Design and Study of a Two-Dimensional (2D) All-Optical Spatial Mapping Module.

Sequentially timed all-optical mapping photography is one of the main emerging ultra-fast detection technologies that can be widely applicable to ultra-fast detection at the picosecond level in fields such as materials and life sciences. We propose a new optical structure for an all-optical spatial mapping module that can control the optical field of two-dimensional imaging while improving spectral resolution and detector sensor utilization. The model of optical parameters based on geometrical optics theory for the given structure has been established, and the theoretical analysis of the inter-frame energy crosstalk caused by incident beam spot width, chromatic aberration, and main errors of the periscope array has been conducted. The optical design of the two-dimensional (2D) all-optical spatial mapping module was finally completed using ZEMAX OpticStudio 2018 software. The results show that our optical module can realize targets of 16 frames and 1.25 nm spectral resolution.

Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma: Machine learning model based on contrast-enhanced computed tomography.

BACKGROUND: Recently, vessels encapsulating tumor clusters (VETC) was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner, and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma (HCC). AIM: To develop and validate a preoperative nomogram using contrast-enhanced computed tomography (CECT) to predict the presence of VETC+ in HCC. METHODS: We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers. Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase. Radiomics features, essential for identifying VETC+ HCC, were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set. The model's performance was validated on two separate test sets. Receiver operating characteristic (ROC) analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets. The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features. ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features, the radiomics features and the radiomics nomogram. RESULTS: The study included 190 individuals from two independent centers, with the majority being male (81%) and a median age of 57 years (interquartile range: 51-66). The area under the curve (AUC) for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825, 0.788, and 0.680 in the training set and the two test sets. A total of 13 features were selected to construct the Rad-score. The nomogram, combining clinical-radiological and combined radiomics features could accurately predict VETC+ in all three sets, with AUC values of 0.859, 0.848 and 0.757. Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models. CONCLUSION: This study demonstrates the potential utility of a CECT-based radiomics nomogram, incorporating clinical-radiological features and combined radiomics features, in the identification of VETC+ HCC.

Associations between the use of red yeast rice preparations and adverse health outcomes: An umbrella review of meta-analyses of randomized controlled trials.

BACKGROUND: Red yeast rice (RYR), a natural lipid-lowering agent, is widely used in clinical practice. However, the existing meta-analyses concerning the safety of RYR preparations have yielded inconsistent results, and the credibility of the evidence has not been quantified. OBJECTIVE: This study was designed to evaluate the existing evidence and offer a comprehensive understanding of the associations between the use of RYR preparations and various adverse health outcomes. SEARCH STRATEGY: Seven literature databases were searched from inception to May 5, 2023, using medical subject headings and free-text terms (e.g., "red yeast rice," "Xuezhikang," and "Zhibitai"). INCLUSION CRITERIA: Meta-analyses that investigated and quantitatively estimated associations between the use of RYR preparations and adverse health outcomes were included in this study. DATA EXTRACTION AND ANALYSIS: Two researchers independently extracted data using a standardized data collection table; any disagreements were resolved by consulting a third researcher. Based on the participant, intervention, comparator and outcome (PICO) framework in each eligible meta-analysis, a series of unique associations between the use of RYR preparations and adverse health outcomes were determined. The associations' effect estimates were re-evaluated using random-effect models. RESULTS: Fifteen meta-analyses, comprising 186 (164 unique) randomized controlled trials, were identified. Based on A MeaSurement Tool to Assess Systematic Reviews version 2, 3 (20%) and 12 (80%) of these meta-analyses had low and critically low confidence, respectively. A total of 61 unique associations between the use of RYR preparations and adverse health outcomes were extracted from eligible meta-analyses. Based on the random-effect models, 10 (16.4%) associations indicated a significant protective effect of RYR preparations against adverse health outcomes, while 5 (8.2%) indicated an increased risk of adverse health outcomes related to uric acid, alanine transaminase and aspartate transaminase levels. The other 46 (75.4%) associations showed no significant difference between the use of RYR preparations and control treatments. Regarding the credibility of the evidence, 21 (34.4%), 34 (55.7%) and 6 (9.8%) associations showed moderate, low and very low credibility, respectively. CONCLUSION: The evidence examined in this study suggests that RYR preparations are safe; however, the credibility of the evidence was not high. Further high-quality evidence is required. Please cite this article as: Ma ZY, Yang SP, Li Y, Xu TT, Yang YL, Yang HY, Li HB, Zhou LJ, Diao Y, Li SY. Associations between the use of red yeast rice preparations and adverse health outcomes: An umbrella review of meta-analyses of randomized controlled trials. J Integr Med. 2024; 22(2): 126-136.

Upregulation of Wheat Heat Shock Transcription Factor TaHsfC3-4 by ABA Contributes to Drought Tolerance.

Drought stress can seriously affect the yield and quality of wheat (Triticum aestivum). So far, although few wheat heat shock transcription factors (Hsfs) have been found to be involved in the stress response, the biological functions of them, especially the members of the HsfC (heat shock transcription factor C) subclass, remain largely unknown. Here, we identified a class C encoding gene, TaHsfC3-4, based on our previous omics data and analyzed its biological function in transgenic plants. TaHsfC3-4 encodes a protein containing 274 amino acids and shows the basic characteristics of the HsfC class. Gene expression profiles revealed that TaHsfC3-4 was constitutively expressed in many tissues of wheat and was induced during seed maturation. TaHsfC3-4 could be upregulated by PEG and abscisic acid (ABA), suggesting that this Hsf may be involved in the regulation pathway depending on ABA in drought resistance. Further results represented that TaHsfC3-4 was localized in the nucleus but had no transcriptional activation activity. Notably, overexpression of TaHsfC3-4 in Arabidopsis thaliana pyr1pyl1pyl2pyl4 (pyr1pyl124) quadruple mutant plants complemented the ABA-hyposensitive phenotypes of the quadruple mutant including cotyledon greening, root elongation, seedling growth, and increased tolerance to drought, indicating positive roles of TaHsfC3-4 in the ABA signaling pathway and drought tolerance. Furthermore, we identified TaHsfA2-11 as a TaHsfC3-4-interacting protein by yeast two-hybrid (Y2H) screening. The experimental data show that TaHsfC3-4 can indeed interact with TaHsfA2-11 in vitro and in vivo. Moreover, transgenic Arabidopsis TaHsfA2-11 overexpression lines exhibited enhanced drought tolerance, too. In summary, our study confirmed the role of TaHsfC3-4 in response to drought stress and provided a target locus for marker-assisted selection breeding to improve drought tolerance in wheat.

Sympathetic skin response for early detection of type 2 diabetic peripheral neuropathy and nephropathy.

BACKGROUND: Diabetic peripheral neuropathy (DPN) and diabetic nephropathy (DN) are common complications of type 2 diabetes mellitus (T2DM). Although nerve conduction studies (NCS) and sympathetic skin response (SSR) can detect DPN, the more sensitive method for early diagnosis remains unclear. Furthermore, whether DPN can be used as a predictor for diabetic nephropathy needs clarification. METHODS: We evaluated nerve conduction studies, sympathetic skin response, and the diabetic nephropathy indicator microalbuminuria (MAU) in 192 patients with type 2 diabetes mellitus and 50 healthy controls. RESULTS: Patients with type 2 diabetes mellitus showed a lower sensory nerve conduction velocity (SCV), sensory active nerve potential (SNAP), motor nerve conduction velocity (MCV), and compound motor action potential (CMAP) than the controls on NCS. Abnormal rates for nerve conduction studies and sympathetic skin response were 75.0% and 83.3%, respectively, in patients with type 2 diabetes mellitus. Interestingly, 54.2% of patients with normal nerve conduction studies had an abnormal sympathetic skin response. Moreover, we found a positive correlation between sympathetic skin response and microalbuminuria for the first time. The abnormal rate of microalbuminuria was 53.8%, lower than that of abnormal nerve conduction studies or sympathetic skin response patients. CONCLUSION: Sympathetic skin response is a more sensitive method than nerve conduction studies for the early diagnosis of diabetic peripheral neuropathy. Abnormal sympathetic skin response might serve as an indicator for early diabetic nephropathy. Additionally, diabetic peripheral neuropathy may occur earlier than diabetic nephropathy in the development of type 2 diabetes mellitus.

The evolution of indium precipitation in gallium focused ion beam prepared samples of InGaAs/InAlAs quantum wells under electron beam irradiation.

Gallium ion (Ga+ ) beam damage induced indium (In) precipitation in indium gallium arsenide (InGaAs)/indium aluminium arsenide (InAlAs) multiple quantum wells and its corresponding evolution under electron beam irradiation was investigated by valence electron energy loss spectroscopy (VEELS) and high-angle annular dark-field imaging (HAADF) in scanning transmission electron microscopy (STEM). Compared with argon ion milling for sample preparation, the heavier projectiles of Ga+ ions pose a risk to trigger In formation in the form of tiny metallic In clusters. These are shown to be sensitive to electron irradiation and can increase in number and size under the electron beam, deteriorating the structure. Our finding reveals the potential risk of formation of In clusters during focused ion beam (FIB) preparation of InGaAs/InAlAs quantum well samples and their subsequent growth under STEM-HAADF imaging, where initially invisible In clusters of a few atoms can move and swell during electron beam exposure.

Identification and validation of PCSK9 as a prognostic and immune-related influencing factor in tumorigenesis: a pan-cancer analysis.

Introduction: Proprotein convertase subtilisin/kexin-9 (PCSK9) has been primarily studied in the cardiovascular field however, its role in cancer pathophysiology remains incompletely defined. Recently, a pivotal role for PCSK9 in cancer immunotherapy was proposed based on the finding that PCSK9 inhibition was associated with enhancing the antigen presentation efficacy of target programmed cell death-1 (PD-1). Herein, we provide results of a comprehensive pan-cancer analysis of PCSK9 that assessed its prognostic and immunological functions in cancer. Methods: Using a variety of available online cancer-related databases including TIMER, cBioPortal, and GEPIA, we identified the abnormal expression of PCSK9 and its potential clinical associations in diverse cancer types including liver, brain and lung. We also validated its role in progression-free survival (PFS) and immune infiltration in neuroblastoma. Results: Overall, the pan-cancer survival analysis revealed an association between dysregulated PCSK9 and poor clinical outcomes in various cancer types. Specifically, PCSK9 was extensively genetically altered across most cancer types and was consistently found in different tumor types and substages when compared with adjacent normal tissues. Thus, aberrant DNA methylation may be responsible for PCSK9 expression in many cancer types. Focusing on liver hepatocellular carcinoma (LIHC), we found that PCSK9 expression correlated with clinicopathological characteristics following stratified prognostic analyses. PCSK9 expression was significantly associated with immune infiltrate since specific markers of CD8+ T cells, macrophage polarization, and exhausted T cells exhibited different PCSK9-related immune infiltration patterns in LIHC and lung squamous cell carcinoma. In addition, PCSK9 was connected with resistance of drugs such as erlotinib and docetaxel. Finally, we validated PCSK9 expression in clinical neuroblastoma samples and concluded that PCSK9 appeared to correlate with a poor PFS and natural killer cell infiltration in neuroblastoma patients. Conclusion: PCSK9 could serve as a robust prognostic pan-cancer biomarker given its correlation with immune infiltrates in different cancer types, thus potentially highlighting a new direction for targeted clinical therapy of cancers.

Protein-protein interactions and related inhibitors involved in the NLRP3 inflammasome pathway.

NOD-like receptor thermal protein domain-associated protein 3 (NLRP3) receptor serves as the central node of immune sensing in the innate immune system, and plays an important role in the initiation and progression of chronic diseases. Cryo-electron microscopy (cryo-EM) has provided insights into the conformation of various oligomers within the NLRP3 activation pathway, significantly advancing our understanding of the mechanisms underlying NLRP3 inflammasome activation. Despite the extensive network of protein-protein interactions (PPIs) involved in the assembly and activation of NLRP3 inflammasome, the utilization of protein-protein interactions has been relatively overlooked in the development of NLRP3 inhibitors. This review focuses on summarizing PPIs within the NLRP3 inflammasome activation pathway and small molecule inhibitors capable of interfering with PPIs to counteract the NLRP3 overactivation. Small molecule NLRP3 inhibitors have been gained significant attention owing to their remarkable efficacy, excellent safety profiles, and unique mechanisms of action.

Development and validation of prediction models for the prognosis of colon cancer with lung metastases: a population-based cohort study.

Background: Current studies on the establishment of prognostic models for colon cancer with lung metastasis (CCLM) were lacking. This study aimed to construct and validate prediction models of overall survival (OS) and cancer-specific survival (CSS) probability in CCLM patients. Method: Data on 1,284 patients with CCLM were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were randomly assigned with 7:3 (stratified by survival time) to a development set and a validation set on the basis of computer-calculated random numbers. After screening the predictors by the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, the suitable predictors were entered into Cox proportional hazard models to build prediction models. Calibration curves, concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA) were used to perform the validation of models. Based on model-predicted risk scores, patients were divided into low-risk and high-risk groups. The Kaplan-Meier (K-M) plots and log-rank test were applied to perform survival analysis between the two groups. Results: Building upon the LASSO and multivariate Cox regression, six variables were significantly associated with OS and CSS (i.e., tumor grade, AJCC T stage, AJCC N stage, chemotherapy, CEA, liver metastasis). In development, validation, and expanded testing sets, AUCs and C-indexes of the OS and CSS prediction models were all greater than or near 0.7, which indicated excellent predictability of models. On the whole, the calibration curves coincided with the diagonal in two models. DCA indicated that the models had higher clinical benefit than any single risk factor. Survival analysis results showed that the prognosis was worse in the high-risk group than in the low-risk group, which suggested that the models had significant discrimination for patients with different prognoses. Conclusion: After verification, our prediction models of CCLM are reliable and can predict the OS and CSS of CCLM patients in the next 1, 3, and 5 years, providing valuable guidance for clinical prognosis estimation and individualized administration of patients with CCLM.

Combination of Chinese herbal medicine and conventional western medicine for coronavirus disease 2019: a systematic review and meta-analysis.

Objective: This study aimed to assess the efficacy and safety of Chinese herbal medicine (CHM) plus conventional western medicine (CWM) in comparison with CWM against COVID-19. Methods: We searched eight electronic databases and three trial registers spanning from January 1, 2020 to May 18, 2023. We included randomized controlled trials (RCTs) comparing the effectiveness and safety of CHM plus CWM and CWM against COVID-19 in our study. The Cochrane Risk of Bias tool 2.0 (RoB2) was applied to evaluate the methodological quality of the included RCTs. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system was employed to assess the certainty of evidence. Statistical analysis was implemented in R version 4.1.2. Results: Our study included 50 RCTs involving 11,624 patients. In comparison with sole CWM, CHM plus CWM against COVID-19 significantly enhanced clinical effective rate (RR = 1.18, 95% CI [1.13, 1.22]), improved chest image (RR = 1.19, 95% CI [1.11, 1.28]), inhibited clinical deterioration (RR = 0.45, 95% CI [0.33, 0.60]), lowered mortality (RR = 0.53, 95% CI [0.40, 0.70]), and reduced the total score of TCM syndrome (SMD = -1.24, 95% CI [-1.82, -0.66]). SARS-CoV-2 nucleic acid conversion time (MD = -2.66, 95% CI [-3.88, -1.44]), duration of hospitalization (MD = -2.36, 95% CI [-3.89, -0.82]), and clinical symptom (fever, cough, fatigue, and shortness of breath) recovery times were shorter in CHM plus CWM groups than in CWM groups. Further, CHM plus CWM treatment was more conducive for some laboratory indicators returning to normal levels. No statistical difference was found in the incidence of total adverse reactions between the two groups (RR = 0.97, 95% CI [0.88, 1.07]). We assessed the risk of bias for 246 outcomes, and categorized 55 into "low risk", 151 into "some concerns", and 40 into "high risk". Overall, the certainty of the evidence ranged from moderate to very low. Conclusions: Potentially, CHM listed in this study, as an adjunctive therapy, combining with CWM is an effective and safe therapy mode for COVID-19. However, more high-quality RCTs are needed to draw more accurate conclusions. Clinical trial registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=293963.

Molecular dynamics simulations identify the topological weak spots of a protease CN2S8A.

Thermophilic enzymes are highly desired in industrial applications due to their efficient catalytic activity at high temperature. However, most enzymes exhibit inferior thermostability and it remains challenging to identify the optimal sites for designing mutations to improve protein stability. To tackle this issue, we integrated topological analysis and all-atom molecular dynamics simulations to efficiently pinpoint the thermally-unstable regions in protein structures. Using a protease CN2S8A as the model, we analyzed the intramolecular hydrogen bonding interactions between adjacent secondary structure elements, and then identified the topological weak spots of CN2S8A where weak hydrogen bonding interactions were formed. To examine the role of these sites in protein structural stability, we designed three virtual mutations at different weak spots and characterized the effects of these mutations on the structural properties of CN2S8A. The results showed that all three mutations increased the protein structural stability. In conclusion, these findings provide a novel method to identify the topological weak spots of proteins, with implications in the rational design of biocatalysts with superior thermostability.

Efficient Discrete Clustering With Anchor Graph.

Spectral clustering (SC) has been applied to analyze varieties of data structures over the past few decades owing to its outstanding breakthrough in graph learning. However, the time-consuming eigenvalue decomposition (EVD) and information loss during relaxation and discretization impact the efficiency and accuracy especially for large-scale data. To address above issues, this brief proposes a simple and fast method named efficient discrete clustering with anchor graph (EDCAG) to circumvent postprocessing by binary label optimization. First of all, sparse anchors are adopted to accelerate graph construction and obtain a parameter-free anchor similarity matrix. Subsequently, inspired by intraclass similarity maximization in SC, we design an intraclass similarity maximization model between anchor-sample layer to cope with anchor graph cut problem and exploit more explicit data structures. Meanwhile, a fast coordinate rising (CR) algorithm is employed to alternatively optimize discrete labels of samples and anchors in designed model. Experimental results show excellent rapidity and competitive clustering effect of EDCAG.

Fast Sparse Discriminative K-Means for Unsupervised Feature Selection.

Embedded feature selection approach guides subsequent projection matrix (selection matrix) learning through the acquisition of pseudolabel matrix to conduct feature selection tasks. Yet the continuous pseudolabel matrix learned from relaxed problem based on spectral analysis deviates from reality to some extent. To cope with this issue, we design an efficient feature selection framework inspired by classical least-squares regression (LSR) and discriminative K-means (DisK-means), which is called the fast sparse discriminative K-means (FSDK) for the feature selection method. First, the weighted pseudolabel matrix with discrete trait is introduced to avoid trivial solution from unsupervised LSR. On this condition, any constraint imposed into pseudolabel matrix and selection matrix is dispensable, which is significantly beneficial to simplify the combinational optimization problem. Second, the l2,p -norm regularizer is introduced to satisfy the row sparsity of selection matrix with flexible p . Consequently, the proposed FSDK model can be treated as a novel feature selection framework integrated from the DisK-means algorithm and l2,p -norm regularizer to optimize the sparse regression problem. Moreover, our model is linearly correlated with the number of samples, which is speedy to handle the large-scale data. Comprehensive tests on various data terminally illuminate the effectiveness and efficiency of FSDK.

Pseudohalogen Resurfaced CsPbBr3 Nanocrystals for Bright, Efficient, and Stable Green-Light-Emitting Diodes.

Lead halide perovskite nanocrystals (LHP NCs) are regarded as promising emitters for next-generation ultrahigh-definition displays due to their high color purity and wide color gamut. Recently, the external quantum efficiency (EQE) of LHP NC based light-emitting diodes (PNC LEDs) has been rapidly improved to a level required by practical applications. However, the poor operational stability of the device, caused by halide ion migration at the grain boundary of LHP NC thin films, remains a great challenge. Herein, we report a resurfacing strategy via pseudohalogen ions to mitigate detrimental halide ion migration, aiming to stabilize PNC LEDs. We employ a thiocyanate solution processed post-treatment method to efficiently resurface CsPbBr3 NCs and demonstrate that the thiocyanate ions can effectively inhibit bromide ion migration in LHP NC thin films. Owing to thiocyanate resurfacing, we fabricated LEDs with a high EQE of 17.3%, a maximum brightness of 48000 cd m-2, and an excellent operation half-life time.

Time-Series Transcriptome Analysis Reveals the Molecular Mechanism of Ethylene Reducing Cold Sensitivity of Postharvest 'Huangguan' Pear.

'Huangguan' pear (Pyrus bretschneideri Rehd) fruit is susceptible to cold, characterized by developing peel browning spots (PBS) during cold storage. Additionally, ethylene pretreatment reduces chilling injury (CI) and inhibits PBS occurrence, but the mechanism of CI remains unclear. Here, we deciphered the dynamic transcriptional changes during the PBS occurrence with and without ethylene pretreatment via time-series transcriptome. We found that ethylene suppressed the cold-signaling gene expression, thereby decreasing the cold sensitivity of the 'Huangguan' fruit. Moreover, the "Yellow" module closely correlated with PBS occurrence was identified via weighted gene co-expression network analysis (WGCNA), and this module was related to plant defense via Gene Ontology (GO) enrichment analysis. Local motif enrichment analysis suggested that the "Yellow" module genes were regulated by ERF and WRKY transcription factors. Functional studies demonstrated that PbWRKY31 has a conserved WRKY domain, lacks transactivation activity, and localizes in the nucleus. PbWRKY31-overexpressed Arabidopsis were hypersensitive to cold, with higher expression levels of cold signaling and defense genes, suggesting that PbWRKY31 participates in regulating plant cold sensitivity. Collectively, our findings provide a comprehensive transcriptional overview of PBS occurrence and elucidate the molecular mechanism by which ethylene reduces the cold sensitivity of 'Huangguan' fruit as well as the potential role of PbWRKY31 in this process.

Alternative Splicing of TaHsfA2-7 Is Involved in the Improvement of Thermotolerance in Wheat.

High temperature has severely affected plant growth and development, resulting in reduced production of crops worldwide, especially wheat. Alternative splicing (AS), a crucial post-transcriptional regulatory mechanism, is involved in the growth and development of eukaryotes and the adaptation to environmental changes. Previous transcriptome data suggested that heat shock transcription factor (Hsf) TaHsfA2-7 may form different transcripts by AS. However, it remains unclear whether this post-transcriptional regulatory mechanism of TaHsfA2-7 is related to thermotolerance in wheat (Triticum aestivum). Here, we identified a novel splice variant, TaHsfA2-7-AS, which was induced by high temperature and played a positive role in thermotolerance regulation in wheat. Moreover, TaHsfA2-7-AS is predicted to encode a small truncated TaHsfA2-7 isoform, retaining only part of the DNA-binding domain (DBD). TaHsfA2-7-AS is constitutively expressed in various tissues of wheat. Notably, the expression level of TaHsfA2-7-AS is significantly up-regulated by heat shock (HS) during flowering and grain-filling stages in wheat. Further studies showed that TaHsfA2-7-AS was localized in the nucleus but lacked transcriptional activation activity. Ectopic expression of TaHsfA2-7-AS in yeast exhibited improved thermotolerance. Compared to non-transgenic plants, overexpression of TaHsfA2-7-AS in Arabidopsis results in enhanced tolerance to heat stress. Simultaneously, we also found that TaHsfA1 is directly involved in the transcriptional regulation of TaHsfA2-7 and TaHsfA2-7-AS. In summary, our findings demonstrate the function of TaHsfA2-7-AS splicing variant in response to heat stress and establish a link between regulatory mechanisms of AS and the improvement of thermotolerance in wheat.

Compact fiber sensor for pH measurement based on the composite effect of hydrogel deformation and LC refractive index variation.

A novel, to the best of our knowledge, type of compact pH fiber sensor combined with a hydrogel based on the whispering gallery mode (WGM) is proposed and integrates a liquid crystal (LC) microdroplet in a capillary in a compact structure as small as 180 µm. In the research, the hydrogel performs both as a supporting frame and a responsive material that causes morphological deformation of the LC microdroplet with pH variation. Moreover, a new phenomenon of pH-induced LC refractive index variation is observed and applied in the pH measurement, so that the acid itself can also lead the LC microdroplet structure transition. Thus, the WGM method is applied to detect the composite effect simultaneously to improve the sensing capability. The sensitivity of the sensor in the pH range from 4.55 to 6.86 reaches 3.19 nm/pH. The response time is short, within 60 s. The simple and compact structure of the sensor reduces the cost and enhances the stability, which is of great potential for biomedical pH measurement.

Pest-YOLO: A model for large-scale multi-class dense and tiny pest detection and counting.

Frequent outbreaks of agricultural pests can reduce crop production severely and restrict agricultural production. Therefore, automatic monitoring and precise recognition of crop pests have a high practical value in the process of agricultural planting. In recent years, pest recognition and detection have been rapidly improved with the development of deep learning-based methods. Although certain progress has been made in the research on pest detection and identification technology based on deep learning, there are still many problems in the production application in a field environment. This work presents a pest detector for multi-category dense and tiny pests named the Pest-YOLO. First, the idea of focal loss is introduced into the loss function using weight distribution to improve the attention of hard samples. In this way, the problems of hard samples arose from the uneven distribution of pest populations in a dataset and low discrimination features of small pests are relieved. Next, a non-Intersection over Union bounding box selection and suppression algorithm, the confluence strategy, is used. The confluence strategy can eliminate the errors and omissions of pest detection caused by occlusion, adhesion and unlabeling among tiny dense pest individuals to the greatest extent. The proposed Pest-YOLO model is verified on a large-scale pest image dataset, the Pest24, which includes more than 20k images with over 190k pests labeled by agricultural experts and categorized into 24 classes. Experimental results show that the Pest-YOLO can obtain 69.59% for mAP and 77.71% for mRecall on the 24-class pest dataset, which is 5.32% and 28.12% higher than the benchmark model YOLOv4. Meanwhile, our proposed model is superior to other several state-of-the-art methods, including the SSD, RetinaNet, Faster RCNN, YOLOv3, YOLOv4, YOLOv5s, YOLOv5m, YOLOX, DETR, TOOD, YOLOv3-W, and AF-RCNN detectors. The code of the proposed algorithm is available at: https://github.com/chr-secrect/Pest-YOLO.

Hierarchical and nested associations of suicide with marriage, social support, quality of life, and depression among the elderly in rural China: Machine learning of psychological autopsy data.

Objectives: To identify mechanisms underpinning the complex relationships between influential factors and suicide risk with psychological autopsy data and machine learning method. Design: A case-control study with suicide deaths selected using two-stage stratified cluster sampling method; and 1:1 age-and-gender matched live controls in the same geographic area. Setting: Disproportionately high risk of suicide among rural elderly in China. Participants: A total of 242 subjects died from suicide and 242 matched live controls, 60 years of age and older. Measurements: Suicide death was determined based on the ICD-10 codes. Influential factors were measured using validated instruments and commonly accepted variables. Results: Of the total sample, 270 (55.8%) were male with mean age = 74.2 (SD = 8.2) years old. Four CART models were used to select influential factors using the criteria: areas under the curve (AUC) ≥ 0.8, sensitivity ≥ 0.8, and specificity ≥ 0.8. Each model included a lead predictor plus 8-10 hierarchically nested factors. Depression was the first to be selected in Model 1 as the lead predictor; After depression was excluded, quality of life (QOL) was selected in Model 2; After depression and QOL were excluded, social support was selected in Model 3. Finally, after all 3 lead factors were excluded, marital status was selected in Model 4. In addition, CART demonstrated the significance of several influential factors that would not be associated with suicide if the data were analyzed using the conventional logistic regression. Conclusion: Associations between the key factors and suicide death for Chinese rural elderly are not linear and parallel but hierarchically nested that could not be effectively detected using conventional statistical methods. Findings of this study provide new and compelling evidence supporting tailored suicide prevention interventions at the familial, clinical and community levels.

Suicide among young-old and old-old adults in rural China: A case-control psychological autopsy study.

OBJECTIVE: Late-life suicide is a vital public health concern. Though gerontological research suggested the young-old and old-old phases were heterogeneous, age differences in the elderly suicide have not been well studied due to the lack of comparable control groups and small samples. The study aimed to examine the age-specific suicidal characteristics and risk factors among the young-old (60-79) and old-old (over 80) elderly. METHODS: Two hundred and forty two suicide decedents and 242 living comparisons were enrolled in a 1:1 matched case-control psychological autopsy study in rural China: 173 young-old and 69 old-old in each group. Suicidal characteristics, demographic characteristics, living arrangements, physical health, mental disorder, and psychosocial factors were collected. We used logistic regression models to assess risk factors of suicide and test for interactions between age and each risk factor. RESULTS: Pesticide suicide was more prevalent among young-old suicides than old-old suicides (56.07% vs. 40.58%, p = 0.029). Non-currently married, unemployment, mental disorder, higher disability in physical activities of daily living, higher hopelessness and higher depressive symptom were significantly associated with suicide among older adults. The effect of poor function in physical activities of daily living on suicide was significantly greater during younger ages (p for interaction = 0.038). CONCLUSIONS: Findings indicated that most suicidal characteristics and risk factors for completed suicide were generally similar among young-old and old-old adults. But poor function in physical activities of daily living predicted increase suicide risk only at younger ages. In addition to common risk factors, age-specific factors should also be noted in suicide prevention. CLINICAL TRIAL REGISTRATION: According to the ICMJE, purely observational studies (those in which the assignment of the medical intervention is not at the discretion of the investigator) will not require registration. Our study was not registered because this is a case-control study. But all procedures of the study were carried out in accordance with the latest version of the Declaration of Helsinki. The study were approved by the Institutional Review Boards of the Central South University, Shandong University, and Guangxi Medical University.