Effects of empagliflozin on progression of chronic kidney disease: a prespecified secondary analysis from the empa-kidney trial

BACKGROUND

Sodium-glucose co-transporter-2 (SGLT2) inhibitors reduce progression of chronic kidney disease and the risk of cardiovascular morbidity and mortality in a wide range of patients. However, their effects on kidney disease progression in some patients with chronic kidney disease are unclear because few clinical kidney outcomes occurred among such patients in the completed trials. In particular, some guidelines stratify their level of recommendation about who should be treated with SGLT2 inhibitors based on diabetes status and albuminuria. We aimed to assess the effects of empagliflozin on progression of chronic kidney disease both overall and among specific types of participants in the EMPA-KIDNEY trial.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA), and included individuals aged 18 years or older with an estimated glomerular filtration rate (eGFR) of 20 to less than 45 mL/min per 1·73 m2, or with an eGFR of 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher. We explored the effects of 10 mg oral empagliflozin once daily versus placebo on the annualised rate of change in estimated glomerular filtration rate (eGFR slope), a tertiary outcome. We studied the acute slope (from randomisation to 2 months) and chronic slope (from 2 months onwards) separately, using shared parameter models to estimate the latter. Analyses were done in all randomly assigned participants by intention to treat. EMPA-KIDNEY is registered at ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and then followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroups of eGFR included 2282 (34·5%) participants with an eGFR of less than 30 mL/min per 1·73 m2, 2928 (44·3%) with an eGFR of 30 to less than 45 mL/min per 1·73 m2, and 1399 (21·2%) with an eGFR 45 mL/min per 1·73 m2 or higher. Prespecified subgroups of uACR included 1328 (20·1%) with a uACR of less than 30 mg/g, 1864 (28·2%) with a uACR of 30 to 300 mg/g, and 3417 (51·7%) with a uACR of more than 300 mg/g. Overall, allocation to empagliflozin caused an acute 2·12 mL/min per 1·73 m2 (95% CI 1·83-2·41) reduction in eGFR, equivalent to a 6% (5-6) dip in the first 2 months. After this, it halved the chronic slope from -2·75 to -1·37 mL/min per 1·73 m2 per year (relative difference 50%, 95% CI 42-58). The absolute and relative benefits of empagliflozin on the magnitude of the chronic slope varied significantly depending on diabetes status and baseline levels of eGFR and uACR. In particular, the absolute difference in chronic slopes was lower in patients with lower baseline uACR, but because this group progressed more slowly than those with higher uACR, this translated to a larger relative difference in chronic slopes in this group (86% [36-136] reduction in the chronic slope among those with baseline uACR <30 mg/g compared with a 29% [19-38] reduction for those with baseline uACR ≥2000 mg/g; ptrend<0·0001).

INTERPRETATION

Empagliflozin slowed the rate of progression of chronic kidney disease among all types of participant in the EMPA-KIDNEY trial, including those with little albuminuria. Albuminuria alone should not be used to determine whether to treat with an SGLT2 inhibitor.

FUNDING

Boehringer Ingelheim and Eli Lilly.

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

BACKGROUND

The EMPA-KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population.

METHODS

EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110.

FINDINGS

Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5-2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62-0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16-1·59), representing a 50% (42-58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1).

INTERPRETATION

In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease.

FUNDING

Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council.

Prevalence and influencing factors of depressive and anxiety symptoms among hospital-based healthcare workers during the surge period of the COVID-19 pandemic in the Chinese mainland: a multicenter cross-sectional study

BACKGROUND

From November 2022 to February 2023, the Chinese mainland experienced a surge in COVID-19 infection and hospitalization, and the hospital-based healthcare workers (HCWs) might suffer serious psychological crisis during this period. This study aims to assess the depressive and anxiety symptoms among HCWs during the surge of COVID-19 pandemic and to provide possible reference on protecting mental health of HCWs in future infectious disease outbreaks.

METHODS

A multicenter cross-sectional study was carried out among hospital-based HCWs in the Chinese mainland from 5 January to 9 February 2023. The PHQ-9 (nine-item Patient Health Questionnaire) and GAD-7 (seven-item Generalized Anxiety Disorder Questionnaire) were used to measure depressive and anxiety symptoms. Ordinal logistic regression analysis was performed to identify influencing factors.

RESULTS

A total of 6522 hospital-based HCWs in the Chinse mainland were included in this survey. The prevalence of depressive symptoms among the HCWs was 70.75%, and anxiety symptoms was 47.87%. The HCWs who perceived higher risk of COVID-19 infection and those who had higher work intensity were more likely to experience depressive and anxiety symptoms. Additionally, higher levels of mindfulness, resilience and perceived social support were negatively associated with depressive and anxiety symptoms.

CONCLUSION

This study revealed that a high proportion of HCWs in the Chinese mainland suffered from mental health disturbances during the surge of the COVID-19 pandemic. Resilience, mindfulness and perceived social support are important protective factors of HCWs' mental health. Tailored interventions, such as mindfulness practice, should be implemented to alleviate psychological symptoms of HCWs during the COVID-19 pandemic or other similar events in the future.

Interactive Dairy Goat Image Segmentation for Precision Livestock Farming

Semantic segmentation and instance segmentation based on deep learning play a significant role in intelligent dairy goat farming. However, these algorithms require a large amount of pixel-level dairy goat image annotations for model training. At present, users mainly use Labelme for pixel-level annotation of images, which makes it quite inefficient and time-consuming to obtain a high-quality annotation result. To reduce the annotation workload of dairy goat images, we propose a novel interactive segmentation model called UA-MHFF-DeepLabv3+, which employs layer-by-layer multi-head feature fusion (MHFF) and upsampling attention (UA) to improve the segmentation accuracy of the DeepLabv3+ on object boundaries and small objects. Experimental results show that our proposed model achieved state-of-the-art segmentation accuracy on the validation set of DGImgs compared with four previous state-of-the-art interactive segmentation models, and obtained 1.87 and 4.11 on mNoC@85 and mNoC@90, which are significantly lower than the best performance of the previous models of 3 and 5. Furthermore, to promote the implementation of our proposed algorithm, we design and develop a dairy goat image-annotation system named DGAnnotation for pixel-level annotation of dairy goat images. After the test, we found that it just takes 7.12 s to annotate a dairy goat instance with our developed DGAnnotation, which is five times faster than Labelme.

[Application effects of 3D visualization reconstruction technique in pheochromocytoma/ paraganglioma surgery]

To investigate the value of 3D visualization reconstruction technology in pheochromocytoma/paraganglioma surgery.The clinical data of 87 patients with pheochromocytoma/paraganglioma admitted to the Department of Urology of Peking Union Medical College Hospital between January 2019 and December 2022 were retrospectively analyzed, and 3D visualization model reconstruction was performed preoperatively in 47 patients [Group A:males was 24 cases,the age M(Q1, Q3)42.00(30.00, 54.00)]. while the remaining 40 patients [Group B: males was 23 cases,the age M(Q1, Q3) 44.00(30.25, 53.75)] was not. The maximum tumor diameter, operation time, intraoperative bleeding, drain retention time and postoperative hospital stay were compared between the two groups. Surgery was successfully completed in both groups. 37 (78.7%) patients in group A underwent laparoscopic surgery, 7 (14.9%) patients underwent open surgery, and 3 (6.4%) patients underwent laparoscopic-to-open surgery. Thirty-one (77.5%) patients in group B underwent laparoscopic surgery, 5 (12.5%) patients underwent open surgery, and 4 (10.0%) patients underwent laparoscopic to open surgery. There was a difference in the maximum diameter of the tumor between the two groups [(6.09±3.02) cm vs (5.32±1.76) cm, P<0.05], the retention time of the drainage tube was significantly shorter in group A compared with group B [(3.20±1.38) d vs (4.02±1.98) d, P<0.05], and the length of the hospital stay after surgery was significantly shorter [(5.75±2.12) d vs (6.49±3.37) d, P<0.05]. Comparison of operation time and intraoperative bleeding between the two groups showed no statistically significant difference (P>0.05).Two cases of postoperative anemia and one case of pulmonary atelectasis in group B patients improved before discharge. Conclusion when the tumor diameter is>6 cm or has a close relationship with the surrounding organs and blood vessels, the use of 3D visual reconstruction technology can formulate and implement a more accurate and safe surgical plan, shorten the retention time of the drainage tube and postoperative hospitalization time, which is conducive to the patient's postoperative recovery and reduce postoperative complications.

Clinical efficacy of modified percutaneous kyphoplasty (PKP) vs. conventional PKP for osteoporotic vertebral compression fractures: a single-center retrospective study

OBJECTIVE

To investigate the clinical efficacy of using a standardized modified percutaneous kyphoplasty (transverse process‑pedicle approach to percutaneous kyphoplasty, TPKP) approach for the treatment of osteoporotic vertebral compression fractures (OVCFs) and to explore the possibility that it may become the preferred option in the future.

PATIENTS AND METHODS

A retrospective analysis was conducted on a total of 81 patients (TPKP group, 43 cases; PKP group, 38 cases) with OVCFs who underwent TPKP and PKP at the Department of Spine Surgery, Wuhan Fourth Hospital, from May 2021 to October 2021. We evaluated the patients' demographic information, intraoperative data (volume of cement injection and, duration of surgery), clinical outcomes at different time points (Visual Analog Scale, Oswestry Dysfunction Index), and radiographic data (Cobb angle, anterior vertebral body height). Statistical analysis was performed to assess the efficacy of the procedure, both within and between the two groups before and after surgery.

RESULTS

The difference in preoperative general information between the two groups of patients was non-statistically significant (p>0.05), and they were comparable. Additionally, no statistically significant difference (p>0.05) was found between the TPKP and PKP groups in terms of operative time, length of hospital stay, recovery of injured spine height, Cobb angle, and cement leakage rate. However, significant statistical differences (p<0.05) were noted between the two groups regarding cement volume, distribution pattern, 1-day postoperative VAS scores, 1-day postoperative ODI scores, and loss of height of the injured spine. TPKP demonstrated superior performance compared to PKP in these specific areas.

CONCLUSIONS

TPKP offers the same surgical safety as the conventional approach, with better cement distribution and better pain relief, as well as the advantage of maintaining the height of the operated vertebral body. The technique is easy to master and use when guided by standard puncture procedures.

Cattle Target Segmentation Method in Multi-Scenes Using Improved DeepLabV3+ Method

Obtaining animal regions and the relative position relationship of animals in the scene is conducive to further studying animal habits, which is of great significance for smart animal farming. However, the complex breeding environment still makes detection difficult. To address the problems of poor target segmentation effects and the weak generalization ability of existing semantic segmentation models in complex scenes, a semantic segmentation model based on an improved DeepLabV3+ network (Imp-DeepLabV3+) was proposed. Firstly, the backbone network of the DeepLabV3+ model was replaced by MobileNetV2 to enhance the feature extraction capability of the model. Then, the layer-by-layer feature fusion method was adopted in the Decoder stage to integrate high-level semantic feature information with low-level high-resolution feature information at multi-scale to achieve more precise up-sampling operation. Finally, the SENet module was further introduced into the network to enhance information interaction after feature fusion and improve the segmentation precision of the model under complex datasets. The experimental results demonstrate that the Imp-DeepLabV3+ model achieved a high pixel accuracy (PA) of 99.4%, a mean pixel accuracy (MPA) of 98.1%, and a mean intersection over union (MIoU) of 96.8%. Compared to the original DeepLabV3+ model, the segmentation performance of the improved model significantly improved. Moreover, the overall segmentation performance of the Imp-DeepLabV3+ model surpassed that of other commonly used semantic segmentation models, such as Fully Convolutional Networks (FCNs), Lite Reduced Atrous Spatial Pyramid Pooling (LR-ASPP), and U-Net. Therefore, this study can be applied to the field of scene segmentation and is conducive to further analyzing individual information and promoting the development of intelligent animal farming.

A Method for Obtaining 3D Point Cloud Data by Combining 2D Image Segmentation and Depth Information of Pigs

This paper proposes a method for automatic pig detection and segmentation using RGB-D data for precision livestock farming. The proposed method combines the enhanced YOLOv5s model with the Res2Net bottleneck structure, resulting in improved fine-grained feature extraction and ultimately enhancing the precision of pig detection and segmentation in 2D images. Additionally, the method facilitates the acquisition of 3D point cloud data of pigs in a simpler and more efficient way by using the pig mask obtained in 2D detection and segmentation and combining it with depth information. To evaluate the effectiveness of the proposed method, two datasets were constructed. The first dataset consists of 5400 images captured in various pig pens under diverse lighting conditions, while the second dataset was obtained from the UK. The experimental results demonstrated that the improved YOLOv5s_Res2Net achieved a mAP@0.5:0.95 of 89.6% and 84.8% for both pig detection and segmentation tasks on our dataset, while achieving a mAP@0.5:0.95 of 93.4% and 89.4% on the Edinburgh pig behaviour dataset. This approach provides valuable insights for improving pig management, conducting welfare assessments, and estimating weight accurately.

[Current use of oral anticoagulation therapy and influencing factors among coronary artery disease patients with nonvalvular atrial fibrillation in China]

Objective: To investigate current use of oral anticoagulant (OAC) therapy and influencing factors among coronary artery disease (CAD) patients with nonvalvular atrial fibrillation (NVAF) in China. Methods: Results of this study derived from "China Atrial Fibrillation Registry Study", the study prospectively enrolled atrial fibrillation (AF) patients from 31 hospitals, and patients with valvular AF or treated with catheter ablation were excluded. Baseline data such as age, sex and type of atrial fibrillation were collected, and drug history, history of concomitant diseases, laboratory results and echocardiography results were recorded. CHA₂DS₂-VASc score and HAS-BLED score were calculated. The patients were followed up at the 3rd and 6th months after enrollment and every 6 months thereafter. Patients were divided according to whether they had coronary artery disease and whether they took OAC. Results: 11 067 NVAF patients fulfilling guideline criteria for OAC treatment were included in this study, including 1 837 patients with CAD. 95.4% of NVAF patients with CAD had CHA₂DS₂-VASc score≥2, and 59.7% of patients had HAS-BLED≥3, which was significantly higher than NVAF patients without CAD (P<0.001). Only 34.6% of NVAF patients with CAD were treated with OAC at enrollment. The proportion of HAS-BLED≥3 in the OAC group was significantly lower than in the no-OAC group (36.7% vs. 71.8%, P<0.001). After adjustment with multivariable logistic regression analysis, thromboembolism(OR=2.48,95%CI 1.50-4.10,P<0.001), left atrial diameter≥40 mm(OR=1.89,95%CI 1.23-2.91,P=0.004), stain use (OR=1.83,95%CI 1.01-3.03, P=0.020) and β blocker use (OR=1.74,95%CI 1.13-2.68,P=0.012)were influence factors of OAC treatment. However, the influence factors of no-OAC use were female(OR=0.54,95%CI 0.34-0.86,P=0.001), HAS-BLED≥3 (OR=0.33,95%CI 0.19-0.57,P<0.001), and antiplatelet drug(OR=0.04,95%CI 0.03-0.07,P<0.001). Conclusion: The rate of OAC treatment in NVAF patients with CAD is still low and needs to be further improved. The training and assessment of medical personnel should be strengthened to improve the utilization rate of OAC in these patients.

Frame vibration states identification for corn harvester based on joint improved empirical mode decomposition - Support vector machine method

The frame of corn harvester is prone to vibration bending and torsional deformation due to the vibration caused by field road bumps and fluctuations. It poses a serious challenge to the reliability of machinery. Therefore it is critical to explore the vibration mechanism, and to identify the vibration states under different working conditions. To address the above problem, a vibration state identification method is proposed in this paper. An improved empirical mode decomposition (EMD) algorithm was used to decrease noise for signals of high noise and non-stationary vibration in the field. The support vector machine (SVM) model was used for identification of frame vibration states under different working conditions. The results showed that: (1) an improved EMD algorithm could effectively reduce noise interference and restore the effective information of the original signal. (2) based on improved EMD - SVM method identify the vibration states of the frame with the accuracy of 99.21%. (3) The corn ears in grain tank were not sensitive to low order vibration, but had an absorption effect on high order vibration. The proposed method has the potential to be applied for accurately identifying vibration state and improving frame safety.

[Changes in percentage of GATA3+ regulatory T cells and their pathogenic roles in allergic rhinitis]

OBJECTIVE

To investigate the changes in percentage of GATA3⁺ regulatory T (Treg) cells in patients with allergic rhinitis (AR) and mouse models.

METHODS

The nasal mucosa specimens were obtained from 6 AR patients and 6 control patients for detection of nasal mucosal inflammation. Peripheral blood mononuclear cells (PBMC) were collected from 12 AP patients and 12 control patients to determine the percentages of Treg cells and GATA3⁺ Treg cells. In a C57BL/6 mouse model of AR, the AR symptom score, peripheral blood OVA-sIgE level, and nasal mucosal inflammation were assessed, and the spleen of mice was collected for detecting the percentages of Treg cells and GATA3⁺ Treg cells and the expressions of Th2 cytokines.

RESULTS

Compared with the control patients, AR patients showed significantly increased eosinophil infiltration and goblet cell proliferation in the nasal mucosa (P < 0.01) and decreased percentages of Treg cells and GATA3⁺ Treg cells (P < 0.05). The mouse models of AR also had more obvious allergic symptoms, significantly increased OVA-sIgE level in peripheral blood, eosinophil infiltration and goblet cell hyperplasia (P < 0.01), markedly lowered percentages of Treg cells and GATA3⁺ Treg cells in the spleen (P < 0.01), and increased expressions of IL-4, IL-6 and IL-10 (P < 0.05).

CONCLUSION

The percentage of GATA3⁺ Treg cells is decreased in AR patients and mouse models. GATA3⁺ Treg cells possibly participate in Th2 cell immune response, both of which are involved in the occurrence and progression of AR, suggesting the potential of GATA3⁺ Treg cells as a new therapeutic target for AR.

Maize disease detection based on spectral recovery from RGB images

Maize is susceptible to infect pest disease, and early disease detection is key to preventing the reduction of maize yields. The raw data used for plant disease detection are commonly RGB images and hyperspectral images (HSI). RGB images can be acquired rapidly and low-costly, but the detection accuracy is not satisfactory. On the contrary, using HSIs tends to obtain higher detection accuracy, but HSIs are difficult and high-cost to obtain in field. To overcome this contradiction, we have proposed the maize spectral recovery disease detection framework which includes two parts: the maize spectral recovery network based on the advanced hyperspectral recovery convolutional neural network (HSCNN+) and the maize disease detection network based on the convolutional neural network (CNN). Taking raw RGB data as input of the framework, the output reconstructed HSIs are used as input of disease detection network to achieve disease detection task. As a result, the detection accuracy obtained by using the low-cost raw RGB data almost as same as that obtained by using HSIs directly. The HSCNN+ is found to be fit to our spectral recovery model and the reconstruction fidelity was satisfactory. Experimental results demonstrate that the reconstructed HSIs efficiently improve detection accuracy compared with raw RGB image in tested scenarios, especially in complex environment scenario, for which the detection accuracy increases by 6.14%. The proposed framework has the advantages of fast, low cost and high detection precision. Moreover, the framework offers the possibility of real-time and precise field disease detection and can be applied in agricultural robots.

Survey of the American Society of Neuroradiology Membership on the Use and Value of Extracranial Carotid Vessel Wall MRI

BACKGROUND AND PURPOSE

Extracranial vessel wall MRI (EC-VWI) contributes to vasculopathy characterization. This survey study investigated EC-VWI adoption by American Society of Neuroradiology (ASNR) members and indications and barriers to implementation.

MATERIALS AND METHODS

The ASNR Vessel Wall Imaging Study Group survey on EC-VWI use, frequency, applications, MR imaging systems and field strength used, protocol development approaches, vendor engagement, reasons for not using EC-VWI, ordering provider interest, and impact on clinical care was distributed to the ASNR membership between April 2, 2019, to August 30, 2019.

RESULTS

There were 532 responses; 79 were excluded due to minimal, incomplete response and 42 due to redundant institutional responses, leaving 411 responses. Twenty-six percent indicated that their institution performed EC-VWI, with 66.3% performing it ≤1-2 times per month, most frequently on 3T MR imaging, with most using combined 3D and 2D protocols. Protocols most commonly included pre- and postcontrast T1-weighted imaging, TOF-MRA, and contrast-enhanced MRA. Inflammatory vasculopathy (63.3%), plaque vulnerability assessments (61.1%), intraplaque hemorrhage (61.1%), and dissection-detection/characterization (51.1%) were the most frequent applications. For those not performing EC-VWI, the reasons were a lack of ordering provider interest (63.9%), lack of radiologist time/interest (47.5%) or technical support (41.4%) for protocol development, and limited interpretation experience (44.9%) and knowledge of clinical applications (43.7%). Reasons given by 46.9% were that no providers approached radiology with interest in EC-VWI. If barriers were overcome, 51.1% of those not performing EC-VWI indicated they would perform it, and 40.6% were unsure; 48.6% did not think that EC-VWI had impacted patient management at their institution.

CONCLUSIONS

Only 26% of neuroradiology groups performed EC-VWI, most commonly due to limited clinician interest. Improved provider and radiologist education, protocols, processing techniques, technical support, and validation trials could increase adoption.

Multi-leveled insights into the response of the eelgrass Zostera marina L to Cu than Cd exposure

Seagrass beds are recognized as critical and among the most vulnerable habitats on the planet; seagrass colonize the coastal waters where heavy metal pollution is a serious problem. In this study, the toxic effects of copper and cadmium in the eelgrass Zostera marina L. were observed at the individual, subcellular, physiologically biochemical, and molecular levels. Both Cu and Cd stress significantly inhibited the growth and the maximal quantum yield of photosystem II (Fv/Fm); and high temperature increased the degree of heavy metal damage, while low temperatures inhibited damage. The half-effect concentration (EC₅₀) of eelgrass was 28.9 μM for Cu and 2246.8 μM for Cd, indicating Cu was much more toxic to eelgrass than Cd. The effect of Cu and Cd on photosynthesis was synergistic. After 14 days of enrichment, the concentration of Cu in leaves and roots of Z. marina was 48 and 37 times higher than that in leaf sheath, and 14 and 11 times higher than that in rhizome; and the order of Cd concentration in the organs was root > leaf > rhizome > sheath. Heavy metal uptake mainly occurred in the organelles, and Cd enrichment also occurred to a certain extent in the cytoplasm. Transcriptome results showed that a number of photosynthesis-related KEGG enrichment pathways and GO terms were significantly down-regulated under Cd stress, suggesting that the photosynthetic system of eelgrass was severely damaged at the transcriptome level, which was consistent with the significant inhibition of Fv/Fm and leaf yellowing. Under Cu stress, the genes related to glutathione metabolic pathway were significantly up-regulated, together with the increased autioxidant enzyme activity of GSH-PX. In addition, the results of recovery experiment indicated that the damage caused by short-term Cd and Cu stress under EC₅₀ was reversible. These results provide heavy metal toxic effects at multiple levels and information relating to the heavy metal resistance strategies evolved by Z. marina to absorb and isolate heavy metals, and highlight the phytoremediation potential of this species especially for Cd.

LettuceTrack: Detection and tracking of lettuce for robotic precision spray in agriculture

The precision spray of liquid fertilizer and pesticide to plants is an important task for agricultural robots in precision agriculture. By reducing the amount of chemicals being sprayed, it brings in a more economic and eco-friendly solution compared to conventional non-discriminated spray. The prerequisite of precision spray is to detect and track each plant. Conventional detection or segmentation methods detect all plants in the image captured under the robotic platform, without knowing the ID of the plant. To spray pesticides to each plant exactly once, tracking of every plant is needed in addition to detection. In this paper, we present LettuceTrack, a novel Multiple Object Tracking (MOT) method to simultaneously detect and track lettuces. When the ID of each plant is obtained from the tracking method, the robot knows whether a plant has been sprayed before therefore it will only spray the plant that has not been sprayed. The proposed method adopts YOLO-V5 for detection of the lettuces, and a novel plant feature extraction and data association algorithms are introduced to effectively track all plants. The proposed method can recover the ID of a plant even if the plant moves out of the field of view of camera before, for which existing Multiple Object Tracking (MOT) methods usually fail and assign a new plant ID. Experiments are conducted to show the effectiveness of the proposed method, and a comparison with four state-of-the-art Multiple Object Tracking (MOT) methods is shown to prove the superior performance of the proposed method in the lettuce tracking application and its limitations. Though the proposed method is tested with lettuce, it can be potentially applied to other vegetables such as broccoli or sugar beat.

The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming

Pork accounts for an important proportion of livestock products. For pig farming, a lot of manpower, material resources and time are required to monitor pig health and welfare. As the number of pigs in farming increases, the continued use of traditional monitoring methods may cause stress and harm to pigs and farmers and affect pig health and welfare as well as farming economic output. In addition, the application of artificial intelligence has become a core part of smart pig farming. The precision pig farming system uses sensors such as cameras and radio frequency identification to monitor biometric information such as pig sound and pig behavior in real-time and convert them into key indicators of pig health and welfare. By analyzing the key indicators, problems in pig health and welfare can be detected early, and timely intervention and treatment can be provided, which helps to improve the production and economic efficiency of pig farming. This paper studies more than 150 papers on precision pig farming and summarizes and evaluates the application of artificial intelligence technologies to pig detection, tracking, behavior recognition and sound recognition. Finally, we summarize and discuss the opportunities and challenges of precision pig farming.

Survey of the American Society of Neuroradiology Membership on the Use and Value of Intracranial Vessel Wall MRI

BACKGROUND AND PURPOSE

Intracranial vessel wall MR imaging is an emerging technique for intracranial vasculopathy assessment. Our aim was to investigate intracranial vessel wall MR imaging use by the American Society of Neuroradiology (ASNR) members at their home institutions, including indications and barriers to implementation.

MATERIALS AND METHODS

The ASNR Vessel Wall Imaging Study Group survey on vessel wall MR imaging use, frequency, applications, MR imaging systems and field strength used, protocol development approaches, vendor engagement, reasons for not using vessel wall MR imaging, ordering-provider interest, and impact on clinical care, was distributed to the ASNR membership between April 2 and August 30, 2019.

RESULTS

There were 532 responses; 79 were excluded due to nonresponse and 42 due to redundant institutional responses, leaving 411 responses. Fifty-two percent indicated that their institution performs vessel wall MR imaging, with 71.5% performed at least 1-2 times/month, most frequently on 3T MR imaging, and 87.7% using 3D sequences. Protocols most commonly included were T1-weighted pre- and postcontrast and TOF-MRA; 60.6% had limited contributions from vendors or were still in protocol development. Vasculopathy differentiation (94.4%), cryptogenic stroke (41.3%), aneurysm (38.0%), and atherosclerosis (37.6%) evaluation were the most common indications. For those not performing vessel wall MR imaging, interpretation (53.1%) or technical (46.4%) expertise, knowledge of applications (50.5%), or limitations of clinician (56.7%) or radiologist (49.0%) interest were the most common reasons. If technical/expertise obstacles were overcome, 56.4% of those not performing vessel wall MR imaging indicated that they would perform it. Ordering providers most frequently inquiring about vessel wall MR imaging were from stroke neurology (56.5%) and neurosurgery (25.1%), while 34.3% indicated that no providers had inquired.

CONCLUSIONS

More than 50% of neuroradiology groups use vessel wall MR imaging for intracranial vasculopathy characterization and differentiation, emphasizing the need for additional technical and educational support, especially as clinical vessel wall MR imaging implementation continues to grow.

Do adult eelgrass shoots rule seedling fate in a large seagrass meadow in a eutrophic bay in northern China?

We conducted field sampling over 19 months to investigate eelgrass population reproduction status and ecological interactions in a large seagrass meadow in a eutrophic bay in northern China. The results showed asexual growth played an important role in the maintenance of existing meadows, and sexual reproduction played a critical role in the colonization of new areas. We conclude that adult eelgrass shoots do rule the fate of seedlings in the large seagrass meadow. Additionally, nutrient resources (N and P) at this location were found to meet eelgrass growth demand. The N/P ratios of seawater and seagrass indicated N limitation relative to P in the eutrophic bay based on the seagrass Redfield ratio (25-30). Nutrient uptake by seagrass might be an important factor in reducing the probability of a red tide in the study area. The results of this study provide fundamental information for eelgrass restoration and conservation.

Characterization of Restenosis following Carotid Endarterectomy Using Contrast-Enhanced Vessel Wall MR Imaging

BACKGROUND AND PURPOSE

Restenosis is an important determinant of the long-term efficacy of carotid endarterectomy. Our aim was to assess the role of high-resolution vessel wall MR imaging for characterizing restenosis after carotid endarterectomy.

MATERIALS AND METHODS

Patients who underwent vessel wall MR imaging after carotid endarterectomy were included in this study. Restenotic lesions were classified as myointimal hyperplasia or recurrent atherosclerotic plaques based on MR imaging features of lesion compositions. Imaging characteristics of myointimal hyperplasia were compared with those of normal post-carotid endarterectomy and recurrent plaque groups. Recurrent plaques were matched with primary plaques by categories of stenosis, and differences in plaque features were compared between the 2 groups.

RESULTS

Twenty-two recurrent lesions from 18 patients (14 unilateral and 4 bilateral) were classified as myointimal hyperplasia or recurrent plaque. Myointimal hyperplasia showed no difference in enhancement compared with normal post-carotid endarterectomy vessels (5 unilateral) but showed stronger enhancement than recurrent plaques (80.10% [SD, 42.42%] versus 56.74% [SD, 46.54%], P = .042). A multivariate logistic regression model of plaque-feature detection in recurrent plaques compared with primary plaques adjusted for maximum wall thickness revealed that recurrent plaques were longer (OR, 4.27; 95% CI, 1.32-13.85; P = .015) and more likely to involve a flow divider and side walls (OR, 6.96; 95% CI, 1.37-35.28; P = .019). Recurrent plaques had a higher prevalence of intraplaque hemorrhage (61.5% versus 30.8%, P = .048) by a χ² test, but compositional differences were not significant in the multivariate model.

CONCLUSIONS

Vessel wall MR imaging can distinguish recurrent plaques from myointimal hyperplasia and reveal features that may differ between primary and recurrent plaques, highlighting its value for evaluating patients with carotid restenosis.

One-Shot Learning with Pseudo-Labeling for Cattle Video Segmentation in Smart Livestock Farming

Simple Summary

Deep learning-based segmentation methods rely on large-scale pixel-labeled datasets to achieve good performance. However, it is resource-costly to label animal images due to their irregular contours and changing postures. To keep a balance between segmentation accuracy and speed using limited label data, we propose a one-shot learning-based approach with pseudo-labeling to segment animals in videos, relying on only one labeled frame. Experiments were conducted on a challenging feedlot cattle video dataset acquired by the authors, and the results show that the proposed method outperformed state-of-the-art methods such as one-shot video object segmentation (OSVOS) and one-shot modulation network (OSMN). Our proposed one-shot learning with pseudo-labeling reduces the reliance on labeled data and could serve as an enabling component for smart farming-related applications.

Abstract

Computer vision-based technologies play a key role in precision livestock farming, and video-based analysis approaches have been advocated as useful tools for automatic animal monitoring, behavior analysis, and efficient welfare measurement management. Accurately and efficiently segmenting animals’ contours from their backgrounds is a prerequisite for vision-based technologies. Deep learning-based segmentation methods have shown good performance through training models on a large amount of pixel-labeled images. However, it is challenging and time-consuming to label animal images due to their irregular contours and changing postures. In order to reduce the reliance on the number of labeled images, one-shot learning with a pseudo-labeling approach is proposed using only one labeled image frame to segment animals in videos. The proposed approach is mainly comprised of an Xception-based Fully Convolutional Neural Network (Xception-FCN) module and a pseudo-labeling (PL) module. Xception-FCN utilizes depth-wise separable convolutions to learn different-level visual features and localize dense prediction based on the one single labeled frame. Then, PL leverages the segmentation results of the Xception-FCN model to fine-tune the model, leading to performance boosts in cattle video segmentation. Systematic experiments were conducted on a challenging feedlot cattle video dataset acquired by the authors, and the proposed approach achieved a mean intersection-over-union score of 88.7% and a contour accuracy of 80.8%, outperforming state-of-the-art methods (OSVOS and OSMN). Our proposed one-shot learning approach could serve as an enabling component for livestock farming-related segmentation and detection applications.

Oral Microbiota Changes Contribute to Autism Spectrum Disorder in Mice

The oral microbiota has been implicated in various neurologic conditions, including autism spectrum disorder (ASD), a category of neurodevelopmental disorders defined by core behavioral impairments. Recent data propose the etiopathogenetic role of intestinal microbiota in ASD. The aim of the present study was to elucidate whether the oral microbiota contributes to the pathogenesis of ASD. On the basis of microbial changes detected in the oral cavity of children with ASD, we transferred oral microbiota from donors with ASD and typical development (TD) into an antibiotic-mediated microbiota-depleted mouse model and found that the ASD microbiota is sufficient to induce ASD-like behaviors, such as impaired social behavior. Mice receiving oral microbiota from the ASD donor showed significantly different microbiota structures in their oral cavity and intestinal tract as compared with those receiving TD microbiota and those not receiving any bacterium. The prefrontal cortex of ASD microbiota recipient mice displayed an alternative transcriptional profile with significant upregulation of serotonin-related gene expression, neuroactive ligand-receptor interaction, and TGF-β signaling pathway relative to that in TD microbiota recipient mice. The expression of serotonin-related genes was significantly increased in ASD microbiota recipient mice and was associated with selective autistic behaviors and changes in abundance of specific oral microbiota, including species of Bacteroidetes [G-7], Porphyromonas, and Tannerella. Machine learning based on the causal inference method confirmed a contributing role of Porphyromonas sp. HMT 930 in ASD. Taken together, the oral microbiota of children with ASD can lead to ASD-like behaviors, differences in microbial community structures, and altered neurosignaling activities in recipient mice; this highlights the mouth-microbial-brain connections in the development of neuropathology and provides a novel strategy to fully understand the etiologic mechanism of ASD.

Reciprocal Field Transplant Experiment and Comparative Transcriptome Analysis Provide Insights Into Differences in Seed Germination Time of Two Populations From Different Geographic Regions of Zostera marina L

Seagrasses are the only submerged marine higher plants, which can colonize the sea through sexual (via seeds) reproduction. The transition between seed dormancy and germination is an important ecological trait and a key stage in the life cycle of higher plants. According to our observations, the seeds of Zostera marina L. (eelgrass) in Swan Lake (SL) and Qingdao Bay (QB) in northern China have the same maturation time (summer) but different germination time. To investigate this phenomenon, we further carried out reciprocal transplantation experiment and transcriptome analysis. Results revealed that differences in the seed germination time between the two sites do exist and are determined by internal molecular mechanisms as opposed to environmental factors. Furthermore, we conducted comparative transcriptome analysis of seeds at the mature and early germination stages in both locations. The results that the number of genes related to energy, hormone and cell changes was higher in SL than in QB, could account for that the dormancy depth of seeds in SL was deeper than that in QB; consequently, the seeds in SL needed to mobilize more related genes to break dormancy and start germination. The results could have important practical implications for seagrass meadow restoration via seeds and provide in-depth and comprehensive data for understanding the molecular mechanisms related to seagrass seed germination.

Deep Learning Based Automatic Grape Downy Mildew Detection

Grape downy mildew (GDM) disease is a common plant leaf disease, and it causes serious damage to grape production, reducing yield and fruit quality. Traditional manual disease detection relies on farm experts and is often time-consuming. Computer vision technologies and artificial intelligence could provide automatic disease detection for real-time controlling the spread of disease on the grapevine in precision viticulture. To achieve the best trade-off between GDM detection accuracy and speed under natural environments, a deep learning based approach named YOLOv5-CA is proposed in this study. Here coordinate attention (CA) mechanism is integrated into YOLOv5, which highlights the downy mildew disease-related visual features to enhance the detection performance. A challenging GDM dataset was acquired in a vineyard under a nature scene (consisting of different illuminations, shadows, and backgrounds) to test the proposed approach. Experimental results show that the proposed YOLOv5-CA achieved a detection precision of 85.59%, a recall of 83.70%, and a mAP@0.5 of 89.55%, which is superior to the popular methods, including Faster R-CNN, YOLOv3, and YOLOv5. Furthermore, our proposed approach with inference occurring at 58.82 frames per second, could be deployed for the real-time disease control requirement. In addition, the proposed YOLOv5-CA based approach could effectively capture leaf disease related visual features resulting in higher GDE detection accuracy. Overall, this study provides a favorable deep learning based approach for the rapid and accurate diagnosis of grape leaf diseases in the field of automatic disease detection.

Automated Individual Cattle Identification Using Video Data: A Unified Deep Learning Architecture Approach

Individual cattle identification is a prerequisite and foundation for precision livestock farming. Existing methods for cattle identification require radio frequency or visual ear tags, all of which are prone to loss or damage. Here, we propose and implement a new unified deep learning approach to cattle identification using video analysis. The proposed deep learning framework is composed of a Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) with a self-attention mechanism. More specifically, the Inception-V3 CNN was used to extract features from a cattle video dataset taken in a feedlot with rear-view. Extracted features were then fed to a BiLSTM layer to capture spatio-temporal information. Then, self-attention was employed to provide a different focus on the features captured by BiLSTM for the final step of cattle identification. We used a total of 363 rear-view videos from 50 cattle at three different times with an interval of 1 month between data collection periods. The proposed method achieved 93.3% identification accuracy using a 30-frame video length, which outperformed current state-of-the-art methods (Inception-V3, MLP, SimpleRNN, LSTM, and BiLSTM). Furthermore, two different attention schemes, namely, additive and multiplicative attention mechanisms were compared. Our results show that the additive attention mechanism achieved 93.3% accuracy and 91.0% recall, greater than multiplicative attention mechanism with 90.7% accuracy and 87.0% recall. Video length also impacted accuracy, with video sequence length up to 30-frames enhancing identification performance. Overall, our approach can capture key spatio-temporal features to improve cattle identification accuracy, enabling automated cattle identification for precision livestock farming.

The super typhoon Lekima (2019) resulted in massive losses in large seagrass (Zostera japonica) meadows, soil organic carbon and nitrogen pools in the intertidal Yellow River Delta, China

Seagrass meadows are key ecosystems, and they are among the most threatened habitats on the planet. Increased numbers of extreme climate events, such as hurricanes and marine heatwaves have caused severe damage to global seagrass meadows. The largest Zostera japonica meadows in China are located in the Yellow River Delta. It had a distribution area of 1031.8 ha prior to August 2019 when the Yellow River Delta was severely impacted by the passage of typhoon Lekima. In this study, we compared field data collected before and after the typhoon to determine its impact on seagrass beds in the Yellow River Delta. The super typhoon caused dramatic changes in Z. japonica in the Yellow River Delta, resulting in a greater than 100-fold decrease in distribution area, a greater than 35% loss of soil organic carbon, and a greater than 65% loss of soil total nitrogen in the top 35 cm sediments. Owing to the lack of seeds and overwintering shoots, as well as the small remaining distribution area, recovery was impossible, even though environmental factors were still suitable for species growth. Thus, restoration efforts are required for seagrass meadow recovery. Additionally, the long-term monitoring of this meadow will provide new information on the ecosystem's status and will be useful for future protection.

Intelligent Perception-Based Cattle Lameness Detection and Behaviour Recognition: A Review

Simple Summary

Cattle lameness detection as well as behaviour recognition are the two main objectives in the applications of precision livestock farming (PLF). Over the last five years, the development of smart sensors, big data, and artificial intelligence has offered more automatic tools. In this review, we discuss over 100 papers that used automated techniques to detect cattle lameness and to recognise animal behaviours. To assist researchers and policy-makers in promoting various livestock technologies for monitoring cattle welfare and productivity, we conducted a comprehensive investigation of intelligent perception for cattle lameness detection and behaviour analysis in the PLF domain. Based on the literature review, we anticipate that PLF will develop in an objective, autonomous, and real-time direction. Additionally, we suggest that further research should be dedicated to improving the data quality, modeling accuracy, and commercial availability.

Abstract

The growing world population has increased the demand for animal-sourced protein. However, animal farming productivity is faced with challenges from traditional farming practices, socioeconomic status, and climate change. In recent years, smart sensors, big data, and deep learning have been applied to animal welfare measurement and livestock farming applications, including behaviour recognition and health monitoring. In order to facilitate research in this area, this review summarises and analyses some main techniques used in smart livestock farming, focusing on those related to cattle lameness detection and behaviour recognition. In this study, more than 100 relevant papers on cattle lameness detection and behaviour recognition have been evaluated and discussed. Based on a review and a comparison of recent technologies and methods, we anticipate that intelligent perception for cattle behaviour and welfare monitoring will develop towards standardisation, a larger scale, and intelligence, combined with Internet of things (IoT) and deep learning technologies. In addition, the key challenges and opportunities of future research are also highlighted and discussed.

[The impact of digoxin on the long-term outcomes in patients with coronary artery disease and atrial fibrillation]

Objective: To investigate the long-term safety of digoxin in patients with coronary artery disease (CAD) and atrial fibrillation (AF). Methods: This was a prospective study, in which 25 512 AF patients were enrolled from China Atrial Fibrillation Registry Study. After exclusion of patients receiving ablation therapy at the enrollment, 1 810 CAD patients [age: (71.5±9.3)years] with AF were included. The subjects were grouped into the digoxin group and non-digoxin group, and were followed up for a period of 80 months. Long-term outcomes were compared between the groups and an adjusted Cox regression analysis was applied to evaluate the risk of digoxin on the long-term outcomes. The primary endpoint was all-cause mortality. Results: The patients were followed up for a median period of 3.05 years. After multivariable adjustment, the Cox regression analysis showed that digoxin significantly increased the risk of all-cause mortality (HR=1.28, 95%CI 1.01-1.61, P=0.038), cardiovascular mortality (HR=1.48,95%CI 1.10-2.00,P=0.010), cardiovascular hospitalization (HR=1.67,95%CI 1.35-2.07,P=0.008) and the composite endpoints (HR=2.02,95%CI 1.71-2.38,P<0.001). In the subgroup of patients with heart failure (HF), digoxin was not associated with the risk of all-cause mortality, but was still associated with the increased risk of cardiovascular mortality (HR=1.44,95%CI 1.05-1.98,P=0.025), cardiovascular hospitalization (HR=1.44,95%CI 1.09-1.90,P=0.010) and the composite endpoints (HR=1.37, 95%CI 1.01-1.70, P=0.004). However, in the subgroup of patients without HF, digoxin was only associated with all-cause mortality (HR=2.56,95%CI 1.44-4.54,P=0.001). Conclusion: Digoxin significantly increased the risk of all-cause mortality in CAD patients with AF, especially in patients without HF.

P–389 The relationship between serum hormone profiles and missed abortion in humans

Study question

Are circulating profiles of metabolic-related hormones also associated with the missed abortion (MA) in humans?

Summary answer

Serum levels of fatty acid-binding protein–4 (FABP4) and fibroblast growth factor 21 (FGF21) are positively associated with MA.

What is known already

A cluster of endocrine hormones, including FABP4, FGF21, adiponectin, lipocalin–2 (LCN2), exhibit pleiotropic effects on regulating systematic metabolism. Serum levels of them are associated with gestational obesity and diabetes and affect pregnancy outcomes, however, the relationship between their circulating profiles and MA is under-investigated.

Study design, size, duration

78 patients with MA and 86 healthy pregnant subjects matching on maternal age and body mass index (BMI) were nested from a prospective cohort in the Chinese population.

Participants/materials, setting, methods

Fasting serum samples from all participants were collected to test their serum levels of FGF21, FABP4, adiponectin, and LCN2 by enzyme-linked immunosorbent assay method (ELISA).

Main results and the role of chance

There were no significant differences in circulating profiles of adiponectin and LCN2 between MA patients and healthy pregnant subjects. By contrast, circulating levels of FGF21 and FABP4 were significantly and independently elevated in patients with MA relative to control cases even after adjusting confounding factors (for FGF21: MA: 28.96 ± 2.17 ng/ml; HP: 19.18 ± 1.12 ng/ml, P &lt; 0.001, for FABP4: MA: 152.50 ± 9.31 pg/ml; HP: 90.86 ± 4.14 pg/ml, P &lt; 0.001). Linear regression analysis showed, FGF21 raised every 10 pg/ml contributed to a 24% (95% CI: 15% - 34%) increase in the risk of MA, whereas the OR of FABP4 for the risk of MA was 1.052 (95% CI: 1.022 –1.088). Furthermore, using serum FGF21 level or FABP4 levels discriminated MA from healthy controls with an area under the operating characteristic’s curve (AUROC) of 0.81 (95% CI 0.76–0.92) and 0.70 (95% CI 0.62 - 0.78), respectively.

Limitations, reasons for caution

The study is limited by the sample size. In addition, our results were based-on Chinese population, whether it could be observed in other ethics group remain to be investigated. Meanwhile, the cause-effect relationship between increased serum FGF21 level and MA remains to be explored.

Wider implications of the findings: Our data would suggest that serum levels of FGF21 and FABP4 are associated with MA. Moreover, circulating FGF21 levels may serve as a potential diagnostic biomarker for the recognition of M.

Trial registration number

IRB Ref. No.: KY201913

Diversity, distribution and conservation of seagrass in coastal waters of the Liaodong Peninsula, North Yellow Sea, northern China: Implications for seagrass conservation

Seagrass beds are highly productive coastal ecosystems that are widely distributed along temperate and tropical coastlines globally. Although seagrass distribution and diversity have been widely reported on a global scale, there have been few reports on seagrass distribution and diversity in northern China, especially for coastal waters of the Liaodong Peninsula in the North Yellow Sea. In the present study, we investigated the distribution and diversity of seagrass in coastal waters of the Liaodong Peninsula in the North Yellow Sea, northern China. Field surveys of seagrass wrack were conducted along shorelines, to identify whether seagrass beds occurred in nearby waters, and sonar methods were then used to collect data relating to seagrass bed extent. Also, we analyzed the major threats facing seagrass beds. The results of the study revealed that four species (Zostera marina L., Z. japonica Aschers. & Graebn., Z. caespitosa M., and Phyllospadix iwatensis M.) were found in study area, covering a total area of 1253.47 ha. Seagrass bed area significantly decreased with increasing water depth, and most seagrass was recorded at depths of 2-5 m. Due to the steep slope of the seabed, seagrass beds exhibited a zonal distribution in most of the study areas. In addition, the amount of seagrass wrack along shorelines could be used to infer the size and distance of seagrass beds. Human activities, such as clam harvesting, land reclamation, coastal aquaculture pose a threat to the seagrass beds. This study provides new information to fill knowledge gaps regarding seagrass distribution in northern China and it provides a baseline for further monitoring of these seagrass beds.

Can the Non-native Salt Marsh Halophyte Spartina alterniflora Threaten Native Seagrass (Zostera japonica) Habitats? A Case Study in the Yellow River Delta, China

Seagrass meadows are critical ecosystems, and they are among the most threatened habitats on the planet. As an anthropogenic biotic invader, Spartina alterniflora Loisel. competes with native plants, threatens native ecosystems and coastal aquaculture, and may cause local biodiversity to decline. The distribution area of the exotic species S. alterniflora in the Yellow River Delta had been expanding to ca.4,000 ha from 1990 to 2018. In this study, we reported, for the first time, the competitive effects of the exotic plant (S. alterniflora) on seagrass (Zostera japonica Asch. & Graebn.) by field investigation and a transplant experiment in the Yellow River Delta. Within the first 3 months of the field experiment, S. alterniflora had pushed forward 14 m into the Z. japonica distribution region. In the study region, the area of S. alterniflora in 2019 increased by 516 times compared with its initial area in 2015. Inhibition of Z. japonica growth increased with the invasion of S. alterniflora. Z. japonica had been degrading significantly under the pressure of S. alterniflora invasion. S. alterniflora propagates sexually via seeds for long distance invasion and asexually by tillers and rhizomes for short distance invasion. Our results describe the invasion pattern of S. alterniflora and can be used to develop strategies for prevention and control of S. alterniflora invasion.

New insights into physiological effects of anoxia under darkness on the iconic seagrass Zostera marina based on a combined analysis of transcriptomics and metabolomics

Coastal hypoxia/anoxia is a major emerging threat to global coastal ecosystems. Macroalgae blooms of tens of kilometers are often observed in open waters. These blooms not only cause a lack of oxygen, but also benthic light limitation. We explored the physiological responses of Zostera marina L. to anoxia under darkness. After exposing Z. marina to anoxia under darkness for 72 h, we measured the elongation of leaves and the decrease in maximal quantum yield of photosystem II (Fv/Fm), and investigated the transcriptomic and metabolomic responses to anoxic stress based on RNA-sequencing and liquid chromatography-mass spectrometry (LC-MS) technology. The results showed that anoxic stress significantly reduced the leaf Fv/Fm, and had a significant negative effect on the photosynthesis and growth of Z. marina. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of up-regulated differentially expressed genes (DEGs) showed that glycolysis was the most significant enrichment pathway (p < 0.001), and most of the important products in glycolysis were significantly up-regulated. This indicated that the glycolysis process of anaerobic respiration is promoted under anoxia. The metabolite results also showed that glyceraldehyde 3-phosphate in the glycolysis pathway was significantly up-regulated. Moreover, three genes encoding sucrose synthase (gene-ZOSMA_310G00150, gene-ZOSMA_81G00980, and gene-ZOSMA_8G00730) and one gene encoding alpha-amylase (gene-ZOSMA_95G00270) were significantly up-regulated, providing the sugar basis for the subsequent increase in glycolysis. Furthermore, gene-encoding oxoglutarate dehydrogenase, the rate-limiting step of the tricarboxylic acid (TCA) cycle, was significantly down-regulated, indicating that this cycle was inhibited under anoxia. Metabolomic results showed that L-tryptophan, L-phenylalanine, and DL-leucine were significantly up-regulated. Only significantly decreased glutamate and non-significantly decreased glutamine, substances consumed in alanine and γ-aminobutyric acid (GABA) shunt mechanisms, were detected in the leaves, while GABA and alanine were not detected. The results of this study show that anoxic stress induces a programmed transcriptomic and metabolomic response in seagrass, most likely reflecting a complex strategy of acclimation and adaptation in seagrass to resist anoxic stress.

Mutations in chronic myelomonocytic leukemia and their prognostic relevance

Chronic myelomonocytic leukemia (CMML) is a hematologic malignancy that overlaps with myeloproliferative neoplasms (MPN) and myelodysplastic syndromes (MDS) and tends to transform into acute myeloid leukemia (AML). Among cases of CMML, > 90% have gene mutations, primarily involving TET2 (~ 60%), ASXL1 (~ 40%), SRSF2 (~ 50%), and the RAS pathways (~ 30%). These gene mutations are associated with both the clinical phenotypes and the prognosis of CMML, special CMML variants and pre-phases of CMML. Cytogenetic abnormalities and the size of genome are also associated with prognosis. Meanwhile, cases with ASXL1, DNMT3A, NRAS, SETBP1, CBL and RUNX1 mutations may have inferior prognoses, but only ASXL1 mutations were confirmed to be independent predictors of the patient outcome and were included in three prognostic models. Novel treatment targets related to the various gene mutations are emerging. Therefore, this review provides new insights to explore the correlations among gene mutations, clinical phenotypes, prognosis, and novel drugs in CMML.

Improving the productivity of Candida glycerinogenes in the fermentation of ethanol from non-detoxified sugarcane bagasse hydrolysate by a hexose transporter mutant

AIMS

In this study, we attempted to increase the productivity of Candida glycerinogenes yeast for ethanol production from non-detoxified sugarcane bagasse hydrolysates (NDSBH) by identifying the hexose transporter in this yeast that makes a high contribution to glucose consumption, and by adding additional copies of this transporter and enhancing its membrane localisation stability (MLS).

METHODS AND RESULTS

Based on the knockout and overexpression of key hexose transporter genes and the characterisation of their promoter properties, we found that Cghxt4 and Cghxt6 play major roles in the early and late stages of fermentation, respectively, with Cghxt4 contributing most to glucose consumption. Next, subcellular localisation analysis revealed that a common mutation of two ubiquitination sites (K9 and K538) in Cghxt4 improved its MLS. Finally, we overexpressed this Cghxt4 mutant (Cghxt4.2A) using a strong promoter, P_CgGAP , which resulted in a significant increase in the ethanol productivity of C. glycerinogenes in the NDSBH medium. Specifically, the recombinant strain showed 18 and 25% higher ethanol productivity than the control in two kinds of YP-NDSBH medium (YP-NDSBH1_G160 and YP-NDSBH2_G160 ), respectively.

CONCLUSIONS

The hexose transporter mutant Cghxt4.2A (Cghxt4^K9A,K538A ) with multiple copies and high MLS was able to significantly increase the ethanol productivity of C. glycerinogenes in NDSBH.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our results provide a promising strategy for constructing efficient strains for ethanol production.

Incidence and associated predictors of adverse pregnancy outcomes of maternal syphilis in China, 2016-19: a Cox regression analysis

OBJECTIVE

This study aimed to investigate the incidence and associated predictors of adverse pregnancy outcomes (APOs) among pregnant women infected with syphilis.

DESIGN

Cox regression analysis.

SETTING

China.

POPULATION OR SAMPLE

Pregnant women who were tested for and diagnosed with syphilis during the index pregnancy and delivered at a gestational age ≥28 weeks between 2016 and 2019.

METHODS

Data were extracted from China's Information System of Prevention of Mother-to-Child Transmission of Syphilis Management. Descriptive analysis provided profiles and pregnancy outcomes of maternal syphilis, as well as the incidence of APOs. Log-rank tests and Cox proportional hazard models were used to investigate factors influencing APOs in infected mothers with singleton births.

MAIN OUTCOME MEASURES

The incidence of APOs and the hazard ratios of associated predictors using Cox proportional hazard model.

RESULTS

Syphilis treatment data were available from 83.86% of diagnosed women. Including deliveries from the total study population, 13.33% experienced APOs. Cox regression indicated that APOs were more likely in women tested and diagnosed in the late trimester, at delivery or postpartum. Women who accepted non-standardised treatment and who received standardised treatment had less risk of APOs.

CONCLUSIONS

China has made huge progress over the last decades in the prevention of mother-to-child transmission of syphilis, but the incidence of APOs among pregnant women infected with syphilis remains high. It is essential to further strengthen access to early detection and standardised treatment of infected women to reduce the risk of APOs.

TWEETABLE ABSTRACT

Access to early detection and standardised treatment reduces the risk of APOs due to maternal syphilis.

Sonar and in situ surveys of eelgrass distribution, reproductive effort, and sexual recruitment contribution in a eutrophic bay with intensive human activities: Implication for seagrass conservation

Seagrass beds are recognized as pivotal and among the most vulnerable coastal marine ecosystems globally. The eelgrass Zostera marina L. is the most widely distributed seagrass species and dominates the temperate northern hemisphere. However, an alarming decline in seagrass has been occurring worldwide due to multiple stressors. Seagrass meadow degradation is particularly serious in the Bohai Sea, in temperate China; however, large areas (> 500 ha) of seagrass meadows and population recruitment have rarely been reported in this area. In the present study, we report on a large eelgrass bed in a eutrophic bay of the Bohai Sea. Sonar and field survey methods were used to investigate the distribution of seagrass and its population recruitment. We also analyzed the major threats to this large seagrass bed. Results showed that a large Z. marina bed with an area of 694.36 ha occurred in this area of the Bohai Sea, with a peripheral area of ~25 km². Seagrass canopy height and plant coverage had a significant correlation with water depth. Asexual reproduction principally occurred in autumn and played a dominant role in population recruitment in vegetated areas, where no seedlings successfully colonized. In contrast, a considerable number of seedlings survived in the seagrass meadow gaps, and thus played a critical role in the recruitment in these areas. The maximum reproductive shoot densities were about 100 and 70 shoots m^-2 at sampling site (S)-1 and S-2 in 2018, respectively, which was about two times more than in 2019 (50 and 20 reproductive shoots m^-2 at S-1 and S-2, respectively). The potential seed output per unit area in 2019 was about 1020 seeds m^-2 at S-1 and 830 seeds m^-2 at S-2, and the seed output in the study area was at a low level compared with global values. Overall, high spring and summer water temperature appeared to induce sexual reproduction of Z. marina in the study area, including reproductive effort, reproductive investment, and seedling development. Furthermore, eelgrass height, aboveground biomass, and density were significantly related to water temperature. Among the potential threatening factors to seagrass in this area, the activities of clam harvesting were intense with daily clam catches >2000 kg, leading to patchy seagrass meadows, especially in the fringe areas. The seagrass bed was also threatened by marine pollution (nutrient loading) and land reclamation. Therefore, the protection and restoration of this seagrass bed are strongly recommended. Our study will provide fundamental information for the conservation and management strategies of large eelgrass beds in the Bohai Sea.

[Establishment and primary clinical application of metabolic evaluation database of urolithiasis]

Objective: To establish the metabolic evaluation database of urolithiasis, perform metabolic evaluation, and provide instructions for treatment and prevention of urolithiasis. Methods: This metabolic evaluation database was developed by JAVA and was established by Oracle11g database and Browser/Server framework. We extracted the clinical data of all patients who had complete information, and analyzed their risk factors of stone formation, stone-related medical history, blood and urine tests results and 24-hour urine analysis. Results: A total of 360 patients diagnosed as urolithiasis were included in this research. Male to female ratio was 1.9∶1, and the urolithiasis was first diagnosed at (35.5±13.5) years old. Family history was positive in 39.7% of patients. Metabolic syndrome occurred in 35.0% of patients. Overweight or obesity occurred in 73.2% and 50.0% of male patients, respectively. Abdominal obesity in 62.3% and 56.1% of male and female patients, respectively. Among all patients, 67.5% had high urine sodium, 53.6% had hypercalciuria, 41.1% had hypocitraturia, 29.7% had hyperuricosuria, 22.5% had hypomagnesuria, 15.8% had hyperoxaluria, 11.7% had hyperphosphoraturia, and 36.4% had low urinary volume. Conclusions: The prevalence of overweight or obesity, abdominal obesity, hypertension, diabetes, and metabolic syndrome in stone patients were significantly higher than those in general population. The number of 24-hour urinary abnormalities was positively associated with body mass index. The interventions on high urinary sodium, low urinary volume, obesity and metabolic syndrome were important to the treatment of urolithiasis. This database would facilitate the metabolic evaluation, provide evidence for the treatment and prevention of urolithiasis, and lay foundation for finding important controllable risk factors of urinary stone.