eps15. Blockage of K33-chain formation, Crn7 ubiquitination, or disruption of Crn7-Eps15 interaction impairs TGN-pool F-actin assembly, a process essential for generating transport carriers. Enforced targeting of Crn7 to TGN bypasses the requirement of K33-ubiquitination for TGN-pool F-actin assembly and post-Golgi trafficking. Our study reveals a role of KLHL20-mediated K33-ubiquitination of Crn7 in post-Golgi transport and identifies a cellular recognition mechanism for this ubiquitin chain type.

The relationship between sleep disorders, anxiety, depression, and cognitive function with restless legs syndrome (RLS) in the elderly.

OBJECTIVES: Restless legs syndrome (RLS) has a significant effect on sleep and quality of life. Delays in diagnosis and treatment are frequent due to a lack of awareness. In this study, a clinical analysis was performed to examine the relationship between sleep, mood, and cognitive function in RLS. METHODS: According to the Pittsburgh Sleep Quality Index score (PSQI), patients with RLS were divided into a sleep disorders group (SD, PSQI > 7) and non-sleep disorders group (NSD, PSQI ≤ 7). Healthy controls were selected as a control group matched for age, cultural background, and marital status. We compared differences between the three groups using the Hamilton Anxiety Scale (HAMA), Hamilton Depression (HAMD), Mini-Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA). The SD and NSD groups were also assessed with the Restless Leg Syndrome Rating Scale (RLSRS) and the severity of RLS between the two groups was compared. The analysis used t-test, ANOVA, and Pearson correlation. RESULTS: (1) Among the 54 RLS patients, 30 people in the control group, 35 patients with sleep disorders (SD, 65%), and 19 patients without sleep disorders (NSD, 35%), there were no significant differences in age, educational level, marital status, or trauma history. (2) The comparison results of the case group (SD and NSD) and the control group showed highly significant differences (P < 0.01) in the PSQI-HAMA-HAMD score but no significant differences between the NSD group, the SD group, and the control group in MMSE score. There was no difference between the NSD group and the control group in the MoCA, but a significant difference (P < 0.05) between the SD group and the control group was found. (3) The comparison between the NSD and the SD groups revealed significant differences in the RLSRS, HAMA, and HAMD scores (P < 0.05), but there were no statistical differences (P > 0.05) between two groups on MMSE and MoCA score. (4) Correlation and regression showed that there was a linear correlation between PSQI scores and RLSRS and HAMD scores in patients with RLS (P < 0.05). The regression equation was PSQI = - 2.393 + 0.494 RLSRS + 0.170 HAMD. CONCLUSIONS: RLS patients were prone to sleep disorders, anxiety, and depression. Sleep disorders increased with the severity of the RLS and had some influence on the patient's cognitive function. Sleep disorders were closely related to RLSRS and HAMD.

Physiological and Transcriptomic Analysis Reveals the Responses and Difference to High Temperature and Humidity Stress in Two Melon Genotypes.

Due to the frequent occurrence of continuous high temperatures and heavy rain in summer, extremely high-temperature and high-humidity environments occur, which seriously harms crop growth. High temperature and humidity (HTH) stress have become the main environmental factors of combined stress in summer. The responses of morphological indexes, physiological and biochemical indexes, gas exchange parameters, and chlorophyll fluorescence parameters were measured and combined with chloroplast ultrastructure and transcriptome sequencing to analyze the reasons for the difference in tolerance to HTH stress in HTH-sensitive 'JIN TAI LANG' and HTH-tolerant 'JIN DI' varieties. The results showed that with the extension of stress time, the superoxide dismutase (SOD), peroxidase (POD), and ascorbate peroxidase (APX) activities of the two melon varieties increased rapidly, the leaf water content increased, and the tolerant varieties showed stronger antioxidant capacity. Among the sensitive cultivars, Pn, Fv/Fm, photosystem II, and photosystem I chlorophyll fluorescence parameters were severely inhibited and decreased rapidly with the extension of stress time, while the HTH-tolerant cultivars slightly decreased. The cell membrane and chloroplast damage in sensitive cultivars were more severe, and Lhca1, Lhca3, and Lhca4 proteins in photosystem II and Lhcb1-Lhcb6 proteins in photosystem I were inhibited compared with those in the tolerant cultivar. These conclusions may be the main reason for the different tolerances of the two cultivars. These findings will provide new insights into the response of other crops to HTH stress and also provide a basis for future research on the mechanism of HTH resistance in melon.

A green and environmental sustainable approach to synthesis the Mn oxide nanomaterial from Punica granatum leaf extracts and its in vitro biological applications.

Pathogenic fungal infections in fruit cause economic losses and have deleterious effects on human health globally. Despite the low pH and high water contents of vegetables and fresh, ripened fruits, they are prone to fungal and bacterial diseases. The ever-increasing resistance of phytopathogens toward pesticides, fungicides and bactericides has resulted in substantial threats to plant growth and production in recent years. However, plant-mediated nanoparticles are useful tools for combating parasitic fungi and bacteria. Herein, we synthesized biogenic manganese oxide nanoparticles (MnONPs) from an extract of Punica granatum (P. granatum), and these nanoparticles showed significant antifungal and antibacterial activities. The production of MnONPs from plant extracts was confirmed by infrared spectroscopy (FTIR), X-ray diffraction (XRD) and UV visible spectroscopy (UV). The surface morphology and shape of the nanoparticles were characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Using a detached fruit method, the MnONPs were shown to exhibit significant antimicrobial activities against two bacterial strains, E. coli and S. aureus, and against the fungal species P. digitatum. The results revealed that the MnONPs had a minimum antimicrobial activity at 25 µg/mL and a maximum antimicrobial activity at 100 µg/mL against bacterial strains in lemon (citrus). Furthermore, the MnONPs exhibited significant ROS scavenging activity. Finally, inconclusive results from the green-synthesized MnONPs magnified their significant synergetic effects on the shelf life of tomatoes (Lycopercicum esculantum) and indicated that they could be used to counteract the phytopathological effects of postharvest fungal diseases in fruits and vegetables. Overall, this method of MnONPs synthesis is inexpensive, rapid and ecofriendly. MnONPs can be used as potential antimicrobial agents against different microbial species.

Effects of a dynamic combined training on impulse response for middle-aged and elderly patients with osteoporosis and knee osteoarthritis: a randomized control trial.

Dynamic combined training is a crucial component in treating musculoskeletal conditions to increase muscle strength and improve functional ability. This randomized control trial aimed to examine the effect of dynamic combined training on muscle strength and contractile rate of force development (RFD) in patients with osteoporosis (OP) and knee osteoarthritis (KOA). 58 participants with OP or KOA were randomly assigned to a control group (CG) (CGOP, n = 12; CGKOA, n = 15) or training group (TG) (TGOP, n = 14; TGKOA, n = 17). The training group participated in a 12-week, three-days-per-week supervised program consisting of stretching and warm-up exercises (10 min), hydraulic resistance training (40 min), and cool-down and relaxation exercises (10 min). All participants were evaluated at baseline and post-training. The maximal voluntary contraction (MVC) and contractile RFD at 0-200 ms increased significantly in middle-aged and older patients with OP. As for KOA, the dynamic combined training program was effective in improving the muscle strength. The maximal voluntary contraction (MVC) and contractile RFD at 0-200 ms increased significantly (by 29.22%, P = .000 and 27.25%, P = .019, respectively) in middle-aged and older patients with OP. In the KOA group, MVC and contractile RFD improved but did not reach statistical significance. The dynamic combined training program is effective for health promotion in older adults with OP or KOA.

Non-Invasive Sensing of Nitrogen in Plant Using Digital Images and Machine Learning for Brassica Campestris ssp. Chinensis L.

Monitoring plant nitrogen (N) in a timely way and accurately is critical for precision fertilization. The imaging technology based on visible light is relatively inexpensive and ubiquitous, and open-source analysis tools have proliferated. In this study, texture- and geometry-related phenotyping combined with color properties were investigated for their potential use in evaluating N in pakchoi (Brassica campestris ssp. chinensis L.). Potted pakchoi treated with four levels of N were cultivated in a greenhouse. Their top-view images were acquired using a camera at six growth stages. The corresponding plant N concentration was determined destructively. The quantitative relationships between the nitrogen nutrition index (NNI) and the image-based phenotyping features were established using the following algorithms: random forest (RF), support vector regression (SVR), and neural network (NN). The results showed the full model based on the color, texture, and geometry-related features outperforms the model based on only the color-related feature in predicting the NNI. The RF full model exhibited the most robust performance in both the seedling and harvest stages, reaching prediction accuracies of 0.823 and 0.943, respectively. The high prediction accuracy of the model allows for a low-cost, non-destructive monitoring of N in the field of precision crop management.

An Efficient and Geometric-Distortion-Free Binary Robust Local Feature.

An efficient and geometric-distortion-free approach, namely the fast binary robust local feature (FBRLF), is proposed. The FBRLF searches the stable features from an image with the proposed multiscale adaptive and generic corner detection based on the accelerated segment test (MAGAST) to yield an optimum threshold value based on adaptive and generic corner detection based on the accelerated segment test (AGAST). To overcome the problem of image noise, the Gaussian template is applied, which is efficiently boosted by the adoption of an integral image. The feature matching is conducted by incorporating the voting mechanism and lookup table method to achieve a high accuracy with low computational complexity. The experimental results clearly demonstrate the superiority of the proposed method compared with the former schemes regarding local stable feature performance and processing efficiency.

A Phenotype-Based Approach for the Substrate Water Status Forecast of Greenhouse Netted Muskmelon.

Cultivation substrate water status is of great importance to the production of netted muskmelon (Cucumis melo L. var. reticulatus Naud.). A prediction model for the substrate water status would be beneficial in irrigation schedule guidance. In this study, the machine learning random forest model was used to forecast plant substrate water status given the phenotypic traits throughout the muskmelon growing season. Here, two varieties of netted muskmelon, "Wanglu" and "Arus", were planted in a greenhouse under four substrate water treatments and their phenotypic traits were measured by taking the images within the visible and near-infrared spectrums, respectively. Results showed that a simplified model outperformed the original model in forecasting speed, while it only uses the top five most significant contribution traits. The forecast accuracy reached up to 77.60%, 94.37%, and 90.01% for seedling, vine elongation, and fruit growth stages, respectively. Combining the imaging phenotypic traits and machine learning technique would provide a robust forecast of water status around the plant root zones.

Corilagin Reduces the Frequency of Seizures and Improves Cognitive Function in a Rat Model of Chronic Epilepsy.

BACKGROUND Worldwide, epilepsy is an important chronic neurological condition. The aim of this study was to evaluate the effects of corilagin, an ellagitannin extracted from medicinal plants, on the frequency of seizures and cognitive function in a rat model of chronic epilepsy. MATERIAL AND METHODS Chronic epilepsy was induced in male Wistar rats by intraperitoneal (IP) injection of pentylenetetrazol (PTZ) for 36 days. Corilagin, 10 mg/kg and 20 mg/kg, was injected IP into treated rats, 24 days before the start of PTZ treatment, until the end of the protocol. The effects of corilagin were assessed by the pattern of epileptic seizures; cognitive function was assessed using the Morris water maze (MWM) navigation test. The mechanism of action of corilagin was investigated by measuring cytokine levels and oxidative stress parameters, including reactive oxygen species (ROS) production, and carbonic anhydrase inhibitory (CAI) activity. Histological analysis of fixed brain tissue sections included cresyl violet acetate staining (Nissl staining) for Nissl substance in the neuronal cytoplasm. RESULTS The corilagin-treated rats, compared with the control group, showed a significantly lower rate of epileptic events, improved cognitive function, reduced level of cytokines, reduced ROS production reduced CAI activity in the brain tissues (P<0.01). Histology of the rat brain tissues study showed that corilagin treatment maintained the neuronal cellular structure and number of surviving cells compared with the control group of rats. CONCLUSIONS The findings of this study showed that corilagin reduced the frequency of seizures and improved the cognitive function in a rat model of chronic epilepsy.

Role of RAGE in Alzheimer's Disease.

Receptor for advanced glycation end products (RAGE) is a receptor of the immunoglobulin super family that plays various important roles under physiological and pathological conditions. Compelling evidence suggests that RAGE acts as both an inflammatory intermediary and a critical inducer of oxidative stress, underlying RAGE-induced Alzheimer-like pathophysiological changes that drive the process of Alzheimer's disease (AD). A critical role of RAGE in AD includes beta-amyloid (Aß) production and accumulation, the formation of neurofibrillary tangles, failure of synaptic transmission, and neuronal degeneration. The steady-state level of Aß depends on the balance between production and clearance. RAGE plays an important role in the Aß clearance. RAGE acts as an important transporter via regulating influx of circulating Aß into brain, whereas the efflux of brain-derived Aß into the circulation via BBB is implemented by LRP1. RAGE could be an important contributor to Aß generation via enhancing the activity of ß- and/or γ-secretases and activating inflammatory response and oxidative stress. However, sRAGE-Aß interactions could inhibit Aß neurotoxicity and promote Aß clearance from brain. Meanwhile, RAGE could be a promoting factor for the synaptic dysfunction and neuronal circuit dysfunction which are both the material structure of cognition, and the physiological and pathological basis of cognition. In addition, RAGE could be a trigger for the pathogenesis of Aß and tau hyper-phosphorylation which both participate in the process of cognitive impairment. Preclinical and clinical studies have supported that RAGE inhibitors could be useful in the treatment of AD. Thus, an effective measure to inhibit RAGE may be a novel drug target in AD.

Role of insulin resistance in Alzheimer's disease.

A critical role of insulin resistance (IR) in Alzheimer's disease (AD) includes beta-amyloid (Aß) production and accumulation, the formation of neurofibrillary tangles (NFTs), failure of synaptic transmission and neuronal degeneration. Aß is sequentially cleavaged from APP by two proteolytic enzymes: ß-secretase and γ-secretase. IR could regulate Aß production via enhancing ß- and γ-secretase activity. Meanwhile, IR induces oxidative stress and inflammation in the brain which contributes to Aß and tau pathology. Aß accumulation can enhance IR through Aß-mediated inflammation and oxidative stress. IR is a possible linking between amyloid plaques and NFTs pathology via oxidative stress and neuroinflammation. Additionally, IR could disrupt acetylcholine activity, and accelerate axon degeneration and failures in axonal transport, and lead to cognitive impairment in AD. Preclinical and clinical studies have supported that insulin could be useful in the treatment of AD. Thus, an effective measure to inhibit IR may be a novel drug target in AD.

Clinical characteristics and lateralization of the horizontal semicircular canal light cupula.

Introduction: Positional vertigo and nystagmus are the main symptoms and signs of dizziness, respectively. Despite the clinical utility of the supine roll test (SRT) and null point (NP) in diagnosing light cupula, a type of positional vertigo, there exists a notable gap in the literature concerning the comprehensive evaluation of lateralization values based on various nystagmus characteristics and the intensity of direction-changing positional nystagmus (DCPN) in the SRT, particularly in comparison to the NP. Additionally, limited data on abnormal canal paresis (CP) in light cupula patients underscores the need for further research with a larger patient population to elucidate this mechanism. This study aims to investigate the characteristics of positional nystagmus and lateralization of the horizontal semicircular canal (HSCC) light cupula, which is a type of positional vertigo and nystagmus that is poorly understood. Methods: Eighty-five patients (17 males, 68 females; mean age, 60.9 years) with light cupula were reviewed. We summarized the characteristics of spontaneous nystagmus and positional nystagmus, including supine positioning nystagmus, bow nystagmus, and lean nystagmus. Then, the side of the NP was identified as the affected side, and the values of the fast phase direction of the spontaneous nystagmus, supine positioning nystagmus, bow nystagmus, and lean nystagmus, as well as the intensity of the DCPN in the SRT, were used to diagnose the affected sides. Caloric testing was also performed for some patients. Results: Light cupula was observed in 5.7% of the patients with positional nystagmus. The frequencies of supine positioning nystagmus (88.2%), bow nystagmus (90.6%), and lean nystagmus (83.5%) were higher than spontaneous nystagmus (61.2%) (p < 0.001). The second NP (NP2) (92.9%) and third NP (NP3) (83.5%) were readily detected, affecting the left and right sides in 38 and 47 patients, respectively. Lateralization through the fast phase directions of bow nystagmus and lean nystagmus did not significantly differ from that of NP (all p > 0.05). However, the accuracy rate of lateralization through the sides with more vigorous DCPN in the SRT was 63.5%, significantly lower than through NP (p < 0.001). Particularly in patients with supine positioning nystagmus (n = 75), the rate was only 58.7% (p < 0.001). However, the rate was 100% in patients without supine positioning nystagmus (n = 10). Among the 70 patients who underwent caloric testing, 37 had abnormal CP, and the sides of the reduced caloric reaction were ipsilateral to the affected sides of the light cupula in 83.8% of the patients. Conclusion: Besides utilizing the NP to determine the affected side, the fast phase direction of the bow nystagmus or lean nystagmus can also aid in identification. However, a simple comparison of the intensity of DCPN in SRT cannot provide accurate lateralization, especially in patients with supine positioning nystagmus. There is a high incidence of CP on the affected side of the light cupula.

Study on nitrogen demand model in pakchoi (Brassica campestris ssp. Chinensis L.) based on nitrogen contents and phenotypic characteristics.

Introduction: In precision agriculture, the diagnosis of the nitrogen (N) nutrition status based on the plant phenotype, combined effects of soil types, various agricultural practices, and environmental factors which are essential for plant N accumulation. It helps to assess the N supply for plants at the right time and optimal amount to ensure high N use efficiency thereby reducing the N fertilizer applications to minimize environmental pollution. For this purpose, three different experiments were performed. Methods: A critical N content (Nc) model was constructed based on cumulative photothermal effect (LTF), Napplications, and cultivation systems on yield and N uptake in pakchoi. Results and discussion: According to the model, aboveground dry biomass (DW) accumulation was found equal or below to 1.5 t/ha, and the Nc value was observed at a constant of 4.78%. However, when DW accumulation exceeded 1.5 t/ha, Nc declined with the increase in DW accumulation, and the relationship between Nc and DW accumulation developed with the function Nc %=4.78 x DW-0.33. An N demand model was established based on the multi-information fusion method, which integrated multiple factors, including Nc, phenotypical indexes, temperature during the growth period, photosynthetically active radiation, and N applications. Furthermore, the model's accuracy was verified, and the predicted N contents were found consistent with the measured values (R2 = 0.948 and RMSE = 1.96 mg/plant). At the same time, an N demand model based on N use efficiency was proposed. Conclusions: This study can provide theoretical and technical support for precise N management in pakchoi production.