Individual Structural Covariance Network Predicts Long-Term Motor Improvement in Parkinson's Disease with STN-DBS.

BACKGROUND AND PURPOSE: The efficacy of long-term chronic subthalamic nucleus deep brain stimulation (STN-DBS) in treating Parkinson's Disease (PD) exhibits substantial variability among individuals. The preoperative identification of suitable DBS candidates through predictive means becomes crucial. Our study aims to investigate the predictive value of characterizing individualized structural covariance networks for long-term efficacy of DBS, offering patients a precise and cost-effective preoperative screening tool. MATERIALS AND METHODS: We included 138 PD patients and 40 healthy controls. We developed individualized structural covariance networks from T1-weighted images utilizing Network Template Perturbation, and computed the networks' topological characteristics. Patients were categorized according to their long-term motor improvement following STN-DBS. Intergroup analyses were conducted on individual network edges and topological indices, alongside correlation analyses with long-term outcomes for the entire patient cohort. Finally, machine learning (ML) algorithms were employed for regression and classification to predict post-DBS motor improvement. RESULTS: Among the PD patients, six edges (left Middle Frontal and left Caudate Nucleus, right Olfactory and right Insula, left Superior Medial Frontal Gyrus and right Insula, right Middle Frontal and left Paracentral Lobule, right Middle Frontal and Cerebellum, left Lobule VIIb of the Cerebellum and the vermis of the Cerebellum) exhibited significant results in intergroup comparisons and correlation analyses. Increased degree centrality and local efficiency of the cerebellum, parahippocampal gyrus, and postcentral gyrus were associated with DBS improvement. A regression model constructed from these six edges revealed a significant correlation between predicted and observed changes in the unified Parkinson's disease rating scale (R=0.671, P<0.001), and receiver operating characteristic analysis demonstrated an area under the curve of 0.802, effectively distinguishing between patients with good and moderate improvement post-DBS. CONCLUSIONS: Our findings reveal the link between individual structural covariance network fingerprints in PD patients and long-term motor outcome following STN-DBS. Additionally, binary and continuous cerebellum-basal ganglia-frontal structural covariance network edges have emerged as potential predictive biomarkers for DBS motor outcome. ABBREVIATIONS: subthalamic nucleus deep brain stimulation = STN-DBS; Parkinson's Disease = PD; machine learning = ML); Network Template Perturbation = NTP.

Intricate synergistic effects between air pollution and carbon emission: An emerging evidence from China.

Due to global climate change and intensifying anthropogenic pollution, China confronts the dual challenge of controlling particulate matter 2.5 µm (PM2.5) pollution and reducing carbon emissions. Quantifying the characteristics of PM2.5 concentrations and CO2 emissions, as well as identifying the driving factors and synergistic effects of PM2.5 reduction and CO2 mitigation, are crucial steps in promoting sustainable urban development and achieving the Sustainable Development Goals (SDGs) in China. In this study, we selected 168 cities as our case-study, and quantified spatial characteristics of PM2.5 concentrations and CO2 emissions from 2015 to 2020 in China. Then we analyzed driving factors affecting the spatial heterogeneity of PM2.5 reduction and CO2 mitigation applying Multi-scale Geographically Weighted Regression (MGWR) model. By employing coupling coordination degree (CCD) model, we further detected the spatiotemporal evolution patterns of the synergistic effects between PM2.5 reduction and CO2 mitigation in key Chinese cities. The result showed that: (a) From 2015 to 2020, PM2.5 concentrations experienced a significant reduction from 59.78 µg/m3 to 49.83 µg/m3, while CO2 emissions increased from 44.88 × 106 t in 2015 to 45.77 × 106 t in 2020; (b) Green economy efficiency (gee), government attention (gover), and environmental regulation (envir) demonstrate the most pronounced synergistic effect on pollution reduction and carbon mitigation, with the drivers exhibiting obvious spatial heterogeneity; (c) The overall coupling coordination level of PM2.5 pollution and CO2 emissions in China dropped from 0.49 in 2015 to 0.46 in 2020, and the coupling coordination grade in northern cities was notably higher than that in southern cities. The result enhances our understanding of spatiotemporal patterns of synergistic effects between PM2.5 reduction and CO2 mitigation, and provides the theoretical basis for policy decision-making to realize pollution decrease and carbon neutral and regional environment governance.

Association between Ambient Volatile Organic Compounds Exposome and Emergency Hospital Admissions for Cardiovascular Disease.

The limited research on volatile organic compounds (VOCs) has not taken into account the interactions between constituents. We used the weighted quantile sum (WQS) model and generalized linear model (GLM) to quantify the joint effects of ambient VOCs exposome and identify the substances that play key roles. For a 0 day lag, a quartile increase of WQS index for n-alkanes, iso/anti-alkanes, aromatic, halogenated aromatic hydrocarbons, halogenated saturated chain hydrocarbons, and halogenated unsaturated chain hydrocarbons were associated with 1.09% (95% CI: 0.13, 2.06%), 0.98% (95% CI: 0.22, 1.74%), 0.92% (95% CI: 0.14, 1.69%), 1.03% (95% CI: 0.14, 1.93%), 1.69% (95% CI: 0.48, 2.91%), and 1.85% (95% CI: 0.93, 2.79%) increase in cardiovascular disease (CVD) emergency hospital admissions, respectively. Independent effects of key substances on CVD-related emergency hospital admissions were also reported. In particular, an interquartile range increase in 1,1,1-trichloroethane, methylene chloride, styrene, and methylcyclohexane is associated with a greater risk of CVD-associated emergency hospital admissions [3.30% (95% CI: 1.93, 4.69%), 3.84% (95% CI: 1.21, 6.53%), 5.62% (95% CI: 1.35, 10.06%), 8.68% (95% CI: 3.74, 13.86%), respectively]. We found that even if ambient VOCs are present at a considerably low concentration, they can cause cardiovascular damage. This should prompt governments to establish and improve concentration standards for VOCs and their sources. At the same time, policies should be introduced to limit VOCs emission to protect public health.

Earthquake supercycles and fault interaction over the past 32 ka in the Lake Ebinur area, Xinjiang, China.

Earthquake prediction and disaster assessment in tectonically active regions require a continuous and complete regional seismic archive, which is commonly difficult to obtain, especially for prehistoric records. Here, high-resolution analysis of the sedimentary sequence from Lake Ebinur in Xinjiang revealed a detailed history of environment evolution since 32 ka ago. Both the Cl content and ultrafine proportion revealed the changing climate: the climate was relatively dry with low lake-water volumes from 32 to 12 ka, while the climate became warmer and wetter since 12 ka. In addition, eight earthquakes were identified by comprehensive analysis of grain size and geochemical element proxies, showing more than two seismic supercycles, with gaps of ∼10.4 ka; these gaps are much larger than those inferred previously (∼4-7 ka). Notably, these seismic events exhibited a pattern of mutual transmittance between the BoA and Jinghenan faults. Such fault interaction can occur in the Lake Ebinur area because it is dominated by weak lithosphere in which strain is easily accumulated and released; the interaction can also be attributed to the unique spatial distribution and immature nature of both faults. Combined with trenching investigations, our high-resolution analysis of lacustrine sediments can reveal a complete history of tectonic activity, which can efficiently serve regional earthquake prediction and disaster assessment.

Efficacy and safety of combined deep brain stimulation with capsulotomy for comorbid motor and psychiatric symptoms in Tourette's syndrome: Experience and evidence.

OBJECTIVES: To evaluate the efficacy and safety of combined deep brain stimulation (DBS) with capsulotomy for comorbid motor and psychiatric symptoms in patients with Tourette's syndrome (TS). METHODS: This retrospective cohort study consecutively enrolled TS patients with comorbid motor and psychiatric symptoms who were treated with combined DBS and anterior capsulotomy at our center. Longitudinal motor, psychiatric, and cognitive outcomes and quality of life were assessed. In addition, a systematic review and meta-analysis were performed to summarize the current experience with the available evidence. RESULTS: In total, 5 eligible patients in our cohort and 26 summarized patients in 6 cohorts were included. After a mean 18-month follow-up, our cohort reported that motor symptoms significantly improved by 62.4 % (P = 0.005); psychiatric symptoms of obsessive-compulsive disorder (OCD) and anxiety significantly improved by 87.7 % (P < 0.001) and 78.4 % (P = 0.009); quality of life significantly improved by 61.9 % (P = 0.011); and no significant difference was found in cognitive function (all P > 0.05). Combined surgery resulted in greater improvements in psychiatric outcomes and quality of life than DBS alone. The synthesized findings suggested significant improvements in tics (MD: 57.92, 95 % CI: 41.28-74.56, P < 0.001), OCD (MD: 21.91, 95 % CI: 18.67-25.15, P < 0.001), depression (MD: 18.32, 95 % CI: 13.26-23.38, P < 0.001), anxiety (MD: 13.83, 95 % CI: 11.90-15.76, P < 0.001), and quality of life (MD: 48.22, 95 % CI: 43.68-52.77, P < 0.001). Individual analysis revealed that the pooled treatment effects on motor symptoms, psychiatric symptoms, and quality of life were 78.6 %, 84.5-87.9 %, and 83.0 %, respectively. The overall pooled rate of adverse events was 50.0 %, and all of these adverse events were resolved or alleviated with favorable outcomes. CONCLUSIONS: Combined DBS with capsulotomy is effective for relieving motor and psychiatric symptoms in TS patients, and its safety is acceptable. However, the optimal candidate should be considered, and additional experience is still necessary.

Quantitative Assessment of Hemodynamics Associated With Embolization Degree in Brain Arteriovenous Malformations.

BACKGROUND AND OBJECTIVES: Grading systems, including the novel brain arteriovenous malformation endovascular grading scale (NBAVMES) and arteriovenous malformation embocure score (AVMES), predict embolization outcomes based on arteriovenous malformation (AVM) morphological features. The influence of hemodynamics on embolization outcomes remains unexplored. In this study, we investigated the relationship between hemodynamics and embolization outcomes. METHODS: We conducted a retrospective study of 99 consecutive patients who underwent transarterial embolization at our institution between 2012 and 2018. Hemodynamic features of AVMs were derived from pre-embolization digital subtraction angiography sequences using quantitative digital subtraction angiography. Multivariate logistic regression analysis was performed to determine the significant factors associated with embolization outcomes. RESULTS: Complete embolization (CE) was achieved in 17 (17.2%) patients, and near-complete embolization was achieved in 18 (18.2%) patients. A slower transnidal relative velocity (TRV, odds ratio [OR] = 0.71, P = .002) was significantly associated with CE. Moreover, higher stasis index of the drainage vein (OR = 16.53, P = .023), shorter transnidal time (OR = 0.15, P = .013), and slower TRV (OR = 0.9, P = .049) were significantly associated with complete or near-complete embolization (C/nCE). The area under the receiver operating characteristic curve for predicting CE was 0.87 for TRV, 0.72 for NBAVMES scores (ρ = 0.287, P = .004), and 0.76 for AVMES scores. The area under the receiver operating characteristic curve for predicting C/nCE was 0.77 for TRV, 0.61 for NBAVMES scores, and 0.75 for AVMES scores. Significant Spearman correlation was observed between TRV and NBAVMES scores and AVMES scores (ρ = 0.512, P < .001). CONCLUSION: Preoperative hemodynamic factors have the potential to predict the outcomes of AVM embolization. A higher stasis index of the drainage vein, slower TRV, and shorter transnidal time may indicate a moderate blood flow status or favorable AVM characteristics that can potentially facilitate embolization.

Correlation of T2DM and Anthropometric Measures with Total Small Bowel Length and Its Effects on Diabetes Remission After Bariatric Surgery.

BACKGROUND: The outcome of weight loss surgery is related to several factors, and for super-obese patients, the rate of weight loss failure and weight recovery after Roux-en-Y gastric bypass (RYGB) is high. Relevant studies have shown that the weight loss effect also correlates with total small bowel length (TSBL) and biliopancreatic (BP) and Roux limbs. However, there are few studies on the relationship between TSBL and anthropometric parameters, the BP limb, the Roux limb, and weight loss effect, and no relevant reports have been reported in China. OBJECTIVES: The objective was to study the relationship between the total length of the small intestine and anthropometric parameters in the Chinese population. The effect of the Roux limb/biliopancreatic limb (RL/BPL) ratio on weight loss and diabetes remission in RYGB patients 1 year after surgery was evaluated to find the appropriate ratio relationship. METHODS: In this prospective study, 148 patients between the ages of 19 and 68 years who underwent laparoscopic Roux-en-Y gastric bypass were enrolled. Height, weight, BMI, the BP limb, the Roux limb, fasting blood glucose (FBG), etc., were noted. To explore the correlation between the total length of the small intestine and these values. Subsequently, the 148 patients were followed up for 1 year after surgery. The patients diagnosed with T2DM before surgery were screened out, and 56 patients were finally identified according to the postoperative follow-up, in which BPL = 50 cm and RL = 150 cm, 175 cm, and 200 cm, respectively. RL/BPL was divided into 3, 3.5, and 4 groups according to the proportional relationship to explore the relationship between RL/BPL and diabetes remission and weight loss. RESULTS: (1) The study included 148 patients (61 women and 87 men). The mean age was 35.68 ± 10.46 years, weight = 127.46 ± 34.51 kg, height = 167.83 ± 9.16 cm, BMI = 44.94 ± 10.58 kg/m2. The average TSBL value was 714.41 ± 101.08 cm. Linear regression analysis showed that TSBL was positively correlated with height, weight, neck circumference, chest circumference, waist circumference, and Roux limb. (2) Fifty-six patients with T2DM who were followed up 1 year after surgery were divided into three groups. Group 1: BPL = 50 cm, RL = 150 cm (n = 20); group 2: BPL = 50 cm, RL = 175 cm (n = 26); group 3: BPL = 50 cm, RL = 200 cm (n = 10); RL/BPL = 3 was associated with higher weight loss than the other groups. The remission rate of diabetes did not differ between the three groups. CONCLUSIONS: TSBL was positively correlated with height, weight, neck circumference, chest circumference, waist circumference, and Roux limb. The TSBL of males was significantly higher than that of females. Among patients with T2DM who participated in the follow-up 1 year after surgery, RL/BPL = 3 (n = 20) had greater weight loss than the other groups.

Argatroban in Patients With Acute Ischemic Stroke With Early Neurological Deterioration: A Randomized Clinical Trial.

Importance: The effect of argatroban in patients with acute ischemic stroke (AIS) and early neurological deterioration (END) is unknown. Objective: To assess the efficacy of argatroban for END in AIS. Design, Setting, and Participants: This open-label, blinded-end point, randomized clinical trial was conducted from April 4, 2020, through July 31, 2022. The date of final follow-up was October 31, 2022. This was a multicenter trial. Eligible patients were adults with AIS who experienced END, which was defined as an increase of 2 or more points on the National Institutes of Health Stroke Scale within 48 hours from symptom onset. Patients who withdrew consent, experienced duplicate randomization, or were lost to follow-up were excluded from the study. Interventions: Patients were randomly assigned to the argatroban group and control group within 48 hours of symptom onset. Both groups received standard therapy based on guidelines, including oral mono or dual antiplatelet therapy. The argatroban group received intravenous argatroban for 7 days (continuous infusion at a dose of 60 mg per day for 2 days, followed by 20 mg per day for 5 days) in addition to standard therapy. Main Outcome and Measure: The primary end point was good functional outcome at 90 days, defined as a modified Rankin Scale score of 0 to 3. Results: A total of 628 patients (mean [SD] age, 65 [11.9] years; 400 male [63.7%]) were included in this study (argatroban group, 314 [50%] and control group, 314 [50%]). Of these, 18 withdrew consent, 1 had duplicate randomization, and 8 were lost to follow-up. A total of 601 patients with stroke were included in the intention-to-treat analysis. Finally, 564 patients were included in the per-protocol analysis as 6 participants in the argatroban group and 31 participants in the control group did not follow the complete protocol. The number of patients with good functional outcome at 90 days was 240 (80.5%) in the argatroban group and 222 (73.3%) in the control group (risk difference, 7.2%; 95% CI, 0.6%-14.0%; risk ratio, 1.10; 95% CI, 1.01-1.20; P = .04). The proportion of symptomatic intracranial hemorrhage was 3 of 317 (0.9%) in the argatroban group and 2 of 272 (0.7%) in the control group (P = .78). Conclusions and Relevance: Among patients with AIS with END, treatment with argatroban and antiplatelet therapy resulted in a better functional outcome at 90 days. This trial provided evidence to support the use of argatroban in reducing disability for patients with END. Trial Registration: ClinicalTrials.gov Identifier: NCT04275180.

Diagnosis of intracranial aneurysms by computed tomography angiography using deep learning-based detection and segmentation.

BACKGROUND: Detecting and segmenting intracranial aneurysms (IAs) from angiographic images is a laborious task. OBJECTIVE: To evaluates a novel deep-learning algorithm, named vessel attention (VA)-Unet, for the efficient detection and segmentation of IAs. METHODS: This retrospective study was conducted using head CT angiography (CTA) examinations depicting IAs from two hospitals in China between 2010 and 2021. Training included cases with subarachnoid hemorrhage (SAH) and arterial stenosis, common accompanying vascular abnormalities. Testing was performed in cohorts with reference-standard digital subtraction angiography (cohort 1), with SAH (cohort 2), acquired outside the time interval of training data (cohort 3), and an external dataset (cohort 4). The algorithm's performance was evaluated using sensitivity, recall, false positives per case (FPs/case), and Dice coefficient, with manual segmentation as the reference standard. RESULTS: The study included 3190 CTA scans with 4124 IAs. Sensitivity, recall, and FPs/case for detection of IAs were, respectively, 98.58%, 96.17%, and 2.08 in cohort 1; 95.00%, 88.8%, and 3.62 in cohort 2; 96.00%, 93.77%, and 2.60 in cohort 3; and, 96.17%, 94.05%, and 3.60 in external cohort 4. The segmentation accuracy, as measured by the Dice coefficient, was 0.78, 0.71, 0.71, and 0.66 for cohorts 1-4, respectively. VA-Unet detection recall and FPs/case and segmentation accuracy were affected by several clinical factors, including aneurysm size, bifurcation aneurysms, and the presence of arterial stenosis and SAH. CONCLUSIONS: VA-Unet accurately detected and segmented IAs in head CTA comparably to expert interpretation. The proposed algorithm has significant potential to assist radiologists in efficiently detecting and segmenting IAs from CTA images.

EB1C forms dimer and interacts with protein phosphatase 2A (PP2A) to regulate fiber elongation in upland cotton (Gossypium hirsutum).

Cotton is the most economically important natural fiber crop grown in more than sixty-five countries of the world. Fiber length is the main factor affecting fiber quality, but the existing main varieties are short in length and cannot suit the higher demands of the textile industry. It is necessary to discover functional genes that enable fiber length improvement in cotton through molecular breeding. In this study, overexpression of GhEB1C in Arabidopsis thaliana significantly promotes trichomes, tap roots, and root hairs elongation. The molecular regulation of GhEB1C involves its interactions with itself and GhB'ETA, and the function of GhEB1C regulation mainly depends on the two cysteine residues located at the C-terminal. In particular, the function activity of GhEB1C protein triggered with the regulation of protein phosphatase 2A, while silencing of GhEB1C in cotton significantly influenced the fiber protrusions and elongation mechanisms., Further, influenced the expression of MYB-bHLH-WD40 complex, brassinosteroids, and jasmonic acid-related genes, which showed that transcriptional regulation of GhEB1C is indispensable for cotton fiber formation and elongation processes. Our study analyzed the brief molecular mechanism of GhEB1C regulation. Further elucidated that GhEB1C can be a potential target gene to improve cotton fiber length through transgenic breeding.

Plastic additive components of PM2.5 increase corrected QT interval: Screening for exposure markers based on airborne exposome.

The impact of industrial chemical components of ambient fine particles (e.g. PM2.5) on cardiovascular health has been poorly explored. Our study reports for the first time the associations between human exposure to complex plastic additive (PA) components of PM2.5 and prolongation of heart rate-corrected QT (QTC) interval by employing a screening-to-validation strategy based on a cohort of 373 participants (136 in the screening set and 237 in the validation set) recruited from 7 communities across China. The high-throughput airborne exposome framework revealed ubiquitous occurrences of 95 of 224 target PAs in PM2.5, totaling from 66.3 to 555 ng m-3 across the study locations. Joint effects were identified for 9 of the 13 groups of PAs with positive associations with QTC interval. Independent effect analysis also identified and validated tris(2-chloroisopropyl) phosphate, di-n-butyl/diisobutyl adipate, and 3,5-di-tert-butyl-4-hydroxybenzaldehyde as the key exposure markers for QTC interval prolongation and changes of selected cardiovascular biomarkers. Our findings highlight the important contributions of airborne industrial chemicals to the risks of cardiovascular diseases and underline the critical need for further research on the underlying mechanisms, toxic modes of action, and human exposure risks.

Particulate Air Pollution and Blood Pressure: Signaling by the Arachidonate Metabolism.

BACKGROUND: Short-term exposure to ambient particulate matter (PM) can raise blood pressure, but the underlying mechanisms are unclear. We explored whether arachidonate metabolites serve as biological intermediates in PM-associated prohypertensive changes. METHODS: This panel study recruited 110 adults aged 50 to 65 years living in Beijing, China. The participants' blood pressure, arterial stiffness, and cardiac and endothelial function were measured up to 7 times. The serum concentrations of arachidonate metabolites were quantified by targeted lipidomics. Ambient concentrations of fine PM (PM2.5), black carbon, and accumulation mode particles were continuously monitored at a station and their associations with the health indicators were evaluated. RESULTS: Interquartile range increases in 25 to 96-hour-lag exposure to PM2.5, black carbon, and accumulation mode particles were associated with significant increases in systolic blood pressure (brachial: 0.8-3.2 mm Hg; central: 0.7-2.8 mm Hg) and diastolic blood pressure (brachial, 0.5-1.5 mm Hg; central, 0.5-1.6 mm Hg). At least 1 pollutant was associated with increases in augmentation pressure and heart rate and decreases in reactive hyperemia index and ejection time. The serum concentrations of arachidonate were significantly increased by 3.3% to 14.6% in association with PM exposure, which mediated 9% of the PM-associated increases in blood pressure. The levels of eicosanoids from the cytochrome P450, cyclooxygenase, and lipoxygenase pathways changed with PM exposure, and those from the cytochrome pathway significantly mediated the association between PM exposure and blood pressure. CONCLUSIONS: Short-term exposure to particulate air pollution was associated with a prohypertensive change in adults, which was in part mediated by alteration of arachidonate metabolism.

A Deep Quality Monitoring Network for Quality-Related Incipient Faults.

Although quality-related process monitoring has achieved the great progress, scarce works consider the detection of quality-related incipient faults. Partial least square (PLS) and its variants only focus on faults with larger magnitudes. In this article, a deep quality monitoring network (DQMNet) for quality-related incipient fault detection is developed. DQMNet includes the feature input layer, feature extraction layers, and the output layer. In the feature input layer, collected variables are divided according to quality variables, and then, features are extracted, respectively, through base detectors. For the feature extraction layers, singular values (SVs) of sliding-window patches and principal component analysis (PCA) are adopted to mine the hidden information layer by layer. For the output layer, statistics are constructed from quality-related/unrelated feature matrix through Bayesian inference. The superiority of DQMNet is demonstrated by a numerical simulation and the benchmark data of Tennessee Eastman process (TEP).

Novel Mechanisms Underlying Rubber Accumulation and Programmed Cell Death in Laticiferous Canals of Decaisnea insignis Fruits: Cytological and Transcriptomic Analyses.

Natural rubber is one of the most important industrial raw materials, and its biosynthesis is still a fascinating process that is still largely unknown. In this research, we studied Decaisnea insignis, a unique rubber-producing plant that is different from other rubber-producing species due to the presence of lactiferous canals in its pericarp. The present study aims to provide novel insights into the mechanisms underlying rubber accumulation and PCD by subjecting the Decaisnea insignis laticiferous canals to light microscopy, TUNEL assay, and DAPI staining, as well as viability analysis, cellular ultrastructure analysis, and molecular analysis using light microscopy, scanning electron microscopy, immunofluorescence labeling, transmission electron microscopy, and transcriptome sequencing. At the cellular level, the origin of small rubber particles in the laticiferous canals had no morphological correlation with other organelles, and these particles were freely produced in the cytosol. The volume of the rubber particles increased at the sunken and expanding stage, which were identified as having the characteristics of programmed cell death (PCD); meanwhile, plenty of the rubber precursors or rubber particles were engulfed by the vacuoles, indicating a vacuole-mediated autophagy process. The accumulation of rubber particles occurred after the degeneration of protoplasts, suggesting a close association between rubber biosynthesis and PCD. The molecular analysis revealed the expression patterns of key genes involved in rubber biosynthesis. The upstream genes DiIPP, DiFPP, and DiGGPPS showed a decreasing trend during fruit ripening, while DiHRT, which is responsible for rubber particle extension, exhibited the highest expression level during the rubber particle formation. Moreover, the transcription factors related to PCD, DiLSD1, and DiLOL2 showed a negative correlation with the expression pattern of DiHRT, thus exhibiting strict rules of sequential expression during rubber biosynthesis. Additionally, the expression trends of DiXCP1 and DiCEP1, which act as proteases during PCD, were positively correlated with DiGGPPS expression. In conclusion, the findings suggest that the autophagic PCD may play a crucial role in rubber accumulation in D. insignis. Further research is still needed to fully understand the complex regulatory network underlying rubber biosynthesis in plants.

Acute myocardial infarction due to coronary embolism caused by a metastatic mass from lung cancer.

BACKGROUND: Acute arterial embolism due to tumor embolus is a rare complication in cancer patients, even rarer is lung tumor embolization leading to acute myocardial infarction. We report a patient who had a diagnosis of acute myocardial infarction(AMI)which was brought on by a coronary artery embolism by a metastatic lung cancer tumor. Clinicians need to be aware that tumor embolism can result in AMI. CASE PRESENTATION: An 80-yeal-old male patient presented with persistent chest pain for 2 h and his electrocardiogram(ECG)showed anterior ST-segment elevation myocardial infarction. Instead of implanting a stent, thrombus aspiration was performed. Pathological examination of coronary artery thrombosis showed that a few sporadic atypical epithelial cells were scattered in the thrombus-like tissue. Combined with immune phenotype and clinical history, metastatic squamous cell carcinoma is more likely. CONCLUSIONS: We report a rare case of a patient who was diagnosed of AMI due to a coronary artery embolism by a metastatic mass from lung cancer. Since there is no evidence-based protocol available for the treatment of isolated coronary thrombosis, we used thrombus aspiration to treat thrombosis rather than implanting a stent.

GhSTP18, a member of sugar transport proteins family, negatively regulates salt stress in cotton.

The sugar transporter protein (STP) family has been shown to play important roles in plant growth, development, and stress response. However, it has not been studied in cotton compared to other major crops. In this study, we identified 90 STP genes from four cotton species, performed bioinformatic analysis, and focused on the role of GhSTP18 in salt stress. According to our results, cotton STP proteins were divided into four subgroups according to the phylogenetic tree. A synteny analysis suggested that whole-genome duplication (WGD) and segmental duplication were key drivers in the expansion of the STP gene family. The transcriptomic data analysis showed that 29 GhSTP genes exhibited sink-specific expression. Quantitative real time-polymerase chain reaction (qRT-PCR) analyses revealed that expression of GhSTP18 was induced by salt treatment, heat treatment, cold treatment, and drought treatment, and continuously increased during a salt stress time course. Notably, GhSTP18 encodes a plasma membrane-localized galactose transporter. Suppression of GhSTP18 transcription by a virus-induced gene silencing (VIGS) assay reduced sensitivity to salt stress in cotton, indicating that GhSTP18 negatively regulates plant salt tolerance. These results provide an important reference and resource for further studying and deploying STP genes for cotton improvement.

Quantification of Pork, Chicken, Beef, and Sheep Contents in Meat Products Using Duplex Real-Time PCR.

Accurate methods for meat speciation and quantification are essential for ensuring the supply of safe and wholesome meat and composite products with animal origins to negate the potential associated hazards, aid classification of consignments at the import control system, and thwart food fraud committed for financial gain. To better enhance meat safety control and combat food fraud, this study developed two duplex real-time polymerase chain reaction (real-time PCR) systems specifically designed for chicken, pork, sheep, and beef, using single-copy, chromosomally encoded, species-specific gene sequences to accurately measure the content of each meat type in meat products. DNA extracted from the raw and boiled reference materials prepared in varying proportions (ranging from 1% to 75%) were used in the development of the duplex assay to derive calibration factors to determine the meat content in different meat products. The method was further validated using proficiency test samples and market monitoring samples. Our findings showed that this method exhibits high specificity and sensitivity, with a significant accuracy range of 0.14% to 24.07% in quantifying the four meat types in both raw and processed meat products. Validation results further confirmed the effectiveness of our method in accurately quantifying meat content. Thus, we have demonstrated the duplex qPCR assays as promising approaches for implementation in routine analysis to strengthen meat safety control systems and combat meat fraud, thereby safeguarding consumer health and trust in the meat industry.

Research on the data validity of a coal mine solid backfill working face sensing system based on an improved transformer.

Solid backfilling in coal mining refers to filling the goaf with solid materials to form a support structure, ensuring safety in the ground and upper mining areas. This mining method maximizes coal production and addresses environmental requirements. However, in traditional backfill mining, challenges exist, such as limited perception variables, independent sensing devices, insufficient sensing data, and data isolation. These issues hinder the real-time monitoring of backfilling operations and limit intelligent process development. This paper proposes a perception network framework specifically designed for key data in solid backfilling operations to address these challenges. Specifically, it analyses critical perception objects in the backfilling process and proposes a perception network and functional framework for the coal mine backfilling Internet of Things (IoT). These frameworks facilitate rapidly concentrating key perception data into a unified data centre. Subsequently, the paper investigates the assurance of data validity in the perception system of the solid backfilling operation within this framework. Specifically, it considers potential data anomalies that may arise from the rapid data concentration in the perception network. To mitigate this issue, a transformer-based anomaly detection model is proposed, which filters out data that does not reflect the true state of perception objects in solid backfilling operations. Finally, experimental design and validation are conducted. The experimental results demonstrate that the proposed anomaly detection model achieves an accuracy of 90%, indicating its effective detection capability. Moreover, the model exhibits good generalization ability, making it suitable for monitoring data validity in scenarios involving increased perception objects in solid backfilling perception systems.