Feasibility and potential of terahertz spectral and imaging technology for Apple Valsa canker detection: A preliminary investigation.

Apple Valsa canker (AVC) caused by the Ascomycete Valsa mali, seriously constrains the production and quality of apple fruits. The symptomless incubation characteristics of Valsa mali make it highly challenging to detect AVC at an early infection stage. After infecting the wound of apple bark, the pathogenic hyphae of AVC will expand and colonize the phloem tissue. Meanwhile, various enzymes and toxic substances released by hyphae cause the decomposition of cellulose and lignin, and the generation of poisonous secondary metabolites in bark tissue. However, these early symptoms of AVC are invisible from the bark's appearance. Fortunately, Terahertz Spectral Imaging (ThzSI) technology with the advantage of penetrating, and fingerprinting is promising for detecting hidden or slight symptoms of the fungal infection. This study is a preliminary investigation of terahertz frequency-domain spectra for AVC in the early stage of infection. Healthy and two-week-infected apple tree branches were prepared for capturing ThzS images, and the spectral data were preprocessed by Multivariate scattering correction (MSC), Savitzky-Golay convolution smoothing (SG), and standard normal variate (SNV) respectively to remove data noise and improve data quality. Principal component analysis (PCA), competitive adaptive reweighted sampling (CARS), and random frog (RFROG) were employed to extract the spectral feature bands to eliminate redundant data and improve computational efficiency. Machine learning models were established based on the spectral features to detect AVC at an early infection stage, where 11 of them exhibited the best performance with F1-score of 99.72%. To further explore disease information in spatial spectra, imaging data were acquired using terahertz imaging technology. Based on imaging data, pseudo-color imaging, histogram equalization, and Otsu segmentation were employed to visualize early infection areas in apple barks. Furthermore, histogram feature (HF), shape feature (SF), and local binary pattern (LBP) extracted from terahertz spectral images were utilized to establish the SVM, RF, and KNN models. HF-SF-KNN and HF-SF-LBP-KNN with the best performance achieved F1-score of 98.82%. This study presents a preliminary application of terahertz spectral and imaging technology for early-stage AVC detection and demonstrates its feasibility. Additionally, it provides a new way to detect AVC, which expands the application of ThzSI technology in tree disease detection in orchards and lays the foundation for further research.

The Impact of Cognitive Load on Cooperation and Antisocial Punishment: Insights from a Public Goods Game Experiment.

This paper investigates the impact of cognitive load on the formation and maintenance of cooperation within a public goods game experiment featuring a punishment option. By integrating the experimental designs of prior studies and manipulating cognitive load through the memorization of numbers with varying digits, we reveal that high cognitive load accelerates the breakdown of cooperation, irrespective of the presence of a punishment system. Furthermore, under high cognitive load, participants are more likely to engage in antisocial punishment, while the punishment of free riders remains unaffected. These findings suggest that increased cognitive load depletes the cognitive resources needed for deliberative decision-making, leading to a higher propensity for antisocial punishment. Our study contributes to the literature by demonstrating the significant influence of cognitive load on cooperative behavior and providing new insights into the causes of antisocial punishment.

A novel strategy to construct hydrogels with anti-swelling and water-retention abilities by covalent surface modification.

Hydrogels have been widely used in various fields due to their diverse properties and flexible preparation methods. However, limited by the open network structure, hydrogels inevitably lose water in air or absorb water in aqueous solution, resulting in the loss of intrinsic functions, which severely hinders their practical applications. To address this issue, a general strategy was developed by subsequently modifying the surface of hydrogels with branched polyethyleneimine (PEI) and (3-(methacryloxy)propyl)trimethoxysilane (MPS) to covalently construct a dense cross-linked siloxane layer on the hydrogel surface. As a proof of concept, poly(2-(dimethylamino)ethyl methacrylate)/sodium alginate (PDMAEMA/SA) hydrogels were chosen as the model hydrogels to verify the feasibility of this strategy. The hydrogels adsorbed PEI to form amino-rich surfaces through hydrogen bonding, followed by covalently grafting MPS through rapid and catalyst-free mutual chemical reactions between acrylates and amine groups, as well as the hydrolysis of MPS. After modification, robust hydrophobic surfaces were successfully fabricated on the hydrophilic hydrogels. The modified hydrogels exhibited extraordinary anti-swelling and water-retention abilities. As the most typical intrinsic properties of hydrogels, the conductivity and sensing performance were well preserved. The strategy reported here provides a new insight into the construction of hydrogels with anti-swelling and water-retention abilities.

LncRNA DCRT Protects Against Dilated Cardiomyopathy by Preventing NDUFS2 Alternative Splicing by Binding to PTBP1.

BACKGROUND: Dilated cardiomyopathy is characterized by left ventricular dilation and continuous systolic dysfunction. Mitochondrial impairment is critical in dilated cardiomyopathy; however, the underlying mechanisms remain unclear. Here, we explored the cardioprotective role of a heart-enriched long noncoding RNA, the dilated cardiomyopathy repressive transcript (DCRT), in maintaining mitochondrial function. METHODS: The DCRT knockout (DCRT-/-) mice and DCRT knockout cells were developed using CRISPR-Cas9 technology. Cardiac-specific DCRT transgenic mice were generated using α-myosin heavy chain promoter. Chromatin coimmunoprecipitation, RNA immunoprecipitation, Western blot, and isoform sequencing were performed to investigate the underlying mechanisms. RESULTS: We found that the long noncoding RNA DCRT was highly enriched in the normal heart tissues and that its expression was significantly downregulated in the myocardium of patients with dilated cardiomyopathy. DCRT-/- mice spontaneously developed cardiac dysfunction and enlargement with mitochondrial impairment. DCRT transgene or overexpression with the recombinant adeno-associated virus system in mice attenuated cardiac dysfunction induced by transverse aortic constriction treatment. Mechanistically, DCRT inhibited the third exon skipping of NDUFS2 (NADH dehydrogenase ubiquinone iron-sulfur protein 2) by directly binding to PTBP1 (polypyrimidine tract binding protein 1) in the nucleus of cardiomyocytes. Skipping of the third exon of NDUFS2 induced mitochondrial dysfunction by competitively inhibiting mitochondrial complex I activity and binding to PRDX5 (peroxiredoxin 5) and suppressing its antioxidant activity. Furthermore, coenzyme Q10 partially alleviated mitochondrial dysfunction in cardiomyocytes caused by DCRT reduction. CONCLUSIONS: Our study revealed that the loss of DCRT contributed to PTBP1-mediated exon skipping of NDUFS2, thereby inducing cardiac mitochondrial dysfunction during dilated cardiomyopathy development, which could be partially treated with coenzyme Q10 supplementation.

Fibroblast-localized lncRNA CFIRL promotes cardiac fibrosis and dysfunction in dilated cardiomyopathy.

CFIRL is a long noncoding RNA (lncRNA), we previously identified as the most significantly upregulated lncRNA in the failing hearts of patients with dilated cardiomyopathy (DCM). In this study, we determined the function of CFIRL and its role in DCM. Real-time polymerase chain reaction and in situ hybridization assays revealed that CFIRL was primarily localized in the nucleus of cardiac fibroblasts and robustly increased in failing hearts. Global knockdown or fibroblast-specific knockout of CFIRL attenuated transverse aortic constriction (TAC)-induced cardiac dysfunction and fibrosis in vivo. Overexpression of CFIRL in vitro promoted fibroblast proliferation and aggravated angiotensin II-induced differentiation to myofibroblasts. CFIRL knockdown attenuated these effects. Mechanistically, RNA pull-down assay and gene expression profiling revealed that CFIRL recruited ENO1, a newly identified noncanonical transcriptional factor, to activate IL-6 transcription. IL-6 exerted a paracrine effect on cardiomyocytes to promote cardiac hypertrophy, which can be prevented by CFIRL knockdown. These findings uncover the critical role of CFIRL, a fibroblast-associated lncRNA, in heart failure by facilitating crosstalk between fibroblasts and cardiomyocytes. CFIRL knockdown might be a potent strategy to prevent cardiac remodeling in heart failure, particularly in DCM.

Effect and Mechanism of Rapamycin on Cognitive Deficits in Animal Models of Alzheimer's Disease: A Systematic Review and Meta-analysis of Preclinical Studies.

Background: Alzheimer's disease (AD), the most common form of dementia, remains long-term and challenging to diagnose. Furthermore, there is currently no medication to completely cure AD patients. Rapamycin has been clinically demonstrated to postpone the aging process in mice and improve learning and memory abilities in animal models of AD. Therefore, rapamycin has the potential to be significant in the discovery and development of drugs for AD patients. Objective: The main objective of this systematic review and meta-analysis was to investigate the effects and mechanisms of rapamycin on animal models of AD by examining behavioral indicators and pathological features. Methods: Six databases were searched and 4,277 articles were retrieved. In conclusion, 13 studies were included according to predefined criteria. Three authors independently judged the selected literature and methodological quality. Use of subgroup analyses to explore potential mechanistic effects of rapamycin interventions: animal models of AD, specific types of transgenic animal models, dosage, and periodicity of administration. Results: The results of Morris Water Maze (MWM) behavioral test showed that escape latency was shortened by 15.60 seconds with rapamycin therapy, indicating that learning ability was enhanced in AD mice; and the number of traversed platforms was increased by 1.53 times, indicating that the improved memory ability significantly corrected the memory deficits. CONCLUSIONS: Rapamycin therapy reduced age-related plaque deposition by decreasing AßPP production and down-regulating ß-secretase and γ-secretase activities, furthermore increased amyloid-ß clearance by promoting autophagy, as well as reduced tau hyperphosphorylation by up-regulating insulin-degrading enzyme levels.

Nuclear AGO2 promotes myocardial remodeling by activating ANKRD1 transcription in failing hearts.

Heart failure (HF) is manifested by transcriptional and posttranscriptional reprogramming of critical genes. Multiple studies have revealed that microRNAs could translocate into subcellular organelles such as the nucleus to modify gene expression. However, the functional property of subcellular Argonaute2 (AGO2), the core member of the microRNA machinery, has remained elusive in HF. AGO2 was found to be localized in both the cytoplasm and nucleus of cardiomyocytes, and robustly increased in the failing hearts of patients and animal models. We demonstrated that nuclear AGO2 rather than cytosolic AGO2 overexpression by recombinant adeno-associated virus (serotype 9) with cardiomyocyte-specific troponin T promoter exacerbated the cardiac dysfunction in transverse aortic constriction (TAC)-operated mice. Mechanistically, nuclear AGO2 activates the transcription of ANKRD1, encoding ankyrin repeat domain-containing protein 1 (ANKRD1), which also has a dual function in the cytoplasm as part of the I-band of the sarcomere and in the nucleus as a transcriptional cofactor. Overexpression of nuclear ANKRD1 recaptured some key features of cardiac remodeling by inducing pathological MYH7 activation, whereas cytosolic ANKRD1 seemed cardioprotective. For clinical practice, we found ivermectin, an antiparasite drug, and ANPep, an ANKRD1 nuclear location signal mimetic peptide, were able to prevent ANKRD1 nuclear import, resulting in the improvement of cardiac performance in TAC-induced HF.

Relationship Between Urinary Iodine Concentration and the Prevalence of Thyroid Nodules and Subclinical Hypothyroidism.

The aim of the study was to investigate the iodine intake in the resident population in Xi'an and analyze the relationship between iodine nutritional status and the prevalence of subclinical hypothyroidism and thyroid nodules (TNs). A total of 2507 people were enrolled in Xi'an. Venous serum thyroid stimulating hormone (TSH), thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TgAb), urinary iodine concentration (UIC), and thyroid ultrasonography were collected. Patients with abnormal TSH were checked for free thyroxine (FT4) and triiodothyronine (FT3). Adults in Xi'an had median UICs of 220.80 µg/L and 178.56 µg/l, respectively. A sum of 16.78% of people had subclinical hypothyroidism. Both iodine excess and iodine deficit increased the frequency of subclinical hypothyroidism. The lowest was around 15.09% in females with urine iodine levels between 200 and 299 µg/l. With a rate of 10.69%, the lowest prevalence range for males was 100-199 µg/l. In Xi'an, 11.37% of people have TNs. In comparison to other UIC categories, TN occurrences were higher in females (18.5%) and males (12%) when UIC were below 100 µg/l. In conclusion, iodine intake was sufficient in the Xi'an area, while the adults' UIC remains slightly higher than the criteria. Iodine excess or deficiency can lead to an increase in the prevalence of subclinical hypothyroidism. Patients with iodine deficiency are more likely to develop TNs.

Consistency between self-reported disease diagnosis and clinical assessment and under-reporting for chronic conditions: data from a community-based study in Xi'an, China.

Aims: The current study aims to investigate the consistency between the surveyees' self-reported disease diagnosis and clinical assessment of eight major chronic conditions using community-based survey data collected in Xi'an, China in 2017. With a focus on under-reporting patients, we aim to explore its magnitude and associated factors, to provide an important basis for disease surveillance, health assessment and resource allocation, and public health decision-making and services. Methods: Questionnaires were administered to collect self-reported chronic condition prevalence among the study participants, while physical examinations and laboratory tests were conducted for clinical assessment. For each of the eight chronic conditions, the sensitivity, specificity, under-reporting, over-reporting, and agreement were calculated. Log-binomial regression analysis was employed to identify potential factors that may influence the consistency of chronic condition reporting. Results: A total of 2,272 participants were included in the analysis. Four out of the eight chronic conditions displayed under-reporting exceeding 50%. The highest under-reporting was observed for goiter [85.93, 95% confidence interval (CI): 85.25-86.62%], hyperuricemia (83.94, 95% CI: 83.22-84.66%), and thyroid nodules (72.89, 95% CI: 72.02-73.76%). Log-binomial regression analysis indicated that senior age and high BMI were potential factors associated with the under-reporting of chronic condition status in the study population. Conclusion: The self-reported disease diagnosis by respondents and clinical assessment data exhibit significant inconsistency for all eight chronic conditions. Large proportions of patients with multiple chronic conditions were under-reported in Xi'an, China. Combining relevant potential factors, targeted health screenings for high-risk populations might be an effective method for identifying under-reporting patients.

Research on Improved Quantitative Identification Algorithm in Odor Source Searching Based on Gas Sensor Array.

In order to improve the precision of gas detection and develop valid search strategies, the improved quantitative identification algorithm in odor source searching was researched based on the gas sensor array. The gas sensor array was devised corresponding to the artificial olfactory system, and the one-to-one response mode to the measured gas was set up with its inherent cross-sensitive properties. The quantitative identification algorithms were researched, and the improved Back Propagation algorithm was proposed combining cuckoo algorithm and simulated annealing algorithm. The test results prove that using the improved algorithm to obtain the optimal solution -1 at the 424th iteration of the Schaffer function with 0% error. The gas detection system designed with MATLAB was used to obtain the detected gas concentration information, then the concentration change curve may be achieved. The results show that the gas sensor array can detect the concentration of alcohol and methane in the corresponding concentration detection range and show a good detection performance. The test plan was designed, and the test platform in a simulated environment in the laboratory was found. The concentration prediction of experimental data selected randomly was made by the neural network, and the evaluation indices were defined. The search algorithm and strategy were developed, and the experimental verification was carried out. It is testified that the zigzag searching stage with an initial angle of 45° is with fewer steps, faster searching speed, and a more exact position to discover the highest concentration point.

A Kaposi's sarcoma-associated herpes virus-encoded microRNA contributes to dilated cardiomyopathy.

Dilated cardiomyopathy (DCM) is the leading cause of heart transplantation. By microRNA (miRNA) array, a Kaposi's sarcoma-associated herpes virus (KSHV)-encoded miRNA, kshv-miR-K12-1-5p, was detected in patients with DCM. The KSHV DNA load and kshv-miR-K12-1-5p level in plasma from 696 patients with DCM were measured and these patients were followed-up. Increased KSHV seropositivity and quantitative titers were found in the patients with DCM compared with the non-DCM group (22.0% versus 9.1%, p < 0.05; 168 versus 14 copies/mL plasma, p < 0.05). The risk of the individual end point of death from cardiovascular causes or heart transplantation was increased among DCM patients with the KSHV DNA seropositivity during follow-up (adjusted hazard ratio 1.38, 95% confidence interval 1.01-1.90; p < 0.05). In heart tissues, the KSHV DNA load was also increased in the heart from patients with DCM in comparison with healthy donors (1016 versus 29 copies/105 cells, p < 0.05). The KSHV and kshv-miR-K12-1-5p in DCM hearts were detected using immunofluorescence and fluorescence staining in situ hybridization. KSHV itself was exclusively detectable in CD31-positive endothelium, while kshv-miR-K12-1-5p could be detected in both endothelium and cardiomyocytes. Moreover, kshv-miR-K12-1-5p released by KSHV-infected cardiac endothelium could disrupt the type I interferon signaling pathway in cardiomyocytes. Two models of kshv-miR-K12-1-5p overexpression (agomiR and recombinant adeno-associated virus) were used to explore the roles of KSHV-encoded miRNA in vivo. The kshv-miR-K12-1-5p aggravated known cardiotropic viruses-induced cardiac dysfunction and inflammatory infiltration. In conclusion, KSHV infection was a risk factor for DCM, providing developmental insights of DCM involving virus and its miRNA ( https://clinicaltrials.gov . Unique identifier: NCT03461107).

Terahertz Spectroscopy and Imaging Techniques for Herbal Medicinal Plants Detection: A Comprehensive Review.

Herbal medicine (HM), derived from various therapeutic plants, has garnered considerable attention for its remarkable effectiveness in treating diseases. However, numerous issues including improved varieties selection, hazardous residue detection, and concoction management affect herb quality throughout the manufacturing process. Therefore, a practical, rapid, nondestructive detection technology is necessary. Terahertz (THz) spectroscopy, with low energy, penetration, and fingerprint features, becomes preferable method for herb quality appraisal. There are three parts in our review. THz techniques, data processing, and modeling methods were introduced in Part I. Three primary applications (authenticity, composition and active ingredients, and origin detection) of THz in medicinal plants quality detection in industrial processing and marketing were detailed in Part II. A thorough investigation and outlook on the well-known applications and advancements of this field were presented in Part III. This review aims to bring new enlightenment to the in-depth THz application research in herbal medicinal plants.

Recent Understanding and Future Directions in the Application of MMP-2 in Encapsulating Peritoneal Sclerosis Clinical Practice.

Encapsulating peritoneal sclerosis (EPS) is an uncommon and harmful complication which may cause destructive outcomes. Matrix metalloproteinase-2 (MMP-2) as a protease can reduce constituents of the extracellular matrix and play a crucial role in the progression of EPS. As a new biomarker, MMP-2 may improve the detection rate of EPS patients in clinical work. In this review, we summarize the recent study of MMP-2 in different etiologies and the assessment of its application value and draw attention to its future directions.

ADAR1 improved Treg cell function through the miR-21b/Foxp3 axis and inhibits the progression of acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation.

Th17/Treg equilibrium towards the pro-inflammatory Th17 side contributes greatly to the rejection during allogeneic hematopoietic stem cell transplantation (allo-HSCT). Forkhead box P3 (Foxp3) is important in the pathogenic conversion between Th17 and Treg cells. However, how Foxp3 expression was regulated is largely unknown. Here, we investigated the role of RNA-editing enzyme ADAR1 in Foxp3-mediated Th17/Treg imbalance and progression of acute graft-versus-host disease (aGVHD), a most serious complication in patients received allo-HSCT. Th1, Th17 and Treg cells were respectively isolated from peripheral blood CD4 + T cells of allo-HSCT patients, and we found that proportions of Th1 and Th17 were markedly increased, while Treg proportion was significantly decreased in aGVHD patients post transplantation compared with non-aGVHD patients, accompanied by decreased ADAR1 and increased miR-21b levels. RNA-immunoprecipitation (RIP) combined with gain- and loss-of-function experiments demonstrated that ADAR1 improved Treg cell functions and negatively regulated the production of miR-21b, a Foxp3-targeting miRNA. Inhibition of miR-21b improved Treg functions, and Foxp3 knockdown could eliminate the effect of miR-21b inhibition or ADAR1 overexpression on Treg function. Finally, an aGVHD mouse model was established and Ad-O/E-ADAR1 was injected into aGVHD mice to verify the effect of ADAR1 on aGVHD progression in vivo. The results showed that ADAR1 overexpression decreased Th17 proportion and increased Treg proportion in aGVHD mice and obviously improved tissue necrosis and reticular structure of aGVHD liver and lung in vivo. Collectively, ADAR1 suppresses miR-21b production and improves Foxp3-mediated Treg cell function to inhibit the progression of aGVHD after allo-HSCT.

Rapid qualitative detection of titanium dioxide adulteration in persimmon icing using portable Raman spectrometer and Machine learning.

Persimmon icing is the white crystalline powder that adheres to the surface of persimmon cakes when the sugar in the persimmon spills over during processing, which is considered the essence of persimmon. Titanium dioxide is a food additive that is commonly added to the surface of persimmon cakes to impersonate high-quality persimmon cakes. However, excessive titanium dioxide can be harmful to humans, so a quick method is needed to identify persimmon cakes as adulterated. Raman spectroscopy with distinctive advantages of water-insensitivity, real-time, field-deployable, label-free, and fingerprinting-identification has been rapidly developed and used in food quality assurance and safety monitoring. In this study, we investigated Raman spectroscopy integrated with machine learning to assess titanium dioxide adulteration in dried persimmon icing. The adaptive iterative reweighting partial least squares (air-PLS) algorithm as an effective algorithm was used to remove fluorescent background signals in raw Raman spectroscopy. Principal components analysis (PCA) was employed to analyze the spectral data and determine the class memberships, and results showed that 99.9% of information could be explained by PC-1 and PC-2. Compared with extreme learning machine (ELM), support vector machine (SVM), back propagation artificial neural network (BP-ANN), and random forest (RF) models, one-dimensional stack auto encoder convolutional neural network (1D-SAE-CNN) could provide the highest detection accuracy of 0.9825, precision of 0.9824, recall of 0.9825, and f1-score of 0.9824. This study shows that Raman spectroscopy coupled with 1D-SAE-CNN is a promising method to detect titanium dioxide adulteration in persimmon icing.

Fully synthetic phosphorylated Tau181, Tau217, and Tau231 calibrators for Alzheimer's disease diagnosis.

Background: The calibrator in immunoassay plays an essential role in diagnosing Alzheimer's disease (AD). Presently, the most well-studied biomarkers for AD diagnosis are three phosphorylated Tau (p-Tau): p-Tau231, p-Tau217, and p-Tau181. Glycogen synthase-3beta (GSK3ß)-phosphorated Tau-441 is the most commonly used calibrator for p-Tau immunoassays. However, the batch-to-batch inconsistency issue of the commonly used GSK3ß-phosphorylated Tau-441 limits its clinical application. Methods: We have successfully generated and characterized 61 Tau monoclonal antibodies (mAbs) with distinct epitopes by using the hybridoma technique and employed them as capture or detection antibodies for p-Tau immunoassays. Through chemical synthesis, we synthesized calibrators, which are three peptides including capture and detection antibody epitopes, for application in immunoassays that detect p-Tau231, p-Tau217, and p-Tau181. The novel calibrators were applied to Enzyme-linked immunosorbent assay (ELISA) and Single-molecule array (Simoa) platforms to validate their applicability and establish a range of p-Tau immunoassays. Results: By employing the hybridoma technique, 49 mAbs recognizing Tau (1-22), nine mAbs targeting p-Tau231, one mAb targeting p-Tau217, and two mAbs targeting p-Tau181 were developed. Peptides, including recognition epitopes of capture and detection antibodies, were synthesized. These peptides were used as calibrators to develop 60 immunoassays on the ELISA platform, of which six highly sensitive immunoassays were selected and applied to the ultra-sensitive Simoa platform. Remarkably, the LODs were 2.5, 2.4, 31.1, 32.9, 46.9, and 52.1 pg/ml, respectively. Conclusion: Three novel p-Tau calibrators were successfully generated and validated, which solved the batch-to-batch inconsistency issue of GSK3ß-phosphorylated Tau-441. The novel calibrators exhibit the potential to promote the standardization of clinical AD diagnostic calibrators. Furthermore, we established a series of highly sensitive and specific immunoassays on the Simoa platform based on novel calibrators, which moved a steady step forward in p-Tau immunoassay application for AD diagnosis.

KLF9 Aggravates Streptozotocin-Induced Diabetic Cardiomyopathy by Inhibiting PPARγ/NRF2 Signalling.

AIMS: Krüppel-like Factor 9 (KLF9) is a transcription factor that regulates multiple disease processes. Studies have focused on the role of KLF9 in the redox system. In this study, we aimed to explore the effect of KLF9 on diabetic cardiomyopathy. METHODS AND RESULTS: Cardiac-specific overexpression or silencing of KLF9 in C57BL/6 J mice was induced with an adeno-associated virus 9 (AAV9) delivery system. Mice were also subjected to streptozotocin injection to establish a diabetic cardiomyopathy model. In addition, neonatal rat cardiomyocytes were used to assess the possible role of KLF9 in vitro by incubation with KLF9 adenovirus or small interfering RNA against KLF9. To clarify the involvement of peroxisome proliferator-activated receptors (PPARγ), mice were subjected to GW9662 injection to inhibit PPARγ. KLF9 was upregulated in the hearts of mice with diabetic cardiomyopathy and in cardiomyocytes. In addition, KLF9 overexpression in the heart deteriorated cardiac function and aggravated hypertrophic fibrosis, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. Conversely, cardiac-specific silencing of KLF9 ameliorated cardiac dysfunction and alleviated hypertrophy, fibrosis, the cardiac inflammatory response and oxidative stress. In vitro, KLF9 silencing in cardiomyocytes enhanced inflammatory cytokine release and oxidative stress; KLF9 overexpression increased these detrimental responses. Moreover, KLF9 was found to regulate the transcription of PPARγ, which suppressed the expression and nuclear translocation of nuclear Factor E2-related Factor 2 (NRF2). In mice injected with a PPARγ inhibitor, the protective effects of KLF9 knockdown on diabetic cardiomyopathy were counteracted by GW9662 injection. CONCLUSIONS: KLF9 aggravates cardiac dysfunction, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. KLF9 may become a therapeutic target for diabetic cardiomyopathy.

Optical imaging spectroscopy coupled with machine learning for detecting heavy metal of plants: A review.

Heavy metal elements, which inhibit plant development by destroying cell structure and wilting leaves, are easily absorbed by plants and eventually threaten human health via the food chain. Recently, with the increasing precision and refinement of optical instruments, optical imaging spectroscopy has gradually been applied to the detection and reaction of heavy metals in plants due to its in-situ, real-time, and simple operation compared with traditional chemical analysis methods. Moreover, the emergence of machine learning helps improve detection accuracy, making optical imaging spectroscopy comparable to conventional chemical analysis methods in some situations. This review (a): summarizes the progress of advanced optical imaging spectroscopy techniques coupled with artificial neural network algorithms for plant heavy metal detection over ten years from 2012-2022; (b) briefly describes and compares the principles and characteristics of spectroscopy and traditional chemical techniques applied to plants heavy metal detection, and the advantages of artificial neural network techniques including machine learning and deep learning techniques in combination with spectroscopy; (c) proposes the solutions such as coupling with other analytical and detection methods, portability, to address the challenges of unsatisfactory sensitivity of optical imaging spectroscopy and expensive instruments.

Collinear double-pulse laser-induced breakdown spectroscopy based Cd profiling in the soil.

Cadmium (Cd) can migrate in the soil and is readily absorbed by crops. High Cd accumulated in grains poses a huge threat to human health by inhibiting the function of the kidney system. Thus, it is crucial to reveal the content of soil Cd in vertical-depth series using a fast, real-time, and reliable method. For this purpose, laser-induced breakdown spectroscopy (LIBS) combined with multivariate chemometrics was developed to analyze Cd content in the soil with vertical-depth series. Soil samples spiked with different levels of Cd were prepared, and LIBS spectra were obtained by single-pulse LIBS (SP-LIBS) and collinear double-pulse LIBS (CDP-LIBS) with wavelengths of 532 nm and 1064 nm. With appropriate parameters, CDP-LIBS showed better performance in detecting Cd than SP-LIBS. Partial least squares regression (PLSR), genetic algorithm (GA)-optimized back propagation artificial neural network (BP-ANN), and particle swarm optimization (PSO)-optimized least squares-support vector machine (LS-SVM) were tested for quantitative analysis of the spectra after median absolute deviation (MAD), multiple scattering correction (MSC), wavelet transform (WT), spectral averaging, and normalization. PSO-optimized LS-SVM yielded an ideal result, with a coefficient of determination (R2, 0.999) and root mean square error (RMSE, 0.359 mg/Kg) in the prediction dataset. Finally, CDP-LIBS coupled with PSO-optimized LS-SVM was employed to analyze soil Cd content in vertical-depth series to reveal the migration pattern of Cd. Our results indicated that soil Cd had a significant positive relationship with the inverse of soil depth. However, Cd was mainly concentrated in 0-20 cm and rarely leached below 45 cm in the soil. This study suggests that LIBS and its enhancement techniques provide a reliable method for revealing the content of soil Cd in vertical-depth series.